Multiscale patterns of sponge diversity on Western Atlantic coral reefs: insights from the Southern Gulf of Mexico and the Mexican Caribbean

Abstract

Introduction:

Sponges are increasingly dominant components of coral reefs in the Tropical Western Atlantic, yet patterns of their diversity across spatial scales remain poorly quantified.

Methods:

We applied a hierarchical sampling design across 13 reefs and five spatial scales —ecoregions (thousands of kilometers), subregions (hundreds of kilometers), coral reefs (tens of kilometers), localities (hundreds of meters), and quadrats (meters)— to assess the relative influence of ecological processes structuring sponge assemblages. Surveys were conducted across 13 coral reefs in the Mexican Caribbean (MC) and the Southern Gulf of Mexico (SGM), including the neritic zones of Campeche/Yucatán (NCY) and Veracruz Neritic zone (VN). In total, 624 quadrats were examined across 60 localities within the 13 reefs.

Results:

Most of the explained variation in assemblage structure occurred at the local (22%) and reef (19%) scales, while regional effects were weak. Gamma diversity declined along a geographic gradient from the MC to the VN, with observed richness ranging from 95 to 63 species and extrapolated estimates reaching 122 and 73, respectively. Sample completeness profiles showed high coverage across subregions (≥ 0.94 for q = 1 and 2), confirming the robustness of interregional comparisons. Beta diversity among subregions was high and consistently dominated by species turnover (BJTU range: 0.64–0.73), indicating that environmental filtering, rather than nested species loss or limited connectivity, drives compositional differences.

Discussion:

Assemblages in the MC exhibited higher richness but lower sponge abundance, likely shaped by oligotrophic conditions and less-impacted predator communities. In contrast, NCY reefs showed moderate richness and high species turnover, reflecting strong environmental heterogeneity, while VN reefs exhibited low richness but high abundance, likely driven by high sedimentation and reduced top-down control. Our findings underscore the central role of small-scale processes in shaping sponge diversity and caution against assuming regional nestedness in reef communities.

1 Introduction

Over the past decades, coral reef structural complexity has declined in response to multiple stressors, including rising sea temperatures, pollution, and ocean acidification (Molina-Hernández et al., 2020). In the Tropical Western Atlantic, these factors have led to unprecedented erosion rates, reshaped reef architecture through increased coral mortality, and driven shifts in community composition toward less structurally complex assemblages, typically dominated by algae and sponges (Bell et al., 2013; Villamizar et al., 2014). Despite these changes, major coral reef monitoring programs in the region — such as the US National Coral Reef Monitoring Program (NCRMP) and the Atlantic and Gulf Rapid Reef Assessment (AGRRA) — still lack taxonomic resolution and precision in quantifying sponge identity and abundance, unlike the detailed data available for corals (Diaz and Rútzler, 2001; Pawlik and McMurray, 2020). Consequently, these protocols are insufficient for detecting regional patterns in sponge diversity.

Sponges play a key role in maintaining coral reef structure by preserving the three-dimensional complexity of the seascape (Wulff and Buss, 1979; Carballo and Bell, 2017; Bell et al., 2018). They also support biodiversity by hosting a rich community of external and endosymbiotic organisms (Wulff, 2016). Among these, several sponge-associated species, such as Spheciospongia vesparium, Callyspongia (Cladochalina) aculeata, Agelas tubulata, and other Caribbean species, contribute significantly to the reef soundscape, an acoustic environment used by many reef larvae as a settlement cue, thereby influencing biodiversity processes (Butler et al., 2016; Pérez-Botello and Simões, 2021; Pérez-Botello et al., 2023). In addition, sponges provide essential ecosystem services that affect both benthic and pelagic dynamics. These include cycling of dissolved organic matter via the “sponge loop” (de Goeij et al., 2013), primary production mediated by microbial symbionts (Wulff, 2006; Bell and Carballo, 2008), and the resuspension of carbonate sediments (Rützler, 2002; Bell and Carballo, 2008). The ongoing debate about the positive or negative impacts of sponges on reef-building corals—bioerosion by boring sponges, overgrowth, and increasing sponge dominance that can shift communities from coral−dominated to sponge−dominated states and reduce reef complexity—underscores the urgent need for a deeper understanding of reef sponge diversity (Wulff, 2017; Pawlik and McMurray, 2020). Achieving this requires data with high taxonomic resolution and robust estimates of spatial and temporal variation.

Describing species diversity patterns through a multiscale approach enables the identification of the relative contributions of the key ecological processes that sustain biodiversity. One effective way to achieve this is by partitioning data variability through hierarchical sampling designs, where spatial scales are treated as factors that reflect the operative range of ecological processes (Underwood and Chapman, 1998). Although it is well established that ecological processes act across multiple spatial scales, their interactions are often underestimated. In coral reef ecosystems, several local-scale processes typically operating at spatial extents of centimeters to a few meters, such as competition, food availability, predation, wave exposure, depth, and light intensity, have been linked to patterns of sponge diversity (Williams et al., 2015; Berman and Bell, 2016; Wulff, 2017). Likewise, large-scale environmental drivers such as oceanographic currents and geological processes are also thought to shape sponge assemblages (Van Soest et al., 2012). However, the relative contribution of these processes across scales remains largely unquantified.

In the Tropical Western Atlantic, few studies have analyzed patterns of sponge diversity variability across spatial scales, from local (a few meters) to regional (hundreds of kilometers), to assess the biological and environmental processes driving these patterns. Guerra-Castro et al. (2011) evaluated sponge diversity associated with mangrove roots in the southern Caribbean and found the highest beta diversity at the scale of neighboring roots (1–5 meters) and at the regional scale. These findings emphasize the potential importance of supply-side processes in colonization and succession (Guerra-Castro and Cruz-Motta, 2018), as well as the influence of regional environmental filters such as storm exposure, primary productivity, sedimentation rates, and freshwater inflows. Similarly, Williams et al. (2015) assessed the diversity patterns of massive sponges, scleractinians (reef−building corals), and gorgonians across four spatial scales: transects (meters), sites (kilometers), areas (tens of kilometers), and ecoregions (hundreds of kilometers). They reported that over 70% of the variability in massive sponge composition occurred at the smallest spatial scales. The authors suggest that differences in wave exposure and reef rugosity could explain this pattern. Likewise, Villamizar et al. (2014) documented significant spatial heterogeneity in sponge assemblages across four geomorphological zones of the Belize Barrier Reef. Despite comparable species richness among zones, notable differences in composition and dominant species reflected the influence of habitat structure and depth. Bell and Carballo (2008) further demonstrated that while species–area relationships may remain consistent across ocean basins, the structure of local sponge assemblages is shaped by environmental factors such as hydrodynamics and sedimentation, which vary regionally and modulate species coexistence. Despite focusing on sponge species with different life histories, these studies consistently highlight high species turnover at small spatial scales.

The coral reefs along the Mexican Atlantic margin offer a unique natural setting to investigate the ecological processes that sustain sponge diversity across contrasting marine environments of the Western Atlantic. This transitional zone encompasses reef systems distributed between two distinct marine basins, the Caribbean Sea and the Gulf of Mexico, which differ markedly in their oceanographic dynamics, geological history, and biophysical conditions (Roberts et al., 1992). Reef geomorphologies are also highly diverse across this area, including bank, fringing, barrier, and atoll-like formations, each with characteristic dimensions and depth profiles (Jordán-Dahlgren and Rodríguez-Martínez, 2003; Blanchon et al., 2022). Oceanographically, the Caribbean Current enters through the Yucatán Strait and gives rise to the Loop Current in the Gulf of Mexico, which generates cyclonic and anticyclonic eddies that can significantly influence larval dispersal and ecological connectivity (Alvera-Azcárate et al., 2009). Additionally, the region supports high sponge diversity, with up to 150 species recorded in the Caribbean coast of Mexico (Carballo et al., 2014) and 161 species in the Southern Gulf of Mexico (Ugalde et al., 2021).

For other reef-associated taxa, such as gorgonians and fishes, biogeographic differences between the Caribbean and the Gulf of Mexico have been interpreted through hypotheses concerning ecological connectivity and environmental gradients. Jordán-Dahlgren (2002) proposed that limited connectivity between reef systems contributes to a declining gradient of gorgonian diversity from the Caribbean into the Gulf of Mexico. Similarly, Nuñez-Lara et al. (2005) emphasized the role of local environmental gradients in shaping fish community composition across reefs within the Mexican Caribbean. More broadly, quantitative biogeographic analyses of shorefishes across the Greater Caribbean have demonstrated that this region is structured into distinct faunal provinces, reflecting major environmental discontinuities between the Gulf and Caribbean basins (e.g., temperature regimes, habitat availability, and shelf morphology) (Robertson and Cramer, 2014). These findings underscore that regional environmental differences can produce consistent divergence in community structure, suggesting similar mechanisms may influence spatial patterns of sponge diversity in the region.

