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Mark Wilson: Marine Biology & Coastal Ecology 2009
Dr Andy Foggo
Diversity and abundance of reef associated fish on a
non-hermatypic tropical reef
Mark Wilson
Dr Andy Foggo
Diversity and abundance of reef associated fish on a
non-hermatypic tropical reef
Abstract
The recent concern over the loss of habitat and species in the tropics and
the increasing bleaching and subsequent death of coral species make
study into the habitat and which aspects of it closely correlate with fish
diversity and abundance a topical one.
Many have considered habitat
complexity to be fundamental in the structuring of fish assemblages, but
as is the case on coral reefs often there is a biological element to the
physical structure. It has been argued that this causes difficulties when
inferring which components of the habitat are responsible for the observed
patterns in diversity and abundance.
In this study the diversity and
abundance of reef associated fish species were recorded using two different
visual census survey methods in conjunction with a benthic survey. The
aim was to investigate which aspects of the habitat correlated with the
diversity and abundance of reef associated fish species in the absence of
the structural complexity of hermatypic reefs. A total of 60 transects and
12 rovers were conducted across the twelve study sites, and in total 71
species were recorded from 30 families.
Results revealed sites with the
highest number of species were also those with the highest numbers of
individuals. Similarly sites with low numbers of species had low numbers
of individuals. Using multiple regression analyse soft coral cover was the
most significant predictor at individual sites, while in predicting the whole
assemblage silt and rubble were the most significant. While it would have
been useful to of had a further measure of habitat complexity such as hole
size with which to infer more about the physical habitat, results did
indicate a biological relationship existing between the fish assemblages and
the habitat at the rocky reefs of Los Cobanos.
Introduction
While
much
concentrates
literature
on
exists
biological
on
factors
community
affecting
recruitment, predation and competition.
ecology
the
assemblages
majority
such
as
Besides these biological factors
the physical make up of the habitat and its complexity has a role to play in
constructing assemblages. Habitat complexity can vary depending on the
species group and the spatial scale at which the habitat is measured (Tews
et al 2004). Tews et al (2004) use what they call the keystone structure
concept to highlight that certain ecosystems may be dominated by a single
keystone structure and that several species groups may depend on this one
important aspect. This view is shared somewhat by Gratwicke and Speight
(2004) who suggest that habitats that are inherently different in species
richness are due to habitat type rather than complexity.
The physical
habitat is often at least in part comprised of a biological element with some
finding correlations between biological factors such as coral species
richness and fish species richness (Roberts & Ormond 1987, Ohman &
Rajasuriya 1998) while others do not (Risk 1972, Luckhurst & Luckhurst
1978).
With the recent concern over habitat and species loss in the
tropical marine environment studies into which aspects of the environment
or habitat affect fish species diversity could aid future conservation effort.
In their 1961 paper on bird species diversity MacArthur & MacArthur
hypothesised that faunal diversity is generally related to the complexity of
the habitat. Since this time many researchers have tested these ideas in
the marine environment and considered the distribution of species and
diversity of reef fish to be a function of substrate and shelter
characteristics (Risk 1972, Luckhurst & Luckhurst 1978, Bell & Galzin
1984, Friedlander & Parrish 1998, Ferreira et al 2001, Gratwicke &
Speight 2004, Lingo & Szedlmayer 2006).
Risk (1972) found what he
described as a striking positive correlation between fish species diversity
and substrate topographic complexity. Using rugosity, vertical relief,
percentage coral cover and sand as variables Luckhurst & Luckhurst
(1978) found increased complexity correlated with increased diversity. Bell
& Galzin (1984) examined the effects of live coral cover in isolation from the
effects of habitat complexity, this was achieved by choosing study sites
that showed comparable complexity but had differing percentages of live
coral cover.
Their findings differed from those of Risk (1972) and
Luckhurst & Luckhurst (1978), and indicated that the amount of live coral
cover may be more important to fish than previously thought
thus the
complexity of coral reef habitats should be considered in terms of both live
coral and a separate structural component (Bell & Galzin 1984).
In varying marine environments it has been shown that diversity is
increased by a favourable habitat (Friedlander & Parrish 1998, Ferreira et
al 2001, Lingo & Szedlmayer 2006,) but what is it that makes habitats
favourable? In the open ocean isolated seamounts are often described as
oases and hotspots of biodiversity (McClain 2007). Burnaford (2004)
suggests that kelp forests have large impacts on communities by providing
protection from predation or stressful abiotic conditions.
