Both small-scale microhabitat preference and large-scale spatial complexity influence coral rubble bed infauna

Both small-scale microhabitat preference and large-scale spatial complexity influence coral rubble bed infauna | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Both small-scale microhabitat preference and large-scale spatial complexity influence coral rubble bed infauna Michelle E Taylor, Alizee Zimmermann, Maria Beger This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9550127/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Globally, coral rubble beds are becoming more prevalent and abundant due to increasing anthropogenic impacts. Despite this, our understanding of the biodiversity and community composition differences of coral rubble organisms is severely lacking. Here, we aim to determine the factors influencing infaunal communities in coral rubble beds in the Turks and Caicos Islands. We collected coral rubble and its associated infauna from 53 sites across the archipelago. Following identification of the specimens, we used logistical regressions models, principal component analyses, and two-way ANOVA to determine if differences in coral rubble biodiversity are influenced by abiotic factors, such as rubble patch size, volume of space within the matrix, and type of rubble present, or biotic factors, such as adjacent habitat. Analysis of the almost 2800 specimens discovered that the highest total specimen abundance is found in smaller rubble patches, and in those with live coral as the closest adjacent habitat. The likelihood of individual phyla presence was influenced by different factors, with very few driving differences in more than one phylum. Our results highlight the complexity of community composition within coral rubble beds and demonstrate that small rubble patches form a valid part of the coral reef ecosystem. Benthic ecology reef degradation reef rubble spatial heterogeneity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Increasing anthropogenic impacts are causing declines of the natural world globally; coral reefs are no exception (IPBES, 2019 ). Ocean acidification, increased frequency and intensity of marine heatwaves, and increased frequency and power of tropical storms have contributed to the loss of almost 14% of coral from coral reefs worldwide between 2009 and 2018 (Souter et al., 2020 ). Following coral mortality, often combined with physical damage from storms or dredging and blast fishing, the living coral framework can become dismantled, resulting in the formation of coral rubble comprised of dead broken corals (Hampton-Smith et al., 2021 ; Kopecky et al., 2024 ). These fragments of coral skeleton can then form into semi-consolidated structures known as coral rubble beds (Kenyon, Doropoulos, et al., 2023 ; Kenyon, Harris, et al., 2023 ). Despite them originating from coral reef degradation, coral rubble still provides an important habitat to many marine organisms (Enochs & Manzello, 2012 ). Coral rubble is a natural habitat that has existed for as long as live coral has (Perry & Hepburn, 2008 ; Scoffin, 1992 ), and coral rubble beds exist in all regions where live coral cover is present. Of the Allen Coral Atlas benthically mapped area, coral rubble extends for half the area of coral reef globally (8.2% and 16% respectively) (Roelfsema et al., 2021 ), demonstrating its importance as a marine habitat. In the Caribbean region, coral rubble covers approximately one third of the area of coral reef (2300 km 2 and 7600 km 2 respectively) (Allen Coral Atlas, 2022 ). While efforts to restore coral reefs have been successful (Lamont et al., 2022 ), the high costs involved means that restoration is not feasible everywhere (Bayraktarov et al., 2016 , 2019 ; Lange et al., 2024 ). Therefore, research into unconsolidated coral rubble beds and their inhabitants is urgently needed as the prevalence of coral rubble beds continues to increase. Coral reefs naturally contain microhabitats, providing distinct niches (Beese et al., 2023 ; Graham & Nash, 2013 ; Risk, 1972 ), which might hold distinct community structures. The characteristics of these microhabitats, including the branch length and interbranch distance of coral structures, benthic type (soft coral, sand, and rubble), available foraging space, and reef type (reef lagoon and reef front), influence the biodiversity and size structure of species found (Depczynski & Bellwood, 2004 ; Ticzon et al., 2012 ; Villegas-Hernández et al., 2022 ; Wehrberger & Herler, 2014 ). Coral rubble bed structures are not homogenous, even on small scales within the same reef area (Masucci et al., 2021 ). Additionally, edge effect predicts that abundance and species richness should be higher in larger habitat patches (Conor & McCoy, 2017 ). It is therefore plausible, but unknown, that differences in coral rubble bed characteristics (rubble type, interstitial space, and mobility) could drive variation in the community structure of associated infauna. Marine organisms have a wide range of habitat requirements that structure habitat partitioning (Ceia et al., 2023 ; Fairclough, 2021 ; Lin et al., 2022 ; Nanami, 2025 ). On coral reefs, scleractinian coral species that offer different microhabitats support very different fish communities (Messmer et al., 2011 ), illustrating that coral reef fish diversity is influenced by individual coral species presence. Both juvenile and adult reef fishes require shelter from predators, often favouring different coral morphologies that reflect the size of refuge provided (Wilson et al., 2008 ). For herbivorous fishes, the available surface area of grazing structure is strongly associated with distribution, indicating that a primary factor driving the distribution is food resource availability (Oakley-Cogan et al., 2020 ; Vercammen et al., 2019 ). Marine invertebrates also require numerous resources, such as shelter, breeding grounds, and