Moreover, reef ecosystems in both the Gulf of Mexico and Caribbean regions are increasingly affected by a combination of anthropogenic and natural stressors, including eutrophication, oil industry accidents, illegal fishing, mass coral bleaching events, and the decomposition of pelagic Sargassum (Rodríguez-Martínez et al., 2019; Gil-Agudelo et al., 2020; Doherty et al., 2025). New coral diseases have further exacerbated reef degradation (Cróquer et al., 2021; Estrada-Saldívar et al., 2021). Along with global warming and ocean acidification, these stressors contribute to a rapidly deteriorating ecological scenario for the region’s coral reefs. In this context, addressing the knowledge gap regarding the spatial patterns of sponge diversity and distribution becomes urgent, not only to highlight the ecological relevance of sponges but also to identify the key processes that sustain those patterns.

This study addresses the following questions: (1) How do sponge assemblages differ among coral reefs along the Mexican Atlantic coast in terms of species composition, richness, and relative dominance, reflecting environmental and biogeographic gradients? (2) Are the sponge assemblages of the Southern Gulf of Mexico coral reefs a subset of the broader sponge diversity found in the Western Caribbean? (3) At which spatial scale is the greatest variation in sponge diversity observed across these ecoregions? By answering these questions, we aim to disentangle the relative contributions of macroecological and local processes in sustaining current patterns of sponge diversity on coral reefs.

2 Materials and methods

2.1 Study area

Thirteen coral reef sites were sampled (Figure 1) in two ecoregions sensuSpalding et al. (2007): The Western Caribbean and the Southern Gulf of Mexico. Although the Western Caribbean Ecoregion encompasses coral reef systems in Mexico, Belize, and Honduras, our study focuses exclusively on coral reefs in the Mexican sector. Accordingly, we refer to this subset as the Mexican Caribbean (from now on MC) throughout the manuscript for clarity and consistency. The reefs in the MC are primarily characterized as coastal reef systems that parallel the shoreline and extend along the Yucatán Peninsula. These reefs typically exhibit two main geomorphological zones: a protected back-reef zone and a fore-reef zone, which are separated by a reef crest where wave breaking occurs. These natural breakwater structures are generally confined to shallow waters (<10 m depth) and develop on or adjacent to a rocky substratum terrace covered by coral-dominated benthic assemblages (Medina-Valmaseda et al., 2022).

Figure 1

We also included as a subregion of the Southern Gulf of Mexico the inner and outer neritic zone of the Campeche/Yucatan coast (from now on NCY) and Veracruz neritic zone (from now on VN) sensuWilkinson et al. (2009) (Figure 1). Reefs in the NCY region occur on an extensive carbonate platform with minimal influence from terrestrial runoff. This region hosts approximately 20 reef formations, most of which are platform-type reefs, some of which emerge above sea level, forming islands. The majority of these reefs are located offshore, at distances ranging from 20 to 130 km from the coastline (Jordán-Dahlgren and Rodríguez-Martínez, 2003). The region also includes the largest reef system in the Gulf of Mexico, Alacranes Reef, which covers an area of approximately 650 km². Alacranes Reef, also a platform-type reef, is distinctive among reefs of the Campeche Bank due to its atoll-like configuration and the presence of a deep lagoon (Tunnell et al., 2007).

On the other hand, the reefs within the VN subregion, located off the coast of Veracruz, are primarily platform and fringing types, characterized by distinct windward and leeward zones separated by a reef crest (Jordán-Dahlgren and Rodríguez-Martínez, 2003). These reefs are directly influenced by discharges from major rivers carrying high sediment loads, particularly during the rainy season (June–September). This hydrodynamic regime is structured by the reef crest, which acts as a natural breakwater where waves dissipate. Such reef crest formations are typically confined to shallow waters (<10 m depth) and develop on or adjacent to a rocky substratum terrace overlain by coral-dominated benthic communities (Medina-Valmaseda et al., 2022).

The Caribbean Current System influences the Western Caribbean and Southern Gulf of Mexico regions; when the current passes through the Yucatan Channel into the Gulf of Mexico, it becomes known as the “Loop Current” (Oey et al., 2005; Enriquez et al., 2010). The Loop Current flows clockwise into the gulf with a northward penetration until the West Florida Shelf (Appendini et al., 2013), generating anticyclonic eddies (clockwise rotating), which travel westward and eventually dissipate near the continental shelf. These eddies, together with continental water discharges and seasonal wind stress, affect the entire Gulf of Mexico water transport, especially over the shelves (Ruiz-Castillo et al., 2016). In general, both MC and SGM are affected by wind waves generated by two meteorological systems: the anticyclonic systems that generate cold fronts known locally as “Nortes” and affect mainly the Mexican coast in the Gulf of Mexico, and tropical cyclones, which are low-pressure systems (including tropical depressions, tropical storms, and hurricanes), most of them approaching the area from the Caribbean Sea (Appendini et al., 2013).

2.2 Sampling design and hypothesis

We implemented a hierarchical sampling design comprising five spatial scales: (1) ecoregions, (2) subregions, (3) coral reefs, (4) localities within reefs, and (5) quadrats within localities. This multiscale structure was specifically designed to quantify the fraction of variation in sponge diversity attributable to each spatial scale, under the assumption that ecological or environmental processes operating at each scale generate distinct and independent sources of variability. Identifying the spatial scales that represent the greatest share of total variation enables us to infer which ecological processes are most influential in shaping regional patterns of sponge diversity. This rationale underpins the structure of Table 1, which outlines the key processes expected to act at each spatial scale. Besides, based on previous literature and regional biogeographic knowledge, we formulated two main hypotheses:

• Regional structuring of sponge assemblages: We hypothesized that most variation in species composition would occur at the broadest spatial scales—ecoregions and subregions—reflecting differences in geological history, oceanographic circulation, and large−scale environmental gradients that limit dispersal and shape regional species pools.

• Directional diversity gradient: We expected a decline in sponge species richness from the Mexican Caribbean to the Southern Gulf of Mexico, consistent with limited connectivity (Jordán-Dahlgren, 2002) and the proposed role of the Caribbean as a center of sponge diversification (Van Soest et al., 2012). We predicted that this gradient could be driven by one of two alternatives, yet mechanistically distinct, beta−diversity processes: nestedness or species turnover:

• Nestedness-driven gradient: If regional sponge assemblages are structured primarily by nestedness, we expect sponge communities in the Southern Gulf of Mexico to be subsets of the Caribbean species pool (Baselga, 2010). This pattern would be consistent with asymmetric dispersal, historical colonization from the Caribbean, and environmental filtering that progressively excludes species unable to tolerate Gulf conditions, without strong regional species replacement.

• Turnover−driven gradient: Alternatively, if species turnover predominates, we expect sponge assemblages in the Southern Gulf of Mexico to differ in composition from those in the Caribbean because species are replaced along environmental and biogeographic gradients (Baselga, 2010). This pattern would suggest stronger regional specialization, limited dispersal across regions, and the influence of distinct oceanographic and environmental regimes that promote the establishment of different species pools rather than simple species loss.

The hypotheses outlined above are not mutually exclusive; detecting a combination of nestedness and turnover would suggest that both regional-scale drivers and directional diversity gradients interact to shape the current distribution and composition of sponge assemblages in these regions.

Sampling efforts were based on a pilot study conducted in 2017 at Alacranes Reef. The number of localities and quadrats per site was determined through simulation of multivariate standard errors at each spatial level, using the SSP package (Guerra-Castro et al., 2021) in the R environment (R Core Team, 2023). This approach allowed for the definition of site-specific effort based on reef extension, resulting in an intentionally unbalanced and asymmetrical design, as recommended by Montes et al. (2021) to optimize biodiversity assessments at large spatial scales. The number of localities per reef ranged from 2 to 9, and quadrats per locality ranged from 5 to 25. To ensure comparability, the statistical quality of ecological data was verified through standardized multivariate error estimates, as well as rarefaction and extrapolation curves of species richness (Chao et al., 2020; Montes et al., 2021).