In the tropics
hermatypic coral reefs form complex structures either continuously
distributed over a large area; or widely spaced and patchily distributed in a
sandy area (Nanami & Nishihira 2003), these patchy reef environments
provide diverse microhabitats, of varying size and complexity in
an
otherwise barren area, thus affecting the spatial distribution of fishes,
recruitment of juveniles and also predation intensity (Levin et al 2000,
Nanami & Nishihira 2003). In areas of the tropics devoid of hermatypic
coral tropical rocky reef patches will provide an analogous habitat for reef
associated fish.
The rock surface provides a stable surface where
microscopic algae, macroalgae, soft corals, gorgonians and sponges are
able to thrive (Gratwicke & Speight 2004). These algae provide grazing for
many fish species (Carpenter 1986, Lawson et al 1999) and are the primary
source of production on rocky reefs, (Klumpp & McKinnon 1989). While a
variety of habitats (Gratwicke & Speight 2005) including artificial reefs
(Lingo & Szedlmayer 2006) have been used to test for relationships
between species richness of tropical reef associated fish and habitat
complexity, the majority of have been conducted on coral reefs. The area
around Los Cobanos, El Salvador has rock derived patch sites with some
soft coral growth and with little connectivity between sites in an otherwise
sandy area. These patch reefs sites are comprised of rock of varying size
and vertical relief, providing an ideal platform from which to test for
relationships between the habitat
and tropical reef associated fish
assemblage structure in the absence of live hermatypic coral.
The
hypothesis that benthic variables should influence the number of fish
species and individuals present at each site was tested as well as tests that
benthic composition might be driving β diversity.
Materials and methods
Collaborators
The survey of the reef at Los Cobanos, El Salvador was carried out with the
help of Natural history museum Stockholm, El Salvador divers, a local dive
facility who in conjunction with FUNZEL (Conservation group) provided all
dive equipment and enlisted the help of Mr Mario Campos as boat captain,
a local artisan fisherman with over 30 years experience and knowledge of
the area.
Mr Lee Munson, an experienced diver with reef monitoring
experience conducted all survey dives.
Study sites
The study was performed from Los Cobanos (130 30’16.7”N, 0890 48’37.6”
W), in Acajutla on the South Coast of El Salvador, South of San Salvador.
The study area (70km2) spans a coastal length of approximately 14 km and
extends 5km off shore. Twelve study sites were selected and GPS marked
by Mario Campos
based on his knowledge with considerations given to
accessibility, familiarity, depth and comparability.
Species identification
A list of candidate species for the area was obtained from fishbase
prediction (www.fishbase.com). Exploratory dives were then conducted in
order to assess the actual species present.
Data collection methods, equipment and modifications
Data were collected through underwater visual census; using the modified
Meso American Barrier Reef System (MBRS) technique (Almada-Villela et al
2003).
Data collected comprised of fish abundance, size and benthic
composition at each site. Because of differences in coral cover, time and
manpower constraints modifications were made to the underwater visual
census. The size, health and species aspect of coral habitat analysis was
omitted due to the lack of corals found at Los Cobanos, and the benthic
survey was performed at the minimum due to time constraints.
Fish surveys were performed by both the rover diver method and 30 metre
(m) transects, see separate rover and transect sections below.
Underwater safety
All dives were conducted by trained divers using PADI (www.PADI.com)
dive tables, staying well within no decompression limits. No solo dives were
conducted; oxygen and a radio were carried on board the vessel at all
times.
Rover dives
Quick estimations of fish abundance were determined using the rover diver
method recording fish species and numbers in an imaginary 2m window
while finning for 30 minutes (Almada-Villela et al 2003).
Fish numbers
were ranked into categories using the following:1 = Single (S), 2 – 10 = Few
(F) 10 – 100 = Many (M), 100+ = Abundant (A)
A second diver meanwhile recorded topographical features such as depth,
rock size, current strength/direction, visibility, and temperature. This
second diver also takes any underwater pictures necessary for fish
identification or recording benthos.
Fish recording transect dives
Five 30m fish transects with a 2m recording window were conducted at
each site following Ribiero (2005). Surveys were conducted between 09:30
and 16:30 hours to take advantage of maximum light levels and to avoid
crepuscular periods when fish may become more or less active. The time,
bow direction, temperature, site, salinity, turbidity (using a sechi disk), sea
state and cloud cover were noted at the time of all transect dives and
recorded on the captain’s slate.