nutrition, from their habitat in order to thrive and contribute to the ecosystem services and function (Asante et al., 2023 ; Bugnot et al., 2022 ). Essential resources of food, refuge from predators, and access to mates are widely available on live coral reefs (Hatcher, 1997 ; Kerry & Bellwood, 2012 ). Despite the degraded structure of coral rubble beds, many of these services provided by live coral to coral-associated species may also be able to be provided by coral rubble. Therefore, fully establishing the function of coral rubble beds is essential to understand their role in the wider coral reef ecosystem. Specimen sampling of infauna from coral rubble beds has been limited and has thus far produced contradictory results. Extrapolating patterns from live coral, it would be expected that more complex structures should host a higher abundance and diversity of reef fishes (Almany, 2004 ; Graham & Nash, 2013 ). However, the fish species richness and total abundance on coral reefs at Lizard Island, Great Barrier Reef, Australia, were only weakly correlated to topographic complexity (Komyakova et al., 2013 ). The internal volume of interpolyp space was the most important factor influencing the abundance and richness of crustaceans on coral reefs in Brazil (Nogueira et al., 2015 ), and in the Mexican Tropical Pacific, the highest abundance of Mollusca was recorded on coral substrate (Barrientos-Luján et al., 2021 ). However, reef complexity accounts for very little variability in Arthropoda, Annelida, and Porifera (Newman et al., 2015 ), while sea urchin densities are negatively correlated with structural complexity (Graham & Nash, 2013 ). These differing preferences of marine organisms showcase the complex interactions between coral reef structure and the infauna communities present. Contrary to expectations, the abundance and diversity of macro-crustaceans is higher on degraded reefs than on a coral reef composed of living Acropora palmata in the Mexican Caribbean (González-Gómez et al., 2018 ). In Kenya, nematode communities had a higher diversity in dead coral fragments compared to coral gravel (small, indistinct pieces of coral skeleton), however the coral morphotype did not have an effect on community structure (Raes et al., 2008 ). Crustacean abundance, biomass and estimated productivity was higher in dead coral and coral rubble when compared to sand, epilithic algal matrix, and fine-branching live coral microhabitats on sites at Lizard Island (Kramer et al., 2014 ). The gastropod Conus preferentially shelter in sand- and rubble-filled depressions on reefs during the day before utilising other microhabitats for feeding (Kohn, 1983 ). On the Caribbean coast of Panama, dead coral habitats support a more diverse and abundant mobile invertebrate assemblage than live coral (Nelson et al., 2016 ). Dissolving collected coral skeletons from SW Indian Ocean seamounts found that 34 families of polychaetes lived within the structures (Narayanaswamy et al., 2017 ). This illustrates that further investigations into the inhabitants of dead coral frameworks are essential to fully determine the biodiversity of coral rubble beds. These studies show the importance of these degraded habitats to multiple marine phyla. Limited surveys of coral rubble bed cryptofauna has given us a baseline biodiversity inventory for a minimal number of locations globally. However, the factors influencing differences in community structure remain unknown. This research aims to rectify this by analysing rubble type, depth, adjacent habitats, and interstitial space to determine what factors drive biodiversity differences in coral rubble beds. Here, we conduct the first species diversity analysis of Caribbean coral rubble beds, using the Turks and Caicos Islands as a study site. Specifically, our objectives are to (a) determine what factors influence the total specimen number found within coral rubble; (b) ascertain the factors influencing the presence likelihood of individual phyla in coral rubble; (c) establish what factors affect the abundance of individual phyla within coral rubble, thereby determining if the biodiversity in coral rubble beds is homogeneous across sites. Methods Sampling area and experimental design We conducted our field study during the summer of 2022 and 2023 in the Turks and Caicos Islands which are located in the northern Caribbean. We selected 53 coral rubble sites from around five of the islands within the archipelago – East Caicos, Grand Turk, North Caicos, Providenciales, and South Caicos (Fig. 1 ). The sites were chosen to cover a variety of water depths and a range of adjacent habitats (live coral, sand, seagrass, and rock). Due to the geographical spread of the sample sites, localised anthropogenic factors differed at each of the islands. Using a 30 cm x 30 cm quadrat, we collected three replicate samples of coral rubble and associated infauna on each SCUBA dive from water depths of 1.1 to 18.7 m. Rubble fragments and infauna were collected to a depth of approximately 15 cm and the depth of collected matrix was measured to allow the volume of coral rubble to be calculated. Due to the small patch size of the coral rubble beds, we were unable to use a systematic sampling design. To ensure the samples were independent, we did not remove more than one sample per rubble patch if the area was less than 1 m 2 . All coral rubble bed quadrats that we sampled from one site were taken from within a 100 m 2 area. Each site was at least 100 m away from any other sites sampled. Once the quadrat had been randomly placed on the coral rubble (Fig. 2 a), we noted the water depth, before photographing the quadrat and surrounding area to analyse for coral rubble type (branching, massive, or a mixture) and the presence of interstitial spaces. Following the American Veterinary Medical Association euthanasia guidelines, we sprayed a mixture of ethanol (95%) and clove bud oil over the