Marine Environmental Research 98 (2014) 1e13
Contents lists available at ScienceDirect
Marine Environmental Research
journal homepage: www.elsevier.com/locate/marenvrev
Ecological structure and function differs between habitats dominated
by seagrasses and green seaweeds
Fernando Tuya a, *, Lydia Png-Gonzalez a, Rodrigo Riera b, c, Ricardo Haroun a,
Fernando Espino a
a
b
c
Centro en Biodiversidad y Gestión Ambiental, Marine Sciences Faculty, Universidad de Las Palmas de Gran Canaria, Las Palmas, Canary Islands, Spain
Centro de Investigaciones Medioambientales del Atlántico (CIMA SL), Arzobispo Elías Yanes 44, 38206 La Laguna, Tenerife, Canary Islands, Spain
Department of Biodiversity, Qatar Environment and Energy Research Institute (QEERI), 5825 Doha, Qatar
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 3 February 2014
Received in revised form
18 March 2014
Accepted 21 March 2014
Marine vegetated habitats, e.g. seagrass meadows, deliver essential functions and services to coastal
ecosystems and human welfare. Impacts induced by humans, however, have facilitated the replacement
of seagrasses by alternative vegetation, e.g. green rhizophytic seaweeds. The implications of habitat shifts
for ecosystem attributes and processes and the services they deliver remain poorly known. In this study,
we compared ecosystem structure and function between Cymodocea nodosa seagrass meadows and
bottoms dominated by Caulerpa prolifera, a green, native, rhizophytic seaweed, through 5 ecological
proxies: (i) primary production (via community metabolism), (ii) composition and abundance of
epifauna (a proxy for provision of habitat for epifauna), composition and abundance of (iii) small-sized
(juvenile) and (iv) large-sized (adult) fishes (proxies for provision of habitat for fishes), and (v) sediment
retention (a proxy for sediment stabilization). Four of these proxies were greater in C. nodosa seagrass
meadows than in C. prolifera beds: gross primary productivity (w1.4 times), the total abundance, species
density and biomass of small-sized fishes (w2.1, 1.3 and 1.3 times, respectively), the total abundance and
species density of large-sized fishes (w3.6 and 1.5 times, respectively), and sediment stabilization (w1.4
times). In contrast, the total abundance and species density of epifauna was larger (w3.1 and 1.7 times,
respectively) in C. prolifera than in C. nodosa seagrass beds. These results suggest that ecosystem
structure and function may differ if seagrasses are replaced by green rhizophytic seaweeds. Importantly,
ecosystem functions may not be appropriate surrogates for one another. As a result, assessments of
ecosystem services associated with ecosystem functions cannot be based on exclusively one service that
is expected to benefit other services.
Ó 2014 Elsevier Ltd. All rights reserved.
Keywords:
Ecosystem services
Macroalgae
Caulerpa
Clonal seaweeds
Atlantic Ocean
1. Introduction
Understanding the complexity of ecosystems is needed to
recognize natural and human processes that cause changes in
community structure, loss of resilience to disturbances, and shifts
to alternative states. A method for simplifying ecological information into management frameworks considers the provision of
‘goods and services’ by ecosystems, i.e. ‘ecosystem services’ (Koch
et al., 2009) e an approach that is widely recognized as a valuable tool for ecosystems management (Barbier et al., 2011). Provision of ecosystem services depends on ecosystem functions; where
the former benefits a group of humans and can be economically
* Corresponding author. Tel.: þ34 928457279; fax: þ34 928452900.
E-mail address: [email protected] (F. Tuya).
http://dx.doi.org/10.1016/j.marenvres.2014.03.015
0141-1136/Ó 2014 Elsevier Ltd. All rights reserved.
quantified, the latter represent an ecological process that underpins
an ecosystem service (Barbier et al., 2011).
Marine vegetated habitats deliver essential functions and services to coastal ecosystems and human well-being (Boström et al.,
2011). On shallow soft-sediment seabeds from tropical to
temperate oceans, seagrasses are the main ‘foundation’ species
(Hemminga and Duarte, 2000), which modify local environmental
conditions and provide food and habitat for a wide range of organisms (Boström et al., 2006; Thomsen et al., 2010). Seagrass
meadows are one of the most productive nearshore habitats,
providing high-value ecosystem services (Cullen-Unsworth and
Unsworth, 2013). Seagrasses are therefore included in many conservation frameworks, e.g. the European ‘92/43/CEE Habitats
Directive’. Conservation of these valuable habitats is vital, particularly since seagrass meadows are declining worldwide, mainly in
areas of intense human activities (Duarte et al., 2008; Hughes et al.,
2
F. Tuya et al. / Marine Environmental Research 98 (2014) 1e13
2009; Waycott et al., 2009). It has been estimated that on a global
scale, ca. 30% of seagrass meadows have been lost from 1879 to
2006, placing seagrass meadows among the most threatened ecosystems on the planet (Waycott et al., 2009). In many areas of the
world, seagrass meadow deterioration induced by humans is
compounded by increasing competition from opportunistic vegetation (various red, green and brown seaweeds), which accelerates
the degradation of these habitats (Thomsen et al., 2012). In these
cases, small patches of seaweeds can proliferate into massive mats,
and convert stable seagrass systems into less stable, depauperate
macroalgal beds (Boström et al., 2006). Habitats that are characterized by sediment stability, high water clarity, an oxic watercolumn, and stable standing crop, productivity and nursery function, can be replaced by habitats characterized by sediment instability, turbid waters, localized hypoxia, and fluctuating
macrophytes biomass, productivity and nursery function (Thomsen
et al., 2012). Despite theoretical simulations (Plummer et al., 2013)
and empirical experiments (Schmidt et al., 2011) that have
improved understanding of how ecological structure and function
may respond to changes in the cover of native seagrasses, there is a
necessity to further develop empirical and experimental research
(Schmidt et al., 2011; Plummer et al., 2013).
Cymodocea nodosa is a seagrass distributed across the Mediterranean Sea and the adjacent eastern Atlantic coasts, including the
Macaronesian oceanic arquipelagos of Madeira and the Canary
Islands (Mascaró et al., 2009). Meadows formed by C. nodosa are the
dominant vegetated communities on shallow soft substrates
throughout the Canary Islands (Reyes et al., 1995; Barberá et al.,
2005), where they provide food and shelter for diverse invertebrate and fish assemblages (Tuya et al., 2006; Espino et al., 2011;
Gardner et al., 2013; Tuya et al., 2013b). Across its distribution
range, widespread deterioration of C. nodosa often results in the
replacement of seagrasses by green algae of the genus Caulerpa,
including native (Lloret et al., 2005; García-Sánchez et al., 2012)
and non-native species (Ceccherelli and Cinelli, 1997; Hendriks
et al., 2009). In the Canary Islands, the presence of C. nodosa has
decreased in the last two decades, correlating with a significant
increase in the presence of the green, native rhizophytic algae
Caulerpa prolifera (Martínez-Samper, 2011; Tuya et al., 2014).
Negative interactions between seagrasses and clonal green seaweeds, including various Caulerpa species, have been demonstrated
experimentally (Dumay et al., 2002; Taplin et al., 2005; Stafford and
Bell, 2006; Tuya et al., 2013a).