A one metre T bar was used during surveys; this was marked at 25cm
increments to aid both in fish size estimation and to aid visualisation of the
2m survey window. The 30 metre tape was weighted at the end and this
marked the central position of the study site. Transects were conducted
around this position in North, East, South and West directions, with the
fifth and final transect being parallel to the last and approx five metres to
one side. Where large rock structures were encountered the transect
direction was adjusted slightly to go over or around these, to gain an
accurate record of the site without making the horizontal distance travelled
deviate greatly. Following standard protocol, the survey diver swims at a
constant rate throughout the transects and records all fish observed in the
survey window on a pre-prepared slate. To avoid any potential bias the
same diver took all the fish recordings during the project. As outlined in
the rover dive section the assistant diver recorded all abiotic variables.
Benthic Survey
Benthic habitat composition was assessed by three 30m transects each of
100 points and recorded on pre-prepared slates. These were conducted in
conjunction with the fish transects, following the same procedure as
described above. By exchanging fish slates for pre-prepared benthic slates
at the end of the fish transect the benthic portion of the survey could be
conducted on the return to the central position, before starting the next
fish transect
Statistical analysis
To characterise the fish assemblages within and between the sites, the
entire data set (square-root transformed) was used to produce an
ordination plot employing non-metric multidimensional scaling (MDS)
based upon a Bray-Curtis similarity matrix in PRIMER 6.0 (Clarke &
Warwick 2001). The cohesion of samples (transects) within sites was then
tested using 1-way anosim (Clarke 1988), with sites as a factor.
The hypothesis that benthic variables should influence the number of fish
species and individuals present at each of the 12 sites was tested first
using the rover data. Benthic data in the form of percentage covers were
transformed (arcsine transformation) prior to analysis. Stepwise multiple
regression (SPSS 15.0) was used to test for power of the full suite of
benthic data (see field methods for list of variables) to predict first the
number of fish species at each site, and then the number of fish
individuals.
Regression models were validated by analysis of residuals and an
examination of co-linearity diagnostics.
The environmental data were then tested for correlation with the whole
assemblage from the rover data using the BVSTEP procedure in PRIMER
6.0 (Clarke & Warwick 2001). Environmental variables were normalised
prior to analysis, and a Bray-Curtis distance matrix was calculated for the
fish assemblage data using square-root transformed abundance class
values. BIOENV (Clarke & Ainsworth 1993) was also used to test the
separate environmental variables in turn.
To test the hypothesis that the benthic composition of sites might be
driving the β diversity of fish assemblages at them, Sørensen’s index of β
diversity (Sørensen 1948) was calculated from the amalgamated fish
transect data for each site, and translated into a triangular matrix. A
similar matrix of site environmental differences was then produced using
normalised environmental variables and a Euclidean distance measure in
PRIMER. The test for concordance between distance matrices (PRIMERRELATE; Clarke & Warwick 2001) was then used to test for correlation
(Spearman’s Rank Correlation) between the β diversity and environmental
difference matrices. This test was then repeated using only coral cover, silt
and sponges as environmental variables following the results of multiple
regression analyses described above. Finally, the analysis was repeated
again using only coral cover in the environmental calculation, as this
variable had the greatest individual predictive power in multiple regression.
The hypothesis that β diversity should be related to the geographical
distance between sites was also tested.
The site to site distances were
calculated using site positions converted from GPS lat/long data to UTM
grid co-ordinates, and distances in metres between sites calculated in
EXCEL. The resulting triangular distance matrix was then correlated with
the triangular β diversity distance matrix using RELATE as described
above.
Finally, to test the validity of conducting the rover diver method as an
alternative to intensive transects in fish surveys the RELATE procedure in
PRIMER was used to test if rover and transect data demonstrate the same
pattern of differences between sites. Both the data sets were square root
transformed prior to analysis, first with rover data ranks assigned median
abundance class values, to incorporate fish abundance as a contributor to
the Bray-Curtis distance metric, and then with presence/absence data.
Results
A total of 60 transects and 12 rovers were conducted across the twelve
study sites, and in total 71 species were recorded from 30 families. From
the transect survey the mean number of species observed per site was 14,
ranging from 7-19. The rovers had a mean of 31 species ranging from 1839 species per site. Using the transect data the number of individuals
recorded per site varied hugely, with a mean of 240 and ranging from 271048. Sites with the highest number of species were also those with the
highest numbers of individuals. No single species occurred at all sites, and
only two sites had species unique to them.
