UNIVERSIDADE DE LISBOA
FACULDADE DE CIÊNCIAS
DEPARTAMENTO DE BIOLOGIA ANIMAL
Contribution to the development of biotic
integrity assessment tools for Portuguese
estuaries based on benthic communities
Paula Maria Chainho de Oliveira
Doutoramento em Biologia
Especialidade de Ecologia Aplicada
2008
UNIVERSIDADE DE LISBOA
FACULDADE DE CIÊNCIAS
DEPARTAMENTO DE BIOLOGIA ANIMAL
Contribution to the development of biotic
integrity assessment tools for Portuguese
estuaries based on benthic communities
Paula Maria Chainho de Oliveira
Tese orientada por:
Professora Catedrática Maria José Costa
Eminent Scholar Daniel M. Dauer
Doutoramento em Biologia
Especialidade de Ecologia Aplicada
2008
To my daughter
Para a minha filha
Acknowledgments
ACKNOWLEDGMENTS/ AGRADECIMENTOS
This thesis represents a very important period of my life and I could not have
accomplished this challenge without the support of those who funded the work, advised me,
helped me with many tasks and provided me encouragement and emotional reassurance to
continue in difficult moments. Therefore, I would like to thank all those who contributed at
different stages, especially:
A realização desta tese representou um período muito importante da minha vida e
não teria sido possível concretizar este desafio sem o apoio daqueles que financiaram a
investigação, os que me orientaram, os que ajudaram em algumas tarefas e todos os que me
apoiaram nos momentos mais difíceis. Assim, quero agradecer a todos os que contribuíram
nas diferentes fases do processo, em especial:
À Professora Maria José Costa, por ter aceite a orientação desta tese, por ter
acreditado que seria capaz de concretizar este desafio até ao fim e por ter sido pragmática
em todos os momentos em que tal foi necessário;
Professor Daniel Dauer for being my “scientific father” along these six years. Our
enthusiastic discussions were fundamental for my scientific growth and your advice was
always helpful in all stages of this thesis. I will always be grateful for your warmth welcome
in the U.S.A., the full integration in the Lab family and the friendship and all the support that
you gave me.
Instituto de Oceanografia and the Benthic Ecology Laboratory for having hosted this
study and the projects that gave support to it/Ao Instituto de Oceanografia e ao Benthic
Ecology Laboratory, por terem acolhido este doutoramento e os projectos no âmbito dos quais
foi desenvolvido;
Ao Lino Costa, por estar sempre presente quando foi preciso, tanto no
aconselhamento científico como nas dificuldades e necessidades do dia-a-dia, e no
entusiasmo face a novos desafios.
À Luísa Chaves, com quem partilhei lutas comuns ao longo dos nossos doutoramentos.
A tua presença preserverante nas campanhas de amostragem, projectos, relatórios
intermináveis, artigos, dificuldades e alegrias foi sempre um alento para continuar. A tua
amizade para além das paredes do IO é o mais importante, que fica para além da tese.
i
Mike Lane, whose friendship was one of the best “consequences” of this Ph.D. Your
support continued much beyond the time that I spent in the U.S.A. I would like to thank you
for all your help with the statistical analysis, revisions, english lessons, scientific discussions,
political discussions, movie sessions, holyday trips and little nothings that we shared every
day.
À Gilda Silva, pelas experiências partilhadas na identificação dos “bichos”, pela ajuda
na formatação e revisão da tese, por estar sempre pronta a ajudar nas tarefas do dia-dia,
mesmo nos dias de mau humor, por saber sempre onde estão as coisas e por partilhar uma
memória comum de quase 20 anos.
Ao Nuno Prista, pelos desafios diários ao conhecimento que me motivaram a não ficar
apenas pelas coisas mais fáceis e já dominadas, pela ajuda no trabalho de campo, e por
partilhar ideologias e frustrações.
À Ana Luisa, pelas viagens intermináveis ao Mondego, pela ajuda com a formatação e
revisão da tese e por todo o apoio nas pequenas-grandes tarefas do quotidiano no laboratório.
À Carmen, Elsa, Pedro Raposo, Isabel Domingos, Carlos Assis, Sílvia, João Paulo,
Bernardo, Jorge, Zé Jacinto, Zé Loff, Carolina, Obadias, Alberto, André, Sérgio e restantes
colegas do laboratório e da sala dos doutorandos, pelo companheirismo de todos os dias,
pelas ajudas em tarefas diversas e por me terem animado nas fases mais difíceis.
Heidi, Bud, Sharon, Cory, Ryan, Colin e Charles, for having included me so promptly in
the Benthic Lab. family and for all the support you gave me during my visits to Norfolk.
Ging, Antone and my “niece” Ema, for having provided the feeling of being home
during all those months spent in a foreign country. I also thank all the philipine family and
latin family, who always welcomed me as a member of the “tribe”.
Ao Sr. Manuel Pata e António pelo apoio nas saídas de campo do Mondego e pelas
histórias da pesca do bacalhau. Ao Francisco Ferreira e tripulação do Mor, pelo entusiasmo
com que sempre se empenharam nas nossas saídas do Tejo. Aos Srs. Ilídio Viola, Vitalino Cruz
e António pelo apoio nas calmas subidas e descidas do Mira, que se tornou o meu local de
estudo favorito por essa “partilha alentejana”.
À Rita Vasconcelos, Manuel Cabral, Susana França, Catarina Vinagre, Sérgio Rodrigues
e Tadeu Pereira, pela ajuda no trabalho de campo e pelos momentos bem passados a bordo e
nas noites de laboratório.
À Carla Azeda e Carla Barrinha por terem sido umas verdadeiras “máquinas de
triagem”, durante longos dias de laboratório. Sem a vossa colaboração não teria sido possível
ter tantos dados.
ii
Acknowledgments
To Professor Jean-Claude Dauvin for having received me at the Wimereux Marine
Station and for all the help with invertebrate taxonomy.
Ao João Castro, por me ter acolhido na estação biológica de Sines e ter partilhado
algumas dicas muito úteis para a identificação dos invertebrados.
Ao Professor Eugénio Sequeira, por ser o modelo daquilo que eu gostava de conservar
quando for mais velha: motivação, ideologia e muita energia. As suas histórias da vida foram
uma inspiração semanal para acreditar que vale a pena insistir na ciência.
Aos companheiros de direcção e aos assessores da LPN, por me terem poupado nas
fases mais difíceis da tese e pela preocupação permanente em que a LPN não adiasse ainda
mais a finalização desta tese difícil de sair.
Ao Rodrigo Leão, por ter composto as melodias que intensificaram os momentos mais
difíceis, mas também os de maior satisfação.
Aos meus amigos Paula Pires, Ana Grave, Luís Soares, Barbosa e Fátima, que
suportaram as minhas ausências prolongadas e se mantiveram sempre ali, no lugar onde se
encontram os amigos.
À Paula, por me ter sempre mostrado que é possível fazermos mesmo aquilo que
pensamos, à partida, não estar ao nosso alcance. Ao longo destes anos, fizeste-me sempre
acreditar que valia a pena tentar coisas novas. Tens sido também tu que me mostras a dura
realidade, tal como ela é e me impeles a enfrentar as dificuldades sem meter a cabeça na
areia.
Aos meus avós, que tão bem souberam manter a “sabedoria dos velhos” e uma família
unida. Esta tese também é um tributo aos vossos sacrifícios ao longo da vida, que nos
permitiram fazer escolhas que nunca estiveram ao vosso alcance.
À minha família interminável, em especial aos primos que mantém o clã sempre
unido. Um agradecimento especial ao Julieu, por estar sempre lá e acreditar que as escolhas
malucas da prima fazem sentido neste mundo voraz.
À minha irmã, Samuel e Tiago, que são uma das partes mais importantes daquele
“ninho familiar”, que me faz sempre querer voltar quando estou longe.
Aos meus pais que, apesar de nem sempre acreditarem que as minhas escolham são as
certas, continuam a apoiar-me incondicionalmente e a permitir a procura dos sonhos. Sei que
estarão sempre aí.
Às minhas gatas Milady, Lua e Maria, companheiras de longas horas de computador,
que tanto me mimaram no trabalho solitário de pensar e redigir a tese.
iii
Ao Luis, companheiro de todas as lutas, cuja paciência interminável me permitiu
arrastar a finalização desta tese, e realizar outros sonhos paralelos. Este também é um
projecto teu, pois sempre acreditaste que valia a pena e apoiaste-me em todos os momentos
mais difíceis. O amor não se lê só nas palavras, às vezes mora nos silêncios mas acima de tudo
nas acções.
À minha filha Filipa, que representou a motivação e inspiração decisivas na recta final
da tese. Espero que um dia venhas a ter a possibilidade de realizar desafios tão ou mais
aliciantes que este.
A presente tese foi financiada pela Fundação para a Ciência e a Tecnologia e ao ESF no âmbito
do III Quadro Comunitário de Apoio, através da atribuição de uma bolsa de doutoramento
(SFRH/BD/5144/2001) e do projecto EFICAS (POCI/MAR/61324/2004). O trabalho realizado beneficiou
ainda do apoio financeiro do Instituto de Ambiente, através do projecto QUERE, e do apoio logístico
facultado pelo Instituto Hidrográfico e Instituto da Água, através do projecto EMINAG.
iv
Resumo
RESUMO
A importância da avaliação e monitorização do estado ecológico dos ecossistemas
aquáticos está actualmente vertida num conjunto de regulamentos ambientais, cuja
publicação em diversos países do Mundo teve lugar, de forma mais acentuada, ao longo das
últimas décadas. Na Europa, a aprovação da Directiva-Quadro da Água (DQA) em 2000, que
estabelece um quadro de acção comunitária no domínio da política da água, representou um
marco importante para o estabelecimento de novos critérios de qualidade da água, ao
introduzir o conceito de estado ecológico. A DQA tem como principal objectivo alcançar o
bom estado ecológico de todas as massas de água até 2015 e requer o desenvolvimento de um
conjunto de indicadores específicos para cada tipo de massas de água, processo que está a
ser levado a cabo pelos diversos Estados Membros. Apesar de alguns países europeus já
incluírem a monitorização de elementos biológicos nos seus programas nacionais, através de
indicadores desenvolvidos especificamente para esse fim, outros iniciaram esse processo
apenas com a implementação da DQA e carecem de instrumentos específicos adaptados às
características dos seus ecossistemas. No caso português, apesar de terem sido conduzidos
alguns estudos de avaliação de impacte ambiental e monitorização com base em indicadores
biológicos, os mesmos restringiam-se a projectos específicos e não tinham o carácter
sistemático requerido pela DQA. Com o início do processo de implementação da DQA em
Portugal, e visto não existirem índices específicos para os sistemas de águas de transição
nacionais, tem vindo a ser testado um conjunto de indicadores desenvolvidos para outros
sistemas estuarinos. No entanto, algumas especificidades dos estuários portugueses são
passíveis de limitar essa aplicação, nomeadamente o facto de Portugal se encontrar numa
zona de transição do ponto de vista biogeográfico e por isso apresentar diferentes
composições faunísticas ao longo do gradiente latitudinal. Para além disso, a maioria dos
estuários portugueses apresenta caudais de descarga irregulares ao longo do ano, o que
provoca alterações frequentes das condições ambientais e consequentemente condiciona a
ocorrência de espécies com diferentes níveis de tolerância ao stress ambiental. Este tipo de
estuários, que podem ser enquadrados na designação de estuários poiquiloalinos (que
apresentam variações das condições de salinidade), tem sido muito pouco estudado,
comparativamente aos estuários homioalinos (que apresentam condições de salinidade
estáveis). Os estuários portugueses são ainda afectados pela ocorrência de fenómenos
climáticos extremos, como as cheias e as secas, cuja frequência tende a aumentar, como
consequência das alterações climáticas. Para além disso, estão sujeitos a pressões
antropogénicas significativas, pelo que nenhum dos estuários poderá ser utilizado para
estabelecer condições de referência.
v
Tendo em conta este cenário, o presente estudo teve como principal objectivo testar
se as características dos estuários portugueses condicionam a utilização de algumas
ferramentas comummente aplicadas na avaliação do estado ecológico deste tipo de sistemas,
com base em comunidades de macroinvertebrados bentónicos. Os sistemas estuarinos
estudados foram o Mondego, o Tejo e o Mira, que foram incluídos no tipo A2 no âmbito do
exercício de tipologia da DQA, mas que apesar disso apresentam características
hidromorfológicas bastante distintas.
A presente tese encontra-se organizada em seis capítulos, quatro dos quais consistem
em artigos científicos publicados e aceites em revistas científicas indexadas, precedidos de
uma introdução geral e finalizando com algumas considerações finais.
O Capítulo 1 consiste numa introdução geral, que sistematiza as principais
características dos estuários e os constrangimentos que as condições ambientais estuarinas e
as pressões antropogénicas colocam às comunidades de macroinvertebrados bentónicos. Neste
capítulo é ainda efectuado um enquadramento geral sobre as políticas e regulamentos que
requerem a utilização de instrumentos de avaliação ambiental com base em comunidades
bentónicas, com particular relevância para a DQA. São indicadas algumas das características
das comunidades de macroinvertebrados bentónicos que os tornam bons indicadores de
qualidade ambiental, assim como uma revisão sumária das principais métricas e índices
utilizados. Este capítulo inclui ainda uma síntese actualizada do estado do conhecimento
relativo às comunidades de invertebrados dos estuários portugueses, nomeadamente no que
diz respeito à sua utilização como indicadores de qualidade e, em particular, nos aspectos
relevantes para a aplicação das metodologias propostas pela DQA. É identificado o estado
actual do processo de implementação em Portugal e as lacunas que levaram à realização do
presente estudo. Finalmente, são apresentados os objectivos da tese e as principais questões
às quais se pretendeu responder.
No Capítulo 2 são identificadas as relações entre os gradientes ambientais estuarinos
e os padrões de distribuição temporal e espacial das comunidades de macroinvertebrados
bentónicos do estuário do Mondego. Esta análise tem como base um conjunto de dados
recolhidos ao longo de todo o gradiente salino do estuário e com uma frequência sazonal, de
forma a cobrir as variações correspondentes ao ciclo hidrológico. Por terem sido realizadas
amostragens após um período de cheia, este estudo permite avaliar o impacto deste tipo de
evento extremo sobre as condições ambientais do estuário e as consequências ao nível da
estrutura das comunidades bentónicas.
No Capítulo 3 é testada a suficiência taxonómica no exercício da tipologia
(identificação de tipos de massas de água), tendo como base as comunidades de
macroinvertebrados bentónicos do estuário do Mondego. O conceito de suficiência
vi
Resumo
taxonómica, ou seja, a identificação dos espécimes a um nível taxonómico superior à espécie,
tem sido utilizado no âmbito da avaliação dos impactes das pressões antropogénicas sobre as
comunidades bentónicas, como forma de reduzir as necessidades em termos de especialistas
com conhecimentos detalhados em termos taxonómicos, permitindo reduzir o tempo de
trabalho laboratorial e, simultaneamente, aumentar a replicação espacial e temporal. Para
além de diferentes níveis taxonómicos, foram ainda testadas diferentes taxocenoses, afim de
verificar se os agrupamentos espaciais de estações de amostragem coincidiam com as
diferentes comunidades bentónicas identificadas através da utilização de todos os taxa.
No Capítulo 4 foi analisada a influência das variações sazonais nas comunidades
bentónicas do estuário do Mondego, na utilização dos índices propostos para avaliação do
estado ecológico dos estuários portugueses, no âmbito da DQA. Foram aplicados os índices de
diversidade de Margalef e Shannon-Wiener, o índice AMBI e o método das curvas ABC,
propostos pelo grupo de trabalho português (Bettencourt et al., 2004). Para averiguar quais
dos índices respondem mais eficazmente aos diferentes níveis de stress antropogénico, foram
utilizadas as medições de variáveis físico-químicas indicadoras de poluição. Foram testadas
algumas metodologias diferentes para utilização destas variáveis na determinação das
condições de referência.
No Capítulo 5 foram utilizadas duas abordagens multimétricas (B-IBI e TICOR) para
avaliar a qualidade ecológica de estuários incluídos no mesmo tipo da DQA (A2), mas com
diferentes características e níveis distintos de pressões antropogénicas, nomeadamente os
estuários do Mondego, Tejo e Mira. As comunidades bentónicas foram classificadas em
diferentes classes de qualidade, de acordo com a DQA e a eficiência das classificações obtidas
foi analisada por comparação com uma classificação prévia, tendo por base os resultados de
variáveis físico-químicas indicadoras de stress antropogénico. O comportamento das métricas
incluídas nos índices utilizados nos diferentes estuários foi analisado, tendo em conta as
especificidades ecológicas de cada estuário e os pressupostos assumidos para a inclusão das
métricas nos índices.
A integração dos resultados obtidos nos diferentes capítulos da tese foi efectuada no
Capítulo 6, através de um conjunto de considerações finais. A principal conclusão da tese é a
de que, efectivamente, as características dos estuários portugueses condicionam a utilização
dos instrumentos existentes para a avaliação do estado ecológico com base em comunidades
de macroinvertebrados bentónicos. As classificações obtidas com os índices testados
reflectem não apenas as diferenças nos níveis de degradação ambiental, mas também
variações espaciais e temporais, o que indicia a necessidade de adaptar essas metodologias
antes do seu uso sistemático em estuários portugueses.
vii
No estuário do Mondego foram identificados três grandes grupos espaciais,
essencialmente determinados por um forte gradiente longitudinal de salinidade. As
comunidades
bentónicas
apresentaram
variações
sazonais
bastante
acentuadas,
particularmente influenciadas pelas alterações dos caudais dulciaquícolas afluentes ao
estuário e às variações salinas daí decorrentes. As alterações mais acentuadas verificaram-se
no período de Inverno, cujas colheitas foram efectuadas após uma cheia, tendo como
consequência uma redução drástica das densidades e número de espécies, ao que se seguiu
uma recuperação significativa no período da Primavera. As variações sazonais observadas,
quer em termos salinos, quer em termos das comunidades de macroinvertebrados bentónicos,
permitiram classificar este estuário como poiquiloalino, dificultando a aplicação do sistema
de Veneza para estratificação longitudinal do estuário em diferentes zonas salinas, sem
modificações prévias, ao contrário do que acontece em estuários homioalinos. Estas
conclusões parecem ter aplicação em estuários semelhantes, como é o caso do estuário do
Mira, cujas variações salinas são igualmente bastante acentuadas entre épocas do ano
distintas.
Diferentes classificações são obtidas quando se utilizam os dados das comunidades
bentónicas correspondentes a diferentes épocas do ano e, para além disso, as classificações
obtidas pelos vários índices diferem, revelando um baixo nível de concordância entre os
mesmos. O período estival parece ser o mais adequado à monitorização do estado ecológico,
uma vez que os índices parecem responder de uma forma mais evidente ao nível de pressão
humana. Verificou-se uma maior correlação entre as respostas dos índices e as variáveis
indicadoras de eutrofização, sendo os índices de biodiversidade os que revelaram maior
capacidade de resposta preditiva à presença de poluição e o método ABC o que se revelou
menos eficaz na correspondência entre a degradação do meio e a resposta biológica. Estes
resultados sugerem que este último método não deverá ser utilizado em estuários sujeitos a
elevados níveis de stress natural. As respostas discriminantes dos índices aos diferentes níveis
de degradação ambiental foram mais eficientes durante o período estival, indicando a
necessidade de estratificação temporal para uma melhor aplicação destes métodos.
Ambos os índices multimétricos (TICOR e B-IBI) se revelaram bastante eficazes na
separação entre locais classificados acima ou abaixo da categoria de Bom estado, mas
incapazes de diferenciar entre outras classes de qualidade (Excelente/Bom, Moderado,
Mau/Medíocre). Para além disso, os resultados dos índices não revelam as diferenças nos
níveis de degradação identificadas entre os diferentes estuários, o que demonstra que as
características hidromorfológicas poderão dificultar o processo de classificação dentro de
estuários pertencentes ao mesmo tipo. As métricas integradas nos índices multimétricos
testados requerem alguns ajustes, que podem passar pela selecção de diferentes métricas e
viii
Resumo
pela alteração dos limites das classes de qualidade para estuários ou tipos de habitats
diferentes.
Apesar disso, os índices multimétricos revelaram-se mais robustos a possíveis erros de
classificação do que métricas individuais, uma vez que integram diferentes tipos de resposta
das comunidades bentónicas. Os estuários com características poiquiloalinas mais marcadas,
tais como o Mondego e o Mira, são aqueles em que a aplicação dos índices existentes parece
ser mais problemática, uma vez que as respostas das comunidades às pressões antropogénicas
se confundem com uma adaptação a condições extremamente variáveis, incluindo a
ocorrência de eventos extremos, como as cheias e as secas. Neste tipo de estuários, as
comunidades bentónicas são dominadas por espécies oportunistas e caracterizadas por uma
menor diversidade de espécies. No entanto, estas especificidades do ponto de vista ecológico,
tais como a dominância de taxa monotípicos, permitem a utilização de abordagens
alternativas para a tipologia, tais como a suficiência taxonómica, apesar da utilização de
diferentes taxocenoses ter-se revelado menos promissora. Não foram encontradas situações
de referência nos três estuários estudados, mas as variáveis físico-químicas, em especial a
concentração em nutrientes, parecem ser bons indicadores de referência para testar a
eficiência dos índices biológicos.
No último capítulo foram ainda sugeridas possíveis de linhas de investigação a seguir,
tendo em conta as questões levantadas pelo presente estudo. A identificação de condições de
referência parece ser um dos principais desafios no âmbito da implementação da DQA, uma
vez que todos os estuários portugueses se encontram, pelo menos, minimamente
intervencionados. A implementação de medidas de recuperação do bom estado de um
estuário piloto onde isso seja viável, tal como o Mira, parece ser um caminho promissor. A
selecção de métricas a serem integradas nos índices é outro dos desafios importantes, sendo
necessário testar a sua utilização nos diversos estuários portugueses. A realização de estudos
de longa duração é outro dos requisitos essenciais para determinar uma correcta
estratificação temporal dos programas de monitorização, de forma a ter em conta os possíveis
efeitos de variações interanuais. Por último, recomenda-se um estudo mais detalhado das
diferenças biogeográficas nas comunidades de macroinvertebrados dos estuários portugueses,
tendo em conta que Portugal é uma zona de transição entre diferentes regiões climáticas.
Diferenças acentuadas na composição taxonómica poderão influenciar o desempenho dos
índices em diferentes regiões do país.
PALAVRAS CHAVE: invertebrados bentónicos; indicadores biológicos; estuários portugueses;
variações sazonais; Directiva-Quadro da Água
ix
Summary
SUMMARY
Benthic macroinvertebrate communities have been widely used as indicators for
assessing and monitoring human impacts over aquatic ecosystems because they respond
predictably to many kinds of natural and anthropogenic pressures. They are also included in
the biological indicators of ecological status required by the Water Framework Directive
(WFD). The major objective of the present study was to investigate if the characteristics of
the Portuguese estuaries constrained the use of existing assessment tools for evaluating
ecological status based on benthic invertebrate communities.
Seasonal samples collected along the estuarine gradient of the Mondego estuary
showed considerable changes in the benthic community composition between seasons and a
drastic reduction on the number of taxa and abundances after a flood, although maintaining a
consistent spatial pattern of aggregation of stations along seasons. Nevertheless, these
changes influenced the results obtained with the application of indices proposed for use in
Portuguese estuaries in the aim of the WFD, requiring a temporal and spatial stratification.
Two multimetric indices were applied in the Mondego, Tejo and Mira estuaries during
the dry period, when indices respond better to pollution indicative variables, indicating that
none of these estuaries are in a Good status. The indices tested are efficient in separating
between benthic communities above and below Good status, but not accurate enough for
discrimination of other quality classes, as required by the WFD and multimetric indices are
more robust than single metrics. These indices are more adequate for estuaries less affected
by natural variation, such as the Tejo estuary. On the other hand, ecological adaptations in
highly dynamic estuaries as the Mondego and Mira estuaries support the use of higher
taxonomic levels in the typology process. Adaptation and validation of metrics and thresholds
of existing indices are recommended for its future application under the implementation of
the WFD.
KEY WORDS: benthic invertebrates; biological indicators; Portuguese estuaries; seasonal
variations; Water Framework Directive
xi
LIST OF PAPERS
This thesis comprises the papers listed below, each corresponding to a Chapter, from 2 to 5.
Chainho, P., Costa, J.L., Chaves, M.L., Lane, M.F., Dauer, D.M. & Costa, M.J. 2006. Seasonal
and spatial patterns of distribution of subtidal benthic invertebrate communities in the
Mondego River estuary, Portugal. Hydrobiologia 555: 59–74.
Chainho, P., Lane, M.F., Chaves, M.L., Costa, J.L., Costa, M.J. & Dauer, D.M. 2006.
Taxonomic sufficiency as a useful tool for typology in a poikilohaline estuary.
Hydrobiologia 587: 63-78.
Chainho, P., Costa, J.L., Chaves, M.L., Dauer, D.M. & Costa, M.J. 2007. Influence of seasonal
variability in benthic invertebrate community structure on the use of biotic indices to
assess the ecological status of a Portuguese estuary. Marine Pollution Bulletin 54: 1586–
1597.
Chainho, P., Costa, J.L., Chaves, M.L., Costa, M.J. & Dauer, D.M. (accepted) Use of
multimetric
indices
to
classify
estuaries
with
different
hydromorphological
characteristics and different levels of human pressure. Marine Pollution Bulletin.
The leading author of the papers comprised in this thesis was responsible for sample
collection and processing, laboratory procedures and species identifications, as well as data
analysis and manuscript writing.
TABLE OF CONTENTS
CHAPTER 1
General Introduction..................................................................3
CHAPTER 2
Seasonal and spatial patterns of distribution of subtidal benthic
invertebrate communities in the Mondego River, Portugal – a
poikilohaline estuary................................................................ 37
CHAPTER 3
Taxonomic sufficiency as a useful tool for typology in a poikilohaline
estuary ................................................................................ 63
CHAPTER 4
Influence of seasonal variability in benthic invertebrate community
structure on the use of biotic indices to assess the ecological status
of a Portuguese estuary ............................................................ 91
CHAPTER 5
Use of multimetric indices to classify estuaries with different
hydromorphological characteristics and different levels of human
pressure.............................................................................. 119
CHAPTER 6
Final Remarks ....................................................................... 151
Appendix 1
Chapter 1
General Introduction
General introduction
Chapter 1
General Introduction
To develop or not to develop a biotic index? – the beginning of this study
The decision to begin a study on benthic assessment tools was greatly influenced by
my previous experience with environmental impact assessment and monitoring studies, using
benthic communities as one of the biological components. Working on Portuguese estuaries, I
soon realized that both spatial and temporal heterogeneity was a key attribute, not only
between estuaries with different location, but also within each estuary.
As every researcher with some basic knowledge on ecology, I started by looking at the
composition of the benthic communities and the distribution of different benthic species, as a
result of the influence of environmental factors. Diversity indices were the very basic start to
a series of attempts to synthesize the vast and complex information of the benthic
communities, but the lack of reference studies on Portuguese estuaries made this approach
very subjective. The next step was the use of conceptual ecological models, such as the
Pearson & Rosenberg (1978) succession model, based on the knowledge of species’ tolerance
to organic pollution, and the Abundance and Biomass Curves (ABC) method (Warwick 1986),
which is based upon ecological relationships between stress and relative body size and
abundance patterns and therefore needs no independent reference conditions. Finally, I came
across multimetric indices, which integrated different types of attributes of the benthic
communities and combined them into a final result.
The Benthic Index of Biotic Integrity (B-IBI) developed by Weisberg et al. (1997) was
my most important inspiration for deciding to accept the challenge of developing a thesis on
benthic indicators of biotic integrity. At the time I wrote my working proposal, there was no
previous record of the application or development of benthic multimetric indices in the
Portuguese estuaries and the available studies on benthic communities were mainly focused
on the zonation of communities along environmental gradients (e.g. Andrade, 1986; Costa,
1988; Moreira et al., 1993) and particular aspects of the ecology of a few species (e.g.
Queiroga, 1990; Marques et al., 1994; Guerreiro, 1998). Some work had been done on the
effects of pollution on benthic communities, but was tipically restricted to narrow areas of a
particular estuary and/or to a single collection (e.g. Rodrigues, 1992; Marques et al., 1993;
Mucha & Costa, 1999).
All these factors, combined with the discussion and approval of the European Water
Framework Directive that included macroinvertebrate communities as indicators of ecological
status in estuaries, triggered the work that has resulted in this thesis. At first, my proposal
pointed towards the development of a B-IBI for Portuguese estuaries, based on the knowledge
3
developed in the USA on identifying habitat types and selecting specific benthic attributes for
each of those habitat types. Nevertheless, the fact that Portuguese estuaries are
characterized by high heterogeneity of environmental conditions and faunal composition, a
single index was very unlikely to be useful for different estuaries. A short time after starting
data compilation I had to recognize that testing the applicability of existing tools and
identifying major problems with their use across different estuaries would be a more
important contribution than developing a totally new index.
The final result, presented as a collection of articles published in international
research journals, is intended to be a contribution to the very challenging discussion on the
adequacy of existing indices to assess estuaries with very particular characteristics, such as
the Portuguese estuaries. During the development of this thesis, the investigation on the use
of benthic indices in Portuguese estuaries flourished and several other teams and researchers
published very important contributions. I truly hope that this thesis may represent an
additional block in building solutions for assessing the benthic status in Portuguese estuaries
and others with similar characteristics.
Estuaries – diversity of classifications
There is no single definition of estuary, although many authors refer to it as an
intermediate zone linking freshwater and marine systems (e.g. McLusky, 1971; Nybakken,
1993) or simply the saline mouth of a river where it meets the sea (Day, 1981a). Nonetheless,
one of the most accepted definitions of an estuary was provided by Pritchard (1967) as a
semi-enclosed coastal body of water, which has a free connection with the open sea, and
within which sea water is measurably diluted with freshwater derived from land drainage.
Additional important attributes of estuaries that serve as the basis for further estuarine
classification include patterns of salinity distribution influenced by interactions between
physiography, annual freshwater discharge patterns, and tidal amplitude.
Day (1981b) classifies estuaries as (1) normal estuaries, if there is an increase in
salinity from the river head towards the sea, (2) hypersaline estuaries, if salinity increases
from sea water values at the mouth to hypersaline values in the upper reaches, and (3) closed
or blind estuaries, if they are temporarily closed by a sand bar across the sea mouth due to
decrease on freshwater imputs, thus not having tidal fluctuations. Normal estuaries can also
be divided in different categories, according to variation in salinity in a vertical water
column, as (1) well-mixed, when no variation in salinity is observed along the vertical column,
(2) partially stratified, when there is a halocline between the upper and lower portions of the
water column but differences in salinity are lower then 3 parts per thousand and (3)
stratified, when differences in salinity between surface and bottom are higher than 3 parts
4
General introduction
Chapter 1
per thousand. In spite of this general classification, any given estuary may show variations in
stratification conditions as a function of factors that influence turbulence, such as
longitudinal distance along the estuary, season of the year or even the phase of the tidal
cycle (Officer, 1983).
The salinity regime is influenced by freshwater discharge, thus there are many
differences between estuaries with different climatic regimes. In temperate zones there is
more rainfall during winter than summer but rivers flow permanently throughout the year,
maintaining estuaries permanently opened to tidal influence (McLusky & McIntyre, 1995). In
these estuaries, fluctuations in salinity may occur frequently, but extreme values are seldom
registered. In contrast, in regions under sub-tropical influences, such as some areas in South
Africa and Australia, rainfall occurs only during the winter and for a short period and there is
a long dry period, during which freshwater flow may cease, interrupting the contact with the
sea for part of the year. These are often referred as temporarily-open estuaries and salinity is
normally very stable during the closing period, although it may register extreme fluctuations
during the rainfall period (Teske & Wooldridge, 2001).
In addition to salinity fluctuations, other variables create significant constraints to the
estuarine environment (Day, 1981b; 1981c; Vernberg, 1983):
(1) temperature ranges are greater than in the adjacent marine and freshwater
ecosystems;
(2) turbidity levels often make estuaries light-limited due to upstream inputs and resuspension of fine deposits, e.g. in the turbidity maximum zone;
(3) dissolved oxygen levels near the bottom are often lower than in rivers and the sea,
due to high allocthonous inputs and water column stratification. Reduction in oxygen
saturation is increased during stratification, since the bottom layer does not have
significant exchanges with the water surface;
(4) sediment type can vary greatly along the estuarine gradient, with coarser sediments
in the upper reaches, very fine sediments in the middle estuary, where the highest
deposition rates occur and sandier sediments near the mouth, resulting from marine
inputs with the tidal movements. In highly hydrodynamic estuaries, sediment
composition can be very unstable between seasons and re-suspension of the surface
layer occurs with the tidal cycle.
5
Estuaries – natural challenges for estuarine communities
High instability in environmental conditions is often postulated as the main reason for
having fewer species in estuaries than in the adjacent ecosystems (rivers and sea) (Sanders,
1968; Boesch, 1972; Wolff, 1973). Sanders (1968) developed a theory based on the stability or
predictability of the environment and on its geological history to explain lower diversity such
as in estuaries and brackish waters, supported by the following elements:
(1) environmental factors are, in general, unstable and unpredictable;
(2) speciation is less probable than in more stable environments;
(3) extinction is more probable than in more stable environments;
(4) estuaries are geologically ephemeral phenomena, thus increasing the likelihood of
extinction of brackish-water populations;
(5) the number of species adapted to the estuarine environment is thus lower than either
in freshwater and marine ecosystems;
(6) the unstable and unpredictable nature of brackish waters prevents colonization by
most freshwater and marine species.
Moreover, Kinne (1971) indicates that environments with pronounced salinity fluctuations
do not promote evolutionary processes because instability acts as a brake to speciation.
Therefore, fewer representatives of phyletic groups are likely to successfully colonize the
estuarine environment. On the other hand, those species that are able to adapt to brackish
waters often undergo ecological expansion as a result of reduced interspecific competition
and can therefore be very abundant.
Regardless of all constraints of the estuarine environment, there are also advantages for
resident organisms, such as (1) shelter against the action of wind waves and oceanic currents;
(2) high availability of food provided by river, saltmarsh and ocean inputs; (3) and food
particles readily available through sinking and downward transport by turbulent water
movements (Wolff, 1983). Estuaries are among the most productive natural systems, mainly
because of the rich supply of organic material from detritus and algae and nutrient input from
rivers (e.g. Day, 1981c; Wolff, 1983; Levin et al., 2001).
Estuarine species are not evenly distributed along the estuarine salinity gradient and
Remane (1934) proposed a first species distribution model, known as the “paradox of brackish
water”. He found that the lowest number of species was not recorded halfway between
freshwater and marine salinity, but displaced towards the freshwater boundary (Figure 1.1).
He assumed that this asymmetric distribution was due to different tolerances of freshwater
6
General introduction
Chapter 1
and marine species to salinity variations. While the number of freshwater species decreases
drastically with a slight increase in salinity, a higher number of marine species are more
tolerant to salinity decrease. The number of species showed two peaks corresponding to
freshwater and marine salinities. This model was later corroborated and adjusted by other
authors (e.g. Wolff, 1973; Boesch et al., 1976; Nybakken, 1993).
Figure 1.1. Remane curve (after Remane, 1934), showing
quantitative relations between freshwater, brackish and
marine invertebrate species. The relative number of
species is indicated by the vertical extension of the
respective areas.
