GREEN et al.
Tropical Ecology 50(1): 41-56, 2009
© International Society for Tropical Ecology
www.tropecol
41
ISSN 0564-3295
The importance of monitoring biological diversity and its application in
Sri Lanka
MICHAEL J.B. GREEN*, RIC HOW, U.K.G.K. PADMALAL & S.R.B. DISSANAYAKE
Department of Wildlife Conservation, 382 New Kandy Road, Malabe, Sri Lanka
Abstract: Sri Lanka, together with the Western Ghats in southern India, is one of the 34
global hotspots for biological diversity. Much of this diversity, in terms of species, is endemic to
the island. While much of Sri Lanka’s flora and fauna has been collected and described prior to
the 20th century, quantitative information about their distribution and status is limited, and
many new species continue to be discovered. The Department of Wildlife Conservation has
recently embarked on an ambitious initiative to benchmark and subsequently monitor key
taxonomic groups of plants and animals that occur within its protected areas. This is in line
with the Convention on Biological Diversity, which requires Member States to identify and
monitor the components of biological diversity important for its conservation and sustainable
use. This paper considers the importance of monitoring biological diversity, reviews current
methodologies and describes the approach developed for protected areas in Sri Lanka.
Resumen: Sri Lanka, junto con los Gates Occidentales del sur de la India, es uno de los 34
puntos calientes de la diversidad biológica del planeta. Mucha de esta diversidad, en términos
de especies, es endémica de la isla. Si bien gran parte de la flora y la fauna de Sri Lanka fue
recolectada y descrita antes del siglo XX, la información cuantitativa sobre su distribución y
estatus es limitada, y se siguen descubriendo muchas especies nuevas. El Departamento de
Conservación de la Vida Silvestre se embarcó recientemente en una iniciativa ambiciosa para
establecer la información básica sobre los grupos taxonómicos clave de plantas y animales que
están presentes en sus áreas protegidas y su monitoreo subsiguiente. Este proyecto responde a
la Convención sobre Diversidad Biológica, la cual requiere que los Estados firmantes
identifiquen y monitoreen los componentes de la diversidad biológica que son importantes para
su conservación y uso sostenible. Este artículo reflexiona sobre la importancia de monitorear la
diversidad biológica, revisa las metodologías actuales y describe el enfoque desarrollado para
las áreas protegidas en Sri Lanka.
Resumo: O Sri Lanka, juntamente com os Ghates ocidentais no sul da Índia, é um dos 34
pontos quentes para a diversidade biológica. Muita desta diversidade, em temos de espécies, é
endémica da ilha. Enquanto muita da flora e fauna do Sri Lanka foi colectada e descrita antes
do século 20, a informação quantitativa da sua distribuição e status é limitada, e muitas novas
espécies continuam a ser descobertas. O Departamento de Conservação de Vida Selvagem
embarcou recentemente numa iniciativa ambiciosa para definir o estado actual e monitorizar,
subsequentemente, os grupos taxonómicos chave das plantas e animais que ocorrem no interior
das áreas protegidas. Isto está em linha com a Convenção para a Diversidade Biológica, a qual
requer aos Estados Membros a identificação e monitorização dos componentes importantes
para a sua conservação e uso sustentado. Este artigo considera a importância da monitorização
da diversidade biológica, revê as metodologias actuais e descreve a abordagem desenvolvida
para as áreas protegidas do Sri Lanka.
*
Corresponding Author; 33 The Close, Norwich, NR1 4DZ, United Kingdom; e-mail: [email protected]
42
BIODIVERSITY MONITORING IN SRI LANKA
Key words: Biodiversity, benchmark, baseline, gradsect, hotspot, inventory, monitor,
sample, survey, Sri Lanka.
Introduction
What is biological diversity?
Biological diversity, that is, the variety of life
on Earth1 resulting from millions of years of
evolution and thousands of years of cultivation of
plants and domestication of animals, can be
described at many levels, from DNA and genes to
species, population, communities and ecosystems.
It is often considered in terms of the diversity of
genes, species and ecosystems – three fundamental
and hierarchically-related levels of biological
organisation (WCMC 1992).
Identifying and monitoring biological diversity
is a huge and potentially infinite task given its
variability in time and space and its spectrum of
levels. For most practical purposes of conserving
biological diversity in situ (i.e. in the wild, rather
than ex situ in ‘captive’ collections of plants and
animals), it is sufficient to focus on species and
ecosystems. Only in a few cases where species are
limited to one or two very small population may it
be necessary to monitor diversity at the genetic
level to mitigate against potential inbreeding and
extinction. This paper focuses largely on species
diversity, the variety of living organisms, including
micro-organisms, fungi, plants and animals. It is
measured by the total number of species within a
given area of study. Species diversity is linked to
the survival of ecosystems and the services that
they provide, many of which directly benefit
human welfare. When a species disappears, it can
affect a whole ecosystem, as can the appearance of
an invasive or exotic species.
1
It is defined in the Convention on Biological
Diversity as “... the variability among living organisms
from all sources including, inter alia, terrestrial, marine
and other aquatic ecosystems and the ecological
complexes of which they are part; this includes diversity
within species, between species and of ecosystems.”
