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Modelling sponge species diversity using a morphological predictor: a tropical test of a temperate model
Journal for
J. Nat. Conserv. 10, 41–50 (2002) © Urban & Fischer Verlag
Nature Conservation
http://www.urbanfischer.de/journals/jnc
Modelling sponge species diversity using a morphological predictor: a tropical test of a temperate model James J. Bell1,* & David K. A. Barnes1,2 1
Department of Zoology and Animal Ecology, University College Cork, Ireland; present address: School of Applied Sciences, University of Glamorgan, Pontypridd, Rhondda Cynon Taff, Wales, CF37 1DL, U.K.; e-mail: [email protected] 2 FRONTIER, The Society for Environmental Exploration, London, U.K.; present address: British Antarctic Society, High Cross, Madingley Road, Cambridge CB3 0ET, U.K.
Abstract The contribution of sponges to marine surveys is often underestimated due to problems of identification, synonymous species and limited numbers of specialists in the field. Bell & Barnes (2001) illustrated how sponge morphological diversity (diversity of body forms) might be used as a predictor of sponge species diversity and richness. This study investigated these relationships at six tropical West Indian Ocean localities in a number of habitat types. These habitats included tropical coral reefs, soft substratum (seagrass, mangrove and sand), caves and boulders. Sampling was undertaken at three depth zones in coral reef habitats only (intertidal, 10–15 m and 20–25 m), with the other habitats sampled in less than 10 m of water. Species diversity and richness were significantly correlated (P < 0.05) with morphological diversity at all localities and depths in coral reef and soft substratum habitats. However, no significant correlation was found between these variables in cave or boulder habitats. The slope of the linear regression found between morphological diversity and species diversity did not significantly differ between coral reef, soft substratum and temperate reef (data taken from Bell & Barnes 2001) habitats. Similarly coral reefs showed the same relationship between morphological diversity and species richness as temperate reefs, however the relationship between morphological diversity and species richness was significantly different at both habitats compared with soft substratum environments. Sponge morphological diversity therefore may be more useful as a predictor of sponge species diversity, rather than species richness, as the former relationship is common between more habitats than the latter. Key words: Morphology, sponge, diversity, richness, coral reefs, temperate reefs.
Introduction Sponges are ubiquitous to virtually all marine habitats and are often very abundant and speciose and as such are a potentially important component of biodiversity. For these reasons sponges should form a significant component of the benthos in biological surveys of marine areas. Conservation and survey groups such as Marine Nature Conservation Review, Coral Cay Conservation, Greenforce, Operation Wallacea, Reef Watch, Sea Search, The Society of Environmental Exploration
(Frontier) and the World Wildlife Conservation Trust often conduct surveys in areas of high sponge diversity such as the Caribbean (Diaz et al. 1990), East Africa (e.g. Barnes 1999) or the east Pacific (van Soest 1985). However, even though sponges are often abundant, rich (number of species) and diverse (probability of predicting the next species found), their contribution to the survey can be considerably underestimated for the following reasons. 1) Sponges can be very difficult to identify
*corresponding author
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J. J. Bell & D. K. A. Barnes
especially in remote areas where little work has been previously undertaken 2) the time taken for sampling sponge communities and associated laboratory work can be considerable 3) problems are often encountered obtaining permits (especially in tropical areas) to export specimens to sponge taxonomists 4) under some circumstances taxonomic uncertainty of a species identity may cause problems in its identification. Although sponge morphology is highly varied, their forms have been classified into a number of distinct types (Boury-Esnault & Rützler 1997). Some of these morphotypes are straight-forward such as encrusting, tubular or funnel shaped others require reference to illustrations such as papillate, ficiform or repent. In a method proposed by Bell & Barnes (2001), morphological diversity was used as an alternative measure of sponge species diversity. Morphological diversity is considerably easier to measure because it requires less time to collect data and the information can be recorded in situ. An obvious disadvantage to this method is the quality of the information obtained. The basis of using morphological diversity as a predictor of species diversity is due to the variation in the phenotypic expression of body shape observed in sponges (e.g. Manconi & Pronzato 1991; Bell & Barnes 2000a) and the importance of environmental parameters in controlling such morphological variation (Bell & Barnes 2000a). These same environmental parameters contribute to the variation in sponge species distributions (Bell & Barnes 2000b). With the apparent link between these two aspects of sponge ecology, a relationship between sponge morphology and species diversity may have seemed intuitive.
The relationship between sponge morphological diversity and species diversity has only been described for a temperate region of very high sponge species diversity (Bell & Barnes 2001). The investigation of such a relationship may be far more useful in tropical areas where the problems of collection of species diversity information (see above) are more difficult. This study tests the validity and general applicability of the formula to predict sponge species diversity by measuring morphological diversity proposed by Bell & Barnes (2001) in different regions, habitats and depth zones. It is important to determine if different relationships exist in different habitats, geographical regions and depth zones, so surveyors know if different relationships should be used in different environments, or whether such a method of estimating sponge species richness and diversity is suitable only in specific habitats. The aim of this study was to examine patterns of sponge morphological diversity, species diversity and richness across six tropical regions in four different habitat types (coral reefs, soft substratum, boulders and caves) and three different depth zones (intertidal, 5–10m, 15–25m), with the objective to determine 1) whether there were linear relationships between morphological and species diversity within different habitats, depth zones and localities, 2) whether these linear relationships (see objective 1) were significantly different between habitats, localities and depth zones and 3) whether tropical relationships between sponge morphological diversity and sponge diversity differed from that of the temperate environment from which it was proposed.
Figure 1. Position of the West Indian Ocean study sites. The sites are Watamu-Malindi (Kenya), Quirimba Island (Northern Mozambique), Anakao region (south-west Madagascar) and Inhaca Island (Southern Mozambique).
Modelling sponge species diversity
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intertidal and subtidal depths. Only the coral reef habitat was sampled at three depth zones as other habitats were either not present at all depths or (in the case of sand) unoccupied by sponges. The morphotypes by which sponges were characterised in this study conform to the categories in the thesaurus of sponge morphology (Boury-Esnault & Rützler 1997) and are illustrated in Figure 2. Analysis Patterns of morphological and species diversity were described with the Shannon and Wiener information function H’ = –∑ pi Ln pi (Krebs 1989, after Maldonado & Young 1996). Lines of best fit were superimposed onto plots of morphological diversity vs species diversity and species richness using standard regression procedures. Where necessary (in order to obtain straight line relationships) data was Log10 transformed. General Linear Model ANalysis Of VAriance (GLM ANOVA) was used to compare the slopes of linear relationships (regression) between species diversity, richness (Log 10) and morphological diversity. This method compares the slope of each relationship to an average slope fitted to all the data to be compared.
