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Marine and Freshwater Research, 2011, 62, 491–501

Spatial variability and human disturbance of sponge assemblages associated with mangrove roots in the southern Caribbean Edlin Guerra-CastroA,B,E, Paula Young B, Adriana Pe´rez-Va´zquez B, Sophie CarteronC and Adriana AlvizuD A

Centro de Ecologıá, Instituto Venezolano de Investigaciones Cientı´ficas, POB 21827, Caracas 1020-A, Venezuela. B Escuela de Ciencias Aplicadas del Mar, Universidad de Oriente, Nućleo Nueva Esparta, Boca de Rıó, Isla de Margarita, Venezuela. C Centre d’Oceánologie de Marseille, Universite´ de la Mediterraneé, 13007 Marseille, France. D Departamento de Biologıá de Organismos, Universidad Simoń Bolı´var, Caracas 1080-A, Venezuela. E Corresponding author. Email: [email protected]

Abstract. Assemblages growing on Caribbean red-mangrove roots are very diverse and characteristically dominated by sponges. The scales of spatial variation of this fauna in the Caribbean region have not been hierarchically quantified, although such information is necessary to understand the relative importance of ecological processes and possible responses to anthropogenic disturbances. We used a hierarchical nested design to identify patterns of spatial variability at different scales, namely among roots, sites, localities and regions within the southern Caribbean. Simultaneously, the sampling considered the relative distance from sources of human disturbance to test the null hypothesis of no difference in sponge diversity among localities as a result of anthropogenic stress. Significant spatial variability in species composition was detected at all spatial scales, especially at the among-root scale. However, there were no differences associated with distance from human disturbance. These results indicate high regional and local b diversity, and also suggest that results from small-scale experiments cannot be scaled up to the entire community. Further, spatial analysis of sponge assemblages is not enough to detect deleterious effects of human disturbances on mangrove areas. Additional keywords: beta diversity, management, spatial scales, taxonomic distinctness, variance components.

Introduction In the Caribbean Sea, prop roots of the coastal mangrove Rhizophora mangle L. are fouled by numerous species of invertebrates and algae (Ru¨tzler 1969; Lacerda et al. 2002). More than 500 species of invertebrates and algae have been reported as being part of this community (Farnsworth and Ellison 1996; Lo´pez et al. 2009; Rocha et al. 2010). Among these organisms, sponges are the richest taxonomic group with more than 170 species (Dıáz and Ru¨tzler 2009), and so this group has been targeted in the studies dealing with this type of coastal system (Dıáz et al. 2004). Mangrove roots with this diversity exist mainly in the Caribbean Sea, where small tidal amplitude permits subtidal fouling of stilt roots (Farnsworth and Ellison 1996), usually on the leeward side of islands where depths exceed 50 cm. This characteristic makes Caribbean mangroves an important contributor to global marine biodiversity (Ellison and Farnsworth 2001; Lacerda et al. 2002). A common finding in quantitative studies dealing with mangrove-root fouling assemblages is the great variability in Ó CSIRO 2011

´ lvarez composition of species among neighbourhood roots (A 1989; Farnsworth and Ellison 1996; Hunting et al. 2008). Likewise, these studies have shown that differences in assemblage composition can be found among localities (i.e. intermediate spatial scales). The patterns found have led to general discussion of whether the observed spatial composition of species is driven by larval supply and dispersal limitations (Bingham 1992; Farnsworth and Ellison 1996) or by habitat conditions such as tidal amplitude, suspended sediment, salinity ´ lvarez 1989; Ru¨tzler 1995; Wulff 2000; Dıáz and predation (A et al. 2004). All of these studies, however, describe communities at a local level, and some of them have inferred characteristics of the natural history of this system using local-scale data (see Sutherland 1980; Bingham 1992; Farnsworth and Ellison 1996). Inference from the local to the broad scale in ecological studies has been criticised (Ricklefs 2008), mainly because local coexistence cannot provide insights into the origin, maintenance and regulation of assemblages with high levels of b diversity. This component of species diversity can be measured as the 10.1071/MF10267

