- Email: [email protected]
Reef fish diversity components as indicators of cumulative effects in a highly impacted fringe reef
Ecological Indicators 10 (2010) 766–772
Contents lists available at ScienceDirect
Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind
Case study
Reef fish diversity components as indicators of cumulative effects in a highly impacted fringe reef Gaspar Gonza´lez-Sanso´n *, Consuelo Aguilar Center of Marine Research, 16th Street No. 114, Playa, Ciudad de La Habana, Cuba
A R T I C L E I N F O
A B S T R A C T
Article history: Received 18 April 2009 Received in revised form 19 November 2009 Accepted 23 November 2009
The main goal of our research was to determine which indicators describing cumulative stress might better explain the differences observed in diversity components of reef fish assemblages off Havana City, Cuba. A total of 35,078 individuals of 119 species were counted in 480 stationary point censuses. Counts were distributed among three zones with different levels of pollution and four habitats with different wave stress. Four indexes of diversity components (S, H0 , J0 and PIE) were calculated and correlative analyses performed to explore the best indicators of cumulative effects explaining observed variation. High correlation was found between all diversity components and two indexes of cumulative effects (ICE) built after distinct criteria. In the first case, pollution and wave action were combined following an interactive model. In the second case, an empirical ICE was obtained by totaling the abundance indicators of three groups of organisms, namely sponges, sabellid polychaetes and filamentous algae. ß 2009 Elsevier Ltd. All rights reserved.
Keywords: Reef fish assemblages Diversity Cumulative effects
1. Introduction There is an increasing worldwide concern about the degradation of coral reef communities. However, our knowledge about the susceptibility to disturbance of most common reef fish species and the diverse communities they form is far from complete (Feary et al., 2007). Several natural and anthropogenic factors acting simultaneously produce cumulative effects on fish assemblages. One way of measuring these effects is analyzing changes in diversity components (Aguilar et al., 2004). The selection of appropriated measures of diversity continues to be controversial in spite of exhaustive periodical reviews (Hill, 1973; Peet, 1975; Washington, 1984; Ghent, 1991; Magurran, 2004; Lamb et al., 2009). Regardless of strong criticism, Shannon index of total diversity and Pielou’s evenness index J0 (=H0 /H0 max) continue to be two of the most popular indexes (Gotelli and Graves, 1996), and have been repeatedly used in reef fish assemblage studies (Chabanet et al., 1997; Rooker et al., 1997; Friedlander et al., 2003; Aguilar et al., 2004; Brokovich et al., 2006; Harborne et al., 2006; Me´ndez et al., 2006; Walter and Haynes, 2006; Mallela et al., 2007). Based on an exhaustive review of the topic, Gotelli and Graves (1996) suggest abandoning the idea of incorporating both evenness and species richness into a single index (e.g. Shannon index), and instead recommend the use of rarefaction for
* Corresponding author. E-mail address: [email protected] (G. Gonza´lez-Sanso´n). 1470-160X/$ – see front matter ß 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.ecolind.2009.11.009
the estimation of species richness (S), and Monte Carlo simulation procedures for Hurlbert’s (1971) probability of interspecific encounter (PIE) estimation as an evenness measure. This approach has been used recently for marine assemblages by Feary et al. (2007) and Godı´nez-Domı´nguez et al. (2009). Marine fish assemblages and habitats off Havana City have been investigated in some detail (Gonza´lez-Dı´az et al., 2003; Aguilar et al., 2004, 2007, 2008). No attempt has been made, however, to investigate the correlation of diversity components with benthic communities’ indicators and/or human impact indicators. Using the same data gathered in 2000 by Aguilar et al. (2004) in the subtidal zone off Havana City, a new analysis was made with three basic objectives: (1) to calculate several indexes of diversity components of fish assemblages (namely H0 , J0 , S and PIE) across a range of disturbance regimes in a highly impacted reef region; (2) to perform correlative analyses of index values with variables describing benthic communities; (3) to determine which indicator describing cumulative stress may better explain the differences observed in diversity components. 2. Materials and methods The study area is located in the subtidal zone off Havana City (Fig. 1), where a fringing reef develops mainly in the 12–15 m deep terrace, located 200–300 m offshore. The bottom between the shore and the reef front is an almost bare rocky plain, which near the coast presents a fringe containing large quantities of the sea urchin Echinometra lucunter (Linnaeus, 1758). Since the impact of
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
767
Fig. 1. Study area with sampling zones. Bar graphs show density of sponges (black), gorgonians (dark gray) and corals (light gray) in each bottom type (e: Echinometra; p: rocky plain; t: terrace).
pollution coming from the city varies notably along the coast from the Havana harbor entrance (most polluted area) towards the southwest, the reef was divided into three different zones according to assumed levels of land-based pollution (Fig. 1). Zone 1 is strongly impacted by the heavily polluted waters coming from Havana harbor; zone 2 has an intermediate level of pollution coming from non-point, small sources along the coast and the discharge of the polluted Almendares river; zone 3 can be considered almost free of significant pollution impacts from land. More details and the rationale for this division can be found in
Aguilar et al. (2004, 2007). Detailed quantitative information on several benthic assemblages of algae and invertebrates for each zone has been published by Gonza´lez-Dı´az et al. (2003). Stationary visual censuses (Bohnsack and Bannerot, 1986) were conducted in 15 sites along the coast (six sites in zone 1, four sites in zone 2 and five sites in zone 3). We used a radius of 5 m due to lower visibility in some sites. Four censuses were realized in each of four habitat types (Echinometra fringe, rocky plain, terrace edge and terrace base) at each site. This sampling schedule was repeated twice (February and June 2000). February data can be considered
Fig. 2. Diagram of a typical bottom profile in the study area showing sampling zones and habitat types: Echinometra (Ec), Rocky plain (Pl), Terrace edge (Te) and Terrace base (Tb). Gradients of main stress sources are shown.