Results Figure 2. The gross morphological categories into which sponge species were classified from tropical and temperate (Bell & Barnes 2001) localities. * denotes those found in tropical localities and + indicates those found in temperate sites.
Methods Study areas Sponges were sampled at four west Indian Ocean sites and two Atlantic sites between 1996 and 2000. The Atlantic sites were the San Blas Islands at 9ºN, near the Smithsonian Tropical Research Institute, and at similar latitude in the Cape Verde Islands, off West Africa. The location of the major sampling areas in the West Indian Ocean is shown in Figure 1. At each site the number and identity of sponges was recorded in randomly placed quadrats of one square metre area. The number of each morphological type was recorded in the same quadrats. Sampling procedures were carried out in each of coral reef, soft substratum (sand and seagrass meadow), cave and boulder habitats in
Do relationships exist between sponge morphological, species diversity and species richness? Linear relationships (Pearsons correlation > 0.25, P < 0.05 in each case) were evident between morphological diversity vs species diversity and morphological diversity vs species richness at all geographical locations. These relationships were also apparent with the small data sets of each of the four main geographical study sites. The relationships are of simple straightline nature in the case of morphological diversity versus (vs) species diversity (Figure 3). Does the diversity of relationship differ with environmental conditions of site (geographical locality)? The relationships found between morphological diversity and species diversity at different depth zones within coral reef habitats (intertidal, 5–10 m and 15–25 m) showed no significant differences between the slopes or intercepts of these relationships at different geographical locations, or between depth zones (GLM ANOVA F-ratio < 1.23, P < 0.05). There was, therefore, one consistent relationship between species di-
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Figure 3. The relationship between sponge morphological diversity, species diversity and richness in coral reef habitats at six tropical localities (averaged over depth). Linear regression and Pearsons correlations (r2) are shown for data from all localities combined as General Linear Model Analysis of Variance showed no significant differences between the relationships at each locality (F-ratio < 1.23, P < 0.05).
versity and morphological diversity at coral reefs, irrespective of depth and site (within those sampled). As such, combining data from all coral reef depth zones and geographic localities is statistically valid (Figure 3). An overall significant positive linear relationship (with data from all depth zones and geographic regions) was found between sponge morphological diversity and species diversity on coral reefs (F-ratio = 41.50, P < 0.001). The slope of the regression was significantly different to zero (t-value 6.44, P < 0.001), thus species diversity was significantly dependent on morphological diversity (Figure 3). Data was only available at depths < 10 m for other habitats (mangroves hardly encroach the subtidal and sea-grasses are restricted to shallow water). A signifi-
cant positive linear relationship (Pearsons correlation = 0.53, P < 0.05) was found between morphological diversity and species diversity in soft substratum habitats (Figure 4). No significant difference was observed between the slopes or the intercepts of these relationships at the different geographic regions (F-ratio < 0.57, P > 0.646). Data from all localities was then combined for soft substratum habitats (Figure 4). A significant positive linear relationship was found between morphological diversity and species diversity when all the data from soft substratum habitats at all localities was combined (F-ratio = 3.23, P = 0.01). However, there was no correlation (Pearsons correlation < 0.24, P < 0.05) between sponge morphological diversity and species diversity at any geographic locality, or with all
Modelling sponge species diversity
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Figure 4. The relationships between sponge morphological diversity, species diversity and richness in soft sediment habitats at six tropical localities (averaged over depth). Linear regression and Pearsons correlations (r2) are shown for data from all localities combined as General Linear Model Analysis of Variance showed no significant differences between the relationships at each locality (F-ratio < 0.57, P > 0.646).
data (from all localities) combined in boulder or cave habitats. No significant differences between localities or depth zones were found between morphological diversity vs species diversity relationships in coral reef or soft substratum habitats. The data from all habitats, localities and depths was therefore plotted (Figure 5) and a GLM ANOVA was used to compare the slopes of the relationships between habitat types. As no significant relationship was found for cave and boulder habitats, only data from coral reefs and soft substratum was used in the comparison. No significant differences (F-ratio = 0.38, P = 0.539) were observed between either the slopes or the intercepts of the relationships between sponge species diversity and morphological diversity between
coral reef and soft substratum habitats (all localities or depths). However, the minimum and maximum species and morphological diversity was lower for soft substratum than for coral reef habitats (Figure 5). Do morphological diversity-species richness relationships differ with environmental conditions of site? Morphological diversity was significantly correlated (Pearsons correlation > 0.50, P < 0.05) with species richness once transformed logarithmically (Log 10 for all habitats and depths). The only habitats with no apparent relationship were, as with morphological diversity vs species diversity, those characterised by caves
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Figure 5. A plot combining sponge morphological diversity, species diversity and species richness for three tropical habitats at all localities and depths (coral reefs only) combined. A single regression line was fitted to soft substratum and coral reef species diversity data as these habitats showed no significant difference between the relationships. However, significant differences were found for species richness data and individual regressions were fitted. Data from cave and boulder habitats were not included in the calculation of average regression lines as no linear relationships were found.