The longitudinal distribution of species along the salinity gradient of estuaries has
also been used to divide estuaries into different regions and most differences in the
established boundaries resulted of different authors having used different biological elements
as a reference (e.g. diatoms, macroinvertebrates). Dahl (1956) questioned the salinity
boundaries proposed by several authors and the Remane curve and firstly introduced the
concept of poikilohaline and homoiohaline waters, the first referring to estuaries with very
unstable salinity conditions and the latter to waters with higher stability of salinity values.
7
Several authors proposed classification systems based on salinity classes, with most
differences concerning the boundaries between freshwater, brackish water and sea water.
Redeke (1935) placed the upper limit of brackish waters at salinity 0.21, while most authors
(e.g. Ekman, 1953; Kinne, 1971) identified this boundary at salinity 0.5 (Table 1.1). On the
other hand, Ekman (1953) considered that only salinities above 34.0 would correspond to
seawater, while most classifications would place that boundary at salinity 30.0 (Table 1.1).
The Venice System identifies five salinity regions along the estuary, as summarized in Table
1.1, and is the most widely used classification system (Anonymous, 1959).
Table 1.1. Classification of different estuarine regions, based on the longitudinal salinity
gradient
Redeke (1935)
Ekman (1953)
Venice System (1959) Kinne (1971)
Freshwater (<0.21)
Freshwater (0.0–0.5)
Limnetic (<0.5)
Oligohalinicum (0.5–5.0)
Oligohaline (0.2–1.8)
Oligohaline brackish (0.5–3.0)
Oligohaline (0.5–5.0)
Horohalinicum (5.0–8.0)
Mesohaline (1.8–18.0)
Mesohaline brackish (3.0–10.0)
Mesohaline (5.0–18.0)
Mesohalinicum (8.0–18.0)
Polyhaline (18.0–30.0)
Polyhaline brackish (10.0–17.0)
Polyhaline (18.0–30.0)
Polyhalinicum (18.0–30.0)
Sea water (>30.0)
Oligohaline seawater (10.0–30.0)
Euhaline (>30.0)
Thalassicum (30.0–40.0)
Mesohaline seawater (30.0–34.0)
Polyhaline seawater (>34.0)
An estuary can also be seen as an ecological boundary between rivers and the sea,
which motivated Attrill and Rundle (2002) to investigate if estuaries would fit into either an
ecotone or ecocline model, with an (1) ecotone being an area of rapid change between two
different and relatively homogeneous community types and an (2) ecocline being a gradient
zone environmentally more stable with a relatively homogenous unique community. They
concluded that estuaries represent a two-ecocline model, with fauna inhabiting the midestuary being either freshwater or marine species at the edge of their range, rather than true
estuarine species. Therefore, they question the existence of true estuarine species, similarly
to other authors that support the theory that species living in estuaries were mainly recruited
from the sea (e.g. Vernberg, 1983).
While most freshwater and marine species are typically stenohaline, withstanding a
very narrow salinity gradient, species occurring in estuaries are characteristically euryhaline,
i.e. capable of living along a wide salinity range (Remane & Schlieper, 1971). The critical
salinity boundary of 5.0-8.0 was indicated by Remane (1934) for euryhaline estuarine
organisms and is still accepted. One major adaptation of these organisms to salinity
fluctuations is the osmotic regulation of body fluids, by actively controlling water losses and
8
General introduction
Chapter 1
gains when exposed to higher or lower salinities, respectively or even capable of regulating
the cellular uptake of specific ions (Vernberg, 1983). Besides physiological adaptations,
organisms can also develop morphological adaptations to salinity, such as reduced sizes,
reduced surface in contact with the water and body surfaces less permeable, by increased
calcium deposits in the exoskeleton or increased mucous secretion. Exposure to salinity
fluctuations can also be avoided by burrowing behaviours, since in general salinity is more
stable in the sediments than in the water column (Sanders et al., 1965; Wolff, 1973). Salinity
is also very important in invertebrate species recruitment, since sharp reductions in salinity
may reduce growth rates and activity in invertebrate larvae. Migration is a very common
strategy for organisms that do not have other means to adapt to stressful conditions that
occur in estuaries during certain periods of the year.
For sedimentary benthos sediment texture is obviously a major factor influencing faunal
distribution in estuaries (e.g. Carriker, 1967; Gray, 1974; Boesch, 1977; Wolff, 1983; Kennish,
1986; Mannino & Montagna, 1997). Sediment characteristics are primarily a function of flow,
since the transport and deposition of sediment particles from rivers into estuaries are
regulated by freshwater flow (Day, 1981b). The middle part of the estuary, where maximum
flocculation occurs normally consists of finer sediments than the uppermost and lower areas,
but sediment composition varies greatly with local hydrodynamic conditions. Seasonal or even
daily changes of the sediment composition, due to fluctuations in flow and tidal movements
can be regarded as physical disturbances and affect the colonization by benthic invertebrate
species. There is a close relationship between sediment grain size and the trophic structure
of benthic communities and, in general, suspension feeders are more common in coarser
sandy sediments while deposit feeders seem to have a preference for muddy sediments
(Carriker, 1967; Rhoads & Young, 1970; Gray, 1974).
Seasonal fluctuations in abundance and composition can be observed due to
recruitment pulses that occur during spring and autumn for most species, but also to the
occurrence of extreme environmental conditions such as low temperatures, floods and
droughts (Alden et al., 1997; Attrill & Power, 2000; Salen-Picard & Arlhac, 2002). Benthic
communities inhabiting estuaries with seasonal floods and/or droughts will change (1) due to
pulses of organic matter during floods that stimulate an increase in abundance of
opportunistic species (Salen-Picard & Arlhac, 2002), (2) changes in the water and sediment
quality conditions, such as higher concentrations of contaminants during droughts (Attrill &
Power, 2000; Grange et al., 2000), (3) disappearance of all but highly euryhaline species
(Chainho et al., 2006), and (4) potential colonization by alien species that are, in general,
much more tolerant to salinity fluctuations than native species (Lee & Bell, 1999; Paavola et
al., 2005).
9
Temperature is also an important factor influencing estuarine organisms’ life cycles,
since slight changes in temperature often initiate the breeding response, interacting with
other factors, such as seasonal changes in temperature, day length and food abundance
(Sastry, 1975).
Another well known adaptation of estuarine organisms is the capacity to regulate
their metabolic rate to very low levels in oxygen-deficient habitats (Vernberg, 1983; Hylland
et al., 1997). Moreover, some benthic species, such as polychaetes and bivalves, can improve
the levels of oxygenation of hypoxic sediments, by increasing water exchanges through their
burrowing activities, phenomena known as
bioturbation (Levinton, 1995). Infaunal
bioturbation activity also influences biogeochemical processes in the sediment and redox
conditions (Rosenberg, 2001) and modifies the characteristics of the substratum (biogenic
habitat modifiers) (Constable, 1999). The level of oxygen in the sediment determines the
vertical distribution of infaunal species, with 95% living in the first 5 cm (Dauer et al., 1987).
Invertebrate estuarine communities also developed special reproductive strategies to
adapt to high hydrodynamic conditions, such as (1) gametal or larval release synchronized
with the tidal cycle, (2) mobile species migrate to release gametes or larvae in locations
compatible with the larval tolerances (Dauer et al., 1980), and (3) some species have benthic
lecitothrophic larvae that benefit from parental care (Vernberg, 1983).
Estuaries – anthropogenic challenges for estuarine communities
Estuaries are particularly exposed to human pressure, since the majority of the urban
areas are located in estuaries and coastal areas, and rivers and estuaries have always been
exploited as sources of food and used as transport ways and disposal receptors. The study of
estuarine ecology is closely related to increasing awareness on the deleterious impacts of
human activities upon estuarine health, as shown by the pioneer work of Alexander et al.
(1935 in McLusky, 1999), a detailed study of the Tees estuary in the UK, reporting extreme
degradation of a large extension of that estuary. Some well known anthropogenic pressures
are urban and industrial sewage discharge, agriculture and urban runoff, navigation,
dredging, fisheries, aquaculture, wetland occupation, invasive species and climate change.
Impacts on estuarine organisms are very complex in nature because the effects are often a
result of interactions between different stressors, confounding the interpretation of data and
the effects of specific pollutants. Nevertheless, some specific pressures and their impacts on
the benthic fauna are well documented:
(1) Organic enrichment – estuaries are naturally rich in organic matter, mainly resulting
allocthonous detrital input as well high levels of autochthonous primary production.
Human activities, such as sewage discharge and aquaculture increase the natural
10
General introduction
Chapter 1
organic load with labile organic matter with a low C:N ratio and a high content of
nutrients when compared to natural sources (Kristensen, 1990; Holmer & Kristensen,
1994). The effects of organic enrichment on benthic invertebrate communities have
been extensively studied and Pearson & Rosenberg’s (1978) model is widely used to
explain the succession of species along an enrichment gradient. These authors found
that an undisturbed macrobenthic community maintains relatively high species
richness and biomass as well as moderate total abundance. A slight increase of
organic inputs favours the occurrence of a higher species number, with higher
abundance and biomass and a peak of opportunistic species occur with high organic
inputs. These opportunistic species are small-bodied and have high growth rates,
explaining a biomass peak. Ultimately, when extreme pollution levels occur,
abundance, biomass and number of taxa decrease abruptly and heavily polluted areas
may be azoic (Pearson & Rosenberg, 1978; Rakocinski et al., 2000).
(2) Eutrophication
–
According
to
the
OSPAR
Convention
(OSPAR,
1997),
an
eutrophication process is “the enrichment of water by nutrients causing an
accelerated growth of algae and higher forms of plant life to produce an undesirable
disturbance to the balance of organisms present in the water and to the quality of
the water concerned, and therefore refers to the undesirable effects resulting from
anthropogenic enrichment by nutrients”. Eutrophication has become a significant
problem in many estuaries and coastal areas over the last four decades (Bricker et
al., 2003), mainly due to sewage discharges an agriculture runoff. Associated with
algal blooms are low dissolved oxygen levels that are the result of particulate matter
deposition and stimulated microbial decomposition of organic matter. Such
decreased oxygen levels may be a direct cause of death or severe disturbance of
benthic invertebrate fauna (Flindt et al., 1997).
(3) Non-nutrient pollutants – The most common groups of contaminants found in
estuaries include heavy metals (e.g. Cu, Cr, Hg, Ni, Pb, Zn), Polynuclear Aromatic
Hydrocarbons (PAHs) Polychlorinated Biphenyls (PCBs) and some pesticides (e.g.
aldrin, DDT, dieldrin, hexachlorobenzene). While pesticides are mainly from diffuse
sources, all others can be either from point source discharges (e.g. industrial
activities) or diffuse origins (motorway lixiviation). The presence of these chemicals
in the water and sediments can affect the reproduction, development, and,
ultimately, survival of living resources and have been referred to as toxic chemicals,
or chemical contaminants. Several authors have shown deleterious effects of these
contaminants on the benthic fauna, including (1) decreased growth rates (Levin et
al., 1996), (2) lower fertility (Zulkosky et al., 2002), (3) carcinogenic and mutagenic
sublethal toxic effects (Kennish, 1992) and bioaccumulation along the benthic food
11
web (Costello & Read, 1994). On the other hand, below certain concentrations,
chemicals may induce competitive advantages to opportunistic species (Boesch &
Rosenberg, 1981 in Rakocinski et al., 2000; Beeby & Richmond, 2001). The toxicity of
sediments with chemical contaminants is often measured through acute toxicity tests
with amphipod species, based on survival and reproduction rates (e.g. Costa et al.,
1998; Casado-Martinez et al., 2007).
(4) Physical impacts – The alteration/destruction of wetlands for urban purposes is a major
cause of habitat loss in estuaries, especially saltmarsh areas, reducing some specific
habitats colonized by benthic invertebrates. Changes in the sediment composition
may also occur in the course of dredging activities, normally performed for sand
extraction and maintenance of the navigations channels. This can lead to
replacement of coarser sediments by fine deposits at the extraction site and to
colonization by benthic communities which are different from those in the original
deposits (Hall, 1994), more often dominated by opportunistic polychaetes (Seiderer &
Newell, 1999; Van Dalfsen et al., 2000). Intensive bottom fishing activities, especially
by gears that dig into the sea-bed or bottom trawling have major impacts upon
benthic communities, such as changes in the ratio of major groups and disappearance
or fragile species (Kaiser & Spencer, 1996; Hill et al., 1999).
Ecological assessment and environmental policies - The Water Framework
Directive
In the last two decades, environmental indicators have become a very important
component of national and international environmental regulations, mainly through the
obligation of developing environmental impact assessment studies for most projects with
potential environmental impacts and environmental policies that require monitoring of the
biological components (e.g. EEA, 2001; OECD, 2001; EPA, 2003). Setting environmental
objectives for estuaries has become a worldwide concern, as shown by the framework for
water quality management defined by the Australian and New Zealand Governments (ANZECC,
2000), the South African National Water Act (Act 56 of 1998), the North American Clean
Water Act (Gibson et al., 2000) and the European Water Framework Directive (WFD)
(2000/60/CE).
The WFD sets the achievement of good ecological status and good chemical status for
surface waters by 2015 as its major objectives. The successful implementation of this
directive depends on an integrated approach to water problems, supported by some
fundamental concepts, such as (1) a single approach of water protection for all waters,
including surface waters and groundwater, (2) achieving Good status for all waters by a set
12
General introduction
Chapter 1
deadline, (3) water management based on river basins, (4) a combined approach of emission
limit values and quality standards, (5) using water pricing as an incentive for better use, (6)
getting citizens involved more closely and (7) streamlining legislation.
The assessment of ecological status requires the development of adequate tools,
based on the identification of surface water types, the definition of type-specific reference
conditions, and the classification of all water bodies within five ecological quality classes. A
common implementation strategy for the WFD was agreed between European Member States
and several working groups developed guidance documents on diferent aspects of the WFD,
including the assessment of ecological status in transitional waters (i.e. estuaries).
Typology
The process of typology was established with the purpose of assigning water bodies to
a physical type, in order to ensure that valid comparisons of its ecological status can be
made. For each type, reference conditions must be described as these form the ‘anchor’ for
classification of the water bodies’ status or quality. The identification of water types
according to the WFD, can follow two different approaches, designated by system A and
system B. If system A is used the type must first be assigned to an Ecoregion, as indicated in
the WFD and then described according to mean annual salinity and mean tidal range. In case
of using system B, at least the same degree of differentiation must be achieved as if system A
was used. System B uses a series of obligatory (e.g. tidal range and salinity) and optional
factors (e.g. mean substratum composition, current velocity) in order to classify surface
waters into types. Within each type, water bodies have to be identified, as the basic
management units of the WFD. The subdivision of water types into smaller water bodies
depends upon the pressures and resulting impacts, because areas that show different quality
status, although included in the same water type, will have to be managed separately.
Reference conditions
The reference condition is a description of the biological quality elements that exist,
or would exist under no or very minor disturbance from human activities, therefore
corresponding to a High status. Reference condition standards are used to assess the
ecological quality by comparing each situation against these standards. Reference conditions
are characterized for each water type, based on the biological elements considered by the
WFD for transitional waters, namely phytoplankton, other aquatic flora (macroalgae and
angiosperms), benthic invertebrate macrofauna and fish fauna. Some methods indicated by
the WFD to define reference conditions are (1) using existing pristine conditions, (2) using
13
historical, paleontological and other available data with sufficient level of confidence about
the values for the reference condition, (3) using modelling techniques, either predictive
models or hindcasting methods or (4) expert judgement when other methods are not possible.
Reference conditions must summarise the range of possibilities and values for the biological
quality elements over periods of time and across the geographical extent of the type, i.e.
reflect the natural variability of the characterization elements.
Classification of quality status
The assessment of chemical status is based on a list of priority substances for which
Environmental Quality Standards (EQSs) are set at the European level. There are only two
categories for chemical status: Good and Bad. On the other hand, there are three groups of
quality elements to be considered in the assessment of ecological status: (1) biological
elements (listed in the reference conditions), (2) hydromorphological elements supporting the
biological elements (i.e. tidal regime and morphological characteristics) and (3) chemical and
physical-chemical elements supporting the biological elements, these last including general
physical-chemical elements (e.g. temperature, salinity, nutrient concentrations) and specific
non-priority substances identified as being discharged in significant quantities. Biological
elements must be assigned into five different quality classes (High, Good, Moderate, Poor and
Bad), by comparing it against the reference conditions for that type and expressed as an
Ecological Quality Ratio (EQR) that varies between 0 (Bad status) and 1 (High status).
Although different methods can be used by different countries to classify the ecological
status, the classifications have to be comparable. To ensure that different methods produce
similar classifications, all European countries are participating in an intercalibration process,
in which the results obtained using different methods are compared within the same water
types.
The integration of biological criteria in the assessment and definition of water quality
standards was one of the major changes introduced by the WFD to European legislation on
water issues. As pointed out by Dauer (1993), the use of biological elements is very important
because (1) they are direct measures of the condition of the biota, (2) they may uncover
problems undetected or underestimated by other methods, and (3) such criteria provide
measurements of progress of restoration efforts. However, biological criteria should not
replace toxicity and chemical assessment methods, but complement the information
produced by those, serving as independent evaluations of the quality of marine and estuarine
ecosystems (Dauer, 1993).
14
General introduction
Chapter 1
Benthic invertebrates as indicators
Benthic macroinvertebrate communities (here defined as organisms retained on a 0.5
mm screen) have been widely used as indicators for assessing and monitoring human impacts
over aquatic ecosystems. Several characteristics of these communities make them respond
predictably to many kinds of natural and anthropogenic pressures:
(1) Most benthic invertebrate species have limited mobility and are less able to avoid
potential harmful conditions than mobile species, thus reflecting local conditions
(Gray, 1979);
(2) Benthic species show very diverse physiological tolerances, life strategies and feeding
modes, being sensitive to different types of stress (Pearson & Rosenberg, 1978;
Bilyard, 1987);
(3) Life cycles, longevity and recruitment potential of most species allow the community
structure to integrate and reflect disturbances over a relatively long period of time
(Paul et al., 2001);
(4) Many benthic organisms live in the sediment-water interface, where contaminants
can accumulate over long periods (Gray & Pearson, 1982);
(5) Benthic organisms are a very important component of estuarine ecosystems, closely
coupled with the pelagic food web, constituting a link for the transport of
contaminants to higher trophic levels (Pearson & Rosenberg, 1978; Herman et al.,
1999).
Because of these characteristics, they have been often used as a proxy for assessment
of the habitat quality or biological integrity, commonly defined as “the capability of
supporting and maintaining a balanced, integrated, adaptive community of organisms having
a species composition, diversity and functional organization comparable to that of the natural
habitat of the region” (Karr & Dudley, 1981). Impacts on aquatic ecosystems may be
measured at different levels of biological organization, which can include several components
of the ecosystem (e.g. estuarine food web), certain communities (e.g. benthic infaunal
macroinvertebrates), a few indicator species (e.g. pollution indicator species) or even
populations (e.g. population dynamics of keystone species).
A good indicator should be (1) applicable to many areas/situations and scales of
measurement, (2) repeatable and reproducible by others besides its authors, (3) sensitive to
pressures acting on the system, responding in a predictable manner, but be relatively
insensitive to expected (natural) sources of interference, (4) operationally simple (e.g. not
require excessive data collection skills), (5) predict changes that can be mitigated through a
15
correct management, (6) integrative and cover key ecological gradients, (7) scientifically
reliable, and (8) the benefits of the information provided by the indicator should outweigh
the costs of usage (Dale & Beyeler, 2001; Niemeijer & Groot, 2007).
Several methods have been used to study benthic communities, incorporating the
simultaneous responses of many species rather than using a single species as indicator. In
general, most approaches are based on the description and quantification of benthic
communities’ patterns and the correlation of those patterns with environmental conditions.
Single or multiple attributes of the benthic communities have been used to measure
deviations from the normal patterns in undisturbed conditions, but the most commonly used
are abundance, biomass, species richness and diversity and the balance between pollutionsensitive and pollution-tolerant species (e.g. Pearson & Rosenberg, 1978; Warwick, 1986;
Weisberg et al., 1997; Borja et al., 2000). With the availability of computational tools, the
analysis of more complex data sets was possible, through methods such as classification and
ordination techniques, which allow identifying general patterns of the benthic communities
and relating them to environmental patterns. These techniques are often used to examine
spatial patterns of distribution and changes occurring along time, associated to disturbance
events (Gray & Pearson, 1982). Although multivariate analysis is very useful for describing
strong pollution gradients and/or changes in the spatial and time distribution patterns, it is
often difficult to interpret it into understandable results for management purposes.
The need to communicate complex patterns of the structure of benthic communities
in a management perspective was one of the major reasons for the development and
successful widespread use of biotic indices or indices of biotic integrity. Indices simplify the
characterization of the overall state of the ecosystem by reducing it to a single number,
quantify
the
deviations
to
reference
conditions
and
facilitate
communication
on
environmental issues to stakeholders and policy makers (Aubry & Elliott, 2006). Diversity
indices are among the most used in ecology and environmental assessment and are often
included in multimetric indices. The most commonly used indices of diversity are the
Shannon-Wiener index (Pielou, 1969), which incorporates species richness and evenness,
Sander’s rarefaction technique (Sanders, 1968), based on an estimate of the number of
species among 100 individuals (ES100), later modified by Hulbert (1971), Margalef and
Simpson’s diversity indices that measure the probability that two individuals randomly
selected from a sample will belong to the same species (Simpson, 1949). The reduction of the
complexity of species composition into a single number, although very appealing, does not
incorporate other important information of the benthic community, such as the sensitiveness
to stress, trophic interactions or life cycles, since all species are given equivalent weights.
Warwick (1986) developed the Abundance-Biomass Comparison method (ABC) that
assumes that in undisturbed communities the biomass curve will lie above the abundance
16
General introduction
Chapter 1
curve, while in highly stressed communities the biomass curve will lie below the abundance
curve. Since the interpretation of the results was mainly graphical, Clarke (1990) proposed
the W-statistic as a measure that expresses the degree to which the biomass curves lie above
the abundance curves. Other indices, such as the AZTI Marine Biotic Index (AMBI) (Borja et
al., 2000) and BENTIX (Simboura & Zenetos, 2002) are based on the classification of species
into different ecological groups, according to their sensitiveness/tolerance to pollution. The
number of ecological groups varies according to each index (five for the AMBI and two for the
BENTIX). AMBI has been changed to incorporate Shannon-Wiener diversity and species richness
into a final classification, based on the classification of status by measuring deviations from
reference conditions using factorial analysis, therefore, this approach is called Multivariate or
M-AMBI (Muxika et al., 2007). Similar to M-AMBI, the Community Disturbance Index (CDI) also
derives classifications using a multivariate model constrained by reference conditions (Flåten
et al., 2007). The Benthic Quality Index (BQI) incorporates a measure of species’ tolerance to
disturbances, but also Hulbert’s diversity index (Rosenberg et al., 2004).
Moreover, there are indices that consider information on the feeding habitat of
invertebrate species, such as the Infaunal Trophic Index (ITI), in which species are assigned to
four different trophic groups (i.e. suspension feeders, carrion feeders, surface deposit
feeders and sub-surface deposit feeders) and the result of the index is based on the relative
contribution of each group (Dauvin et al., 2007). Information on the taxonomic value of the
benthic communities has also been incorporated in assessment tools, such as taxonomic
distinctness, a measure that captures phylogenetic diversity, represented by taxonomic
distances between every two pairs of individuals (Clarke & Warwick, 1998). The “complexity”
of the ecological species at a given location can also be used as an indicator by determining
the exergy, a thermodynamically based index that measures the maximum amount of useable
work that can be extracted when a system is brought into equilibrium with a reference state
(Marques et al., 1997). One major problem of most of these indices concerns its application
to estuaries because of the high level of natural stress in this transitional environment.
Species adapted to the high natural stress in estuaries are also commonly identified as
opportunists under disturbances caused by pollution (Borja & Muxika, 2005; Chainho et al.,
2006; Chainho et al., 2007).
Most authors recommend the use of multiple methods based on different assumptions
or data analysis approaches in order to more robustly encompass the diverse responses of the
benthic communities to stressors (e.g. Dauer et al., 1993; Van Dolah et al., 1999; Bettencourt
et al., 2004; Borja & Muxika, 2005; Salas et al., 2006; Flåten et al., 2007). Multimetric
indices, i.e. indices that combine different metrics into a single index value, are thought to
be more accurate and robust in assessing benthic community condition compared to single
metrics. These metrics are biological measurements that represent the structure and function
17
of the benthic invertebrate assemblages. In some multimetric indices developed for North
American estuaries, such as the B-IBI and the MAIA index, habitat specific thresholds and
temporal stratification applications are indicated as a solution to encompass natural
differences along the estuarine gradient and eliminate noise introduced by seasonal changes
in the communities (Weisberg et al., 1997; Van Dolah et al., 1999; Llansó et al., 2002).
As pointed out by Diaz et al. (2004), a plethora of indices are continuously being
developed, with no apparent justification. This author argues that the refinement and
adaptation of the existing indices to different regions from those for which they were
developed should be the priority.
Portuguese estuaries
Before the publication of the Water Framework Directive, available studies on benthic
communities in Portuguese estuaries were mainly focused on the zonation of communities
along environmental gradients (e.g. Andrade, 1986; Marques & Bellan-Santini, 1987; Costa,
1988; Quintino & Rodrigues, 1989; Quintino et al., 1989; Moreira et al., 1993) and particular
aspects of the ecology of a few species (e.g. Queiroga, 1990; Marques et al., 1994; Guerreiro,
1998). Some work had been done on the effects of pollution on benthic communities, but
often restricted to narrow areas of a particular estuary and/or to a single collection (e.g.
Rodrigues, 1992; Marques et al., 1993; Mucha & Costa, 1999). Some of these studies were
conducted as part of environmental impact studies, often related to dredging operations
needed for maintaining navigation conditions in estuaries (e.g. Costa et al., 1999; Carvalho et
al., 2001; Rodrigues & Quintino, 2002;), but also for monitoring purposes (Pereira et al.,
1997; Silva et al., 2006). Long term data sets are available only for the Mondego (e.g. Dolbeth
et al., 2007) and Tejo estuaries (e.g. Silva, 2006; Silva et al., 2006), making it difficult to
interpret variations in benthic communities related to inter-annual changes in the
environmental conditions. With the process of implementation of the WFD the investigation
on assessment of the ecological status in Portuguese estuaries was encouraged and several
teams and researchers got involved in the implementation process, publishing very important
contributions.
The Portuguese working group for transitional waters compiled relevant data for
Portuguese
estuaries
into
a
database,
although
for
most
estuaries
data
on
hydromorphological, physical chemical and biological elements were not available for
oligohaline and tidal freshwater stretches (Bettencourt et al., 2004). System B was used as a
typology tool for Portuguese transitional waters and in addition to the obligatory factors (i.e.
latitude/longitude, salinity and tidal range), mixing conditions, wave exposure and depth
were also used as optional factors in the identification of water types. Portuguese estuaries
18
General introduction
Chapter 1
were classified into two different water types, namely type A1 that included Minho, Lima,
Douro and Leça estuaries, characterized by mesotidal and stratified conditions, and type A2,
which included well-mixed estuaries with irregular river discharge, namely Ria de Aveiro,
Mondego, Tejo, Sado, Mira, Arade and Guadiana estuaries (Bettencourt et al., 2004). Type A2
is unique in the European context, but it includes estuaries with very distinct characteristics,
For instance, the area of these estuaries varies between 17 Km2 and 2200 Km2 and the
average freshwater flows may range from 10 m3.s-1 to 400 m3.s-1 (Mira and Tejo estuaries,
respectively) (Ferreira et al., 2003). Estuaries were further divided into water bodies, taking
natural and human components into account and the number of water bodies identified in
each estuary varied between three (Lima, Douro, Mondego, Mira and Guadiana estuaries) and
six (Sado estuary) (Ferreira et al., 2005). Nevertheless, Teixeira et al. (in press) concluded
that six sectors would be needed in the Mondego estuary to encompass the benthic
communities’ variability and define habitat specific reference conditions. The ShannonWiener diversity index, the Margalef species richness index (Legendre & Legendre, 1976), the
AMBI index (Borja et al., 2000) and the ABC method (Warwick, 1986) were selected to assess
the benthic condition in the Portuguese estuaries and a combination of two or three indices
(TICOR approach) is proposed to classify the benthic status according to the requirements of
the WFD (Bettencourt et al., 2004).
The efficiency of these indices was tested in the Mondego estuary by Salas et al.
(2004), showing that AMBI was more accurate in separating between degraded and
undegraded conditions. These authors recommend the complementary use of different
methods, since single indices did not always show predictable responses to anthropogenic
stress. However, when tested in other locations, these indices and others, such as taxonomic
distinctness and exergy were not sensitive enough to classify benthic status into five different
categories, as required by the WFD (Salas et al., 2005). Moreover, Carvalho et al. (2006)
corroborated the usefulness of AMBI to identify the responses of benthic communities along
gradients of organic enrichment in the Óbidos coastal lagoon. Conversely, Quintino et al.
(2006) concluded that variability of environmental indicators and indices within stations could
be as large between stations when using AMBI, BQI, and the United Kingdom ecological quality
ratio – the latter derived for benthic communities, abundance/richness and biomass/richness
ratios. Those authors emphasized the need for further testing and validating indices that
were developed elsewhere before applying it to Portuguese estuarine systems.
19
FRAMEWORK AND OBJECTIVES OF THIS STUDY
Available comprehensive scientific data on benthic invertebrate communities of
Portuguese estuaries was very scarce in the beginning of the present study, either because
data sets did not include information on different spatial units (i.e. habitats) along the
estuarine gradient, or collections were obtained in a specific season, thus not including
information on time variability of the benthic communities. These aspects are particularly
important in the aim of the implementation of the European Water Framework Directive that
requires a systematic assessment of the ecological quality based on biological elements,
including benthic invertebrates, taking into account the natural variability (spatial and
temporal). Specific features of the Portuguese estuaries and the current state of knowledge
on the respective benthic communities represented a challenge and a reason for developing
the present research, as follows:
(1) Portugal is a transition area since, although included in the subtropical sub province
(Strait of Gibraltar to Finisterre) of the Lusitanian climatic province, for most
taxonomic groups there are differences between the northern and southern
assemblages (OSPAR Commission, 2000). Cape Carvoeiro is indicated as a transition
area for coastal marine ecosystems (Hayden et al., 1984) and the Tejo estuary is also
pointed out as a biogeographical boundary between Mediterranean, temperate and
sub-tropical Atlantic realms (INAG, 2001);
(2) Most Portuguese estuaries have irregular river discharge, altering regularly the
environmental conditions and constraining the occurrence of benthic species with
different levels of tolerance to natural stress. This type of estuary is known as
poikilohanine (variable salinity conditions) and is poorly known when compared to
homiohaline estuaries (stable salinity conditions). Although all influenced by irregular
river discharge, poikilohaline estuaries have very distinct morphological and
hydrological characteristics;
(3) Portuguese estuaries are strongly affected by extreme climatic events, such as floods
and droughts, whose frequency is expected to increase with climate change;
(4) Most Portuguese estuaries are under severe anthropogenic stress and none can be
considered as a pristine transitional area, hence reference conditions cannot be
derived based on existing sites;
(5) The WFD requires the identification of water types that are ecologically meaningful
and further definition of type specific reference conditions, against which the
classification of the ecological status of water bodies must be done. The WFD is
20
General introduction
Chapter 1
particularly demanding for countries with no systematic monitoring of the biological
components, as is the case of Portugal.
(6) A considerably high number of indices to assess benthic invertebrate status are
available for marine environments but very few were developed specifically for
estuarine conditions. No specific indices have been developed for Portuguese
estuaries.
Considering this particular context, the main objective of this study was to
investigate if the characteristics of the Portuguese estuaries constrained the use of existing
assessment tools for evaluating ecological status based on benthic invertebrate communities.
To test this hypothesis, several different questions were formulated:
(1) What are the major environmental gradients influencing the spatial distribution of
benthic invertebrate communities in Portuguese estuaries?
(2) Do seasonal variations in the environmental conditions change those spatial patterns
of distribution?
(3) How do seasonal patterns in macroinvertebrates influence the results of benthic
indices?
(4) Are there significant differences in the classifications obtained with indices when
applied during different seasons?
(5) Do benthic invertebrate communities show different responses to natural and
anthropogenic sources of stress?
(6) Which environmental variables best reflect the responses of the benthic communities
to human stressors?
(7) Can higher taxonomic levels and taxocenes be used in the typology process?
(8) Do hydromorphological differences in estuaries included in the same type influence
the use of indicators?
(9) Are multimetric indices better than individual metrics?
(10)Are available indices adequate to assess ecological status in Portuguese estuaries with
the accuracy required by the WFD?
Three different Portuguese estuaries were selected to test the assessment tools and
answer these questions, namely the Mondego, Tejo and Mira estuaries. Seasonal samples were
collected in the Mondego estuary to investigate aspects related to seasonal variations, while
21
only summer collections took place in the other estuaries, allowing for comparisons of
different levels of human pressure and different hydromorphological characteristics.
THESIS OUTLINE
This thesis was divided in six different chapters, including a General Introduction,
four papers published or in press in scientific journals included in the science citation index
and some Final Remaks, as it follows:
-
Chapter 1 is a general introduction that summarises and organizes the major
characteristics of estuaries and the constraints that these particular environments
present to benthic invertebrate communities. This introduction also gives an overview of
policies and regulations that require the implementation of benthic assessment tools,
with particular emphasis for the European Water Framework Directive. Some advantages
of using benthic invertebrates as indicators of environmental quality are indicated and a
summary revision of the major attributes and indices used is also presented. This chapter
also includes an update on the current knowledge on the benthic communities of
Portuguese estuaries and some of the major findings on the use of benthic assessment
tools in these estuaries, in the context of the implementation of the WFD. The objectives
of the thesis and the questions behind the definition of these objectives conclude this
chapter.
-
Chapter 2 consists of a paper that identifies seasonal and spatial patterns of distribution
of subtidal benthic invertebrate communities in the Mondego River estuary. This paper
examines the adaptations associated with benthic communities in estuaries with highly
variable environmental conditions, including the occurrence of floods, addressing
questions 1, 2 and 5. It was published in the journal Hydrobiologia, referenced as
Chainho, P., Costa, J.L., Chaves, M.L., Lane, M.F., Dauer, D.M. & Costa, M.J. 2006.
Seasonal and spatial patterns of distribution of subtidal benthic invertebrate
communities in the Mondego River estuary, Portugal. Hydrobiologia 555: 59–74.
-
Chapter 3 consists of a paper on the use of taxonomic sufficiency in Mondego River
estuary for typology purposes. Different water body types are identified using the Venice
salinity system and ecological consistency of that identification is evaluated by analysing
the spatial patterns of distribution of benthic invertebrate communities among different
seasons. Different taxonomic levels and taxocenes are used to test for their ability to
discriminate between water body types previously defined, addressing questions 2 and 7.
This paper was published in Hydrobiologia, referenced as Chainho, P., Lane, M.F.,
22
General introduction
Chapter 1
Chaves, M.L., Costa, J.L., Costa, M.J. & Dauer, D.M. 2006. Taxonomic sufficiency as a
useful tool for typology in a poikilohaline estuary. Hydrobiologia 587: 63-78.