In this study, we used sponge individual counts as a proxy for abundance, as this metric provides a more direct estimate of demographic patterns, such as recruitment. Although conventional approaches often measure sponge abundance by colony surface cover or volume (Wulff, 2001; Bell et al., 2017), these metrics do not distinguish between a single large individual and multiple smaller ones occupying the same space. As a result, they are less informative for examining species diversity patterns and demographic structure. Sponge individuals were identified and counted within 1 m² quadrats spaced 2 m apart along a 20 m transect. All transects were deployed perpendicular to the coast and randomly placed at depths ranging from 6 to 18 meters, across diverse reef geomorphologies (e.g., fringing, patch, and bank reefs). In total, 624 quadrats were examined across 60 localities in 13 coral reefs (Figure 1, Table 1). Additionally, depth and substrate inclination were recorded at each quadrat to account for potential effects of light incidence, sediment accumulation, and hydrodynamic exposure on sponge abundance and assemblage composition. Inclination was measured in situ as the angle (in degrees) of the substrate relative to the horizontal plane, using a handheld underwater clinometer integrated in a dive compass. Both measurements were taken at the center of each quadrat and used as a continuous environmental variable in subsequent analyses.

Species were identified in situ whenever possible by a taxonomic specialist with extensive experience in the Porifera of this region (see Ugalde et al., 2021), thereby ensuring high reliability of field identifications. For specimens requiring further examination, tissue samples were collected and processed in the laboratory, following standard protocols for spicule dissociation and microscopic identification (Hajdu et al., 2011; Ugalde et al., 2021). All specimens were deposited in the National Porifera Collection “Gerardo Green” (CNPGG) at the Universidad Nacional Autónoma de México.

2.3 Analysis of data: spatial variation in sponge assemblage structure

Data were organized into an N (quadrats) × P (species) matrix, with entries representing counts of each species. Data were fourth-root transformed to reduce the influence of highly abundant species while retaining information from rarer species. A matrix of Bray-Curtis dissimilarities between samples was calculated (Clarke, 1993). To evaluate the first hypothesis regarding the relevance of spatial scales, we partitioned multivariate variation using a fully nested PERMANOVA model with sequential sums of squares (Type I; Anderson, 2017). Sources of variation, factor types, number of levels, and associated spatial scales used in the model are described in Table 1. Depth and substrate inclination were included as continuous covariables. The significance of each factor was tested using 9,999 permutations of residuals under the reduced model. The proportion of total variance explained by each source was estimated from the relativized square root of its component of variation (ecoregion, subregion, reef, locality, depth, substrate inclination, and residual). To assess whether differences in sponge assemblage structure among subregions were associated with variations in within-group multivariate dispersion, we performed a test for homogeneity of multivariate dispersions (PERMDISP; Anderson et al., 2006) based on distances among centroids of reef localities in Bray–Curtis space. Patterns of similarity among the centroids of coral reef localities were visualized using a metric multidimensional scaling (mMDS) based on Bray-Curtis distances. All statistical analyses were conducted using PRIMER v7 and PERMANOVA+ (Clarke et al., 2014a).

2.4 Analysis of data: biogeographic analysis of species diversity

To evaluate the above predictions of biogeographic processes, we used the components of species diversity defined by Whittaker (1972). Specifically, alpha diversity represented the number of observed sponge species per locality, while gamma diversity reflected the total number of sponge species within each subregion. We applied the integrated four-step procedure proposed by Chao et al. (2020) based on Hill numbers of order q = 0, 1, and 2, which generalizes the incidence-based richness and Shannon and Simpson diversities. This framework consisted of: (1) assessing sample completeness profiles to evaluate the effectiveness of the sampling effort; (2) calculating asymptotic diversity estimates to infer the true diversities of entire assemblages; (3) performing non-asymptotic coverage-based rarefaction and extrapolation to compare subregions at a standardized coverage (C_max); and (4) assessing evenness profiles derived from the slopes of the diversity profile. We considered a sample coverage (q = 1) value of 0.9 as acceptable for assessing the reliability of the inventory (Chao et al., 2020). To test the second hypothesis, that sponge assemblage diversity would be higher in the Mexican Caribbean (MC) compared to the Southern Gulf of Mexico (SGM), gamma diversity estimates were compared among subregions following the geographic gradient. These analyses were conducted using the iNEXT and iNEXT-4steps packages (Hsieh et al., 2016; Chao et al., 2020) in the statistical software R (R Core Team, 2021).

Beta diversity, defined as the variation in species composition among localities (Anderson et al., 2010), was assessed using the Jaccard similarity coefficient. To address the processes driving the beta diversity between subregions, we partitioned total beta diversity into turnover (BJTU) and nestedness (BJNE) components following Baselga (2010), using the BETAPART package (Baselga and Orme, 2012) in R. Finally, to further examine distributional patterns of species, we used an ordered shade plot (Clarke et al., 2014b) displaying the relative frequency of the 50 most important species that differentiate localities. Spatial patterns of species co-occurrence were assessed using hierarchical clustering, with Whittaker’s Index of Association as the resemblance measure. These analyses were performed using PRIMER v7 and PERMANOVA+ (Clarke et al., 2014a).

3 Results

A total of 137 species belonging to 17 orders, 48 families, and 71 genera were recorded. The most diverse families were Microcionidae (12 spp), Niphatidae (12 spp), and Aplysinidae (10 spp). The complete list of species, their spatial distribution, and counts are available in Zenodo at https://doi.org/10.5281/zenodo.17982627. Across the 13 coral reefs sampled, the average abundance of sponges per square meter varied substantially among reefs and subregions (Figure 2). Reefs in the VN exhibited the widest range of sponge densities, with some reefs such as Isla de Enmedio and Blanquilla reaching average values exceeding 20 individuals per m², while others like Cabezo and Hornos had considerably lower means. In contrast, reefs in the MC and NCY displayed more moderate and consistent sponge abundances, generally ranging between 5 and 15 individuals per m². Overall, these results suggest pronounced differences in sponge population densities across the region, with the highest variability observed in the VN subregion.

Figure 2

3.1 Spatial variation in sponge assemblage structure

Sponge assemblages varied significantly across spatial scales (Table 2). Most of the explained variation occurred at intermediate-to-fine scales, particularly at the levels of localities (21.99%) and coral reefs (18.87%), both statistically significant (p < 0.001). The subregional scale accounted for a smaller, though significant, portion of the variation (13.31%, p = 0.0085). In contrast, no significant variation was detected at the ecoregional level. Notably, the largest share of total variation (42.11%) remained at the residual level, which reflects differences among quadrats within localities. This highlights the importance of processes acting at the finest spatial scale (1–2 m), such as microhabitat heterogeneity, stochastic settlement and recruitment, or biological interactions, in promoting local coexistence and enabling higher species richness within sponge assemblages. Depth explained a modest portion of the total variation (4.02%, p = 0.0414), while substrate inclination had no significant effect.

These quantitative results were further supported by the metric multidimensional scaling (mMDS) ordination, which revealed clear compositional differences among subregions (Figure 3), although the overlap between groups indicates compositional continuity along the gradient from the Mexican Caribbean to the Southern Gulf of Mexico. MC localities (blue dots) clustered tightly toward the lower right quadrant of the ordination space, suggesting relatively homogeneous assemblages across reefs within this subregion. Localities from NCY (red dots) were more dispersed across central regions of the plot, overlapping with both MC and VN, suggesting intermediate compositional structure. In contrast, localities from the Veracruz Neritic zone (green dots), clustered toward the left of the ordination space, indicating a distinct species composition from MC, although with some shared structure with NCY.

Figure 3

Despite these visual patterns, the PERMDISP test confirmed that dispersion among localities was statistically similar across subregions (F = 1.493, p = 0.282), indicating that observed differences in community structure are driven primarily by compositional differences (centroid positions) rather than heterogeneity within subregions. Therefore, subregional identity is associated with distinct community centroids in multivariate space, but not with greater or lesser internal variability.