In the Mediterranean and other subtropical and tropical seas,
the replacement of seagrasses by various Caulerpa species alters
substratum and hydrodynamic traits (Hendriks et al., 2009), as well
as associated fish assemblages (Pérez-Ruzafa et al., 2006). To date,
however, there have been almost no comprehensive examinations
of the differences in ecosystem structure and function between
landscapes dominated by seagrasses and green rhizophytic seaweeds, despite the large value of seagrasses (Vassallo et al., 2013).
In this study, we aimed to determine the differences in ecological
structure and function between C. nodosa seagrass meadows and
adjacent bottoms dominated by the native, green rhizophytic, alga
C. prolifera on shallow landscapes of the Canary Islands (eastern
Atlantic), through 5 ecological proxies: (i) primary production (via
community metabolism), (ii) composition and abundance of
epifauna, a proxy for provision of habitat for epifauna, composition
and abundance of (iii) small-sized (juvenile) and (iv) large-sized
(adult) fishes, proxies for provision of habitat for fishes, and (v)
sediment retention, a proxy for sediment stabilization.
2. Material & methods
2.1. Study area
Two monospecific C. nodosa seagrass meadows (ca. 50e80 ha,
70e80% of seagrass coverage, 5e8 m depth; www.sebadales.org)
(Martínez-Samper, 2011; Tuya et al., 2014) were selected in the east
coast of Gran Canaria Island (Fig. 1). We also selected two sites of
soft bottom predominantly covered by the green rhizophytic algae
C. prolifera, at a similar depth range (6e8 m depth) and proximity to
the shore, relative to C. nodosa seagrass meadows (Fig. 1). These two
C. prolifera-dominated beds were dominated by C. nodosa in the
1990s (Tuya et al., 2013a) and extend ca. 60e90 ha (MartínezSamper, 2011). Sites were 100s of meters apart; monospecific
C. nodosa seagrass meadows were ca. 10 km apart from C. proliferadominated bottoms (Fig. 1). It was impossible to intersperse sites as
a result of the arrangement of habitats. Sites, however, were not
only similar in depth, but also presented similarities for a range of
environmental factors, particularly sea water temperature, surface
PAR and wave exposure (Appendix A, Tuya et al., 2014).
Fig. 1. Study area. Position of the two sites within each habitat type in the east coast of Gran Canaria Island.
F. Tuya et al. / Marine Environmental Research 98 (2014) 1e13
2.2. Community metabolism
Net production and respiration was assessed through the oxygen
evolution method (Strickland and Parsons, 1972). At each study site,
incubations were performed underwater, by randomly fixing 3 clear
and 3 dark Plexiglas bottles (ca. 1 l of volume, 30 cm long, 6.6 cm of
diameter) on the soft bottom, encompassing vegetation of each
habitat type (i.e. leaves of C. nodosa or fronds of C. prolifera). Bottles
were slowly inserted in the sediment without cutting below-ground
roots, rhizomes, stolons and rhizoids, minimizing sediment
disruption. The oxygen concentration of the water was measured at
the start and the end of incubations using a portable oxygen-meter
(Hanna HI9829, Germany). Duration of incubations (2 h) was established after a pilot study (Appendix B); all incubations started between 10:00e11:00 a.m. on days with no cloud cover (ca. surface
PAR was between 1000 and 1500 mmol of photons m2 s1). Once
incubations were finished, all vegetation inside bottles was harvested to calculate O2 production on a per area and vegetation
biomass basis (g dry weight of above-ground vegetation); dry
weight was obtained after oven-drying at 60 C for 48 h. Differences
between initial and final O2 concentration in the clear bottles were
compared to differences between initial and final O2 concentration
in the dark bottles, to calculate net/gross community primary production and respiration using the following formulas:
Benthic Net Primary Production
¼ ðFcb Icb Þ V C Qp1 t 1
Benthic Respiration ¼ ðFdb Idb Þ V C Qr t 1
Icb and Fcb are the initial and final water O2 concentrations (clear
bottles); Idb and Fdb are the initial and final water O2 concentrations
(dark bottles); V is the bottle volume (1 l); C is the oxygen to carbon
conversion factor of 0.375 mg C per mg O2; Q1
p and Qr are the
photosynthetic and respiratory quotients (1.2 and 1, respectively); t
is the incubation time (2 h). All concentrations are in mg O2 l1.
Final values were expressed on a per area (m2) and vegetation
biomass basis (g DW). At each site, incubations were performed at
four times throughout an entire annual cycle (July 2012, October
2012, February 2013 and May 2013).
2.3. Epifauna
Epifauna inhabiting each site within each habitat were sampled
by lowering a quadrat (0.04 m2) with an attached cotton bag over the
vegetation (n ¼ 10), cutting seagrasses or seaweeds just above the
sediment surface (Gardner et al., 2013). Epifaunal samples were
frozen until being processed. Epifauna were collected at two
(random) times (October 2011 and November 2012) to test if faunal
differences between C. nodosa and C. prolifera-dominated sites were
consistent over time. In the lab, samples were washed through a
0.5 mm mesh sieve. The remaining fraction was separated into
taxonomic groups under a dissecting microscope. Macrofaunal
specimens were, whenever possible, determined to species level, by
means of a binocular microscope, or using a Nikon Eclipse microscope equipped with Nomarski interference. Organisms were preserved in a 70% ethanol solution. The vegetation biomass (wet
weight) of each sample was also measured; in all cases, epiphytes
represented a very small biomass fraction and were not separated.
2.4. Small-sized fishes
Small-sized (mainly juvenile) fishes were sampled through a
6 m long, 4 m wide, 0.5 m high seine net with a mesh size of 1 mm.
3
The net was towed close to the bottom by two SCUBA divers
following a 25 m transect (100 m2 per trawl). Trawls were performed at random directions within both habitats. This method
captures small fishes that have little swimming ability and seek
refuge within vegetated canopies. The technique has proven to be
effective in capturing small fish (juveniles, predominantly) in the
study area (Espino et al., 2011). Trawls (n ¼ 3) were carried out
during daylight hours at each site within each habitat at four
sampling occasions throughout an annual cycle (same dates as incubations). All captured fishes were identified, counted, measured
(TL 1 mm) and weighted (0.001 g).
2.5. Large-sized fishes
Large-sized (mainly adults) fishes were sampled by means of
underwater visual census through 25 m long 4 m wide strip
transects (100 m2). Counts were carried out randomly during
daylight hours (typically between 10:00e12:00 a.m.) by the same
two observers (FT and FE) to minimize potential bias. The abundance and size of all fish species within 2 m at each side of each
transect were recorded on waterproof paper by a SCUBA diver.
Visual census counts (n ¼ 6) were performed at each site within
each habitat at four sampling occasions throughout an annual cycle
(same dates as above). Pelagic fish species were ignored in further
analyses, since their spatial patterns are typically independent of
the dominant vegetated habitat on the bottom.