quadrat and into the matrix of the coral rubble to temporarily stun the infauna and allow collection of the specimens. We then collected all the coral rubble fragments and organisms that were inside the quadrat and sealed them into a WhirlPak bag, to ensure the mobile animals did not escape whilst we brought them to the surface (Fig. 2 b). This collection method will slightly underestimate the abundance and diversity of the coral rubble infauna, as numerous motile organisms were able to move through the matrix to avoid capture. We particularly noted that Ophiuroidea (brittle stars) were barely affected by the clove bud oil and were very difficult to collect, because they quickly moved out of the quadrat area into the surrounding coral rubble. Most reef fishes moved out of the collection area as the divers approached, so any fish collected were opportunistic and do not give a true representation of the species using the habitat. Once the coral rubble and infauna were collected from the quadrat, we then measured the depth of rubble that had been collected to give a total volume of the sample (Fig. 3 ). Finally, we mapped and measured the coral rubble patch size and distance of the sampled quadrats to the adjacent habitats. Rubble patches were categorised as small S (≤ 1 m 2 ), medium M (1 ≤ 10 m 2 ), large L (10 < 100 m 2 ), or extra-large XL (≥ 100 m 2 ). The adjacent habitats were categorised as either live coral reef, rock, seagrass bed, or sand. If two habitats were equidistant to the sampled quadrat, we combined them as a category (coral/rock, sand/rock, sand/rock/seagrass). On the surface, we removed each coral rubble fragment from the WhirlPak bag and rinsed the pieces with fresh water over a 75 µm mesh filter to collect all visible organisms. We used tweezers to remove algae from the fragments to ensure no organisms were missed in the collection. Each collected specimen was given a unique identification number and photographed individually (Bresser USB digital microscope DST-1028) before being preserved in 99% ethanol and identified to the lowest taxonomic group possible (Fig. 2 c). We anticipate that all organisms over 0.5 mm in length were collected. We then selected 950 of the collected specimens (from Annelida, Arthropoda, Chordata, Cnidaria, Echinodermata, Mollusca, and Porifera phyla) to be DNA barcoded at the Canadian Centre for DNA Barcoding (CCDB) at the University of Guelph, Canada. Specimens were selected to give a comprehensive representation of the collected organisms. We used a variety of primers (selected for their specimen phylum relevance) and targeted the COI mitochondrial gene (Supplementary Table S1 ). All our collected specimens have now been curated into the permanent collection at the Natural History Museum of Los Angeles County. We also photographed all the collected coral rubble pieces to allow size measurements to be taken (Fig. 2 d). Using Image J (version 1.54p), we measured the length (longest span in any direction) and width (perpendicular to length) to the nearest 1 mm. We categorised the rubble fragments as branching (identified by rubble shape), massive (identified by size and/or presence of coral polyps that indicated the coral genus), shell (included mollusc shells and worm tubes), rock (where it was clear calcification had occurred), or other (where the source was not clear) (Fig. 3 ). We measured the volume of the coral rubble fragments using the displacement method (Frings et al., 2011 ; Scherle, 1970 ) (Fig. 2 e), allowing the interstitial space that was present in the coral rubble bed before the fragments were removed to be estimated (Gee & Bauder, 1986 ). Using the depth of rubble collected and the approximate volume of the individual rubble pieces, we were able to create an estimate of free space within the matrix of each rubble sample site (Fig. 2 f). This approach then allowed each quadrat to be categorised both in terms of most prevalent rubble type present and in volume of interstitial space available to mobile cryptofauna. Statistical analysis To determine the factors which influence the total specimen abundance, we ran a linear model and Tukey post hoc tests. We used a logistical regression model to investigate the relationship between factors and the presence/absence of individual phyla. We used multivariable logistical regression to compare multiple predictors to individual phyla presence likelihood. Then to compare the abundance of individual phyla to rubble patch size and adjacent habitat, we used a two-way ANOVA and Tukey pairwise post hoc test (using the “emmeans” package version 1.11.1). Finally, we used principal component analysis and PERMANOVA (Bray-Curtis dissimilarity) (using “vegan” package version 2.6-4) to investigate the effect of rubble patch size and adjacent habitat on the phyla composition. All statistical analyses were carried out in R (version 4.3.1). We determined significance at a 95% confidence level. Results Total specimen number In total, 2,769 specimens were collected from the coral rubble beds in the Turks and Caicos Islands, with a total organism density of 193.5 organisms m − 2 . With 1,887 specimens (68.1%), Annelida was the most abundant phylum, followed by Arthropoda (224; 8.8%), Mollusca (230; 8.3%) and Echinodermata (213; 7.7%). Chordata, Cnidaria, Nemertea, Porifera or unidentified composed the remaining 7.2% of collected specimens. The total number of coral rubble infauna specimens per site was influenced by a number of factors. Total specimen abundance decreased with increasing rubble patch size (F = 18.88, p < 0.01), with XL rubble patches (≥ 100 m 2 ) having almost half the number of specimens on average (10.9 specimens per 0.09 m 2 quadrat) compared to all patches smaller than 100 m 2 (19.3–19.6 collected specimens per 0.09 m 2 quadrat). The percentage of each rubble type within the quadrat also influenced the total number of collected specimens. With