and boulder habitats (graphs not shown, Pearsons correlation > 0.13, P > 0.05) and no further analysis was performed on this data. No significant differences were observed between the slopes of the relationships at each depth zone or locality in coral reef habitats so all data was combined (F-ratio < 0.45, P < 0.001). A significant linear regression (F-ratio = 23.84, P < 0.001) was fitted to all the data from all depth zones and localities from coral reef habitats, with the calculation of a slope significantly different to zero (t-value = 4.88, P < 0.001). On coral reefs, the same linear relationship between sponge morphological diversity and sponge species richness was found, irrespective of locality or depth zone. A significant linear relationship was found between morphological diversity and sponge species richness
(Log 10) at each locality (Pearsons correlation > 0.41, P < 0.001) in soft substratum habitats. GLM ANOVA showed no significant difference (F = 0.44, P = 0.727) between the slopes of these relationships for soft substratum habitats at the different localities, so all the data was combined (Figure 4). A linear regression was fitted to this combined relationship, the slope of which was significantly different to zero (t-value = 2.55, P = 0.02). Sponge species richness (Log 10) was significantly linearly correlated with sponge morphological diversity, irrespective of locality. Boulder and cave habitats showed no linear relationships at any localities between morphological diversity species richness (Log 10). A plot was constructed of sponge morphological diversity and species richness (Log 10) for all habitats combined (except boulder and cave habitats) as there
Modelling sponge species diversity
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Figure 6. A comparison between the relationship of sponge morphological diversity, species diversity (a) and richness (b) at tropical and temperate habitats (taken from Bell & Barnes 2001). A combined regression was calculated for coral reef, soft substratum and temperate reef habitats for species diversity data only as species richness relationships were only the same for coral and temperate reef data. Cave and boulder habitats were not included in the calculation of average regression lines as no linear relationships were found.
was no significant difference observed between depth zones (coral reefs only) or localities for each habitat type (Figure 5). GLM ANOVA was then used to compare the slopes of the relationship between coral reef and soft substratum habitats. These habitats could not be compared with boulder and cave habitats, as no linear relationships were found between species richness and morphological diversity for this habitat type. A significant difference was observed between the slopes of the relationships of species richness and morphological diversity in coral reef and soft substratum habitats (F-ratio = 9.51, P = 0.003). A significantly greater increase in species richness per unit increase in morphological diversity was observed for coral reef than for soft substratum habitats. Also any given value of morphological diversity in soft substratum environ-
ments corresponded to a lower sponge species richness than for coral reef habitats. Do relationships differ between temperate and tropical environments? Relationships between sponge morphological diversity and species diversity, morphological diversity and species richness have previously been established at a temperate site (Lough Hyne, south-west Ireland, see Bell & Barnes 2001). To compare temperate and tropical relationships the current data was combined with the temperate data from the literature (Figure 6a). Thus, relationships were compared between tropical coral reef and soft substratum habitats vs temperate cliffs (all depths and localities combined for each habi-
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J. J. Bell & D. K. A. Barnes
tat). No significant differences (GLM ANOVA) were found between the slopes of the relationships between morphological and species diversity at these three habitat types (F-ratio = 1.25, P = 0.29). A unit increase in morphological diversity corresponded to the same increase in sponge species diversity, irrespective of habitat. A linear regression fitted to all the data showed morphological diversity to be significantly dependent on species diversity with a slope significantly different to zero (t-value = 9.73, P < 0.001). GLM ANOVA of the relationship between species richness (Log 10) and morphological diversity, in contrast, showed a significant difference between habitats (Figure 6b). No significant difference was found between coral reef and temperate reef habitats (t-value 0.09, P = 0.928), but both these habitats had significantly different slopes to soft substratum habitats (tvalue = 4.05, P < 0.001). A unit increase in morphological diversity resulted in a greater increase in species richness in coral and temperate reefs than for soft substratum habitats. Morphological diversity and species richness values obtained for soft substratum habitats were lower than for those from coral and temperate reef habitats. Linear regression equations were generated for the relationship between sponge species diversity and morphological diversity for all habitats combined (Figure 6a), but separately for hard (coral and temperate reef) and soft substratum habitats from the relationship between species richness (Log 10) and morphological diversity (Figure 6b).
Discussion Using the diversity of easily identifiable sponge morphotypes (Figure 2), the diversity and richness of sponge species can be predicted in coral reef and tropical soft substratum habitats. The relationship between morphological diversity and species diversity was the same as that found for a temperate assemblage (Bell & Barnes 2001), irrespective of locality or depth. This suggests that sponge morphological diversity may then be used as an effective universal surrogate for predicting sponge species diversity, with the exception of boulder and cave habitats. It seems likely that this relationship between sponge morphological diversity and species diversity is a characteristic feature of most sponge communities. However, although morphological diversity was also linearly correlated with sponge species richness (Log 10), significantly different relationships existed between soft and hard (coral and temperate reef habitats) substratum habitats, even though there was no difference between localities (within each habitat).
The differences between these habitats resulted from relatively low sponge richness, but with those species found exhibiting many different body forms. The difference between soft substratum and hard substratum habitats may have been intuitive, considering the nature of these environments. The relationship between sponge morphological diversity, richness and species diversity was not found in cave or boulder habitats. This may have been expected as species inhabiting these types of environment commonly exhibit encrusting forms because of the nature of the habitat. Boulders, which are in disturbed areas are often only colonised by encrusting forms, as these can regenerate much faster than other types in this destructive environment (Ayling 1983). In more sheltered environments, sponges typically inhabit the undersides of boulders, probably to prevent sediment settlement on their surfaces (Maughan & Barnes 2000). The nature of the two-dimensional habitat associated with the undersides of boulders obviously restricts sponge morphology to encrusting or low profile forms (Bell 2001). Cave habitats often experience strong surge that may also prevent the growth of species that exhibit non-encrusting or massive morphological types (Sarà 1970; Corriero et al. 2000). There are important implications from transforming species richness onto a logarithmic scale. It means that the measurement of morphological diversity is less effective as a predictor of sponge richness at higher species richness values than it is of species diversity (for which the relationship is linear). Therefore, morphological diversity is likely to be a better predictor of sponge species diversity than of species richness in communities with high numbers of sponge species. This also means the ability of the current method as a monitoring tool remains speculative. Although this method may be extremely useful in identifying areas of high, low, or moderate sponge species diversity and richness, it may require a considerable amount of change in any particular community before this method detects it. It will also be insensitive to the loss or gain of rare species from, or to, a community. However, these statements are also true for any measurement of species diversity. There are many uses for this method of estimating sponge species diversity and richness from the measurement of morphological diversity. 1) This method will be useful in identifying areas of relatively high sponge species diversity and richness that may be important for the purposes of designation, management and conservation of marine areas. 2) It could also be used as an initial survey tool for prioritising and directing more detailed surveys.