[Article 2]
Why identify and monitor biological diversity?
Understanding biological diversity in terms of
the processes by which ecosystems and their
components function, be it at community, species,
population or genetic levels, is critical to informing
its sustainable use and safeguarding it for the
benefit of future generations. Given that biological
diversity is dynamic, continually evolving and
changing in response to biotic and abiotic
fluctuations and other environmental pressures, it
is necessary to record in time and space (i.e.
benchmark) its status quo and, subsequently,
monitor that status quo in order to identify
changes and assess their impacts. Such impacts
may require intervention or mitigation measures
to safeguard the future conservation, including
sustainable use, of biological diversity. Crucially
important is the need to identify species present in
areas of natural habitat ahead of any changes in
land use in order to assess what diversity may be
lost from a locality. This is particularly pertinent
to tropical ecosystems, where levels of endemism
tend to be higher than in more temperate regions
and, consequently, the risks of species becoming
globally extinct may be greater.
States Parties to the Convention on Biological
Diversity are required to identify and monitor the
components of biological diversity important for its
conservation and sustainable use (Article 7). These
components, as defined in Annex I of Article 7,
include: ecosystems and habitats, species and
communities; and genomes and genes of social,
economic, cultural, scientific or conservation
importance. The provisions apply to the
components of biological diversity both within (insitu) and outside of (ex-situ) their natural habitats.
Sampling biological diversity
Species diversity, as measured by inventories,
is the ‘stock in trade’ for selection of areas for
conservation, many management decisions, nearly
all environmental impact assessments and most
political discussions on biodiversity. While
GREEN et al.
surrogates may be found for defining ecosystem
diversity (such as forest types or vegetation
associations) and genetic diversity is more
frequently described only for larger charismatic or
economically important species, diversity at the
species level invariably underpins considerations
of biological diversity in both scientific and public
debates.
Description of species diversity is generally
confined to well researched groups, such as
vascular plants and larger vertebrates, with little
attention given to the remaining 99% of
biodiversity that is made up of non-vascular
plants, fungi, invertebrates and micro-organisms
(Ponder & Lunney 1999). The completeness of
inventories compiled for these frequently
monitored charismatic groups are greatly
influenced by scale, with global or continental
diversity generally well described by species
richness (Myers et al. 2000), regional or landscape
diversity less well described (Gomez de Silva &
Medellin 2001) and local diversity often poorly
described (How 1998; Thompson et al. 2003).
Questions concerning the derivation, accuracy,
adequacy and interpretation of inventories are a
central issue to consider when determining the
relevance of species lists to the conservation and
management of biological diversity.
Sampling considerations
An understanding of the strengths and
limitations of the methodology employed to
generate species inventories is essential to their
interpretation. Methodologies vary enormously,
particularly between plants which are sedentary
and animals which are mobile to varying degrees.
Plant species richness is usually determined or
counted in absolute terms with all individuals,
species or assemblages in an area measured in
totality, while animal species richness can only be
estimated by one of several approaches that take
into account the movement or behaviour of the
specific group being assessed.
Vertebrate groups, which represent the
’charismatic’ taxa that form the majority of the
faunal species inventories currently available for
biodiversity assessment, all require different
sampling methodologies. Thus, inventories should
only be interpreted after taking into account:
• methodological constraints with respect to
the taxonomic group being assessed;
•
•
43
timing and duration of the survey; and
expertise of the recorders in identifying the
taxa and their experience with the
methodologies.
Timing, duration and replication of sampling
The distribution and abundance of most faunal
species vary temporally in relation to daily,
seasonal or longer-term cycles or fluctuations in
their environments. This variation reflects the
genetic diversity of species as well as the diversity
of communities to which they belong. Thus,
sampling of the different faunal groups should be
undertaken at times of day or night and during
seasons of greatest activity. In the case of plants,
sampling is best done during the flowering seasons
or, at least, avoiding the driest times of year, to
facilitate the ready identification of species.
Shortcomings in interpreting these temporal
variations are compounded by the fact that
different responses may be expected in different
ecoregions, where driving environmental variables,
such as day-length, rainfall and temperature,
operate at different times and scales. Frequently,
biodiversity surveys are of such short duration
that less than 50% of the total assemblage is
recorded and this percentage is generally highly
skewed in favour of the more common species
(How 1998).
In assessing species diversity it is essential
that consideration is given to variation in activity
and distribution over sampling time. There are no
‘hard and fast’ rules concerning the number of
replicates needed to accurately assess variation
but 35 replicates per sampling unit of classification
has been shown to be necessary to generate precise
and unbiased estimates of diversity evenness
indices (Payne et al. 2005).
Expertise
An additional constraint applicable to species
inventories relates to the expertise of the recorder.
Lists based on observation alone, without
supporting evidence from voucher specimens, are
subjective and have to be assessed with respect to
the competence of the observer to correctly identify
the species. This is particularly relevant to birds
and amphibians where the experience of the
observer is crucial to the species specific
identification of calls, behaviour and, in the case of
44
BIODIVERSITY MONITORING IN SRI LANKA
mammals, indirect evidence
droppings and feeding signs.
such
as tracks,
Inventory interpretation
Species inventories are used in a wide variety
of contexts and analysed in many different ways.