3.2 Alpha and gamma diversity patterns

A comprehensive analysis using the four-step incidence-based framework revealed distinct patterns in sponge gamma diversity across the three subregions. Sample completeness profiles (Figure 4A) indicated high coverage across all subregions (≥ 0.94 for q = 1 and 2), ensuring reliable diversity comparisons. The MC showed the lowest completeness for q = 0 (0.78), suggesting a higher proportion of undetected rare species. Rarefaction and extrapolation curves based on sampling size (Figure 4B) consistently ranked MC as the most diverse subregion, followed by the NCY, and then the VN. Although the MC subregion exhibits the highest species accumulation rate, the lack of stabilization across all curves reflects the presence of vanishingly rare taxa that are difficult to reveal with current sampling intensity (Figure 4B). Asymptotic and empirical diversity profiles (Figure 4C) revealed consistent differences among subregions across all Hill numbers (q = 0–2). For species richness (q = 0), asymptotic estimates indicated substantially higher total richness in the MC (121.7 species) compared to the NCY (101.4 species) and VN (73.1 species), confirming a pronounced regional gradient. Differences among subregions progressively decreased with increasing diversity order. For Shannon diversity (q = 1), MC remained the most diverse assemblage, but the gap with NCY and VN narrowed, reflecting a reduced influence of rare species. This convergence was even more evident for Simpson diversity (q = 2), where values differed less among regions, indicating that dominant and highly frequent species contribute more similarly across subregions. In all cases, empirical diversity estimates closely approached their asymptotic counterparts for q = 1 and q = 2, whereas larger gaps for q = 0, particularly in MC. At the maximum standardized coverage (C_max = 0.979), extrapolated species richness reached 112 for MC, 94 for NCY, and 69 for VN, confirming a clear geographic gradient in gamma diversity from east to west (Figure 4D). Shannon and Simpson diversities showed a similar ranking, although differences narrowed with increasing diversity order (q), indicating that much of the variation stems from rare and moderately common species. Despite the differences in total richness, the evenness profiles for q = 1 and 2 were remarkably similar across subregions, with Pielou’s evenness indices ranging from 0.90 to 0.91 and normalized Hill slope-derived evenness values decreasing from 0.66 (q = 1) to 0.47–0.52 (q = 2) (Figure 4E). The quantile-based frequency distribution analysis further revealed that, in MC, nearly half of the species fell into the lowest incidence quantiles (Q1–Q2), reflecting high rarity and spatial restriction (Figure 4F). In contrast, the NCY subregion showed a more even distribution, with a notable proportion of widespread species in high quantiles (Q7–Q10). VN exhibited an intermediate pattern, with fewer broadly distributed species, underscoring a regional gradient where species turnover and rarity structure gamma diversity across the gradient.

Figure 4

As predicted, coral reefs in the Veracruz subregion exhibited the lowest alpha diversity, with observed species richness ranging from 26 to 41 species (Table 3). In contrast, reefs in the Mexican Caribbean, particularly Puerto Morelos and Cozumel, displayed the highest richness values, with 61 and 51 species, respectively. Reefs in the Campeche/Yucatan subregion showed intermediate richness levels, ranging from 33 species at Sisal to 47 at Cayo Arcas. In general, observed richness values were closely aligned with the estimated richness, suggesting that sampling captured most of the local diversity. Estimated sampling coverage for q = 1 exceeded the 0.90 threshold for reliable incidence-based richness estimation in nearly all reef localities, ranging from 84.0% in Akumal to 98.3% in Alacranes (Table 3). These results confirm that sampling effort was sufficient across all reefs.

3.3 Local and regional Beta diversity

From a total of 137 species, in general, species sharing between regions was moderate: 58 species were shared between MC and NCY, 41 between MC and VN, and 40 between NCY and VN, while around 22–26 species were not shared among subregions. The decomposition of beta diversity revealed that species turnover (BJTU) was the dominant component of total beta diversity (BJAC) across all subregions, while nestedness (BJNE) played a comparatively minor role (Table 4). The Campeche/Yucatan coast exhibited the highest overall beta diversity (BJAC = 0.767), driven primarily by a strong turnover component (BJTU = 0.731), suggesting high heterogeneity in species composition among its coral reef localities. The Mexican Caribbean also showed high beta diversity (BJAC = 0.746), with turnover (BJTU = 0.692) accounting for most of the compositional dissimilarity. In contrast, the Veracruz zone displayed slightly lower beta diversity (BJAC = 0.714) and the highest contribution from nestedness (BJNE = 0.076), indicating that some reef assemblages in this subregion may represent species-poorer subsets of richer communities. Overall, these results suggest that species replacement, rather than nested subset structures, is the principal driver of spatial variability in sponge assemblages within each subregion.

The shade-plot based on relativized occurrence frequencies (0–100%) revealed distinct patterns of dominant species across subregions (Figure 5). In the Mexican Caribbean (MC), species such as Mycale (Mycale) laevis, Spirastrella coccinea, Siphonodictyon coralliphagum, and Iotrochota birotulata exhibited consistently high frequencies, underscoring their widespread distribution and potential dominance in that subregion. In contrast, the NCY subregion was characterized by high relative occurrences of Aiolochroia crassa, Amphimedon compressa, and Desmapsamma anchorata, particularly in reefs such as Cayo Arcas and Alacranes. The VN zone displayed distinct dominance by species like Desmapsamma anchorata, Geodia neptuni, Scopalina ruetzleri, and Haliclona (Soestella) caerulea, with high frequencies across multiple localities. Additionally, several species, such as Amphimedon compressa and Iotrochota birotulata, were present in all subregions, yet their frequency of occurrence varied notably, with A. compressa being particularly frequent in NCY and VN, and I. birotulata being most frequent in MC. This pattern indicated that sponge species occurring in sponge species-poor coral reefs are not a subset of species occurring in sponge species-rich coral reefs.

Figure 5

4 Discussion

The spatial analysis of sponge assemblages across shallow (<18m) coral reefs along the Mexican Atlantic coast revealed distinct patterns of diversity, composition, and spatial structure that can be directly interpreted in terms of interacting ecological mechanisms operating across spatial scales. First, sponge assemblages differed markedly among coral reefs and subregions, with most of the explained variation concentrated at intermediate-to-fine spatial scales, particularly among quadrats, localities, and reefs, indicating a strong influence of local environmental filtering, biotic interactions, and microhabitat heterogeneity on assemblage structure and coexistence of species. Second, sponge communities in the Southern Gulf of Mexico were not simply a subset of those in the Mexican Caribbean; rather, compositional differences were dominated by species turnover, suggesting that spatial variation in environmental conditions and limited connectivity, rather than progressive species loss alone, structure regional diversity gradients. These results support a framework in which local processes interact with regional context to shape observed assemblage patterns. In the following sections, we interpret these results in relation to the spatial hierarchy of assemblage structure (4.1), patterns of alpha, beta, and gamma diversity (4.2), and the ecological mechanisms that underlie these patterns (4.3).

4.1 Spatial variation in sponge assemblage structure

The hierarchical sampling design revealed that the greatest proportions of variation in sponge assemblage composition occurred at small to intermediate spatial scales, underscoring the central role of small-scale ecological and environmental processes in shaping sponge diversity. Such fine−scale dominance indicates that sponge assemblage structure is primarily driven by spatially heterogeneous environmental filters (e.g., light, hydrodynamics, sedimentation) acting during settlement and post−settlement stages. Our findings align with previous multi-scale works about the diversity of sponges in other Caribbean regions (Guerra-Castro et al., 2011; Williams et al., 2015). These results suggest that small-scale environmental variation and biological interactions can exert a stronger influence than broader-scale dispersal or historical effects under certain conditions.

In this context, deterministic processes such as larval supply, habitat selection, competition, or differential predation may dominate the spatial structuring of sponge assemblages at finer scales, even as regional processes continue to shape broader biogeographic patterns. Thus, fine−scale processes act within the constraints imposed by regional species pools and dispersal pathways. Together, these processes directly influence local alpha diversity by regulating which species can establish and persist within individual reefs and microhabitats. This view is supported by experimental evidence showing context-dependent outcomes: It has been demonstrated that sponge larval settlement is highly selective, with larvae preferentially settling in shaded and cryptic microhabitats where post−settlement survival is significantly enhanced (Maldonado and Young, 1996; Maldonado and Uriz, 1998; Ettinger-Epstein et al., 2008; Abdul Wahab et al., 2011). This leads to significant spatial structuring even within a single reef (Uriz et al., 1998). Similarly, Bell and Carballo (2008) emphasized that local hydrodynamics and sedimentation processes can drive fine-scale variation in sponge communities, even in the absence of strong regional species–area gradients.