768
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
representative of dry season conditions, and June data of rainy season conditions. We considered each combination of zone, habitat and date a sample. Site data inside each zone were pooled, with stationary counts the sampling units. Sample sizes were therefore 24 for zone 1, 16 for zone 2 and 20 for zone 3. Three main factors influence fish assemblages in the study area (Fig. 2). Overfishing is an important human impact affecting all zones and habitats to the same degree. Wave action is a natural source of habitat heterogeneity, which decreases with depth. Pollution is very high near Havana harbor, decreasing towards the southwest. Wave action and pollution can be combined in two ways to produce two different indicators of cumulative effect (Fig. 3). In both cases we define a rank-based index of cumulative effect (ICE). In the first case, ICE values (ranks) result from simply adding the levels of both sources. We call this approach additive. In the second case, we consider an interaction between wave effect and pollution, the first ‘‘washing’’ shallower sites and decreasing pollution effects. We call this approach interactive. A third approach for ICE was obtained using data on benthic assemblages, which can be considered good indicators of organic pollution, the main type of pollution in the study area. We used published quantitative data (Gonza´lez-Dı´az et al., 2003) on sponge colonies density, percent of sabellid polychaetes coverage and percentage of filamentous algae (Cladophora and Herposiphonia) to build an index by simply adding the values of the three variables. We transformed the values obtained into ranks to make a fear comparison with the two models described earlier. We call this third approach empirical (Fig. 3). Four different indexes were used to measure diversity components. The total number of species (S) and probability of interspecific encounter (PIE; Hurlbert, 1971) with their empirical 95% confidence intervals were calculated in rarified samples standardized to 280 individuals using the EcoSim software (Gotelli and Entsminger, 2001). Shannon index of diversity P (H0 = pi ln pi) and Pielou’s eveness index (J0 = H0 /ln S) were calculated for total samples (zone habitat season) using Excel
2003. Association between diversity indexes, benthic variables and cumulative effect values (ICE) was assessed using Spearman’s rank correlation coefficient (rs). Analyses were made using STATISTICA 6.0. 3. Results A total of 35,078 individuals of 119 species were counted in 480 stationary point censuses (Table 1). Species abundances were strongly uneven, with only 30 species forming more than 90% of total individuals counted. The most abundant species were: the bluehead Thalassoma bifasciatum, a small-sized and territorial species feeding on small invertebrates; the bicolor damselfish Stegastes partitus, a small-sized highly territorial omnivore; the ocean surgeonfish Acanthurus bahianus, a medium-sized wandering herbivore and the slippery dick Halichoeres bivittatus, a smallsized and territorial species feeding on small gastropods. These species can be considered dominant in the studied assemblage and they accounted for more than 55% of all individuals censused. In general terms, the fish assemblage was strongly dominated by small- or medium-sized species of low trophic level (mostly herbivores, omnivores and small invertebrate feeders). Larger species were notoriously absent and no individuals of commercial Table 1 Total number (N) and percentage representation of species totaling 90 percent of all individual counted. Maximum total length (Lmax) observed is also given for each species. Family ordering follows Nelson (2006). Family
Species
Lmax (cm)
Main food
Holocentridae
Holocentrus adscencionis Myripristis jacobus
357 179
1.0 0.5
28 17
SC SF&C
Serranidae Malacanthidae Carangidae
Cephalophoplis fulva Malacanthus plumieri Caranx ruber
826 318 543
2.4 0.9 1.5
25 40 20
SF&C SF&I SF&C
Lutjanidae
Lutjanus synagris Ocyurus chrysurus
315 246
0.9 0.7
26 30
SF&C SI
Haemulidae
Haemulon flavolineatum Haemulon plumieri
498 625
1.4 1.8
20 25
M&D M&D
Mullidae
Mulloidichthys martinicus
271
0.8
30
SI
Chaetodontidae
Chaetodon capistratus Chaetodon striatus
576 132
1.6 0.4
17 15
SI SI
Pomacentridae
Abudefduf saxatilis Chromis cyanea Chromis multilineata Stegastes leucostictus Stegastes partitus
581 943 942 249 5274
1.7 2.7 2.7 0.7 15.0
15 10 14 10 9
O P P O O
Labridae
Bodianus rufus Clepticus parrae Halichoeres bivittatus Halichoeres garnoti Thalassoma bifasciatum
261 469 2167 485 8768
0.7 1.3 6.2 1.4 25.0
14 26 15 18 12
SI P SG SG SI
Scaridae
Sparisoma aurofrenatum Sparisoma chrysopterum
616 110
1.8 0.3
31 29
H H
Labrisomidae Chaenopsidae
Malacoctenus triangulatus Emblemaria pandionis
122 317
0.3 0.9
7 5
SI P
Acanthuridae
Acanthurus bahianus Acanthurus chirurgus Acanthurus coeruleus
3738 527 1020
10.7 1.5 2.9
19 21 25
H H H
Tetraodontidae
Canthigaster rostrata
139
0.4
11
O
31614 3464 35078
90.1 9.9 100.0
Sub total Rest (89 spp.) Total
Fig. 3. Graphical representation of three approaches for ranking cumulative effects.
N
%
C = crustaceans; D = decapods; H = plants (herbivores); I = invertebrates; SC = small crustaceans; SF = small fish; SG = small gastropods; SI = small invertebrates; M = mollusks; O = plants and animals (omnivores); P = plankton.
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
769
Fig. 4. Mean abundance (standard error) of four most abundant species. Labels formed by sampling zone number and season (R = rainy; D = dry).
species of groupers, snappers, grunts and jacks were observed along the study. Barracuda, big rays and sharks were also absent in our censuses. Habitat preferences were evident in the two most abundant species (Fig. 4). Bluehead was by far most abundant on the terrace edge, with the subsequent preferred habitat the terrace base. In both cases, abundance of this species was much lower at the highly impacted zone 1. In the terrace base abundance was also low at the medium impacted zone 2. No differences are apparent between sampling dates. Bicolor damselfish was even more segregated among habitats, and was very abundant at both terrace locations. Strong fluctuations in abundance are apparent between sampling dates for this species, but this does not mask the much lower abundance at zone 1 in both habitats. The third species by its total abundance, ocean surgeonfish, did not show any clear trend by habitat, zone or date of sampling. Finally, slippery dick was more abundant in zone 1 for all habitats. This species showed an abundance pattern that can be considered almost contrary to those of bluehead and bicolor damselfish. Values of S and PIE varied among areas inside each habitat in a similar but complex fashion (Fig. 5). In Echinometra fringe and rocky plain habitats, lowest values were found in area 2, while values in areas 1 and 3 were very similar. In both terrace habitats, however, a clear trend was evident in which values decreased from most impacted zone 1 to least impacted zone 3. PIE values showed a very high correlation with H0 (rs = 0.949, p < 0.001, n = 24) and with J0 (rs = 0.928, p < 0.001, n = 24). S values were also highly correlated with H0 (rs = 0.909, p < 0.001, n = 24) and in less degree with J0 (rs = 0.730, p < 0.001, n = 24). In most cases, diversity measures showed significant correlations with sponge density, polychaete coverage and proportion of filamentous algae (Table 2). Only J0 was not correlated with sponge density. All diversity indexes were also correlated with rank values predicted by interactive and empirical indicators of cumulative
effect (ICE). No correlation was found in any case with the additive approach predicted values. The contribution of the four most abundant species to diversity indexes was assessed using rank correlation between the proportion of each species and each diversity index (Table 3). All diversity indexes showed a very high negative rank correlation with the proportion of bluehead (the most abundant species) in samples (Fig. 6). This was not the case for the second most abundant species, bicolor damselfish, for which no correlation was found. Ocean surgeonfish proportion was weakly and negatively correlated with S and H0 but not with PIE and J0 . Finally, slippery dick proportion in samples was weakly correlated with all indexes. 4. Discussion Other authors have also used an index-based approach to quantify cumulative effects. Ugland et al. (2008) used a simple indicator of pollution effect by averaging the relative abundance of five polychaete species. Hale and Heltsche (2008) showed that an index based in several benthic indicators strongly discriminated stations in their study. A critical question about our results, however, is related to the reliability of the variables we used to build our indicator of cumulative effect. We summarize below evidence in scientific literature supporting our selection. An increase of sponge biomass with organic pollution and high sediment load is well documented (Chalker et al., 1985; Rogers, 1990; Wilkinson and Cheshire, 1990; Aerst and van Soest, 1997; Ward-Paige et al., 2005; Costa et al., 2008). Sponges are filter feeders that primarily consume ultraplankton. As Ru¨tzler (2004) asserts, land runoff and organic pollution in moderate concentration may benefit sponges by providing nutrients for bacteria. Sponges and corals respond to nutrient and sediment increase in very different ways, with coral biomass decreasing in reefs stressed by pollution and siltation (Aerst and van Soest, 1997; Nughes and
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
770
Fig. 5. Estimated values of the probability of interspecific encounter (PIE) and species number (S) in samples rarefied to 280 individuals (95% confidence intervals). Labels formed by sampling zone number and season (R = rainy; D = dry).