As Boero (2001) states: “Look at species lists in a
standard ecological paper and check how accurate
are the data sets that, often, are analysed with the
most sophisticated statistical packages”. Many
inventories
are
merely
compendiums
of
information collected previously from an area and,
therefore, contain all the inherent limitations
associated with the use of non-quantitative
methodologies.
Inventories
generated
from
museum or herbarium collections are cases in
point. Similarly, unwarranted emphasis is
regularly placed on threatened species, for which
surveys are rarely adequate, with the result that
these threatened taxa form the basis of resource
allocation for species recovery plans, weight the
criteria for reserve design, constrain development
or exploitation and underpin many state-of-theenvironment decisions (Possingham et al. 2002).
However, for the better studied taxonomic groups,
such as birds and mammals and to lesser extent
flowering plants, there may be sufficient historical
records by way of species inventories to identify
and evaluate long-term and broad-scale changes in
the composition and distribution of the flora or
fauna.
Sampling adequacy and inventory evaluation
The detection of faunal species is highly
variable and dependent on the complex
relationship between an animal’s behaviour and
its environment. Consequently, there is a high
degree of variation in determining the composition
of species in floral or faunal assemblages.
Assessments of faunal assemblages are often made
using the most conservative information available
- the basic species inventory. Balmer (2002)
provides evidence that analyses devoid of species’
relative abundances do not reveal the real
ecological patterns in the data, based on an
analysis of assemblage differences using similarity
measures that considered both species presence
and abundance. It is particularly important that
analyses include species recorded only once at one
or more locations, as this may provide valuable
information about rare species most at risk from
threats such as environmental change and
disturbance. Many ecological packages allow for
this type of analysis.
Species accumulation curves or alternative
methods (Diserud & Aagaard 2002; Smith et al.
2000; Thompson et al. 2003), based on either
sampling effort or captures, are essential for an
appraisal of the completeness of an inventory. For
example, species accumulation curves were used to
identify forests which were not adequately
surveyed during the National Conservation
Review, thereby highlighting the need for further
sampling prior to any decisions being taken about
their future management (Green & Gunawardena
1997). Other approaches to determining the
adequacy of inventories are based on the
probability of capturing new species using capturerecapture algorithms (Nichols et al. 1998).
The area of inventory evaluation is expanding
rapidly in the literature with suggestions that auto
similarity (Cao & Larsen 2002) and sensitivity
analysis (Freitag & van Jaarsveld 1998) provide
more accurate measures of species richness than
estimates or comparisons based on sample size.
Long-term monitoring of biological diversity is
expensive and rarely undertaken. However,
repeated surveys provide fundamental information
on seasonal, annual and other cyclical changes
that cannot be obtained by other means. Such
studies are necessary for obtaining a detailed
inventory of threatened, rare or uncommon species
in a location (How & Cooper 2002).
Alternatives to species inventories
Umbrella, focal, indicator or keystone species
(Lambeck 1997), have been proposed as surrogates
to replace more time-consuming and expensive
surveys to inventory entire taxonomic groups.
While some of the literature on the effectiveness of
these alternative approaches remains conjectural
(Simberloff 1998), it has been shown for woody
plants in Sri Lanka, for example, that highertaxon richness can be used as a surrogate for total
species richness (Balmford et al. 1996a, 1996b).
The use of surrogates has been taken even
further using the concept of congruence, whereby
knowledge about the diversity of one taxonomic
group is interpreted to reflect the diversity of other
groups. MacNally et al. (2002) advise caution in
using this approach, having found a lack of
GREEN et al.
congruence in diversity between taxonomic groups
within a specific area (i.e. high diversity in one
taxonomic group does not necessarily correlate
with high diversity in another). At the bioregional
scale in Western Australia, for example, taxa
assemblages differ markedly according to the
underlying climatic, edaphic and environmental
conditions (McKenzie et al. 2000).
Finally, at regional scales, there is recent
literature to suggest that species richness can be
predicted
from
environmental
variables
(Trakhtenbrot & Kadmon 2006). Such an approach
has considerable attraction in terms of costs and
time, with a potentially important role in
informing regional policy and decision-making
processes.
Sri Lanka - a case study
Sri Lanka, together with the Western Ghats in
southern India, is a global hotspot for biological
diversity (Myers et al. 2000), 34 of which are
currently recognised (Mittermeier et al. 2005).
These 34 hotspots are defined regions where 75%
of the planet’s most threatened mammals, birds
and amphibians survive within habitat covering
just 2.3% of the Earth’s surface. To qualify as a
hotspot, a region must meet two criteria: it must
contain at least 1,500 species of vascular plants
( > 0.5 percent of the world’s total) as endemics;
and it must have lost at least 70% of its original
habitat due to the impact of human activities.
Knowledge about Sri Lanka’s wealth of species
is summarised in Table 1 for some of the better
known and more conspicuous taxonomic groups of
plants and animals. Levels of endemism are
extremely high for many of these groups, an
extreme example being freshwater crabs. All 51
species are endemic and 26 species are known
from only one locality (Bahir & Pethiyagoda 2006).