The sites differed in their
assemblage composition (Figure 1), anosim indicated significant overall site
differences in assemblage (R = 0.486; P = 0.001), with 56/66 pair-wise site
comparisons being significantly different (P < 0.05).
Stepwise multiple regression using the rover data indicated that three
benthic variables together explained 81.7% (adjusted R2) of the variation in
number of fish species at the sites. The single most powerful predictor was
coral cover, explaining 53% (adjusted) of the pattern (See table 2 for full
results).
Using the rover data to predict number of fish individuals stepwise
multiple regression indicated that only coral cover was a significant
predictor of abundance, explaining 39.2% (adjusted R2) of the pattern. (See
table 3 for full results).
For the corresponding stepwise multiple regressions using the transect
data to predict number of fish species, See table 4.
For corresponding
stepwise multiple regressions using the transect data to predict number of
fish individuals, see table 5.
BVSTEP analysis indicated that the combination of silt, rubble, coralline
algae and rock size best correlated with the whole assemblage sampled by
the rover surveys (ρ= 0.648); BIOENV indicated that the best individual
correlations were between assemblage structure and silt (ρ = 0.428),
Rubble (ρ = 0.425) and Coralline Algae (ρ = 0.354) (all other variables ρ <
0.2).
β diversity (table 7) was well correlated with the pattern of site differences
calculated using all environmental variables (β = 0.384; P = 0.014), and
with that based on data describing silt, rubble and coralline algal cover (β =
0.354; P = 0.011). However representing differences between sites in terms
of coralline algae alone did not produce significant correlation with β
diversity patterns β = -0.042; P = 0.614). Nor was β diversity correlated
with the simple geographical separation of the sites β = 0.152; P = 0.373).
The test for that β diversity should be related to the geographical distance
between sites was not significant.
Finally, the test for concordance between rover and transect data sets
indicated weak significant correlations between the two distance matrices
using abundance weighted (= 0.297; P = 0.042) and presence/absence (=
0.333; P = 0.044) approaches.
Discussion
The abundance and diversity of reef associated fish species observed in the
absence of hermatypic coral at Los Cobanos seems comparable to that
found on some hermatypic reefs (Bell & Galzin 1984, Friedlander & Parrish
1998). If we consider the widely used expression in ecology of the more we
look the more we find and consider the level of effort employed in the
survey this notion is highlighted further. The Los Cobanos area is suffering
from overfishing from artisan fishers and from spear fisherman, the first
have significantly reduced the catch rates, from 1974-1991 approximately;
average day time catches were 200lbs whereas now they are on average
30lbs (M. Campos pers. Comm.).
Sharks were also caught in large
numbers in the past but none have been caught or seen in the area for 10
years (M. Campos pers. Comm.). Spear fisherman could also be having an
impact on the reef, no large grouper were recorded during the survey and
the only clue to their presence came from a meeting with a spear fisherman
who had taken one from the reef.
The reef associated fish in this study seem to form discrete assemblage
structures at the twelve study sites, with consistency existing between the
patterns of species richness and abundance and the benthic predictors.
Multivariate statistical analysis demonstrated some concordance in the
relationship between the benthic environment and the fish assemblages
when using the benthic variables as predictors.
Soft coral cover is the
number one predictor, at 53% when trying to predict the number of species
using the rover data, if used in conjunction with silt this increases to 67%
and increases further to 81% when sponges are added. Soft coral cover
was the only significant predictor at 39% for the number of individuals.
Soft coral cover was again the number one predictor at 33% when using
the transect data to predict the number of individuals, if using soft coral
cover and silt together as predictors this increases to 59%. When looking
at the number of individuals using the transect data only one predictor
was significant, again this was soft coral cover at 28%. In most cases the
predictive
benthic
variables
are
positively
characteristics of the habitat, ie vertical relief.
associated
with
other
The general results and
observations seem to imply the importance of the biological element
provided by the soft coral, and a three dimensional characteristic provided
by the vertical relief being important to the local fish assemblages. While
the three dimensional structural complexity of hermatypic coral is
significant (Friedlander & Parrish 1998), here any structural complexity
provided by the soft coral is arguably minimal. The structure and area of
the larger rock surfaces do provide more available space and a source of
attachment for the soft coral (Gratwicke & Speight 2005). Simply by their
size the larger rock surfaces create a more heterogeneous habitat and with
wider niche availability and in keeping with the Hutchinsonian concept of
the niche allow more species to co-exist (Hutchinson 1957).