2.6. Sediment stabilization
Vegetative fragments of C. nodosa (ca. 12e18 cm long horizontal
rhizomes with 5e7 shoots and associated leaves) and ramets of
C. prolifera, including rhizoids and fronds (ca. 20e25 cm long), were
transplanted into 40 17 12 cm pots. Two 50 cm metal stakes
were attached to each pot on its outer side through cables ties, and
hammered to fix the pots into the bottom. All pots were filled with
the same amount of sediment (medium to coarse sands from a local
sandy bottom at 8 m depth). Six pots, 3 containing ca. 80e100 g
WW of C. nodosa and 3 containing ca. 70e90 g WW of C. prolifera
(these biomasses are typical from the study region, Tuya et al.,
2013a, this study), were deployed at 3 randomly-selected sandy
sites at 8e10 m depth on the 5th of July 2012. Each pot was carefully
buried into the seabed to mimic natural conditions. On the 26th of
July 2012, all pots were sealed underwater and subsequently
transported to the lab, where the sediment remaining within each
pot was weighted (dry weigh after 48 h at 60 C). Results were
expressed as % of retained sediment. This approach measured the
net effect of both above- and below ground vegetated compartments on sediment retention.
2.7. Statistical procedures
Differences in community metabolism (biomass and primary
productivity) between habitats (C. nodosa vs. C. prolifera) and times
were tested by means of 2-way ANOVAs; ‘Site’ was pooled within
‘Habitat’ to increase the power of the analysis, due to the low
replication within sites for community primary productivity at each
time (n ¼ 3). ‘Site’ is a random source of variation. Therefore, there
is no statistical restriction to pool sites within habitats, as there is
no formal hypothesis associated with ‘Site’. The model included the
factors ‘Time’ (fixed factor, as times were separated to encompass
an entire annual cycle) and ‘Habitat’ (fixed factor, orthogonal to
‘Time’). Differences in the total abundance and species density (the
number of species per area) (Gotelli and Colwell, 2001) of epifauna
were tested by three-way ANCOVAs, including the factors ‘Time’
(random factor), ‘Habitat’ (fixed factor, orthogonal to ‘Time’) and
4
F. Tuya et al. / Marine Environmental Research 98 (2014) 1e13
an entire annual cycle), ‘Habitat’ (fixed factor, orthogonal to ‘Time’)
and ‘Site’ (random factor nested within ‘Habitat’). The same model,
but in the multivariate context, tested for differences in the
assemblage structure of small- and large-sized fishes between
habitats, times and sites within habitats through PERMANOVA.
Differences in sediment retention between sites and the identity of
transplanted fragments (Cymodocea vs. Caulerpa’) were tested by a
2-way ANOVA, including the factors: ‘Site’ (random factor) and
‘Cymodocea vs. Caulerpa’ (fixed factor, orthogonal to ‘Site’). For all
tests, data were square-root or ln (xþ1) transformed when the
Cochran’s test determined that variances were heterogeneous
among groups, and pairwise comparisons (SNK tests) resolved
differences when a significant ‘Time Habitat’ was detected. When
variances remained heterogeneous despite transformations, the
ANOVAs were performed anyway, as ANOVA is robust to heterogeneous variances for balanced studies; in these cases, however,
the alpha value was set at a more conservative value (0.01) to
decrease a type I error rate (Underwood, 1997).
We calculated the trophic structure of each site within each
habitat and time by multiplying the trophic status (provided by
fishbase.org) of each species (an integer that varies between 2 and
5, the higher the value the higher in the food web the species is) by
its mean proportion and adding up all species-specific values; ttests compared mean trophic structure values between both habitats separately for both small- and large-sized fishes.
Multivariate ANOVAs (PERMANOVAs) were based on Braye
Curtis dissimilarities, and P-values calculated after 4999 permutations under a reduced model (Anderson, 2001). Canonical Analysis
of Principal coordinates (CAP) was used as a constrained ordination
procedure to visualize differences in the multivariate structure of
epifauna, small and large-sized fishes between C. nodosa and
C. prolifera dominated bottoms. To facilitate visualization of ordinations, only centroids for times and habitats (C. nodosa vs. C.
prolifera) were shown (i.e. site effects within habitat types were
pooled). All multivariate data (abundance matrices) were square
root transformed prior to analyses to down-weight the most
abundant taxa. All multivariate statistical procedures were carried
out with the PRIMER 6.0 package with PERMANOVA add-on.
3. Results
3.1. Community metabolism
Fig. 2. Differences in community metabolism: (a) Gross primary productivity (per
area) and (b) gross primary productivity (per vegetation biomass) at C. nodosa and
C. prolifera-dominated beds for each sampling time. Differences in (c) the biomass of
each species are also included. Error bars are þSE of means (n ¼ 6 for primary productivity measurements and n ¼ 12 for above-ground biomass measurements, sites
within each habitat were pooled).
Gross primary productivity (per area and vegetation biomass)
was larger (w1.4 times) in C. nodosa than in C. prolifera-dominated
beds (Figs. 2a and b; Table 1, Appendix B). This outcome was
consistent through time (Table 1). The biomass per area of aboveground tissues of C. nodosa was usually larger than C. prolifera
(Fig. 2c); however, differences were temporally inconsistent
(Table 1), e.g. no significant difference was observed in February2013 (Fig. 2c, pairwise tests for ‘Time Habitat’).
3.2. Epifauna
‘Site’ (random factor nested within ‘Habitat’). The vegetation
biomass per sample (i.e., either the total leaf biomass of C. nodosa or
the frond biomass of C. prolifera) was included as a covariate to
account for differences in the amount of available habitat between
samples. The same model, but in the multivariate context, tested for
differences in epifaunal assemblage structure between habitats,
times and sites through PERMANOVA. Differences in the total
abundance, species density and total biomass of small- and largesized fishes between habitats, times and sites within each habitat
were tested by means of 3-way ANOVAs. The model included the
factors: ‘Time’ (fixed factor, as times were separated to encompass
A total of 4655 epifaunal organisms, belonging to 104 taxa, were
identified (Appendix C). The total epifaunal abundance was larger
(w3.1 times) in C. prolifera-dominated beds than in C. nodosa
meadows (Fig. 3a; Table 2); this difference was more pronounced in
October 2011 than in November 2012 (Table 2). The species density
of epifauna was also larger (w1.7 times) in C. prolifera-dominated
beds than in C. nodosa meadows (Fig. 3b; Table 2). The CAP analysis
efficiently separated epifaunal assemblages collected from the two
2
habitats in the ordination space (Fig. 4a, d1 ¼ 0.9958). This difference in epifaunal assemblage structure between habitats was
corroborated by PERMANOVA (Table 2).
F. Tuya et al. / Marine Environmental Research 98 (2014) 1e13
Table 1
Results of 2-way ANOVAs testing the effects of ‘Time’ (fixed factor) and ‘Habitat’
(fixed factor, C. nodosa vs. C. prolifera) on gross primary production. P-values highlighted in bold denote significant results.
df
Primary production
(mL2 hL1)
Time
Habitat
Time Habitat
Residual
Primary production
(g DWL1 hL1)
Time
Habitat
Time Habitat
Residual
Biomass (mL2)
Time
Habitat
Time Habitat
Residual
MS
F
P
Untransformed data, Cochran’s test,
C ¼ 0.1840 (n.s.)
3
6150.09
2.42
0.0807
1
12913.43
5.07
0.0299
3
3297.64
1.30
0.2894
40
2546.49
Untransformed data, Cochran’s test,
C ¼ 0.3435 (n.s.)