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Marine and Freshwater Research

variability in species composition among sampling units for a given area at a given spatial scale (Anderson et al. 2010). The understanding of spatial patterns of variation, in turn, depends on the scale at which the researchers decide to observe them (Underwood and Chapman 1996). More importantly, natural phenomena and ecological processes operate differently in space and time (Allen and Starr 1982). Therefore, identifying the scales of variation in assemblage composition allows us to understand the relative importance of processes by which b diversity is created and maintained (Underwood et al. 2000). Simultaneously, understanding spatial scales at which variation is larger may help in the design of sampling strategies to detect environmental impact (Fraschetti et al. 2001) and provide the necessary information for the determination of conservation units and the design of marine protected areas (Benedetti-Cecchi et al. 2003). For mangrove-root assemblages, Farnsworth and Ellison (1996) proposed that these assemblages could be considered patchy communities that are readily identifiable at several natural scales, from roots at the finest scale, clustered with neighbouring roots at a particular site in a mangrove cay (intermediate scale), to groups of cays or localities in a region (broad scale). However, variation of species composition on these spatial scales has not been hierarchically quantified. Mangrove areas attract a wide range of economic activities, including e.g. resorts, fishing and marinas. These activities are common in Caribbean mangroves (Ellison and Farnsworth 1996), and the effects of some of them (e.g. by oil contamination, increased suspended sediment) on root assemblages have been documented (Garrity and Levings 1993; Dıáz and Ru¨tzler 2009). This situation calls for management that effectively protects mangrove-root epibiosis. In this context, Dıáz and Ru¨tzler (2009) suggested that richness and abundance of sponges could be used as indicators of mangrove epibenthic community health. In other marine systems, the presence/ absence of certain sponge species has been recommended as an indicator of environmental stress (Carballo et al. 1996). Hence, we predict that only resistant species will persist under marginal conditions, whereas species intolerant to pollution will mainly occur in near-pristine environments. Therefore, assessing spatial variability in composition of sponge assemblages near and far from human disturbance tests the hypothesis that sponges may be used as bioindicators of environmental quality in mangrove areas. To identify relevant scales of variation in species composition and explore the potential use of sponge assemblages to indicate stress in mangrove ecosystems, we assessed spatial patterns of sponge diversity on R. mangle roots by applying a hierarchically nested design to (1) quantify the spatial variability of sponge assemblage at four spatial scales (from metres to hundreds of kilometres) and (2) test the null hypothesis that localities near human disturbances will not differ in richness, species composition and taxonomic diversity from localities far from these activities. Materials and methods Study sites Fringe mangrove forests from the following three national parks along the southern Caribbean were evaluated: (1) Bastimentos

E. Guerra-Castro et al.

National Park, Panama´ (BNP), (2) Morrocoy National Park (MNP), western Venezuela and (3) La Restinga National Park (LRNP), eastern Venezuela (Fig. 1). These forests are dominated by R. mangle, which grows on the shore of the mainland, sand cays or even in shallow waters where it can form ‘mangrove cays’. These national parks are in areas with different oceanographic and meteorological characteristics (Spalding et al. 2007); however, they have relatively local environmental heterogeneity (Table 1). BNP is an archipelago composed of numerous mangrove keys, shallow coral reefs and seagrass beds in an area of 600 km2, where their principal lagoon, Bahıá Almirante, receives sea water directly from the Caribbean Sea and freshwater from several mainland creeks (D’Croz et al. 2005). Likewise, MNP stretches over 320 km2 and comprises a system of interconnected lagoons, where seagrass beds and mangrove cays are predominant, opening to the sea through several channels, being severely affected by freshwater inflow during seasonal rainfall (Bone et al. 2001). LRNP, in contrast, is a coastal hypersaline lagoon of 30 km2 connected with the sea by one channel and without any freshwater runoff (Go´mez Gaspar 1991). A common aspect within these parks is the variety of human activities that could be disturbing the environmental quality in some specific localities (Table 1). Sampling and experimental design The survey design combined the hierarchy of spatial scales and whether localities were near to or far from human activities, carried out twice considering two national parks for each survey. The first study was carried out in BNP and LRNP (September– October 2007), and the second in MNP and LRNP (April–May 2008). In both cases, separation between parks was over hundreds of kilometres. Within each park, three locations near different human disturbances (,20 m) and three locations far from these activities (.500 m) were randomly selected to test the hypothesis of human influence (proximal or distant). The proximal condition was defined by the presence of towns with grey-water effluents, marinas and/or fishing wharfs (Table 1). Separation among locations, independently of their condition, was hundreds of metres. Hanging roots (those that are not touching the bottom) were considered as the sampling unit (Farnsworth and Ellison 1996). The sample size selected was 14 roots per locality. This was calculated using analyses of statistical power (Faul et al. 2007) to detect 15% differences in sponge richness per roots among localities (data from a pilot study in BNP). Within each location, 14 roots were evaluated in two groups of seven roots, separated by 15–20 m. This division was made to represent an extra small spatial scale (sites within localities). Overall, 336 roots were sampled in both surveys (7 roots per site, 14 per location, 84 per park and 168 per survey) and the spatial hierarchy in both was roots within sites, sites within localities and localities (proximal and distant to human disturbance) within Parks (see Accessory Publication to this paper, available on the web). Each root was sampled non-destructively and sponges were photographed and identified in situ to the lowest taxonomic level possible (mainly species and genera). When identification was not possible in the field, reference specimens were collected for further identification in the laboratory. The hypotheses