With the
addition of a biological element such as soft coral cover the habitat is
further improved and can sustain more diversity and abundance of species
(Bellwood et al 2004).
Many other studies are more specific when
considering the niche concept and have surveyed the habitat at a different
spatial scale to that adopted here and used hole size as a measure of
heterogeneity (Shulman 1984, Hixon & Beets 1989, Lingo & Szedlmayer
2006). Studies on artificial reefs have been able to show holes and hole
size to be important in the structuring of reef fish assemblages and are
used by fish as shelter and refuge sites from predators (Shulman 1984,
Roberts & Ormond 1987 Hixon & Beets 1989, Lingo & Szedlmayer 2006).
In natural systems number of holes only was found to be significant
(Roberts & Ormond 1987) as apposed to number and size on artificial
reefs.
The use of hole size may have been prudent at Los Cobanos,
unfortunately due to time constraints this variable was not recorded.
Despite this, it is clear from the results that soft coral cover is by far the
strongest predictor of the fish assemblages on the rocky reef habitat at Los
Cobanos across sites and across the two study methods, rover
transects.
and
From their study on Red Sea coral reefs Roberts & Ormond (1987) found
soft coral to be significantly positively correlated with overall species
richness, however this was confounded with depth. These findings are the
opposite to those of Risk (1972) who found no correlation between fish
diversity and biological diversity. The correlations between fish diversity
and characteristics of the benthos may vary between species and between
families dependant on their lifestyle (Roberts & Ormond 1987). Territorial
species or those with smaller home ranges may be expected to be more
influenced by local characteristics of the benthic habitat (Roberts &
Ormond 1987), while those with a larger territory may be expected to be
more influenced by the habitat at a larger spatial scale in conjunction with
the keystone structure concept of Tews et al (2004).
Past studies conducted on hermatypic coral reefs have shown live coral
cover to be a factor in fish assemblages and some suggest that this could
in fact be due to the complexity of the structure provided by some coral
species allowing sites of refuge and shelter (Risk 1972, Luckhurst &
Luckhurst 1978, Bellwood et al 2004). Perhaps the correlation seen here
between live soft coral and fish diversity is not due to the structural
component of the coral as clearly the soft coral observed at Los Cobanos
bears little comparison in complexity with the likes of that seen on
hermatypic reefs. In his study on coral reef fish diversity, Risk (1972)
found what he described as a striking correlation between fish species
diversity and substrate topographic complexity; he found no correlation
between fish numbers and either complexity or biological diversity.
Luckhurst & Luckhurst (1978) attempted to investigate the affect of live
coral in isolation from rugosity and vertical relief; while they found positive
correlations between surface rugosity and fish assemblage they found no
relationship between the assemblage and coral species richness.
In
1984 Bell & Galzin noted that there were no studies which examined effect
of live coral cover in isolation from the significant effect of changes in
habitat complexity on the structure of fish assemblages. By choosing
study sites that showed comparable complexity but had differing
percentages of live coral cover Bell & Galzin (1984) concluded that live
coral cover may have more importance in structuring reef fish assemblages
than previously thought, they went on to suggest that structural
complexity on reefs and live coral cover should be considered separately. It
could be that the suggestion made by Bell & Galzin (1984) of considering
the effect of live coral cover in isolation from habitat complexity has been
achieved in the present study at Los Cobanos, albeit with soft coral. The
present study shows a clear relationship does exist between the soft coral
cover and the fish assemblages at the rocky reef patches of Los Cobanos.
Again considering the minimal complexity of the soft coral at Los Cobanos
perhaps a biological relationship is the over arching factor responsible for
the structuring of the fish assemblages on tropical rocky reefs. Or perhaps
the keystone structure concept proposed by Tews et al (2004) is more
important to some species and fish assemblage structure should consider
the lifestyle characteristics of the fish species in relation to range size and
territoriality before inferring which variables of the habitat are important.
By viewing the assemblage in this way the problems of confounding
variables highlighted by Roberts & Ormond (2004) could be eliminated. It
seems that when investigating fish assemblages and looking for causal
factors between diversity and the habitat, different methods and criteria
need to be adopted according to the species and the habitat in question.
As Gratwicke & Speight (2005) point out if looking at percentage live cover
across a range of habitats it is not significant, probably because habitats
such as sea grass beds with low fish diversity have a very high proportion
of live cover.