Modelling sponge species diversity
3) It seems likely that relatively inexperienced users can use a method, such as that proposed here, in a range of habitats for quickly estimating sponge species diversity and richness. It may be critical for organisations using non-specialists with limited time and resources, as it will allow quick and easy collection of data. 4) As a monitoring tool, the method needs to be developed further and then tested. One such way this may be possible is to increase the number of morphological categories/groups used. In most cases, sponge taxonomists describe a single gross morphological category for each sponge species (such as those used in this study). It is this limited number of morphological categories that leads in part to the logarithmic relationship found between morphological diversity and species richness. However, many studies have illustrated how variable sponge morphology can be under different environmental situations within a single gross morphological group or species (Bell et al. 2002; Kanndorp 1999; Manconi & Pronzato 1991; Palumbi 1984, 1986). For example, Bell et al. (2002) found Cliona celata (Grant) to show at least five different morphologies under different environmental conditions, although its morphology is generally classified as massive (see Figure 2). Although this may appear contradictory, sponges generally only show one morphological type in a single habitat (e.g. Manconi & Pronzato 1991). This means using more morphological groups will not over-estimate the contribution of a single sponge species in any particular habitat (compared to other habitats, localities etc.). However, for different species that may be classified within the same gross morphological group (under the current method) smaller scale morphological differences may be present. Increasing the number of morphological groups for these gross morphological categories, would allow differentiation between a greater number of species. A consequence of increasing the number of morphological groups is the greater amount of time required in the field, but this should still be possible by non-sponge specialists. Although the proposed method of measuring morphological diversity, as a surrogate for species diversity/richness will undoubtedly reduce the quality of the data obtained, the method has a number of key advantages in certain applications. However, the method now requires further refinement to determine if nonsponge specialists can be quickly and easily trained to identify the different morphological forms. The examination of further localities would also help give confidence that the relationship between sponge morphological diversity, species diversity and richness applies more generally than those habitats and localities included in this paper. Once more habitats are examined
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a more rigorous method can be developed. Further development of a morphological approach to biological survey techniques may in the future be extended to the community (rather than group) level. It may be possible to include many groups, which show high plasticity in their morphology (e.g. corals see Chappell 1980), but not others (such as anemones) whose morphology is relatively consistent between different species. Although not a replacement for detailed examination of sponge communities, the current method in estimating sponge species diversity should prove a useful tool in situations when specialist skills are unavailable or limited. Although the quality of information obtained by methods such those described in the present study is reduced, they should not be underestimated in their usefulness in the future of nature conservation. Acknowledgements: The authors wish to thank all the scientific staff, logistic staff and volunteer research assistants of the Frontier Mozambique Marine Research Programme, the Frontier Madagascar Marine Research Programme and Jo and Finn Barnes. The Mozambique programme was a collaborative venture between the Society for Environmental Exploration (SEE) in the UK and the Ministépara a Coordenação de Acção Ambiental (MICOA) in Mozambique, it was part funded by the Darwin Initiative for the Survival of Species (Department of the Environment, UK). The current Madagascar programme is a collaborative venture between the Society for Environmental Exploration (SEE) in the UK and the Institut Halieutique et des Sciences Marines (Universite de Toliara). We also wish to thank Damon StanwellSmith for making the visits to Mozambique and Madagascar possible. Finally we are very grateful to Claire Shaw for her help in the production of this manuscript.
References Ayling A (1983) Growth and regeneration rates in thinly encrusting demospongiae from temperate waters. Biological Bulletin 165: 343–252. Barnes DKA (1999) High diversity of tropical intertidal zone sponges in temperature, salinity and current extremes. African Journal of Ecology 37: 424–434. Boury-Esnault N & Rützler K (1997) Thesaurus of sponge morphology. Smithsonian Contributions to Zoology: 596. Bell JJ (2001) The ecology of sponges at Lough Hyne Marine Nature Reserve, Co. Cork, Ireland. Submitted Ph.D. thesis, University College Cork. Bell JJ, Barnes DKA & Turner JR (2002) The importance of micro and macro morphological variation in adaptation of a sublittoral demosponge to current extremes. Marine Biology 140: 75–81. Bell JJ & Barnes DKA (2001) Sponge morphological diversity: A qualitative predictor of Species Diversity? Aquatic conservation: Marine and Freshwater Ecosystems 11: 109–121.
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Bell JJ & Barnes DKA (2000a) The influence of bathymetry and flow regime on the morphology of sublittoral sponge populations at Lough Hyne MNR. Journal of the Marine Biological Association of the United Kingdom 80: 707–718. Bell JJ & Barnes DKA (2000b) A sponge diversity within a ‘marine island’. Hydrobiologia 440: 55–64. Chappell J (1980) Coral morphology, diversity and reef growth. Nature 286: 249–252. Corriero G, Liaci LS, Ruggiero D & Pansini M (2000) The sponge community of a semi-submerged Mediterranean cave. Marine Ecology-Pubblicazioni Della Staione Zoologica Di Napolii 21: 85–96. Diaz MC, Alvarez B & Laughlin RA (1990) The sponge fauna on a fringing coral reef in Venezuela, II: community structure. In: New perspectives in sponge biology (ed K Rützler): 367–375. Smithsonian Institute Press, Washington DC. Kaandorp JA (1999) Morphological analysis of growth forms of branching marine sessile organisms along environmental gradients. Marine Biology 134: 295–306. Krebs CJ (1989) Ecological Methodology. Harper Collins, London.
Maldonado M & Young CM (1996) Bathymetric patterns of sponge distribution on the Bahamian slope. Deep Sea Research 43: 897–915. Manconi R & Pronzato R (1991) Life cycle of Spongilla lacustris (Porifera,Spongillidae): a cue for environment-dependent phenotype. Hydrobiologia 220: 155–160. Maughan BC & Barnes DKA (2000) Epilithic boulder communities of Lough Hyne, Ireland: the influences of water movement and sediment. The Journal of the Marine Biological Association of the United Kingdom 80: 767–776. Palumbi SR (1984) Tactics of acclimation: morphological changes of sponges in an unpredictable environment. Science 225: 1478–1480. Palumbi SR (1986) How body plans limit acclimation: responses of a demosponge to wave force. Ecology 67: 208–214. Sarà M (1970) Competition and cooperation in sponge populations. Symposium of the Zoological Society of London 25: 273–284. Received 27. 04. 01 Accepted 13. 09. 01
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J. Nat. Conserv. 10, 41–50 (2002) © Urban & Fischer Verlag
Nature Conservation
http://www.urbanfischer.de/journals/jnc
Modelling sponge species diversity using a morphological predictor: a tropical test of a temperate model James J. Bell1,* & David K. A. Barnes1,2 1
Department of Zoology and Animal Ecology, University College Cork, Ireland; present address: School of Applied Sciences, University of Glamorgan, Pontypridd, Rhondda Cynon Taff, Wales, CF37 1DL, U.K.; e-mail: [email protected] 2 FRONTIER, The Society for Environmental Exploration, London, U.K.; present address: British Antarctic Society, High Cross, Madingley Road, Cambridge CB3 0ET, U.K.