Our results also contribute to the ongoing debate regarding bottom-up versus top-down control of sponge communities. The importance of predation (top-down control) has been supported by manipulative experiments and cross-Caribbean surveys (Pawlik et al., 2018), which showed that chemically undefended sponge species are selectively grazed in reefs with abundant spongivores. In contrast, Wulff (2017) found limited evidence of within-reef top-down control but strong context-dependent bottom-up effects associated with higher food availability. Our observations suggest that these mechanisms are not mutually exclusive and may vary in strength across spatial and ecological contexts, depending on local physical conditions and habitat configuration. Specifically, environmental context modulates both sponge performance and predator effectiveness. In physically stable reefs with low sedimentation and moderate hydrodynamics, sponge predators can effectively access and selectively graze susceptible species, strengthening top−down control (Pawlik et al., 2018). In contrast, in environments characterized by strong hydrodynamics and high sediment loads, physical stress constrains sponge growth and survival while potentially reducing predator efficiency or access, thereby weakening top−down control and allowing bottom−up processes to dominate.

For instance, despite higher species richness in the MC subregion, sponge abundance remained low, a pattern that is consistent with the naturally oligotrophic conditions of the Caribbean Sea, where low concentrations of dissolved organic nutrients limited food availability for suspension feeders and favored systems sustained by tight internal recycling of organic matter (Lesser, 2018). This pattern illustrates how high diversity does not necessarily translate into high biomass or dominance. Meanwhile, in VN, the observed high abundance but low richness of sponges may reflect a release from top-down control, long−standing fishing pressure on spongivorous fishes, combined with increased nutrient loads derived from river runoff and coastal inputs, conditions known to characterize the southwestern Gulf of Mexico (Salas-Pérez and Granados-Barba, 2008; Gil−Agudelo et al., 2020; Loh et al., 2015). These contrasting outcomes illustrate that top−down and bottom−up controls are not mutually exclusive but instead operate along a context−dependent gradient shaped by physical forcing, productivity, and trophic structure. These patterns are consistent with the emerging consensus that Caribbean sponge communities are structured by a combination of factors, including predation pressure and nutrient availability, which together influence sponge food uptake and community composition (Wulff, 2017; Pawlik et al., 2018).

Altogether, our findings support the view that sponge community assembly is primarily shaped by local environmental filters and deterministic ecological processes, with regional-scale dispersal and historical contingencies playing a secondary, yet non-negligible role, reinforcing the importance of explicitly considering spatial scale when interpreting sponge ecological patterns. Integrating spatial hierarchy into sponge ecology thus reveals the complex interplay between bottom-up and top-down mechanisms that vary across regions and reef types.

4.2 Alpha, Beta, and Gamma diversity patterns

Two main patterns of sponge diversity were detected, reflecting the interaction between broad biogeographic gradients and local-scale processes. First, a clear geographic gradient of gamma and alpha diversity was observed, decreasing from the Mexican Caribbean (MC) to the Northern Campeche–Yucatán (NCY) and Veracruz Neritic (VN) subregions. At the local scale, this pattern likely reflects stronger environmental filtering and fewer suitable microhabitats in NCY and VN. In contrast, at the regional scale, it reflects differences in habitat extent, geomorphological complexity, and connectivity to the Caribbean species pool. Sample-based rarefaction and asymptotic extrapolations confirmed that MC harbors the highest sponge richness (95 observed, 122 extrapolated species), followed by NCY (84 observed, 101 extrapolated species) and VN (63 observed, 73 extrapolated species), consistent with expectations based on biogeographic and ecological theory. This pattern likely reflects subregional differences in reef size, habitat complexity, and proximity to Caribbean source pools, where isolated or fragmented systems tend to support fewer species (MacArthur and Wilson, 1967).

The Caribbean Sea has long been recognized as a center of sponge diversity and speciation (Van Soest et al., 2012), and our data reinforces this notion. Moreover, quantile-based incidence profiles revealed that MC hosted a larger proportion of locally rare and spatially restricted species (Q1–Q2), suggesting that fine-scale habitat heterogeneity and microhabitat specialization promote high alpha diversity (local turnover) even where overall sponge abundance remains low. In contrast, NCY showed a higher proportion of widely distributed species (Q7–Q10), possibly linked to broader habitat connectivity and reduced environmental heterogeneity. Despite regional differences in richness, evenness metrics showed similar levels across subregions, implying comparable patterns in relative abundance structure within assemblages.

If proximity to a regional source pool were the primary driver of diversity patterns, nestedness would be expected to dominate beta diversity. However, the observed patterns deviate from this expectation. Species turnover (replacement) prevailed instead. Following the conceptual framework proposed by Baselga (2010), this result indicates that sponge assemblages across subregions are not subsets of one another but are composed of distinct species. This prevalence of turnover implies that beta diversity is driven mainly by species replacement associated with environmental gradients, hydrodynamic regimes, and dispersal barriers, rather than by unidirectional species loss.

Distinct species compositions among subregions support this interpretation. Species-level differences, therefore, provide concrete evidence of environmental and ecological sorting. Importantly, although the dominant species differed taxonomically among regions, they share broadly comparable ecological attributes within each subregion, suggesting that dominance is driven by regional environmental filters acting on functional traits rather than by species identity per se. In oligotrophic, clear−water reefs of the MC, dominant species are typically well adapted to low food availability and stable conditions, often exhibiting massive or tubular morphologies, such as Mycale (Mycale) laevis, Aplysina cauliformis, Niphates digitalis, Xestospongia muta. In contrast, in the VN, dominance by a distinct set of species is consistent with tolerance to higher turbidity, sedimentation, eutrophication, and physical disturbance. These communities are dominated primarily by encrusting forms or massive species with more rigid body walls, including Amphimedon compressa, Neopetrosia subtriangularis, and Spirastrella coccinea (Figure 5). Together, these patterns indicate that the observed spatial turnover in species composition reflects mechanistic processes of environmental filtering and ecological sorting operating along regional gradients of turbidity, sedimentation, nutrient enrichment, and physical disturbance. These gradients select for functionally similar traits, such as compact morphologies, enhanced sediment tolerance, and structural resistance, resulting in assemblages that are functionally comparable but taxonomically distinct.

Similar conclusions have emerged from studies of other benthic organisms, in which variation in local environmental factors promoted the development of distinct assemblages across nearby sites (Robertson and Cramer, 2014; Williams et al., 2015; Guerra-Castro et al., 2016; Miyazawa et al., 2020), thereby overriding regional-scale influences. Thus, high beta diversity can arise even over relatively short spatial distances when environmental gradients are pronounced. In particular, the elevated species turnover observed in the NCY subregion reflects a pronounced environmental gradient (Roberts et al., 1992; Alvera-Azcárate et al., 2009), further supporting the role of local environmental filters in structuring sponge assemblages.

4.3 Environmental factors and processes associated with diversity patterns

The environmental factors discussed below provide a mechanistic framework that integrates the spatial structure and diversity patterns described above, linking alpha, beta, and gamma diversity to local-scale environmental filters and regional connectivity constraints, helping explain how observed patterns emerge from underlying physical and ecological processes.

The dominance of particular sponge morphologies across subregions provides insights into how local environmental conditions act as filters shaping assemblage composition (Schönberg, 2021). Encrusting forms, for example, are often associated with environments characterized by strong hydrodynamic forces, turbulent flows, and intermediate sediment sizes (Schönberg, 2021; González-Murcia et al., 2022). Under these conditions, hydrodynamic stress acts as a strong mechanical filter, selectively favoring low-relief morphologies that reduce drag forces and enhance attachment strength, while excluding more exposed growth forms. These conditions may exclude species with massive or branching morphologies, which are less able to withstand drag or remain attached under high-energy conditions (Bell and Smith, 2004). In line with this, we observed that encrusting species such as Desmapsamma anchorata, Amphimedon compressa, Iotrochota arenosa, Clathria (Thalysias) venosa, and Neopetrosia subtriangularis were more frequent in reefs of the VN zone. In contrast, species with massive or branching morphologies, e.g., Iotrochota birotulata, Callyspongia (Cladochalina) aculeata, Xestospongia muta, were more common in the MC and NCY subregions. Although NCY and VN reefs are both exposed to seasonal cold fronts, the VN region’s narrower continental shelf intensifies local hydrodynamic regimes. These dynamics, driven by tides, winds, and eddies, alter current direction and magnitude, further contributing to selective filtering based on morphology (Salas-Monreal et al., 2009; Allende-Arandía et al., 2015). Additionally, VN reefs are subject to substantial river runoff (Avendaño et al., 2019), thereby elevating sediment loads and reducing light availability. Sedimentation can physically abrade sponge tissue, clog aquiferous systems, and increase metabolic maintenance costs (Schönberg, 2016). These processes disproportionately affect erect, branching, and massive species, which have larger exposed surfaces and are more susceptible to sediment accumulation. Together, high hydrodynamic energy and sedimentation appear to select for a subset of tolerant species, likely explaining the lower richness but higher abundance patterns observed in VN.