increasing percentage of “other” (usually small rubble fragments with unidentifiable morphology), there was a significant increase in specimen count (F = 4.86, p = 0.029). A higher percentage presence of rock pieces within the sampled quadrat was linked to slight decrease in total specimen count (F = 4.16, p = 0.043). There was no significant difference in total specimen count when compared to the percentage of branching and massive rubble pieces present. The adjacent habitat to the sampled coral rubble was significant in driving the total number of specimens collected. The highest mean number of specimens collected were from quadrats that had live coral as the closest adjacent habitat (mean = 23.7 specimens per 0.09 m 2 quadrat), while quadrats that lacked an adjacent habitat within 25 m, because they were in large rubble patches, had the lowest number of specimens (mean = 4.5 specimens per 0.09 m 2 quadrat). Rubble patches with sand as the closest adjacent habitat had fewer specimens (mean = 7.2 specimens per 0.09 m 2 quadrat) than live coral (mean = 23.7 specimens per 0.09 m 2 quadrat; p = 0.0003), equally distanced live coral and rock (mean = 19.7 specimens per 0.09 m 2 quadrat; p = 0.039), and rock (mean = 18.3 specimens per 0.09 m 2 quadrat; p = 0.013). However, the distance from the sampled quadrat to the closest live coral does not affect the total number of specimens found within coral rubble (individual coral colonies: p = 0.055; coral reef: p = 0.22). With increasing distance from the sampled quadrat to sand, we observed a slight increase in the total number of specimens collected (p = 0.025), while with increasing distance to hard bedrock, the total number of specimens decreased (p = 0.028). Distance to the closest individual coral colony, reef, and/or seagrass did not influence total specimen abundance. The overall quadrat volume and total volume of rubble fragments within the quadrat were both very strong predictors of the total number of specimens present. Increased quadrat volume (cm 3 ) and rubble volume (cm 3 ) increases the total number of specimens (F = 32,720, p < 2.2e-16 and F = 31,360, p < 2.2e-16 respectively). However, despite varying widely, the mean volume, length, and width of individual rubble pieces, number of rubble fragments within the quadrat, volume of interstitial space, percentage of available space within the rubble matrix, and water depth did not affect the total number of specimens (Supplementary Table S2). Differences in total specimen count exist between individual sites but not between islands surveyed. Presence likelihood of individual phyla Individual phyla presence is determined by various factors (Supplementary Table S3). Prevalence of the collected phyla showed the same pattern as abundance. Annelida was the most prevalent phylum, being collected from 96.2% of the sites, followed by Arthropoda (94.3%), Mollusca (92.5%), Echinodermata (77.4%), Porifera (49.1%), Chordata (41.5%), Nemertea (15.1%), and Cnidaria (7.5%). Annelida The likelihood of Annelida presence in coral rubble increases as the quadrat volume (depth of rubble surveyed) increases (β = 0.0008, p = 0.0015), and as the rubble patch size decreases (β = -0.0008, p = 0.034). Likelihood of Annelida presence also increases with increased mean rubble fragment volume (β = 0.0114, p = 0.021), increased mean rubble fragment length (β = 0.814, p = 0.031), and larger mean rubble fragment width (β = 1.466, p = 0.040). Rubble type significantly influences the presence of Annelida, with an increased likelihood of Annelida occurrence in branching rubble (β = 2.890, p < 0.0001) and a decreased likelihood in shell/branching rubble (β = -2.890, p = 0.019). The composition of the rubble fragments also influences the likelihood of Annelida presence. With increasing proportion of shells (β = 0.064, p = 0.0006), and rock fragments (β = -0.402, p = 0.001) the likelihood of Annelida presence decreases. There is a significant positive association between “other” (unidentifiable) rubble pieces and Annelida presence (β = 0.043, p = 0.014). However, when compared in a multivariable logistical regression model, the proportion of rubble composed of shell and rock fragments was significantly negatively associated with Annelida presence (shell: β = -0.070, p = 0.0014; rock: β = -0.049, p = 0.0011), while the proportion of the unidentifiable fragments did not show a significant result (β = 0.047, p = 0.101). The likelihood of Annelida presence also is influenced by distance to adjacent habitats. With increasing distance from coral and rock, the likelihood of Annelida presence decreases significantly (β = -0.313, p = 0.003 and β = -0.348, p = 0.006 respectively). Annelida are also more likely to be present when interstitial space is increased (β = 0.0006, p = 0.004), rubble volume is increase (β = 0.0009, p = 0.041), and number of rubble fragments within the quadrat decreases (β = -0.041, p = 0.002). Arthropoda The only factor with a significant influence on the likelihood of Arthropoda presence is adjacent habitat type. Arthropoda presence was significantly lower in samples adjacent to rubble (within large rubble beds with no other habitat within 25 m) (β = -2.485, p = 0.045) and sand (β = -2.213, p < 0.001), compared to the coral reference. Rock and seagrass did not influence Arthropoda presence (β = -0.945, p = 0.069 and β = -1.792, p = 0.079, respectively). Chordata Chordata presence is not significantly influenced by rubble patch size, rubble type, water depth, quadrat volume, rubble fragment abundance, interstitial space, or rubble fragment size. The mean volume of shell fragments within the sampled quadrat does have a significant influence on Chordata presence, with increasing mean volume increasing the likelihood of presence (β = 0.022, p = 0.034). However, the small sample size of Chordata is likely to have affected these results. Cnidaria Cnidaria presence is not