3
0.09
0.74
0.5332
1
0.70
5.47
0.0244
3
0.013
0.11
0.9566
40
0.12
Ln (xþ1) transformed data, Cochran’s test,
C ¼ 0.3593 (P < 0.01)
3
0.42
12.22
0.001
1
0.01
0.20
0.6588
3
0.12
3.75
0.0137
88
0.03
3.3. Small-sized fishes
A total of 335 fishes, representing 19 species, were collected
(Appendix D). Overall, the total abundance, species density and
total biomass was larger (w2.1, 1.3 and 1.3 times, respectively) in
C. nodosa than in C. prolifera-dominated beds (Fig. 5aec, respectively). However, significant differences between habitats were
exclusively detected for the total abundance (Table 3), since the
species density of small-sized fishes was larger in C. prolifera than in
5
Table 2
Results of 3-way, uni- and multivariate, ANCOVAs testing the effects of ‘Time’
(random factor), ‘Habitat’ (fixed factor, C. nodosa vs. C. prolifera) and sites (random
factor nested within ‘Habitat’) on ecological attributes of epifauna. P-values highlighted in bold denote significant results.
df
Total abundance
Covariate
Time
Habitat
Site(Habitat)
Time Habitat
Time Site (Habitat)
Residual
Species density
Covariate
Time
Habitat
Site(Habitat)
Time Habitat
Time Site (Habitat)
Residual
Assemblage structure
Covariate
Time
Habitat
Site(Habitat)
Time Habitat
Time Site (Habitat)
Residual
MS
F
P
Square-root transformed data, Cochran’s test,
C ¼ 0.2296 (n.s.)
1
37.62
21.51
0.0002
1
125.87
2005.55
0.0218
1
139.10
40.07
0.0220
2
3.47
1.98
0.1562
1
13.87
221.09
0.0144
2
0.06
0.03
0.9676
31
1.75
Ln (xþ1) transformed data, Cochran’s test,
C ¼ 0.2156 (n.s.)
1
2.15
27.75
0.0002
1
4.28
13.73
0.1018
1
14.48
37.85
0.0002
2
0.38
4.93
0.0156
1
0.02
0.06
0.8270
2
0.31
4.01
0.0280
31
0.07
Square-root transformed data
1
9391.91
7.82
0.0002
1
30836.35
12.07
0.0708
1
24816.15
8.34
0.0021
2
2974.31
2.47
0.0064
1
15649.38
6.12
0.0574
2
2554.30
2.12
0.0210
31
1201.33
C. nodosa beds in October-2012 and February-2013, while the
biomass of small-sized fishes was larger in C. prolifera than in
C. nodosa beds in February-2013 (Fig. 5b and c; Table 3). The
assemblage structure of small-sized fishes differed between habitats (PERMANOVA, Table 3). Indeed, small-sized fish assemblages
from the two habitats differed along the second canonical axis of
2
the ordination space (Fig. 4b, d1 ¼ 0.8166). The trophic structure of
small-sized fish assemblages did not differ between both habitats
(t-test6 ¼ 0.9114, P ¼ 0.3955).
3.4. Large-sized fishes
A total of 759 fishes (37 species) were visually counted
(Appendix E). The total abundance and species density was larger
(w3.6 and 1.5 times, respectively) in C. nodosa than in C. proliferadominated beds (Fig. 6a and b; Table 3); this difference was
consistent through time (‘Times Habitat’, P > 0.05, Table 3). The
CAP analysis efficiently separated large-sized fish assemblages from
2
the two habitats along the first canonical axis (Fig. 4c, d1 ¼ 0.7726);
this difference in assemblage structure between habitats was
further demonstrated by PERMANOVA (Table 3). The trophic
structure of large-sized fish assemblages did not differ between
both habitats (t-test6 ¼ 0.4439, P ¼ 0.5029).
3.5. Sediment stabilization
Fig. 3. Differences in (a) total abundance and (b) species density of epifauna at
C. nodosa and C. prolifera-dominated beds for each sampling time. Error bars are þSE of
means (n ¼ 10, sites within each habitat were pooled).
Overall, C. nodosa showed a larger potential to stabilize sediments relative to C. prolifera (w1.4 times, i.e. a mean 88% vs. 63% of
sediment retention after 3 weeks, Fig. 7). However, retention of
sediments between pots with transplanted C. nodosa and transplanted C. prolifera differed among sites (Fig. 7; ANOVA:
‘Site Cymodocea vs. Caulerpa’, P < 0.01, Table 4); pairwise tests for
‘Site Cymodocea vs. Caulerpa’ showed significant differences in
sediment retention between pots with either transplanted
C. nodosa or C. prolifera at sites 1 and 2, but not at site 3 (Fig. 7).
6
F. Tuya et al. / Marine Environmental Research 98 (2014) 1e13
Fig. 4. Canonical Analysis of Principal coordinates (CAP) ordinations. Visualization of
differences in the multivariate structure of (a) epifauna, (b) small-sized fishes and (c)
large-sized fishes between C. nodosa and C. prolifera bottoms. Only centroids for times
and habitats (C. nodosa vs. C. prolifera) are plotted.
4. Discussion
Our approach has suggested significant differences in
community-scale attributes and processes between bottoms
dominated by seagrasses (C. nodosa) and bottoms covered by green
rhizophytic clonal seaweeds (C. prolifera). Changes in provision of
these functions varied in space and time, typically between 1.3 and
3.6 times, i.e. some functions differed in magnitude more strongly
than others between the two habitat types.
There was a difference in primary productivity between the two
habitats of ca. 1.4 times higher in C. nodosa compared with
C. prolifera, on a per area basis. From this perspective, both canopyforming species may play a similar role as primary producers in the
Fig. 5. Differences in (a) total abundance, (b) species density and (c) total biomass of
small-sized fishes at C. nodosa and C. prolifera-dominated beds for each sampling time.
Error bars are þSE of means (n ¼ 6, sites within each habitat were pooled).
coastal seascape. This suggests that large-scale changes from
C. nodosa seagrass to Caulerpa-dominated meadows do not cause
large changes in the uptake of CO2 and release of O2 by the system.
In this context, it has been previously reported that although
eutrophication may change the identity and structure of primary
producers from seagrass to macroalgae, it does not necessarily lead
to altered rates of C acquisition by the system (Borum and SandJensen, 1996; Stutes et al., 2007; Antón et al., 2011). Although the
magnitude of primary productivity did not greatly differ between
bottoms dominated by C. nodosa and C. prolifera, the contrasting
physiognomy of the two species (C. nodosa vs. C prolifera) profoundly affected associated biota. While the total epifaunal abundance was much larger in C. prolifera beds (w3.1 times), the total
abundance of associated fishes was considerably larger in C. nodosa
F. Tuya et al. / Marine Environmental Research 98 (2014) 1e13
7
Table 3
Results of 3-way, uni- and multivariate, ANOVAs testing the effects of ‘Time’ (fixed
factor), ‘Habitat’ (fixed factor, C. nodosa vs. C. prolifera) and sites (random factor
nested within ‘Habitat’) on ecological attributes of fishes. P-values highlighted in
bold denote significant results.
df
Small-sized fishes: total abundance
Time
Habitat
Site(Habitat)
Time Habitat
Time Site (Habitat)
Residual
Small-sized fishes: species density
Time
Habitat
Site(Habitat)
Time Habitat
Time Site (Habitat)
Residual
Small-sized fishes: total biomass
Time
Habitat
Site(Habitat)
Time Habitat
Time Site(Habitat)
Residual
Small-sized fishes: assemblage
structure
Time
Habitat
Site(Habitat)
Time Habitat
Time Site(Habitat)
Residual
Large-sized fishes: total abundance
Time
Habitat
Site(Habitat)
Time Habitat
Time Site(Habitat)
Residual
Large-sized fishes: species density
Time
Habitat
Site(Habitat)
Time Habitat
Time Site(Habitat)
Residual
Large-sized fishes: assemblage
structure
Time
Habitat
Site(Habitat)
Time Habitat
Time Site(Habitat)
Residual
MS
F
P
Untransformed data, Cochran’s test,
C ¼ 0.2346 (n.s.)