Much of this diversity is found in the montane,
submontane and lowland rain forests of the wet
zone and moist monsoon forests of the
intermediate zone. It is also here that levels of
endemism are highest, especially among flowering
plants (Dassanayake et al. 1980-2000) and some of
the less mobile faunal groups, such as tree-frogs,
agamid lizards and skinks (Bambaradeniya 2006).
While much of Sri Lanka’s flora and fauna had
been collected and described prior to the 20th
century, many new species continue to be
45
discovered and await scientific description,
particularly among some of the invertebrate and
smaller vertebrate groups. Spiders, for example,
are poorly researched: 501 species are known but
the actual number might exceed 4,000 species
(Benjamin & Bambaradeniya 2006). Among
vertebrates, much recent collection and taxonomic
review of amphibians has resulted in a near
doubling of this fauna from 53 to 102 species,
based on published descriptions. More new species
await description: the total size of this group is
currently estimated at about 140 species
(Pethiyagoda et al. 2006).
Much, but by no means all, of Sri Lanka’s
biological diversity is represented within its
system
of
protected
areas,
administered
principally by the Department of Wildlife
Conservation and the Forest Department. Such
protected areas, in theory though not always in
reality, have been selected for their wealth of
biological diversity and are safeguarded under
various national legislation for long-term
conservation purposes. Knowing what and how
biological diversity is distributed within a
protected area is essential for informing its future
management, as well as providing context to the
planning and management of the country’s entire
protected areas system. As relatively little is
known about biological diversity within many of
Sri Lanka’s protected areas, let alone outside
protected areas, a priority is to identify and
monitor the components of biological diversity
within such areas designated for its conservation,
particularly since so much species diversity is
endemic to the island.
Recent surveys of in situ biological diversity
The most comprehensive nationwide survey to
date is the National Conservation Review of forest
biodiversity, undertaken in 1991-1996 by the
Forest Department. Woody plants and selected
animal groups within all natural forests of 200 ha
or more, except those occurring in the politically
inaccessible northern and eastern parts of the
country, were surveyed (Green & Gunawardena
1997). Totals of 1,153 woody plant, 64 butterfly, 71
mollusc, 32 amphibian, 65 reptile, 139 bird and 37
mammal species were recorded, representing a
significant proportion of the diversity of each of
these groups as summarised in Table 1. Other
more recent surveys have been carried out in
46
BIODIVERSITY MONITORING IN SRI LANKA
Table 1. Recorded diversity of Sri Lanka’s better known flora (Dassanayake et al. 1980-2000;
Senaratna 2001; MENR 2002) and fauna (Bambaradeniya 2006).
Taxonomic groups
No.
species
No.
endemics
%
endemics
Notes
INDIGENOUS FLORA
Algae
896
unavailable
Fungi
1,920
unavailable
Lichens
110
39
Mosses
575
unavailable
Liverworts
190
unavailable
Ferns and allies
314
57
1
0
Gymnosperms
Angiosperms
3,044
919
28.2
18.2
30.2
Excludes 1,083 exotic species
INDIGENOUS INVERTEBRATE FAUNA
Bees
148
21
14.2
Dragon/damselflies
120
57
47.5
2.4
Aphids
84
2
Ants
181
1
0.6
Butterflies
243
20
8.2
27
1
3.7
501
unavailable
51
51
100.0
246
204
82.9
Ticks
Spiders
Freshwater crabs
Land snails
Includes 4 new endemic species to be described
Total number of species likely to exceed 8,000
Of the 7 genera, 5 are endemic to Sri Lanka
Excludes 18 exotic, mostly agricultural species
VERTEBRATE FAUNA
Freshwater fish
82
44
53.7
Excludes 22 species introduced since 1982
Amphibians
102
88
86.3
Many more amphibian species await description
Reptiles
184
105
57.1
Includes 5 marine turtle and 13 marine snake species
Birds
482
25
5.2
91
16
17.6
Mammals
greater detail for specific taxonomic groups, such
as plants at Peak Wilderness (Singhakumara
1995a) and Kanneliya-Dediyagala-Nakiyadeniya
(Singhakumara 1995b), amphibians and reptiles in
the Knuckles (de Silva 2005) and an island-wide
survey of land snails (Naggs et al. 2005), but none
covers the range of plant and animal groups, using
quantitative methods, employed by the National
Conservation Review.
The task of identifying further and monitoring
the components of Sri Lanka’s biological diversity
is urgent because there is evidence that much is
being lost rapidly. Deforestation and degradation
of forests, for example, has reduced closed canopy
forest from 84% in 1888 to 24% in 1992 (Legg &
Jewell
1995),
the
causal
factors
being
encroachment and alienation of forest land for
Includes 220 breeding residents
Excludes 16 introduced and 27 marine mammal spp.
settlement and agriculture (Forestry Planning
Unit 1995). Loss of habitat is accompanied by a
reduction in the distribution and abundance of
species and, in the case of endemics, may even
result in their global extinction. Reference to the
14 volume Revised Handbook to the Flora of
Ceylon (Dassanayake et al. 1980-2000), for
example, shows that 133 (4.4%) of Sri Lanka’s
3,044 indigenous species have not been
accessioned by the National Herbarium at
Peradeniya since the beginning of the 20th century
(R. Pethiyagoda, pers. comm. 2007). Of these, 63
are endemic, which amounts to 6.9% of the
country’s 919 endemic species. While not
necessarily extinct, there is a serious lack of
knowledge about the conservation status of a
significant component of the flora, underlining the
GREEN et al.
importance of routinely monitoring such biological
diversity.