significantly influenced by rubble patch size, rubble type, water depth, quadrat volume, rubble fragment abundance, interstitial space, or rubble fragment size. The percentage of available space within the sampled quadrat does have a significant influence on Cnidaria presence, with increasing percentage of available space the likelihood of Cnidaria presence decreases (β = -0.053, p = 0.014). However, the small sample size of Cnidaria is likely to have affected these results. Echinodermata There is a significant negative relationship between rubble patch size and the presence of Echinodermata (β = -0.0007, p = 0.0025). However, Echinodermata presence is not significantly affected by rubble type, water depth, quadrat volume, rubble fragment abundance, interstitial space, or rubble fragment size. Mollusca There is a significant negative relationship between rubble patch size and the presence of Mollusca (β = -0.0006, p = 0.0042). Rubble patches ≥ 100 m 2 (category XL) were significantly less likely to contain Mollusca (p = 0.031). Conversely, Mollusca presence is not significantly affected by rubble type, water depth, quadrat volume, rubble fragment abundance, interstitial space, or rubble fragment size. Nemertea There is a significant positive relationship between the number of rubble fragments within a sample quadrat and the presence of Nemertea. As the number of rubble fragments increases the likelihood of Nemertea presence also increases (β = 0.003, p = 0.041). There is also a significant negative association between mean length of rubble fragment pieces and Nemertea presence, with likelihood decreasing as mean length increases (β = -1.054, p = 0.043). However, due to the small sample size these influences are weak. Nemertea presence is not significantly affected by rubble type, water depth, quadrat volume, interstitial space, rubble patch size, or rubble fragment size. Porifera There is a statistically significant positive relationship between interstitial space and Porifera presence (β = 0.00012, p = 0.049), indicating that Porifera are more likely to occur in areas with greater interstitial space. Adjacent habitat type also has a significant influence on the likelihood of Porifera presence. Porifera presence was significantly lower in samples adjacent to rock (β = -1.147, p = 0.014). Likelihood of presence is increased with decreasing distance to the nearest live coral colony (β = -0.336, p = 0.021). No other factors influenced the likelihood of Porifera presence. Other (unidentifiable specimens) Water depth has a significant negative association with presence of “other” phyla (β = -0.215, p = 0.0009). A rubble patch size of 1.1–10 m 2 (category M) has a lower likelihood of “other” phyla presence when compared to the other size categories (p = 0.046). The smallest rubble patch size category (≤ 1 m 2 ) also shows a marginal negative association with the presence of “other” phyla, but it is not significant (p = 0.077). Quadrats containing mostly massive rubble pieces also showed a lower likelihood of “other” phyla presence (p = 0.031). No other factors influenced the likelihood of “other” phyla presence. Phyla abundance Individual phyla abundance is affected by different factors. Significant differences in organism count exist among patch sizes (F (3, 1395) = 4.80, p < 0.001), and as an interaction of patch size and phylum (F (24, 1395) = 3.07, p < 0.001) (Supplementary Table 4) (Fig. 4 a). Each rubble patch size has a distinct phyla composition (Fig. 5 a), with significant differences between extra-large XL rubble patches (≥ 100 m 2 ) and small S (≤ 1 m 2 ) (p = 0.007), medium M (1 ≤ 10 m 2 ) (p = 0.009), and large L (10 < 100 m 2 ) (p = 0.019). Both PC1 and PC2 axes explain gradients in the community structure (62.64% and 25.87% respectively), with PC1 being primarily driven by the relative abundance of Chordata, Mollusca, and Porifera, while variation along PC2 was driven by Cnidaria and Echinodermata (Fig. 5 a). A PERMANOVA (Bray-Curtis dissimilarity) shows marginal differences in species composition across patch types (F = 1.53, R² = 0.03, p = 0.094), indicating that patch size explains a small but potentially meaningful proportion of variation. Adjacent habitat also has a significant effect on organism abundance (F (7, 1359) = 5.23, p < 0.001), with a significant interaction between adjacent habitat and phylum also present (F (56, 1359) = 2.96, p < 0.001) (Supplementary Table S5) (Fig. 4 b). Quadrats with seagrass, sand/rock/seagrass, sand/rock and rubble as the adjacent habitat are more closely related in phyla abundance than rock, sand, coral, and coral/rock (Fig. 5 b). Both PC1 and PC2 axes explain major variance in the taxonomic composition (80.82% and 14.8% respectively). PC1 captures the most significant pattern in community composition, with all phyla contributing in the positive direction. Mollusca is strongest driver of variation along PC2, with Cnidaria also notably contributing but in the negative direction (Fig. 5 b). A PERMANOVA (Bray-Curtis dissimilarity) shows that adjacent habitat explains a small but significant proportion of the variation (F = 1.70, R 2 = 0.08, p = 0.009), confirming that the adjacent habitat to coral rubble influences differences in phyla composition. Annelida Annelids are more abundant in quadrats that are adjacent to coral (mean = 16) than rock (mean = 12.8, p = 0.006), rubble (mean = 3.5, p < 0.0001), sand (mean = 4, p < 0.0001), and seagrass (mean = 2.4, p < 0.0001). Annelids are also more abundant in quadrats which are adjacent to coral/rock (mean = 14.2) than rubble (p < 0.0001), sand (p < 0.0001), and seagrass (p < 0.0001). Quadrats adjacent to rock contain more annelids than those adjacent to rubble (p = 0.0001), sand (p < 0.0001), and seagrass (p < 0.0001). However, annelids were more abundant in quadrats which were equal distance to sand and rock (mean = 15.5) than rubble (p = 0.0001), sand (p < 