Spatial analyses of sponge assemblages

82°


72°

493

62° 0

250

500 km

3 0

5

0.5

1 km

6

N 18°

18°

4

Caribbean Sea

3 2 2

3

1

1

10°

10°

82°

72°

62°

1

0 1 2 3 4 km

2 4 5

1 3 2

1 2

4 3

5

6 0

1

2 km

Fig. 1. Mangrove systems evaluated in the southern Caribbean Sea. 1, Bastimentos National Park; 2, Morrocoy National Park; 3, La Restinga National Park. The localities within each of the three parks are shown. Numbers within circles indicate localities close to human disturbances.

Table 1. Names of localities within each national park Geographical coordinates and some environmental variables (annual mean and range) are included, as well as the type of human disturbances that is close or away from the mangrove roots sampled Park

Locality ID

Local name

Latitude

Longitude

Salinity

Depth (m)

Human activity

9.358 9.338 9.348 9.348 9.338 9.288

82.268 82.248 82.258 82.208 82.188 82.178

33 (32–36) 33 (32–36) 33 (32–36) 33 (32–36) 33 (32–36) 33 (32–36)

0.8–1.3 1.5–2.0 0.8–1.2 0.7–1.0 1.0–1.2 1.5–2.0

E1.2 km away from Saigoń Marina, Town sewages Town sewages, local airport Town sewages E2.1 km away from Bastimento Town E9 km from Bastimento Town

BNP 1 2 3 4 5 6

STRI Saigoń Coloń Town Bastimento Town Bastimento mangroves Solarte South

1 2 3 4 5 6

Entrada a la Laguna Puente de Boca del Rio Embarcadero El Indio Frente a la boya La Tortuga Embarcadero La Restinga

10.978 10.978 10.988 10.988 11.008 11.008

64.178 64.168 64.168 64.168 64.168 64.158

37 (36–39) 38 (36–39) 39 (36–40) 39 (36–40) 43 (39–45) 41 (39–42)

1.2–1.5 1.5–2.0 1.8–2.3 2.0–2.8 1.8–2.3 0.9–1.2

E700 m away from El Puente 30 fishing ships regularly anchored Dock with 96 tourist boats E300 m away from embarcadero El Indio E1.6 km away from embarcadero La Restinga Dock with 96 tourist boats

1 2 3 4 5 6

Embarcadero Agua Salobre Tumba Cuatro Canõ a Boca Grande Embarcadero Morrocoy Las Luisas Puente de Tucacas

10.858 10.838 10.848 10.858 10.848 10.798

68.248 68.268 68.278 68.298 68.298 68.318

36 (30–42) 37 (30–42) 37 (22–42) 36 (22–42) 36 (22–42) 33 (3–40)

0.9–1.4 1.5–1.7 1.3–1.6 0.6–1.8 0.6–0.8 0.4–0.6

Dock with 40 tourist boats and town sewages E2.1 km away from two neighbourhood marinas E2.4 km away from Embarcadero Morrocoy Marina, fuel station, dock with 24 tourist boats E1.6 km away from Embarcadero Morrocoy Marina, town sewages

LRNP

MNP

494


concerned species composition, so all information gathered in the field was of presence/absence type and the data were organised into a species-by-samples matrix. The lengths of both main and adventitious roots were measured. Data analyses Univariate (species richness) and multivariate (species composition) data were analysed using a mixed four-factor design and PERMANOVA based on Euclidean distances and Bray–Curtis dissimilarities, respectively (Anderson 2001). Given the indeterminacy of Bray–Curtis values between two samples with no species, a dummy species was added to all roots (zero-adjusted Bray–Curtis) (Clarke et al. 2006). The four factors considered were as follows: Parks (two levels; random), Condition (two levels, proximal and distant; fixed), Location (three levels; random and nested within the interaction of Parks and Condition) and Site (two levels; random and nested within Location). Length of each root (including adventitious roots) was used as a covariable to estimate the amount of variation explained by ‘substrate area’. The statistical significance of each term was obtained by using a random subset of 9999 permutations of residuals under a reduced model. Given the ability of PERMANOVA to record differences when heterogeneity in multivariate dispersion exists, a multivariate dispersion test (PERMDISP) (Anderson 2006) was applied to those significant sources of variation. The importance of each spatial scale was quantified with estimates of variance components (VC) and then were squareroot transformed to obtain values interpretable in the original scale of measurement (e.g. Bray–Curtis dissimilarities) (Anderson et al. 2005). Because two PERMANOVA analyses were carried out (one per survey), estimates of variability from each were averaged using the following equation: VCw ¼