-
Chapter 4 consists of a paper that examines the influence of seasonal variability in the
benthic invertebrate communities of the Mondego estuary and how those changes might
influence the use of biotic indices. The methods proposed by the WFD Portuguese working
group for transitional waters are tested to see how robust the results are when no
temporal stratification is applied, addressing questions 3, 4 and 6. This paper was
published in Marine Pollution Bulletin, referenced as Chainho, P., Costa, J.L., Chaves,
M.L., Dauer, D.M. & Costa, M.J. 2007. Influence of seasonal variability in benthic
invertebrate community structure on the use of biotic indices to assess the ecological
status of a Portuguese estuary. Marine Pollution Bulletin 54: 1586–1597.
-
Chapter 5 consists of a paper that compares the results obtained by two different
multimetric indices, TICOR approach and B-IBI, when applied to three Portuguese
estuaries with different hydromorphological characteristics and different levels of human
pressure. The results of these indices are tested for consistency with a priori status
categories based physical-chemical criteria, addressing questions 8, 9 and 10. This paper
is in press in Marine Pollution Bulletin, referenced as Chainho, P., Costa, J.L., Chaves,
M.L., Costa, M.J. & Dauer, D.M. In press. Use of multimetric indices to classify estuaries
with different hydromorphological characteristics and different levels of human
pressure. Marine Pollution Bulletin.
-
Some final remarks are presented in Chapter 6, integrating the results obtained in each
chapter and presenting the major conclusions of the study. Relevant questions that arose
from this thesis are also formulated, as guidance for the development of possible future
studies.
23
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33
Chapter 2
Seasonal and spatial patters
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Seasonal and spatial patterns
Chapter 2
Seasonal and spatial patterns of distribution of subtidal
benthic invertebrate communities in the Mondego River,
Portugal – a poikilohaline estuary
ABSTRACT
The use of benthic assemblages to assess ecological quality of estuarine environments
is a major tool for the implementation of the Water Framework Directive (2000/60/CE) for
European aquatic ecosystems. Benthic communities show spatially heterogeneous
distributions and experience seasonal variations due to both natural and anthropogenic
stresses. The major goal of this study was to quantify the relationships between
environmental gradients and the spatial and temporal patterns of the benthic communities
along a Portuguese estuary. Seasonal and spatial variations relating macrobenthic
communities and measures of water and sediment quality along the northern branch of the
Mondego River estuary were examined at seven sampling stations from July 2000 to June
2001. Cluster analysis of biological data indicated three major groups of communities based
on spatial distribution patterns: (1) a lower sector with stronger marine influence and
dominated by Streblospio shrubsolii and Cerastoderma glaucum; (2) a middle sector with
dominance of S. shrubsolii and Corophium multisetosum; (3) and an upper sector where C.
multisetosum dominates a community characterized by a lower number of species. Canonical
correspondence analyses of biological and environmental data determined a major salinity
gradient influencing benthic communities. Seasonal changes of benthic communities were
mainly determined by freshwater input and salinity changes that imposed a strong decrease in
densities and number of species during winter, followed by a recovery during spring. Benthic
ecological structure and contaminant levels indicated that the Mondego northern branch is
moderately disturbed, although opportunistic species dominated the benthic community,
suggesting that natural and anthropogenic sources of stress may be acting together. The
Mondego River estuary, a poikilohaline-type estuary, characterized by strong seasonal
changes in water flow and salinity, cannot be consistently stratified into salinity regions
based upon the Venice classification system. Biotic communities, exemplified here by the
benthic communities, are seasonally displaced, compared to a homiohaline-type estuary
where the Venice system can be applied without modification. Future identification of
reference conditions and design of monitoring programs cannot be accomplished without
understanding how interactions between biotic and physical-chemical dynamics differ
between homiohaline and poikilohaline estuaries. Results obtained in this study could be used
to assist future assessments in other Portuguese estuaries.
KEY WORDS: benthic condition, spatial patterns, seasonal variations, environmental gradients,
Mondego River estuary, Venice salinity system.
37
INTRODUCTION
Benthic invertebrate communities have been widely used as indicators of the
ecological status of coastal and estuarine ecosystems (e.g. Pearson & Rosenberg, 1978; Hily
et al., 1986; Dauer, 1993; Weisberg et al., 1997; Borja et al., 2003) and were included in the
biological elements indicated by the Water Framework Directive (WFD) (2000/60/EC) for use
in environmental monitoring. Benthic infaunal species live in the sediments and show
relatively low mobility, being exposed to stress due to contaminants, low dissolved oxygen,
limiting nutrient levels and physical disturbances (Dauer et al., 1992; Weisberg et al., 1997;
Cowie et al., 2000). Benthic communities include species with different life cycles and
specific tolerances to stress events, which make them suitable to be classified into different
functional groups that reflect the magnitude of disturbances (e.g. Bilyard, 1987). They also
play an important role in the chemical fluxes of the water/sediment interface (Aller & Aller,
1998; Aller et al., 2001) and are one of the main compartments of aquatic food webs, being
effective indicators of impacts at higher levels of biological organization (Bilyard, 1987; Alden
et al., 1997).
In spite of all the advantages mentioned above some biological characteristics of
benthic communities have to be taken into account when interpreting results of benthic
condition assessment. Benthic communities show high spatial heterogeneity in estuaries that
are related to the influence of natural gradients of different factors contributing to the
overall distribution of species. Many benthic species occur along a wide spectrum of an
estuarine environment while some others are confined to a narrower habitat, according to
their tolerance to environmental variables such as salinity, sediment type, depth, etc. In
addition to spatial patterns, temperate estuarine invertebrate communities also show
important temporal variations related to seasonal and interannual changes. Seasonal
fluctuations in abundance and composition can be due to recruitment pulses that occur during
spring and autumn for most species, but also to the occurrence of extreme environmental
conditions such as low temperatures, floods and droughts (Alden et al., 1997; Attrill & Power,
2000; Salen-Picard & Arlhac, 2002). Freshwater flow variability is one of the main factors
influencing the high temporal and spatial changes in physical, chemical and biological
conditions in estuaries, particularly in rivers that show strong seasonal changes (Kimmerer,
2002). These hydrodynamic fluctuations have an important effect on the erosion and
depositional cycles, influencing the sediment composition and therefore the colonization by
particular benthic communities. In addition, widely varying salinity patterns in an estuary will
alter local benthic community composition due to seasonal flow patterns (Boesch, 1977b) or
extreme episodic storm events (Boesch et al., 1976a, b).
38
Seasonal and spatial patterns
Chapter 2
The Mondego River estuary, located in the western Atlantic Portuguese coast is
divided into two branches that diverge 7.5 km upstream from the river mouth and have
different hydrographic characteristics (Figure 2.1). In the southern branch the water
circulation is mainly driven by tidal excursion and the only freshwater input comes from the
Pranto River, a small tributary. The northern branch receives most of the freshwater input
and is strongly influenced by seasonal water flow fluctuations (Flindt et al., 1997). These two
branches were originally in contact through a small channel in the upstream area but the
southern branch became gradually silted up and the connection occurs only during strong
spring tides (Cunha & Dinis, 2002). The southern branch subsystem has been widely studied
concerning physical and chemical variables that influence ecological processes. These studies
identified an eutrophication gradient as one of the main factors influencing benthic
communities (Flindt et al., 1997; Marques et al., 1997; Lillebø et al., 1999; Martins et al.,
2001; Cardoso et al., 2002). In contrast few studies have been carried out in subtidal
communities of the northern branch (Marques et al., 1993; Pardal et al., 1993) and they did
not cover the region upstream of the link between the southern and northern branches.
POPR
ORT
TUUGG
AL
A
Atlantic Ocean
L
FRANCE
FRANCE
SPAIN
SPAIN
Figueira da Foz
1
2
3
Montemor-o-Novo
4
7
5
6
2 Km
Figure 2.1. Location of sampling stations selected in the northern branch of the Mondego
River estuary.
Understanding the spatial and temporal variations of the benthic communities is a
basic tool for discriminating between pollution induced changes and natural variations
(Boesch, 1973; Holland et al., 1987) and the first step towards the development of
environmental indicator tools for Portuguese estuaries. Assessment of the benthic condition
39
of the northern branch of the Mondego River estuary can give a reasonable representation of
both natural and man-made impacts in the entire river basin since it receives most of the
freshwater generated upstream. This paper gives an overview of the spatial distribution of
benthic communities in the northern branch of the Mondego River estuary, identifying the
main environmental gradient generating the distribution of those communities. Seasonal
changes were also analyzed by examining variations in the dominant species. These findings
emphasize the ecological importance of the poorly understood biotic differences between
homiohaline and poikilohaline estuaries.
METHODS
Study area
The Mondego River estuary is located on the Portuguese Atlantic coast (40º08’ N;
8º50’ W), a temperate-warm region influenced both by Atlantic and Mediterranean climates
(Figure 2.1). This region is characterized by a rainfall period that extends from November to
May and a drought period of very low water flow between June and October (Loureiro et al.,
1986). River flow data for the period between 1987 and 1997 measured at the Coimbra dam
indicated an annual mean flow of 812 m3 s−1. Maximum flows were measured from December
to March and minimum flows occurred between June and October (Figure 2.2). Average
monthly flows varied between a maximum value of 167 m3 s−1 in January and a minimum
average flow of 15 m3 s−1 in September. The Mondego River flow regime is very irregular and
important daily changes can occur due to the action of dams controlling the discharges. This
estuary is affected by a mesotidal semi-diurnal regime and is normally totally mixed, except
for periods of extreme floods or droughts when it can be only partially mixed (Cunha & Dinis,
2002). During the last decades the Mondego River estuary was severely altered by the
construction of dams located upstream, the drainage of some mudflat areas, embankment of
the river margins, dredging activities to maintain a navigation channel and intensive
agriculture use. Sediment grain size has a very heterogeneous spatial distribution along the
estuary, much coarser in the upstream areas where it consists mainly of very coarse sand and
some marginal locations covered with fine sand. The lower section has a dominant
composition of medium to fine sand although there are small areas near the river banks were
sandy mud sedimentation occurs (Cunha & Dinis, 2002).
40
Seasonal and spatial patterns
Chapter 2
Sampling design
A total of seven sampling stations were selected along the longitudinal extension of
the northern branch of the estuary (Figure 2.1) in an attempt to cover the salinity range
between the vicinity of the river mouth and the upper tidal reaches. Three benthic
invertebrate samples were taken at each station using a modified van Veen grab (0.05 m2)
and their contents were fixed and preserved with 4% buffered formalin. Grab contents were
sieved in the laboratory using a 500 µm mesh and preserved in 70% alcohol. All samples were
sorted using a microscope and invertebrates were identified to the highest possible taxonomic
separation. Bottom dissolved oxygen (DO) (mg l−1), water temperature (ºC) and salinity were
measured in situ using a Data Sonde Surveyor 4 and a Sechii disc was used to measure
transparency (m). Additional water samples were collected and frozen for subsequent analysis
of nitrates (mg l−1), nitrites (mg l−1), phosphates (mg l−1) and ammonia (mg l−1). The analyses
were made by the laboratory of the Portuguese Environmental Institute using methods
certified by the Portuguese Quality Institute. At each station, another grab sample was taken
and frozen for sediment grain size, total organic content (TOC) and heavy metals analysis.
Sediment grain size composition was determined using an AFNOR type sieve battery (0.063
mm; 0.25 mm; 0.5 mm; 2 mm; 9.25 mm) after drying the sediment (60ºC) for a period of
48 h. Samples were classified using the Roux (1964) scale. TOC was obtained as the difference
between dry weight, measured after drying the sample at 60ºC during 24 h and ash weight,
obtained after ignition at 480ºC for a period of 12 h. Heavy metal concentrations (mg kg−1) in
the sediment (arsenic, chromium, lead, cooper and zinc) were also determined by the
Portuguese Environmental Institute, using certified methods.
Flow (m3.s-1)
750
500
250
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Months
Figure 2.2. Average month flows measured at Coimbra dam between 1987 and 1997
(source: Portuguese Water Institute).
41
Seasonal variations were assessed by repeating the surveys every 3 months, namely in
July (summer) and October 2000 (autumn) and in February/ March (winter) and June (spring)
2001. All samples were collected on low tide, during spring tide periods. The winter cruise
took place immediately after a flood event and Stations 1 and 7 could not be sampled due to
the strong currents impeding the use of the collecting devices.
Data analysis
Spatial patterns
Stations were classified into spatial groups using the ‘‘mean variance per
comparison’’ technique described by Williams & Stephenson (1973). By applying this
technique it was possible to group stations into spatial groups independent of the effects
associated with collections conducted during different seasons. The technique estimates the
variance between stations and between sampling events by calculating the Euclidean distance
between stations and sampling events (over all species) after stations and sampling events
were centred to their respective means. The variance estimates were used as a measure of
dissimilarity between stations for cluster analyses in order to assign the spatial groups. A
flexible sorting strategy was used for the cluster analysis with an intensity coefficient or
value of –0.25 (Boesch, 1977a). Dissimilarity coefficients were calculated using a program
written in the SAS/IML® matrix programming language while the dendrograms for this analysis
were produced using PROC CLUSTER of the SAS/Stat® software package. All species counts
were standardized to have an overall mean value of zero and a standard deviation of one
prior to conducting this analysis. The analysis was conducted using data collected during only
three seasons (summer, autumn and spring) due to the missing observations in winter. An
overall test for a significant difference in species composition between site groups was
accomplished using a MANOVA (Wilk’s λ) while pairwise comparisons between individual site
groups were made using an F-test on pairwise squared Mahalanobis distances. Descriptive
measures determined for the benthic communities of each group identified by the cluster
analysis were the average density, the Shannon-Wiener diversity index (H’ loge), the number
of species (considering each taxon as a species), the Simpson’s dominance index (λ') and the
top 10 dominant species. Similarity percentage breakdown procedure (SIMPER) (Clarke &
Warwick, 1994), included in the PRIMER software package was used to determine the
contribution of individual taxa towards the dissimilarity between and similarity within the
groups identified by Cluster analysis.
42
Seasonal and spatial patterns
Chapter 2
Seasonal variation
Multivariate ordination techniques were applied to analyze spatio-temporal variation
in the species density reduced data set and identify the relations between environmental and
biological data, using CANOCO 4.5 software. Relations between environmental and biological
data were analyzed by performing a Canonical Correspondence Analysis (CCA). CCA constrains
the axes to be linear combinations of the environmental variables (ter Braak & Šmilauer,
2002).
The species data matrix was reduced by eliminating taxa that occurred in less than
five samples and accounted for less than 0.1% of the total abundance, to obtain an
interpretable ordination diagram. A matrix of explanatory variables was also constructed to
determine the variation in the species data that was related to environmental factors. The
reduced environmental matrix excluded variables that showed collinearity (silt and clay) and
variables which registered values under the detection limit (nitrates, nitrites, phosphates and
ammonia). Metals were also excluded because they never exceeded Long et al.’s (1995)
effects range-median (ERM) or Crommentuijn et al.’s (2000) maximum permissible
concentrations (MPC) and any differences found between stations would not have a
biologically meaningful interpretation. All other variables measured were included, namely
dissolved oxygen, water temperature, salinity, transparency, depth, sediment type (stones,
coarse sand, medium sand, fine sand) and total organic content.
Selection of variables was based on stepwise multiple regressions and the statistical
significance of the variables added to the analysis was tested using a Monte Carlo permutation
test (499 unrestricted permutations) (ter Braak & Verdonschot, 1995). Decision about the
ordination model to use in the constrained analysis (CCA) was based on length of gradient
calculated by a previous Detrended Canonical Correspondence Analysis (DCCA). Since the
longest gradient was 4.05 the CCA was based on a unimodal model. DCCA was also used to
obtain the ordination of species and samples, since an ‘‘arch effect’’ was apparent in the
initial canonical correspondence analysis (CCA) (Gauch, 1982).
Seasonal variations were analyzed by plotting major taxonomic groups and ecological
groups for each station group-season combination based on he classification of Borja et al.
(2000). These authors assigned taxa to one of five ecological groups, according to their
sensitivity to an increasing stress gradient (I to V). Contributions from individual taxa to
dissimilarities between seasons were estimated using the similarity percentage breakdown
procedure (SIMPER). Densities of the dominant species were plotted for each season.
43
Results
Benthic macrofauna general characterization
A total of 38 394 invertebrate specimens were collected and 84 taxa identified
(Appendix 1). The highest densities were registered during spring at station 9 (56 613 ind m-2)
while the lowest values were observed during winter at station 4 (160 ind m-2). The 10
dominant species accounted for 93% of the total average density with the amphipod
Corophium multisetosum Stock, 1952 (47%) and the polychaete Streblospio shrubsolii
(Buchanan, 1890) (21%) being the two dominant species. The dominance of C. multisetosum
was due to the high numbers collected during spring at the three upstream stations.
S. shrubsolii was the most abundant species during all other seasons. Dominant species found
during summer and autumn were typical estuarine surface and subsurface deposit feeders
(e.g. S. shrubsolii, Spio martinensis Mesnil, 1896, Chaetozone setosa Malmgren, 1867) but
some freshwater invertebrates such as insect larvae (Ephemeroptera and Diptera) were
collected during winter and spring, mainly in the upstream stations.
Spatial patterns in benthic communities
Cluster analysis indicated three main groups of stations in the northern branch of the
Mondego River estuary (Figure 2.3). There was a significant difference in species composition
across all site groups (Wilk’s λ=0.063; DF=28:33; P<0.0001) and between each of the
individual site groups (Table 2.1). Spatial Group A consisted of stations 1 and 2, which are
located in the lower sector of the estuary. These stations are characterized by medium sand
sediments, a stronger tidal influence and a salinity decrease associated with flood events that
occur primarily during winter. This group had the lowest dissolved oxygen concentrations, as
well as higher levels for TOC, ammonia, lead, copper and zinc concentrations (Table 2.2).
This may be due to the spatial group’s proximity to the urban area of Figueira da Foz that has
harbour facilities, sewage outfalls and a large bridge with automobile traffic. Lead and zinc
concentrations exceeded Long et al.’s (1995) Effects Range-Low (ERL) at the station located
closer to the bridge during winter. The benthic community identified for this group was
dominated by some polychaete and bivalve species. The spionid polychaete S. shrubsolii
showed the higher average abundance (29%), followed by the suspension feeding bivalves
Cerastoderma glaucum (Poiret, 1789) (25%) and Scrobicularia plana (da Costa, 1778) (10%)
(Table 2.2). Group B clustered stations 3, 4 and 5, located in the middle sector of the
estuary. At this location salinity decreased during winter and spring but tidal influence
maintained relatively high salinities during the drought period. It is a transition zone for
sediment that changes gradually from medium to coarse sand moving upstream. The lower
44
Seasonal and spatial patterns
Chapter 2
average percentages of TOC were found in this spatial group (Table 2.2). The benthic
community was dominated by only two species, S. shrubsolii (48%) and the amphipod
C. multisetosum (37%) (Table 2.2). The two uppermost stations formed Group C,
characterized by lower salinities, higher oxygen levels and coarser sand. Chromium and zinc
measured at these sites exceeded Crommentuijn et al.’s (2000) Negligible Concentration (NC)
values and Long et al.’s (1995) ERL values and higher nitrates and TOC levels were also
measured, probably due to intensive agriculture use in this area. The benthic community was
strongly dominated by C. multisetosum (77%), mainly because of high numbers collected
during spring. Oligochaetes (10%) and an introduced bivalve species Corbicula fulminea
(Müller, 1774) (8%) were also abundant. Although in low numbers, insects larvae (Ephoron
virgo (Olivier, 1791) and Chironomidae) occurred in this area associated with higher winter
and spring freshwater input (Table 2.2).
All seasons
Flexible Beta Distance (β = -0.25)
2.0
1.5
1.0
0.5
0.0
1
2
Group A
3
4
Group B
5
6
7
Group C
Figure 2.3. Cluster analysis of the density data set collected in the northern branch of the
Mondego River estuary. Stations were grouped into spatial groups independent of the effects
associated with collections conducted during different seasons using the “mean variance per
comparison” method described by Williams & Stevenson (1973).
SIMPER analysis showed higher dissimilarities between Groups A and C (91%) and
higher closeness of stations of Group B to A than to C. S. shrubsolii gave the highest
45
contribution to the dissimilarities between the lower and the middle sector of the estuary
(16%), except for the spring assemblage. Although dominant in both assemblages this spionid
occurs with lower density at Group A stations. On the other hand, C. glaucum, the polychaete
S. martinensis and the gastropod Hydrobia ulvae (Pennant, 1777) were found with much
higher densities in Group A and explained 14%, 7% and 6% of the dissimilarity between Groups
A and B, respectively. The high density of C. multisetosum in the upstream stations
accounted for 27% of the dissimilarity between Groups B and C. Oligochates, S. shrubsolii and
C. fulminea were also important in separating these two groups and explained 15%, 15% and
12% of the dissimilarities between Groups B and C, respectively. Ecological groups obtained
by classifying taxa according to their sensitivity to pollution (Borja et al., 2000) were used as
a measure of the ecological structure of the assemblages showing an average density
domination of 18 taxa belonging to Group III, which includes species tolerant to organic
enrichment. Over 92% of the organisms collected during the study were classified in this
group, while only two taxa, Oligochaeta and Capitella capitata, or about 5% of the total
number of organisms were classified into Group V (Figure 2.4), considered as first-order
opportunistic species.
Table 2.1. Pairwise comparisons of species
composition between site groups. Shown are the
pairwise squared Mahalanobis distances between site
groups, the F values and their associated
probabilities.
Site Group
B
A
A
C
15.37
16.07
3.26
3.41
0.0007
0.0005
22.74
4.02
<0.0001
46
Seasonal and spatial patterns
Chapter 2
Seasonal variation in benthic communities
Major variations were found in winter assemblages that showed a reduced number of
species and extremely low abundances (Table 2.2). In contrast, higher numbers and stronger
dominance were registered during spring in all station groups with increased densities in
Group C. As previously mentioned the ecological structure of the Mondego River estuary was
numerically dominated by Group III species (Figure 2.4). However, some variations of the
specific composition occurred between seasons. Summer and autumn registered a higher
heterogeneity of the ecological groups represented in Group A, mainly because of the
occurrence of rare species of marine influence. Spatial Group C registered the highest
numerical representation of Group V during summer and winter, due to the density of
oligochaetes (Figure 2.4). Spring showed higher homogeneity due to the strong numerical
abundance of Group III species that lowered the relative contribution of other groups. SIMPER
analysis showed which species contributed the most to the seasonal variations within each
station group:
Group A – higher dissimilarities were found between winter assemblages and all other
seasons. Only four taxa were collected and with very low numbers in this period, namely
S. shrubsolii, Hesionidae, the isopod Cyathura carinata (Kroyer, 1847) and Turbellaria.
C. glaucum, S. plana, S. martinensis, Mediomastus fragilis Rasmussen, 1973 and C. setosa
were the species which best discriminated between summer and all other seasons, showing
higher densities during summer, decreasing towards winter (Figure 2.5). S. shruboslii was the
best discriminating species (>20%) between spring and other seasons due to the higher
densities found in this period (Figure 2.5). Summer was also characterized by the presence of
rare species such as Eumida sanguinea (Örsted, 1843), Glycera gigantea de Quatrefages,
1866, Nephtys cirrosa Ehlers, 1868, Nephtys hombergii Savigny, 1818 and Modiolus barbatus
(Linnaeus, 1758), that were absent during other seasons. Some other species revealed a
relatively important presence during summer and autumn but were absent from the winter
and spring assemblages such as Heteromastus filiformis (Claparède, 1864) and C. setosa.
47
Table 2.2. Descriptive biological and environmental parameters of groups of stations
identified in the Mondego River estuary (A, B and C). Maximum and minimum average values
seasonally determined (summer – S; autumn – A; winter – W; spring – Sp) are presented for
each group, concerning density, Shannon-Wiener diversity, number of species and Simpson’s
dominance. Top ten dominant species are listed with the respective contributions to total
density
Group A
Group B
Group C
(Stations 1 and 2)
(Stations 3, 4 and 5)
(Stations 6 and 7)
Biological parameters
Density
(ind m-2)
380 W - 9420 Sp
504 W - 9651 Sp
433 W - 39720 Sp
Diversity
1.00 W - 2.24 A
0.70 Sp - 1.52 W
0.63 Sp - 1.27 S/W
N Species
4 W - 40 S
14 W - 38 S
8 W - 14 Sp
0.31 S/A - 0.04 W/Sp
0.24 W - 0.67 Sp
0.34 S - 0.72 Sp
Dominance
Streblospio shrubsolii (29%)
Dominant
species
Streblospio shrubsolii (48%)
Corophium multisetosum (77%)
Cerastoderma glaucum (25%) Corophium multisetosum (37%)
Oligochaeta (10%)
Scrobicularia plana (10%)
Oligochaeta (3%)
Corbicula fulminea (8%)
Hydrobia ulvae (7%)
Spio martinensis (2%)
Ephoron virgo (2%)
Spio martinensis (6%)
Hydrobia ulvae (2%)
Nemertea (1%)
Chaetozone setosa (5%)
Nemertea (1%)
Cyathura carinata (<1%)
Mediomastus fragilis (5%)
Hediste diversicolor (1%)
Chironomidae (<1%)
Angulus tennuis (3%)
Gammarus subtypicus (1%)
Gammarus subtypicus (<1%)
Heteromastus filiformis (2%) Capitella capitata (1%)
Boccardiella ligerica (<1%)
Oligochaeta (1%)
Saduriella losadai (<1%)
Corbicula fulminea (1%)
Environmental parameters
Depth (m)
3.00 - 5.50
0.80 - 5.00
3.50 - 6.00
Salinity
7.00 - 40.20
7.00 - 31.60
2.00 – 14.20
DO (mg l )
3.40 - 9.00
6.40 - 9.50
6.40 - 9.60
NO3 (mg l-1)
-1
1.00 - 4.70
2.50 - 5.40
3.20 - 5.40
-1
< 0.05
0.05 - 0.10
0.05 - 0.07
-1
NH4 (mg l )
0.08 - 0.33
0.08 - 0.23
0.08 - 0.20
-1
As (mg kg )
1.20 - 9.00
0.90 - 4.60
1.00 - 13.00
Pb (mg kg-1)
NO2 (mg l )
2.40 - 92.00
4.00 - 28.30
2.40 - 40.00
-1
1.30 - 28.00
0.60 - 9.00
0.70 - 23.00
-1
2.40 - 59.00
5.30 - 44.00
3.00 - 70.00
-1
9.40 - 184.00
13.00 - 71.00
12.00 - 115.00
0.40 - 9.90
0.20 - 4.00
1.20 - 10.10
Medium sand
Coarse-Medium sand
Coarse sand
Cu (mg kg )
Cr (mg kg )
Zn (mg kg )
TOC (%)
Sediment
type
48
Seasonal and spatial patterns
Chapter 2
Figure 2.4. Ecological groups (Borja et al., 2000) identified seasonally for groups of
stations defined in the Mondego River estuary.
Group B – high dissimilarities between seasons were found, with the lowest
dissimilarities registered between summer and autumn assemblages (57%). S. shrubsolii gave
the highest contribution to dissimilarities between all seasons, except for spring, due to
density changes. A higher number of species was collected during autumn and summer
(Table 2.2). C. multisetosum occurred only during winter and spring (Figure 2.5) and
contributed most to the dissimilarities between these seasonal assemblages (30%).
S. martinensis, C. setosa, G. gigantea and the bivalve Angulus tenuis (da Costa, 1778)
occurred only during summer and autumn periods, showing the same pattern as Group A,
although with lower densities. Chironomidae occurred only during the winter period.
Group C – upper sector assemblages showed a higher homogeneity between seasons,
except for winter and spring (80% dissimilar) due to the contribution of C. multisetosum (60%)
that registered a strong numerical increase during spring (Figure 2.5). This species accounted
for the highest contribution to the dissimilarities between spring and other seasons (>50%).
Oligochaetes and C. fulminea were also abundant in Group C, except for the winter period
(Figure 2.5). Chironomidae occurred exclusively during winter and spring and E. virgo
occurred only during spring.
49
Figure 2.5. Seasonal variations on the densities of the eight dominant species in
the benthic community of the northern branch of the Mondego River estuary
(S – summer; A – autumn; W – winter; Sp – spring). Standard error is indicated.
50
Seasonal and spatial patterns
Chapter 2
Relationships between environmental and biological variables
After data reduction 28 taxa were retained, that accounted for more than 99% of the
total abundance.
The constrained ordination (CCA) of species density with stepwise forward selection
of environmental variables retained only three environmental variables (P<0.05): salinity,
medium sand and TOC. The ordination plot showed an apparent arch effect on species and
samples, suggesting the need for detrending. DCCA of species abundance data produced an
ordination in which the first four axes were statistically significant (P<0.01), with respective
eigenvalues of 0.66, 0.14, 0.06 and 0.03. The first two axes explained 34.9% of the total
variance in species data and 56.8% of the total variance on the species–environment relation.
Salinity presented a negative correlation with the first axis (–0.90) and it was the variable
with the highest explanatory power related to this axis (Figure 2.6). Medium sand content
also explained some of the variation on the first axis, with a correlation of –0.67. In spite of
explaining some of the variance in species distribution, TOC showed low correlations with the
first two axes (<0.30) (Figure 2.6).
Salinity and sediment grain size established the main gradient separating species that
apparently have an optimal distribution in lower salinities and coarser sands, such as
C. multisetosum, C. fulminea, E. virgo, Chironomidae, Alkmaria romijnii (Grube, 1863) and
Oligochaeta (Figure 2.6). These species were mainly identified in the Group C assemblage.
The ordination indicates a medium location of S. shrubsolii, C. carinata, Hediste diversicolor
(O.F. Müller, 1776), Saduriella losadai Holthuis, 1964, Nemertea, Lekanesphaera hookerii
(Leach, 1814) and Websterinereis glauca (Claparède, 1870) along the saline gradient. Some of
these species occurred with higher densities in Group B stations but all of them demonstrated
tolerance to changes occurring along the estuary since they showed a wide distribution along
the three different regions identified. In the DCCA plot the remaining species were located
closer to the positive end of the salinity and sediment vectors, associated with spatial Group
A stations. A small part of the species variation was still explained by the second axis (6.2%),
separating species characteristic of Groups A and C assemblages from Group B. Although the
correlation of TOC to this axis was not very high, this variable apparently explains part of the
differences mentioned, since the Group B stations registered lower values. DCCA ordination of
species and samples also revealed temporal differences in similarity within groups, separating
the plots of the same stations in different seasons (Figure 2.6).
51
Sarm
3
Wgla
Mpal
Hdiv
Chir
Sshr
Neme
Ms
Ccap
Smar
A4 S3
S4 A3
Hulv
A2
Sp2Sp1
S2 S1
Sal
Aten
Npul
0 Ncir Ggig
Hfil Spla
Mbar Cgla
Cset
Mfra
Nhom
Hesi
A1
Lhok
Sp3
Sp4
W4
W3
S7 A5 W5
A6 Sp5 S5
A7 Sp6
S6
Olig W6
Arom Cful
W2 Sp7Cmul
Ccar
TOC Slos
Esan
Evir
-2
-1
0
5
Figure 2.6. DCCA of benthic invertebrate density for the stations sampled in
the Mondego River estuary during summer (S), autumn (A), winter (W) and
spring (Sp). Taxa data were square root transformed. Environmental variables
- Salinity (Sal), Medium sand (Ms) and Total Organic Content (TOC) - were
plotted on the ordination as arrows. See Appendix 1 for taxa abbreviations.
DISCUSSION
The identification of the spatial and seasonal patterns of change in the benthic
communities of the Mondego River estuary may be an important contribution to the
development of biological criteria to assess the environmental condition of Portuguese
estuaries. The study design led to the identification of three spatial groups with distinct
environmental and biological characteristics in the northern branch of this estuary, instead of
the five classes established by the Venice system. That system, based on the identification of
salinity classes, is widely accepted and indicated by the WFD to identify different water
types. Salinity decreases moving upstream from spatial Group A near the mouth of the River
to the spatial Group C upstream and is coupled with a transition from medium to coarse sands
upstream. Several sources of anthropogenic disturbance were identified in Group A, such as a
well developed urban area with harbour facilities that require periodic dredging of the access
52
Seasonal and spatial patterns
Chapter 2
channel, dumping and a bridge with high traffic levels. This sector showed organic
enrichment and higher levels of heavy metals were measured in the bridge vicinity. Lower
organic enrichment was found in spatial Group B while the Group C stations showed higher
levels of organic matter and nutrient concentrations, probably related to nutrient loads from
intensive agriculture.
Benthic communities presented similar patterns of longitudinal change along the
estuary. The lower sector assemblages were dominated by the surface deposit feeder S.
shrubsolii and some suspension feeding (C. glaucum) and deposit-feeding (S. plana) bivalve
species. Group B showed a stronger dominance of S. shrubsolii populations, shared with the
amphipod C. multisetosum. The last species mentioned accounted for almost 80% of the
upper sector assemblages due to high densities found during spring. DCCA identified a saline
gradient influencing species distribution. Seasonal differences found in community
composition and structure, were apparently also related to salinity changes caused by high
freshwater input from upstream. Although salinity values were obtained with a single
measurement for each season, daily and monthly flows measured upstream strongly indicate
that they were representative of seasonal changes (Figure 2.2). Colonization of Group A
stations by marine species was observed during the drought season while Group C stations
were colonized by freshwater species during higher flow periods. Species with higher
tolerances to salinity changes such as S. shrubsolii, H. diversicolor, C. carinata and S. losadai
showed a wider distribution and persistence between seasons. These results are consistent
with previous studies in the Mondego River estuary (Marques et al., 1993; Pardal et al., 1993),
although the number of species and densities collected during this study were much higher.
The higher densities in the present study are probably due to the use of a 1 mm mesh sieve
during previous studies, compared to the use of a 0.5 mm mesh sieve in the present study.
Salinity effects may be acting together with physical disturbances caused by the
strong currents occurring during the rainfall period and consequent alterations of the erosion–
deposition cycles. Winter communities were very impoverished both numerically and in terms
of the number of species and stronger changes occurred in the lower sector of the estuary,
where most stenohaline species were found. In the middle sector lower salinities persisted for
a longer period and the benthic community was apparently adapted to this saline regime
showing lower changes between seasons. S. shrubsolii, a typical estuarine species dominated
the community over all seasons, except for spring when C. multisetosum increased its
density. This polychaete is classified as an opportunistic species that colonises organically
enriched sediments (Pearson & Rosenberg, 1978; Sardá & Martin, 1993). This change in the
dominance may be due to competition as both species occupy similar spatial niches (surface
feeders dwelling in the upper 1 cm of the sediment) and occur in high densities. Previous
studies carried on Portuguese estuaries showed the prevalence of this amphipod in salinities
53
ranging from 2.5 to 10 and coarser sediment (Queiroga, 1990). Cunha et al. (2000) concluded
that C. multisetosum abundance may be associated with increased freshwater inflow
following rainy periods and subsequent decreasing abundance with the higher summer
temperatures, since it is a cold-temperature species, with its southern limit in Portugal.
During spring, C. multisetosum seems to replace the dominant spionid S. shrubsolii in Group
B, since increasing densities occur in the lower sector for this species in the same period. The
benthic community of the upper sector seems to be more stable with lower fluctuations in
specific composition and densities, except for the spring boom of C. multisetosum.