Reef geomorphology further shapes local conditions that influence sponge diversity (Bell and Smith, 2004; Bell and Carballo, 2008). MC reefs are mostly fringing types, whereas NCY and VN are predominantly bank reefs (Blanchon et al., 2022). Fringing reefs in MC, combined with prevailing south-to-north currents, promote more homogeneous conditions and greater larval connectivity (Carrillo et al., 2015; Blanchon et al., 2022), facilitating high gamma diversity and reduced spatial turnover within the subregion. In contrast, NCY and VN reefs exhibit greater structural heterogeneity and are more strongly influenced by local hydrodynamic and sedimentary regimes, which act as environmental filters shaping sponge assemblages. These localized processes contribute to higher spatial turnover and greater variability in species composition among nearby reefs.

Finally, the inverse relationship between richness and abundance observed across subregions reflects the interaction of bottom-up and top-down controls. Although MC reefs harbored the highest species richness, they exhibited the lowest sponge abundance. Oligotrophic conditions in the MC subregion may constrain food availability for filter-feeding sponges. Oligotrophic conditions in MC may constrain sponge abundance, despite their ability to exploit dissolved organic carbon (de Goeij et al., 2013; Pawlik et al., 2015), while intact predator communities exert strong top-down control (Aguilar-Medrano and Arias-González, 2018). In this scenario, diversity is high, but competitive exclusion and predation limit the dominance of individual species. In contrast, NCY reefs benefit from regional upwelling that enhances productivity (Enriquez et al., 2010), while VN reefs receive nutrient-rich inputs via river runoff. However, overfishing in VN likely suppresses sponge predator populations (Gil-Agudelo et al., 2020), reducing top-down pressure. The combination of nutrient enrichment and predator release may thus promote high sponge abundance dominated by a few tolerant species.

Collectively, these observations reinforce the idea that sponge diversity and abundance are shaped by strong spatial heterogeneity driven by local environmental conditions and context−dependent ecological processes. Most variation occurs at fine spatial scales, highlighting the importance of site−specific factors in regulating community composition and dominance patterns. At broader scales, regional diversity is maintained primarily through species turnover rather than nestedness, underscoring environmental differentiation as a key driver of sponge assemblage structure. These findings emphasize that predicting sponge community responses to ongoing environmental change requires explicit consideration of physical setting, trophic dynamics, and spatial scale. Accordingly, preserving environmental heterogeneity and trophic interactions will be critical for sustaining sponge diversity and the ecological functions they support within coral reef ecosystems.

References

• 1

  Abdul WahabM. A.de NysR.WhalanS. (2011). Larval behaviour and settlement cues of a brooding coral reef sponge. Coral Reefs30, 451–460. doi: 10.1007/s00338-011-0727-5. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 2

  Aguilar-MedranoR.Arias-GonzálezJ. E. (2018). Functional reef fish groups of the Mexican Caribbean: implications of habitat complexity. Rev. Mex. Biodivers.89, 1138–1153. doi: 10.22201/ib.20078706e.2018.4.2398

  • CrossRef
  • Google Scholar
  • View reference in article

• 3

  Allende-ArandíaM. E.Zavala-HidalgoJ.Romero-CentenoR.Mateos-JassoA.Vargas-HernándezJ. M.ZamudioL. (2015). Analysis of ocean current observations in the Northern Veracruz Coral Reef System, Mexico: 2007–12. J. Coast. Res.32, 46–55. doi: 10.2112/jcoastres-d-14-00148.1. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 4

  Alvera-AzcárateA.BarthA.WeisbergR. H. (2009). The surface circulation of the Caribbean Sea and the Gulf of Mexico as inferred from satellite altimetry. J. Phys. Oceanogr.39, 640–657. doi: 10.1175/2008JPO3765.1

  • CrossRef
  • Google Scholar
  • View reference in article

• 5

  AndersonM. J. (2017). “ Permutational multivariate analysis of variance (PERMANOVA),” in Wiley StatsRef: Statistics Reference Online (eds BalakrishnanN.ColtonT.EverittB.PiegorschW.RuggeriF.TeugelsJ. L.). doi: 10.1002/9781118445112.stat07841

  • CrossRef
  • Google Scholar
  • View reference in article

• 6

  AndersonM. J.CristT. O.ChaseJ. M.VellendM.InouyeB. D.FreestoneA. L.et al. (2010). Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist. Ecol. Lett.14, 19–28. doi: 10.1111/j.1461-0248.2010.01552.x. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 7

  AndersonM. J.EllingsenK. E.McArdleB. H. (2006). Multivariate dispersion as a measure of beta diversity. Ecol. Lett.9, 683–693. doi: 10.1111/j.1461-0248.2006.00926.x. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 8

  AppendiniC. M.Torres-FreyermuthA.OropezaF.SallesP.LópezJ.MendozaE. T. (2013). Wave modeling performance in the Gulf of Mexico and Western Caribbean: Wind reanalyses assessment. Appl. Ocean Res.39, 20–30. doi: 10.1016/j.apor.2012.09.004. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 9

  AvendañoO.Salas-MonrealD.AnisA.Salas-de-LeonD. A.Monreal-GomezM. A. (2019). Monthly surface hydrographical variability in a coral reef system under the influence of river discharges. Estuar. Coast. Shelf Sci.222, 53–65. doi: 10.1016/j.ecss.2019.04.012. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 10

  BaselgaA. (2010). Partitioning the turnover and nestedness components of beta diversity. Global Ecol. Biogeogr.19, 134–143. doi: 10.1111/j.1466-8238.2009.00490.x. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 11

  BaselgaA.OrmeC. D. L. (2012). betapart: an R package for the study of beta diversity. Methods Ecol. Evol.3, 808–812. doi: 10.1111/j.2041-210X.2012.00224.x. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 12

  BellJ. J.BiggerstaffA.BatesT.BennettH.MarlowJ.McGrathE.et al. (2017). Sponge monitoring: Moving beyond diversity and abundance measures. Ecol. Indic.78, 470–488. doi: 10.1016/j.ecolind.2017.03.001. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 13

  BellJ. J.CarballoJ. L. (2008). Patterns of sponge biodiversity and abundance across different biogeographic regions. Mar. Biol.155, 563–570. doi: 10.1007/s00227-008-1036-6. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 14

  BellJ. J.DavyS. K.JonesT.TaylorM. W.WebsterN. S. (2013). Could some coral reefs become sponge reefs as our climate changes? Global Change Biol.19, 2613–2624. doi: 10.1111/gcb.12212. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 15

  BellJ. J.RovelliniA.DavyS. K.TaylorM. W.FultonE. A.DunnM. R.et al. (2018). Climate change alterations to ecosystem dominance: how might sponge-dominated reefs function? Ecology. 99 (9). doi: 10.1002/ecy.2446. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 16

  BellJ. J.SmithD. (2004). Ecology of sponge assemblages (Porifera) in the Wakatobi region, south-east Sulawesi, Indonesia: richness and abundance. J. Mar. Biol. Assoc. U. K.84, 581–591. doi: 10.1017/S0025315404009580h. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 17

  BermanJ.BellJ. J. (2016). Short-term temporal variability in a temperate sponge assemblage. Mar. Biol.163, 51. doi: 10.1007/s00227-016-2825-y. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 18

  BlanchonP.Medina-ValmasedaA. E.Islas-DomínguezE.Guerra-CastroE.BlakewayD.Garza PérezJ. R.et al. (2022). Linear breakwater reefs of the greater Caribbean: Classification, distribution & morphology. PloS One17, e0270053. doi: 10.1371/journal.pone.0270053. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 19

  ButlerJ.StanleyJ. A.ButlerM. J. (2016). Underwater soundscapes in near-shore tropical habitats and the effects of environmental degradation and habitat restoration. J. Exp. Mar. Biol. Ecol.479, 89–106. doi: 10.1016/j.jembe.2016.03.006. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 20

  CarballoJ. L.BellJ. J. (Eds.) (2017). Climate Change, Ocean Acidification and Sponges: Impacts Across Multiple Levels of Organization (Cham: Springer International Publishing).