½ðn1 1ÞVC1 þ ½ðn2 1ÞVC2 ; n1 þ n2 1

where the subscript w represents the weighted mean and n is the number of replicates for the respective factor at each survey (Hunter and Schmidt 2004). Non-metric multidimensional scaling (nMDS) ordinations (Clarke 1993) were calculated to illustrate spatial similarities in species composition among roots. However, to show differences among localities, distances among centroids were represented using principal coordinate ordinations (PCO) (Anderson et al. 2008). This method reveals the relative sizes and directions of effects in complex experimental designs without plotting the samples. Finally, species responsible for significant differences among parks were identified with SIMPER analysis (Clarke 1993). Disturbed communities support more closely related sibling species than do stable communities (Warwick and Clarke 2001). Therefore, to assess the potential use of sponges as indicators of environmental quality, taxonomic distinctness tests (TAXDTEST) (Warwick and Clarke 1995) were applied for localities within each park, predicting that localities proximal to human disturbances will have average taxonomic distinctness values (AvTD) smaller than those expected by chance.


This test was carried out using 5000 simulations of AvTD values calculated from random subsets of species reported at each park. The validity of each species name and their taxonomic affiliation were checked in the World Porifera Data Base (van Soest et al. 2008). The following five taxonomic levels were considered: species, genus, family, order and class. All statistical analyses were carried out with the PRIMER v6 and PERMANOVA add-on programs (PRIMER-E Ltd, Plymouth, UK). Results Scales of spatial variation Species richness Fifty-seven sponge species (see Accessory Publication to this paper) were identified from the 336 roots evaluated. The species found with greatest frequency were Mycale microsigmatosa (127 roots), Tedania ignis (125), Haliclona manglaris (104), Halichondria magniconulosa (87), Haliclona curacaoensis (67), Mycale magnirhaphidifera (57) and Dysidea etheria (54). All other species appeared between 1 and 39 times. Number of species per root varied among sites within localities and among localities within parks (Fig. 2, Table 2). Length of root was found to have a positive effect on the number of species. Nonetheless, parks have apparently no significant effect on richness by root. The highest variations in richness was at the levels of roots and locations (Table 3). Composition of sponge assemblages There was significant variability in the composition of the assemblage at all spatial scales (Table 4). Residuals (differences observed between neighbouring roots) were the spatial scale with greatest variability, followed by the variation between localities and parks, with sites and root length the terms explaining the least variation (Table 3). In general, neighbourhood roots share ,70% of their species; roots from different localities within a park may be up to 21% dissimilar in their composition, and roots from different parks could be 20% dissimilar as well. National parks within each survey showed the same multivariate dispersion (PERMDISP, P . 0.05 in both surveys) and, therefore, statistical significances at this scale seen in the PERMANOVA is likely to be due to real differences in ‘average’ species composition rather than dispersion effects (Anderson 2001, 2006). Dissimilarity among the parks and the high variability among roots is seen in Fig. 3, even when stress in both figures is .0.20. Also, differences in multivariate dispersion (PERMDISP, P , 0.05) were found among localities, suggesting that some localities could differ in their dispersion and not necessarily in their average species composition. Even so, clear difference in centroids of localities could be seen for both surveys, mainly discernible along Axis 2 (Fig. 4). SIMPER analysis for Survey 1 indicated that the average Bray–Curtis similarity between roots at BNP was 26.0, whereas for LRNP it was 20.6. Most frequent species at BNP were Haliclona manglaris, Tedania ignis and Mycale microsigmatosa (Table 5). Most common species at LRNP were M. microsigmatosa, Halichondria magniconulosa and Haliclona curacaoensis. Both national parks were differentiated mainly



495

(a)

Number of species per root

12

12

BNP

10

10

8

8

6

6

4

4

2

2

0

LRNP

0 2*

3*

4*

1

5

6

2*

3*

6*

1

4

5

3*

6*

1

4

5

(b) 12

12

MNP

10

10

8

8

6

6

4

4

2

2

0

0 1*

4*

6*

2

3

5

LRNP

2* Localities

Fig. 2. Number of sponge species (mean s.d.) per root from the (a) first and (b) second surveys. Sites were pooled within localities only for figure presentation. Numbers 1–6 refer to localities within each park in Fig. 1. Asterisk indicates localities close to human disturbances.