Biodiversity Baseline Survey
The Department of Wildlife Conservation has
recently embarked on an ambitious initiative,
known as the Biodiversity Baseline Survey, to
benchmark and subsequently monitor the diversity
of species within key taxonomic groups that occur
within protected areas. The design and sampling
protocols developed for this Survey are outlined
below, together with their application in a
selection of protected areas. Full details of the
methodology can be found in the field manual
(Green et al. 2007a).
Benchmarking biological diversity in
Sri Lanka’s protected areas
Scope
The Biodiversity Baseline Survey, ongoing
since mid-2006, is being undertaken in terrestrial
and aquatic habitats of seven protected areas,
chosen on account of their high and differing
biodiversity:
• Bundala National Park
• Ritigalala Strict Natural Reserve
• Horton Plains National Park
• Udawalawe National Park
• Minneriya National Park
• Wasgomuwa National Park
• Peak Wilderness Sanctuary
The following six taxonomic groups were
selected for purposes of the Survey on the basis of
being (a) well known and of general interest to
scientists and managers, (b) relatively easy to
survey systematically and identify, and (c)
potentially
of
value
to
protected
areas
management:
• Mammals
• Reptiles
• Birds
• Freshwater fish
• Amphibians
• Vascular plants
Stratified and gradsect sampling of terrestrial
habitats
Knowledge about the distribution of the
different habitats within an area provides a sound
47
basis for stratifying the design of a survey at an
appropriate scale. Habitat maps were available for
this purpose (e.g. EML 2006), having been derived
from overlays of a suite of geographic and
environmental variables that include geology, soil,
altitude, aspect, land use and vegetation. The
habitats identified from these overlays are too
numerous for purposes of this Survey, so sampling
focuses on the main vegetation types, while taking
into account the spatial distribution of other
environmental variables such as geology, soils,
slope, altitude and streams for aligning transects,
as well as roads for purposes of access. Horton
Plains National Park, for example, can be
stratified into five main vegetation types, each of
which is sampled by aligning transects along the
gradients of such variables (Fig. 1).
This is similar to the gradsect approach used
in the National Conservation Review (Green &
Gunawardena 1997). Gradsects are essentially
transects aligned along environmental gradients,
enabling a maximum diversity of taxa to be
sampled with a minimum effort.
Quantitative integrated sampling design for
terrestrial habitats
Sampling of the different taxonomic groups is:
(a) quantitative to ensure that measures of species
richness and abundance are robust and able to be
statistically analysed; and (b) integrated in design
to provide the basis for examining relationships
between plant and animal species, assemblages or
taxonomic groups within the same sampling units
and to make most efficient use of time, energy and
other resources spent marking out and sampling
transects.
The design is also simple rather than
sophisticated, so that it can be readily applied to
other protected areas and repeated for monitoring
purposes by Department of Wildlife Conservation
staff and others engaged by the Department in
such work in the future.
Units for sampling terrestrial vascular plants
and vertebrates are described in Box 1. The key
design features of this integrated, quantitative
approach to sampling terrestrial species diversity
are as follows:
• Each habitat type is sampled by a minimum of
four replicate transects of 1 km, taking into
account as much of the environmental
variation (notably in geology, soil, aspect and
48
BIODIVERSITY MONITORING IN SRI LANKA
Fig. 1. Horton Plains National Park – habitats are sampled within each vegetation type
while also aligning transects along other environmental gradients, such as slope, soil and
geology, as shown diagrammatically by the two lines superimposed on the vegetation map.
•
•
•
altitude) as practicable, within the constraints
of time and access to the area.
Quadrats, measuring 100 m x 5 m, are located
at 150 m intervals along 1 km transects (i.e. 4
quadrats per 1 km transect).
Each quadrat is divided into 10 m x 5 m plots,
within which each taxonomic group is
sampled. Vascular plants are recorded in every
plot of each quadrat; vertebrate taxonomic
groups are recorded from within certain plots
in either all quadrats (birds) or alternate
quadrats (amphibians, reptiles, mammals).
Field work logistics are based on sampling a
total of 4 km of transects within a four-day
period. Four days/nights are considered to be
the minimum period of time necessary to
effectively sample (trap) small mammals at a
given location (see Wijesinghe & Brooke 2005).