The AZTI Marine Biotic Index (AMBI) approach of Borja et al. (2000) produces an
overall evaluation of benthic community condition, relative to anthropogenic stress, by
scoring benthic species based upon relative tolerance to pollution. Using this approach the
Mondego River estuary would be considered moderately disturbed since Group III species are
dominant. These species are tolerant to excess organic matter and occur in normal conditions
but increase their numbers when stimulated by organic enrichment. Based on AMBI values,
winter communities in the upper sector would be considered severely degraded due to the
dominance of oligochaetes and summer and autumn communities in Group A would be less
disturbed since a higher number of pollution sensitive species occur (e.g. A. tenuis,
Nephtys spp., Glycera spp., Owenia fusiformis Delle Chiaje, 1842, Eteone picta de
Quatrefages, 1866, E. sanguinea, Diopatra neapolitana Delle Chiaje, 1841). Pollution sensitive
species did occur in all sectors but generally in low densities and with great variation
between seasons. These results suggest caution in applying and interpreting the AMBI
approach when strong seasonal patterns occur. Nevertheless, benthic communities are still
under seasonal physical and physiological stress that favours the settlement of species with
opportunistic life histories and/or wide tolerance to changes in environmental conditions,
such as S. shrubsolii (Sardá & Martin, 1993; Rossi & Lardicci, 2002). The present data
demonstrate the ability of this species to colonize and produce high-density local populations
in the lower sector of the Mondego River between winter and spring. Lardicci et al. (1997)
indicated peaks of fecundity occurring every 2 months for this species when food availability
is not a limiting factor.
Estuaries may be classified in many ways including geomorphology (e.g. drowned river
valleys, fjords, etc.), degree of saline stratification (e.g. highly stratified, partially stratified,
etc.), and tidal mixing (e.g., macrotidal, microtidal, etc.) (Lauff, 1967; Elliott & McLusky,
2002). Major variations in amount of freshwater flow may be due to strong seasonal
differences in rainfall and such differences can be amplified by dam placement. Boesch
(1977b) states that poikilohaline estuaries, where strong seasonal changes in salinity and
water flow occur at specific locations, cannot be assessed using the Venice system. He also
states that euryhaline marine species are displaced as an effect of poikilohalinity, allowing
54
Seasonal and spatial patterns
Chapter 2
the domination of estuarine endemic species. The dominance of S. shrubsolii in Group B
during summer and autumn and in Group A during winter and spring indicates an agreement
of the Mondego River estuary results with poikilohalinity effects theory. Apparently, stronger
freshwater inputs displace euryhaline species found in the lower sector of the estuary during
lower flow periods, allowing the dominance of the spionid S. shrubsolii. At the same time,
this estuarine endemic species is displaced from the middle sector by freshwater species such
as the amphipod C. multisetosum. The Mondego River estuary, a poikilohaline type estuary,
characterized by strong seasonal changes in water flow and salinity, cannot be consistently
stratified into salinity regions based upon the Venice classification system as indicated by the
WFD. Biotic communities, exemplified here by the benthic communities, are seasonally
displaced, compared to a homiohaline-type estuary where the Venice system can be applied
without modification. Future identification of reference conditions and design of monitoring
programs cannot be accomplished without understanding how interactions between biotic and
physical-chemical dynamics differ between homiohaline and poikilohaline estuaries (Elliott &
McLusky, 2002). Our results indicate that seasonal and spatial stratification may be necessary
to be able to separate natural and anthropogenic stresses. In addition, further research is
necessary in understanding the relative roles of river flow versus groundwater as sources of
pollutants. For example, during low river flow seasons, groundwater flow may become
relatively much more important than during times of high river flow. Understanding ecological
patterns, particularly where spatial and/or temporal variation, is great, also requires a
comprehensive
appreciation
of
the
interactions
of
geomorphology,
hydrology,
and
climatology.
ACKNOWLEDGMENTS
This study was financially supported by two Ph.D. fellowships (SFRH/BD/5144/2001
and SFRH/ BD/6365/2001) granted by FCT (Science and Technology Foundation) and ESF in
the aim of the III European Community Support Framework. Financial support was also given
to a project sponsored by Instituto de Ambiente. The SAS/IML program used here was written
by Dr. Raymond W. Alden III of the University of Nevada, Las Vegas. We would also like to
thank Professors Jean-Claude Dauvin and João Castro for the help with the identification of
some invertebrate species. Finally, we thank Gilda Silva and Nuno Prista for their valuable
comments and contributions to the final draft of this manuscript.
55
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59
Chapter 3
Taxonomic sufficiency
Chainho, P., Lane, M.F., Chaves, M.L., Costa, J.L., Costa, M.J. & Dauer, D.M. 2006.
Taxonomic sufficiency as a useful tool for typology in a poikilohaline estuary.
Hydrobiologia 587: 63-78.
Taxonomic sufficiency
Chapter 3
Taxonomic sufficiency as a useful tool for typology in a
poikilohaline estuary
ABSTRACT
Taxonomic sufficiency has been used mainly to assess benthic condition, based on the
assumption that taxa can be identified to a taxonomic level higher than the species level
without losing the ability to detect changes related to pollution stress. Identifying taxa to a
higher level reduces the expertise and time needed to identify organisms and consequently
allows increased spatial and temporal replication. The usefulness of taxonomic sufficiency for
typology (identification of water body types) was examined using the benthic communities of
the Mondego River estuary (Portugal). Benthic samples were collected seasonally along the
Northern branch of the Mondego River estuary from July 2000 to June 2001 and several
environmental parameters were measured simultaneously. Cluster analysis of species data
indicated three major ecological groups, mainly related to a saline gradient along the
estuary. The same groups were found when taxa were aggregated to higher taxonomic levels
(genus, family, order, class), except for the phylum level. The overall spatial pattern was
driven by: (1) the dominance of bivalves and the occurrence of rare marine species in the
Lower Estuary; (2) the dominance of polychaetes in the Middle Estuary; (3) and the
dominance of arthropods in the Upper Estuary. The ability of different taxocenes to
discriminate the three ecological groups was also examined. Mollusca and Bivalvia were the
only taxocenes producing the same groupings, although other taxocenes (Annelida,
Polychaeta, Spionidae, and Arthropoda) showed a significant ability to discriminate between
all three groups. Compared to using all taxa identified to the lowest possible taxonomic level,
our results indicate that for typology (1) several higher taxonomic levels were sufficient (2)
while few taxocenes alone were sufficient.
KEY WORDS: typology, Water Framework Directive, Venice system, salinity gradient,
taxonomic levels, taxocenes.
63
INTRODUCTION
The concept of taxonomic sufficiency, first introduced by Ellis (1985), refers to
taxonomic identification to the highest possible level that retains taxonomic accuracy and
sufficient biological information to assess environmental stress effects. Since then, several
authors examined the effects of reducing the taxonomic resolution, mainly concerning
environmental impact assessment and monitoring studies (Warwick, 1988; Baldó et al., 1999;
Gomez Gesteira et al., 2003; Terlizzi et al., 2003), but also in studies of biodiversity and
conservation (Bianchi & Morri, 2000).
The cost effectiveness of monitoring programs using benthic communities has been
presented as a major reason for using taxonomic sufficiency since it provides a significant
reduction in costs due to high taxonomic identification expertise (Ferraro & Cole, 1995;
Pagola-Carte et al., 2002). Moreover, some biological considerations have been proposed to
support taxonomic sufficiency, mainly the assumption that biological responses to stress
comply with a hierarchical structure. Species are the most sensitive taxa but as the level of
stress increases the adaptability of lower taxonomic levels is exceeded (first individual, than
species, genus, etc.). Therefore, impacts resulting from increasing levels of stress are shown
at higher levels of taxonomic organization, reducing the taxonomic resolution needed to
identify their effects in benthic communities (Ferraro & Cole, 1990). Additional support to
taxonomic aggregation is given by the frequent level of redundancy of biological data, which
allows the same inference to be drawn at different levels of taxonomic identification (Ferraro
& Cole, 1992, 1995).
Regardless of the advantages, taxonomic sufficiency has been also a controversial
topic among the scientific community, particularly because it might generate losses of
ecological information (Maurer, 2000), for example by incorporating both monotypic and
polytypic taxa to the same level (May, 1990). Olsgard et al. (1998) also emphasized that the
assumption underlying most assessment studies, namely that faunal patterns are a function of
changes in environmental conditions may not be true at higher taxonomic levels. Inherent in
these arguments is the understanding that higher taxonomic levels cannot be used as
surrogates of species diversity without having a previous knowledge of each system. The
usefulness of this method also depends on the objective of the study, locations chosen,
variables measured, analytical procedures and sample size (Ferraro & Cole, 1990).
Although several monitoring studies indicate little loss of information when using
higher taxonomic levels to assess marine benthic communities (Dauvin et al., 2003), only a
single study has examined estuarine benthic communities (De Biasi et al., 2003). The
European Water Framework Directive (WFD) (2000/60/EC) defines achieving good water
64
Taxonomic sufficiency
Chapter 3
quality status of all European water bodies by 2015 as a major goal, requiring the
development of adequate assessment tools, based on the identification of surface water
types, the definition of type-specific reference conditions, and the classification of all water
bodies within five ecological quality classes.
The exercise of typology aims to separate water bodies into different type units,
based on their physical and biological characteristics, assuring that physical typology is as
simple as possible but ecologically relevant (Vincent et al., 2002). As a first step, water
bodies are assigned to a surface water category, namely rivers, lakes, transitional waters,
coastal waters or artificial water bodies. These categories are further divided into types using
the obligatory factors of latitude, longitude, tidal range and salinity to define transitional and
coastal water types. The WFD indicates that the Venice system salinity classes (Anonymous,
1959) should be used for typology. Optional factors that are more appropriate to the
ecological characteristics of each region (e.g. depth, current velocity, mean substratum
composition) should also be used if the ecological separation cannot be achieved only with
the obligatory factors (Vincent et al., 2002). Using the WFD typological criteria in a
poikilohaline estuary is a challenge since salinity is highly variable, making the use of the
Venice system questionable. The aim of the present study was to test taxonomic sufficiency
for typology in a poikilohaline estuary, using the benthic communities of the Mondego River
estuary, given that previous studies focused mainly on the assessment of the benthic
condition. Because benthic communities of most European estuaries are poorly known, a
substantial effort is necessary to define meaningful water types; therefore, taxonomic
sufficiency could be a useful tool to reduce the identification effort and thereby allow an
increase in the sampling effort.
METHODS
Study area
The Mondego River estuary is located in the western coast of Portugal (40º08’ N;
8º50’ W) and it can be considered a poikilohaline estuary with high seasonal changes in
freshwater flows and salinity, as well as daily changes related to tides (Chainho et al., 2006).
The Mondego River estuary is divided into two branches with different hydrographic
characteristics, namely higher freshwater discharges in the northern branch and a strong tidal
influence in the southern branch. According to the criteria of the WFD this estuary is included
in the Atlantic/North Sea eco-region complex, is fully to partially mixed (during periods of
strong floods or droughts), mesotidal (2–4 m), with a residence time of two days in the
65
northern branch and nine days in the southern branch (Flindt et al., 1997) and with intertidal
areas significantly reduced by channelization, particularly in the northern branch.
Sampling
A total of seven sampling stations were selected along the saline gradient of the
northern branch of the Mondego River estuary (Figure 3.1). Three benthic invertebrate
samples were taken at each station using a modified van Veen grab (0.05 m2). Grab contents
were fixed and preserved with 4% buffered formalin, sieved using a 500 µm mesh and
preserved in 70% ethanol. All samples were sorted and identified to the lowest possible
taxonomic level. Several environmental variables were measured including water depth,
bottom dissolved oxygen, water temperature, transparency and nutrients concentration, as
well some sediment variables such as sediment grain size and total organic content. The
methods used to determine these parameters are detailed in a previous study of Chainho et
al. (2006). Sampling surveys were conducted nearly every three months, specifically in July
(summer) and October 2000 (autumn), February/March (winter) and June (spring) 2001, in
order to assess seasonal variations. The winter cruise took place immediately after a flood
event and stations 1 and 7 could not be sampled at that time due to strong currents. Further
details are described in the methods section in Chainho et al. (2006).
POPR
ORT
TUUGG
AL
A
Atlantic Ocean
L
FRANCE
FRANCE
SPAIN
SPAIN
Figueira da Foz
1
2
3
Montemor-o-Novo
4
7
5
6
2 Km
Figure 3.1. Location of sampling stations in the northern branch in the Mondego River estuary,
Portugal.
66
Taxonomic sufficiency
Chapter 3
Data analysis
General characterization
The redundancy of biological data was examined by determining the percentage of
monotypic and polytypic taxa (i.e. genus, family, order, class and phylum) at each sampling
station. A rank correlation coefficient (Spearman) was used to measure relationships between
the species data and higher taxonomic levels using the RELATE routine of the PRIMER 5.0
software package (Clarke & Warwick, 1994). Taxa were aggregated to different taxonomic
levels for each sampling station and their respective similarity matrices were calculated using
Bray–Curtis similarities on log transformed data. Pairwise comparisons were made between
the species similarity matrix and all the others and rank correlation values (ρ) were
calculated for each comparison. When ρ=1, a perfect match between similarity matrices is
obtained whereas when ρ=0 matrices do not have any relation (Clarke & Gorley, 2001). A
Monte Carlo permutation test (999 permutations) was used to test the significance of the
correlation coefficients (P<0.01). These coefficients (ρ) were further used as similarity
measures in a triangular matrix of q values calculated between all pairs of data sets and a
cluster analysis was conducted to group different taxonomic levels using group average
linking.
Typology
Different water body types were identified in the Mondego River estuary based on the
salinity classes (Venice system) and compared to the ecological groups identified using the
benthic community data. Spatial groups of stations based on the abundance of benthic
invertebrates were identified using the ‘‘mean variance per comparison’’ technique described
by Williams & Stephenson (1973). By applying this technique it was possible to group stations
into spatial groups independent of the effects associated with collections conducted during
different seasons. The technique estimates the variance between stations and between
sampling events by calculating the Euclidean distance between stations and sampling events
(over all species) after stations and sampling events were centered to their respective means.
These variance estimates (the centered Euclidean distances) were used as a measure of
dissimilarity between stations for cluster analyses to define the spatial groups. A flexible
sorting strategy was used for the cluster analysis with an intensity coefficient or value of –
0.25 (Boesch, 1977a). Dissimilarity coefficients were calculated using a program written in
the SAS/IML® matrix programming language while the dendrograms for this analysis were
produced using PROC CLUSTER of the SAS/Stat® software package. All species counts were
standardized to have an overall mean value of zero and a standard deviation of one prior to
conducting this analysis. The analysis was performed using data collected during only three
67
seasons (summer, autumn and spring) due to the missing observations in winter. The average
density, the Shannon-Wiener diversity index (H’ loge), the total number of taxa, the number
of taxa included in major taxonomic groups and the six most abundant species (dominants)
were used as descriptive measures of the benthic communities of each group identified by the
cluster analysis.
Multivariate analysis of variance (MANOVA) was used to test for significant overall
differences in centroids (Huberty, 1994; Johnson & Wichern, 1998), between the ecological
groups identified. The statistical test used for the MANOVAs was Wilk’s λ (Huberty, 1994)
which were conducted using SAS software’s MANOVA procedure. If a MANOVA was significant,
pairwise Wilk’s λ were conducted between ecological groups.
In order to examine the influence of seasonality stations were also classified into
spatial groups for each seasonal data set independently using Bray–Curtis similarities on
square root transformed data. Similarity coefficients were used to produce hierarchical
cluster dendrograms, using group average linking.
Descriptive discriminant analysis was used to determine if there was a significant
separation between ecological groups and to describe which taxa showed the best
discriminant ability. Discriminant analysis uses a set of response variables, in this case counts
of individual taxa, to create linear composites or linear discriminant functions (LDFs) of these
variables that describe separation between groups (Huberty, 1994). Two-dimensional plots
showing group centroids and their associated 95% confidence ellipses for the LDFs developed
were produced to identify specific taxa that were important in separating the groups. LDF
axes were labeled using the names of those taxa with a significant ANOVA between ecological
groups and with a high between-group structure r value (≥|0.80|). Order of the taxa along
the axes was based on the magnitude of the between group structure r values (loadings). A
multivariate strength-of-association index (1–Wilk’s λ) (Huberty, 1994) was used to determine
the relative distances between groups of stations. Only taxa with more than a single count
were used in the analyses and all analyses were conducted using log transformed data. A P
value of 0.05 was used as the statistical test criterion for all discriminant analyses which were
conducted using SAS© software’s CANDISC procedure.
Taxonomic sufficiency
New data matrices were produced by aggregating species data to higher taxonomic
levels and into different taxocenes, as listed in Table 3.1. Taxocenes were chosen because of
their general dominance of temperate estuarine macrobenthic communities.
The experimental design applied in this study aimed to determine if there were
significant differences between pre-established ecological groups using all available taxa and
68
Taxonomic sufficiency
Chapter 3
to identify which, if any, taxonomic levels and taxocenes provided sufficient information to
generate the same groups with significant differences. Therefore, all analyses conducted for
the species data set were also performed for each taxonomic level and taxocene, namely
cluster analysis using the mean variance per comparison approach, MANOVA and descriptive
discriminant analysis. Only taxonomic levels and taxocenes that produced the same clusters
and revealed significant differences between centroids were considered adequate for
typology in the Mondego River estuary.
Table 3.1. Levels of aggregation used for taxonomic levels and taxocenes and
number of taxa included in each level
Taxonomic levels
Taxocenes
Species
85
Annelida
43
Genus
76
Polychaeta
39
Isopoda
4
Family
63
Spionidae
7
Insecta
6
Order
36
Oligochaeta
4
Mollusca
9
Class
9
Arthropoda
28
Bivalvia
6
Phylum
6
Amphipoda
9
Gastropoda
2
RESULTS
General characterization
A total of 39 835 specimens were collected in the northern branch of the Mondego
River estuary and 85 different taxa were identified, comprising 76 genera, 63 families, 36
orders, 9 classes and 6 phyla (Table 3.1). Cluster analysis of the correlation coefficients
between matrices of similarity obtained for different taxonomic levels showed very high
correlations between the species matrix and those obtained using genus, family and order
levels (ρ>0.90; P<0.001). Correlation between species level and class level matrices was
lower (ρ=0.80; P<0.001), as well as with the phylum matrix (ρ=0.57; P<0.001) (Figure 3.2 a).
Over 80% of the genera identified were monotypic, as well as 74% of families and 58% of
orders. On the other hand over 50% of classes and phyla included more than 3 species (Figure
3.2b).
Annelids included the highest number of species (43) (Table 3.1) and accounted for
38% of the total abundance, due to the major contribution of the polychaete Streblospio
shrubsolii (Buchanan, 1890) (22%). The amphipod Corophium multisetosum Stock, 1952 was
the dominant species, accounting for 40% of the total abundance.
69
a)
80
Correlations with
species data
Genus
Family
Order
Class
Phylum
85
(ρ=0.996)
(ρ=0.963)
(ρ=0.939)
(ρ=0.804)
(ρ=0.568)
90
95
100
Species
Genus
Family
Order
Class
Phylum
b)
Figure 3.2. Taxonomic similarity. a) Cluster analysis of the similarity between
different taxonomic levels, obtained by group average linking. A rank
correlation coefficient (Spearman) was used to compare similarity matrices
(Bray-Curtis on square root transformed data) obtained for species and other
taxonomic levels and the coefficients of pairwise tests (ρ) were used as
similarity measures in the cluster analysis (P<0.01). b) Number of species (%)
included in each level of taxonomic aggregation (n.i. non identified to the
species level).
Typology
Cluster analyses extracting seasonal effects, using species level abundance data,
identified three major ecological groups in the Mondego River estuary (Figure 3.3) and there
was a significant difference between the groups (MANOVA, F=8.15; P<0.001). Pairwise Wilk’s
λ tests also indicated significant differences between all ecological groups (P<0.05).
70
Taxonomic sufficiency
Chapter 3
Flexible Beta Distance (β = -0.25)
a)
All seasons
2.0
1.5
1.0
0.5
0.0
1
2
3
4
5
6
7
b)
Figure 3.3. Taxonomic composition of the three spatial groups identified in the
Mondego River. a) Similarity dendrogram of stations when seasonal effects are
removed using the “mean variance per comparison”, applied to Euclidean
distances, using a flexible beta distance, method described by Williams &
Stevenson (1973) (from Chainho et al., 2006). b) Percent composition of major
taxonomic groups in each of the seven stations. Salinity classes of the Venice
system corresponding to the mean annual salinity in each station are indicated
below clusters (see legend of Figure 3.4).
The Lower Estuary community type included stations 1 and 2 and was characterized by
a numerical dominance in density of polychaetes (52%) and bivalves (41%), showing the
highest number of taxa and diversity (Figure 3.3, Table 3.2). These stations had sediments
consisting mainly of medium sand (Table 3.2). Stations 3, 4 and 5 were identified as the
Middle Estuary community type dominated in density by polychaete species (53%), mainly
S. shrubsolii and characterized by medium to coarse sand sediments. The amphipod
C. multisetosum was also dominant (36%) due to the high numbers registered during spring.
The Upper Estuary community type (stations 6 and 7) was largely dominated in density by
amphipods (80%) and consisted mainly of coarse sediment (Figure 3.3, Table 3.2). Considering
71
the average annual salinity values there is an overlap of salinity classes and of the ecological
groups identified. Only 16 taxa occurred across all ecological regions half of which were
annelids.
Table 3.2. Biological and environmental descriptive parameters of the regions identified in
the Mondego River estuary. Maximum, minimum and average density values (ind m-2)
seasonally determined (winter – W; spring – Sp) are presented for each group. Shannon-Wiener
diversity, total number of taxa and number of taxa included in different taxocenes are
indicated for each group. Six most abundant species (dominants) are listed with their
respective contributions to total density and the indication of the Class in bold (AAmphipoda; B- Bivalvia; G- Gastropoda; I- Insecta; N- Nemertea; O- Oligochaeta; PPolychaeta). Salinity and depth (m) ranges and sediment type are also indicated. Lower
Estuary includes stations 1 and 2, Middle Estuary includes stations 3, 4 and 5 and Upper
Estuary includes stations 6 and 7. For station locations see Figure 3.1.
Lower estuary
Middle estuary
Upper estuary
(380 W) 7 162 (9 497 Sp)
(651 W) 5 761 (9 702 Sp)
(453 W) 14 927 (39 550 Sp)
1.6 ± 0.7
1.1 ± 0.5
0.9 ± 0.3
N Taxa
60
57
21
Polychaetes
32
21
5
Oligochaetes
3
4
4
Amphipods
4
7
2
Isopods
4
4
3
Insects
0
4
3
Gastropods
2
1
1
Bivalves
6
5
1
Other
Groups
9
10
2
Mean
Density
Diversity
Streblospio shrubsolii (30%)P Streblospio shrubsolii (47%)P
Corophium multisetosum (78%)A
Cerastoderma glaucum (25%)B Corophium multisetosum (36%)A Corbicula fulminea (8%)B
Dominant
Species
Scrobicularia plana (10%)B
Spio martinensis (2%)P
Tubificoides sp. (4%)O
Hydrobia ulvae (6%)G
Hydrobia ulvae (2%)G
Nais sp. (4%)O
Spio martinensis (6%)P
Tubificoides sp. (1%)O
Echytraeus sp. (2%)O
Chaetozone setosa (5%)P
Tetrastemmatidae (1%)N
Ephoron virgo (2%)I
Depth
3.0 - 5.5
0.8 - 5.0
3.5 - 6.0
Salinity
7.0 – 40.0
7.0 - 31.6
2.0 - 14.2
Medium sand
Coarse-Medium sand
Coarse sand
Sediment
type
Strong seasonal changes were observed in the Mondego River estuary benthic
communities, with the lowest number of species and abundances found during winter and the
72
Taxonomic sufficiency
Chapter 3
highest abundance observed during spring, associated with salinity changes along seasons
(Table 3.2). Cluster analysis of seasonal data showed that three major ecological groups were
again obtained with different similarity levels for different sampling events (Figure 3.4).
Stations 1 and 2, located in the Lower Estuary always grouped together, except for winter
when station 1 could not be sampled (Figure 3.4). Stations 3 and 4 were always included in
the same group, as well as stations 6 and 7 but station 5 switched between groups over
sampling periods (Figure 3.4).
Summer and autumn assemblages showed a higher similarity between the Lower and
Middle Estuary benthic communities with salinity ranging from euryhaline to mesohaline
(Figure 3.4). Winter and spring assemblages showed a higher level of separation between
different ecological groups and included station 5 in the Upper Estuary, due high abundances
of the amphipod C. multisetosum. Salinity values were much lower during these seasons,
especially during winter when all stations were classified as oligohaline, except for the Lower
Estuary that was mesohaline. Discriminant analysis showed significant separation of the Lower
Estuary group along the first LDF (λ1=111.2; F=8.15; P<0.001) (Figure 3.5a). Separation along
this axis was due mainly to the occurrence of rare species of polychaetes with marine affinity
(r>0.99) such as Diopatra neapolitana Delle Chiaje, 1841, Eteone picta de Quatrefages, 1866,
Eumida sanguinea (Örsted, 1843) and Pectinaria koreni (Malmgren, 1866) in the Lower estuary
and to a lesser extent to higher abundances of some common species in this group of stations,
namely the bivalves Cerastoderma glaucum (Poiret, 1789), Scrobicularia plana (da Costa,
1778) and Angulus tenuis (da Costa, 1778) and the polychaetes Heteromastus filiformis
(Claparède, 1864), Owenia fusiformis Delle Chiaje, 1842, Mediomastus fragilis Rasmussen,
1973 and Spio martinensis Mesnil, 1896. The Middle and Upper Estuary overlapped along the
first LDF but were significantly separated along the second LDF (λ2=12.7; F=2.97; P<0.05). The
polychaetes S. shrubsolii (r=–0.91), Scoloplos armiger (Müller, 1776) (r=–0.84) and Hediste
diversicolor (O.F. Müller, 1776) (r=–0.82) discriminated best the Middle Estuary while the
Upper Estuary was characterized by a highly diverse group of taxa including oligochaetes
(Tubificoides sp., Limnodrilus hoffmeisteri Claparède, 1862, Echytraeus sp. and Nais sp.),
isopods (Saduriella losadai Holthuis, 1964 and Cyathura carinata (Kroyer, 1847)), insects
(Ephoron virgo (Olivier, 1791) and Chironomidae), the bivalve Corbicula fulminea (Müller,
1774) and the amphipod C. multisetosum (Figure 3.5a).
73
80
60
40
20
0
4
4
5
5
6
6
7
7
60
40
20
0
1
1
2
2
4
3
4
Winter
3
Autumn
5
5
6
6
7
7
Figure 3.4. Cluster analysis of the abundance data of benthic invertebrates collected seasonally in the
Mondego River estuary (stations 1 and 7 were not sampled during winter). Stations were grouped into spatial
groups by group average linking and similarity measures were obtained by calculating the Bray-Curtis
coefficient using log transformed data. Salinity classes of the Venice system corresponding to measures of
salinity obtained in each station are indicated below clusters.
■>30.0 Euryhaline ■18.0/20.0-30.0 Polyhaline ■5.0/6.0-18.0/20.0 Mesohaline □0.5-5.0/6.0 Oligohaline
100
3
Spring
3
100
2
2
100
80
60
40
20
0
80
1
1
Summer
80
60
40
20
0
100
Similarity
Similarity
Similarity
Similarity
74
3.92
9.28
14.64
Lower
Estuary
20.00
D.nea, E.pic, E.san, H.fil, N.hom, O.fus, P.kor, P.cir
S.mar, M.fra, M.bar, C.set, S.pla, C.gla, A.ten,
G.gig, P.cil, N.pul, S.mar, C.cap, H.ulv, G.spi
-1.44
Middle
Estuary
Upper
Estuary
-3.60
-6.00
-1.80
0.00
1.80
3.60
5.40
1.20
Middle
Estuary
4.80
8.40
Lower
Estuary
12.00
Polydora, Glycera, Angulus, Cerastoderma, Scrobicularia,
Chaetozone, Modiolus, Mediomastus, Diopatra, Eteone,
Eumida, Heteromastus, Owenia, Pectinaria, Prionospio,
Solen, Spio, Hydrobia, Capitella, Gastrosaccus
-2.40
Upper
Estuary
b)
Echytraeidae, Orbinidae
-2.04
Upper
Estuary
0.32
Middle
Estuary
2.68
5.04
Lower
Estuary
7.40
c)
Corophiidae Capitellidae, Nephtyidae, Mysidae, Glyceridae,
Hydrobiidae, Cardiidae, Tellinidae, Scrobicularidae,
Mytilidae, Cirratullidae, Onuphidae, Oweniidae,
Pectinariidae, Phyllodocidae
-3.40
-4.40
-1.84
-0.28
1.28
2.84
4.40
Figure 3.5. Discriminant analysis of the ecological groups identified in the northern branch of the Mondego River estuary using taxonomic
levels that produced the same cluster as obtained for all species (a)species; b)genus;.c)family; d)order; e)class). Groups’ centroids and
95% confidence ellipses are plotted on the first two discriminant functions. See Appendix 1 for species abbreviations (continues).
-6.80
-3.60
-1.64
0.32
2.28
4.24
Tubi, S.los, E.vir, L.hof, Echy, Chir, C.car, C.ful,
Turb, Nais, C.mul
S.shr, S.arm, H.div
Gammarus, Saduriella, Ephoron,
Boccardiella, Limnodrilus
Scoloplos, Hediste, Streblospio
6.20
Taxonomic sufficiency
Chapter 3
75
Isopoda, Tubificina
Amphipoda
-3.40
-3.20
-1.44
Middle
Estuary
1.72
3.36
5.00
Capitellida, Mysidacea, Mesogastropoda,
Cardioidea, Cirratullida, Mytiloidea, Oweniida,
Phyllodocida, Solenoidea, Eunicida
-0.08
-0.80
0.20
Middle
Estuary
Lower
Estuary
Polychaeta, Gastropoda
-1.20
-1.80
-0.48
0.24
-0.28
Lower
Estuary
1.68
2.40
0.96
-1.56
Upper
Estuary
d)
0.88
2.04
3.20
2.20
3.20
Insecta, Crustacea,
Oligochaeta, Turbellaria
ma
1.20
Upper
Estuary
e)
Figure 3.5. (continued) Discriminant analysis of the ecological groups identified in the
northern branch of the Mondego River estuary using taxonomic levels that produced the
same cluster as obtained for all species (a)species; b)genus;.c)family; d)order; e)class).
Groups’ centroids and 95% confidence ellipses are plotted on the first two discriminant
functions. See Appendix 1 for species abbreviations.
Orbiniidea
76
Taxonomic sufficiency
Chapter 3
Taxonomic sufficiency
Taxonomic levels
Cluster analysis conducted on abundance data sets aggregated to taxonomic levels higher
than the species level produced the same clusters as using taxa identified to the species
level, except at the phylum level (Table 3.3). Wilk’s λ statistics revealed an overall
difference between centroids of the different regions identified in the Mondego River estuary
for all taxonomic levels (F values significant at P<0.001). Pairwise tests between centroids
also indicated significant differences between ecological regions for all taxonomic levels
(F values significant at P<0.01). Both LDFs provided a significant separation between regions
for all taxonomic levels, except for the class level (P<0.01).
All centroids were well separated along the first LDF for data aggregated at higher
levels except at the class level for which the Lower and Middle Estuary overlapped along the
first LDF, but were separated along the second LDF (Figs. 5b–e).
All discriminant plots showed a better separation of the Lower Estuary along the first
LDF, except for the class level. At this taxonomic level the first LDF explains the separation
between the Upper Estuary and the other two groups, mainly because of the occurrence of
common groups of taxa (i.e. polychaeta and gastropoda) in the Lower and Middle Estuary
(Figure 3.5e). Although MANOVA and discriminant analyses indicated significant differences
between groups for all taxonomic levels, the relative degree of differences between groups
decreased at higher taxonomic levels as indicated by both the multivariate strength-ofassociation index (1–Wilk’s λ) (Table 3.3) and by the reduction in magnitude of the scales in
the axes of the discriminant plots observed in Figure 3.5. A similar pattern was observed for
all taxonomic levels with respect to taxa that showed higher discriminatory ability. Several
bivalve and polychaete taxa discriminated better the Lower Estuary, some polychaete taxa
discriminated the Middle Estuary and a very diverse group of taxa (e.g. insects, oligochaetes,
crustaceans) discriminated better the Upper Estuary. Of all taxocenes tested only Mollusca
and Bivalvia indicated the same ecological groups as obtained using species. Cluster analysis
of all other taxocenes showed different hierarchical structures (Table 3.3).
All taxocenes tested showed significant overall differences between centroids of the
three regions identified in the Mondego River estuary (F values significant at P<0.01),
although only Annelida, Polychaeta, Spionidae, Arthropoda, Mollusca and Bivalvia were
significantly different between all pairwise groups tested (F values significant at P<0.05)
(Table 3.3). There was no overlap of the group ellipses along both LDFs of taxocenes
representing the Phylum level (i.e. Annelida, Artropoda, Mollusca) but below that taxonomic
level only bivalves showed no overlap. Polychaeta species provided good discrimination
between the Lower Estuary and the other groups along the first LDF but there was some
77
degree of overlap of the Middle and Upper Estuary, resulting mainly from the occurrence of
Nereid species (i.e. H. diversicolor, Websterinereis glauca (Claparède, 1870)) in both groups.
Amphipoda and Oligochaeta discriminated only the Upper Estuary, Gastropoda only the Middle
Estuary, while Isopoda and Insecta provided sufficient information to separate the Middle
Estuary from the Upper Estuary (Table 3.3). Both LDFs were significant for the taxocenes that
separated all three groups (F values significant at P<0.01) with the first LDF explaining a
higher percentage of variance (>65%).
Table 3.3. Discrimination ability of different taxonomic levels and taxocenes determined by
Wilk’s λ test on the centroides defined for each region
Taxocenes
Similar cluster
Lower Estuary
Middle Estuary
Upper Estuary
1- λ
−
0.999
Genus
Yes
0.998
Family
Yes
0.993
Order
Yes
0.974
Class
Yes
0.835
Phylum
No
0.660
Annelida
No
0.946
Polychaeta
No
0.898
Spionidae
No
0.597
Oligochaeta
No
0.587
Arthropoda
No
0.872
Amphipoda
No
0.448
Isopoda
No
0.295
Insecta
No
0.356
Mollusca
Yes
0.876
Bivalvia
Yes
0.829
Gastropoda
No
0.408
Species
Upper solid lines represent no differences between the Lower and Middle Estuary and lower solid lines
represent no differences between the Lower and Upper Estuary. The first column identifies which
taxonomic levels and taxocenes produced the same cluster obtained using all species. The strength of
association between groups for each taxonomic level and taxocene is shown in the right column
(1- Wilk’s λ)
Taxocenes
Spionid polychaetes were important in discriminating between spatial groups for
discriminant analyses conducted on both the Annelida and Polychaeta. S. martinensis (r=0.86)
and Polydora ciliata (Johnston, 1838) (r=0.97) were among the group of species that best
discriminated the Lower Estuary (higher correlations with the first LDF). Boccardiella ligerica
(Ferronnieère, 1898) (r=–0.96) and S. shrubsolii (r=0.95) showed the best discriminating
78
Taxonomic sufficiency
Chapter 3
ability between the Upper and Middle Estuary, along the second LDF. The discriminant
analysis using only this family revealed some degree of overlap along both LDFs, although all
groups were significantly different (Figure 3.6c). That overlap was mainly related to the
occurrence of S. shrubsolii, across all groups, although with different abundances, and the
occurrence of S. martinensis in the Lower and Middle Estuary but with significantly higher
abundance in areas of higher salinity (Table 3.2). The results of the cluster analysis for this
group identified very similar groups of stations, with a single shift in positions of stations 2
and 3.