Within the literature, much research has been conducted on hermatypic
reefs with regard to habitat structure and fish communities; however very
little exists on rocky reefs. When conducting their study in 2000 Ferreira
et al noted that few studies on habitat and community structure had been
conducted away from coral reefs. This was echoed in 2004 by Gratwicke &
Speight who noted that studies interested in the relationship between fish
assemblages and habitat complexity/heterogeneity conducted
on
hermatypic coral reefs were controversial. They suggest this is due to there
being problems with separating the biological factors associated with live
coral from the physical factors of structure alone. They go on to say that
other factors such as diversity of coral species could be more strongly
correlated to fish species diversity, and any findings may not be easily
applied to fish assemblages in other habitats (Gratwicke & Speight 2004).
Detailed information on the feeding guilds of the fish at Los Cobanos may
provide further insight into habitat preference if a relationship existed
between soft coral abundance and obligate corallivores and grazers at sites
with higher algal cover.
While it is counter-intuitive, silt was the second most significant predictor
when considering species diversity, one would expect heavily silted sites to
not show high coral abundance as silting would be expected to inhibit coral
growth but some sites with a high silt percentage also show a high coral
percentage. Time lags could explain this in part if there has been a recent
increase in silting, environmental changes that can effect population
dynamics can be subject to time lags depending on the particular life
histories of the species (Bull & Bonsall 2008). The observed silting could
be input from land from deforestation or the presence of a shrimp farm in
the area and the in situ observation of a possible convergence of local
currents causing the concentration of silt particles.
There is no correlation between beta diversity and the geographical
distance between sites, there is however a significant relationship between
beta diversity, coral cover, silt and sponges, but not with coral cover alone.
This is in direct opposition to the single variable of soft coral cover shown
to be so significant in predicting diversity and fish abundance at individual
sites, highlighting the previous counter intuitive thoughts on the
relationship between coral and silt. The patchiness of sites at Los Cobanos
could be subdividing the populations (Sale 2004), perhaps supported by
the statistic that no significance was found between geographical distance
between sites and beta diversity.
One could hypothesise that fish are
having minimal movement between sites and recruitment into a new site
would be subject to larval recruitment and being carried on the currents as
opposed to migration.
Most fish seldom move between patches of a
suitable habitat once the larval stage is complete (Sale 2004). Any recruits
then reaching maturity and remaining at a less than ideal site (ie one with
minimal soft coral and/or heavily silted) may be more likely
to be a
generalist as habitat specialists are more likely to be governed by habitat
availability than generalists that are able to utilize a range of habitat types
(Brown 1984). Further demonstrating how fish lifestyle characteristics and
feeding guilds could provide further insight into the causal factors of the
habitat responsible for the observed fish assemblage structure on the rocky
reefs of Los Cobanos.
It is perhaps not unexpected to find more diversity and more individuals in
areas with significant coral cover, it may be unexpected that this is also
linked in some cases to high silt percentage cover. In the endeavour to
investigate tropical fish assemblage structure and habitat complexity away
from a hermatypic coral reef, the results here seem to suggest a biological
relationship exists between the fish assemblage and soft coral at Los
Cobanos.
Unlike where on hermatypic coral reefs the complex physical
structure can provide shelter and refuge for fish (Risk 1972, Luckhurst &
Luckhurst 1978, Bellwood et al 2004) and could be the causal factor
between the habitat and fish diversity/abundance this clearly is not the
case with the soft coral at Los Cobanos.