Table 2 Spearman’s rank correlation coefficients (rs) and associated probabilities (p) for combinations of diversity components and environmental or stress indicator variables: S = number of species; PIE = probability of interspecific encounter; J0 = Pielou’s evenness index; H0 = Shannon’s diversity index; ICE = index of cumulative effect. Variables
Sponges Polychaetes Filamentous algae ICE additive ICE Interactive ICE empirical
S
J0
PIE
H0
rs
p
rs
p
rs
p
rs
p
0.68 0.59 0.40 0.02 0.44 0.63
<0.001 0.002 0.049 0.935 0.030 0.001
0.45 0.56 0.48 0.32 0.48 0.71
0.026 0.004 0.016 0.130 0.018 <0.001
0.31 0.53 0.42 0.13 0.44 0.51
0.142 0.008 0.043 0.554 0.033 0.010
0.62 0.60 0.46 0.21 0.48 0.68
0.001 0.002 0.024 0.318 0.018 <0.001
Table 3 Spearman’s rank correlation coefficients (rs) and associated probabilities (p) for combinations of diversity components and most abundant species: S = number of species; PIE = probability of interspecific encounter; J0 = Pielou’s evenness index; H0 = Shannon’s diversity index. Species
Thalassoma bifasciatum Stegastes partitus Acanthurus bahianus Halichoeres bivittatus
S
J0
PIE
H0
rs
p
rs
p
rs
p
rs
p
0.73 0.26 0.52 0.51
<0.001 0.225 0.009 0.010
0.88 0.08 0.28 0.58
<0.001 0.713 0.175 0.002
0.81 0.20 0.14 0.58
<0.001 0.348 0.522 0.003
0.87 0.11 0.44 0.52
<0.001 0.622 0.029 0.008
Roberts, 2003). Sponge cover was negatively correlated with hard coral cover in the Florida Keys (Maliao et al., 2008). Polychaetes have been considered good indicators of eutrophication by several authors (Crema et al., 1991; Mayer-Pinto and Junqueira, 2003; Ugland et al., 2008). Filtering abilities of sabellid polychaetes are very high (Licciano et al., 2005, 2007), giving this group a competitive advantage in environments impacted by sewage-
polluted and eutrophicated waters (Licciano et al., 2002). Increasing availability of inorganic nutrients is known to stimulate the abundance of ephemeral macroalgae, including those of genus Cladophora (Gordon and McComb, 1989; Lapointe et al., 2004; Kraufvelin et al., 2007; McClanahan et al., 2007; Mutchler et al., 2007; Karez et al., 2008). During a study carried out in the Swedish Skagerrak archipelago, Pihl et al. (1999) concluded that the
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
771
the manuscript. We also thank divers Luis Sanchez and Armando Perez for their assistance in the field. Partial funding for this research was provided by a Canadian International Development Agency Tier 2 Grant to the Centro de Investigaciones Marinas, Cuba and the University of New Brunswick, Saint John, Canada.
References
Fig. 6. Relationship of probability of interspecific encounter (PIE, black circles in upper panel), species number (S, white circles in upper panel), Shannon’s diversity index (H0 , white circles in bottom panel) and Pielou’s eveness index (J0 , black circles in bottom panel) with numerical proportion of Thalassoma bifasciatium (P) in samples.
development of green algal mats (Cladophora and Enteromorpha) was most probably caused by a general elevation in nutrient levels. Several authors have identified wave action as a factor controlling settlement success and growth rates of some sessile organisms in reefs (Massel and Done, 1993; McClanahan et al., 2002). This supports our assumption of a decreasing wave impact from shallower to deeper habitats. In this case wave action can be considered a habitat heterogeneity-inducing factor. The correlation among diversity indexes and cumulative effects (ICE) can be explained by the response of the two most abundant wrasses (bluehead and slippery dick). The proportional abundance of bluehead decreased consistently at sites of higher stress, while that of slippery dick increased. These responses contribute to increased evenness at more stressed sites, decreasing the high dominance of bluehead and allowing other species to be present. A plausible explanation for this change in relative abundance is that slippery dick has a higher tolerance to stressor effects than bluehead, a hypothesis already advanced by Aguilar et al. (2004). Slippery dick appears to be more tolerant to siltation than other species of wrasses (Aliaume et al., 1990; Baelde, 1990; BouchonNavaro et al., 1992; Thomas and Logan, 1992). After McKenna (1997), small wrasses (especially Halichoeres bivittatus) dominated the assemblages at the impacted site in his study. Acknowledgements We acknowledge the contribution of two anonymous reviewers whose comments contributed significantly to the enhancement of
Aerst, L.A.M., van Soest, R.W.M., 1997. Quantification of sponge/coral interactions in a physically stressed reef community, NE Colombia. Mar. Ecol. Prog. Ser. 148, 125–134. Aguilar, C., Gonza´lez-Sanso´n, G., Faloh, I., Curry, A., 2008. Spatial variation in stable isotopes (d13C and d15N) in marine fishes along the coast of Havana City: evidence of human impacts from harbor and river waters. J. Coast. Res. 24, 1281–1288. Aguilar, C., Gonza´lez-Sanso´n, G., Herna´ndez, I., MacLatchy, D.L., Munkittrick, K.R., 2007. Effects-based assessment in a tropical coastal system: status of bicolor damselfish (Stegastes partitus) on the north shore of Cuba. Ecotoxicol. Environ. Saf. 67, 459–471. Aguilar, C., Gonza´lez-Sanso´n, G., Munkittrick, K.R., MacLatchy, D.L., 2004. Fish assemblages on fringe coral reefs of the northern coast of Cuba near Havana Harbor. Ecotoxicol. Environ. Saf. 58, 126–138. Aliaume, C., Laserre, G., Louis, M., 1990. Organisation spatiale des peuplements ichtyologiques des herbiers a‘Thalassia du Grand Culde Sac marin en Guadeloupe. Rev. Hydrobiol. Trop. 23, 231–250. Baelde, P., 1990. Differences in the structures of fish assemblages in Thalassia testudinum beds in Guadeloupe, FrenchWest Indies, and their ecological significance. Mar. Biol. 105, 163–173. Bohnsack, J.A., Bannerot, S.P., 1986. A stationary visual census technique for quantitatively assessing community structure of coral reef fishes. NOAA Tech Rep NMFS 41, iii+15 p. Bouchon-Navaro, Y., Bouchon, C., Louis, M., 1992. L’ichthyofaune des herbiers de phanerogames marines de la baie de Fort-de-France (Martinique, Antilles Franc¸aises). Cybium 16, 307–330. Brokovich, E., Baranes, A., Goren, M., 2006. Habitat structure determines coral reef fish assemblages at the northern tip of the Red Sea. Ecol. Indicators 6, 494–507. Chabanet, P., Ralambondrainy, H., Amanieu, M., Faure, G., Galzin, R., 1997. Relationships between coral reef substrata and fish. Coral Reefs 16, 93–102. Chalker, B.E., Carr, K., Gill, E., 1985. Measurement of primary production and calcification in situ on coral reefs using electrode techniques. In: Proc Fifth Internat Coral Reefs Cong., Tahiti, vol. 6, pp. 167–172. Costa Jr., O.S., Nimmo, M., Attrill, M.J., 2008. Coastal nitrification in Brazil: a review of the role of nutrient excess on coral reef demise. J. S. Am. Earth Sci. 25, 257– 270. Crema, R., Castelli, A., Prevedelli, D., 1991. Long term eutrophication effects on macrofaunal communities in Northern Adriatic Sea. Mar. Pollut. Bull. 22 (10), 503–508. Feary, D.A., Almany, G.R., Jones, G.P., McCormick, M.I., 2007. Coral degradation and the structure of tropical reef fish communities. Mar. Ecol. Prog. Ser. 333, 243– 248. Friedlander, A.M., Brown, E.K., Jokiel, P.L., Smith, W.R., Rodgers, K.S., 2003. Effects of habitat, wave exposure, and marine protected area status on coral reef fish assemblages in the Hawaiian archipelago. Coral Reefs 22, 291–305. Ghent, A.W., 1991. Insights into diversity and niche breadth analyses from exact small-sample tests of the equal abundance hypothesis. Am. Midl. Nat. 126, 213– 255. Godı´nez-Domı´nguez, E., Freire, J., Franco-Gordo, C., Gonza´lez-Sanso´n, G., 2009. Decomposing diversity patterns of a soft-bottom macroinvertebrate community in the tropical eastern Pacific. J. Mar. Biol. Assoc. U.K. 89 (1), 31–38. Gonza´lez-Dı´az, P., Guardia, E., de la Gonza´lez-Sanso´n, G., 2003. Efecto de efluentes terrestres sobre las comunidades bento´nicas de arrecifes coralinos de Ciudad de la Habana, Cuba. Rev. Invest. Mar. 24, 193–204. Gordon, D.M., McComb, A.J., 1989. Growth and production of the green alga Cladophora montagneana in a eutrophic Australian estuary and its interpretation using a computer program. Water Res. 23, 633–645. Gotelli, N.J., Graves, G.R., 1996. Null Models in Ecology. Smithsonian Institution Press, Washington. Gotelli, N.J., Entsminger, G.L., 2001. EcoSim: Null models software for ecology, Version 7.0. Acquired Intelligence Inc. & Kesey-Bear, http://homepages. together.net/gentsmin/ecosim.htm. Hale, S.S., Heltsche, J.F., 2008. Signals from the benthos: development and evaluation of a benthic index for the nearshore Gulf of Maine. Ecol. Indicators 8, 338– 350. Harborne, A.R., Mumby, P.J., Zychaluk, K., Hedley, J.D., Blackwell, P.G., 2006. Modeling the beta diversity of coral reefs. Ecology 87, 2871–2881. Hill, M.O., 1973. Diversity and evenness: a unifying notation and its consequences. Ecology 54, 427–432. Hurlbert, S.H., 1971. The nonconcept of species diversity: a critique and alternative parameters. Ecology 52, 577–586. Karez, R., Engelbert, S., Kraufvelin, P., Pedersen, M.F., Sommer, U., 2008. Biomass response and changes in composition of ephemeral macroalgal assemblages along an experimental gradient of nutrient enrichment. Aquat. Bot. 78, 103–117.