by the frequency of H. manglaris, M. microsigmatosa, T. ignis, H. magniconulosa, H. curacaoensis, Haliclona implexiformis and Clathria schoenus. In the second survey, average Bray– Curtis similarity for MNP was 21.6 and 19.6 for LRNP. Species with greatest percentage contribution in similarity at MNP were T. ignis, M. microsigmatosa and Haliclona caerulea (Table 5). Most common species in LRNP were H. magniconulosa, M. microsigmatosa and Mycale magnirhaphidifera. Differentiation between these parks was determined by T. ignis, M. microsigmatosa, M. magnirhaphidifera, H. caerulea, H. manglaris and H. curacaoensis. Usefulness of mangrove sponges as indicators of human disturbances Richness and composition of sponge assemblages In all cases, we found no evidence to reject the null hypothesis of equality in richness and species composition among localities near to v. far from human disturbances (PERMANOVA, P . 0.05). In multivariate analysis, possible effects of small power can be discounted by visualising the

patterns of distance among centroids of proximal and distant localities in Fig. 4, and in the pseudo F-values of #1 for the Condition factor and its interaction with the Park factor. Similarly, in univariate analysis, the F-values were very low (,1) for the Condition term. In both surveys, including univariate and multivariate analysis, these sources of variation were excluded for the model because their P-values were .0.25 (Underwood 1997). Nonetheless, an interesting pattern emerges from univariate and multivariate analysis in data from BNP, where, although not statistically significant, proximal localities have fewer species and different sponge assemblages than do distant localities (Figs 2a, 4a). Taxonomic analysis In BNP, 36 species were identified, of which 12 belong to the Haplosclerida and 14 are in Poecilosclerida. Ten species in the first order belong to the family Chalinidae, whereas in the second order, six belong to the family Mycalidae and four to the Microcionidae family. From the six localities evaluated, only two (one near and one far from human disturbances) showed low

496



Table 2. PERMANOVA based on Euclidean distances calculated on the number of species per root, with length of root as a covariate Source of variation Survey 1 Root length Parks Condition Parks Condition Localities (Park Co) Sites (Loc (Park Co)) Residuals Total Survey 2 Root length Parks Condition Parks Condition Localities (Park Co) Sites (Loc (Park Co)) Residuals Total

d.f.

SS

F

P (perm) Source of variation

1 1 1 1 8 12 143 167

147.70 16.08 73.62 92.75 287.10 129.07 507.97 1254.30

1 1 1 1 8 12 143 167

73.96 0.95 0.16 9.79 157.73 40.65 327.28 610.52

12.65 0.44 0.86 2.59 3.29 3.03

0.000 0.524 0.499 0.145 0.032 0.001

13.24 4.93E–02 1.70E–02 0.49 5.83 1.48

0.000 0.829 0.914 0.495 0.004 0.134

Table 3. Estimates of univariate and multivariate variation at each significant term after exclusion of terms with a P-value .0.25 Values are also expressed with square-root transformation (restoring original units) and as a proportion of the total variability Source of variation Richness of species Root length Parks Localities Sites Roots Totals Composition of assemblage Root length Parks Localities Sites Roots Totals

Table 4. PERMANOVA based on the Bray]Curtis (presence/absence) dissimilarities of multivariate data in factorial hierarchical spatial design, with length of root as a covariate

Component of variation

Square root

Proportion

0.60 0.73 1.59 0.40 2.70 6.01

0.78 0.85 1.26 0.64 1.64

0.10 0.12 0.26 0.07 0.45

34.66 410.06 457.15 121.58 1037.86 2061.30

5.89 20.25 21.38 11.03 32.22

0.02 0.20 0.22 0.06 0.50

AvTD in relation to that expected (Fig. 5a) (TAXDTEST analysis). In LRNP (Survey 1), 33 species were identified, with most belonging to the orders Haplosclerida (11 species, 8 in Chalinidae), Poecilosclerida (6 species, 5 in Mycalidae), Halichondrida (5 species) and Dictyoceratida (5 species). Neither locality in LRNP showed reductions in AvTD, compared with that expected. During the second survey, MNP samples contained 27 species, of which the orders Poecilosclerida and Haplosclerida included seven species each, with four in Halichondrida. Families Chalinidae and Mycalidae included five and four species, respectively. In LRNP, 25 species were detected, with most belonging to the orders Haplosclerida (12 species), Poecilosclerida (6 species) and Halichondrida (4 species). Again, the most common families were Chalinidae

d.f.