Figure 1 Results of ordination plot (MDS) based on Bray Curtis similarity matrix
Tib Pic
Rover:
Species 26 36
Indiv’s 114 426
Ja
Raj
Lor Zav Qui Zun Alb La
R
36 27 29 32
333 285 109 480
Transect:
Species 18 19
17 15 18 12
Indiv’s 149 1048 261 417 175 55
Pan T
Cr
28
107
33
269
38
526
18 32
267 330
39
424
10
54
10
83
14
132
7
27
17
406
11
72
Table 1 Summary of species and individuals at each site (rover individual values derived from
middle value of each rank as used throughout)
Analysis using rover data
Fish species
Predictors
Constant
%Coral
Cover:
Regression
Residual
Mean²
F
P
R
Adjusted
R²
9.616
0.757
97.301
7.20
Constant
%Coral
Cover,
Silt:
62.552
Regression
4.989
Residual
Constant
%Coral
Cover,
Silt,
Sponges:
49.105
Regression
2.836
Residual
13.384
0.530
11.594
0.858
12.539
0.677
0.003
Constant
%Coral
Cover
Regression
Residual
403672.0
27.877
-11.270
15.655
0.931
17.316
0.817
0.001
Fish Individuals
Mean²
30.624
0.004
Table 2. Model summary of multiple regression of site data and ANOVA results, with
coefficients using the benthic data to predict the number of observed fish species from the
rover data
Predictors
Coefficients
F
P
R
Adjusted
R²
0.668
0.392
Coefficients
-42.483
1972.521
8.077 0.017
49975.092
Table 3 Model summary of multiple regression of site data and ANOVA results, with
coefficients using the benthic data to predict the number of fish individuals from the rover
data
26.909
-16.726
-26.729
Analysis using transect totals data
Fish species
Predictors
Constant
%Coral Cover:
Regression
Residual
% Coral Cover, Silt
Regression
Residual
Mean² F
P
R
Adjusted R² Coefficients
9.915
0.0632 0.339
26.263
67.854 6.643 0.28
10.215
0.820
57.090 9.205 0.007
6.202
0.599
11.944
26.194
-14.384
Table 4 Model summary of multiple regression of site data and ANOVA results, with
coefficients using the benthic data to predict the number of observed fish species from the
transect data
Fish Individuals
Predictors
Mean²
F
P
R
Adjusted R² Coefficients
Constant
-49.936
%Coral Cover:
0.590 0.283
1773.582
Regression
309440.374 5.350 0.043
Residual
57837.054
Table 5 Model summary of multiple regression of site data and ANOVA results, with
coefficients using the benthic data to predict the number of observed fish individuals from
the transect data
Diversity indices
Sites
H Value
Tiburon
8.11398
La Pichelera
7.77921
JaJaJa
7.81136
Rajadura
5.42852
Lorenita
10.7353
Zavaneta
5.73335
Quinoguerita 4.7478
Zuniga
5.62029
Albanico
7.24102
La Roca
4.88486
Panpanera
5.58354
Tres Cruces
5.85473
Table 6 Shannon Weiner values of sites using the transect data
Tiburon
Tiburon
La Pichelara
JaJaJa
Rajadura
Lorenita
Zavaneta
Quinoguerita
Zuniga
Albanico
La Roca
Panpanera
Tres Cruces
La Pichelara
JaJaJa
Rajadura
0.528
0.75
0.634
0.603
0.473
0.461
0.554
0.536
0.586
0.559
0.5
0.610
Lorenita
Zavaneta
Quinoguerita
Zuniga
Albanico
La Roca
Panpanera
0.484
0.484
0.524
0.555
0.625
0.625
0.654
0.456
0.633
0.542
0.609
0.667
0.667
0.710
0.554
0.524
0.531
0.594
0.676
0.646
0.746
0.571
0.576
0.845
0.5
0.370
0.333
0.444
0.255
0.44
0.565
0.274
0.321
0.586
0.676
0.676
0.644
0.393
0.625
0.567
0.646
0.628
0.4
0.554
0.587
0.533
0.697
0.529
0.591
0.597
0.611
0.623
0.526
Table 7 Beta diversity values
0.676
Acknowledgements
Thanks to J. Ready, S. Kullander, all at FUNZEl, all at El Salvador
divers, for funding and field organisation. Thanks to M. Campos for
his boat and his captaincy and his invaluable experience of the Los
Cobanos region. Thanks to L. Munson for his competence and skill in
the field and all data collection, and A. Foggo for comments and
support.
References
Almada-Villela PC Sale P.F., Gold-Bouchot G. and Kjerfve B. (2003) Manual
of methods for the MBRS synoptic monitoring program. MBRS Technical
Document No. 4, MBRS, Belize City
Bell JD, Galzin (1984) Influence of live coral cover on coral reef fish
communities. Mar Ecol Prog Ser 15: 265-274
Bellwood DR, Hughes TP, Folke C, Nystrom M. (2004) Confronting the coral
reef crisis. Nature 429
Brown JH (1984) On the relationship between the abundance and
distribution of species. Am Nat 124: 255-279
Bull JC, Bonsall MB. (2008) Overcompensatory population dynamic
responses to environmental stochasticity. J Anim Ecol 77: 1296-1305
Burnaford JL (2004) Habitat modification and refuge from sublethal stress
drive a marine plant-herbivore association. Ecology 85: 2837-2849
Carpenter RC (1986) Partitioning herbivory and its effects on coral-reef algal
communities. Ecol Monogr 56: 345-363
Clarke KR (1988) Detecting change in benthic community structure.