0.0001) and seagrass (p < 0.0001) (Supplementary Table S6). The highest abundance of Annelida is in M sized rubble patches (mean = 15.2), almost double of that found in XL sized rubble patches (mean = 8). The XL rubble patch category has significantly less abundance of Annelida than S (p < 0.0001), M (p < 0.0001), and L (p < 0.0001) (Supplementary Table S7). Other Phyla Multiple factors contribute to differences in abundance of Arthropoda, Chordata, Cnidaria, Echinodermata, Mollusca, Nemertea, Porifera and unidentified specimens. Despite differences in mean abundance when adjacent habitats are compared, none are significant (Supplementary Table S5). The abundance of individual phyla is also not significantly different when compared to rubble patch size (Supplementary Table S6). Some of the insignificant results are likely due to the small sample sizes. Discussion Coral rubble beds support a high number of associated taxa which occupy the habitat. Here, we show that both rubble patch size and type, and adjacency to live habitat, influence the abundance and diversity of coral rubble bed infauna. Total specimen abundance was lowest in the extra-large rubble patches. High rubble fragment volume and deep quadrat depth correlated with high total specimen abundance. Rubble fragment type influenced the total specimen abundance, with a higher specimen count found in quadrats with a higher percentage of small, morphologically unidentifiable rubble fragments, compared to other types of fragments. The adjacent habitat to rubble patches significantly influenced the total specimen abundance, with most organisms present in rubble closest to live coral. Individual phyla abundance was driven by different factors, with only rubble patch size and number of fragments affecting the likelihood of multiple phyla being present. Total specimen abundance The total abundance of coral rubble infauna is strongly influenced by various small-scale physical habitat characteristics. Small rubble patch size supports a significantly higher specimen count than larger patches, potentially suggesting higher habitat heterogeneity in the smaller rubble patches. Edge effect and the Area Per Se hypothesis would account for the opposite trend, with smaller patches having a lower abundance of specimens (Conor & McCoy, 2017 ). We show that extra-large XL (≥ 100 m 2 ) rubble patch sizes had nearly half the infaunal density of smaller patches. Contrastingly, in algal beds, polychaetes, amphipods and ostracods occurred in low abundances in small patches following colonisation, which is also inconsistent with traditional predications using edge effect (Roberts & Poore, 2006 ). Terrestrial habitats show the same pattern, with species richness and abundance increasing with patch size. This is likely due to resource limitation and competition (Lawrence et al., 2018 ), and extinction probability decreasing with increasing patch size because large patch sizes can maintain large population sizes (MacArthur & Wilson, 2001 ; Mortelliti et al., 2014 ). Therefore, the differences in infaunal abundance in varying coral rubble bed patch sizes does not follow expected trends. Colonisation at remote sites is lower than at non-remote (Barnes, 2017 ), likely due to the dispersal challenges of reaching suitable habitat over long distances. The lower total specimen abundance found in larger rubble patches could also be explained by the increased distance infauna needs to cover to move into the area. Regardless of pelagic larval duration, both invertebrates and fish species have the most successful dispersal over short distances (Becker et al., 2007 ; Conklin et al., 2018 ; Sammarco & Andrews, 1988 ). Therefore, low colonisation efficiency is likely to be driving the lower abundance in larger rubble patches. Rubble volume and quadrat depth were the most robust predictors of total specimen abundance, with rubble volume and quadrat depth being directly proportionally related to total specimen abundance, underscoring the importance of three-dimensional structure in coral rubble bed infaunal community assemblages. Previously, a comparison of 2D and 3D surveys on coral reefs showed the importance of including cryptic reef habitats to ensure representative biomass, abundance, and diversity estimates (Kornder et al., 2021 ), emphasising the importance of these cryptic species to the coral reef habitat. Typically, living corals create the large benthic structures that directly affect the ecosystem function of the habitat. Light availability, habitat provisioning, productivity, and ecosystem biodiversity is determined by the 3D structural complexity (Burns et al., 2019). The strongest and most consistent predictor of reef fish biomass, abundance, species richness and trophic structure is structural complexity and reef zone category (Darling et al., 2017 ). Similarly, topographical complexity on coral reefs in the U.S. Virgin Islands explained the variation seen in the diversity of conspicuous invertebrates, however processes independent of coral traits also play an important role in determining the community structure (Idjadi & Edmunds, 2006 ). The main structuring factor of polychaete populations is habitat structure, with the highest structural complexity at the microhabitat level containing the highest richness and diversity of polychaete species (Miri et al., 2023 ; Serrano & Preciado, 2007 ). Extrapolating the knowledge of structural complexity on coral reefs to coral rubble, it would be expected that samples with higher complexity should have a greater abundance of infauna. Since deep quadrat depth and high rubble volume could be described as a higher structural complexity, as more interstitial spaces create complex habitats in such rubble beds, it explains why a higher abundance of infauna is found in deep rubble with high rubble volume. The composition of rubble type and size within the sample also affected infaunal