Survey 1 Root length 1 Parks 1 Condition 1 Parks Condition 1 Localities (Park Co) 8 Sites (Loc (Park Co)) 12 Residuals 143 Total 167 Survey 2 Root length 1 Parks 1 Condition 1 Parks Condition 1 Localities (Park Co) 8 Sites (Loc (Park Co)) 12 Residuals 143 Total 167

SS

F

P (perm)

10 020 2.91 56 724 5.52 9373 1.02 9807 0.97 81 221 3.15 38 163 2.79 1.63Eþ05 3.69Eþ05

0.006 0.009 0.501 0.459 0.000 0.000

7617 2.69 30 838 2.96 272 8.70E–02 3168 0.31 81 936 6.54 18 833 1.42 1.58Eþ05 3.01Eþ05

0.023 0.063 0.945 0.887 0.000 0.025

(10 species) and Mycalidae (5 species). Neither locality in either park showed a reduction in AvTD from that expected by chance. (Fig. 5b). Discussion Scales of spatial variation The surveys revealed a clear pattern in species composition; the major source of variation came from differences observed among neighbourhood roots. Added to this variability, national parks and localities represented an important source of variation in species composition, with smaller differences among sites within the same locality. Also, species richness, as a measure of diversity, revealed differences between localities and sites, highlighting the fact that larger roots host more species. These differences showed that processes at intermediate and small spatial scales (e.g. local disturbances and environmental variation, and limited dispersal of species) have a strong effect on the establishment of sponges on the roots, and the area of the substrate positively affects richness. However, the expected number of species per root is independent from the process of large spatial scales, although the parks assessed in the present study are environmentally distinct and have very different areas. Therefore, richness, as estimator of diversity, does not allow us to make inferences about the differences in the patterns of diversity existing at large spatial scales. The present results demonstrated that measures of species richness alone is not adequate to capture the regional diversity of sponge assemblages growing on R. mangle roots. Spatial patterns in mangrove-encrusting species have been discussed previously (Farnsworth and Ellison 1996; Hunting et al. 2008); however, the only study focussed on quantitative evaluation of assemblages at different spatial scales is that of Farnsworth and Ellison (1996). These authors defined the following five spatial scales: (1) front and backs of root


(a)

PCO2 (21% of total variation)

(a)


Stress: 0.24

Stress: 0.23 Fig. 3. Non-metric multidimensional scaling (nMDS) ordinations of Bray–Curtis similarities among roots observed during the (a) first and (b) second surveys. Filled triangles correspond to roots from BNP, open triangles to LRNP (a). Filled triangles correspond to MNP, open triangles to LRNP (b).

(1-cm scales), (2) roots close and extending away from the peat bank (0.5 m), (3) along linear transects parallel to shore (1–50 m), (4) on leeward and windward shores of cays (0.5 km) and (5) between cays (1–10 km). In fact, only Levels 3 and 5 are real (nested) spatial scales; the others are orthogonal fixed factors that occur over a specific spatial scale (Underwood and Chapman 1996), on which other processes could be acting. No study has indicated quantitatively the hierarchy of spatial scales at which species composition changes, necessary to allow us to identify those processes that better explain the high b diversity of this particular Caribbean system. The hierarchy of spatial variability was as follows: among roots . localities E national parks . sites. The present results revealed a diversity of ecological processes that operate hierarchically on the species composition, especially at the scale 1–7 m (among roots). High variability at small spatial scales is common in very diverse marine ecosystems, such as in fauna inhabiting kelp holdfasts (Anderson et al. 2005), rocky coasts (Benedetti-Cecchi 2001; Cruz-Mota 2007), subtidal hard

40 LRNP

LRNP LRNP

20

LRNP

0

BNP

BNP BNP BNP BNP

LRNP BNP

⫺20 ⫺40

LRNP

0 ⫺20 20 PCO1 (44.4% of total variation)

40

(b) 40 PCO2 (24.3% of total variation)

(b)

497

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LRNP LRNP LRNP MNP

MNP

0

⫺20 ⫺40

MNP MNP MNP

MNP LRNP LRNP

0 ⫺20 20 PCO1 (44.1% of total variation)

40

Fig. 4. Principal coordinate ordinations (PCO) of Bray–Curtis centroids of localities observed in the (a) first and (b) second surveys. Filled triangles correspond to locations near human disturbances, open triangles to locations distant from human disturbance.

surfaces (Glasby 1998; Fraschetti et al. 2001) and sponges in seagrass meadows (Barnes et al. 2006). For benthic communities presenting high variability on spatial scales of a few metres, difference in life histories, larval availability, behaviour of larvae, survival of recruits, time of colonisation and successional changes have been proposed as key processes (Lewin 1986; Underwood and Fairweather 1989). These, combined with the substrate spatiotemporal variability, could be responsible for the high variability among neighbouring roots. For example, settlement and recruitment of sponges (i.e. T. ignis) on mangrove roots is influenced by content of tannins (Hunting et al. 2010), and tannin production changes with root development and fouling (Gill and Tomlinson 1977; Hunting et al. 2010). This relationship predicts a positive feedback in recruitment that may be reflected in the number and identity of sponge species that inhabit each root (Hunting et al. 2010). Production of tannins and larval behaviour are small-scale processes (vary among roots and among sponge species); therefore, their effect in the levels of b diversity among roots should be measured and considered.