This governs the length of field trips, the
duration of which is a multiple of four days. In
practice this amounts to the following
sampling rates and intensities:
o
Vascular plants: four quadrats (i.e. 1 km)
per day.
o
Amphibians and reptiles: five alternate
plots within each of two quadrats per day
(i.e. 1 km per day), using the Quadrat
Clearing Technique (Heyer et al. 1994).
o
Birds: two Variable Circular Plots (VCPs)
at the beginning and end of each of four
quadrats surveyed early morning and
evening (i.e. 1 km per day). Birds are
recorded directly or indirectly from their
songs over a period of 10 minutes, within
three zones of radius 0-10 m, >10-20 m and
>20 m.
o
Mammals: eleven small aluminium box
traps (Sherman or Elliott) for small
mammals (e.g. rodents) at 10 m intervals
and two larger Tomahawk traps for small
GREEN et al.
49
Box 1. Description of sampling units
Transects – 1 km long
Four replicate transects, 1 km in length, are located within each defined habitat (e.g. vegetation type). A
transect may cover more than one habitat type in areas comprising a mosaic of highly fragmented habitats.
Where necessary or appropriate, transects may be extended from 1 km to up to 4 km in order to cover
several vegetation types along a major environmental gradient, such as altitude. Such transects are
essentially gradsects.
Quadrats – 100 m x 5 m
The length of a quadrat is defined for the duration of the sampling period by a centre line of highly visible
nylon cord, marked at 10 m intervals by tape. A thin cane or pole, 2.5 m in length, is aligned perpendicular
to this central cord in order to determine the width of the quadrat. Cords are removed at the end of the
sampling period (four-days).
The ends of each 100 m length of quadrat line are georeferenced, using a GPS (Global Positioning
System), and permanently marked for purposes of future monitoring, using paint and/or a thick nylon cord
tied loosely around a branch of vegetation (not applicable in grasslands).
Quadrats may be aligned along a single straight line 1 km in length, or in a square (250 m x 250 m) or
rectangle (350 m x 150 m). Regardless of transect shape, quadrats must be 150 m apart. This criterion is
particularly important with respect to mobile taxa, such as birds, to minimise the potential for recording the
same individual in adjacent quadrats. Sometimes, where access is very restricted or where the habitat is
very linear in its distribution (e.g. riverine vegetation), it may be necessary to establish four parallel
quadrats, spaced at least 150 m apart, either side of an access route.
Plots – 10 m x 5 m
The subdivision of quadrats into plots, by marking the central nylon cord at 10 m intervals, is critical. It
enables the reptile/amphibian Quadrat Clearing Technique to be applied at 20 m intervals, small mammal
traps to be positioned at 10 m intervals and, most importantly, it provides the basis for examining potential
relationships between plant and animal (amphibian, reptile or small mammal) species and assemblages.
carnivores at the beginning and end of
each of two quadrats along four transects
per day (i.e. 4 km per day, repeated over
four days/nights).
Note that the two quadrats sampled for
mammals alternate with those sampled for
amphibians and reptiles to minimise disturbance
to one taxonomic group while recording another.
The relationship between these different
sampling units with respect to the different
taxonomic groups is shown diagrammatically in
Fig. 2. The way in which transects were laid out in
the field varied according to the terrain,
distribution of the habitat and access, as
illustrated in Fig. 3.
A total of 120 days of field work was
undertaken during an initial six-month period of
the Biodiversity Baseline Survey in 2006-07, based
on an average of two 10-day field trips (including
travel time) per month. Sampling intensity
amounted to a total of 304 quadrats distributed
along 76 km of transects in four protected areas,
each of which was stratified into 4 or 5 habitat
types (Green et al. 2007b-e).
Stratified sampling of aquatic habitats
Aquatic habitats are stratified into river subbasins, using topographic survey maps of an
appropriate scale. As for the survey of terrestrial
habitats, a minimum of four replicates are
sampled within each river sub-basin. Of the total
of 106 river sub-basins, 38 (36%) were surveyed
during the initial six-month period of field work in
2006-07.
Quantitative sampling design for aquatic
habitats
Replicate sampling of the head, mid- and lower
reaches of at least four rivers or streams within
each sub-basin of a protected area is undertaken
for fish and various measures of water quality that
include pH, conductivity, dissolved oxygen, total
dissolved solids, turbidity and temperature. Other
50
BIODIVERSITY MONITORING IN SRI LANKA
Fig. 2. Location of quadrats within a transect and Variable Circular Plots (VCP) within a
quadrat. Quadrats A and C are sampled for mammals, quadrats B and D for reptiles (not to
scale).
Fig. 3. Quadrats within a transect (1 km) are aligned in a single line (a), in parallel (b, d) or
in a square (c), depending on the distribution of the habitat, access to it and terrain. Quadrats
are aligned perpendicular to environmental gradients, such as altitude (as shown by contours
in b and d) to maximise sampling of biological diversity (not to scale).
large water bodies, such lakes, reservoirs and
swamps, are similarly sampled. Fish are sampled
using sweep, throw, gill and seine nets, rod and
line, and by snorkelling for a standard period of
time, or until it is apparent that additional species
are unlikely to be recorded from the sampling
station.
GREEN et al.
Analysing the results
The types of analyses applied to a biodiversity
sampling regime depend entirely on the objectives
of the study, the methodologies used and the data
collected and available for analysis. For purposes
of the Biodiversity Baseline Survey, data analysis
is undertaken in the following sequence:
(i) Data are checked for various recording and
entry errors.