Mollusks and bivalves showed very similar discriminatory ability between groups, as
shown by the ellipse plot (Figs. 3.6a–b) and the strength of association levels which were
higher than 0.80 for both taxocenes (Table 3.3). Species best separating different regions
were all correlated with the first LDF. C. fulminea was negatively correlated to the first LDF
while all other bivalve species showed significant high positive correlations with that axis
(F values
significant
at
P<0.05).
Isopods
(C.
carinata;
S.
losadai),
amphipods
(C. multisetosum), insects (E. virgo; Chironomidae) and mysids (Gastrosaccus spinifer (Goës,
1864)) contributed to the discriminant ability of arthopods, although none of those groups,
when tested, discriminated all regions when used independently (Table 3.3).
79
80
-1.52
-0.24
2.32
3.60
H.ulv, A.ten, C.gla, S.pla, M.bar, S.mar, Nudi
1.04
C. ful
-1.20
-2.80
-1.60
Upper
Estuary
-0.40
2.00
3.20
A.ten, C.gla, S.pla, M.bar , S.mar
0.80
Middle
Estuary
Lower
Estuary
b)
B.lig
-1.20
-1.80
-0.64
-0.08
0.48
1.04
1.60
-1.04
Upper
Estuary
-0.28
Middle
Estuary
0.48
Lower
Estuary
2.00
S.mar, S.shr, P.cil
1.24
c)
Figure 3.6. Discriminant analysis of the ecological groups identified in the northern branch of the Mondego River estuary using taxocenes
that produced the same cluster as obtained for all species ( a)Mollusca; b)Bivalvia). The discriminant plot of family Spionidae c) is also
shown. Groups’ centroids and 95% confidence ellipses are plotted on the first two discriminant functions. See Appendix 1 for species
abbreviations.
C.ful
-1.40
-2.80
-0.60
-0.76
Middle
Estuary
0.00
-0.12
Lower
Estuary
1.20
1.80
0.60
Upper
Estuary
a)
0.52
1.16
1.80
Taxonomic sufficiency
Chapter 3
DISCUSSION
The Mondego River estuary is a poikilohaline estuary, characterized by strong seasonal
changes in water flow and salinity which presents some challenges in the identification of
saline regions based upon the Venice classification system as indicated by the WFD (Chainho
et al., 2006). This type of salinity regime associated with strong tidal and seasonal changes
has been already recognized in Portuguese systems by Moreira et al. (1993) in Ria de Aveiro.
In poikilohaline estuaries benthic communities are seasonally displaced and estuarine species
are dominant (Boesch, 1977b), as confirmed in the Mondego where the numerical dominance
of S. shrubsolii and C. multisetosum was observed throughout most of the year.
The results of seasonal cluster analysis showed a consistent pattern of aggregation of
stations among seasons, despite strong changes observed in the structure of the benthic
community within each group. The only exception was station 5, which is apparently located
in a transition zone and changed groups in different seasons. The overall station group
consistency supports the definition of three main ecological types in the northern branch of
the Mondego River estuary, namely the Lower Estuary, the Middle Estuary and the Upper
Estuary.
Nevertheless, within each of these three station groups the Venice salinity classes
varied greatly between seasons, ranging from oligohaline to polyhaline in some areas of the
estuary, depending upon the freshwater flow regime. This scenario seems to fit into the
ecocline concept introduced by Boesch (1977b) and further discussed by Attrill & Rundle
(2002), defined as a boundary of progressive change between two systems, freshwater and
marine. The latter proposed a two ecocline model, with two overlapping salinity gradients,
one from upriver to mid-estuary for freshwater species and another extending from the sea to
the mid-estuary for marine species, whose associated benthic communities change location
along the estuary in relation to changes in freshwater flow. Furthermore they suggest that
truly estuarine endemic species do not exist. In the Mondego, seasonal changes in freshwater
flow act as an environmental gradient and euryhaline estuarine species and freshwater
species shift their distributions in relation to the associated changes in salinity. Although
insect species extended their distribution downstream in the Mondego River estuary during
high flows and marine species of polychaetes included in families such as Phyllodocidae,
Glyceridae and Cirratulidae moved upstream during low freshwater flow periods, as indicated
in the two-ecocline model, estuarine endemic species were also observed, such as
C. multisetosum and S. losadai. Previous studies carried out in Portuguese estuaries showed
that the amphipod C. multisetosum occurs preferentially in salinities ranging from 2.5 to 10
81
(Queiroga, 1990), which is in agreement with the movements of this species upstream and
downstream in the Mondego River, following salinity changes.
Using average annual salinities and benthic community groups obtained independently
of seasonal effects appears to be a reasonable approach to define water body types in the
Mondego River estuary, since there was a good correspondence between both approaches.
The Lower Estuary had an average salinity in the euryhaline class and a fauna characterized
by the dominance of marine bivalve and polychaete species. The Middle Estuary had an
average salinity in the polyhaline class and a fauna dominated by polychaetes, mainly the
tolerant spionid S. shrubsolii. The Upper Estuary had an average salinity in the mesohaline
class and a fauna dominated by the estuarine endemic amphipod C. multisetosum. Average
annual salinities in the oligohaline and tidal freshwater range were not observed although
salinity measured at some stations was in the oligohaline class during winter and spring.
Discriminant analysis showed that rarer species also played an important role in separating
ecological groups, since some of them are found exclusively at one station group, such as the
marine polychaetes (e.g. D. neapolitana, E. picta) in the Lower Estuary. On the other hand,
estuarine tolerant species (e.g. S. shrubsolii) provided good discrimination of the Middle
Estuary, while a highly diverse group of taxa including freshwater species discriminated the
Upper Estuary from the other groups. Overall our findings suggest that an ecocline model for
explaining benthic community composition may be appropriately applied to the Mondego
River estuarine gradient provided the model allows for the inclusion of estuarine endemic
species, as suggested by Boesch (1977b).
Techniques used to test the hypotheses of obtaining the same ecological groups with
taxonomic levels higher than the species showed that only the phylum level produced
significantly different results. The class level provides less discriminating ability between
ecological groups, since both LDFs are necessary to separate all groups and the location of
centroids and ellipses indicate that groups are closer. This is mainly related to the occurrence
of common groups such as polychaetes and gastropods in the Lower and Middle Estuary. On
the other hand, when taxa were grouped to genus, family and order levels good
discriminating ability between ecological groups was observed, with centroids and ellipses
exhibiting very similar relative position and shape when compared to those of species level.
Correlations between similarity matrices of different taxonomic levels corroborated these
results by showing a higher closeness of genus, family and order levels to the species matrix.
As pointed out by Ferraro & Cole (1992, 1995), a high number of monotypic taxa
increases the probability of taxonomic sufficiency at taxonomic levels higher than species,
mainly because of redundancy in their responses to pollution. As shown in our results over 70%
of genera and families were monotypic and although the percentage was lower for orders,
those that were polytypic included mainly species found in the same ecological groups. For
82
Taxonomic sufficiency
Chapter 3
example, the order Phyllodocida, which included 22 different species, was collected almost
exclusively in the Lower Estuary.
Most studies concerning taxonomic sufficiency for detecting pollution impacts
concluded that family level was a good surrogate for species, since there was no loss of
information in the benthic responses to pollution stress (Warwick, 1988; Baldó et al., 1999;
Dauvin et al., 2003; De Biasi et al., 2003; Gomez Gesteira et al., 2003; Terlizzi et al., 2003)
or loss of statistical power to detect differences between degraded and undegraded locations
(Ferraro & Cole, 1990, 1992; 1995). The present study indicates that, for typological purposes
in poikilohaline estuaries, order can be used without significant loss of information. Even so,
family level is most likely the best compromise since most taxonomic manuals are more
adequate for identifications at this level and ecologists with taxonomic training are familiar
with the procedures. These findings corroborate the suggestion of De Biasi et al. (2003) to use
family level to assess spatial patterns in the Magra estuary (Italy).
Although some taxocenes demonstrated the ability to discriminate between the preestablished ecological groups (e.g. arthropods and annelids), only mollusks and bivalves
identified the same groups using cluster analysis. The discrimination of the Upper Estuary was
mostly related to the high abundance of C. fulminea, an introduced species that can easily
adapt to freshwater environments and reach very high densities. Although a density of
830 ind m–2 was recorded for this species in the Upper Estuary, there is no information about
its occurrence in other Portuguese estuaries since most studies did not cover upstream areas.
Only 16 species occurred across all ecological groups, half annelid species, indicating
the adaptive abilities of this group. This low number of species seems to agree with the
arguments of Kinne (1971) stating that environments with pronounced salinity fluctuations do
not promote evolutionary processes because instability acts as a brake to speciation.
Nevertheless, family Spionidae, which included the highest number of species among all
families identified in the Mondego River Estuary, showed a discriminating ability almost as
good as other taxocenes. This family seems to have a very high plasticity with species
occurring along the entire estuary, which is why, despite the overlap observed along LDF axes
in the ellipse plots, it showed significant differences between all ecological groups and the
results of cluster analysis were very similar to those using species. These results suggest some
caution when using taxocenes because the loss of ecological information might lead to
different conclusions obtained with different analytical procedures.
The dominant species S. shrubsolii showed a very wide distribution occurring in all
ecological groups, S. martinensis was very common in the Middle and Lower Estuary and
B. ligerica was collected exclusively in the Upper Estuary. The other species of this family
were rare (i.e. P. ciliata, Prionospio malmgreni Claparède, 1870, Prionospio cirrifera Wirén,
83
1883 and Pygospio elegans Claparède, 1863), occurring mainly in the Lower Estuary. Spionids
are often classified as opportunists and used as pollution indicators (e.g. Weisberg et al.,
1997; Borja et al., 2000; Eaton, 2000). In addition, spionid species exhibit a diverse variety of
reproductive patterns including monotely, polytely, broadcast spawning, internal and
external brooding, and poecilogony (Gudmundsson, 1985; Blake & Arnofsky, 1999). Feeding
behaviours include deposit feeding, suspension feeding, switching between deposit and
suspension feeding interface feeding) (Dauer et al., 1981), as well as, commensal and
predatory behaviours (Williams, 2001; 2002). It is useful to make a distinction between
opportunist species and stress tolerant species (Gray, 1979). Spioinds can generally be
considered to be opportunistic species and some species may also be stress tolerant.
However, there is little physiological data to distinguish between species that are
opportunistic, stress tolerant to natural stresses and stress tolerant to anthropogenic stress.
These patterns are very similar to those obtained in the James River, Chesapeake Bay, a
homiohaline estuary (Dauer, unpublished data) where spionids also revealed good
discriminating ability between salinity classes, showing habitat specific distributions of
species in this family and high adaptability to different conditions.
CONCLUSIONS
This study demonstrates the effective application of the concept of taxonomic
sufficiency in the identification of water body types in a poikilohaline estuary. Although
taxonomic sufficiency has been widely tested for detecting pollution impacts, showing that
the family level provides enough information to separate between degraded and undegraded
sites, there was no previous substantial scientific basis for the use of taxa aggregated to
higher taxonomic levels for typology. The present study shows that taxa identified to the
family level discriminate the same ecological types as using the species level, mainly because
of the high number of monotypic families occurring in poikilohaline estuaries.
Taxocenes demonstrated less ability to identify water body types when used
separately, although mollusks and bivalves have identified the same types and annelids have
shown a habitat specific distribution, in particular the family Spionidae. The use of these
taxocenes needs further investigation namely on the effects of natural versus human induced
stress since spionids and also some bivalve species are very well adapted to strong
environmental changes. The same methodology should be applied to other estuaries with
similar seasonal hydrologic changes but lower human pressure. Future typological studies
should also include regions that are farther upstream in order to clarify application of the
WFD to estuarine gradients.
84
Taxonomic sufficiency
Chapter 3
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1997. An estuarine Benthic Index of Biotic Integrity (B-IBI) for Chesapeake Bay.
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Williams, J.D. 2002. The ecology and feeding biology of two Polydora species (Polychaeta:
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the Philippines. Journal of Zoology 257: 339-351.
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87
Chapter 4
Seasonal variability in benthic
indices
Chainho, P., Costa, J.L., Chaves, M.L., Dauer, D.M. & Costa, M.J. 2007. Influence of
seasonal variability in benthic invertebrate community structure on the use of biotic
indices to assess the ecological status of a Portuguese estuary. Marine Pollution
Bulletin 54: 1586–1597.
Seasonal variability in benthic indices
Chapter 4
Influence of seasonal variability in benthic invertebrate
community structure on the use of biotic indices to assess
the ecological status of a Portuguese estuary
ABSTRACT
The present study focused on the use of benthic invertebrate communities to assess
the ecological quality of a Portuguese estuary characterized by strong seasonal changes and
with eutrophication problems. Seasonal benthic samples were collected during a flood year
and the methodology proposed by the WFD Portuguese group was used to classify benthic
assemblages into five different quality classes. Factor analysis was applied to classify stations
based on their physical-chemical status. Different classifications were obtained with different
indices and among seasons and there was low agreement between indices and index-season
interactions. Diversity indices were better correlated to eutrophication related variables than
AMBI and ABC method. Predictable responses of benthic indices to anthropogenic stress
symptoms were stronger during the dry period.
KEY WORDS: estuarine invertebrates, Water Framework Directive, Mondego River estuary,
biotic indices, DIN, physical-chemical classification.
91
INTRODUCTION
The achievement of good ecological quality status in coastal and transitional waters is
one of the main goals of the European Water Framework Directive (WFD) (2000/60/EC). The
implementation of the WFD requires the development of assessment tools adequate for all
European aquatic systems, based on (1) the identification of surface water types, (2) the
definition of type-specific reference conditions and (3) the classification of all water bodies
within five ecological quality classes. The recognition that reference conditions are rare
among transitional European waters and that historical data and paleontological studies are
lacking for most water bodies (invalidating modeling) indicates that expert judgment is the
best available tool. There is no consensus among experts on using physical-chemical criteria
to define reference conditions for the biological elements. For example, some authors use
contaminant concentrations to separate reference and degraded conditions (e.g. Weisberg et
al., 1997; Llansó et al., 2002b), in contrast others state that biological elements should be
used initially to identify dysfunctions in the ecosystem and abiotic elements only when biotic
degradation is detected (Borja & Heinrich, 2005). Indices are useful tools to communicate
with managers because they reduce complex scientific data, integrate different types of
information, and produce results that can be easily interpreted in the perspective of water
quality management (Wilson & Jeffrey, 1994). Nonetheless, there is no consensus among
managers and scientists concerning which of the numerous existing indices should be used.
New indices are continuously being developed, but as pointed out by Diaz et al. (2004), a
major effort should be focused on updating the available tools, in order to improve their
performance in different ecosystems. Several classification tools have been developed in
Europe over the last years using macroinvertebrate communities as indicators of
anthropogenic disturbances in marine and transitional waters (e.g. Warwick, 1986; Majeed,
1987; Grall & Glémarec, 1997; Borja et al., 2000; Simboura & Zenetos, 2002; Rosenberg et
al., 2004), but none seems to fulfill adequately all the requirements of the WFD. Recent
developments on the implementation of the WFD indicate a tendency to combine different
types of metrics such as composition, abundance and sensitivity into a final result (Vincent et
al., 2002), aiming to integrate a wider range of benthic community responses. Molvaer et al.
(1997 in Vincent et al., 2002) proposed a combination of the Shannon-Wiener and Hulbert
(HS100) diversity indices with total organic carbon as a classification system for marine and
transitional waters in Norway. In Spain, Borja et al. (2004) developed the Ecological Quality
Ratio, which combines species richness, Shannon-Wiener diversity index and the AZTI Marine
Biotic Index (AMBI). Moreover, the Portuguese WFD working group also proposed a
classification system for marine and transitional waters, based on the combination of two or
three indices (Shannon-Wiener diversity index, Margalef species richness, AMBI and ABC
92
Seasonal variability in benthic indices
Chapter 4
method), depending on the type of data available (Bettencourt et al., 2004). As indicated by
the WFD guidance documents, the definition of reference conditions and subsequent
classification have to incorporate the natural variability of aquatic systems and minimize
intrinsic variability of biological elements, by choosing compartments (e.g. areas, seasons,
biological attributes) that allow valid comparisons between biological communities of the
same type. Ultimately, Member States are allowed to exclude a quality element, if natural
variability, other than seasonal, does not permit the definition of reliable reference
conditions (Vincent et al., 2002).
Estuaries are highly dynamic environments, mainly influenced by the hydrological
regime and, as described by Boesch (1977), there is a biotic change along the estuarine
complex-gradient that results in major spatial differences. Nevertheless, these spatial
patterns can be significantly altered over time, mainly in poikilohaline estuaries,
characterized by strong seasonal changes in freshwater discharges (Boesch, 1977; Chainho et
al., 2006). Several authors have investigated the major factors producing seasonal variations
in benthic communities (e.g. Lopez-Jamar et al., 1986; Alden et al., 1997; Sardá et al., 1999;
Ducrotoy & Ibanez, 2002; Salen-Picard & Arlhac, 2002; Reiss & Kröncke, 2005a). In temperate
regions there is a general pattern of a decline in benthic community condition (abundance
and/or diversity) over autumn and winter and a recovery in summer, after spring recruitment
(Lopez-Jamar et al., 1986; Alden et al., 1997). This pattern is normally associated with
environmental conditions that determine food availability (Marsh & Tenore, 1990) and such
conditions are fundamentally modulated by freshwater flows and the occurrence of extreme
conditions, such as floods and droughts. Benthic communities inhabiting estuaries with
seasonal floods and/or droughts will change (1) due to pulses of organic matter during floods
that stimulate an increase in abundance of opportunistic species (Salen-Picard & Arlhac,
2002), (2) changes in the water quality conditions, such as higher concentrations of
contaminants during droughts (Attrill & Power, 2000; Grange et al., 2000), (3) disappearance
of all but highly euryhaline species (Chainho et al., 2006), and (4) potential colonization by
alien species that are, in general, much more tolerant to salinity fluctuations than native
species (Lee & Bell, 1999; Paavola et al., 2005).
Most of the indices currently used to assess the benthic status were developed,
applied and/or validated for coastal marine ecosystems that generally have much less
seasonal variation than estuarine ecosystems. The applicability of benthic community indices
to USA monitoring programs addressed spatial and temporal variability by defining different
thresholds for each habitat type and selecting an index period, respectively. Several indices
and subsequent adaptations to different biogeographic regions are calculated using only
summer collections (Weisberg et al., 1997; Paul et al., 2001; Smith et al., 2001; Llansó et al.,
2002b), because the difference in benthic community metrics should be maximal during the
93
summer period due to increased water temperatures, water column stratification, occurrence
of bottom low dissolved oxygen conditions, and salinity (Alden et al., 1997). On the other
hand, in Europe no recommendations were proposed regarding either the modeling of
seasonal variability or the selection of a favorable period to apply the available classification
tools. Benthic indices are known to differ in the effects of seasonality, especially recruitment
events (Reiss & Kröncke, 2005b); however, few studies have examined how benthic indices
respond to ecosystems with strong seasonality. The main objective of the present study was
to examine how seasonal variations in benthic subtidal communities influence the results
obtained when using the assessment tools proposed for implementing the WFD in Portugal,
namely the Shannon-Wiener, Margalef, AMBI and ABC method indices. More specifically, this
paper addresses the following questions: (1) which environmental variables best reflect the
responses of the benthic communities to human stressors; (2) how do seasonal patterns in
macroinvertebrates influence the results of the indices; (3) which season(s) display better
correlations between stressors and the classifications obtained with the indices.
Methods
Study area
The Mondego River estuary is divided in two branches with different hydrographic
characteristics, the northern branch, mainly influenced by freshwater discharges of the
Mondego River and the southern branch, that drains the Pranto River and is more influenced
by tidal cycles since freshwater flow is low. It is a mesotidal and well-mixed estuary, with a
very irregular hydrological regime, namely low water flow during the dry period and strong
freshwater discharges during the rainy period. An average annual river flow of 80 m3 s-1 has
been registered in the Mondego River estuary but the sampling survey was carried out during
a flood year with an average annual river flow of 187 m3 s-1. Maximum river flows over
1000 m3 s-1 were measured in December 2000 and January 2001, corresponding to the biggest
flood of the last two decades (www.inag.pt, October 2003). Eutrophication is considered a
major problem in this estuary that was classified as a Potential Problem Area under the
OSPAR Convention because of the detection of eutrophication symptoms such as high nutrient
concentrations and shifts in macroalgae and seaweed species (Zostera spp. to Ulva spp.) in
the southern branch, mainly as a consequence of hydrodynamic characteristics (OSPAR
Commission, 2003). Benthic communities are dominated by opportunistic species, mainly
bivalves and polychaetes in higher salinity areas, and amphipods and oligochaetes in upstream
areas (Chainho et al., 2007).
94
Seasonal variability in benthic indices
Chapter 4
Sampling
Seasonal sampling surveys (July and October 2000, February and June 2001) were
conducted in the Mondego River estuary, western Portugal (Figure 4.1). Ten sampling stations
were distributed along the saline gradient of the northern branch and southern branch of the
Mondego River estuary (Figure 4.1). Three benthic invertebrate samples were taken at each
station using a modified van Veen LMG grab (0.05 m2) and grab contents were fixed and
preserved with 4% buffered formalin, sieved using a 500 µm mesh and preserved in 70%
ethanol. All samples were sorted and identified to the lowest possible taxonomic level, in
order to determine the number of taxa and their respective abundances. Biomass of species
per sample was also determined as ash free dry weight, after ignition at 450ºC. Several
environmental variables were measured (1) in water: bottom dissolved oxygen, temperature,
transparency, salinity, nutrients concentrations (NO3, NO2, NH4, P); and (2) in the sediment:
sediment grain size, heavy metals concentrations (As, Cr, Cu, Pb, Zn) and total organic
content. Dissolved inorganic nitrogen (DIN) was calculated using N-NO3, N-NO2 and N-NH4.The
methods used to determine these parameters are detailed in a previous study by Chainho et
al. (2006).
POPR
ORT
TUUGG
AL
A
Atlantic Ocean
L
FRANCE
FRANCE
SPAIN
SPAIN
Figueira da Foz
2
1
8
3
Montemor-o-Novo
9
4
7
10
5
6
2 Km
Figure 4.1. Location of sampling stations in the Mondego River estuary.
95
Data analysis
Identification of habitat types
The Mondego River estuary was entirely included in type A2 , i.e., needing further
separation in water bodies representing homogenous units for which specific environmental
objectives must apply (Bettencourt et al., 2004). The delimitation of water bodies has to
account not only for hydromorphological and biological characteristics, but also for
differences in human pressures (Vincent et al., 2002). Since salinity is the major
environmental variable influencing the distribution of benthic communities in the Mondego
River estuary (Chainho et al., 2006), habitat types were identified according to their salinity
measures (minimum, maximum, mean and standard deviation) as suggested by Bald et al.
(2005). A cluster analysis was conducted using software SPSS 13.0 to group stations using data
standardized by subtracting the mean and dividing by the standard deviation. Stations were
grouped using the Ward’s minimum variance hierarchic method and Euclidean distances were
used as a dissimilarity measure (Hair et al., 1998).
Benthic invertebrate classification and seasonal variations
The benthic invertebrate condition of transitional waters was assessed by calculating
the Shannon-Wiener diversity index (H’), the Margalef species richness (Legendre & Legendre,
1976) (D), the AMBI index (Borja et al., 2000) and the ABC method (W) (Warwick, 1986),
following the methodology suggested by the WFD Portuguese working group (Bettencourt et
al., 2004) (Table 4.1). All indices were calculated for each sampling station and for each
season, using the abundance per replicate. Calculations were done using PRIMER 5 software
package and AMBI index software 3.0. Because AMBI is the only index with higher values
corresponding to worse quality, the reciprocal 1/AMBI was used when comparing to other
indices and environmental variables. Variation of the different indices, species richness (S)
and abundance (N) among seasons was assessed using the adjusted coefficient of variation:
Cv=(SD/M)100, with SD the standard deviation and M the mean.
Reference conditions and physical-chemical classification
Most Portuguese estuaries have been subject to increased human pressures
particularly in recent decades and there is no historical data available on ecological
conditions prior to anthropogenic impacts. When no reference sites exist some authors
propose the use of reference physical-chemical data, using multivariate analysis (Borja et al.,
2003; Bald et al., 2005), similar to applications in North American estuaries (Weisberg et al.,
1997; Van Dolah et al., 1999; Llansó et al., 2002a). In this study, reference conditions for
96
Seasonal variability in benthic indices
Chapter 4
High and Bad status for the parameters Secchi disc transparency (T), dissolved oxygen (O2),
ammonia (NH4) and nitrates (NO3), were those defined by Borja et al. (2004) and Bald et al.
(2005) (Table 4.2). These authors used low or background levels of contamination to estimate
virtual reference concentrations, weighted by salinity so that different reference conditions
were defined for each of the Venice system (1959) salinity classes. An additional variable was
considered, namely chlorophyll a (Chl a) and reference concentrations followed criteria
established by Borja et al. (2004). For Chl a, the same reference concentrations for High and
Bad status were considered across all salinity classes because no dilution factors are known
for this parameter.
One of the major problems arising from classification procedures is to integrate
information of several variables into a final status. A factor analysis was used to reduce the
number of variables, as suggested by Bald et al. (2005). Factor analysis is a data reduction
method that creates a smaller and entirely new set of variables that become surrogates of
the original set of variables, retaining their nature and character (Hair et al., 1998). A
separate factor analysis was conducted using software SPSS 13.0, for stations included in
different salinity habitat types and two virtual stations representing reference conditions for
each variable (High and Bad status) were included in each data set (Bald et al., 2005).
Factors were extracted with a component analysis conducted on a data set previously
log10 (x+1) transformed. A scree test criterion was used to determine the number of factors
extracted, by plotting the number of factors against eigenvalues and identifying the inflection
point after which the proportion of unique variance is higher than common variance (Hair et
al., 1998). Factors were rotated using a Varimax rotation to redistribute the variance by
factors and obtain a meaningful pattern of variable loadings by maximizing the sum of
variances of the factor matrix. The amount of variance accounted by the factor solution for
each variable was assessed by examining the communalities. The adequacy of the factor
analysis to combine variables into a new structure represented by factors was tested using a
Bartlett test of sphericity, a statistical test for the presence of correlations among variables
(Green, 1979; Hair et al., 1998). A numerical value of 1, following the derivation of the
Ecological Quality Ratio (EQR), as defined in the WFD, was assigned to the distance between
both virtual reference stations (High and Bad status). The range values for the physicalchemical status classification (PC-EQR) were: High, 0.83–1; Good, 0.62–0.82; Moderate, 0.41–
0.61; Poor, 0.20–0.40; and Bad, <0.20 (Bald et al., 2005).
97
98
> 4.0
2.5 – 4.0
< 2.5
< 2.5
3.0 – 4.0
2.0 – 3.0
1.0 – 2.0
0.0 – 1.0
Good
Moderate
Poor
Bad
0.1 – 1.0
0.1 – 1.0
-0.1 – 0.1
-1.0 – -0.1
-1.0 – -0.1
1.2 – 3.3
3.3 – 5.0
5.0 – 6.0
6.0 – 7.0
W = Σ (Bi- pi )/50(S-1)
AMBI={0(%GI)+1,5(%GII)+3(%GIII)+
4,5(%GIV)+6(%GV)}/100
0.0 – 1.2
ABC-method
AMBI
2.7
11.5
24.0
32.5
2.7
11.5
24.0
32.5
Oligohaline
Mesohaline
Polyhaline
Euhaline
Oligohaline
Mesohaline
Polyhaline
Euhaline
Salinity
2.5
0.5
0.5
0.5
8.0
2.0
2.0
2.0
T (m)
58.6
53.7
46.6
41.6
98.6
93.7
86.6
81.6
O2 (%)
Bad status
High status
19.2
31.8
50.4
63.4
2.3
3.3
4.7
5.7
NH4 (µmol -1)
28.9
87.2
163.0
218.9
10.7
30.1
58.7
78.7
NO3 (µmol l-1)
30.0
30.0
30.0
30.0
4.0
4.0
4.0
4.0
Chl a (µg l-1)
Table 4.2. Concentrations of pollution indicative variables (average values) for virtual stations corresponding to High
and Bad status, weighted
based on the criteria
defined by Borja et al. (2004) and Bald et al. (2005) (for
Salinity by salinity,T(m)
O2 (%)
abbreviations see data analysis section)
Adapted from Bettencourt et al., 2004) (pi – relative abundance of the ith species; S – number of species; N – number of
individuals; GI to GV – ecological groups; Bi – relative biomass of the ith species - for acronyms see the methods section
> 4.0
> 4.0
D = (S-1)/logeN
H’ = -Σ pi log2pi
High
Classification
Calculation
Margalef
Shannon-Wiener
Table 4.1. Calculation and thresholds used for each index included in the WFD Portuguese working group approach
Seasonal variability in benthic indices
Chapter 4
Relationship between the benthic invertebrate and physical-chemical condition
The best indicators of benthic condition are expected to respond predictably to
environmental impacts, thus showing increasing or decreasing values according to different
pollution levels. Correlations between the results of the four indices tested in different
seasons and variables representing environmental impacts were performed to investigate the
ecological consistency between indices and variables. Total phosphorus and heavy metals
were not included in the analysis since concentrations never exceeded 0.1 mg l-1 P and Long
et al’s (1995) effects range medium, respectively. A pairwise Kendall correlation coefficient
was used to test for significant correlations (P<0.05) between indices and variables with every
possible seasonal combination (all seasons, combinations of 3 seasons, combinations of 2
seasons and individual seasons). The best combinations of indices, environmental variables
and seasons were assessed by identifying the number of correct correlations according to an
expected response. All indices were expected to be positively correlated with transparency
and dissolved oxygen and negatively correlated with nutrients and chlorophyll a. Correlations
were calculated using software SPSS 13.0.
RESULTS
Identification of habitat types
Cluster analysis using salinity attributes identified four major groups of stations in the
Mondego River basin, corresponding to different classes of the Venice system (oliogohaline,
mesohaline, polyhaline and euhaline) as indicated in Figure 4.2. Higher salinity levels were
measured during the dry period (July and October) and lower values were registered during
winter, corresponding to a flood period. The highest salinity range over seasons was recorded
in stations included in the euhaline salinity class (33.2), whereas the lowest range occurred in
the oligohaline stations (12.2) (Table 4.3). Groups of stations defined by salinity are
consistent with those identified when using the benthic communities, as shown by Chainho et
al. (2006; 2007) with station 5 corresponding to a transitional area.
Benthic invertebrate classification and seasonal variations
A total of 38 718 specimens were collected in the Mondego River estuary and 92 taxa
were identified (see Appendix 1). The polychaete Streblospio shrubsolii (Buchanan, 1890) and
the amphipod Corophium multisetosum Stock, 1952 were the dominant species in the
Mondego River estuary, although there are significant differences in the composition of the
99
benthic communities among different habitat types (Table 4.3). The highest densities were
found in the oligohaline, mainly due to the abundance of C. multisetosum during spring, and
the lowest abundances occurred in the mesohaline. Fewer specimens were collected during
winter, except for the polyhaline communities (southern branch), where the lowest densities
were registered during spring. The number of species identified in each habitat type also
varied between seasons and the lowest number was always found during winter and spring,
while summer and autumn registered the highest number of species (Table 4.3).
Salinity
40
Euclidean distance
30
20
10
0
10
9
Polyhaline
8
1
2
Euhaline
3
4
Mesohaline
5
6
7
Oligohaline
Figure 4.2. Groups of stations obtained for the Mondego River estuary, using a cluster
analysis based on salinity (mean, minimum, maximum and standard deviation). Stations
were grouped using the Ward’s minimum variance hierarchic method and Euclidean
distances were used as a dissimilarity measure.
The results of the biological indices indicated different classifications between
sampling events (Table 4.4). AMBI classified most stations in a Good status, but stations 6, 9
and 10 changed between Poor and Good, while stations 3, 5, 7 and 8 changed between
Moderate and Good. Only three stations maintained the same classification throughout the
year, namely Good status (1, 2, and 4). Classifications obtained with Shannon-Wiener
diversity index were more heterogeneous and none of the stations maintained the same
classification across seasons. Some stations changed from classifications below Good status to
Good status (1, 2, 3, 8), while other stations, although changing classifications between
seasons, never achieved more than the Moderate status (4, 5, 6, 7, 9 and 10). According to
100
Seasonal variability in benthic indices
Chapter 4
the Portuguese guidelines for classification on transitional waters (Bettencourt et al., 2004),
only three different classes apply for the Margalef and W-statistic, namely Bad/Poor,
Moderate and Good/High classes. Classifications obtained in the Mondego River estuary when
calculating the Margalef species richness were also very heterogeneous along seasons and only
stations 6, 7 and 8 had a single classification throughout the year. Station 1 changed between
Moderate and Good/High, while the remaining stations changed between Bad/Poor and
Moderate. Most stations were classified in the Moderate status when using the W-statistic,
four of which maintained that status along seasons (2, 4, 5 and 9) and some others changed to
Good/High during some seasons (1, 6, 7 and 8). Station 3 changed between the worst and the
best status, while station 10 was never classified above Moderate (Table 4.4). In general,
stations were better classified during summer/autumn using Shannon-Wiener and Margalef
indices, but during the same period the worst classifications were obtained when using AMBI.
There was a very low agreement between classifications given by different indices to the
same stations during the same season. Station 1 was classified in a Good status by all indices
during summer and station 10 was included in the class Moderate by all indices during
autumn. For all other stations different classifications were given by different indices, when
considering a specific season.
The results of the adjusted coefficient of variation demonstrated that ShannonWiener and Margalef indices were more variable among seasons, when compared to the other
two indices used, and showed a variation very similar to the number of species, higher during
summer and autumn (Figure 4.3). Total abundance was also highly variable over time. (Table
4.3; Figure 4.3).
Physical-chemical classification
Factor analysis provided a representation of the position of each station relative to
reference conditions for High and Bad status (Figure 4.4). Only the first three factors were
used to define the multidimensional space for every salinity-habitat type, based on a scree
test and the cumulative variation explained. Although analyses were conducted separately for
each salinity habitat type, all results are presented in common plots (Figure 4.4). More than
85% of the total variation was explained by factors F1 to F3 for all salinity habitat types
(Table 4.5). For oligohaline, mesohaline and polyhaline stations, factor analysis seems to be a
good representation of the overall structure of stations according to physical-chemical
parameters, corroborated by the results of the Bartlett test of sphericity (P<0.01) (Table 4.6).
The results of this test for euhaline stations (Table 4.6) indicated no significant correlations
between variables and the derived factors (P=0.169), suggesting that factor analysis is less
appropriate for reducing the number of variables within this salinity stretch.
101
102
45.8 – 113.8
O2 (%)
16.1 – 75.8
NO3 (µmol l-1)
Medium sand
0.4 – 7.2
Medium sand
Chl a (µg l-1)
Sediment type
Coarse-Medium sand
1.3 – 14.3
44.3 – 79.1
41.0 – 75.8
2.2 – 9.4
80.3 – 112.0
0.8 – 1.5
2.0 – 31.6
1.5 – 5.0
Hesionidae n.i. (2%) P
Capitella capitata (5%) P
Hydrobia ulvae (5%) G
Tetrastemmatidae n.i. (6%) N
Spio martinensis (12%) P
Streblospio shrubsolii (61%) P
(9 W) 40 (26 S)
(287 W) 1 640 (3 568 S)
Mesohaline
Oligohaline
Coarse sand
1.8 – 24.0
56.0 – 94.8
50.5 – 87.1
2.2 – 12.8
71.8 – 113.7
2.0 – 14.2
2.0 – 14.2
0.8 – 6.0
Echytraeus sp. (2%) O
Nais sp. (4%) O
Tubificoides sp. (4%) O
Corbicula fulminea (6%) B
Streblospio shrubsolii (15%) P
Corophium multisetosum (66%) A
(13 W) 38 (26 S)
(963 W) 13 463 (35 127 Sp)
(A- Amphipoda; B- Bivalvia; G- Gastropoda; N- Nemertea; O- Oligochaeta; P- Polychaeta). See methods section for abbreviations
0.7 – 37.