abundance; for example, high percentages of small, morphologically unidentifiable rubble fragments were associated with a high total specimen count, while large proportions of rock fragments present in the quadrat were associated with modest declines. Studies on tropical invertebrate coral infauna influenced by habitat type and rugosity are lacking. However, density and biomass of epifauna > 0.5 mm found in rocky reef habitats in New Zealand did show differences among different habitats, with highest values in sites with algal presence (Taylor, 1998 ). Furthermore, reef fish assemblages on rocky reefs in the Gulf of California did not differ between habitats of different rock sizes (Aburto-Oropeza & Balart, 2001 ). Microhabitat structure on subtidal rocky reefs influenced the variation of invertebrate assemblages, with larger surface area explaining the most variation (Alexander, 2013 ). Similarly, within our samples, smaller fragments of rubble would have a larger surface area and thus could explain the higher specimen count observed. These findings highlight that both quantity and quality of the physical habitat is critical in shaping coral rubble bed infaunal assemblages. Beyond the physical characteristics of the sampled rubble bed, the larger-scale spatial context of a coral rubble bed also played a key role in determining infaunal abundance. Quadrats closest to live coral yielded the highest specimen counts, while those lacking any adjacent habitat within 25 meters—typically found in large and extra-large rubble fields—had the lowest number of specimens. This finding suggests that recruitment and retention of species may be enhanced by adjacent habitats to rubble beds, potentially through spillover effects. Both larval dispersal and recruitment of marine invertebrates influences their abundance, diversity, and richness, which in turn influences ecological stability (Holstein, 2014 ). Local and regional oceanographic patterns and biotic factors (such as abundance of microbial bio-films and proximity to conspecific adult) affect the recruitment of invertebrates (Hadfield, 2011 ; Karlson & Hurd, 1993 ). Monitoring recruitment of dead coral branches in the Central Mexican Pacific found that there is a temporal trend with higher recruitment in warmer months, however malacostracans, ostracods, gastropods and polychaetes were all commonly observed, regardless of water temperature (Rodríguez-Troncoso et al., 2019 ). Our samples were all collected in the summer months (July and August), which might have been during the main recruitment phase, however we do not anticipate this to have affected the overall survey results. Although proximity to live coral communities was important, the actual distance to the nearest colony did not significantly influence the total abundance of infauna, indicating that it is the presence not proximity of the coral habitat that is the influential factor. Therefore, small, isolated patches of coral rubble, even when they are not directly adjacent to live coral, may be the most important form of the habitat for reef regeneration and colonisation following disturbance, since the greatest abundance and diversity is found there. Overall, these results highlight the importance of both small-scale habitat complexity and large-scale location within the wider coral reef ecosystem, in determining the overall abundance of coral rubble bed infauna. Phyla abundance Multiple factors were influential in the presence likelihood of different phyla; however, very few factors influenced more than one phylum. Twelve factors (quadrat volume (cm 3 ), rubble type, rubble patch size (m 2 ), percentage composition of rubble fragment types, number of rubble fragments, rubble volume (cm 3 ), rubble fragment dimensions, and distance to adjacent habitat) were significantly influential in determining the likelihood of Annelida presence, whilst the other phyla were only determined by fewer than four factors: Arthropoda = 2, Cnidaria = 1, Chordata = 1, Echinodermata = 1, Mollusca = 1, Nemertea = 2, Porifera = 3, Other = 4. The low prevalence of Cnidaria, Chordata, and Nemertea are likely why there are limited significant determining factors. Only four factors determined the likelihood of presence of more than one phylum – distance to nearest coral, interstitial space, number of rubble pieces within the quadrat, and rubble patch size. Small isolated patches are incredibly important for biodiversity conservation (Wintle et al., 2019 ), showcasing the need to understand and protect the infauna found in rubble patches of all sizes. The probability of detecting Annelida is significantly greater in quadrats with greater volume/depth, more available interstitial space, and when rubble pieces are larger and less numerous. In these situations, there is a greater surface area available for colonisation and an expanded habitat complexity is thus present. Colonisation of fresh rubble fragments after a disturbance will likely follow the typical coral reef succession pattern, with primary colonisers of bacteria, protozoans, diatoms, algae, and invertebrate larvae settling first (Somma et al., 2023 ). A greater volume of benthic community will lead to a greater accumulation of organic matter over time, compared to a baseline. In deeper rubble there is also more space for organic matter accumulation, which provides a greater source of nutrition to the rubble inhabitants. Both, greater benthic community volume and the subsequent organic matter accumulation could be the driving influence for Annelida presence patterns seen in varying rubble depth and fragment size. The type and composition of fragments within the rubble also plays a critical role in the likelihood of phylum presence. A higher percentage of branching coral fragments within the matrix significantly supports Annelida occurrence, likely due to the high structural complexity it creates. A higher percentage of shell