Abstract The contribution of sponges to marine surveys is often underestimated due to problems of identification, synonymous species and limited numbers of specialists in the field. Bell & Barnes (2001) illustrated how sponge morphological diversity (diversity of body forms) might be used as a predictor of sponge species diversity and richness. This study investigated these relationships at six tropical West Indian Ocean localities in a number of habitat types. These habitats included tropical coral reefs, soft substratum (seagrass, mangrove and sand), caves and boulders. Sampling was undertaken at three depth zones in coral reef habitats only (intertidal, 10–15 m and 20–25 m), with the other habitats sampled in less than 10 m of water. Species diversity and richness were significantly correlated (P < 0.05) with morphological diversity at all localities and depths in coral reef and soft substratum habitats. However, no significant correlation was found between these variables in cave or boulder habitats. The slope of the linear regression found between morphological diversity and species diversity did not significantly differ between coral reef, soft substratum and temperate reef (data taken from Bell & Barnes 2001) habitats. Similarly coral reefs showed the same relationship between morphological diversity and species richness as temperate reefs, however the relationship between morphological diversity and species richness was significantly different at both habitats compared with soft substratum environments. Sponge morphological diversity therefore may be more useful as a predictor of sponge species diversity, rather than species richness, as the former relationship is common between more habitats than the latter. Key words: Morphology, sponge, diversity, richness, coral reefs, temperate reefs.
Introduction Sponges are ubiquitous to virtually all marine habitats and are often very abundant and speciose and as such are a potentially important component of biodiversity. For these reasons sponges should form a significant component of the benthos in biological surveys of marine areas. Conservation and survey groups such as Marine Nature Conservation Review, Coral Cay Conservation, Greenforce, Operation Wallacea, Reef Watch, Sea Search, The Society of Environmental Exploration
(Frontier) and the World Wildlife Conservation Trust often conduct surveys in areas of high sponge diversity such as the Caribbean (Diaz et al. 1990), East Africa (e.g. Barnes 1999) or the east Pacific (van Soest 1985). However, even though sponges are often abundant, rich (number of species) and diverse (probability of predicting the next species found), their contribution to the survey can be considerably underestimated for the following reasons. 1) Sponges can be very difficult to identify
*corresponding author
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J. J. Bell & D. K. A. Barnes
especially in remote areas where little work has been previously undertaken 2) the time taken for sampling sponge communities and associated laboratory work can be considerable 3) problems are often encountered obtaining permits (especially in tropical areas) to export specimens to sponge taxonomists 4) under some circumstances taxonomic uncertainty of a species identity may cause problems in its identification. Although sponge morphology is highly varied, their forms have been classified into a number of distinct types (Boury-Esnault & Rützler 1997). Some of these morphotypes are straight-forward such as encrusting, tubular or funnel shaped others require reference to illustrations such as papillate, ficiform or repent. In a method proposed by Bell & Barnes (2001), morphological diversity was used as an alternative measure of sponge species diversity. Morphological diversity is considerably easier to measure because it requires less time to collect data and the information can be recorded in situ. An obvious disadvantage to this method is the quality of the information obtained. The basis of using morphological diversity as a predictor of species diversity is due to the variation in the phenotypic expression of body shape observed in sponges (e.g. Manconi & Pronzato 1991; Bell & Barnes 2000a) and the importance of environmental parameters in controlling such morphological variation (Bell & Barnes 2000a). These same environmental parameters contribute to the variation in sponge species distributions (Bell & Barnes 2000b). With the apparent link between these two aspects of sponge ecology, a relationship between sponge morphology and species diversity may have seemed intuitive.
The relationship between sponge morphological diversity and species diversity has only been described for a temperate region of very high sponge species diversity (Bell & Barnes 2001). The investigation of such a relationship may be far more useful in tropical areas where the problems of collection of species diversity information (see above) are more difficult. This study tests the validity and general applicability of the formula to predict sponge species diversity by measuring morphological diversity proposed by Bell & Barnes (2001) in different regions, habitats and depth zones. It is important to determine if different relationships exist in different habitats, geographical regions and depth zones, so surveyors know if different relationships should be used in different environments, or whether such a method of estimating sponge species richness and diversity is suitable only in specific habitats. The aim of this study was to examine patterns of sponge morphological diversity, species diversity and richness across six tropical regions in four different habitat types (coral reefs, soft substratum, boulders and caves) and three different depth zones (intertidal, 5–10m, 15–25m), with the objective to determine 1) whether there were linear relationships between morphological and species diversity within different habitats, depth zones and localities, 2) whether these linear relationships (see objective 1) were significantly different between habitats, localities and depth zones and 3) whether tropical relationships between sponge morphological diversity and sponge diversity differed from that of the temperate environment from which it was proposed.
Figure 1. Position of the West Indian Ocean study sites. The sites are Watamu-Malindi (Kenya), Quirimba Island (Northern Mozambique), Anakao region (south-west Madagascar) and Inhaca Island (Southern Mozambique).
Modelling sponge species diversity
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intertidal and subtidal depths. Only the coral reef habitat was sampled at three depth zones as other habitats were either not present at all depths or (in the case of sand) unoccupied by sponges. The morphotypes by which sponges were characterised in this study conform to the categories in the thesaurus of sponge morphology (Boury-Esnault & Rützler 1997) and are illustrated in Figure 2. Analysis Patterns of morphological and species diversity were described with the Shannon and Wiener information function H’ = –∑ pi Ln pi (Krebs 1989, after Maldonado & Young 1996). Lines of best fit were superimposed onto plots of morphological diversity vs species diversity and species richness using standard regression procedures. Where necessary (in order to obtain straight line relationships) data was Log10 transformed. General Linear Model ANalysis Of VAriance (GLM ANOVA) was used to compare the slopes of linear relationships (regression) between species diversity, richness (Log 10) and morphological diversity. This method compares the slope of each relationship to an average slope fitted to all the data to be compared.