772
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
Kraufvelin, P., Ruuskanen, A.T., Nappu, N., Kiirikki, M., 2007. Winter colonisation and succession of filamentous macroalgae on artificial substrates and possible relationships to Fucus vesiculosus settlement in early summer. Estuar. Coast. Shelf Sci. 72, 665–674. Lamb, E.G., Bayne, E., Holloway, G., Schieck, J., Boutin, S., Herbers, J., Haughland, D.L., 2009. Indices for monitoring biodiversity change: are some more effective than others? Ecol. Indicators 9, 432–444. Lapointe, B.E., Barile, P.J., Matzie, W.R., 2004. Anthropogenic nutrient enrichment of seagrass and coral reef communities in the Lower Florida Keys: discrimination of local versus regional nitrogen sources. J. Exp. Mar. Biol. Ecol. 308, 23–58. Licciano, M., Giangrande, A., Gambi, M.C., 2002. Reproduction and simultaneous hermaphroditism in Branchiomma luctuosum (Polychaeta, Sabellidae) from the Mediterranean Sea. Invert. Biol. 121, v55–v65. Licciano, M., Stabili, L., Giangrande, A., 2005. Clearance rates of Sabella spallanzanii and Branchiomma luctuosum (Annelida: Polychaeta) on a pure culture of Vibrio alginolyticus. Water Res. 39, 4375–4384. Licciano, M., Stabili, L., Giangrande, A., Cavallo, R.A., 2007. Bacterial accumulation by Branchiomma luctuosum (Annelida: Polychaeta): a tool for biomonitoring marine systems and restoring polluted waters. Mar. Environ. Res. 63, 291–302. McClanahan, T.R., Carreiro-Silva, M., DiLorenzo, M., 2007. Effect of nitrogen, phosphorous, and their interaction on coral reef algal succession in Glover’s Reef, Belize. Mar. Pollut. Bull. 54, 1947–1957. McKenna, J.E., 1997. Influence of physical disturbance on the structure of coral reef fish assemblages in the dry tortugas. Carib. J. Sci. 33 (1–2), 82–97. Magurran, A.E., 2004. Measuring Biological Diversity. Blackwell Publishing, Malden, USA. Maliao, R.J., Turingan, R.G., Lin, J., 2008. Phase-shift in coral reef communities in the Florida Keys National Marine Sanctuary (FKNMS), USA. Mar. Biol. 154, 841–853. Mallela, J., Roberts, C., Harrod, C., Goldspink, C.R., 2007. Distributional patterns and community structure of Caribbean coral reef fishes within a river-impacted bay. J. Fish Biol. 70, 523–537. Massel, S.R., Done, T.J., 1993. Effects of cyclone waves on massive coral assemblages on the Great Barrier Reef: meteorology, hydrodynamics and demography. Coral Reefs 12, 153–166. Mayer-Pinto, M., Junqueira, A.O.R., 2003. Effects of organic pollution on the initial development of fouling communities in a tropical bay, Brazil. Mar. Pollut. Bull. 46, 1495–1503. McClanahan, T., Polunin, N., Done, T., 2002. Ecological states and the resilience of coral reefs. Conserv. Ecol. 6, 18.
˜ a, A., Sant, S., Barrio, J., Marı´n, B., 2006. Me´ndez, E., Ruiz, L.J., Prieto, A., Torres, A., Farin Fish community of a fringing reef at Mochima national Park, Venezuela. Cienc. Mar. 32, 683–693. Mutchler, T., Dunton, K.H., Townsend-Small, A., Fredriksen, S., Rasser, M.K., 2007. Isotopic and elemental indicators of nutrient sources and status of coastal habitats in the Caribbean Sea, Yucatan Peninsula, Mexico. Estuar. Coast. Shelf Sci. 74, 449–457. Nelson, J.S., 2006. Fishes of the World, 4th ed. Wiley, Hoboken. Nughes, M.M., Roberts, C.M., 2003. Partial mortality in massive reef corals as an indicator of sediment stress on coral reefs. Mar. Pollut. Bull. 46, 314–323. Peet, R.K., 1975. Relative diversity indices. Ecology 56, 496–498. Pihl, L., Svenson, A., Moksnes, P.-O., Wennhage, H., 1999. Distribution of green algal mats throughout shallow soft bottoms of the Swedish Skagerrak archipelago in relation to nutrient sources and wave exposure. J. Sea Res. 41, 281–294. Rogers, C.S., 1990. responses of coral reefs and organisms to sedimentation. Mar. Ecol. Prog. Ser. 62, 185–202. Rooker, J.R., Dokken, Q.R., Pattengill, C.V., Holt, G.J., 1997. Fish assemblages on artificial and natural reefs in the Flower Garden Banks National Marine Sanctuary, USA. Coral Reefs 16, 83–92. Ru¨tzler, K., 2004. Sponges on coral reefs: a community shaped by competitive cooperation. Boll. Museo. Ist. Biol. Univ. Genova 68, 85–148. Thomas, M.L.H., Logan, A., 1992. A guide to the ecology of shore line and shallowwater marine communities of Bermuda. Bermuda Biol. St. Res. (Spec. Publ. 30). Ugland, K.I., Bjørgesæter, A., Bakke, T., Fredheim, B., Gray, J.S., 2008. Assessment of environmental stress with a biological index based on opportunistic species. J. Exp. Mar. Biol. Ecol. 366, 169–174. Walter, R.P., Haynes, J.M., 2006. Fish and coral community structure are related on shallow water patch reefs near San Salvador, Bahamas. Bull. Mar. Sci. 79, 365– 374. Ward-Paige, C.A., Risk, M.J., Sherwood, O.A., Jaap, W.C., 2005. Clionid sponge surveys on the Florida reef tract suggest land-based nutrient inputs. Mar. Pollut. Bull. 51, 570–579. Washington, H.G., 1984. Diversity, biotic and similarity indices. Water Res. 18, 653– 694. Wilkinson, C.R., Cheshire, A.C., 1990. Comparisons of sponge populations across the barrier reefs of Australia and Belize evidence for higher productivity in the Caribbean. Mar. Ecol. Prog. Ser. 67, 285–294.