Proceedings X1V International biometric conference, Namur: Invited papers.
Societe Adolphe Quetelet, Gembloux, Belgium
Clarke KR, Ainsworth, M. (1993) A method of linking multivariate
community structure to environmental variables. Mar. Ecol. Prog. Ser. 92:
205-219
Clarke KR & Warwick RM (2001) Change in marine communities: An
approach to statistical analysis and interpretation, 2nd edition.
Ferreira CEL, Goncalves JEA, Coutinho R (2001) Community structure of
fishes and habitat complexity on a tropical rocky shore Environ Biol Fish 61:
353-369
Friedlander AM, Parrish JD (1998) Habitat characteristics affecting fish
assemblages on a Hawaiian coral reef. J Exp Mar Biol Ecol 224: 1-30
Gratwicke B, Speight MR (2004) The relationship between fish species
richness, abundance and habitat complexity in a range of shallow tropical
marine habitats. J Fish Biol 66: 650-667
Hixon MA, Beets JP (1989) Shelter characteristics and Caribbean fish
assemblages – experiments with artificial reefs. Bull Mar Sci 44: 666-680
Hutchinson GE (1957) Concluding remarks, Cold Spring Harbor
Symposium. Quantitative Biology 22: 415–427.
Klumpp DW, McKinnon AD (1989) Temporal and spatial patterns in primary
production of a coral-reef epilithic algal community. J Exp Mar Biol Ecol
131: 1-22
Lawson GL, Kramer DL, Hunte W (1999) Size related habitat use and
schooling behaviour in two species of surgeon fish (Acanthurus bahianus and
A-coeruleus) on a fringing reef in Barbados, West Indies. Environ Biol Fish
54: 19-33
Levin PS, Tolimieri N, Nicklin M, Sale PF (2000) Integrating individual
behaviour and population ecology: the potential for habitat-dependant
population regulation in a reef fish. Behavioural ecology 11: 565-571
Lingo ME, Szedlmayer ST (2006) The influence of habitat complexity on reef
fish communities in the north-eastern Gulf of Mexico. Environ Biol Fish 76:
71-80
Luckhurst BE, Luckhurst K (1978) Analysis of the influence of substrate
variables on coral reef fish communities. Mar Biol 49: 317-323
MacArthur RH, MacArthur JW (1961) On bird species diversity. Ecology 42:
594-598
McClain CR (2007) Seamounts: identity crisis or split personality? J biogeogr
34: 2001-2008
Moreno I (2002) Effects of substrate on the artificial reef fish assemblage in
Santa Eulalia Bay (Ibiza, western Mediterranean) Journal of marine science
59: 144-149
Nanami A, Nishihira M (2003) Effects of habitat connectivity on the
abundance and species richness of coral reef fishes: comparison of an
experimental habitat established at a rocky reef flat and a sandy sea bottom.
Environ Biol Fish 68: 183-196
Ohman MC. & Rajasuriya A (1998) Relationships between habitat structure
and fish communities on coral and sandstone reefs. Environ Biol Fish 53:
19–31.
Risk MJ (1972) Fish diversity on a coral reef in the Virgin Islands. Bull 193:
1-6
Roberts CM, Ormond RFG (1987) Habitat complexity and coral reef fish
diversity and abundance on red sea fringing reefs. Mar Ecol Prog Ser 41: 1-8
Sale PF (2004) Connectivity, recruitment variation and the structure of reef
fish communities. Integr. Comp. Biol. 44: 390-399
Shulman MJ, (1984) Resource limitation and recruitment patterns in a coral
reef fish assemblage. J. Exp. Mar. Biol. Ecol. 74: 85-109
Sørensen, T.A. (1948) A method of establishing groups of equal amplitude in
plant sociology based on similarity of species content, and its application to
analyses of the vegetation on Danish commons. Kongelige Danske
Videnskabernes Selskabs Biologiske Skrifter, 5: 1–34
Tews J, Brose U, Grimm V, Tielborger K, Wichmann MC, Schwager M,
Jeltsch F (2004)
Animal species diversity driven by habitat
heterogeneity/diversity: the importance of keystone structures. J. Biogeogr
31: 79-92