3
53.18
3.06
0.1134
1
295.02
15.24
0.0598
2
19.35
1.64
0.2102
3
61.07
3.51
0.0892
6
17.41
1.47
0.2185
32
11.81
Untransformed data, Cochran’s test,
C ¼ 0.2193 (n.s.)
3
5.39
16.87
0.0025
1
10.08
2.99
0.226
2
3.37
1.42
0.2563
3
9.69
30.35
0.0005
6
0.32
0.13
0.9908
32
2.37
Square-root transformed data,
Cochran’s test, C ¼ 0.2166 (n.s.)
3
32.93
2.54
0.1524
1
45.64
1.32
0.3693
2
34.54
1.75
0.1898
3
60.73
4.69
0.0514
6
12.95
0.66
0.6848
32
19.72
Square-root transformed data
3
4916.37
1.51
0.1744
1
7484.50
3.81
0.0282
2
1963.04
0.86
0.3896
3
3476.96
1.06
0.4120
6
3254.68
1.43
0.0726
32
2267.69
Ln (xþ1) transformed data, Cochran’s
test, C ¼ 0.2986 (P < 0.01)
3
0.74
0.50
0.6965
1
21.17
36.03
0.0267
2
0.58
2.78
0.068
3
0.51
0.34
0.7967
6
1.49
7.09
0.0001
80
0.21
Ln (xþ1) transformed data, Cochran’s
test, C ¼ 0,2586 (P < 0.05)
3
0.47
2.99
0.1177
1
2.11
42.61
0.0227
2
0.04
0.50
0.611
3
0.02
0.15
0.9282
6
0.15
1.60
0.159
80
0.10
Square-root transformed data
3
1
2
3
6
80
1789.71
25662.10
2143.51
5230.97
2215.28
1672.38
0.77
11.97
1.28
2.36
1.32
Fig. 6. Differences in (A) total abundance and (b) species density of large-sized fishes
at C. nodosa and C. prolifera-dominated beds for each sampling time. Error bars are þSE
of means (n ¼ 12, sites within each habitat were pooled).
distinct architecture. The seagrass C. nodosa has often a larger
standing stock resulting from large, strap-like, leaves (usually 500e
1200 shoots m2 and 25e40 cm long, Reyes et al., 1995; Tuya et al.,
2014) that generate complex and denser canopies. A larger canopy
provides more opportunities for refuge of associated fishes,
particularly for small-sized individuals (Gullström et al., 2008; Hori
et al., 2009; Espino et al., 2011). This notion was supported by our
0.6730
0.0006
0.2644
0.0336
0.1496
meadows (w2.1 and 3.6 times for small- and large-sized fishes,
respectively).
Coastal fish assemblages are sensitive to local changes in the
identity of the main habitat-forming species (Rotherham and West,
2002; Tuya et al., 2009). Our results have indicated a consistently
greater presence of fishes on bottoms dominated by the seagrass
C. nodosa relative to C. prolifera, as previously reported by other
studies (York et al., 2006; Verdiell-Cubedo et al., 2007). C. nodosa
and C. prolifera create 3-dimensional habitats, providing settlement, refuge, and foraging opportunities for a wide range of fish
species. These two canopy-forming species have, however, a
Fig. 7. Percent of retained sediment after 3 weeks in pots with transplanted C. nodosa
and C. prolifera vegetative fragments. Error bars are þSE of means (n ¼ 3).
8
F. Tuya et al. / Marine Environmental Research 98 (2014) 1e13
Table 4
Results of 2-way ANOVA testing the effects of ‘Site’ (random factor) and the identity
of transplanted fragments (‘C. nodosa vs. C. prolifera’) on sediment retention. P-values
highlighted in bold denote significant results.
df
Sites
Cymodocea vs. Caulerpa
Sites Cymodocea vs. Caulerpa
Residual
MS
F
P
Square root transformed data, Cochran’s
test. C ¼ 0.5971 (n.s.)
2
9.91
37.68
0.0001
1
10.71
2.91
0.2299
2
3.67
13.97
0.0007
12
0.26
results; we found a larger species density and biomass of smallsized fishes in C. nodosa meadows, particularly in periods with
maximum seagrass biomass (July-2012 and May-2013). This seasonality fits previous observations in the study region that
demonstrated pronounced seasonal variability in ecological attributes of C. nodosa and associated invertebrates and fishes (Tuya
et al., 2001, 2006), including a season of maximum vitality followed by a period of senescence (Reyes et al., 1995; Tuya et al.,
2006). Importantly, this result highlights that the value of seagrasses as habitat for small-sized fishes, relative to other adjacent
habitats (e.g. Caulerpa-dominated seabeds), may change seasonally,
as previously reported from the Mediterranean when the green
seaweed Caulerpa taxifolia colonize rocky substrates previously
dominated by the seagrass Posidonia oceanica (Francour et al.,
1995). As a range of studies have highlighted, when biogenic habitats deteriorate, associated resident fish assemblages are negatively affected from a biodiversity perspective, what can have
implications for associated commercial fisheries (Hauxwell et al.,
1998; Cebrián et al., 2009). It is worth noting, moreover, that our
surveys for both small and large-sized fishes were limited to
daylight hours (Robblee and Zieman, 1984); the distribution and
abundance of fish assemblages may change between the day and
nighttime and, as a result, we cannot generalize our results to all
circumstances.
Epifaunal invertebrates are sensitive to changes in plant structure and associated epiflora (Edgar, 1990; Thomsen et al., 2010), so
differences in the diversity, abundance and structure of invertebrate assemblages are expected between different types of vegetation within the same geographical and environmental context
(Sirota and Hovel, 2006). We found relatively low epifaunal abundances in C. nodosa meadows, possibly explained by space limitation, because C. nodosa has a low leaf surface area and low cover of
algal epiphytes (Reyes and Sanson, 2001) compared to other seagrasses, such as Posidonia sinuosa and Amphipholis griffithii
(Gardner et al., 2013). Moreover, unlike other seagrasses like A.
griffithii, C. nodosa does not exhibit structural complexity across the
vertical axis, and therefore does not provide complex living space in
the vertical plane (Gardner et al., 2013). Epifaunal assemblages
may, therefore, be subjected to substrate competitive exclusion due
to space limitation (Duffy and Harvilicz, 2001) and high predation
pressure, mainly from fishes (Edgar and Shaw, 1995). Epifaunal
organisms, particularly crustaceans, are the main constituent of
diets of seagrass-associated fishes (Klumpp et al., 1989; Connolly,
1994). It is possible that the relatively low abundances of epifauna
in C. nodosa seagrass beds are caused by stronger ‘top-down’ control. Despite the trophic structure of fish assemblages did not
significantly differ between C. nodosa and C. prolifera habitats, the
larger abundances of fishes in C. nodosa meadows may partially
support this idea. The relatively large epifaunal abundance in
C. prolifera beds was unexpected, because Caulerpa species usually
contain caulerpenyne e a major secondary metabolite (Jung et al.,
2002; Box et al., 2010) that can be toxic and deter herbivorous
feeding (Smyrniotopoulos et al., 2003). In contrast, Caulerpa induces organic enrichment of the seabed (Holmer et al., 2009), and
may thereby increase the local abundances of epifauna (SánchezMoyano et al., 2001).