Results Figure 2. The gross morphological categories into which sponge species were classified from tropical and temperate (Bell & Barnes 2001) localities. * denotes those found in tropical localities and + indicates those found in temperate sites.
Methods Study areas Sponges were sampled at four west Indian Ocean sites and two Atlantic sites between 1996 and 2000. The Atlantic sites were the San Blas Islands at 9ºN, near the Smithsonian Tropical Research Institute, and at similar latitude in the Cape Verde Islands, off West Africa. The location of the major sampling areas in the West Indian Ocean is shown in Figure 1. At each site the number and identity of sponges was recorded in randomly placed quadrats of one square metre area. The number of each morphological type was recorded in the same quadrats. Sampling procedures were carried out in each of coral reef, soft substratum (sand and seagrass meadow), cave and boulder habitats in
Do relationships exist between sponge morphological, species diversity and species richness? Linear relationships (Pearsons correlation > 0.25, P < 0.05 in each case) were evident between morphological diversity vs species diversity and morphological diversity vs species richness at all geographical locations. These relationships were also apparent with the small data sets of each of the four main geographical study sites. The relationships are of simple straightline nature in the case of morphological diversity versus (vs) species diversity (Figure 3). Does the diversity of relationship differ with environmental conditions of site (geographical locality)? The relationships found between morphological diversity and species diversity at different depth zones within coral reef habitats (intertidal, 5–10 m and 15–25 m) showed no significant differences between the slopes or intercepts of these relationships at different geographical locations, or between depth zones (GLM ANOVA F-ratio < 1.23, P < 0.05). There was, therefore, one consistent relationship between species di-
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Figure 3. The relationship between sponge morphological diversity, species diversity and richness in coral reef habitats at six tropical localities (averaged over depth). Linear regression and Pearsons correlations (r2) are shown for data from all localities combined as General Linear Model Analysis of Variance showed no significant differences between the relationships at each locality (F-ratio < 1.23, P < 0.05).
versity and morphological diversity at coral reefs, irrespective of depth and site (within those sampled). As such, combining data from all coral reef depth zones and geographic localities is statistically valid (Figure 3). An overall significant positive linear relationship (with data from all depth zones and geographic regions) was found between sponge morphological diversity and species diversity on coral reefs (F-ratio = 41.50, P < 0.001). The slope of the regression was significantly different to zero (t-value 6.44, P < 0.001), thus species diversity was significantly dependent on morphological diversity (Figure 3). Data was only available at depths < 10 m for other habitats (mangroves hardly encroach the subtidal and sea-grasses are restricted to shallow water). A signifi-
cant positive linear relationship (Pearsons correlation = 0.53, P < 0.05) was found between morphological diversity and species diversity in soft substratum habitats (Figure 4). No significant difference was observed between the slopes or the intercepts of these relationships at the different geographic regions (F-ratio < 0.57, P > 0.646). Data from all localities was then combined for soft substratum habitats (Figure 4). A significant positive linear relationship was found between morphological diversity and species diversity when all the data from soft substratum habitats at all localities was combined (F-ratio = 3.23, P = 0.01). However, there was no correlation (Pearsons correlation < 0.24, P < 0.05) between sponge morphological diversity and species diversity at any geographic locality, or with all
Modelling sponge species diversity
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Figure 4. The relationships between sponge morphological diversity, species diversity and richness in soft sediment habitats at six tropical localities (averaged over depth). Linear regression and Pearsons correlations (r2) are shown for data from all localities combined as General Linear Model Analysis of Variance showed no significant differences between the relationships at each locality (F-ratio < 0.57, P > 0.646).
data (from all localities) combined in boulder or cave habitats. No significant differences between localities or depth zones were found between morphological diversity vs species diversity relationships in coral reef or soft substratum habitats. The data from all habitats, localities and depths was therefore plotted (Figure 5) and a GLM ANOVA was used to compare the slopes of the relationships between habitat types. As no significant relationship was found for cave and boulder habitats, only data from coral reefs and soft substratum was used in the comparison. No significant differences (F-ratio = 0.38, P = 0.539) were observed between either the slopes or the intercepts of the relationships between sponge species diversity and morphological diversity between
coral reef and soft substratum habitats (all localities or depths). However, the minimum and maximum species and morphological diversity was lower for soft substratum than for coral reef habitats (Figure 5). Do morphological diversity-species richness relationships differ with environmental conditions of site? Morphological diversity was significantly correlated (Pearsons correlation > 0.50, P < 0.05) with species richness once transformed logarithmically (Log 10 for all habitats and depths). The only habitats with no apparent relationship were, as with morphological diversity vs species diversity, those characterised by caves
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J. J. Bell & D. K. A. Barnes
Figure 5. A plot combining sponge morphological diversity, species diversity and species richness for three tropical habitats at all localities and depths (coral reefs only) combined. A single regression line was fitted to soft substratum and coral reef species diversity data as these habitats showed no significant difference between the relationships. However, significant differences were found for species richness data and individual regressions were fitted. Data from cave and boulder habitats were not included in the calculation of average regression lines as no linear relationships were found.