(ii) The effectiveness of sampling is assessed
using species accumulation curves.
(iii) Species diversity is measured using both
alpha and beta statistics.
(iv) Observed species diversity is interpreted in
the areas of interest.
Data screening
Data screening is a basic process that is vital
for all biological survey work. At best, analyses are
worthless if the data used are incorrect. At worst,
it is wasteful of time and, more critically, can lead
to completely erroneous conclusions upon which
management or policy decisions may be based.
Such outcomes must be avoided at all costs.
It is essential, therefore, to check all data for
errors, such as incorrect coding of sites, missspellings of species names, incorrect recording of
numbers and erroneous data entry. Many
techniques can be used but two-way pivot tables
(matrices) of species by quadrat or habitat type,
containing the numbers of recorded individuals, is
one very effective method.
Data appraisal - assessing effectiveness of sampling
The first step in data appraisal, after screening
and verifying the data, is to evaluate the number
of species recorded in relation to the effort
expended in encountering them. The effort
expended can be measured by the number of
individuals encountered, the number of units
sampled or the time taken (e.g. number of days). A
graph of the cumulative number of species
encountered plotted against effort provides a
species accumulation or discovery curve that
enables an investigator to assess the relative
completeness of the sampling regime.
Some examples of species accumulation curves
are provided in Fig. 4. Inadequately sampled
assemblages continue to show a steep incline in
the number of species encountered as sampling
effort increases, as in the case of birds at Ritigala
51
and Horton Plains; while a well sampled
assemblage shows a distinct plateau in the
cumulative number of species with additional
sampling, as evident for plants at Wasgomuwa and
to a less extent Peak Wilderness (Fig. 4).
Caution should prevail in the analysis and
interpretation of data from locations that are
poorly sampled for their composite species
assemblages. Where there is no evidence of any
plateau in the cumulative number of species,
further sampling is necessary. If this is not
possible because of lack of time or other resources,
it is imperative that the inadequacy of the
sampling is highlighted in all analyses and reports
to ensure that any management and policy
decisions take account of this constraint.
Several predictive models are also available for
estimating the potential number of species in a
defined sampling unit. These are based variously
on the functions of the number of species seen in
only one or two samples (Chao 2, Jacknife), the
number of species that have only one or two
individuals in the entire pool of samples (Chao 1),
or the proportions of samples that contain each
species (Bootstrap). These estimates of potential
species diversity can be generated from ecological
packages such as Primer-E (Clarke & Warwick
2001) and Estimate S (Colwell 2005).
Species diversity measures
The core analyses of any conservation study
are the estimates of biological diversity. A sample
often comprises subgroups, referred to here as
units, such as particular localities, regions or
habitat types. As a consequence, two levels of
diversity are commonly considered: alpha
diversity, which is the diversity within a unit; and
beta diversity, which is the amount of
compositional variation between units.
Alpha [α] diversity
The best known measurement of diversity
within a unit is Species Richness (S), which is the
number of species in the unit. It is an intuitive and
well-established measure that is widely used by
field ecologists because of its simplicity and ease of
calculation. It is also readily appreciated and
easily communicated to colleagues, decision
makers and the general public.
However, there is a wide and growing
literature on other measures of diversity that have
appeal because they are less dependent on sample
52
BIODIVERSITY MONITORING IN SRI LANKA
Fig. 4. Examples of species accumulation curves for plants (left) and birds (right) in various protected
areas, based on records from the Biodiversity Baseline Survey.
size or effort and take into account the distribution
of species’ abundances in the unit under
consideration. The generality and applicability of
such measures have been evaluated by Jost (2006)
and his recommendations have been followed in
the Biodiversity Baseline Survey by adopting two
indices of alpha diversity, in addition to Species
Richness. These, calculated using the program
Primer-E (Clarke & Warwick 2001), are as follows:
• Shannon Entropy (H’) calculated from exp
S
(−
∑p
ln pi ), where, pi is the proportion
i
Beta [β] diversity
Beta diversity quantifies the amount of
compositional variation and relationships between
units of interest, such as habitats within a locality.
There are numerous ways of measuring beta
diversity that are dependent on concepts or
measurements
of
underlying
sources
of
compositional variation (see Magurran 2003).
For purposes of the Biodiversity Baseline
Survey, a widely-used measure, the matrix of the
Bray-Curtis coefficient of similarity, is calculated
i =1
•
of individuals of the ith species.
Simpson Concentration (D) calculated from
S
1/
∑p
2
i
.
i =1
It is clear from plots of these three measures
for seven habitats at Wasgomuwa National Park,
for example, that Species Richness is correlated
with both diversity indices in all cases except
grassland. Furthermore, both species diversity
indices (H’ and D) are strongly correlated (Fig. 5).
Comparisons of alpha diversity are a valuable
means of assessing the relative conservation
importance of different units (e.g. protected areas,
habitats, transects).
Fig. 5. Measures of alpha diversity in Wasgomuwa
National Park, using Species Richness (S), Shannon
Entropy (H’) and Simpson Concentration (D). Dry Mixed
Evergreen Forest (DMEF) is classified into dry,
intermediate and wet types.
GREEN et al.