Contents lists available at ScienceDirect
Ecological Indicators journal homepage: www.elsevier.com/locate/ecolind
Case study
Reef fish diversity components as indicators of cumulative effects in a highly impacted fringe reef Gaspar Gonza´lez-Sanso´n *, Consuelo Aguilar Center of Marine Research, 16th Street No. 114, Playa, Ciudad de La Habana, Cuba
A R T I C L E I N F O
A B S T R A C T
Article history: Received 18 April 2009 Received in revised form 19 November 2009 Accepted 23 November 2009
The main goal of our research was to determine which indicators describing cumulative stress might better explain the differences observed in diversity components of reef fish assemblages off Havana City, Cuba. A total of 35,078 individuals of 119 species were counted in 480 stationary point censuses. Counts were distributed among three zones with different levels of pollution and four habitats with different wave stress. Four indexes of diversity components (S, H0 , J0 and PIE) were calculated and correlative analyses performed to explore the best indicators of cumulative effects explaining observed variation. High correlation was found between all diversity components and two indexes of cumulative effects (ICE) built after distinct criteria. In the first case, pollution and wave action were combined following an interactive model. In the second case, an empirical ICE was obtained by totaling the abundance indicators of three groups of organisms, namely sponges, sabellid polychaetes and filamentous algae. ß 2009 Elsevier Ltd. All rights reserved.
Keywords: Reef fish assemblages Diversity Cumulative effects
1. Introduction There is an increasing worldwide concern about the degradation of coral reef communities. However, our knowledge about the susceptibility to disturbance of most common reef fish species and the diverse communities they form is far from complete (Feary et al., 2007). Several natural and anthropogenic factors acting simultaneously produce cumulative effects on fish assemblages. One way of measuring these effects is analyzing changes in diversity components (Aguilar et al., 2004). The selection of appropriated measures of diversity continues to be controversial in spite of exhaustive periodical reviews (Hill, 1973; Peet, 1975; Washington, 1984; Ghent, 1991; Magurran, 2004; Lamb et al., 2009). Regardless of strong criticism, Shannon index of total diversity and Pielou’s evenness index J0 (=H0 /H0 max) continue to be two of the most popular indexes (Gotelli and Graves, 1996), and have been repeatedly used in reef fish assemblage studies (Chabanet et al., 1997; Rooker et al., 1997; Friedlander et al., 2003; Aguilar et al., 2004; Brokovich et al., 2006; Harborne et al., 2006; Me´ndez et al., 2006; Walter and Haynes, 2006; Mallela et al., 2007). Based on an exhaustive review of the topic, Gotelli and Graves (1996) suggest abandoning the idea of incorporating both evenness and species richness into a single index (e.g. Shannon index), and instead recommend the use of rarefaction for
* Corresponding author. E-mail address: [email protected] (G. Gonza´lez-Sanso´n). 1470-160X/$ – see front matter ß 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.ecolind.2009.11.009
the estimation of species richness (S), and Monte Carlo simulation procedures for Hurlbert’s (1971) probability of interspecific encounter (PIE) estimation as an evenness measure. This approach has been used recently for marine assemblages by Feary et al. (2007) and Godı´nez-Domı´nguez et al. (2009). Marine fish assemblages and habitats off Havana City have been investigated in some detail (Gonza´lez-Dı´az et al., 2003; Aguilar et al., 2004, 2007, 2008). No attempt has been made, however, to investigate the correlation of diversity components with benthic communities’ indicators and/or human impact indicators. Using the same data gathered in 2000 by Aguilar et al. (2004) in the subtidal zone off Havana City, a new analysis was made with three basic objectives: (1) to calculate several indexes of diversity components of fish assemblages (namely H0 , J0 , S and PIE) across a range of disturbance regimes in a highly impacted reef region; (2) to perform correlative analyses of index values with variables describing benthic communities; (3) to determine which indicator describing cumulative stress may better explain the differences observed in diversity components. 2. Materials and methods The study area is located in the subtidal zone off Havana City (Fig. 1), where a fringing reef develops mainly in the 12–15 m deep terrace, located 200–300 m offshore. The bottom between the shore and the reef front is an almost bare rocky plain, which near the coast presents a fringe containing large quantities of the sea urchin Echinometra lucunter (Linnaeus, 1758). Since the impact of
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
767
Fig. 1. Study area with sampling zones. Bar graphs show density of sponges (black), gorgonians (dark gray) and corals (light gray) in each bottom type (e: Echinometra; p: rocky plain; t: terrace).
pollution coming from the city varies notably along the coast from the Havana harbor entrance (most polluted area) towards the southwest, the reef was divided into three different zones according to assumed levels of land-based pollution (Fig. 1). Zone 1 is strongly impacted by the heavily polluted waters coming from Havana harbor; zone 2 has an intermediate level of pollution coming from non-point, small sources along the coast and the discharge of the polluted Almendares river; zone 3 can be considered almost free of significant pollution impacts from land. More details and the rationale for this division can be found in
Aguilar et al. (2004, 2007). Detailed quantitative information on several benthic assemblages of algae and invertebrates for each zone has been published by Gonza´lez-Dı´az et al. (2003). Stationary visual censuses (Bohnsack and Bannerot, 1986) were conducted in 15 sites along the coast (six sites in zone 1, four sites in zone 2 and five sites in zone 3). We used a radius of 5 m due to lower visibility in some sites. Four censuses were realized in each of four habitat types (Echinometra fringe, rocky plain, terrace edge and terrace base) at each site. This sampling schedule was repeated twice (February and June 2000). February data can be considered
Fig. 2. Diagram of a typical bottom profile in the study area showing sampling zones and habitat types: Echinometra (Ec), Rocky plain (Pl), Terrace edge (Te) and Terrace base (Tb). Gradients of main stress sources are shown.