and boulder habitats (graphs not shown, Pearsons correlation > 0.13, P > 0.05) and no further analysis was performed on this data. No significant differences were observed between the slopes of the relationships at each depth zone or locality in coral reef habitats so all data was combined (F-ratio < 0.45, P < 0.001). A significant linear regression (F-ratio = 23.84, P < 0.001) was fitted to all the data from all depth zones and localities from coral reef habitats, with the calculation of a slope significantly different to zero (t-value = 4.88, P < 0.001). On coral reefs, the same linear relationship between sponge morphological diversity and sponge species richness was found, irrespective of locality or depth zone. A significant linear relationship was found between morphological diversity and sponge species richness
(Log 10) at each locality (Pearsons correlation > 0.41, P < 0.001) in soft substratum habitats. GLM ANOVA showed no significant difference (F = 0.44, P = 0.727) between the slopes of these relationships for soft substratum habitats at the different localities, so all the data was combined (Figure 4). A linear regression was fitted to this combined relationship, the slope of which was significantly different to zero (t-value = 2.55, P = 0.02). Sponge species richness (Log 10) was significantly linearly correlated with sponge morphological diversity, irrespective of locality. Boulder and cave habitats showed no linear relationships at any localities between morphological diversity species richness (Log 10). A plot was constructed of sponge morphological diversity and species richness (Log 10) for all habitats combined (except boulder and cave habitats) as there
Modelling sponge species diversity
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Figure 6. A comparison between the relationship of sponge morphological diversity, species diversity (a) and richness (b) at tropical and temperate habitats (taken from Bell & Barnes 2001). A combined regression was calculated for coral reef, soft substratum and temperate reef habitats for species diversity data only as species richness relationships were only the same for coral and temperate reef data. Cave and boulder habitats were not included in the calculation of average regression lines as no linear relationships were found.
was no significant difference observed between depth zones (coral reefs only) or localities for each habitat type (Figure 5). GLM ANOVA was then used to compare the slopes of the relationship between coral reef and soft substratum habitats. These habitats could not be compared with boulder and cave habitats, as no linear relationships were found between species richness and morphological diversity for this habitat type. A significant difference was observed between the slopes of the relationships of species richness and morphological diversity in coral reef and soft substratum habitats (F-ratio = 9.51, P = 0.003). A significantly greater increase in species richness per unit increase in morphological diversity was observed for coral reef than for soft substratum habitats. Also any given value of morphological diversity in soft substratum environ-
ments corresponded to a lower sponge species richness than for coral reef habitats. Do relationships differ between temperate and tropical environments? Relationships between sponge morphological diversity and species diversity, morphological diversity and species richness have previously been established at a temperate site (Lough Hyne, south-west Ireland, see Bell & Barnes 2001). To compare temperate and tropical relationships the current data was combined with the temperate data from the literature (Figure 6a). Thus, relationships were compared between tropical coral reef and soft substratum habitats vs temperate cliffs (all depths and localities combined for each habi-
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J. J. Bell & D. K. A. Barnes
tat). No significant differences (GLM ANOVA) were found between the slopes of the relationships between morphological and species diversity at these three habitat types (F-ratio = 1.25, P = 0.29). A unit increase in morphological diversity corresponded to the same increase in sponge species diversity, irrespective of habitat. A linear regression fitted to all the data showed morphological diversity to be significantly dependent on species diversity with a slope significantly different to zero (t-value = 9.73, P < 0.001). GLM ANOVA of the relationship between species richness (Log 10) and morphological diversity, in contrast, showed a significant difference between habitats (Figure 6b). No significant difference was found between coral reef and temperate reef habitats (t-value 0.09, P = 0.928), but both these habitats had significantly different slopes to soft substratum habitats (tvalue = 4.05, P < 0.001). A unit increase in morphological diversity resulted in a greater increase in species richness in coral and temperate reefs than for soft substratum habitats. Morphological diversity and species richness values obtained for soft substratum habitats were lower than for those from coral and temperate reef habitats. Linear regression equations were generated for the relationship between sponge species diversity and morphological diversity for all habitats combined (Figure 6a), but separately for hard (coral and temperate reef) and soft substratum habitats from the relationship between species richness (Log 10) and morphological diversity (Figure 6b).
Discussion Using the diversity of easily identifiable sponge morphotypes (Figure 2), the diversity and richness of sponge species can be predicted in coral reef and tropical soft substratum habitats. The relationship between morphological diversity and species diversity was the same as that found for a temperate assemblage (Bell & Barnes 2001), irrespective of locality or depth. This suggests that sponge morphological diversity may then be used as an effective universal surrogate for predicting sponge species diversity, with the exception of boulder and cave habitats. It seems likely that this relationship between sponge morphological diversity and species diversity is a characteristic feature of most sponge communities. However, although morphological diversity was also linearly correlated with sponge species richness (Log 10), significantly different relationships existed between soft and hard (coral and temperate reef habitats) substratum habitats, even though there was no difference between localities (within each habitat).
The differences between these habitats resulted from relatively low sponge richness, but with those species found exhibiting many different body forms. The difference between soft substratum and hard substratum habitats may have been intuitive, considering the nature of these environments. The relationship between sponge morphological diversity, richness and species diversity was not found in cave or boulder habitats. This may have been expected as species inhabiting these types of environment commonly exhibit encrusting forms because of the nature of the habitat. Boulders, which are in disturbed areas are often only colonised by encrusting forms, as these can regenerate much faster than other types in this destructive environment (Ayling 1983). In more sheltered environments, sponges typically inhabit the undersides of boulders, probably to prevent sediment settlement on their surfaces (Maughan & Barnes 2000). The nature of the two-dimensional habitat associated with the undersides of boulders obviously restricts sponge morphology to encrusting or low profile forms (Bell 2001). Cave habitats often experience strong surge that may also prevent the growth of species that exhibit non-encrusting or massive morphological types (Sarà 1970; Corriero et al. 2000). There are important implications from transforming species richness onto a logarithmic scale. It means that the measurement of morphological diversity is less effective as a predictor of sponge richness at higher species richness values than it is of species diversity (for which the relationship is linear). Therefore, morphological diversity is likely to be a better predictor of sponge species diversity than of species richness in communities with high numbers of sponge species. This also means the ability of the current method as a monitoring tool remains speculative. Although this method may be extremely useful in identifying areas of high, low, or moderate sponge species diversity and richness, it may require a considerable amount of change in any particular community before this method detects it. It will also be insensitive to the loss or gain of rare species from, or to, a community. However, these statements are also true for any measurement of species diversity. There are many uses for this method of estimating sponge species diversity and richness from the measurement of morphological diversity. 1) This method will be useful in identifying areas of relatively high sponge species diversity and richness that may be important for the purposes of designation, management and conservation of marine areas. 2) It could also be used as an initial survey tool for prioritising and directing more detailed surveys.