498



Table 5. Contribution of dominant species to the similarities among roots within each national park Species

Contribution (%)

Cumulative contribution

35.78 17.36 10.48 8.89 5.65 4.95 3.22 3.06 2.81

35.78 53.14 63.62 72.51 78.16 83.12 86.34 89.40 92.20

34.63 19.48 15.12 12.65 7.76 5.08

34.63 54.11 69.23 81.88 89.64 94.72

Survey 1 – BNP Haliclona manglaris Tedania ignis Mycale microsigmatosa Haliclona implexiformis Haliclona piscaderaensis Clathria schoenus Dysidea etheria Chalinula molitba Lissodendoryx isodictyalis Survey 2 – MNP Tedania ignis Mycale microsigmatosa Haliclona caerulea Haliclona manglaris Dysidea etheria Chelonaplysilla erecta

Species at LRNP

Contribution (%)

Cumulative contribution

Mycale microsigmatosa Halichondria magniconulosa Haliclona curacaoensis Haliclona tubifera Tedania ignis Mycale magnirhaphidifera Scopalina ruetzleri Scopalina sp.

21.84 20.77 18.33 9.79 7.41 6.74 3.31 2.51

21.84 42.61 60.94 70.73 78.14 84.88 88.19 90.70

Halichondria magniconulosa Mycale microsigmatosa Mycale magnirhaphidifera Haliclona curacaoensis Tedania ignis Scopalina sp.

34.09 19.30 13.66 9.70 7.85 6.93

34.09 53.39 67.05 76.75 84.60 91.53

(a) 100

BNP

90

90

80

80 3

70

5

1 4

2

AvTD

AvTD

100

6

LRNP

6

5

2 4

70

60

60

50

50

1

3

40

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Number of species Fig. 5. Funnel plot for average taxonomic distinctness (AvTD) at each lagoon system from the (a) first and (b) second surveys. Filled circles correspond to locations near human disturbance, open circles correspond to locations far from human disturbance. Funnels represent the simulated 95% confidence intervals for the expected AvTD values at each park.


Besides the high variability among roots, important differences among national parks and among localities were established. This is an indicator of high local and regional b diversity (Legendre et al. 2005; Anderson et al. 2010). Two main models have been proposed to explain high b diversity among communities, namely limited dispersal history (Neutral theory) and biological/environmental control (Niche theory) (Liebold 1995; Gaston and Chown 2005). For mangrove-root assemblages, these processes have been proposed in several papers, with some degree of controversy among them. Several works have highlighted environmental heterogeneity as the structural force that maintains the difference between localities (e.g. Inclań Rivadeneyra 1989; Pawlik et al. 2007; Dıáz and Ru¨tzler 2009). Nevertheless, Bingham (1992) and Farnsworth and Ellison (1996) suggested that larval supply and dispersion could explain differences observed between localities, denying environmental control as a force that maintains variability among local assemblages. However, Hunting et al. (2008) suggested that if dispersal limitations were the dominant force in maintaining b diversity, species should be homogenously distributed after multiple generations; however, this does not happen. Alternatively, Wulff (2000, 2005) and Waddell and Pawlik (2000) proposed that predation could be important in determining differences in sponge fauna among mangrove cays, especially when predators are absent in some areas. Some species of sea stars, angel fishes and parrot fishes feed on mangrove sponges (Wulff 2005; Nagelkerken et al. 2008); however, the hypothesis of control by predation was rejected by Sutherland ´ lvarez (1989) and Ellison and Farnsworth (1992), (1980), A using manipulative experiments. In any case, high levels of b diversity among localities, and among national parks, suggested that medium scale-processes cannot be generalised or scaled up to higher scales. All these models could be acting simultaneously and dispersal limitation could explain differences in some places under particular circumstances at a specific spatial scale, as environmental constraints or biological interactions could in others. The only way to ascertain which models are actually taking place is by carrying experiments over wider spatial scales. With some exceptions (e.g. H. magniconulosa in LRNP, C. schoenus in BNP), numerous species were shared among the parks but their frequency differed. The dominant species in BNP were not the same as in LRNP and the most important species in LRNP were not the same as in MNP. These results suggest that relative abundance of each species conforms to some mechanism, associated with each national park, which controls the success of each species in reproducing, dispersing or settling. At this spatial scale, atmospheric and oceanographic processes (such as e.g. hurricanes, storms, upwelling events and freshwater inflows) have been proposed as factors that control the presence, abundance and distribution of sponges in mangrove habitats (Nagelkerken et al. 2008). As a consequence, it is predictable that the dominance and relative abundance of species at each park are associated with the regional seasonality (Dıáz and Ru¨tzler 2009). BNP and MNP are strongly affected by the rainy season and freshwater from creeks, whereas LRNP is considerably more saline without freshwater inflow. For example, mass mortality of mangrove-root fouling assemblages was detected in LRNP in 1988, as a consequence of the