26.7 – 79.1
28.3 – 124.3
16.1 – 51.6
6.1 – 106.7
57.8 – 109.2
0.3 – 1.5
10.0 – 34.1
DIN (µmol l )
-1
2.2 – 18.3
NH4 (µmol l )
-1
1.1 – 2.7
Chaetozone setosa (3%) P
Chaetozone setosa (5%) P
T (m)
Cerastoderma glaucum (3%) B
Spio martinensis (6%) P
7.0 – 40.2
Scrobicularia plana (4%) B
Hydrobia ulvae (6%) G
Salinity range
Streblospio shrubsolii (20%) P
Scrobicularia plana (10%) B
0.8 – 4.0
Hydrobia ulvae (23%) G
Cerastoderma glaucum (25%) B
3.0 – 5.5
Tubificoides sp. (32%) O
(22 W/Sp) 53 (39 A)
(1 984 Sp) 2 822 (4 418 A)
Polyhaline
Streblospio shrubsolii (30%) P
(3 W) 60 (41 S)
(380 W) 6 315 (9 497 Sp)
Depth range (m)
Dominant
Species
N. Taxa
Mean Density
Euhaline
Table 4.3. Biological and environmental descriptive parameters for habitat types identified in the Mondego River estuary, according to the
salinity classification. Maximum, minimum and mean density values (ind m-2) seasonally determined (summer - S; autumn - A; winter – W;
spring – Sp) are presented for each group. The total number of taxa is indicated for each group. Six most abundant species (dominants) are
listed with their respective contributions to total density and the indication of the taxon in bold. Deph, physical-chemical water parameters
ranges and sediment type are also indicated.
Seasonal variability in benthic indices
Chapter 4
The communalties for each variable indicated transparency, ammonia and chlorophyll a as
variables most correlated with the factor solution for oligohaline, mesohaline and polyhaline
stations (Table 4.6). Loadings of variables in factors show different relationships between
variables in different salinity habitat types. For instance, dissolved oxygen achieves very
positive loadings on factor 1 for polyhaline stations, whereas for other salinity stretches the
same variable is negatively correlated with this factor (Table 4.6). The opposite was observed
for transparency and chlorophyll a, with negative loadings in factor 2 for mesohaline and
polyhaline stations and lower positive loadings for the oligohaline stretch. Physical-chemical
conditions seem to be relatively stable over time, among the class ranges used, since
classifications for each station varied only between Good and High over seasons, except for
euhaline stations (stations 1 and 2) that varied between Poor and High between sampling
events (Table 4.4).
Table 4.4. Range of classifications obtained for each sampling station in the Mondego River
estuary across seasons, based on the results of biological indices and on the physical-chemical
ecological quality ratio (PC-EQR) determined by the factorial analysis.
Stations
ShannonWiener
Margalef
AMBI
ABC method
PC- EQR
1
Moderate-Good Moderate-Good/High Good
Moderate-Good/High Poor-High
2
Poor-Good
Bad/Poor-Moderate
Good
Moderate
3
Poor-Good
Bad/Poor-Moderate
Moderate-Good Bad/Poor-Good/High High
4
Bad-Moderate
Bad/Poor-Moderate
Good
Moderate
Good-High
5
Bad-Moderate
Bad/Poor-Moderate
Moderate-Good Moderate
Good-High
6
Bad-Poor
Bad/Poor
Poor-Good
7
Poor-Moderate
Bad/Poor
Moderate-Good Moderate-Good/High Good-High
8
Poor-Good
Moderate
Moderate-Good Moderate-Good/High Good-High
9
Bad-Moderate
Bad/Poor-Moderate
Poor-Good
Moderate
Good-High
10
Poor-Moderate
Bad/Poor-Moderate
Poor-Good
Bad/Poor-Moderate
Good-High
Moderate-High
Moderate-Good/High High
Relationship between the benthic invertebrate and physical-chemical condition
Kendall correlations between the benthic indices and physical-chemical variables
indicated few significant relationships for most variables (Figure 4.5). DIN was the variable
most correlated with differences found in the benthic condition (Figure 4.5a). For both DIN
and chlorophyll a, all significant correlations of environmental variables with biological
indices were the expected, namely a decline of the benthic condition as a response to an
increase of the concentrations of the pollution indicative parameters. For these variables,
respectively 47% and 17% of the total number of tests showed an expected significant
103
correlation with benthic indices, except for combinations with winter samples, which were
not calculated since no significant correlations were found between the results of physicalchemical variables and benthic indices during that season. For O2, NO3, NO4, significant
correlations included both predictable (correct) and opposite to predictable (incorrect)
responses of benthic indices (Figure 4.5a). For NO3, the number of incorrect significant
correlations was higher than the correct ones and for NH4 and PC-EQR all significant
correlations were contrary to the predicted response (incorrect). Transparency is not
represented in Figure 4.5 because no significant correlations were obtained between this
variable and the results of the benthic indices.
12
10
8
6
10
4
2
0
H'
D
AMBI
W
S
N
Figure 4.3. Boxplot of the adjusted coefficient of variation for the different
biotic indices studied, species richness and abundance along season in the
Mondego River estuary. The mean, quartiles and extreme values and
indicated in each box. See methods section for abbreviations.
Margalef and Shannon-Wiener were the indices that showed the highest number of
correct significant correlations with pollution indicative variables, 21% and 19% of the total
number of tests, respectively (Figure 4.5b). Moreover, both indices showed a higher number
of correct significant correlations when considering only variables with no unpredictable
correlations (DIN and chlorophyll a), being correlated with those variables in most sampling
seasons or combinations of seasons (89% and 78% of the total number of tests, respectively)
(Figure 4.6).
104
-4.00
-2.00
0.00
Hp
4.00
0.00
1.00
2.00
F1
2.00
-2.00
Hm
Bo
-3.00
Be
Ho
Bm
-1.00
Bp
3.00
-2.00
-1.00
0.00
1.00
He
F3
-4.00
b)
-2.00
He
Bp
0.00
F1
Be
Hm
Ho
Hp
2.00
Bm
Bo
4.00
Figure 4.4. Distribution of the Mondego River estuary stations within the multidimensional space defined by the factor analysis in the
first (F1) and second (F2) factors (a) and in the first and third (F3) factors (b). Location of stations corresponding to a High (H) and Bad
(B) status are identified for each salinity habitat type, indicated by the symbols: ■ euhaline (e); ● polyhaline (p); ■ mesohaline (m) and
● oligohaline(o).
F2
2.00
a)
Seasonal variability in benthic indices
Chapter 4
105
106
3.2/ 64.7%
0.8/ 80.8%
0.7/ 94.1%
2.6/ 52.2%
1.3/ 77.9%
0.6/ 90.8%
1
2
3
0.7/ 89.3%
1.6/ 75.7%
2.2/ 43.7%
Polyhaline
1.4/ 90.4%
1.5/ 61.9%
1.6/ 31.9%
Euhaline
-0.07
-0.36
0.22
0.93
-0.32
0.44
0.33
-0.08
0.78
0.96
0.79
0.98
O2
NH4
NO3
Chl a
0.18
0.07
0.99
F2
F1
T
Com
F3
0.14
-0.12
-0.16
-0.14
1.05
(X2 = 26.3; p = 0.003)
Oligohaline
0.98
0.86
0.97
0.84
0.92
Com
-0.18
0.11
0.65
-0.46
0.33
F1
-0.17
0.55
-0.17
0.24
-0.79
F2
Mesohaline
F3
0.99
-0.32
-0.24
-0.23
-0.01
(X2 = 26.1; p = 0.004)
0.92
0.83
0.97
0.84
0.90
Com
0.01
0.19
-0.54
0.45
0.11
F1
-0.23
0.51
0.03
0.12
-0.73
F2
Polyhaline
F3
0.96
0.13
-0.20
-0.24
0.35
(X2 = 36.1; p = 0.000)
0.85
0.97
0.90
0.81
0.98
Com
0.01
0.55
0.02
0.04
-0.57
F1
0.09
0.21
-0.63
0.41
0.22
F2
Euhaline
F3
0.64
0.20
-0.07
-0.45
0.19
(X2 = 14.1; p = 0.169)
Table 4.6. Loadings of each pollution indicative variable in each factor (F1, F2 and F3) of the factorial analysis, for each
salinity habitat type identified in the Mondego River estuary. Communalties for each variable are indicated (Com), as well as
the results of the Bartlett test of sphericity (P<0.01)
Mesohaline
Eigenvalues/Cumulative percentage
Oligohaline
Factors
Table 4.5. Eigenvalues and cumulative percentages obtained for each factor in the factorial analysis for each
salinity habitat type identified in the Mondego River estuary
Seasonal variability in benthic indices
Chapter 4
Nearly 7% of the tests for AMBI were significantly correlated with pollution-indicative
variables as expected, although this index was also unpredictably correlated with some of the
variables (Figure 4.5b).
% sig. correlations
a)
50
N = 36
40
30
20
10
0
O2
NH4
NO3
DIN
Chl a
PC-EQR
% sig. correlations
b)
50
N = 54
40
30
20
10
0
H'
D
Correct
AMBI
W
Incorrect
Figure 4.5. Percentage of correct (expected) and incorrect (opposite to expected)
significant correlations (Kendall coefficient of correlation P<0.05) obtained
between pollution indicative variables and biological indices when different
combinations of seasons were tested. The total number of tests is also indicated
(N). a) percentage of significant correlations for each variable; b) percentage of
significant correlations for each biological index.
AMBI responded predictably to variations in the concentrations of DIN in summer and
when summer/autumn results were considered together, while a significant correlation with
chlorophyll a was obtained only for spring values. No significant correlations were found
between the ABC method and DIN and chlorophyll a (Figure 4.6), which was significantly
correlated only with NO3, when considering all pollution indicative variables (Figure 4.5b).
Figure 4.7 shows that correct significant correlations were found between the results of
benthic indices and the variables DIN and chlorophyll a when using data of all seasons
together, different season combinations and most single seasons. No significant correlations
were registered during winter or any season combinations that included winter, except for all
seasons. Benthic indices responded predictably to DIN concentrations when using all seasons,
107
all seasons except winter, combinations of two seasons excluding winter and every single
season, except winter. Nevertheless, significant correlations for chlorophyll a were obtained
only when using a combination of three seasons (summer, autumn and spring) and autumn and
spring data, combined and separately.
% sig. correlations
100
DIN
75
N=9
Chl a
50
25
0
H'
D
AMBI
W
Figure 4.6. Number of significant correct (expected) correlations (Kendall coefficient
of correlation P<0.05) obtained between DIN and chlorophyll a and biological indices
when different combinations of seasons were tested. The total number of tests (N) is
also indicated.
% sig. correlations
100
DIN
N=4
Chl a
75
50
25
0
All
S/A/Sp
S/A
S/Sp
A/Sp
S
A
Sp
Figure 4.7. Number of significant correct (expected) correlations (Kendall coefficient
of correlation P<0.05) obtained between DIN and chlorophyll a and biological
indices, for different combinations of seasons (All – all seasons data; S – Summer; A –
Autumn; Sp – Spring). The total number of tests (N) is also indicated.
Summer showed the highest number of significant correlations with DIN when
considering a single season, while summer-autumn was the best two-season combination for
the same variable. On the other hand, best correlations with chlorophyll a were found in
autumn as a single season, and autumn-spring when considering a two-season combination.
Correlations between indices showed that only the results of Margalef and Shannon-Wiener
108
Seasonal variability in benthic indices
Chapter 4
indices were correlated to each other in all seasons and combinations of seasons (P<0.05).
The highest correlation between these indices was obtained in autumn (r=0.778; P<0.01).
AMBI and Shannon-Wiener results were also correlated when summer-autumn combination
was considered (r=0.337; P<0.05).
DISCUSSION
Estuaries are particularly challenging due to strong spatial, seasonal and interannual
variations of environmental characteristics that influence benthic communities, mainly
hydrological conditions that change based on the volume of freshwater discharges. These
changes are particularly severe in southern European estuaries, where the annual dry period
is extended, causing higher fluctuations in the salinity regime (Elliott & McLusky, 2002).
Several studies have shown that benthic communities experience seasonal changes in
abundance and biomass, mainly related to recruitment events (e.g. Lopez-Jamar et al., 1986;
Alden et al., 1997; Sardá et al., 1999; Ducrotoy & Ibanez, 2002; Salen-Picard et al., 2002;
Reiss & Kröncke, 2005a). Some benthic indices, particularly diversity indices, are greatly
affected by such seasonal changes (Salas et al., 2004; Reiss & Kröncke, 2005b). In addition,
such seasonal changes also result in changes in species composition, greatly affecting indices
that include compositional metrics such as pollution sensitive and pollution indicative
categories. In the Mondego estuary, extreme events such as floods dramatically change
environmental conditions and consequently benthic community structure (Chainho et al.,
2006).
The present study was carried out during a flood year, when the strongest flood over
a twenty years period occurred, which seems to have a direct effect on the benthos. Biotic
classifications of condition varied greatly dependent upon the index or approach used. Similar
to previous studies, diversity indices were more variable than AMBI and ABC method (Salas et
al., 2004; Reiss & Kröncke, 2005b), since the former rely on species composition and
abundance, while the latter reflect mainly the balance between pollution indicative and
pollution sensitive species. Salas et al. (2004) corroborated these results in the Mondego River
estuary, Portugal, based in benthic samples collected fortnightly over a year, in the southern
branch of that estuary. In that study, AMBI showed less temporal variability when compared
to diversity indices, although seasonal variations are documented for the abundance and
composition of the benthic subtidal communities in the Mondego River estuary (Marques et
al., 2002; Chainho et al., 2006). The AMBI index seems to be appropriate for all European
coastal environments (Borja et al., 2003) but its application to systems with strong
109
seasonality and/or naturally high levels of stress, such as transitional or estuarine systems, is
problematic, as shown in the present study.
The WFD sets good ecological status as a major target and requires the
implementation of appropriate measures to water bodies that are classified below Good
status. Therefore, as emphasized by Quintino et al. (2006), the critical boundary between
Moderate and Good status will determine the need for applying remediation measures that
account for large costs and consequently must be carefully defined. For ecosystems lacking
reference conditions or historical data, such as the Portuguese estuaries, best professional
judgement must be used to approximate reference conditions. Professional judgement can be
used to develop a priori criteria to determine conditions indicative of minimal anthropogenic
impacts – thereby allowing determination of metrics and values for biological thresholds
indicative of the boundary between Moderate and Good status. In the development of marine
and estuarine benthic indices, such a priori criteria have primarily been either (1) physicalchemical (sediment contaminant and/or low dissolved oxygen levels, e.g. Weisberg et al.,
1997); (2) species responses to a known physical, chemical or organic gradient (e.g. Pearson &
Rosenberg, 1978; Rakocinski et al., 2000; Smith et al., 2001), or (3) best professional
judgement based upon empirical observations (e.g. Borja et al., 2000; Eaton, 2001).
The methodology proposed by Bald et al. (2005) to identify habitat types based on the
salinity Venice system seems to be adequate for the Mondego estuary, since the groups of
stations identified are ecologically meaningful over time, despite changes occurring in the
benthic communities (Chainho et al., 2006; 2007). Additionally, these groups are coincident
with water bodies identified by Ferreira et al. (2007) using a method that accounts for
environmental variables and human pressure, as recommended by the WFD.
The structure identified by the factor analysis is mainly driven by variables related to
eutrophication processes, such as nitrogen related variables and chlorophyll a, corroborating
previous studies that identify eutrophication as a major problem, at least in the southern
branch of the Mondego estuary (Martins et al., 2001; Marques et al., 2003). Based on the
physical-chemical EQR values, all oligohaline, mesohaline and polyhaline stations achieve
Good status over all seasons and euhaline stations change between classifications below and
above Good, showing that although environmental conditions are also highly variable along
the year, they still meet the criteria required for the Basque Country (Borja et al., 2004; Bald
et al., 2005). Factor analysis was developed to reduce the complexity inherent in interpreting
the results of different physical-chemical variables, by identifying relationships between
variables and representing it by a single value, but it does not seem to cope with extreme
events. For instance, the correlation between dissolved oxygen and other variables was
contradictory, which is apparently related to the fact that this variable was never limiting in
terms of negative effects on the biota (concentrations were always above 3.0 mg l-1). High
110
Seasonal variability in benthic indices
Chapter 4
levels of dissolved oxygen may not be an indicator of Good status since, as indicated by
Ferreira et al. (2002), oxygen saturation may occur in the Mondego southern branch
associated to macroalgae blooms, during spring and summer. However, such macroalgae
blooms are less likely during years of high flow (Martins et al., 2001) and would not explain
the high levels of dissolved oxygen found in the present study.
No significant correlations were found between physical-chemical EQRs and the
results of biological indices, indicating that the benthos is not responding predictably to a
combined effect of all variables. On the other hand, DIN and chlorophyll a displayed
significant correlations with all biological indices, except for the ABC method, and all
correlations were indicative of degradation of the benthic community with increasing
concentrations. Considering that these two variables are good predictors of degradation in
the Mondego estuary, in particular DIN as a primary symptom of eutrophication (OSPAR
Commission, 2003), it may be concluded that Margalef and Shannon-Wiener indices respond
better to variations in nutrient impacts than AMBI and that W-statistics does not show a
predictable response to anthropogenic pressures. This last method has been widely applied,
but Dauer et al. (1993) have draw attention to the fact that its use in estuaries is limited by
the presence of many species adapted to high levels of natural stress, exhibiting the same
response as to environmental degradation, namely the numeric dominance of short-lived
opportunistic species. This author also emphasized the influence of large-sized nonindigenous species, such as Corbicula fluminea (Müller, 1774), that can greatly affect the
results of the ABC method. Although the use of multiple indices is recommended to account
for different responses of the benthic community to stress and to create a more robust
approach, the present results indicate in creating combined metric or index approaches: (1)
the ABC method is weakly related to the eutrophication related stress and should not be
used, and (2) the Margalef and Shannon-Wiener indices are redundant and only one should be
used.
The predictability of responses of benthic indices to pollution-indicative variables also
depends on the season considered, as shown by the results of the correlations obtained for
different seasons and combinations of seasons. A more predictable response is obtained
during the dry period, while all combinations that included winter data showed no significant
correlations between biological and physical-chemical indicators. Flows can have direct
effects on benthic organisms, by physical displacement, but may also affect the benthos by
indirect paths, such as altering intermediate abiotic and biotic variables (Hart & Finelli,
1999). These complex interactions are hardly predictable, as shown by the results obtained in
this study. Data from summer and/or autumn provided the strongest and most ecologically
meaningful relationships between benthic community structure and eutrophication indicators,
specifically DIN concentrations, in the Mondego estuary. This conclusion is consistent with
111
temporal stratification applications in North American estuaries (Weisberg et al., 1997; Van
Dolah et al., 1999; Llansó et al., 2002a), although Alden et al. (1997) suggested that spring
could be included with summer when a combination of two seasons would increase statistical
power. Finally, thresholds of benthic indices used to define ecological status should be
calibrated for hydrographically and/or biogeographically different estuarine or transitional
ecosystems.
ACKNOWLEDGMENTS
This study was financially supported by two Ph.D. fellowships (SFRH/BD/5144/2001
and SFRH/ BD/6365/ 2001) granted by FCT (Science and Technology Foundation) and ESF in
the aim of the III European Community Support Framework. Project QUERE granted by
Instituto de Ambiente and project EFICAS (POCI/MAR/61324/ 2004) granted by FCT. We would
like to thank Ana Luisa Rego and Sérgio Rodrigues for their support to the field work.
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Chapter 5
Multimetric indices in different
estuaries
Chainho, P., Costa, J.L., Chaves, M.L., Costa, M.J. & Dauer, D.M. (accepted) Use of
multimetric
indices
to
classify
estuaries
with
different
hydromorphological
characteristics and different levels of human pressure. Marine Pollution Bulletin.
Multimetric indices in different estuaries
Chapter 5
Use of multimetric indices to classify estuaries with
different hydromorphological characteristics and different
levels of human pressure
ABSTRACT
The assessment of estuaries based on benthic communities is widely used to
determine impacts caused by human pressure and is one of the required tools for the
implementation of the European Water Framework Directive (WFD). Our study compared
multimetric approaches (B-IBI and TICOR) to assess the benthic condition of three Portuguese
estuaries (Mondego, Tejo, and Mira rivers) with different levels of natural and human induced
stress. Benthic community condition was classified into quality status categories of the WFD
and compared for consistency with a priori status categories based physical-chemical criteria.
Both multimetric indices discriminated equally well between locations classified above or
below the Good status category but were unable to provide good separation between other
quality classes (High/Good, Moderate, Poor/Bad). Metrics included in these indices are
greatly affected by natural stress and we recommend the development of habitat-specific
thresholds to increase the discriminatory ability of any benthic condition index.
KEYWORDS:
benthic
indices;
estuaries;
environmental
assessment;
natural
stress;
anthropogenic stress; European Water Framework Directive
119
INTRODUCTION
On a global scale, increased awareness of the biotic impacts of coastal ecosystem
pollution has stimulated efforts to develop integrative approaches to the environmental
assessment of ecological integrity that are reliable and robust. Such approaches must include
methods for habitat or water type classification and data reduction/simplification through
the use of multimetric indices. Biological criteria for identifying impaired waters have been
developed since 1972 in the USA to meet the requirements of the Clean Water Act (Gibson et
al., 2000). Likewise, the European Water Framework Directive (WFD) was approved in 2000
(2000/60/EC) to ensure a comprehensive approach across all European aquatic systems in
order to achieve Good ecological status and Good chemical status of all water bodies by 2015.
The achievement of these major quality objectives is supported by the analysis of pressures
and impacts upon the aquatic ecosystems. The development of assessment tools based on
benthic invertebrates is widely accepted because of several characteristics that make these
communities suitable indicators of environmental health (e.g. Dauer, 1993). A plethora of
benthic community assessment indices (Diaz et al. 2004) has resulted in confusion in
responding to legislative requirements for environmental protection and/or restoration. Diaz
et al. (2004) reviewed 64 benthic indices and concluded that more emphasis should be given
to validation and refinement of existing indices rather than proposing and propagating new
indices. By setting a very demanding timetable, the WFD implementation process has
encouraged European countries with less experience in using biological assessment tools to
adapt existing ones consistent with the recommendations of Diaz et al. (2004).
Numerous papers have been published over the last five years on the use of indices to
assess the benthic status of estuarine and marine water bodies, with diversity indices (e.g.
Shannon-Wiener, Hulbert), the AMBI index, the ABC method and the BQI index being the most
tested across countries (e.g. Borja et al., 2003; Bettencourt et al., 2004; Solis-Weiss et al.,
2004; Marín-Guirao et al., 2005; Muxika et al., 2005; 2007; Reiss & Kröncke, 2005; Labrune et
al., 2006; Quintino et al., 2006; Salas et al., 2006; Zettler et al., 2007). Some problems in
using these indices have been identified: (1) different conclusions of environmental condition
when applying different indices to the same data (Salas et al., 2004; Labrune et al., 2006;
Quintino et al., 2006; Chainho et al., 2007), and (2) ecological condition classifications
contrary to a priori expectations based on known pressures thus raising issues of the validity
and/or appropriate application of any given index without further calibration or modification
(Salas et al., 2004; Solis-Weiss et al., 2004; Marín-Guirao et al., 2005; Dauvin et al., 2007).
Some of the reasons indicated for the incongruence between indices and their inability to
detect pressures are (1) lack of sensitivity to different kinds of stressors and/or multiple
120
Multimetric indices in different estuaries
Chapter 5
stressors (Solis-Weiss et al., 2004; Labrune et al., 2006, Quintino et al., 2006), (2) inability to
detect subtle changes (Quintino et al., 2006), (3) inability to separate natural variability from
anthropogenic stress (Borja & Muxika, 2005; Reiss & Kröncke, 2005; Labrune et al., 2006;
Quintino et al., 2006; Chainho et al., 2007; Zettler et al., 2007) and (4) insufficient
information concerning the tolerance and/or life history strategies of species in relation to
different types of pollution (Marín-Guirao et al., 2005).
Most authors recommend the use of multiple methods based on different assumptions
or data analysis approaches in order to more robustly encompass the diverse responses of the
benthic communities to stressors (e.g. Dauer et al., 1993; Van Dolah et al., 1999; Bettencourt
et al., 2004; Borja & Muxika, 2005; Salas et al., 2006; Flåten et al., 2007). Multimetric
indices, i.e. indices that combine metrics into a single index value, should be more accurate
and robust in assessing benthic community condition compared to single metrics. Weisberg et
al. (1997) developed a benthic index of biotic integrity (B-IBI) to assess benthic community
quality in the Chesapeake Bay, with metrics and thresholds selected according to their ability
to discriminate between samples declared degraded or undegraded based upon specific
criteria including levels of bottom dissolved oxygen, sediment contaminants and total organic
carbon of the sediment. Metrics representative of diversity, abundance, biomass, feeding
guilds, and functional groups relative to pollution sensitivity were used to characterize
benthic condition in distinct habitat types. Similar approaches in developing IBI indices
occurred in other regions in the USA (e.g. Van Dolah et al., 1999; Llansó et al., 2002). The
calibration and validation of the IBI approach requires large databases, which has been
indicated as a major problem for its use in regions with little information on benthic
communities (Salas et al., 2006).
In Portugal, four indices (Shannon-Wiener, Margalef, AMBI and ABC-method) were
selected to assess the benthic condition and a combination of two or three indices (TICOR
approach) is proposed to classify the benthic status according to the requirements of the WFD
(Bettencourt et al., 2004). Presently it is unresolved and/or unreasonable to expect that any
single metric or simple index can be both representative (able to measure status and trends
that are relevant to policy decisions) and sensitive (reflects response to management actions)
(Borja & Dauer, in press) while also being broadly applicable at large biogeographical scales.
These concerns also apply to other indices that initially were considered of wide application,
such the AMBI (Borja et al., 2003; Quintino et al., 2006). This index was initially developed
for marine environments and its application to estuaries is problematic when species adapted
to the high natural stress in estuaries are also found in coastal regions (Borja & Muxika, 2005;
Chainho et al., 2006). Such species may be inappropriately classified based upon knowledge
of their distribution at the tail ends of their ecological niches in coastal waters. Indeed, for
species that are widely distributed over different habitat types, it is reasonable to expect
121
that sensitivity to natural and/or anthropocentric stresses could be habitat-dependent and
not necessarily a constant characteristic. The authors of AMBI recommend that this problem
can be addressed by changing the thresholds of quality classes instead of modifying the
assignation of species to ecological groups, since the latter would not allow comparisons
across different areas and impact types (Borja & Muxika, 2005). Likewise, the evaluation of
benthic condition based on diversity indices requires the definition of reference values for
each habitat type, since the number of species varies greatly along the salinity gradient (e.g.
Remane & Schlieper, 1971), with sediment type (e.g. Warwick et al., 1991) and presence of
aquatic vegetation (Borja & Muxika, 2005), among other variables. Other factors, such as the
presence of non-indigenous species might also influence the results of the assessment, as
emphasized by Dauer et al. (1993) and Chainho et al. (2007).
The selection of criteria to identify the ecological status of estuaries where no
reference conditions are available is an additional question that needs to be addressed. In the
B-IBI approach, only benthic metrics that showed significant differences between reference
and impacted locations were selected to integrate the index. Reference sites were chosen by
eliminating locations with known pressures (high development levels and point sources), high
contaminant levels (heavy metals and PAHs), low dissolved oxygen, high organic content and
high sediment toxicity (bioassay survival) (Weisberg et al., 1997). The WFD also requires a
Good chemical status of all water bodies, although the definition of criteria is still under
discussion. Consistent with the objectives of the WFD, the objective of the present study is to
evaluate the efficacy of these two approaches (B-IBI and TICOR) in assessing the benthic
ecological condition in ecosystems with high levels of natural variability and anthropogenic
stress.
METHODS
Study area
Three estuaries located along the western coast of Portugal were used as case studies
(Figure 5.1). All estuaries were included in type A2 – mesotidal, well mixed estuaries with
irregular river discharge, in the aim of the typology process of the WFD (Bettencourt et al.,
2004), although having different hydrological characteristics, as shown in Table 5.1.
122
Almada
Lisboa
V. F. Xira
5 Km
Barreiro
2 Km
Montemor-o-Novo
Odemira
2 Km
A – IBERIAN PENINSULA
SPAIN
V.N. Milfontes
D – MIRA
D
C
B
POR
TUG
AL
123
(C) and Mira (D) estuaries are indicated.
Figure 5.1. Location of the study areas in the Iberian Peninsula (A). Stations sampled in the Mondego (B), Tejo
C – TEJO
Cascais
B – MONDEGO
Figueira da Foz
FRANCE
Multimetric indices in different estuaries
Chapter 5
The Mondego River estuary is divided into two branches with different hydrological
characteristics, the northern branch with stronger freshwater discharges of the Mondego River
and the southern branch that drains the Pranto River and is mainly influenced by tidal
excursion (Ferreira et al. 2003). An average annual river flow of 80 m3 s-1 has been registered
in the Mondego River estuary but river flow values between 4 and 1800 m3 s-1 have been
measured, during drought and flood situations, respectively (www.inag.pt, August 2007). The
Tejo River estuary is one of the largest European estuaries (320 km2), registering an annual
average flow of 400 m3 s-1, with monthly discharges that may vary from 100 to 2200 m3 s-1.
Two distinct areas can be identified in this estuary, a large and shallow upper region,
characterized by extensive mudflats and salt marsh cover, and a deeper and narrower lower
region (Ferreira et al., 2003). The Mira River estuary is a coastal plain estuary, with a narrow
channel shape. Freshwater flow in the Mira River estuary also shows marked seasonal
changes, with an average annual flow of 10 m3 s-1, but ranging between 0 and 500 m3 s-1
(Blanton et al., 2000). Summer and winter salinities are shown in Figure 5.2, to illustrate
seasonal variations occurring in different estuarine areas.
Table 5.1. Major hydrographic characteristics of the Mondego, Tejo
and Mira estuaries and catchments land use (Nb – Northern branch; Sb
– Southern branch)
Mondego
2
Area (km )
6
-3
Volume (10 m )
3
-1
River flow (m s )
Residence time (days)
Tejo
Mira
9
320
3
21
2 200
17
80
400
10
19
14
2 (Nb)
9 (Sb)
Population (thousands)
693
2 810
24
Industry units (number)
277
294
51
102 700
276 105
12 030
Irrigated areas (ha)
Human pressure varies among the studied estuaries, with higher levels of population,
industry and agriculture use in the Tejo and Mondego estuaries than in the Mira River estuary
(Table 5.1). Eutrophication is considered a major problem in the Mondego River estuary, and
the southern branch was identified as a problem area under the designation of vulnerable
zones, while the Tejo and Mira estuaries were considered non-problem areas (Ferreira et al.,
2003). Contamination by heavy metals is well documented in the Tejo River estuary, both in
the sediments (e.g. Caçador et al., 1996) and accumulated by different levels of the food
124
Multimetric indices in different estuaries
Chapter 5
web (França et al., 2005). Negligible concentrations have been measured in the Mondego
River estuary (Chainho et al., 2006), while in the Mira River estuary some areas registered
contamination by heavy metals, although in lower levels than those found in the Tejo River
estuary (data obtained from the Portuguese Water Institute monitoring program).
Mondego
Salinity
40
30
20
10
0
MS
MS
MS
FS
FS
FS
SC
FS
FS
FS
Tejo
40
Salinity
30
20
10
0
MS MS CS MS FS SC SC MS FS SC FS SC FS SC SC CS SC SC SC SC
Mira
Salinity
40
30
20
10
0
CS
P
SC
P
SC
SC
Summer
SC
SC
SC
SC
MS
Winter
Figure 5.2. Summer and winter salinity values registered in the
Mondego, Tejo and Mira estuaries. Dominant sediment type is indicated
for each location (P – Pebbles; CS – Coarse sand; MS – Medium sand; FS –
Fine sand; SC – Silt & clay). Stations are ordered from upstream to
downstream locations (left to right).
The Mondego River estuary is characterized by profound hydromorphological changes
that occurred over the last 50 years, with the construction of the Low Mondego irrigation
125
system. The Tejo River estuary is also highly modified by embankments and the installation of
harbour infrastructures, while the Mira River estuary has only minor hydromorphological
changes, mainly embankments along the urban areas of Odemira and Vila Nova de Milfontes.
Freshwater discharge is regulated by dams located upstream in all river basins.
Sampling
Although benthic field surveys were conducted in different seasons in all estuaries,
only summer data (July 15 through September 30) was used in this study, consistent with the
development and application of the B-IBI method (Weisberg et al., 1997). Sampling surveys
took place in the years 2000 in the Mondego River estuary and 2003 in the Tejo and Mira
estuaries. Ten sampling stations were selected in the Mondego River estuary, 20 stations in
the Tejo River estuary and 11 stations in the Mira River estuary in order to be representative
of the salinity gradient and different sediment types (Figure 5.1). Three benthic invertebrate
samples were taken at each station using a modified van Veen LMG grab (0.05 m2) and grab
contents were fixed and preserved with 4% buffered formalin, sieved using a 500 µm mesh
and preserved in 70% ethanol. All samples were sorted and identified to the lowest possible
taxonomic level, in order to determine the number of taxa and their respective abundances.
Biomass of species per sample was also determined as ash free dry weight, after ignition at
450ºC. Several environmental variables were measured (1) in water: bottom dissolved oxygen,
salinity, nutrients concentrations (NO3, NO2, NH4, P), and (2) in the sediment: sediment grain
size, total organic carbon and heavy metals concentrations (As, Cr, Cu, Pb, Zn, Hg, Ni, Cd).
Methods used to determine these parameters are detailed in a previous study by Chainho et
al. (2006) for the Mondego River estuary. Chemical analyses were done by Instituto de
Ambiente and Instituto Hidrográfico, using certified methods.
Data analysis
Physical-chemical status
The WFD sets the objectives of Good ecological status and Good chemical status for
all European surface waters. The Directive also states that biological elements and
hydromophological, chemical and physical-chemical elements supporting the biological
elements have to be used in the assessment of ecological status (Ecostat, 2003). In order to
classify a water body as in Good status, physical-chemical conditions have be within a certain
range that ensures ecosystem functioning at that specific water type and meet the Ecological
Quality Standards (EQS) for specific pollutants (Ecostat, 2003). EQS are still under
development, as well as type specific thresholds for other physical-chemical elements. In this
126
Multimetric indices in different estuaries
Chapter 5
study we used criteria already developed and applied in other countries for dissolved oxygen,
nutrient enrichment and contamination by heavy metals, since no specific criteria have been
developed for Portuguese transitional waters. Only three quality classes were considered,
namely High/Good, Moderate and Poor/Bad, since available thresholds are not always
adequate for a classification into five quality classes, as required by the WFD. Dissolved
oxygen was classified according to the criteria recommended by Bald et al. (2005) (Table
5.2). These authors used background concentrations to estimate reference conditions,
weighted by salinity so that different reference conditions were defined for each of the
Venice system (1959) salinity classes (Table 5.2).