  • Google Scholar
  • View reference in article

• 21

  CarballoJ. L.GómezP.Cruz-BarrazaJ. A. (2014). Biodiversidad de Porifera en México. Rev. Mex. Biodivers.85, 143–153. doi: 10.7550/rmb.32074

  • CrossRef
  • Google Scholar
  • View reference in article

• 22

  CarrilloL.JohnsE. M.SmithR. H.LamkinJ. T.LargierJ. L. (2015). Pathways and hydrography in the Mesoamerican barrier reef system part 1: circulation. Cont. Shelf Res.109, 164–176. doi: 10.1016/j.csr.2015.09.014. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 23

  ChaoA.KubotaY.ZelenýD.ChiuC.-H.LiC.-F.KusumotoB.et al. (2020). Quantifying sample completeness and comparing diversities among assemblages. Ecol. Res.35, 292–314. doi: 10.1111/1440-1703.12102. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 24

  ClarkeK. R. (1993). Non-parametric multivariate analyses of changes in community structure. Aust. J. Ecol.18, 117–143. doi: 10.1111/j.1442-9993.1993.tb00438.x. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 25

  ClarkeK. R.GorleyR. N.SomerfieldP. J.WarwickR. M. (2014a). Change in marine communities: an approach to statistical analysis and interpretation (Plymouth: PRIMER-E, Ltd).

  • Google Scholar
  • View reference in article

• 26

  ClarkeK. R.TweedleyJ. R.ValesiniF. J. (2014b). Simple shade plots aid better long-term choices of data pre-treatment in multivariate assemblage studies. J. Mar. Biol. Assoc. U. K.94, 1–16. doi: 10.1017/S0025315413001227. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 27

  CróquerA.WeilE.RogersC. S. (2021). Similarities and differences between two deadly Caribbean coral diseases: White Plague and Stony Coral Tissue Loss Disease. Front. Mar. Sci.8, 709544. doi: 10.3389/fmars.2021.709544

  • CrossRef
  • Google Scholar
  • View reference in article

• 28

  de GoeijJ. M.van OevelenD.VermeijM. J. A.OsingaR.MiddelburgJ. J.de GoeijA. F. P. M.et al. (2013). Surviving in a marine desert: The Sponge Loop retains resources within coral reefs. Science342, 108–110. doi: 10.1126/science.1241981. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 29

  DiazM. C.RútzlerK. (2001). Sponges: an essential component of Caribbean coral reefs. Bull. Mar. Sci.69, 535–546.

  • Google Scholar
  • View reference in article

• 30

  DohertyM. L.JohnsonJ. V.Goodbody-GringleyG. (2025). Widespread coral bleaching and mass mortality during the 2023–2024 marine heatwave in Little Cayman. PloS One20, e0322636. doi: 10.1371/journal.pone.0322636. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 31

  EnriquezC.Mariño-TapiaI. J.Herrera-SilveiraJ. A. (2010). Dispersion in the Yucatan coastal zone: Implications for red tide events. Cont. Shelf Res.30, 127–137. doi: 10.1016/j.csr.2009.10.005. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 32

  Estrada-SaldívarN.Quiroga-GarcíaB. A.Pérez-CervantesE.Rivera-GaribayO. O.Alvarez-FilipL. (2021). Effects of the stony coral tissue loss disease outbreak on coral communities and the benthic composition of cozumel reefs. Front. Mar. Sci.8, 632777. doi: 10.3389/fmars.2021.632777

  • CrossRef
  • Google Scholar
  • View reference in article

• 33

  Ettinger-EpsteinP.WhalanS.BattershillC. N.de NysR. (2008). A hierarchy of settlement cues influences larval behaviour in a coral reef sponge. Mar. Ecol. Prog. Ser.365, 103–113. doi: 10.3354/meps07503. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 34

  Gil-AgudeloD. L.Cintra-BuenrostroC. E.BrennerJ.González-DíazP.KieneW.LusticC.et al. (2020). Coral reefs in the Gulf of Mexico Large Marine Ecosystem: Conservation status, challenges, and opportunities. Front. Mar. Sci.6, 807. doi: 10.3389/fmars.2019.00807

  • CrossRef
  • Google Scholar
  • View reference in article

• 35

  González-MurciaS.CoppockA. G.EkinsM.BattershillC. N.JonesG. P. (2022). Effects of exposure, depth and aspect on sponge communities on a coral reef. Mar. Ecol. Prog. Ser.685, 111–126. doi: 10.3354/meps13981. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 36

  Guerra-CastroE. J.CajasJ. C.SimõesN.Cruz-MottaJ. J.MascaróM. (2021). SSP: an R package to estimate sampling effort in studies of ecological communities. Ecography44, 561–573. doi: 10.1111/ecog.05284. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 37

  Guerra-CastroE. J.CondeJ. E.Cruz-MottaJ. J. (2016). Scales of spatial variation in tropical benthic assemblages and their ecological relevance: epibionts on Caribbean mangrove roots as a model system. Mar. Ecol. Prog. Ser.548, 97–110. doi: 10.3354/meps11693. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 38

  Guerra-CastroE. J.Cruz-MottaJ. J. (2018). Colonization and succession as drivers of small-scale spatial variability in epibionts on mangrove roots in the Southern Caribbean. Mar. Ecol. Prog. Ser.588, 15–27. doi: 10.3354/meps12404. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 39

  Guerra-CastroE.YoungP.Pérez-VázquezA.CarteronS.AlvizuA. (2011). Spatial variability and human disturbance of sponge assemblages associated with mangrove roots in the southern Caribbean. Mar. Freshw. Res.62, 491–501. doi: 10.1071/MF10267. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar
  • View reference in article

• 40

  HajduE.PeixinhoS.FernandezJ. C. (2011). Esponjas marinhas da Bahia: guia de campo e laboratório. (Rio de Janeiro: Museu Nacional, Universidade Federal do Rio de Janeiro).

  • Google Scholar

• 41

  HsiehT. C.MaK. H.ChaoA. (2016). iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods Ecol. Evol.7, 1451–1456. doi: 10.1111/2041-210x.12613. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 42

  Jordán-DahlgrenE. (2002). Gorgonian distribution patterns in coral reef environments of the Gulf of Mexico: evidence of sporadic ecological connectivity? Coral Reefs21, 205–215. doi: 10.1007/s00338-002-0226-9. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 43

  Jordán-DahlgrenE.Rodríguez-MartínezR. E. (2003). “ The Atlantic coral reefs of Mexico,” in Latin American Coral Reefs. Ed. CortésJ. ( Elsevier Science, Amsterdam), 131–158.

  • Google Scholar

• 44

  LesserM. P. (2018). Eutrophication on coral reefs: What is the evidence for phase shifts, nutrient limitation and coral bleaching? BioScience68, 6–17. doi: 10.1093/biosci/bix165

  • CrossRef
  • Google Scholar

• 45

  LohT.-L.McMurrayS. E.HenkelT. P.VicenteJ.PawlikJ. R. (2015). Indirect effects of overfishing on Caribbean reefs: sponges overgrow reef-building corals. PeerJ3, e901. doi: 10.7717/peerj.901. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 46

  MacArthurR. H.WilsonE. O. (1967). The Theory of Island Biogeography (Princeton, NJ: Princeton University Press).

  • Google Scholar

• 47

  MaldonadoM.UrizM.-J. (1998). Microrefuge exploitation by subtidal encrusting sponges: patterns of settlement and post-settlement survival. Mar. Ecol. Prog. Ser.174, 141–150. doi: 10.3354/meps174141. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 48

  MaldonadoM.YoungC. M. (1996). Effects of physical factors on larval behavior, settlement and recruitment of four tropical demosponges. Mar. Ecol. Prog. Ser.138, 169–180. doi: 10.3354/meps138169. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 49

  Medina-ValmasedaA. E.BlanchonP.Alvarez-FilipL.Pérez-CervantesE. (2022). Geomorphically controlled coral distribution in degraded shallow reefs of the Western Caribbean. PeerJ10, e1259. doi: 10.7717/peerj.1259. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 50

  MiyazawaE.MontillaL. M.Agudo-AdrianiE. A.AscanioA.Mariño-BriceñoG.CroquerA. (2020). On the importance of spatial scales on beta diversity of coral assemblages: a study from Venezuelan coral reefs. PeerJ8, e9082. doi: 10.7717/peerj.9082. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 51

  Molina-HernándezA.González-BarriosF. J.PerryC. T.Álvarez-FilipL. (2020). Two decades of carbonate budget change on shifted coral reef assemblages: are these reefs being locked into low net budget states? Proc. R. Soc B.287, 20202305. doi: 10.1098/rspb.2020.2305. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 52

  MontesE.LefcheckJ. S.Guerra-CastroE.KleinE.KavanaughM. T.de Azevedo MazzucoA. C.et al. (2021). Optimizing large-scale biodiversity sampling effort: Toward an unbalanced survey design. Oceanography34, 80–91. doi: 10.5670/oceanog.2021.216

  • CrossRef
  • Google Scholar

• 53

  Nuñez-LaraE.Ernesto Arias-GonzálezJ.LegendreP. (2005). Spatial patterns of Yucatan reef fish communities: Testing models using a multi-scale survey design. J. Exp. Mar. Biol. Ecol.324, 157–169. doi: 10.1016/j.jembe.2005.04.011. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 54

  OeyL.EzerT.LeeH. (2005). “ Loop Current, rings and related circulation in the Gulf of Mexico: A review of numerical models and future challenges,” in Circulation in the Gulf of Mexico: Observations and Models. Eds. SturgesW.Lugo-FernándezA. ( American Geophysical Union, Washington, DC), 31–56.