Submerged macrophytes reduce near-bed water velocity and
modify the local sediment transport, significantly increasing wave
attenuation (Koch et al., 2009; Infantes et al., 2012). In addition,
seagrass rhizomes and roots extend inside the sediment and
contribute to its stabilization by altering the erodability (Fonseca,
1996; Christianen et al., 2013). Experimental evidence of sediment stabilization remains, however, scarce (but see Christianen
et al., 2013), including differences among different types of
shallow-water vegetation. This study has suggested that C. nodosa
has a larger capacity to retain sediments than C. prolifera, even
though Caulerpa stolons, in the Mediterranean, can also have high
sediment-retention capacity, favoring sediment stabilization and
protection against erosion (Hendriks et al., 2009). This is not surprising, as the reticulated below-ground compartments of the
seagrass C. nodosa create a complex 3-dimensional underground
system that is otherwise absent in bottoms dominated by
C. prolifera. These results reinforce the notion of the contribution of
seagrasses to sediment stabilization and coastal protection
(Infantes et al., 2012), including low-canopy seagrass species
(Christianen et al., 2013), such as C. nodosa.
The simultaneous assessment of multiple ecosystem attributes
and functions simultaneously is challenging, but pertinent. Because
of complex interrelations and interactions among the different
biological elements of ecosystems, different ecosystem attributes/
processes may not be good surrogates for one another. For example,
our study has identified a mismatch between primary production,
epifaunal and fish assemblages between bottoms dominated by
either C. nodosa or C. prolifera. Therefore, management of
ecosystem services associated with ecosystem functions cannot be
exclusively based on one function/service that is expected to
merely benefit other services (Bennett et al., 2009). The ‘Cymodocea
vs. Caulerpa’ case study provided empirical evidence of differences
in four ecosystem functions between shallow habitats dominated
by seagrasses and green rhizophytic seaweeds. Our study, however,
was limited to two sites within each habitat type at an oceanic island. It is obvious that similar comparisons from other regions,
encompassing a range of locations under distinct environmental
scenarios, may reach different results, so similar studies are
necessary to assess the generality of our interpretations.
Author contributions
Fernando Tuya conceived and designed the study, performed
research, analyzed data, wrote the paper; Lidia Png-González performed research, analyzed data, commented on the paper; Rodrigo
Riera performed research, analyzed data, commented on the paper;
Ricardo Haroun conceived the study, commented on the paper;
Fernando Espino performed research, analyzed data, commented
on the paper.
Acknowledgments
This study was partially supported by the UE project ECOSERVEG, within the BEST initiative (Voluntary Scheme for Biodiversity and Ecosystem Services in Territories of the EU Outermost
Regions and Oversees Countries and Territories, Grant n
07.032700/2012/635752/SUB/B2). F Tuya was supported by the
MINECO ‘Ramón y Cajal’ program. We acknowledge T Sánchez for
his help during fieldwork and M Thomsen and D Smale for
providing valuable comments on a previous draft.
F. Tuya et al. / Marine Environmental Research 98 (2014) 1e13
9
Appendices
Appendix A
Environmental scenario of each study site within habitats dominated by either Cymodocea nodosa or Caulerpa prolifera (data from Tuya et al., 2014).
Cymodocea nodosa
Latitude
Longitude
Depth (m)
Sediment type
Mean annual SST
Mean PAR
Caulerpa prolifera
Site 1
Site 2
Site 1
Site 2
27 51’22.7500
15 23’12.2400
5
Coarse sands
21.2 C
8.13 E m2 day1
27 52’11.5400
15 23’6.3600
8
Coarse sands
21.2 C
8.15 E m2 day1
27 55’4.5500
15 22’52.3200
6
Coarse sands
21.2
8.16 E m2 day1
27 55’48.5400
15 22’24.1000
7
Medium sands
21.4
8.12 E m2 day1
Appendix B
Community net primary production (NP) and respiration (R) rates (mg C h1) for sites within C. prolifera or C. nodosa dominated bottoms. Gross primary production rates
according to different incubation times on a C. nodosa meadow (pilot study) are also included.
C. prolifera
C. nodosa
Site 1
June 2012
NP (g DW1)
R (g DW1)
NP (m2)
R (m2)
September 2012
NP (g DW1)
R (g DW1)
NP (m2)
R (m2)
February 2013
NP (g DW1)
R (g DW1)
NP (m2)
R (m2)
May 2013
NP (g DW1)
R (g DW1)
NP (m2)
R (m2)
Times (h)
Gross primary production (m2)
Site 2
Site 1
Site 2
Mean
SD
Mean
SD
Mean
SD
Mean
SD
0.34
0.09
58.02
38.17
0.11
0.02
20.81
4.92
0.34
0.11
57.60
36.73
0.09
0.10
19.34
34.39
0.35
0.12
59.27
55.12
0.08
0.07
5.56
12.12
0.50
0.29
87.50
86.30
0.24
0.19
33.66
33.37
0.37
0.30
65.10
59.34
0.06
0.25
16.24
50.27
0.09
0.15
35.02
19.77
0.07
0.20
36.29
20.67
0.42
0.20
86.67
51.92
0.18
0.23
30.45
31.59
0.22
0.07
51.13
0.11
0.18
0.24
30.91
45.39
0.84
0.15
61.88
60.74
0.63
0.14
6.16
39.36
0.20
0.04
32.25
13.40
0.11
0.05
19.78
13.41
0.90
0.01
49.38
17.94
0.34
0.01
7.70
22.80
0.72
0.03
53.23
16.31
0.32
0.04
15.83
25.37
0.23
0.03
56.77
7.69
0.06
0.01
4.51
4.43
0.36
0.08
29.82
24.67
0.33
0.08
11.79
20.67
0.55
0.21
87.89
53.61
0.20
0.23
5.54
48.75
0.63
0.01
61.20
6.56
0.21
0.03
18.46
20.49
1:00
51.76 25.65
1:30
55.86 31.34
2:00
67.87 38.22
2:30
66.89 27.54
3:00
61.48 32.22
Appendix C
Mean abundances (ind 0.04 m2) of epifaunal organisms per site within each habitat type and time.
Group
Species
November-2011
C. nodosa
Site 1
Nematoda
Nematoda
Nematoda
Olygochaeta
Polychaeta
Polychaeta
Polychaeta
Polychaeta
Polychaeta
Polychaeta
Polychaeta
Polychaeta
Polychaeta
Polychaeta
Polychaeta
Polychaeta
Polychaeta
Calyptronema sp.
Enoplida sp1
Unidentified
Unidentified
Aponuphis bilineata
Platynereis dumerilii
Nereididae sp.1
Exogone naidina
Salvatoria sp.
Streptosyllis bidentata
Syllis sp.