Table 5.2. Criteria used to classify the chemical status based on the concentration of heavy
metals in the sediment, nutrient concentrations in water and percentage of bottom dissolved
oxygen (ERM – effects range-median; ERL – effects range-low)
Classification
Heavy
Nutrients
metals
(µmol N/L)
Dissolved oxygen (%)
Oligohaline
High/Good
Moderate
Poor/Bad
< ERL
a
ERL – ERM b
> ERM
c
Mesohaline
Polyhaline
Euhaline
> 80.4
> 85.2
< 7.0
> 68.2
> 73.2
7.0 – 71.0
54.9 – 68.2
59.9 – 73.2
> 71.0
< 54.9
< 59.9
a
no more than two chemicals exceed ERL
b
more than two chemicals exceed ERL, but none exceeded ERM
c
more than one chemical exceed ERM
67.0 – 80.4 71.9 – 85.2
< 67.0
< 71.9
Dissolved inorganic nitrogen (DIN) was used as an indicator of nutrient enrichment,
following the criteria defined by the United States National Estuarine Eutrophication
Assessment (NEEA) (Bricker et al., 2003). Contamination by heavy metals was assessed based
on Long et al.’s (1995) effects range-medium (ERM) and effects range-low (ERL)
concentrations. Only locations where no more the two metals exceeded the ERL
concentrations were considered at High/Good status for heavy metals (Table 5.2). For DIN
and heavy metals, the same reference concentration thresholds for High/Good, Moderate and
Poor/Bad status were considered across all salinity classes because no dilution factors are
known for these parameters.
127
Benthic invertebrate status
The benthic invertebrate condition of transitional waters was assessed using two
different multimetric approaches (Tables 5.3 and 5.4), the TICOR methodology suggested by
the WFD Portuguese working group (Bettencourt et al., 2004) and the B-IBI (Weisberg et al.,
1997). The TICOR approach recommends a combination of two or three of the following four
indices, depending on the available data: (1) the Shannon-Wiener diversity index (H’) (log2),
(2) the Margalef species richness (D) (loge) (Legendre & Legendre, 1976), (3) the AMBI index
(Borja et al., 2000), and (4) the ABC-method (Warwick, 1986). The ABC-method was excluded
because previous studies showed an apparent lack of predictable response of this index to
pollution-induced stress in estuaries with strong seasonal changes (Chainho et al., 2007). All
indices were calculated for each sampling station based on the benthic invertebrate
abundance data of all replicates, using PRIMER 5.0 software package and AMBI 3.0 index
software. Bettencourt et al. (2004) provide a table with a qualitative approach on how to
determine the ecological status based on the combination of results of two or three different
indices, but not all possible combinations are presented. This problem was addressed by
converting threshold values for each index into a numerical Ecological Quality Ratio (EQR),
defined as the ratio between reference and observed values of the relevant biological quality
elements, varying between 0 and 1. The overall classification for each location was obtained
by averaging EQR values obtained for the different indices and assigning it to a quality class
according to the following ranges: High, >0.80; Good, 0.61-0.80; Moderate, 0.41-0.6; Poor,
0.21-0.4; Bad, ≤0.20. B-IBI metrics were calculated using abundance and biomass datasets,
according Weisberg et al. (1997) and Alden et al. (2002). Since benthic invertebrate species
found in the Portuguese estuaries differ significantly from those occurring in the Chesapeake
Bay, some of the metrics had to be changed or suppressed: (1) pollution-indicative taxa were
those included in ecological groups EG IV and EG V of the AMBI list, (2) pollution-sensitive
taxa were those included in EG I and EG II of the AMBI list, and (3) several metrics that could
not be calculated were not used, i.e. sediment depth related metrics, tolerance score and
Tanypodinae to Chironomidae percent abundance ratio.
Thresholds used to classify sampling locations are indicated in Table 5.3. Quality
classes were reduced to three different classifications, namely High/Good, Moderate and
Poor/Bad, since for Margalef and B-IBI indices, thresholds for all five quality classes are not
available.
A Kendall correlation coefficient was used to test for significant correlations between
the numerical results of benthic indices (Shannon-Wiener, Margalef, AMBI, EQR and B-IBI) and
the reciprocal 1/AMBI was used because AMBI is the only index with higher values
corresponding to worse quality.
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Multimetric indices in different estuaries
Chapter 5
Table 5.3.Thresholds of indices used to classify benthic invertebrate communities
Shannon-Wiener (H’)
Margalef (D)
AMBI
EQR
B-IBI
> 3.0
> 4.0
< 3.3
> 0.6
≥ 3.0
Moderate
2.0 – 3.0
2.5 – 4.0
3.3 – 5.0
0.4 – 0.6
2.7 – 2.9
Poor/Bad
< 2.0
< 2.5
> 5.0
< 0.4
< 2.6
High/Good
Comparison between benthic and physical-chemical classifications
The WFD requires the identification of the ecological status of a water body based on
the “one out all out” principle, which means that both biological and physical-chemical
elements must be at least in Good status in order to achieve the environmental objectives for
surface waters (Ecostat, 2003). Therefore, the comparison between physical-chemical and
benthic invertebrates classifications was made considering two categories of results: (1)
above Good status, which included stations classified as High and Good, and (2) below Good
status, which included stations classified as Moderate, Poor and Bad. Physical-chemical and
benthic classifications were also compared to check the agreement found for the three
classes defined (Poor/Bad, Moderate and Good/High). A G-test of independence with
Williams’ correction was used to investigate if the level of agreement between biological and
physical-chemical classifications was independent of the index used (P<0.05). A pairwise
Kendall correlation coefficient was used to test for significant correlations between the
results of the benthic indices and pollution indicative variables (dissolved oxygen,
transparency, nutrients, total organic content and heavy metals).
RESULTS
Physical-chemical status
Dissolved oxygen was consistently high in all estuaries studied (Figure 5.3) and low
oxygen levels (below 50% saturation) were measured only in the upstream stations of the Mira
River estuary, close to sewage point-source discharges. Dissolved inorganic nitrogen (DIN)
concentrations showed moderate nutrient enrichment in all three estuaries (Figure 5.3) and
some stations located in the upstream area of the Tejo River estuary registered
concentrations above 71 µmol l-1, corresponding to a Poor/Bad status. The lowest nutrient
concentrations were measured in the middle Tejo estuary and lower Mira estuary. In the
129
Mondego estuary, higher concentrations where found in the southern branch, when compared
to the northern branch. Contamination by heavy metals was not detected in the Mondego
River estuary since all measured metals registered concentrations below ERL values (Figure
5.3). The Mira River estuary was moderately contaminated (Figure 5.3), mainly due to
concentrations of As, Cu, Cd and Ni above ERL values, but low concentrations of all metals
were measured in the uppermost and downstream stations. On the other hand, the Tejo River
estuary showed some highly contaminated areas since 30% of the sampling stations were
classified as in Poor/Bad status (Figure 5.3), mainly near industrial areas.
Concentrations of Hg and Zn exceeded ERM values, while all other heavy metals,
except for Ni, exceeded ERL values (Figure 5.3). According to the WFD, the general
classification of the physical-chemical status has to be based on the poorest status obtained
for any physical-chemical element. The general physical-chemical status in each studied
estuary was based on that requirement and, as shown in Figure 5.3, most locations are at a
Moderate status, with some areas of the Tejo and Mira estuaries classified as in a Poor/Bad
status. There was a single station, located near the mouth of the Mira River estuary that met
the objective of Good status for all physical-chemical elements considered.
Benthic invertebrate status
Both methods used to identify the ecological status based on the benthic communities
classified most stations below Good status. TICOR classified 20%, 25% and 0% of the stations
located in the Mondego, Tejo and Mira River estuary stations, respectively, as Good in status,
while the B-IBI classified 20%, 15% and 9% of stations as Good in status (Figure 5.4). The B-IBI
classified most stations in all three estuaries as Poor/Bad (70%, 75%, 91%, respectively for the
Mondego, Tejo and Mira River estuary stations) while the TICOR approach classified most
stations as Moderate in status (50%, 45%, 55%, respectively for the Mondego, Tejo and Mira
River estuary stations) (Figure 5.4). Among TICOR component indices, AMBI identified a higher
number of stations as Good in status in the Mondego and Mira estuaries than the ShannonWiener and Margalef indices (Figure 5.4).
Kendall coefficient of correlation showed that Shannon-Wiener and Margalef indices
were highly correlated in the Mondego (r=0.689; P<0.0001) and Tejo estuaries (r=0.731;
P<0.0001) and were more correlated to EQR values than the AMBI in all estuaries (Table 5.4).
All indices were correlated to each other in the Tejo estuary, including the B-IBI, in contrast
to the Mira estuary, where significant correlations were found only between the diversity
indices and the EQR value.
130
80%
100%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
0%
40%
60%
Mondego
High/Good
Moderate
Tejo
80%
Poor/Bad
Physico-chemical status
20%
Nutrients
Mira
100%
Figure 5.3. Classifications obtained in the Mondego, Tejo and Mira estuaries based on physical-chemical elements. The results of
the different types of pollution indicative elements (dissolved oxygen, nutrients and heavy metals) are also shown.
0%
Mira
Tejo
Mondego
60%
Heavy metals
40%
Mira
Mira
20%
Tejo
Tejo
0%
Mondego
Mondego
Dissolved oxygen
Multimetric indices in different estuaries
Chapter 5
131
TICOR
100%
80%
60%
40%
20%
0%
Mondego
Tejo
Mira
Shannon-Wiener, Margalef & AMBI
100%
80%
60%
40%
20%
0%
H'
D
AMBI
H'
D
Mondego
AMBI
Tejo
H'
D
AMBI
Mira
B-IBI
100%
80%
60%
40%
20%
0%
Mondego
Tejo
High/Good
Moderate
Mira
Poor/Bad
Figure 5.4. Classifications obtained in the Mondego, Tejo and Mira
estuaries using TICOR and B-IBI approaches. The results of the different
TICOR metrics (Shannon-Wiener, Margalef and AMBI indices) are also
shown.
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Multimetric indices in different estuaries
Chapter 5
Table 5.4. Significant correlations (Kendall coefficient of correlation
obtained between different biological indices and between indices
and pollution indicative variables for each estuary. The total number
of stations is indicated (N). H’ – Shannon-Weiner Index, D – Margalef
Index, AMBI –AZTI Marine Biotic Index, EQR – Ecological Quality Ratio,
B-IBI – Benthic Index of Biotic Integrity, DIN – Dissolved Inorganic
Nitrogen
Mondego
Tejo
Mira
(N=10)
(N=20)
(N=11)
H' - D
0.689**
0.731***
-
H' - AMBI
-
0.480**
-
H' - EQR
0.689**
0.850***
0.673**
H' - B-IBI
-
0.517**
-
D - AMBI
-
-
-
D - EQR
0.733**
0.754***
0.564*
D - B-IBI
-
0.343*
-
AMBI - EQR
0.556*
0.484**
-
AMBI - B-IBI
-
0.378*
-
EQR - B-IBI
-
0.466**
-
H' - DIN
-0.867**
-
-
D - DIN
-0.733**
-
-
EQR - DIN
-0.556*
-0.326*
-
* p<0.05; ** p<0.01; *** p<0.001
The benthic species composition was different between estuaries, as shown in
Table 5.5, with more than twice the number of taxa identified in the Tejo compared to the
Mondego and Mira estuaries. Conversely, mean density in the Mondego River estuary was more
than twice that found in the other two estuaries, while the mean biomass was very similar in
the Mondego and Tejo estuaries, but much lower in the Mira River estuary (Table 5.5).
Polychaetes and amphipods were the dominant groups in all three estuaries, although
different species dominated in each estuary and bivalves were better represented in the
Mondego River estuary (Table 5.5). These differences were also reflected in the composition
and density of the pollution indicative, pollution sensitive and tolerant species, as shown in
Figure 5.5, representing the density and number of species of each EG identified according to
133
the AMBI list of species (Borja et al., 2000). Tolerant species (EG III) were dominant in all
estuaries, with higher densities in the Mondego and Mira estuaries than in the Tejo.
Nevertheless, the number of taxa identified as pollution sensitive (EG I and II) in the Tejo
River estuary was higher than all other EGs within the same estuary and compared to all EGs
of the remaining estuaries (Figure 5.5).
Table 5.5. Biological descriptive parameters for the Mondego, Tejo and Mira estuaries. The
mean density (ind m-2) and biomass (g m-2) and the total number of taxa are indicated for each
estuary. Ten most abundant taxa (dominants) are listed (see Appendix 1 for complete list of
taxa) with their respective contributions to total density and the indication of the Class in
bold (A- Amphipoda; B- Bivalvia; G- Gastropoda; I- Insecta; Is- Isopoda; N- Nemertea; OOligochaeta; P- Polychaeta; n.i. – not identified)
Mondego River estuary
Tejo River estuary
Mira River estuary
Mean
Density
4 582
2 104
1 969
Mean
Biomass
2.57
2.73
0.44
71
143
68
N. of Taxa
Streblospio shrubsolii (35%)P
Chaetozone setosa (26%)P
Corophium multisetosum (16%)A Streblospio shrubsolii (17%)P
Corophium orientale (27%)A
Boccardiella redeki (13%)P
Hydrobia ulvae (13%)G
Corophium acherisicum (10%)A Leptocheirus pilosus (12%)A
Tubificoides sp. (6%)O
Tubificoides sp. (10%)O
Alkmaria romijni (10%)P
Tetrastemmatidae n.i. (5%)N
Pisione remota (7%)P
Polydora cornuta (4%)P
Hediste diversicolor (6%)P
Cerastoderma glaucum (3%)B
Corbula gibba (4%)B
Streblospio shrubsolii (6%)P
Chaetozone setosa (2%)P
Boccardiella redeki (2%)P
Chironomidae n.i. (5%)I
Echytraeus sp. (2%)O
Cossura coasta (2%)P
Cyathura carinata (3%)Is
Spio martinensis (2%)P
Limnodrilus hoffmeisteri (1%)O Corophium acherisicum (2%)A
Dominant Scrobicularia plana (4%)B
species Corbicula fulminea (4%)B
Comparison between benthic and physical-chemical classifications
Using our criteria defined to classify physical-chemical elements, only one station located in
the Mira River estuary was classified as in Good status, while the benthic indices indicated a
higher number of stations above Good status. The level of agreement of the benthic indices
and the physical-chemical classification is not significantly independent of the index used
when considering only stations classified above or below Good status neither when all classes
were considered, as shown by the result of the G-tests of independence (Table 5.6).
134
Multimetric indices in different estuaries
Chapter 5
Number of species
50
40
30
20
10
0
EG I
EG II
EG III
EG IV
EG V
Density (ind/m 2)
4000
3000
2000
1000
0
EG I
EG II
EG III
Mondego
Tejo
EG IV
EG V
Mira
Figure 5.5. Number and density of taxa included in each Ecological
Group (I, II, III, IV and V), as defined by Borja et al. (2000), for
Mondego, Tejo and Mira estuaries.
A gradient of agreement between AMBI (lowest agreement) and B-IBI (highest
agreement) is clear when below or above Good status is considered. When using two status
categories (above or below Good), the agreement between biological and physical-chemical
results was highest for the B-IBI (87.8%). The TICOR approach resulted in a 78.1% level of
agreement while the lowest agreement level was obtained using the AMBI index (65.8%).
When all quality classes were considered (Poor/Bad, Moderate and Good/High), the best
agreement between physical-chemical and biological classifications was obtained with the
TICOR approach (53.7%), and the worst when using B-IBI (26.8%) (Table 5.6).
The level of agreement when considering all classes was much lower for all indices
and there was a higher percentage of stations matching the physical-chemical classification
using TICOR than any of the component indices alone (Table 5.6). AMBI and B-IBI were the
only indices that classified correctly the single station identified as in a Good physicalchemical status.
135
Table 5.6. Level of agreement (%) between status categories determined by the
biological indices/approaches compared to status categories determined by physicalchemical elements. Data for the three estuaries were combined. A. Two status
categories, i.e., stations classified above or below Good status. B. Three status
categories, i.e., stations classified as High/Good, Moderate and Poor/Bad. Results of
a G-Williams test conducted to investigate if the frequency of agreement is
independent of the index used are also shown
Shannon
Margalef
AMBI
TICOR
B-IBI
75.6%
85.4%
65.8%
78.1%
87.8%
46.9%
41.5%
48.8%
53.7%
26.8%
-Wiener
A. Above/below Good status
(GW = 7.141; p = 0.128; df = 4)
B. All classes
(GW = 6.986; p = 0.137;df = 4)
Kendall correlations between the benthic indices and physical-chemical variables
indicated significant correlations in the Mondego and Tejo River estuaries, with Shannon-Wiener, Margalef and EQR results correlated with DIN concentrations (P<0.01) (Table 5.4).
DISCUSSION
Indices of biotic integrity have long been recognized as useful tools to measure
biological responses to pollution, identify the need to apply mitigation measures and evaluate
the efficiency of those measures, mainly because these indices: (1) are documented to
accurately reflect both watershed level stressors and resulting exposure variables (Dauer et
al., 2000; Salas et al., 2006), (2) reduce large amounts of data to a meaningful single value,
and (3) are valuable tools to communicate complex data to a general audience (Weisberg et
al., 1997; Aubry & Elliott, 2006).
Nevertheless, the efficiency of indices depends on a predictive understanding of the
responses of the component metrics of the index to environmental stress and disturbance, at
multiple spatial and temporal scales (Andersen, 1997), that might vary considerably between
the region for which they were developed and other regions where they might be used.
The present study compared two multimetric indices, B-IBI and TICOR approach, in
estuaries with different hydromorphological characteristics and different human pressures,
namely the Mondego, Tejo and Mira estuaries. B-IBI was developed using a priori specific
physical-chemical criteria (i.e., bottom-water dissolved oxygen concentrations, levels of
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Multimetric indices in different estuaries
Chapter 5
sediment contaminants, and/or total organic carbon of the sediment) to: (1) identify samples
considered undegraded, degraded or indeterminate, (2) select metrics based upon significant
differences, in an ecologically meaningful manner, between undegraded and degraded data,
and (3) determine thresholds for scoring each metric, using only data from samples declared
undegraded. As such, the B-IBI approach relies upon reference or minimally-impacted
conditions. In contrast, the TICOR approach is based solely upon best professional judgment
to determine thresholds for each of the component indices and the combined index.
Physical-chemical reference conditions
Most studies recently published on the efficiency of benthic indices to separate
between degraded and undegraded conditions are based on prior knowledge of pressures
acting over different locations (Salas et al., 2004; 2006; Labrune et al., 2006; Quintino et al.,
2006) or using physical-chemical indicators (Weisberg et al., 1997; Paul et al., 2001; Marín-Guirao et al., 2005). The latter approach was used in the present study since no reference
conditions were available and the results indicate that none of the estuaries seems to meet
the WFD objective of Good physical-chemical status. Eutrophication problems in the Mondego
River estuary and contamination by heavy metals in the Tejo River estuary are well
documented, but the Mira River estuary has been characterized as a relatively pristine
ecosystem (Marques et al., 1993; Carvalho et al., 2005). Nevertheless, physical-chemical
elements measured during the present study showed significant concentrations of nutrients
and metals, as well as the occurrence of low oxygen levels in some areas of the Mira River
estuary. These results confirm the effect of known pollution sources, such as the Odemira
sewage discharge, the irrigation perimeter of the Mira catchment area and mining activities
that used to occur in upstream areas.
In determining between quality classes using physical-chemical indicators, specific
threshold values separating quality classes are assumed to have a meaningful relationship to
pollution-induced alterations in benthic populations. While the use of ERM and ERL values is
widely accepted as a reference for heavy metals contamination (e.g. Weisberg et al., 1997;
Mucha et al., 2003), criteria for dissolved oxygen and eutrophication descriptors still lack
consensus among the scientific community. According to the criteria of the United States
National Estuarine Eutrophication Assessment (NEEA) or the OSPAR Comprehensive procedure,
oxygen concentrations ranging between 2 mg l-1 and 5-6 mg l-1 may cause stress responses in
invertebrate fauna (Bricker et al., 2003; OSPAR Commission, 2003). The application of either
the NEAA or OSPAR dissolved oxygen criteria to our study would have produced very similar
classifications to ours, but using the criteria of Weisberg et al. (1997) would have resulted in
all stations classified as undegraded, since dissolved oxygen concentrations were consistently
137
high along time (unpublished data). On the other hand, the OSPAR Commission criteria for
DIN, based on background concentrations, are much less stringent than the NEEA criteria,
since concentrations of 44 µmol l-1 and 34 µmol l-1were defined for the Mondego and Tejo
estuaries, respectively, as corresponding to non-problem areas in terms of eutrophication
(OSPAR Commission, 2003). The five uppermost stations of the Mondego River estuary and
eight stations of the Tejo River estuary would have been classified as Good for nutrients if the
OSPAR criteria had been applied. No background concentrations are indicated for the Mira
River estuary. These background concentrations, defined as the lowest winter concentrations
measured in those estuaries, have to be used with some caution since the oldest monitoring
records were registered in the early 80’s, when estuaries were already under considerable
human pressure. Bricker et al. (2003) consider that nutrients are not a robust descriptor of
eutrophication in estuaries and use the NEAA approach to identify problem and non-problem
areas, based on several indicators of pressure, state and response of the aquatic system
(Bricker et al., 2003). Based on the NEAA methodology, the Mondego River estuary was
identified as a potential problem area by Ferreira et al. (2003), while the Tejo and Mira
estuaries were considered non problem areas. Nevertheless, this evaluation was based on
data from only the lower Mira River estuary. In spite of the lower level of human pressure in
the Mira River basin when compared to the Mondego and Tejo river basins (Table 5.1), this
estuary is also subject to nutrient enrichment, at least in upstream areas, because of a low
flow, particularly during the dry period.
Biological indices
Diversity
Diversity was an attribute considered in both B-IBI and TICOR, but the former
considered habitat specific thresholds, while the latter adopted reference values defined for
marine communities in Norway. Diversity indices are, in general, good indicators of change in
the community structure but their use as an indicator depends on the natural heterogeneity
of the communities studied, since diversity is an ambiguous concept and there is no single
definition of high and low diversity. When no reference conditions are available, diversity can
only be useful for comparing communities from different locations and/or tracking temporal
changes a benthic community at a specific site.
The Shannon-Wiener diversity index is very popular among ecologists as a measure of
variety and abundance of organisms, since it incorporates a species richness component, but
also a species evenness component (Magurran, 2005), while the Margalef index is considered a
species richness index (Read et al., 1978). In this study, the Shannon-Wiener and Margalef
indices showed highly correlated results, thus their simultaneous use as responsive metrics is
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Multimetric indices in different estuaries
Chapter 5
redundant and overemphasizes the diversity component of TICOR, as indicated by the
correlation levels of these indices and the EQR values in all estuaries. As pointed out by some
authors (Izsák, 2007; Chainho et al., 2007), the use of correlated indices does not contribute
additional information, therefore only one of these indices should be used. The ShannonWiener is more widely used and has been included in the majority of papers published on
comparing different indices to assess ecological status (e.g. Salas et al., 2004; Labrune et al.,
2005; Marín-Guirao et al., 2005; Quintino et al., 2006). Thus it is more suitable for
comparisons across estuaries.
Redundancy is also not considered by the metric selection criteria used in B-IBI, since
all candidate metrics that showed significant differences between degraded and reference
locations and were ecologically meaningful were retained in the index (Weisberg et al., 1997;
Van Dolah et al., 1999; Llansó et al., 2002). Paul et al. (2001) developed a multimetric index
for the Virginian Province, conceptually similar to the B-IBI, but using stepwise discriminant
analysis to select the best subset of metrics for separating between degraded and reference
sites. Some problems concerning the use of this statistical method, such as failure to select
the best subset of variables of a given size, sampling error capitalization and the use of
incorrect number of degrees of freedom have also been identified and Hulberty (1989)
suggests a previous elimination of variables with no predictive validity and variables highly
correlated with other variables as an alternative for reducing the number of metrics. An
alternative approach to minimize redundancy in multimetric indices would be to combine the
results of related metrics (e.g. diversity and dominance indices) into a single value prior to
combining it with other metrics, to balance the contribution of different attributes of the
benthic community. The indication of the logarithmic base and the abundance data type
(abundance per replicate, density, etc.) used to calculate diversity indices must be specified,
in order to assure their correct use based on specific thresholds, such as those defined in B-IBI
and TICOR.
Pollution-indicative and pollution-sensitive taxa
Biotic indices have long included information on the tolerance and sensitiveness of
species to pollution. The B-IBI includes pollution-sensitive and pollution-indicative metrics
using either abundance or biomass estimates while the TICOR approach includes the
abundance of taxa placed into five ecological groups corresponding to different tolerance
levels (using the AMBI index). For the B-IBI a two-step procedure was used to determine which
species to include in the pollution-sensitive and pollution-indicative metrics (Weisberg et al.,
1997). First a candidate list of species for both metrics was developed using the literature
and prior knowledge of each candidate species. Second, for the pollution-sensitive metric a
139
candidate species had to have a higher abundance in reference samples compared to
degraded samples while candidate species for the pollution-indicative metric had to have a
higher abundance in degraded samples compared to reference samples. The assignation of
species by the AMBI index was based on literature addressing the sensitivity/tolerance of taxa
to organic enrichment (Borja et al., 2000).
In the present study, the AMBI index seems to overestimate the benthic status in all
estuaries, contributing to the overall higher category obtained with TICOR. The tendency for
overestimation when using AMBI has been mentioned by other authors. Marín-Guirao et al.
(2005) and Quintino et al. (2006) attributed AMBI’s overestimation of ecological status to the
development of the AMBI based on the species’ tolerance to organic pollution, which might
make this index less sensitive to other types of pollution such as metal contamination and
physical disturbance. The weight given to dominant species has also been indicated as leading
to misclassification, since diversity and the number of species are not considered (Labrune et
al., 2006). The effect of the dominance of tolerant species is reflected in the three different
estuaries studied, as mentioned before by Dauvin et al. (2007). Tolerant species such as
Streblospio shrubsolii (Buchanan, 1890) and Corophium spp. (both in EG III) are dominant in
the Mira and Mondego River estuaries, therefore constraining the AMBI results towards a
general classification of stations into Good status. In contrast, the more balanced distribution
of species by ecological groups in the Tejo River estuary gives more weight to relative
abundance of species included in other groups. On one hand, the higher species richness in
the Tejo River estuary seems to reflect a higher diversity of habitat types, as shown by
different combinations of sediment types and salinity classes. On the other hand, the higher
number of sensitive species (EG I and EG II) also indicates that these species find favourable
conditions for their settlement in the Tejo River estuary, regardless of the overall highest
pollution levels. Furthermore, the number of species and their distribution among ecological
groups is very similar in the Mondego and Mira estuaries, but density and biomass are
considerably higher in the Mondego River estuary, which seems to be an indication of nutrient
enrichment.
Both estuaries are under severe natural stress caused by seasonal and daily changes in
salinity and freshwater flow and periodically affected by floods and droughts. Extreme events
have severe impacts on benthic communities and affect the results obtained when using
biotic indices (Chainho et al., 2006; 2007) in the Mondego River estuary, where the number of
taxa and their respective abundances decreased significantly after a flood. Droughts also
influence the estuarine water quality because freshwater flow is reduced and temperatures
increase, lowering dissolved oxygen levels and increasing salinity (Attrill & Power, 2000),
which corresponds to what was observed in the Mira River estuary during summer. The
ecological process of community succession, widely documented after Pearson & Rosenberg
140
Multimetric indices in different estuaries
Chapter 5
(1978), can be greatly affected by natural environmental variability (Rakocinski et al., 2000),
such as salinity fluctuation in estuarine environments or even be interrupted by disturbance
events (Boesch et al., 1976). Ritter et al. (2005) show that a salinity-stressed estuary is in a
constant state of early to intermediate succession and there is no climax community but a
constant replacement of tolerant species, according to the existing environmental conditions.
The distribution of species by ecological groups in the Mondego and Mira estuaries is
consistent with Ritter et al.’s (2005) characterization of a salinity-stressed estuary, i.e.
dominance of tolerant species and low representation of pollution sensitive and pollution
indicative species. In contrast, a higher number of pollution sensitive species was identified in
the Tejo River estuary when compared to tolerant species, but pollution indicative species
assigned to ecological group IV were very representative, giving some evidence of the
presence of different successional states.
Multimetric indices
As emphasized by Borja & Dauer (in press), the use of indices to identify impacts of
human pressure over ecosystem function requires that these indices are appropriately applied
in space and time and generate results that are interpreted in an acceptable manner. In the
present study we tested two multimetric approaches developed for different biogeographical
regions, including one proposed for assessing the ecological status of Portuguese transitional
waters (TICOR). A previous study by Chainho et al. (2007) pointed out some problems related
to the applicability of TICOR without prior temporal stratification due to strong seasonal
changes in the Mondego estuary. In this study, only summer data was considered and all
different salinity habitats were covered in each estuary.
The classifications obtained in the Mondego, Tejo and Mira estuaries using different
benthic indices show that the level of agreement between physical-chemical classifications
and benthic classifications were not significantly different among indices used. The
discrimination between stations above or below Good physical-chemical status level was
higher than when three classification levels (Poor/Bad, Moderate and Good/High) were used,
suggesting that none of these indices is sensitive to smaller differences in status, as referred
to by Quintino et al. (2006). This seems to indicate the need for a geographical adaptation of
the metrics and thresholds of both indices, similarly to what has been referred by other
authors (e.g. Van Dolah et al., 1999; Salas et al., 2006, Blanchet et al., in press; Borja &
Dauer, in press), since the B-IBI was developed specifically for the Chesapeake Bay and TICOR
is composed of indices whose thresholds were also defined for other biogeographic regions.
Additionally, as indicated by the correlation between pollution indicative variables and
benthic indices, only diversity indices seem to respond to the stressors measured and only to
141
nutrient related ones, corroborating the results of Chainho et al. (2007). Nevertheless, in the
Mira River estuary there is no apparent response of the indices to stressors and only AMBI and
B-IBI identified the only station in a Good status. The low diversity and richness found in this
estuary is apparently the reason for the worse classification by B-IBI and TICOR, when
compared to the Mondego and Tejo estuaries.
All indices were correlated to each other in the Tejo estuary, while in the Mondego
and Mira estuary only some TICOR components were related. Having no evidence that this
fact relies on different pressure levels, it seems likely to be related to differences in
hydrographical characteristics. The Tejo estuary is one of the largest European estuaries,
with a water volume and residence time much higher than the other estuaries studied, acting
as a buffer that reduces variations in parameters such as salinity, temperature and sediment
composition. In contrast, the Mondego and Mira estuaries register strong variations in
environmental conditions, not only across seasons but also daily variations associated with the
tidal cycle. In the Mira estuary salinity amplitudes of 25 units were registered between
seasons and measurements along the tidal cycle showed variations up to 15 units during a
flood period (unpublished data). As pointed out by Ritter et al. (2005), frequent disturbances
in environmental conditions, such as salinity changes, prevent the establishment of
equilibrium species and the benthic communities remain in a constant state of early to
intermediate succession. This seems to explain the strong correlation between all indices
tested in the Tejo estuary, similarly to what had been found in the Chesapeake Bay (Borja et
al., in press), since communities characterized by high diversity and pollution-sensitive
species were identified in some locations, whereas low diversity and pollution-tolerant
species are found in other locations.
CONCLUSIONS
The WFD guidance document on ecological status states that the mismatch between
the biological and physical-chemical monitoring results may be an indication that the
biological methods used are not sensitive to the effects of anthropogenic changes,
emphasizing the need to improve biological methods (Ecostat, 2003). The present study
showed that hydromorphological differences between estuaries included in the same WFD
type (A2) may confound and complicate the classification process, both for physical-chemical
and biological elements.
The use of physical-chemical parameters to define reference conditions still lacks
consensus among experts and the benthic communities do not always show predictable
responses to all types of stressors. Both the B-IBI and the TICOR approach seem to be efficient
142
Multimetric indices in different estuaries
Chapter 5
in discriminating between locations above or below Good status, as required by the WFD, but
were much less efficient in discriminating other quality classes, indicating the need for
further adaptation and validation of metrics. The use of diversity can be misleading in
estuaries with a natural low diversity, as stressed by Puente et al. (in press), but this problem
could be addressed by defining different thresholds for each habitat type, following the
approach used in the B-IBI. Metrics related to the tolerance of species to pollution stress also
need some adjustments in estuaries with strong natural pressures, since the dominance of
tolerant species often overestimates the ecological status, especially in the case of the AMBI.
This could imply the development of separate sets of metrics and thresholds for the Tejo
estuary and for the Mondego and Mira estuaries, since benthic communities are under
different levels of natural stress.
The future use of indices to classify the benthic status in Portuguese estuaries will
require a better understanding of the spatial and temporal patterns of the invertebrate
communities. In estuaries with almost no knowledge available on the benthic community
patterns, such as the Mira estuary, a greater monitoring effort will be needed before being
able to adapt existing benthic indices to an acceptable level of confidence. Ferraro et al.
(1991) concluded that the effect of natural disturbances on the benthos may sometimes be
greater than the effect of wastewater discharge and recommend long term studies (≥6 years)
to reliably discriminate between them. The monitoring frequency required by the WFD for the
benthic fauna (every 3 years) seems consequently inappropriate for a consistent assessment
of the benthic status of estuarine systems with similar characteristics to Mondego and Mira
River estuaries.
AKNOWLEDGEMENTS
This study was financially supported by two Ph.D. fellowships (SFRH/BD/5144/2001
and SFRH/ BD/6365/2001) granted by FCT (Science and Technology Foundation) and ESF in
the aim of the III European Community Support Framework, project QUERE granted by
Instituto de Ambiente, and projects ERIC (FCT/P/MAR/15263/1999) and EFICAS
(POCI/MAR/61324/2004) granted by FCT. We would like to thank Ana Luisa Rego, Sérgio
Rodrigues, Nuno Prista, Rita Vasconcelos, Manuel Cabral and Tadeu Pereira for their support
to the field work.
143
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Chapter 6
Final Remarks
Final Remarks
Chapter 6
Final Remarks
The implementation of the Water Framework Directive required the development of
ecological assessment tools in European countries. Some of these countries have well
developed scientific backgrounds and monitoring programs that include biological elements.
In contrast, in some other countries these elements were not included in the monitoring
programs and no specific tools were available for assessment of the ecological status when
the WFD was agreed upon, such is the case for Portugal. Therefore, the implementation of
this Directive was particularly demanding and the most feasible solution to accomplish a very
demanding timetable was an adaptation of existing tools. The main objective of this study
was to investigate if the characteristics of the Portuguese estuaries constrained the use of
existing assessment tools for evaluating ecological status based on benthic invertebrate
communities.
The development and use of benthic biotic indices is grounded in several ecological
assumptions of the responses of benthic communities to human induced stress. For instance,
it is assumed that in degraded conditions (1) species diversity is lower (e.g. Green, 1979); (2)
opportunistic species are more representative than pollution-sensitive species (e.g. Weisberg
et al., 1997; Borja et al., 2000; Paul et al., 2001); (3) abundance is dominated by smallbodied species (e.g. Warwick, 1986); (4) there is a higher deposit feeders/suspension feeders
ratio (e.g. Dauvin et al., 2007), deep-burrowers are less abundant (e.g. Rosenberg, 2001);
and (5) there is a lower phylogenetic diversity (Clarke & Warwick, 1998). However,
particularly in estuaries, there are also natural factors of stress that may produce similar
responses in benthic communities, making difficult to separate between natural and
anthropogenic sources of stress. Moreover, the natural spatial and temporal gradients of
environmental conditions within estuaries confounds and potentially constrains the use of tools
developed for other regions, e.g. coastal ecosystems.