  • Google Scholar

• 55

  PawlikJ. R.LohT.-L.McMurrayS. E. (2018). A review of bottom-up vs. top-down control of sponges on Caribbean fore-reefs: what’s old, what’s new, and future directions. PeerJ6, e4343. doi: 10.7717/peerj.4343. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 56

  PawlikJ. R.McMurrayS. E. (2020). The emerging ecological and biogeochemical importance of sponges on coral reefs. Annu. Rev. Mar. Sci.12, 315–337. doi: 10.1146/annurev-marine-010419-010807. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 57

  PawlikJ. R.McMurrayS. E.ErwinP.ZeaS. (2015). A review of evidence for food limitation of sponges on Caribbean reefs. Mar. Ecol. Prog. Ser.519, 265–283. doi: 10.3354/meps11093. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 58

  Pérez-BotelloA. M.DáttiloW.SimõesN. (2023). Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs. PeerJ11, e16381. doi: 10.7717/peerj.16381. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 59

  Pérez-BotelloA. M.SimõesN. (2021). Sponge-dwelling fauna: a review of known species from the Northwest Tropical Atlantic coral reefs. Biodivers. Data J.9, e63372. doi: 10.3897/BDJ.9.e63372. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 60

  R Core Team (2021). R: A Language and Environment for Statistical Computing (Vienna: R Foundation for Statistical Computing).

  • Google Scholar

• 61

  R Core Team (2023). _R: A Language and Environment for Statistical Computing_. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

  • Google Scholar

• 62

  RobertsH. H.WilsonP. A.Lugo-FernándezA. (1992). Biologic and geologic responses to physical processes: examples from modern reef systems of the Caribbean-Atlantic region. Cont. Shelf Res.12, 809–834. doi: 10.1016/0278-4343(92)90046-M

  • CrossRef
  • Google Scholar

• 63

  RobertsonD. R.CramerK. L. (2014). Defining and dividing the Greater Caribbean: Insights from the biogeography of shorefishes. PloS One9, e102918. doi: 10.1371/journal.pone.0102918. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 64

  Rodríguez-MartínezR. E.Medina-ValmasedaA. E.BlanchonP.Monroy-VelázquezL. V.Almazán-BecerrilA.Delgado-PechB.et al. (2019). Faunal mortality associated with massive beaching and decomposition of pelagic Sargassum. Mar. pollut. Bull.146, 201–205. doi: 10.1016/j.marpolbul.2019.06.015. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 65

  Ruiz-CastilloE.Gomez-ValdesJ.SheinbaumJ.Rioja-NietoR. (2016). Wind-driven coastal upwelling and westward circulation in the Yucatan shelf. Cont. Shelf Res.118, 63–76. doi: 10.1016/j.csr.2016.02.010. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 66

  RützlerK. (2002). Impact of crustose clionid sponges on Caribbean reef corals. Acta Geol. Hisp.37, 61–72.

  • Google Scholar

• 67

  Salas-PérezJ. J.Granados-BarbaA. (2008). Oceanographic characterization of the Veracruz Reef System, southwestern Gulf of Mexico. Atmósfera21, 281–301.

  • Google Scholar

• 68

  Salas-MonrealD.Salas-de-LeónD. A.Monreal-GómezM. A.Riverón-EnzástigaL. (2009). Current rectification in a tropical coral reef system. Coral Reefs28, 871–879. doi: 10.1007/s00338-009-0521-9. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 69

  SchönbergC. H. L. (2016). Happy relationships between marine sponges and sediments – a review and some observations from Australia. J. Mar. Biol. Assoc. U. K.96, 493–514. doi: 10.1017/S0025315415001411. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 70

  SchönbergC. H. L. (2021). No taxonomy needed: Sponge functional morphologies inform about environmental conditions. Ecol. Indic.129, 107806. doi: 10.1016/j.ecolind.2021.107806. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 71

  SpaldingM. D.FoxH. E.AllenG. R.DavidsonN.FerdañaZ. A.FinlaysonM.et al. (2007). Marine ecoregions of the world: a bioregionalization of coastal and shelf areas. BioScience57, 573–583. doi: 10.1641/B570707. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 72

  TunnellJ. W.Jr.ChávezE. A.WithersK. (Eds.) (2007). Coral Reefs of the Southern Gulf of Mexico (College Station, TX: Texas A&M University Press).

  • Google Scholar

• 73

  UgaldeD.FernandezJ. C.GomezP.Lobo-HajduG.SimoesN. (2021). An update on the diversity of marine sponges in the southern Gulf of Mexico coral reefs. Zootaxa5031, 1–112. doi: 10.11646/zootaxa.5031.1.1. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 74

  UnderwoodA. J.ChapmanM. G. (1998). A method for analysing spatial scales of variation in composition of assemblages. Oecologia117, 570–578. doi: 10.1007/s004420050694. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 75

  UrizM. J.MaldonadoM.TuronX.MartíR. (1998). How do reproductive output, larval behaviour, and recruitment contribute to adult spatial patterns in Mediterranean encrusting sponges? Mar. Ecol. Prog. Ser.167, 137–148. doi: 10.3354/meps167137. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 76

  Van SoestR. W. M.Boury-EsnaultN.VaceletJ.DohrmannM.ErpenbeckD.De VoogdN. J.et al. (2012). Global diversity of sponges (Porifera). PloS One7, e35105. doi: 10.1371/journal.pone.0035105. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 77

  VillamizarE.DíazM. C.RützlerK.De NóbregaR. (2014). Biodiversity, ecological structure, and change in the sponge community of different geomorphological zones of the barrier fore reef at Carrie Bow Cay, Belize. PSZN I: Mar. Ecol.35, 425–435. doi: 10.1111/maec.12099. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 78

  WhittakerR. H. (1972). Evolution and measurement of species diversity. Taxon.21, 213–251. doi: 10.2307/1218190

  • CrossRef
  • Google Scholar

• 79

  WilkinsonT.WikenE.Bezaury-CreelJ.HouriganT.AgardyT.HerrmannH.et al. (2009). Ecorregiones marinas de América del Norte (Montreal: Comisión para la Cooperación Ambiental).

  • Google Scholar

• 80

  WilliamsS. M.ChollettI.RoffG.CortésJ.DrydenC. S.MumbyP. J. (2015). Hierarchical spatial patterns in Caribbean reef benthic assemblages. J. Biogeogr.42, 1327–1335. doi: 10.1111/jbi.12509. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 81

  WulffJ. (2001). Assessing and monitoring coral reef sponges: Why and how? Bull. Mar. Sci.69 (2), 831–846.

  • Google Scholar

• 82

  WulffJ. L. (2006). Rapid diversity and abundance decline in a Caribbean coral reef sponge community. Biol. Conserv.127, 167–176. doi: 10.1016/j.biocon.2005.08.007. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 83

  WulffJ. (2016). “ Sponge contributions to the geology and biology of reefs: Past, present, and future,” in Coral Reefs at the Crossroads. Eds. HubbardD. K.RogersC. S.LippsJ. H.StanleyJ. G. D. ( Springer Netherlands, Dordrecht), 103–126.

  • Google Scholar

• 84

  WulffJ. (2017). Bottom-up and top-down controls on coral reef sponges: disentangling within-habitat and between-habitat processes. Ecology98, 1130–1139. doi: 10.1002/ecy.1754. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 85

  WulffJ. L.BussL. W. (1979). Do sponges help hold coral reefs together? Nature281, 474–475. doi: 10.1038/281474a0. PMID:

  • Pubmed Abstract
  • CrossRef
  • Google Scholar