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Gilbert and Joan hurricanes (Orihuela et al. 1991). Species such as Haliclona viridis and H. permollis (unaccepted synonymies of Amphimedon chloros and H. (Reniera) cinerea; Van Soest et al. 2008) were the only ones that survived and dominated for some months after the events (Orihuela et al. 1991). In BNP, Dıáz and Ru¨tzler (2009) found that sponge abundances vary in time, and that the direction of these changes was correlated with local abiotic factors. Likewise, Bingham and Young (1995) stated that the dynamics of mangrove-fouling community is strongly dependent on stochastic events, and that these changes occur in very short time scales. Sutherland (1980) proposed that mangrove-fouling assemblages are very stable, and once species have colonised a given root, are able to live for many years and resist the invasion of most other larvae. All these processes are of medium or wider spatial scales and cannot explain the levels of b diversity found among neighbouring roots. In the light of these results, it seems that spatial small-scale processes (e.g. larval behaviour, tannins concentration) are more important than ‘dispersal limitations’ and ‘environmental control’ in preserving b diversity in mangrove sponges at the southern Caribbean. Usefulness of mangrove sponges as indicators of human disturbances Surprisingly, we did not find patterns to support the statement that richness of sponges, the composition of assemblages or their taxonomic diversity can be used as indicators of environmental quality in mangrove areas. Spatial variability in sponge diversity is so high that potential effects of human disturbances could be masked by the natural spatial variability. It is important to emphasise that our analysis involved varying impacts, mainly sewage, marinas and boat docks associated with tourism, treated as replicates because we were interested in detecting patterns of sponge diversity under intensive human activities. Sponge diversity was low in some strongly affected areas (e.g. Tucacas in MNP, Saigoń in BNP, Embarcadero La Restinga in LRNP), and also in some healthy ones (e.g. Tumba cuatro in MNP, La Tortuga in LRNP and Bastimento mangroves in BNP). The opposite was also observed; highly affected areas can support very diverse sponge assemblages (e.g. Embarcadero Morrocoy in MNP, El Indio in LRNP). Consequently, spatial evaluations of sponge assemblages do not suffice to infer environmental health. However, an important factor that could be crucial to detect the response of sponge diversity to human disturbances is the temporal changes in local assemblages or populations. Dıáz and Ru¨tzler (2009) found that abundances of sponges decrease with increasing suspended sediment and nutrients (both anthropogenic). However, this pattern could be detected only if data were obtained before the perturbation occurs. Mangrove sponges have been suggested as indicators of health for mangrove epibiont communities (Dıáz et al. 2004; Dıáz and Ru¨tzler 2009); however, caution is advised with such criteria, in the light of our data, because it could lead to false negative outcomes in future assessments of environmental impact (Underwood and Chapman 2003). We consider that the effect of specific coastal developments on mangrove-root fouling assemblages, as was proposed, would be better approached with experimental designs of the Beyond BACI

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type (sampling different time scales before and after a proposed development that might cause impact) using multivariate data (Underwood 1991; Clarke 1993), especially because of the high spatial and temporal variability found in this system and the insensitivity of univariate estimators (i.e. richness) in detecting difference owing to impacts. In conclusion, the present results suggest that high variability in sponge composition among roots is found regionally, and that regional and local communities are not equivalent. This implies that future research programs on mangrove sponges or the entire fouling assemblage must consider different spatial scales if generalisation is the main goal. The same conclusion applies for management; if protection of biodiversity of mangrove-root fouling assemblages is the aim, only regional efforts can effectively reach that objective (each park, and location within, contribute uniquely to the biodiversity of Caribbean mangroves). Furthermore, temporal evaluations, at different scales, are necessary to test some of the hypotheses discussed here, particularly those related to effects of human disturbances. Acknowledgements Part of data in this study was collected during the course Taxonomy and Ecology of Caribbean Sponges (2007, STRI, Bocas del Toro, Panama). E.G.C. thanks CEA-IVic. and FONACIT for partially covering their participation in the 2007 STRI sponge course. We thank STRI for financing this course. Special thanks go to R. Parkinson, C. Carmona-Sua´rez, O. Insam and D. Romero for English revision of early drafts. E.G.C. is grateful to J. J. Cruz-Motta, K. R. Clarke and M. J. Anderson for their suggestions that helped improve this article substantially. This gratitude is extended to A. Boulton, M. C. Dıáz and two anonymous reviewers. All the authors express their deepest thanks to M. C. Dıáz for her invaluable support and stimulus in the study of mangrove sponges.

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Manuscript received 28 October 2010, accepted 11 March 2011

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