(see Ludwig & Reynolds 1988; McCune & Grace
2002). As information in similarity matrices is
usually very difficult to understand, various
analytical procedures are used to assist with
interpretation, usually by means of graphical
representations. Principal Coordinates Analysis
(known by several other names including
ordination,
metric
scaling,
seriation
and
multidimensional scaling) was adopted during the
initial stage of the Biodiversity Baseline Survey,
using the statistical package Genstat (Genstat
2006). Currently, similarity matrices are examined
with non-metric Multidimensional Scaling, using
the ecological package Primer-E. Both of these
approaches present the similarity matrix in two
(or more) dimensions. The relative advantages of
the latter are discussed by Clarke (1993).
An example of non-metric Multi-dimensional
Scaling, shown in Fig. 6, reveals some important
features of floristic data collected from Peak
Wilderness National Park. First, Submontane
Forest quadrats fall into two distinct sub-groups,
indicating this may be a heterogeneous habitat
type. Similarly, there are two sub-groups of
Lowland Forest, one of which is similar to Lowland
Disturbed Forest. Montane Forest appears similar
to one of the Submontane Forest sub-groups but
care should be exercised because these two subgroups may actually differ on a third axis. Finally,
Secondary Submontane Forest, although only
represented by four quadrat samples, are quite
widely spread, suggesting that they may constitute
a heterogeneous group.
Principle Coordinates Analysis and non-metric
Multidimensional Scaling are powerful tools to
validate, or otherwise, the original stratification of
habitat types upon which field sampling is based.
As demonstrated in Fig. 6, habitat types assigned
to quadrats on the basis of vegetation maps
invariably prove to be an oversimplification and
some re-classification may be necessary. Also,
outliers in the analyses need to be reviewed with
respect to various modifying processes (e.g. timber
extraction, fire, species enrichment) that may
explain
deviations
from
expected
species
composition.
Conclusions
Species inventories are central to the
identification and description of biodiversity
53
Fig. 6. Beta diversity for vascular plants at Peak
Wilderness Sanctuary. Each point represents a quadrat.
The Stress value of 0.09 indicates that the two
dimensional plot provides a good approximation of the
distances between quadrats, in terms of similarity in
species composition.
hotspots at a variety of scales (Brooks et al. 2001);
they play an important role in selection of areas
for conservation (Cabeza & Moilanen 2001;
Margules & Pressey 2000); and also provide the
basis of most environmental impact assessment
protocols. However, the value of species
inventories is proportional to their completeness
and accuracy. These key measures are seldom
highlighted in the presentation of inventories and,
together with a statement of methods employed,
are
essential
for
their
assessment
and
interpretation.
Species inventories can be enhanced when
greater emphasis is given to improving
identification skills and the quality of data
presented for interpretation. The practice of
vouchering is desirable for most taxonomic groups
as it provides: ‘hard evidence’ of the identity of the
species; baseline information on species biology;
and, importantly, an opportunity to evaluate
species changes over time.
Species inventories are decidedly more
informative if accompanied by quantitative data on
species abundance, since this permits a more
accurate and enhanced level of assessment of both
the methodology and comprehensiveness of the
inventories.
No single index of diversity adequately depicts
species diversity in a unit. However, there is
generally a strong correlation between all indices
once sample sizes become large. This highlights
the importance of extensive sampling.
54
BIODIVERSITY MONITORING IN SRI LANKA
The use of surrogates for assessing biological
diversity may be helpful if resources (time and
funds) are scarce but their limitations must be
understood
and
fully
acknowledged.
Environmental correlates can inform assessments
of biological diversity but they cannot replace
detailed inventory surveys.
In Sri Lanka, a hotspot for biological diversity,
significant progress has been made in identifying
diversity at species levels in systematic,
quantifiable ways at national scales, beginning
with the National Conservation Review in 19911996 and followed up more recently with the
Biodiversity Baseline Survey described here. Such
extensive surveys provide the basis for future
monitoring, which is a crucial next step towards
the Government of Sri Lanka meeting its
obligations under the Convention on Biological
Diversity.
Acknowledgements
The Biodiversity Baseline Survey is part the
Protected Area Management and Wildlife
Conservation Project, funded by the Asian
Development
Bank,
World
Bank-Global
Environment Facility and the Government of the
Netherlands. It has been undertaken in two
phases
for
the
Department
of
Wildlife
Conservation, Ministry of Environment and
Natural Resources, Sri Lanka: initially by ARD
Inc. in association with Infotechs Ideas Pvt. Ltd
and Greentech Consultants Pvt. Ltd and
subsequently, during an extension to the Project,
by Infotechs Ideas Pvt. Ltd in association with
Greentech Consultants Pvt. Ltd.
Various members of the Biodiversity Baseline
Survey team contributed to the development of
methods for sampling the different taxonomic
groups, further details of which can be found in the
field manual (Green et al. 2007a): B.M.P.
Singhakumara (plants), S.M.D.A.U. de Alwis
(fish), P.N. Dayawansa (amphibians and reptiles),
D. Weerakoon (birds), M.R. Wijesinghe (non-volant
mammals) and W.B. Yapa (bats).
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