768
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
representative of dry season conditions, and June data of rainy season conditions. We considered each combination of zone, habitat and date a sample. Site data inside each zone were pooled, with stationary counts the sampling units. Sample sizes were therefore 24 for zone 1, 16 for zone 2 and 20 for zone 3. Three main factors influence fish assemblages in the study area (Fig. 2). Overfishing is an important human impact affecting all zones and habitats to the same degree. Wave action is a natural source of habitat heterogeneity, which decreases with depth. Pollution is very high near Havana harbor, decreasing towards the southwest. Wave action and pollution can be combined in two ways to produce two different indicators of cumulative effect (Fig. 3). In both cases we define a rank-based index of cumulative effect (ICE). In the first case, ICE values (ranks) result from simply adding the levels of both sources. We call this approach additive. In the second case, we consider an interaction between wave effect and pollution, the first ‘‘washing’’ shallower sites and decreasing pollution effects. We call this approach interactive. A third approach for ICE was obtained using data on benthic assemblages, which can be considered good indicators of organic pollution, the main type of pollution in the study area. We used published quantitative data (Gonza´lez-Dı´az et al., 2003) on sponge colonies density, percent of sabellid polychaetes coverage and percentage of filamentous algae (Cladophora and Herposiphonia) to build an index by simply adding the values of the three variables. We transformed the values obtained into ranks to make a fear comparison with the two models described earlier. We call this third approach empirical (Fig. 3). Four different indexes were used to measure diversity components. The total number of species (S) and probability of interspecific encounter (PIE; Hurlbert, 1971) with their empirical 95% confidence intervals were calculated in rarified samples standardized to 280 individuals using the EcoSim software (Gotelli and Entsminger, 2001). Shannon index of diversity P (H0 = pi ln pi) and Pielou’s eveness index (J0 = H0 /ln S) were calculated for total samples (zone habitat season) using Excel
2003. Association between diversity indexes, benthic variables and cumulative effect values (ICE) was assessed using Spearman’s rank correlation coefficient (rs). Analyses were made using STATISTICA 6.0. 3. Results A total of 35,078 individuals of 119 species were counted in 480 stationary point censuses (Table 1). Species abundances were strongly uneven, with only 30 species forming more than 90% of total individuals counted. The most abundant species were: the bluehead Thalassoma bifasciatum, a small-sized and territorial species feeding on small invertebrates; the bicolor damselfish Stegastes partitus, a small-sized highly territorial omnivore; the ocean surgeonfish Acanthurus bahianus, a medium-sized wandering herbivore and the slippery dick Halichoeres bivittatus, a smallsized and territorial species feeding on small gastropods. These species can be considered dominant in the studied assemblage and they accounted for more than 55% of all individuals censused. In general terms, the fish assemblage was strongly dominated by small- or medium-sized species of low trophic level (mostly herbivores, omnivores and small invertebrate feeders). Larger species were notoriously absent and no individuals of commercial Table 1 Total number (N) and percentage representation of species totaling 90 percent of all individual counted. Maximum total length (Lmax) observed is also given for each species. Family ordering follows Nelson (2006). Family
Species
Lmax (cm)
Main food
Holocentridae
Holocentrus adscencionis Myripristis jacobus
357 179
1.0 0.5
28 17
SC SF&C
Serranidae Malacanthidae Carangidae
Cephalophoplis fulva Malacanthus plumieri Caranx ruber
826 318 543
2.4 0.9 1.5
25 40 20
SF&C SF&I SF&C
Lutjanidae
Lutjanus synagris Ocyurus chrysurus
315 246
0.9 0.7
26 30
SF&C SI
Haemulidae
Haemulon flavolineatum Haemulon plumieri
498 625
1.4 1.8
20 25
M&D M&D
Mullidae
Mulloidichthys martinicus
271
0.8
30
SI
Chaetodontidae
Chaetodon capistratus Chaetodon striatus
576 132
1.6 0.4
17 15
SI SI
Pomacentridae
Abudefduf saxatilis Chromis cyanea Chromis multilineata Stegastes leucostictus Stegastes partitus
581 943 942 249 5274
1.7 2.7 2.7 0.7 15.0
15 10 14 10 9
O P P O O
Labridae
Bodianus rufus Clepticus parrae Halichoeres bivittatus Halichoeres garnoti Thalassoma bifasciatum
261 469 2167 485 8768
0.7 1.3 6.2 1.4 25.0
14 26 15 18 12
SI P SG SG SI
Scaridae
Sparisoma aurofrenatum Sparisoma chrysopterum
616 110
1.8 0.3
31 29
H H
Labrisomidae Chaenopsidae
Malacoctenus triangulatus Emblemaria pandionis
122 317
0.3 0.9
7 5
SI P
Acanthuridae
Acanthurus bahianus Acanthurus chirurgus Acanthurus coeruleus
3738 527 1020
10.7 1.5 2.9
19 21 25
H H H
Tetraodontidae
Canthigaster rostrata
139
0.4
11
O
31614 3464 35078
90.1 9.9 100.0
Sub total Rest (89 spp.) Total
Fig. 3. Graphical representation of three approaches for ranking cumulative effects.
N
%
C = crustaceans; D = decapods; H = plants (herbivores); I = invertebrates; SC = small crustaceans; SF = small fish; SG = small gastropods; SI = small invertebrates; M = mollusks; O = plants and animals (omnivores); P = plankton.
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
769
Fig. 4. Mean abundance (standard error) of four most abundant species. Labels formed by sampling zone number and season (R = rainy; D = dry).
species of groupers, snappers, grunts and jacks were observed along the study. Barracuda, big rays and sharks were also absent in our censuses. Habitat preferences were evident in the two most abundant species (Fig. 4). Bluehead was by far most abundant on the terrace edge, with the subsequent preferred habitat the terrace base. In both cases, abundance of this species was much lower at the highly impacted zone 1. In the terrace base abundance was also low at the medium impacted zone 2. No differences are apparent between sampling dates. Bicolor damselfish was even more segregated among habitats, and was very abundant at both terrace locations. Strong fluctuations in abundance are apparent between sampling dates for this species, but this does not mask the much lower abundance at zone 1 in both habitats. The third species by its total abundance, ocean surgeonfish, did not show any clear trend by habitat, zone or date of sampling. Finally, slippery dick was more abundant in zone 1 for all habitats. This species showed an abundance pattern that can be considered almost contrary to those of bluehead and bicolor damselfish. Values of S and PIE varied among areas inside each habitat in a similar but complex fashion (Fig. 5). In Echinometra fringe and rocky plain habitats, lowest values were found in area 2, while values in areas 1 and 3 were very similar. In both terrace habitats, however, a clear trend was evident in which values decreased from most impacted zone 1 to least impacted zone 3. PIE values showed a very high correlation with H0 (rs = 0.949, p < 0.001, n = 24) and with J0 (rs = 0.928, p < 0.001, n = 24). S values were also highly correlated with H0 (rs = 0.909, p < 0.001, n = 24) and in less degree with J0 (rs = 0.730, p < 0.001, n = 24). In most cases, diversity measures showed significant correlations with sponge density, polychaete coverage and proportion of filamentous algae (Table 2). Only J0 was not correlated with sponge density. All diversity indexes were also correlated with rank values predicted by interactive and empirical indicators of cumulative
effect (ICE). No correlation was found in any case with the additive approach predicted values. The contribution of the four most abundant species to diversity indexes was assessed using rank correlation between the proportion of each species and each diversity index (Table 3). All diversity indexes showed a very high negative rank correlation with the proportion of bluehead (the most abundant species) in samples (Fig. 6). This was not the case for the second most abundant species, bicolor damselfish, for which no correlation was found. Ocean surgeonfish proportion was weakly and negatively correlated with S and H0 but not with PIE and J0 . Finally, slippery dick proportion in samples was weakly correlated with all indexes. 4. Discussion Other authors have also used an index-based approach to quantify cumulative effects. Ugland et al. (2008) used a simple indicator of pollution effect by averaging the relative abundance of five polychaete species. Hale and Heltsche (2008) showed that an index based in several benthic indicators strongly discriminated stations in their study. A critical question about our results, however, is related to the reliability of the variables we used to build our indicator of cumulative effect. We summarize below evidence in scientific literature supporting our selection. An increase of sponge biomass with organic pollution and high sediment load is well documented (Chalker et al., 1985; Rogers, 1990; Wilkinson and Cheshire, 1990; Aerst and van Soest, 1997; Ward-Paige et al., 2005; Costa et al., 2008). Sponges are filter feeders that primarily consume ultraplankton. As Ru¨tzler (2004) asserts, land runoff and organic pollution in moderate concentration may benefit sponges by providing nutrients for bacteria. Sponges and corals respond to nutrient and sediment increase in very different ways, with coral biomass decreasing in reefs stressed by pollution and siltation (Aerst and van Soest, 1997; Nughes and
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
770
Fig. 5. Estimated values of the probability of interspecific encounter (PIE) and species number (S) in samples rarefied to 280 individuals (95% confidence intervals). Labels formed by sampling zone number and season (R = rainy; D = dry).