Spatial and seasonal patterns
Benthic communities show high spatial heterogeneity in estuaries related to the
influence of natural gradients of a diversity of factors. Estuarine benthic communities include
both eurytopic species with broad habitat distributions and stenotopic species with narrow
habitat distributions. In addition to spatial patterns, temperate estuarine invertebrate
communities also show important temporal variations related to seasonal and interannual
changes. The Mondego River estuary was used as a case study to investigate the patterns of
distribution of the benthic invertebrate communities in a poikilohaline estuary, i.e. an estuary
with great changes in environmental conditions, particularly in salinity. Three major groups of
communities were identified, based on spatial distribution patterns: (1) a lower sector with
151
stronger marine influence dominated by the polychaete Streblospio shrubsolii (Buchanan, 1890)
and the bivalve Cerastoderma glaucum (Poiret, 1789); (2) a middle sector dominated by S.
shrubsolii and the amphipod Corophium multisetosum Stock, 1952; (3) and an upper sector
where C. multisetosum dominated a community characterized by a lower number of species
and the presence of an introduced bivalve species, Corbicula fulminea (Müller, 1774), in
considerably high numbers (Chapter 2). These spatial groups were mainly determined by the
salinity gradient, although salinity changed dramatically across seasons. In spite of
considerable differences in the species composition when compared to other Portuguese
estuaries, the patterns of distribution of major taxonomic groups in the Mondego are very
similar to those found in the Minho (Sousa et al., 2007), Ria de Aveiro (Moreira et al., 1993)
and Mira estuaries (Andrade, 1986), with a transition between the numerical dominance of
bivalve, polychaete and amphipod species, from downstream to upstream stations (Chapters 2
and 3).
Species composition changes between seasons were mainly related to variations in
freshwater flows. The impacts upon benthic communities were even more dramatic during
extreme events, such as floods, with a significant decrease in the number of taxa and their
respective abundances, as observed in the Mondego estuary (Chapter 2). Environmental
conditions during the flood period resulted in considerable differences (e.g. lower salinity,
different sediment composition, higher nutrient concentrations) and most species were
classified as opportunists (Chapters 2 and 4). These results corroborated other studies
indicating that benthic communities inhabiting estuaries with seasonal floods and/or droughts
will change (1) due to pulses of organic matter during floods that stimulate an increase in
abundance of opportunistic species (Salen-Picard & Arlhac, 2002); (2) changes in the water
quality conditions, such as higher concentrations of contaminants during droughts (Attrill &
Power, 2000; Grange et al., 2000) and (3) potential colonization by alien species that are, in
general, much more tolerant to salinity fluctuations than native species (Lee & Bell, 1999;
Paavola et al., 2005). In general, the consequences of floods are more dramatic than droughts
because the first occur in a short period of time with great intensity and have immediate
effects (e.g. mortality) on the benthic communities, while the latter occur during a prolonged
period with more gradual effects (e.g. colonization by marine species).
In spite of the strong changes observed in the structure of the Mondego estuarine
benthic community, the pattern of aggregation of stations based upon their similarity was
consistent over seasons, except for a transition station that changed groups in different
seasons (Chapter 3). The overall station group consistency supports the definition of three
main ecological types in the northern branch of the Mondego River estuary, namely the Lower
Estuary, the Middle Estuary and the Upper Estuary. Nevertheless, within each of these three
station groups the Venice salinity classes varied greatly between seasons, ranging from
oligohaline to polyhaline in some areas of the estuary, depending upon the freshwater flow
regime (Chapter 3). This scenario seems to fit into the ecocline concept introduced by Boesch
152
Final Remarks
Chapter 6
(1977) and further discussed by Attrill & Rundle (2002), defined as a boundary of progressive
change between two systems, freshwater and marine. The latter proposed a two ecocline
model, with two overlapping salinity gradients, one from upriver to mid estuary for
freshwater species and another extending from the sea to the mid-estuary for marine species,
whose associated benthic communities change location along the estuary in relation to
changes in freshwater flow. In the Mondego estuary, seasonal changes in freshwater flow act
as an environmental gradient and euryhaline estuarine species and freshwater species shift
their distributions in relation to the associated changes in salinity.
In conclusion, the Venice system cannot be used to stratify poikilohaline estuaries
into salinity regions without modification, such as the methodology suggested by Bald et al.
(2005) using different salinity measures (minimum, maximum, mean and standard deviation).
This methodology was successfully applied to the Mondego estuary, producing habitat types
that were ecologically meaningful (Chapter 4).
Influence of seasonal variability in the use of benthic indices
Most of the indices currently used to assess benthic status were developed, applied
and/or validated for coastal marine ecosystems and their application to estuarine ecosystems
that have strong temporal and spatial heterogeneity must be cautiously considered and
rigorously validated. Several USA monitoring programs addressed temporal variability by
selecting summer as the period for application of indices (e.g. Weisberg et al., 1997; Paul et al.,
2001; Smith et al., 2001; Llansó et al., 2002). In temperate regions, the measured response of
the benthos as indicated by benthic community metrics should be maximal during this period
due to the biological responses to the effects of increased water temperatures, water column
stratification, and occurrence of bottom low dissolved oxygen conditions (Alden et al., 1997). In
Europe no recommendations were proposed regarding either the modelling of seasonal
variability or the selection of an optimal time period to apply the available classification tools.
There are known responses of benthic indices to some seasonal cycles, especially recruitment
events (Reiss & Kröncke 2005), but few studies have examined how benthic indices respond in
ecosystems with strong seasonality. Seasonal samples collected in the Mondego estuary
showed that indices proposed for use in Portuguese estuaries (Shannon-Wiener and Margalef
diversity indices, ABC method and AMBI) generate different results when applied in different
seasons. Similar to previous studies, diversity indices were more variable than the AMBI index
and the ABC method (Salas et al., 2004; Reiss & Kröncke, 2005), because the former relies on
species richness and abundance, while the latter reflect mainly the balance between
pollution indicative and pollution sensitive species (Chapter 4).
These results confirmed the need for temporal stratification and the identification of
the best period for application of indices was determined based on the predictability of
responses of benthic indices to physical-chemical pollution-indicative variables, because no
153
reference conditions were available. The critical boundary between Moderate and Good
status was used as a criterion to examine the predictability of responses because remediation
measures are required by the WFD for all water bodies below Good status. Following the
method proposed by Bald et al. (2005), factor analysis was used to reduce the complexity
inherent in interpreting the results of different physical-chemical variables, by identifying
relationships between variables and representing them by a single value (Ecological Quality
Ratio). Nevertheless, this method of representing a combined effect of all variables does not
adequately characterize extreme events because no predictable responses of the benthic
indices were obtained in the Mondego estuary (Chapter 4). In contrast, DIN and chlorophyll a
displayed significant correlations with all biological indices, except for the ABC method, and
all correlations were indicative of degradation of the benthic community with increasing
concentrations (Chapter 4). Data from summer and/or autumn provided the strongest and
most ecologically meaningful relationships between benthic community structure (Chapter 4)
and eutrophication indicators - specifically DIN concentrations (Chapters 4 and 5), consistent
with temporal stratification applications in North American estuaries (Weisberg et al., 1997;
Van Dolah et al., 1999; Llansó et al., 2002).
Adequacy of existing indices to classify the benthic status of Portuguese estuaries
According to the TICOR approach proposed for application in Portuguese estuaries,
two or three of four indices (Shannon-Wiener and Margalef diversity indices, the ABC method
and the AMBI index) should be used to assess ecological status, depending on the type of data
available (Bettencourt et al., 2004). The results obtained in the Mondego estuary showed that
no predictable responses were obtained when using the ABC method, not even during the best
season for application of the indices (summer/autumn) (Chapter 4). For that reason, this
index was not selected when testing the use of multimetric indices (Ticor and B-IBI) in
different estuaries during the dry period.
Three estuaries located along the western coast of Portugal and included in type A2 –
mesotidal, well mixed estuaries with irregular river discharge – were used as case studies.
Although in the same type in the aim of the typology process of the WFD, these estuaries
have different hydrological characteristics. The Tejo estuary is the largest Portuguese
estuary, with higher river flow, longer residence time and higher levels of human pressure
than the Mondego and Mira estuaries. These characteristics strongly influence environmental
conditions as seen by nutrient enrichment measured in the Mira estuary in spite of the lower
level of human pressure in this River basin when compared to the Mondego and Tejo river
basins (Chapter 5).
Most studies recently published on the efficiency of benthic indices to separate
between degraded and undegraded conditions are based on prior knowledge of pressures
acting over different locations (Salas et al., 2004; 2006; Labrune et al., 2006; Quintino et al.,
154
Final Remarks
Chapter 6
2006) or using physical-chemical indicators (Weisberg et al., 1997; Paul et al., 2001; Marín-Guirao et al., 2005). The latter approach was used in the present study since no reference
conditions were available and the results indicate that none of the estuaries seems to meet
the WFD objective of Good physical-chemical status. Eutrophication problems in the Mondego
River estuary and contamination by heavy metals in the Tejo River estuary are well
documented, but the Mira River estuary has been characterized as a relatively pristine
ecosystem (Marques et al., 1993; Carvalho et al., 2005). Nevertheless, physical-chemical
elements measured during the present study showed significant concentrations of nutrients
and metals, as well as the occurrence of low oxygen levels in some areas of the Mira River
estuary (Chapter 5). The use of physical-chemical indicators to identify different levels of
pressure seems promising, although needing some improvement on the identification of
relationships between pressures and impacts in estuaries with different hydrologic conditions,
such as those studied here (Chapters 4 and 5).
The classifications obtained in the Mondego, Tejo and Mira estuaries using different
benthic indices show that the level of agreement between physical-chemical classifications
and benthic classifications were not significantly different among indices used (Chapter 5).
Some attributes included in both multimetric approaches (TICOR and B-IBI), such as diversity
indices and pollution-indicative and pollution-sensitive taxa were examined in more detail.
Although diversity indices showed predictable responses to pollution indicative variables, the
definition of thresholds for ecological classification must be calibrated by the natural
heterogeneity of the communities studied. This requires a very detailed knowledge of the
diversity patterns along the estuarine gradient, which might vary significantly across
estuaries, as indicated by differences found between the three studied systems. Moreover,
the use of more than one diversity measure can be redundant (Izsák, 2007) and
overemphasize the weight of this ecological feature in the final result of multimetric
approaches (Chapter 4 and 5). In the view of the wider use of the Shannon-Wiener index,
which has been included in the majority of papers published on comparing different indices to
assess ecological status (e.g. Salas et al., 2004; Labrune et al., 2005; Marín-Guirao et al.,
2005; Quintino et al., 2006), this index seems to be more suitable for comparisons across
estuaries. The use of information on the sensitiveness/tolerance of invertebrate taxa to
pollution through indices such as the AMBI also revealed some problems related to the high
levels of natural stress, that favour the dominance of opportunistic species, such as
S. shrubsolii and Corophium spp. and the results obtained in this study indicate an
overestimation of the benthic status when using this index (Chapters 4 and 5), as it was found
in other locations (Marín-Guirao et al., 2005; Quintino et al., 2006). For both type of metrics
(diversity and sensitiveness/tolerance), the selection of species from a candidate list based
on confirmed differences in abundance between reference samples and degraded samples and
the definition of habitat specific thresholds, such as proposed in the B-IBI (Weisberg et al.,
1997) seems preferable.
155
None of the indices tested in Portuguese estuaries seems to be sensitive to smaller
differences in status, because the discrimination between stations above or below Good
physical-chemical status level was higher than when three classification levels (Poor/Bad,
Moderate and Good/High) were used (Chapter 5), as previously found by Quintino et al.
(2006). This indicates the need for a geographical adaptation of both indices (see e.g. Van
Dolah et al., 1999; Salas et al., 2006, Blanchet et al., in press; Borja & Dauer, in press).
Ecological adaptations of invertebrates in stressed estuaries and how they affect
the use of benthic assessment tools
The application of a single index across a strong environmental gradient and/or
numerous habitat types is difficult and confounded by our ability to separate the effects of
natural and anthropogenic stresses. All indices tested in this study are strongly influenced by
natural stress, limiting their use without modification (Chapters 4 and 5) and the results
obtained, compared to the known levels of pressure over the estuarine systems suggested
that natural and anthopogenic sources of stress may be acting together (Chapters 2, 3, 4 and
5). Diversity is an ambiguous concept and there is no single definition of high and low
diversity but, in general, highly stressed environments show lower diversity (e.g. Sanders,
1968; Kinne, 1971). This requires the identification of natural patterns of variation of the
number of species and their abundance along estuarine gradients and across estuaries.
The ecological process of community succession, widely documented after Pearson &
Rosenberg (1978), can be greatly affected by natural environmental variability (Rakocinski et
al., 2000), such as salinity fluctuation in estuarine environments, or even be interrupted by
disturbance events (Boesch et al., 1976). Ritter et al. (2005) show that a salinity-stressed
estuary is in a constant state of early to intermediate succession and there is no climax
community but a constant replacement of tolerant species, according to the existing
environmental conditions. The distribution of species by ecological groups in the Mondego and
Mira estuaries is consistent with Ritter et al.’s (2005) characterization of a salinity-stressed
estuary, i.e. dominance of tolerant species and low representation of pollution sensitive and
pollution indicative species. In contrast, a higher number of pollution sensitive species was
identified in the Tejo River estuary when compared to tolerant species, but pollution
indicative species were also very representative, giving some evidence of the presence of
different successional states (Chapter 5).
Succession in benthic communities is likely to be frequently interrupted in highly
dynamic estuaries (e.g. the Mondego and Mira estuaries) characterized by strong seasonal
fluctuations in the environmental conditions and drastic changes induced by the occurrence
of extreme events (floods and droughts), benthic communities’ succession processes are likely
to be frequently interrupted. It is important to understand how resilient are benthic
communities, and how will they evolve after these short-term perturbations and to which
156
Final Remarks
Chapter 6
extent induced changes in the benthic community will affect the assessment of ecological
status. For instance, Ferraro et al. (1991) concluded that the effect of natural disturbances
on the benthos may sometimes be greater than the effect of wastewater discharge and
recommend long term studies (≥6 years) to reliably discriminate between them. The
monitoring frequency required by the WFD for the benthic fauna (every 3 years) seems
consequently inappropriate for a consistent assessment of the benthic status of estuarine
systems with similar characteristics to Mondego and Mira River estuaries.
Even indicators based on the functional structure of the benthic communities, such as
the ABC method, have a limited use in naturally stressed estuaries, because of the presence
of many species adapted to high levels of natural stress, exhibiting the same response as to
environmental degradation, namely the numeric dominance of short-lived opportunistic
species (Dauer et al., 1993), as it was found in the Mondego estuary (Chapter 4).
All indices were correlated to each other in the Tejo estuary, while in the Mondego
and Mira estuary only some TICOR components were related (Chapter 5). Having no evidence
that this fact relies on different pressure levels, it seems likely to be related to differences in
hydrographical characteristics.
High levels of natural stress, such as those found in the Mondego and Mira estuaries,
seem to act as a brake to speciation, as referred by Kinne (1971) and fewer representatives of
phyletic groups are evolved in such way to allow their successful colonization of the estuarine
environment. A much higher number of species was found in the Tejo estuary than in the
Mondego and Mira estuaries, these last characterized by a high number of monotypic taxa
(Chapters 3 and 5). As pointed out by Ferraro & Cole (1992, 1995), the dominance of
monotypic taxa increases the probability of taxonomic sufficiency at taxonomic levels higher
than species, mainly because of redundancy in their responses to pollution. The Mondego
estuary benthic community showed over 70% of monotypic genera and families. As a
consequence, for typological purposes taxonomic levels up to the order can be used without
significant loss of information in poikilohaline estuaries (Chapter 3). Moreover, the family
level is most likely the best compromise since most taxonomic manuals are more adequate for
identifications at this level and ecologists with taxonomic training are familiar with the
procedures. The use of different taxocenes for typology was also tested, demonstrating less
ability to identify water body types. Nevertheless, mollusks and bivalves have identified the
same types as all species and annelids have shown a habitat specific distribution, in particular
the family Spionidae (Chapter 3). These findings were confirmed by results obtained in the
Mira estuary on the use of different taxonomic levels and taxocenes (unpublished data).
157
CONCLUSIONS
As a general conclusion of this study, there is strong evidence that the characteristics
of Portuguese estuaries constrain the use of existing assessment tools for evaluating
ecological status based on benthic invertebrate communities. The application of the indices
proposed for Portuguese estuaries in the aim of the WFD (TICOR) and a multimetric approach
developed for North American estuaries (B-IBI) seem to be efficient in discriminating between
locations above or below Good status, as required by the WFD, but are much less efficient in
discriminating other quality classes. Nevertheless, the classifications obtained do not reflect
only differences on the level of degradation, but also spatial and temporal variations
indicating the need for further adaptations before a standard use in Portuguese estuaries.
Some other questions were addressed in the present study and the major conclusions can
be summarized as follows:
1. Spatial patterns of distribution of the benthic communities in Portuguese estuaries
are mainly determined by the salinity gradient, as in estuarine systems of other
regions, but seasonal variations in freshwater flows alter those patterns dramatically,
especially during the occurrence of extreme events. These constrains require spatial
and temporal stratification of sample collection for monitoring purposes, since the
derivation of reference conditions applicable to all estuarine gradient and different
seasons does not seam feasible;
2. Seasonal variations on the composition of benthic communities change the results of
benthic indices and the respective classification of the benthic ecological status. The
results of this study point towards a more efficient use of benthic indices during the
dry period;
3. The response of benthic invertebrate communities to natural and anthropogenic
sources of stress is very similar and there seems to be a better discrimination in
estuaries with lower variations in environmental conditions, such as the Tejo estuary.
For that reason, indices and metrics developed for homiohaline estuaries seem to be
more appropriate for use in this estuary than in others with dominant poikilohaline
characteristics, such as the Mondego and Mira estuaries, for which metrics and
thresholds need some adjustments before use;
4. Existing indices seem to be efficient in separating between benthic communities
above and below Good status, but not accurate enough for discrimination of other
quality classes, as required by the WFD. Consequently, novel combinations of metrics
and class boundaries should be proposed and validated;
158
Final Remarks
Chapter 6
5. Multimetric indices seem to be more robust to possible misclassifications than
individual metrics, but these metrics require further adaptation and validation before
inclusion in the method selected for future use in Portuguese estuaries;
6. No reference conditions based upon pristine conditions were found in the three
estuaries studied, but physical-chemical variables and nutrient concentrations in
particular seem to be a good surrogate for testing the efficiency of benthic indices;
7. Speciation processes seem to be affected in estuaries with strong environmental
fluctuations, which show a dominance of monotypic taxa, supporting the use of higher
taxonomic levels in the typology process;
FUTURE RESEARCH LINES
A scientific study is never the final answer for a question, but solely the “tip of the
iceberg” that generates working hypotheses. This study provided some evidence on the
problems and possible solutions for the application of benthic indices in Portuguese estuaries,
but also raised new challenges for future work, such as:
-
Identification of reference conditions – The development of a method based on
existing reference conditions, as B-IBI, require the selection of habitat specific
reference sites. Since all Portuguese estuaries are, at least, minimally impacted, a
selection of a representative number of reference sites does not seem feasible in a
short-term period. Selecting a pilot estuary with lower human pressure, such as the
Mira estuary, and applying mitigation measures that reduce significantly the current
impacts could serve as a case study to understand the natural evolution of benthic
communities that are under natural stress and use it as a reference for estuaries with
similar characteristics (e.g. Mondego estuary);
-
Selection of metrics – the selection of metrics to be included in benthic indices to be
used in Portuguese estuaries might imply that different metrics and thresholds are
used in different habitats, within and among estuaries. A comprehensive examination
of the responses of different metrics of communities exposed to diverse natural and
anthropogenic levels of stress is needed;
-
Long term studies – the definition of monitoring programs in the aim of the WFD
require a better understanding of inter-annual changes on the benthic communities,
to determine their resilience and the length of the recovery period before they reach
equilibrium, after being disturbed by natural events (e.g. floods and droughts). A
temporal stratification of the monitoring programs might not be compatible with the
monitoring frequency indicated by the WFD;
159
Biogeographical differences and climate changes - Portugal is a transition area, with
-
a recognized boundary between assemblages northern to Cape Carvoeiro southern to
the Tejo estuary. With increased effects of the climate change on the latitudinal
distribution of species, a gradual change of the composition of benthic communities is
also expected. A possible effect of these changes on the use benthic assessment tools
might require particular concern, since strong differences in the taxonomic
composition across different regions might influence the performance of indices.
The first two questions are currently being addressed by several studies developed by
different Portuguese research teams in different estuaries and also by the Portuguese working
group. These challenges might also be partially carried out through the ongoing
intercalibration process, in which different countries are adjusting class boundaries by
comparing classifications obtained for the same water types using different methods. The
third question requires a national monitoring/research policy that favours long term
monitoring/research studies, promoting the compilation of a thorough and systematic
database on the benthic communities of all Portuguese estuaries. The last question requires
that taxonomic skills are recognized as an important scientific competency and some funds
are allocated for training taxonomists publishing taxonomic compendiums on the Portuguese
fauna.
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163
Appendix 1
List of taxa identified in the
Mondego, Tejo and Mira estuaries
Mondego
Phyllum Cnidaria
Class Anthozoa
Order Actiniaria
Family Actiniidae
Actinia equina (Linnaeus, 1758)
Phyllum Plathyelmintha
Class Turbellaria
Turbellaria n.i. (Turb)
Phyllum Nemertea (Neme)
Family Tetrastemmatidae
Tetrastemmatidae n.i.
Family Tubulanidae
Tubulanidae n.i.
Phyllum Annelida
Class Oligochaeta (Olig)
Family Echytraeidae
Echytraeus sp. (Echy)
Family Naididae
Chaetogaster sp.
Nais sp. (Nais)
Naididae wncs
Paranais sp.
Family Tubificidae (Tubi)
Brachiura sowerbyi Beddard 1892
Limnodrilus hoffmeisteri Claparède, 1862 (Lhof)
Tubifex tubifex (Müller, 1774)
Tubificidae wcs
Tubificidae wncs
Tubificoides sp.
Uncinais uncinata (Ørsted, 1842)
Class Polychaeta
Family Ampharetidae
Alkmaria romijni (Grube, 1863) (Arom)
Melinna palmata Grube, 1870
Family Aphroditidae
Aphroditidae n.i.
Family Capitellidae
Capitella capitata (O. Fabricius, 1780) (Ccap)
Heteromastus filiformis (Claparède, 1864) (Hfil)
Mediomastus fragilis Rasmussen, 1973 (Mfra)
Notomastus linearis Claparède, 1870
Notomastus profundus Eisig, 1887
Tejo
Mira
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Mondego
Family Cirratulidae
Aphelochaeta sp.
Caulleriella A
Caulleriella alata (Southern, 1914)
Caulleriella bioculata (Keferstein, 1862)
Chaetozone gibber Woodham & Chambers, 1994
Chaetozone setosa Malmgren, 1867 (Cset)
Cirratulus sp.
Tharyx A
Timarete tentaculata (Treadwell, 1941)
Family Cossuridae
Cossura coasta Bogdanos & Fredj, 1983
Family Dorvilleidae
Staurocephalus kefersteini McIntosh, 1869
Family Eunicidae
Marphysa sanguinea (Montagu, 1815)
Family Glyceridae
Glycera alba (O.F. Müller, 1776)
Glycera convoluta Keferstein, 1862
Glycera gigantea de Quatrefages, 1866 (Ggig)
Glycera tesselata Grube, 1863
Glycera tridactyla Schmarda, 1861
Family Goniadidae
Glycinde nordmanni (Malmgren, 1865)
Goniada emerita Audouin & Milne-Edwards, 1833
Goniada maculata Örsted, 1843
Goniada norvegica Audouin and Milne-Edwards, 1833
Family Hesionidae
Hesionidae n.i. (Hesi)
Ophiodromus flexuosus (Delle Chiaje, 1825)
Psamathe cirrata Keferstein, 1862
Family Lumbrineridae
Lumbrineris coccinea (Renier, 1804)
Scoletoma impatiens (Claparède, 1868)
Family Nephtydidae
Nephtys caeca (Fabricius, 1780)
Nephtys cirrosa Ehlers, 1868 (Ncir)
Nephtys hombergii de Lamarck, 1818 (Nhom)
Nephtys hystricis McIntosh, 1900
Nephtys incisa Malmgren, 1865
Nephtys longosetosa Oersted, 1842
Nepthys pulchra Rainier, 1991 (Npul)
X
Tejo
Mira
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Mondego
Family Nereididae
Alitta succinea (Frey & Leuckart, 1847)
Hediste diversicolor (O.F. Müller, 1776) (Hdiv)
Neanthes fucata (Savigny, 1818)
Websterinereis glauca (Claparède, 1870) (Wgla)
Family Onuphidae
Diopatra neapolitana delle Chiaje, 1841 (Dnea)
Family Opheliidae
Ophelia radiata (Delle Chiaje, 1828)
Family Orbinidae
Scoloplos armiger (Müller, 1776) (Sarm)
Family Oweniidae
Myriochele heeri Malmgren, 1867
Owenia fusiformis Delle Chiaje, 1842 (Ofus)
Family Pectinariidae
Pectinaria koreni (Malmgren, 1866) (Pkor)
Family Pholoidae
Pholoe minuta (Fabricius, 1780)
Family Phyllodocidae
Eteone picta de Quatrefages, 1866 (Epic)
Eumida sanguinea (Örsted, 1843) (Esan)
Family Pilargiidae
Pilargiidae n.i.
Sigambra constricta (Southern, 1921)
Sigambra tentaculata (Treadwell, 1941)
Family Pisionidae
Pisione remota (Southern, 1914)
Family Poecilochaetidae
Poecilochaetus serpens Allen, 1904
Family Poligordiidae
Polygordiidae n.i.
Family Polynoidae
Harmothoe benthophila Hardy & Gunther, 1935
Harmothoe impar (Johnston, 1839)
Family Sabellariidae
Sabellaria alveolata (Linnaeus, 1767)
Sabellaria spinulosa Leuckart, 1849
Sabellariidae n.i.
Family Protodriliidae
Protodrylus hatscheki Pierantoni, 1908
X
X
Tejo
X
Mira
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Mondego
Family Sabelariidae
Sabellaria alveolata (Linnaeus, 1767)
Sabellaria spinulosa Leuckart, 1849
Sabellariidae n.i.
Family Sabellidae
Jasmineira candela (Grube, 1863)
Family Saccocirridae
Saccocirrus papillocercus Bobretzky, 1872
Familidae Serpulidae
Pomatoceros triqueter (Linnaeus, 1767)
Family Sigalionidae
Sthenelais boa (Johnston, 1833)
Family Spionidae
Aonides oxycephala (Sars, 1862)
Boccardiella ligerica (Ferronnieère, 1898) (Blig)
Boccardiella redeki (Horst, 1920)
Malacoceros fuliginosus (Claparède, 1868)
Polydora ciliata (Johnston, 1838) (Pcil)
Polydora cornuta Bosc, 1802
Polydora websteri Hartman in Loosanoff & Engle, 1943
Prionospio cirrifera Wirén, 1883 (Pcir)
Prionospio malmgreni Claparède, 1870
Pygospio elegans Claparède, 1863
Scolelepis bonnieri (Mesnil, 1896)
Scolelepis cantabra (Rioja, 1918)
Spio martinensis Mesnil, 1896 (Smar)
Streblospio shrubsolii (Buchanan, 1890) (Sshr)
Family Syllidae
Autolytus sp.
Exogone sp.
Parapionosyllis cabezali Parapar, San Martín & Moreira,
2000
Pionosyllis pulligera (Krohn, 1852)
Sphaerosyllis bulbosa Southern, 1914
Sphaerosyllis taylori Perkins, 1981
Sphaerosyllis torulosa
Family Terebellidae
Lanice conchilega (Pallas, 1766)
Class Hirudinea
Hirudinea n.i.
Tejo
Mira
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Mondego
Phyllum Arthropoda
Class Crustacea
Order Ostracoda
Ostracoda n.i.
Order Tanaidacea
Family Paratanaidae
Heterotanais oerstedi (Kroyer, 1842)
Leptochelia dubia Kroyer, 1842
Leptochelia savignyi Kroyer, 1842
Family Tanaidae
Tanais dulongii (Audouin, 1826)
Order Mysidacea
Family Mysidae
Acanthomysis longicornis (Milne-Edwards, 1837)
Gastrosacus spinifer (Goës, 1864) (Gspi)
Leptomysis gracilis (GO Sars, 1864)
Mesopodopsis slabberi (van Beneden, 1861)
Neomysis integer (Leach, 1814)
Order Isopoda
Family Anthuridae
Cyathura carinata (Kroyer, 1847) (Ccar)
Family Chaetiliidae
Saduriella losadai Holthuis, 1964 (Slos)
Family Cirolanidae
Eurydice naylori Jones & Pierpoint 1997
Eurydice spinigera Hansen, 1890
Family Gnathiidae
Paragnathia formica (Hesse, 1864)
Family Idoteidae
Family Sphaeromatidae
Lekanesphaera hookeri (Leach, 1814) (Lhok)
Lekanesphaera rugicauda (Leach, 1814)
Order Amphipoda
Amphipoda sp1
Amphipoda sp2
Family Ampeliscidae
Ampelisca diadema (Costa, 1853)
Ampelisca lusitanica Bellan-Santini & Marques, 1987
Ampelisca spinifer Reid, 1951
Family Amphilochidae
Amphilochus brunneus Della Valle, 1893
Amphilochus manudens Bate, 1862
Amphilochus neapolitanus Della Valle, 1893
Tejo
Mira
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Mondego
Gitana sarsi Boeck, 1871
Family Amphitoidae
Amphitoe sp.
Family Aoridae
Leptocheirus pilosus Zaddach, 1844
Family Atylidae
Atylus massiliensis Bellan-Santini, 1975
Family Corophiidae
Corophium acherusicum Costa, 1851
Corophium multisetosum Stock, 1952 (Cmul)
Corophium crassicorne Bruzelius, 1859
Corophium orientale Schellenberg, 1928
Family Gammariidae
Gammarus subtypicus Stock, 1966
Gammaridae n.i.
Family Haustoridae
Haustorius arenarius (Slabber, 1769)
Family Hyalidae
Hyale pontica Rathke, 1837
Family Ischyroceridae
Ericthonius punctatus (Bate, 1857)
Jassa ocia (Bate, 1862)
Family Melitidae
Abludomelita obtusata (Montagu, 1813)
Melita obtusata (Montagu, 1813)
Melita palmata (Montagu, 1804) (Mpal)
Family Oedicerotidae
Pontocrates altamarinus (Bate & Westwood, 1862)
Family Phoxocephaliidae
Metaphoxus pectinatus (Walker, 1896)
Family Pontoporeiidae
Bathyporeia sarsi Watkin, 1938
Family Urothoidae
Urothoe brevicornis Bate, 1862
Urothoe intermedia Bellan-Santini & Ruffo, 1986
Order Cumacea
Family Bodotriidae
Bodotria scorpioides (Montagu, 1804)
Cumopsis goodsir (Van Beneden, 1861)
Iphinoe tenella Sars, 1878
Order Astacidea
Family Diogenidae
Diogenes pugilator (Roux, 1829)
Tejo
X
Mira
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Mondego
Order Cirripeda
Family Chtamalophiidae
Chthamalus montagui Southward, 1976
Order Decapoda
Family Crangoniidae
Crangon crangon (Linnaeus, 1758)
Family Processidae
Processa canaliculata Leach, 1896
Family Palaemonidae
Palaemon longirostris H. Milne-Edwards, 1837
Family Pirimelidae
Pirimela denticulata (Montagu, 1808)
Family Portunidae
Carcinus maenas (Linnaeus, 1758)
Class Insecta
Order Colembola
Colembola n.i.
Order Diptera
Family Ceratopogonidae
Ceratopogonidae n.i.
Family Chironomidae
Chironomidae n.i. (Chir)
Family Rhagionidae
Rhagionidae n.i.
Order Ephemeroptera
Ephemeroptera n.i.
Family Caenidae
Caenis sp.
Family Polymitarcidae
Ephoron virgo (Olivier, 1791) (Evir)
Order Plecoptera
Family Leuctridae
Leuctridae n.i.
Phyllum Mollusca
Class Gastropoda
Family Hydrobiidae
Hydrobia ulvae (Pennant, 1777) (Hulv)
Family Nassariidae
Hinia reticulata (Risso, 1826)
Family Rissoidae
Rissoa parva (da Costa, 1778)
Tejo
X
X
X
Mira
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Mondego
Class Bivalvia
Family Anomiidae
Anomia ephippium Linnaeus, 1758
Family Cardiidae
Acanthocardia paucicostata (Sowerby G.B. II, 1841)
Cerastoderma edule (Linnaeus, 1758)
Cerastoderma glaucum (Poiret, 1789) (Cgla)
Parvicardium exiguum (Gmelin, 1791)
Family Corbiculariidae
Corbicula fulminea (Müller, 1774) (Cful)
Family Corbulidae
Corbula gibba (Olivi, 1792)
Family Hiatellidae
Hiatella arctica (Linnaeus, 1767)
Family Lucinidae
Dictyota divaricata J.V. Lamouroux, 1809
Loripes lacteus (Linnaeus, 1758)
Family Mactridae
Spisula solida (Linnaeus, 1758)
Family Mytilidae
Modiolus barbatus (Linnaeus, 1758) (Mbar)
Musculus costulatus (Risso, 1826)
Mytilus edulis Linnaeus, 1758
Mytilus galloprovincialis Lamarck, 1819
Family Nuculidae
Nucula hanleyi Winckworth, 1931
Nucula nucleus (Linnaeus, 1758)
Nucula turgida Marshall 1875
Family Ostreidae
Ostrea edulis Linnaeus, 1758
Family Pectinidae
Chlamys septemradiata (Müller O.F., 1776)
Chlamys varia (Linné, 1758)
Family Pholadidae
Barnea candida (Linnaeus, 1758)
Family Sareptidae
Yoldiella sp.
Family Scrobiculariidae
Scrobicularia plana (da Costa, 1778) (Spla)
Abra alba (Wood W., 1802)
Family Solenidae
Solen marginatus Pulteney, 1799 (Smarg)
Tejo
Mira
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Family Tellinidae
Angulus tennuis (da Costa, 1778) (Aten)
Family Veneridae
Ruditapes decussatus (Linnaeus, 1758)
Tapes rhomboides (Pennant, 1777)
Venerupis senegalenis (Gmelin, 1791)
Venerupis saxatilis (Fleuriau de Bellevue, 1802)
Venus casina Linnaeus, 1758
Class Polyplacophora
Family Ischnochitonidae
Lepidochitona cinerea (Linnaeus, 1767)
Class Opisthobranchia
Opisthobranchia n.i. (Nudi)
Phyllum Echiura
Class Ophiuroidea
Family Ophiuridae
Ophiuridea n.i.
Family Ophiolepidae
Ophiolepidae n.i.
Mondego
X
Tejo
X
X
X
X
X
X
X
X
X
X
Mira
X