Modelling sponge species diversity
3) It seems likely that relatively inexperienced users can use a method, such as that proposed here, in a range of habitats for quickly estimating sponge species diversity and richness. It may be critical for organisations using non-specialists with limited time and resources, as it will allow quick and easy collection of data. 4) As a monitoring tool, the method needs to be developed further and then tested. One such way this may be possible is to increase the number of morphological categories/groups used. In most cases, sponge taxonomists describe a single gross morphological category for each sponge species (such as those used in this study). It is this limited number of morphological categories that leads in part to the logarithmic relationship found between morphological diversity and species richness. However, many studies have illustrated how variable sponge morphology can be under different environmental situations within a single gross morphological group or species (Bell et al. 2002; Kanndorp 1999; Manconi & Pronzato 1991; Palumbi 1984, 1986). For example, Bell et al. (2002) found Cliona celata (Grant) to show at least five different morphologies under different environmental conditions, although its morphology is generally classified as massive (see Figure 2). Although this may appear contradictory, sponges generally only show one morphological type in a single habitat (e.g. Manconi & Pronzato 1991). This means using more morphological groups will not over-estimate the contribution of a single sponge species in any particular habitat (compared to other habitats, localities etc.). However, for different species that may be classified within the same gross morphological group (under the current method) smaller scale morphological differences may be present. Increasing the number of morphological groups for these gross morphological categories, would allow differentiation between a greater number of species. A consequence of increasing the number of morphological groups is the greater amount of time required in the field, but this should still be possible by non-sponge specialists. Although the proposed method of measuring morphological diversity, as a surrogate for species diversity/richness will undoubtedly reduce the quality of the data obtained, the method has a number of key advantages in certain applications. However, the method now requires further refinement to determine if nonsponge specialists can be quickly and easily trained to identify the different morphological forms. The examination of further localities would also help give confidence that the relationship between sponge morphological diversity, species diversity and richness applies more generally than those habitats and localities included in this paper. Once more habitats are examined
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a more rigorous method can be developed. Further development of a morphological approach to biological survey techniques may in the future be extended to the community (rather than group) level. It may be possible to include many groups, which show high plasticity in their morphology (e.g. corals see Chappell 1980), but not others (such as anemones) whose morphology is relatively consistent between different species. Although not a replacement for detailed examination of sponge communities, the current method in estimating sponge species diversity should prove a useful tool in situations when specialist skills are unavailable or limited. Although the quality of information obtained by methods such those described in the present study is reduced, they should not be underestimated in their usefulness in the future of nature conservation. Acknowledgements: The authors wish to thank all the scientific staff, logistic staff and volunteer research assistants of the Frontier Mozambique Marine Research Programme, the Frontier Madagascar Marine Research Programme and Jo and Finn Barnes. The Mozambique programme was a collaborative venture between the Society for Environmental Exploration (SEE) in the UK and the Ministépara a Coordenação de Acção Ambiental (MICOA) in Mozambique, it was part funded by the Darwin Initiative for the Survival of Species (Department of the Environment, UK). The current Madagascar programme is a collaborative venture between the Society for Environmental Exploration (SEE) in the UK and the Institut Halieutique et des Sciences Marines (Universite de Toliara). We also wish to thank Damon StanwellSmith for making the visits to Mozambique and Madagascar possible. Finally we are very grateful to Claire Shaw for her help in the production of this manuscript.
References Ayling A (1983) Growth and regeneration rates in thinly encrusting demospongiae from temperate waters. Biological Bulletin 165: 343–252. Barnes DKA (1999) High diversity of tropical intertidal zone sponges in temperature, salinity and current extremes. African Journal of Ecology 37: 424–434. Boury-Esnault N & Rützler K (1997) Thesaurus of sponge morphology. Smithsonian Contributions to Zoology: 596. Bell JJ (2001) The ecology of sponges at Lough Hyne Marine Nature Reserve, Co. Cork, Ireland. Submitted Ph.D. thesis, University College Cork. Bell JJ, Barnes DKA & Turner JR (2002) The importance of micro and macro morphological variation in adaptation of a sublittoral demosponge to current extremes. Marine Biology 140: 75–81. Bell JJ & Barnes DKA (2001) Sponge morphological diversity: A qualitative predictor of Species Diversity? Aquatic conservation: Marine and Freshwater Ecosystems 11: 109–121.
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Bell JJ & Barnes DKA (2000a) The influence of bathymetry and flow regime on the morphology of sublittoral sponge populations at Lough Hyne MNR. Journal of the Marine Biological Association of the United Kingdom 80: 707–718. Bell JJ & Barnes DKA (2000b) A sponge diversity within a ‘marine island’. Hydrobiologia 440: 55–64. Chappell J (1980) Coral morphology, diversity and reef growth. Nature 286: 249–252. Corriero G, Liaci LS, Ruggiero D & Pansini M (2000) The sponge community of a semi-submerged Mediterranean cave. Marine Ecology-Pubblicazioni Della Staione Zoologica Di Napolii 21: 85–96. Diaz MC, Alvarez B & Laughlin RA (1990) The sponge fauna on a fringing coral reef in Venezuela, II: community structure. In: New perspectives in sponge biology (ed K Rützler): 367–375. Smithsonian Institute Press, Washington DC. Kaandorp JA (1999) Morphological analysis of growth forms of branching marine sessile organisms along environmental gradients. Marine Biology 134: 295–306. Krebs CJ (1989) Ecological Methodology. Harper Collins, London.
Maldonado M & Young CM (1996) Bathymetric patterns of sponge distribution on the Bahamian slope. Deep Sea Research 43: 897–915. Manconi R & Pronzato R (1991) Life cycle of Spongilla lacustris (Porifera,Spongillidae): a cue for environment-dependent phenotype. Hydrobiologia 220: 155–160. Maughan BC & Barnes DKA (2000) Epilithic boulder communities of Lough Hyne, Ireland: the influences of water movement and sediment. The Journal of the Marine Biological Association of the United Kingdom 80: 767–776. Palumbi SR (1984) Tactics of acclimation: morphological changes of sponges in an unpredictable environment. Science 225: 1478–1480. Palumbi SR (1986) How body plans limit acclimation: responses of a demosponge to wave force. Ecology 67: 208–214. Sarà M (1970) Competition and cooperation in sponge populations. Symposium of the Zoological Society of London 25: 273–284. Received 27. 04. 01 Accepted 13. 09. 01
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