Table 2 Spearman’s rank correlation coefficients (rs) and associated probabilities (p) for combinations of diversity components and environmental or stress indicator variables: S = number of species; PIE = probability of interspecific encounter; J0 = Pielou’s evenness index; H0 = Shannon’s diversity index; ICE = index of cumulative effect. Variables
Sponges Polychaetes Filamentous algae ICE additive ICE Interactive ICE empirical
S
J0
PIE
H0
rs
p
rs
p
rs
p
rs
p
0.68 0.59 0.40 0.02 0.44 0.63
<0.001 0.002 0.049 0.935 0.030 0.001
0.45 0.56 0.48 0.32 0.48 0.71
0.026 0.004 0.016 0.130 0.018 <0.001
0.31 0.53 0.42 0.13 0.44 0.51
0.142 0.008 0.043 0.554 0.033 0.010
0.62 0.60 0.46 0.21 0.48 0.68
0.001 0.002 0.024 0.318 0.018 <0.001
Table 3 Spearman’s rank correlation coefficients (rs) and associated probabilities (p) for combinations of diversity components and most abundant species: S = number of species; PIE = probability of interspecific encounter; J0 = Pielou’s evenness index; H0 = Shannon’s diversity index. Species
Thalassoma bifasciatum Stegastes partitus Acanthurus bahianus Halichoeres bivittatus
S
J0
PIE
H0
rs
p
rs
p
rs
p
rs
p
0.73 0.26 0.52 0.51
<0.001 0.225 0.009 0.010
0.88 0.08 0.28 0.58
<0.001 0.713 0.175 0.002
0.81 0.20 0.14 0.58
<0.001 0.348 0.522 0.003
0.87 0.11 0.44 0.52
<0.001 0.622 0.029 0.008
Roberts, 2003). Sponge cover was negatively correlated with hard coral cover in the Florida Keys (Maliao et al., 2008). Polychaetes have been considered good indicators of eutrophication by several authors (Crema et al., 1991; Mayer-Pinto and Junqueira, 2003; Ugland et al., 2008). Filtering abilities of sabellid polychaetes are very high (Licciano et al., 2005, 2007), giving this group a competitive advantage in environments impacted by sewage-
polluted and eutrophicated waters (Licciano et al., 2002). Increasing availability of inorganic nutrients is known to stimulate the abundance of ephemeral macroalgae, including those of genus Cladophora (Gordon and McComb, 1989; Lapointe et al., 2004; Kraufvelin et al., 2007; McClanahan et al., 2007; Mutchler et al., 2007; Karez et al., 2008). During a study carried out in the Swedish Skagerrak archipelago, Pihl et al. (1999) concluded that the
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
771
the manuscript. We also thank divers Luis Sanchez and Armando Perez for their assistance in the field. Partial funding for this research was provided by a Canadian International Development Agency Tier 2 Grant to the Centro de Investigaciones Marinas, Cuba and the University of New Brunswick, Saint John, Canada.
References
Fig. 6. Relationship of probability of interspecific encounter (PIE, black circles in upper panel), species number (S, white circles in upper panel), Shannon’s diversity index (H0 , white circles in bottom panel) and Pielou’s eveness index (J0 , black circles in bottom panel) with numerical proportion of Thalassoma bifasciatium (P) in samples.
development of green algal mats (Cladophora and Enteromorpha) was most probably caused by a general elevation in nutrient levels. Several authors have identified wave action as a factor controlling settlement success and growth rates of some sessile organisms in reefs (Massel and Done, 1993; McClanahan et al., 2002). This supports our assumption of a decreasing wave impact from shallower to deeper habitats. In this case wave action can be considered a habitat heterogeneity-inducing factor. The correlation among diversity indexes and cumulative effects (ICE) can be explained by the response of the two most abundant wrasses (bluehead and slippery dick). The proportional abundance of bluehead decreased consistently at sites of higher stress, while that of slippery dick increased. These responses contribute to increased evenness at more stressed sites, decreasing the high dominance of bluehead and allowing other species to be present. A plausible explanation for this change in relative abundance is that slippery dick has a higher tolerance to stressor effects than bluehead, a hypothesis already advanced by Aguilar et al. (2004). Slippery dick appears to be more tolerant to siltation than other species of wrasses (Aliaume et al., 1990; Baelde, 1990; BouchonNavaro et al., 1992; Thomas and Logan, 1992). After McKenna (1997), small wrasses (especially Halichoeres bivittatus) dominated the assemblages at the impacted site in his study. Acknowledgements We acknowledge the contribution of two anonymous reviewers whose comments contributed significantly to the enhancement of
Aerst, L.A.M., van Soest, R.W.M., 1997. Quantification of sponge/coral interactions in a physically stressed reef community, NE Colombia. Mar. Ecol. Prog. Ser. 148, 125–134. Aguilar, C., Gonza´lez-Sanso´n, G., Faloh, I., Curry, A., 2008. Spatial variation in stable isotopes (d13C and d15N) in marine fishes along the coast of Havana City: evidence of human impacts from harbor and river waters. J. Coast. Res. 24, 1281–1288. Aguilar, C., Gonza´lez-Sanso´n, G., Herna´ndez, I., MacLatchy, D.L., Munkittrick, K.R., 2007. Effects-based assessment in a tropical coastal system: status of bicolor damselfish (Stegastes partitus) on the north shore of Cuba. Ecotoxicol. Environ. Saf. 67, 459–471. Aguilar, C., Gonza´lez-Sanso´n, G., Munkittrick, K.R., MacLatchy, D.L., 2004. Fish assemblages on fringe coral reefs of the northern coast of Cuba near Havana Harbor. Ecotoxicol. Environ. Saf. 58, 126–138. Aliaume, C., Laserre, G., Louis, M., 1990. Organisation spatiale des peuplements ichtyologiques des herbiers a‘Thalassia du Grand Culde Sac marin en Guadeloupe. Rev. Hydrobiol. Trop. 23, 231–250. Baelde, P., 1990. Differences in the structures of fish assemblages in Thalassia testudinum beds in Guadeloupe, FrenchWest Indies, and their ecological significance. Mar. Biol. 105, 163–173. Bohnsack, J.A., Bannerot, S.P., 1986. A stationary visual census technique for quantitatively assessing community structure of coral reef fishes. NOAA Tech Rep NMFS 41, iii+15 p. Bouchon-Navaro, Y., Bouchon, C., Louis, M., 1992. L’ichthyofaune des herbiers de phanerogames marines de la baie de Fort-de-France (Martinique, Antilles Franc¸aises). Cybium 16, 307–330. Brokovich, E., Baranes, A., Goren, M., 2006. Habitat structure determines coral reef fish assemblages at the northern tip of the Red Sea. Ecol. Indicators 6, 494–507. Chabanet, P., Ralambondrainy, H., Amanieu, M., Faure, G., Galzin, R., 1997. Relationships between coral reef substrata and fish. Coral Reefs 16, 93–102. Chalker, B.E., Carr, K., Gill, E., 1985. Measurement of primary production and calcification in situ on coral reefs using electrode techniques. In: Proc Fifth Internat Coral Reefs Cong., Tahiti, vol. 6, pp. 167–172. Costa Jr., O.S., Nimmo, M., Attrill, M.J., 2008. Coastal nitrification in Brazil: a review of the role of nutrient excess on coral reef demise. J. S. Am. Earth Sci. 25, 257– 270. Crema, R., Castelli, A., Prevedelli, D., 1991. Long term eutrophication effects on macrofaunal communities in Northern Adriatic Sea. Mar. Pollut. Bull. 22 (10), 503–508. Feary, D.A., Almany, G.R., Jones, G.P., McCormick, M.I., 2007. Coral degradation and the structure of tropical reef fish communities. Mar. Ecol. Prog. Ser. 333, 243– 248. Friedlander, A.M., Brown, E.K., Jokiel, P.L., Smith, W.R., Rodgers, K.S., 2003. Effects of habitat, wave exposure, and marine protected area status on coral reef fish assemblages in the Hawaiian archipelago. Coral Reefs 22, 291–305. Ghent, A.W., 1991. Insights into diversity and niche breadth analyses from exact small-sample tests of the equal abundance hypothesis. Am. Midl. Nat. 126, 213– 255. Godı´nez-Domı´nguez, E., Freire, J., Franco-Gordo, C., Gonza´lez-Sanso´n, G., 2009. Decomposing diversity patterns of a soft-bottom macroinvertebrate community in the tropical eastern Pacific. J. Mar. Biol. Assoc. U.K. 89 (1), 31–38. Gonza´lez-Dı´az, P., Guardia, E., de la Gonza´lez-Sanso´n, G., 2003. Efecto de efluentes terrestres sobre las comunidades bento´nicas de arrecifes coralinos de Ciudad de la Habana, Cuba. Rev. Invest. Mar. 24, 193–204. Gordon, D.M., McComb, A.J., 1989. Growth and production of the green alga Cladophora montagneana in a eutrophic Australian estuary and its interpretation using a computer program. Water Res. 23, 633–645. Gotelli, N.J., Graves, G.R., 1996. Null Models in Ecology. Smithsonian Institution Press, Washington. Gotelli, N.J., Entsminger, G.L., 2001. EcoSim: Null models software for ecology, Version 7.0. Acquired Intelligence Inc. & Kesey-Bear, http://homepages. together.net/gentsmin/ecosim.htm. Hale, S.S., Heltsche, J.F., 2008. Signals from the benthos: development and evaluation of a benthic index for the nearshore Gulf of Maine. Ecol. Indicators 8, 338– 350. Harborne, A.R., Mumby, P.J., Zychaluk, K., Hedley, J.D., Blackwell, P.G., 2006. Modeling the beta diversity of coral reefs. Ecology 87, 2871–2881. Hill, M.O., 1973. Diversity and evenness: a unifying notation and its consequences. Ecology 54, 427–432. Hurlbert, S.H., 1971. The nonconcept of species diversity: a critique and alternative parameters. Ecology 52, 577–586. Karez, R., Engelbert, S., Kraufvelin, P., Pedersen, M.F., Sommer, U., 2008. Biomass response and changes in composition of ephemeral macroalgal assemblages along an experimental gradient of nutrient enrichment. Aquat. Bot. 78, 103–117.