Demonax brachychona
Desdemona sp
Sabellidae sp.1
Aonides oxycephala
Polyophthalmus pictus
Schroederella laubieri
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
October-2012
C. prolifera
C. nodosa
Site 2
Site 1
Site 2
0
0
0
0
0
0
0
0
0.1
0.4
0.5
0
0
0
0
0.2
0
0.9
1
0
0
0
0
0.1
0.2
0
0
0
0
0
0
0
6
0
0
0.1
0
0
0.1
0.2
0.8
0
0
0
0
0.5
0.2
0.1
0.1
0.1
0.1
Site 1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
C. prolifera
Site 2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Site 1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Site 2
0
0
0.3
0
0
1.7
0
0
0.1
0
0
0
0
0
0
0
0
(continued on next page)
10
F. Tuya et al. / Marine Environmental Research 98 (2014) 1e13
Appendix C (continued )
Group
Species
November-2011
C. nodosa
Sipunculidea
Pycnogonida
Actinopterygii
Asteroidea
Ophiuroidea
Copepoda
Cumacea
Decapoda
Decapoda
Decapoda
Decapoda
Decapoda
Isopoda
Isopoda
Isopoda
Isopoda
Isopoda
Isopoda
Tanaidacea
Tanaidacea
Tanaidacea
Tanaidacea
Tanaidacea
Tanaidacea
Ostracoda
Ostracoda
Ostracoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Amphipoda
Bivalvia
Bivalvia
Bivalvia
Gastropoda
sp. 1
Unidentified
Opeatogenys cadenati
Coscinasterias tenuispina
Unidentified
Unidentified
Unidentified
Caridea
Galatheoidea
Paguroidea
Brachyura
Larva
sp. 1
sp. 2
sp. 3
sp. 4
sp. 5
sp. 6
Apseudes sp.
Apseudes talpa
Leptochelia savignyi
Tanais dulongii
Zeuxo exsargasso
Unidentified
Halocyprida
Myodocopida
Podocopida
Caprella acanthifera
Caprella liparotensis
Phtisica marina
Pseudoprotella phasma
Mantacaprella macaronensis
Ericthonius punctatus
Ischyrocerus inexpectatus
Microjassa cumbrensis
Ampithoe helleri
Ampithoe ramondi
Ampithoe sp.
Aora gracilis
Aora spinicornis
Aora sp.
Autonoe longipes
Microdeutopus anomalus
Microdeutopus damnoniensis
Microdeutopus stationis
Microdeutopus sp.
Cheiriphotis sp.
Corophium sp.
Leptocheirus mariae
Leptocheirus pilosus
Leptocheirus sp.
Medicorophium minimum
Apherusa bispinosa
Apherusa chiereghinii
Apherusa vexatrix
Apherusa sp.
Lysianassina longicornis
Amphilochus neapolitanus
Peltocoxa mediterranea
Dexamine spinosa
Liljeborgia sp.
Elasmopus sp.
Maera inaequipes
Harpinia sp.
Stenothoe monoculoides
Pereionotus testudo
Microprotopus longimanus
Unidentified
Cardiidae sp. 1
Unidentified1
Unidentified2
Bittium sp.
October-2012
C. prolifera
C. nodosa
C. prolifera
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
0
0.1
0
0
0
0
0
0
0
0
0
0
0.1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.8
0
0.7
0.4
0
0
0.4
0
0.3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2.1
0
0
0
0
0.2
0.2
0
0
0.2
0
0
1.5
0.5
0
0
0
0
0
0
0
0
0
0
0
0.1
0
4.7
1.1
14.5
18.1
2.3
0.1
0
0
1.9
0
0
0
0
0
0
0
0
0.3
0
0
0
0
0
0
0
0
0.7
0.1
0
0.3
0
0.8
0
0
0
0
0.9
0.1
0
0
0
0
0
0.3
0
0
0
0
0
0
0
0.7
0
0.9
0.6
0.1
0
0
0
0.5
0.1
0
0
0
0
0
0
0
0
0.7
0.5
0
0
0
0.2
0
0.1
0
0
0
2.5
0
0
1.4
0
0.1
0
1
33.1
0
0
0
0
0.2
0
0
0
0.1
0
0.1
0
0
0
2.1
0.1
0.1
0.1
0.1
0
0
0
0
0.3
0.7
0.2
0.1
0
0
0
0.2
0.1
0.1
0.6
0.4
0
0.3
0.3
0.1
0
0.3
0
0
0
0
0
0
0
0
0
0
0
1.4
1
0
0
3.3
8.5
0.5
7.7
28.2
1.9
0
0.1
0
0
17.1
0
0
0
0
4.1
0.5
0.5
0.2
0
3.7
0.7
0.1
0
6.7
0.2
0
0
0.2
0
2.3
0.4
0
0
0.5
0
0
2.8
0.3
0.2
0.1
0.1
0
0
0.2
0
0
0
0.1
0
0
0
0
0
0
3.9
0.1
0
0
0
0
0
0
0
0
0
0
0
0
0
0.5
0
0.5
0.6
0.8
0
0
0
0
0.6
0
0.5
0
0.1
0
0
0
0
0
0
0
0
0
0
0
0.1
0
0
0
0
0
0
0.4
0
0
0
0
0
0
0
0.1
0
0
0
0
0
0.6
0.1
0
0.1
1.1
0
0
0
0
0.1
0
13.8
0.8
0.4
0.1
0
0.1
0
0
0
0.1
0
0
0
0
0.1
1.2
0
0.9
1.6
1.4
0.1
0
0
0
3.3
0.2
0.6
0
0.3
0
0
0
0
0
0
0
0
0.1
0
0
0
0
0
0
0
0
0
0.4
0
0
0
0
0.3
0
0
0.2
0
0.3
0.1
0
0
1.9
0
0
6.9
3.6
0.5
14.4
1.1
5.3
1.5
0.3
0
0
0.2
0.6
0.5
0
0
0
22.1
0
0
0
0.1
0.6
0
0.1
0
2
1.6
0
0
0
0
0.1
2.6
0
0
3
0
0
5
0
5.1
0.1
0
0
0.2
0.1
0
0
2.2
0.8
0
0
1.6
0.1
0.1
19.4
0.1
0
0
0.2
0
0
0
0.4
0
0.5
0.7
12.9
0
2
0
0
0.3
0.4
0
3
0
2.3
0.2
0
0.2
0
1.2
0.2
0
0.1
0
0.4
5
0.1
0
0.1
0
0
0
0
0
1.6
1.3
0.2
0
0
0
0
7.2
0
0
0.3
0.6
0
0
0
0
0.5
0
0
0
0
0
0
1.5
0
0
0
0.1
0
0
9
0
0
0
0
0
0
0
0.9
0
0.3
0.3
2.3
F. Tuya et al. / Marine Environmental Research 98 (2014) 1e13
11
Appendix C (continued )
Group
Species
November-2011
October-2012
C. nodosa
C. prolifera
Site 1
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Gastropoda
Eulimidae sp.1
Cerithiopsis sp.
Nystiellidae sp. 1
Alvania sp.
Rissoinae sp.1
Anachis sp.
Mitrella sp.
Vexillum zebrinum
Volvarina sp.
Pyramidella dolabrata
Retusidae sp. 1
Nudibranchia
Smaragdia viridis
Tricolia sp.
Trochidae sp. 1
Turbinidae sp. 1
0
0
0
0.1
0
0
0.1
0
0
0
0
0
0
0
0
0.1
C. nodosa
Site 2
Site 1
Site 2
0
0
0.7
3.4
0
0
0.1
0.9
0
0
0.8
0
0
0
0
0.1
0
0
0
0
0
0
0.9
0
0
0
0.3
0.1
0.4
0
0
0
0
0
0.1
0
0
0.1
1.8
0.4
0
0
0.6
0
0.3
0
0.1
0
Site 1
C. prolifera
Site 2
0
0
0
0
0.2
0
0
0
0.1
0
0
0
0.3
0.4
0
0
0
0.1
0
0.5
1.1
0
0
0
0
0.1
0.1
0
0.5
0.7
0
0.1
Site 1
Site 2
0.1
0.4
0
16.6
5.1
0
0.1
0
0.1
0
5.3
0
0
0.2
0
0
0.1
0.1
0
4
9.1
0
0
0
0
0
0.9
0
0.1
0.4
0
0.1
Appendix D
Mean abundances (ind per trawl) of small-sized fishes per site within each habitat type and time.
July-2012
Bothus podas maderensis
Canthigaster capistrata
Gobius niger
Mullus surmuletus
Mycteroperca fusca
Nerophis ophidion
Scorpaena maderensis
Scorpaena porcus
Sparisoma cretense
Sphoeroides marmoratus
Spondyliosoma cantharus
Stephanolepis hispidus
Symphodus trutta
Sygnathus arcus
Sygnathus typle
Synodus saurus
Synodus synodus
Uranoscopus caber
Xyrichtys novacula
October-2012
February-2013
May-2013
C. nodosa
C. prolifera
C. nodosa
C. prolifera
C. nodosa
C. prolifera
C. nodosa
C. prolifera
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
0
0.67
0
0.33
0.33
0
0
0
3
0.33
0
0
0.67
0
4
0
0.67
0
0.67
0
3
0
0
0
0
0
0
8.33
0.33
0.33
0.33
1.33
0
2.33
0
0
0
0.33
0.33
0.67
0
0.33
0
0
0
0
0.33
0
0
0
0.33
0
0.33
0
0
0
0
0
0.67
0
0
0
0
0
0
0
0
0
0
1
0
0.67
0
0
0
0
0.33
0.33
0
0
0
0
0
0
0.33
0.33
0
0.33
0
0
4
0
0
0.33
0.67
1.00
1.67
0
0
0
0
0
0.33
4.67
2.67
0
0
0
0
2
0
0
0
0.33
0.67
3
1
0
0
0
0
0
3.33
0
0
0.33
0
1
1
0
0.33
0
0
0.67
1.67
0
0
0
0
0
0
1.67
0
0
0.33
0
0.33
2
0.33
0.67
0
0
0
1.67
0
0
0
1
0
0
0.67
1.00
0
0
0
0
1
0
0
0
1.33
0.33
0.67
0
0
0
0
0
0
2.67
0.67
0
0.33
0
0
0.33
0
0.67
0
0.33
0
0.67
0.67
0
0
0
0
0.67
1.00
1
0
0
0
0
0
0
0
0
0
0.33
0
0
0
0
0
0
0
0.67
0
0
0.33
0.67
0
0
0
0
0
0
0.67
2.67
0
0
0
0
0
0
4
1.33
0.33
0
0
0
1
0
0
0
0
0
1.33
0
0
0
0
0.33
0.67
2
0.67
0
0
0
0
0.33
0
0
0
1.33
0.33
1
0
0
0
0
0
0
0.67
0.67
0
0.33
0
0
1
0
0.33
0
0
0.33
0
0
0
0
0
0
0
0.67
0.67
0
0.33
0
0
0
0.33
0.33
0
0
Appendix E
Mean abundances (ind 100 m2) of large-sized fishes per site within each habitat type and time.
July-2012
Bothus podas maderensis
Canthigaster capistrata
Dasyatis pastinaca
Diplodus annularis
Diplodus sargus cadenati
Diplodus vulgaris
Gobius niger
Mullus surmuletus
Myliobatis aquila
Pagellus erythrinus
Pagrus pagrus
Pegusa lascaris
Pseudocaranx dentex
Serranus cabrilla
Serranus scriba
October-2012
February-2013
May-2013
C. nodosa
C. prolifera
C. nodosa
C. prolifera
C. nodosa
C. prolifera
C. nodosa
C. prolifera
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
0
7.67
0
0
0
0
0
0
0
0
0
0
0
0
0.17
0
6.00
0.17
0
0
0
0
0
0
0
0
0
0
0
0
0
1.83
0.03
0
0
0
0
0
0
0
0
0
0
0.17
0
0
0.67
0
0
0
0
0
0
0
0
0
0
0
0
0
0.17
3.83
0
0.17
0.50
0.33
0
0
0
0
0
0
1.00
0
0
0.17
5.17
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1.67
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1.33
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3.50
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4.17
0
0
0
1.33
0
0.83
0.17
0.17
0
0
0.50
0
0
0
1.19
0
0
0
0.22
0.17
0.14
0.03
0.03
0
0.33
0.08
0
0
0
1.50
0
0
0
0
0
0
0.17
0
0
0
0
0
0.17
0.03
2.28
0
0
0
0.26
0.03
1.55
0.06
0.03
0
0.06
0.10
0
0.06
0
1.50
0
0
0
0
0
0
0.17
0
0
0
0
0
0
0
3.50
0.17
0
0
0
0
0
0
0
0
0
0
0
0
0.17
2.00
0
0
0
0
0
8.33
0
0
0
0
0
0
0.17
(continued on next page)
12
F. Tuya et al. / Marine Environmental Research 98 (2014) 1e13
Appendix E (continued )
July-2012
Sparisoma cretense
Sphoeroides marmoratus
Spondyliosoma cantharus
Stephanolepis hispidus
Symphodus trutta
Synodus saurus
Synodus synodus
Trachinus draco
Xyrichtys novacula
October-2012
February-2013
May-2013
C. nodosa
C. prolifera
C. nodosa
C. prolifera
C. nodosa
C. prolifera
C. nodosa
C. prolifera
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
Site 1
Site 2
1.50
0.33
0
0
0
0.17
0
0
0.33
1.00
1.17
0
0.17
0
0
0
0
0.33
0.50
1.69
0
0.19
0
0
0.17
0
0.06
0
0.17
0
0.17
0
0
0.17
0
0
2.50
1.00
0
0
0
0.17
0
0
0
2.17
1.50
0
0
0
0
0
0
0.17
0
1.00
0
0.17
0
0.17
0
0
0
0
0.83
0
0.17
0
0
0
0
0.33
1.33
0.17
0
0
0
0
0
0
1.00
5.33
1.33
4.50
0
0.17
0
0
0
0.17
1.72
0.89
0.75
0.33
0.03
0
0
0
0.03
0
0.67
0
0.50
0
0
0
0
0
18.67
0.67
0.33
1.17
0
0.50
0
0.33
0.50
4.51
0.76
0.93
0.36
0.03
0.08
0
0.06
0.34
0
2.17
0
0.17
0
0
0
0
0
0.50
2.00
0
0
0
0.17
0
0
0
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