772
G. Gonza´lez-Sanso´n, C. Aguilar / Ecological Indicators 10 (2010) 766–772
Kraufvelin, P., Ruuskanen, A.T., Nappu, N., Kiirikki, M., 2007. Winter colonisation and succession of filamentous macroalgae on artificial substrates and possible relationships to Fucus vesiculosus settlement in early summer. Estuar. Coast. Shelf Sci. 72, 665–674. Lamb, E.G., Bayne, E., Holloway, G., Schieck, J., Boutin, S., Herbers, J., Haughland, D.L., 2009. Indices for monitoring biodiversity change: are some more effective than others? Ecol. Indicators 9, 432–444. Lapointe, B.E., Barile, P.J., Matzie, W.R., 2004. Anthropogenic nutrient enrichment of seagrass and coral reef communities in the Lower Florida Keys: discrimination of local versus regional nitrogen sources. J. Exp. Mar. Biol. Ecol. 308, 23–58. Licciano, M., Giangrande, A., Gambi, M.C., 2002. Reproduction and simultaneous hermaphroditism in Branchiomma luctuosum (Polychaeta, Sabellidae) from the Mediterranean Sea. Invert. Biol. 121, v55–v65. Licciano, M., Stabili, L., Giangrande, A., 2005. Clearance rates of Sabella spallanzanii and Branchiomma luctuosum (Annelida: Polychaeta) on a pure culture of Vibrio alginolyticus. Water Res. 39, 4375–4384. Licciano, M., Stabili, L., Giangrande, A., Cavallo, R.A., 2007. Bacterial accumulation by Branchiomma luctuosum (Annelida: Polychaeta): a tool for biomonitoring marine systems and restoring polluted waters. Mar. Environ. Res. 63, 291–302. McClanahan, T.R., Carreiro-Silva, M., DiLorenzo, M., 2007. Effect of nitrogen, phosphorous, and their interaction on coral reef algal succession in Glover’s Reef, Belize. Mar. Pollut. Bull. 54, 1947–1957. McKenna, J.E., 1997. Influence of physical disturbance on the structure of coral reef fish assemblages in the dry tortugas. Carib. J. Sci. 33 (1–2), 82–97. Magurran, A.E., 2004. Measuring Biological Diversity. Blackwell Publishing, Malden, USA. Maliao, R.J., Turingan, R.G., Lin, J., 2008. Phase-shift in coral reef communities in the Florida Keys National Marine Sanctuary (FKNMS), USA. Mar. Biol. 154, 841–853. Mallela, J., Roberts, C., Harrod, C., Goldspink, C.R., 2007. Distributional patterns and community structure of Caribbean coral reef fishes within a river-impacted bay. J. Fish Biol. 70, 523–537. Massel, S.R., Done, T.J., 1993. Effects of cyclone waves on massive coral assemblages on the Great Barrier Reef: meteorology, hydrodynamics and demography. Coral Reefs 12, 153–166. Mayer-Pinto, M., Junqueira, A.O.R., 2003. Effects of organic pollution on the initial development of fouling communities in a tropical bay, Brazil. Mar. Pollut. Bull. 46, 1495–1503. McClanahan, T., Polunin, N., Done, T., 2002. Ecological states and the resilience of coral reefs. Conserv. Ecol. 6, 18.
˜ a, A., Sant, S., Barrio, J., Marı´n, B., 2006. Me´ndez, E., Ruiz, L.J., Prieto, A., Torres, A., Farin Fish community of a fringing reef at Mochima national Park, Venezuela. Cienc. Mar. 32, 683–693. Mutchler, T., Dunton, K.H., Townsend-Small, A., Fredriksen, S., Rasser, M.K., 2007. Isotopic and elemental indicators of nutrient sources and status of coastal habitats in the Caribbean Sea, Yucatan Peninsula, Mexico. Estuar. Coast. Shelf Sci. 74, 449–457. Nelson, J.S., 2006. Fishes of the World, 4th ed. Wiley, Hoboken. Nughes, M.M., Roberts, C.M., 2003. Partial mortality in massive reef corals as an indicator of sediment stress on coral reefs. Mar. Pollut. Bull. 46, 314–323. Peet, R.K., 1975. Relative diversity indices. Ecology 56, 496–498. Pihl, L., Svenson, A., Moksnes, P.-O., Wennhage, H., 1999. Distribution of green algal mats throughout shallow soft bottoms of the Swedish Skagerrak archipelago in relation to nutrient sources and wave exposure. J. Sea Res. 41, 281–294. Rogers, C.S., 1990. responses of coral reefs and organisms to sedimentation. Mar. Ecol. Prog. Ser. 62, 185–202. Rooker, J.R., Dokken, Q.R., Pattengill, C.V., Holt, G.J., 1997. Fish assemblages on artificial and natural reefs in the Flower Garden Banks National Marine Sanctuary, USA. Coral Reefs 16, 83–92. Ru¨tzler, K., 2004. Sponges on coral reefs: a community shaped by competitive cooperation. Boll. Museo. Ist. Biol. Univ. Genova 68, 85–148. Thomas, M.L.H., Logan, A., 1992. A guide to the ecology of shore line and shallowwater marine communities of Bermuda. Bermuda Biol. St. Res. (Spec. Publ. 30). Ugland, K.I., Bjørgesæter, A., Bakke, T., Fredheim, B., Gray, J.S., 2008. Assessment of environmental stress with a biological index based on opportunistic species. J. Exp. Mar. Biol. Ecol. 366, 169–174. Walter, R.P., Haynes, J.M., 2006. Fish and coral community structure are related on shallow water patch reefs near San Salvador, Bahamas. Bull. Mar. Sci. 79, 365– 374. Ward-Paige, C.A., Risk, M.J., Sherwood, O.A., Jaap, W.C., 2005. Clionid sponge surveys on the Florida reef tract suggest land-based nutrient inputs. Mar. Pollut. Bull. 51, 570–579. Washington, H.G., 1984. Diversity, biotic and similarity indices. Water Res. 18, 653– 694. Wilkinson, C.R., Cheshire, A.C., 1990. Comparisons of sponge populations across the barrier reefs of Australia and Belize evidence for higher productivity in the Caribbean. Mar. Ecol. Prog. Ser. 67, 285–294.