pieces and rock fragments within the matrix is less favourable for Annelida, potentially reflecting the substrate instability and reduced burrowing potential. Members of 11 annelid families almost exclusively exist in interstitial environments (Worsaae et al., 2021 ), highlighting the importance of available space to this group of marine organisms. Polychaete samples taken from Cabo Pulmo, Mexico, found 82 species belonging to 61 genera and 21 families in dead Pocillopora verrucosa coral (Bastida-Zavala, 1995 ), while 82 species from 19 families were found on coral reefs in Central America (Dean, 2009 ), showing the high diversity of Annelida that can inhabit coral rubble. The trends seen in Annelida presence likelihood highlights the specific microhabitat preferences within the coral rubble matrix and suggests that not all rubble complexes offer equal ecological value for this group. Polychaete abundance and size in the Mexican Caribbean is larger in the back reef, suggesting that increased rubble movement influences the community composition (Hepburn et al., 2004 ). The percentage composition of rubble did not influence the presence likelihood of any other phyla. This does not mean that the other phyla have no microhabitat preferences, but likely is a result of limited sample specimens collected. While depth is widely recognized as a key driver of marine community structure, its limited influence in this study suggests that biological interactions may play a more dominant role in shaping phylum-level assemblages. Water depth drives assemblage structure of fish, invertebrate, and benthic communities (Bergen et al., 2001 ; Costa et al., 2024 ; Heidmann et al., 2024 ; Saeedi et al., 2022 ). Therefore, it was unexpected that water depth was only a significant influencer on the presence likelihood of “other” phyla. In over 94% of the sites (almost 84% of individually sampled quadrats), Annelida was the most abundant phylum collected (Taylor, Zimmermann & Beger, 2026 in prep). In sandy beach sediment, the presence of polychaete Scolelepis squamata inhibited the density development of Nemertea species (Maria et al., 2011 ), suggesting that fauna abundance and diversity can be controlled by biological interactions. In the sampled coral rubble beds, the high abundance of Annelida may have been dominating the habitat, reducing the abundance of other phyla. The differences seen in organism abundance by rubble patch size, adjacent habitat, and the interaction of patch size and adjacent habitat with phylum indicates that both are key factors influencing the abundance patterns in coral rubble beds. Annelida abundance was greatest in rubble patches which were adjacent to coral than another other habitat, and in category medium M patch sizes (1.1–10 m 2 ), and lowest in extra-large XL patch sizes (≥ 100 m 2 ) and quadrats with seagrass, sand or rubble as the adjacent habitat. No other phyla had a significant difference in abundance in different rubble patch sizes or samples taken from rubble with differing adjacent habitats. Although the influence of patch size and adjacent habitat on Annelida abundance is consistent with the total specimen abundance, it is likely that the high proportion of Annelida in the total specimen count accounts for this. Spatial patterns of intertidal invertebrate abundance vary on scales of centimetres to hundreds of metres. Small scale differences are likely due to behavioural responses to microhabitats, whilst large-scale differences are influenced by recruitment and mortality due to the limited adult dispersal (Underwood & Chapman, 1996 ). In coral rubble, we are likely seeing the effect of small-scale microhabitat preference within the rubble patches. Yet, among patches, the abundance and distribution of species is probably driven by recruitment from nearby adjacent habitats when the rubble is first formed and then from within the rubble once the patch is established. Surveys on Panulirus guttatus (Caribbean spiny lobster) in Mexico showed that lobster density did not vary with reef complexity, however their diet included significantly more crustaceans in the less complex reef patch (Lozano-Álvarez et al., 2017 ). This suggests that although shelter is an important driver in microhabitat preference, it is likely not the most influential. Conclusion Overall, our results emphasise that coral rubble bed infaunal communities are shaped not only by microhabitat complexity, but also by the surrounding habitat matrix. The physical rubble fragment characteristics are important to both the presence likelihood and abundance of multiple phyla. Whilst the broader spatial context of coral rubble is highly influential in both the total abundance of infauna and in individual phylum occurrence. Additional studies including more samples of the less dominant marine groups are needed to fully understand the effects of the physical, biological, and ecological characteristics of coral rubble beds on their associated infauna. Declarations Competing Interest Statement: No competing interests. Author Contribution All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by M.E.T. Funding acquisitions were made by M.E.T. and A.Z. The first draft of the manuscript was written by M.E.T. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgement We would like to thank the staff and interns at the Turks and Caicos Reef Fund for their assistance in the field data collection. We would also like to thank L. Harris, G. Paulay, J. Lang and G. Hendler for their assistance in identifying the collected specimens.Research was conducted under the Department of Environment and Coastal Resources (DECR) Turks and Caicos Islands Scientific Research Permit #2023-04-17-20 and #2022-06-07-27. Data Availability Data deposition information itemGenetic data: Stored in BOLD Systems. Code “TCICR”. Title “Biodiversity of Coral Rubble Beds in Turks and Caicos Islands”.Observation and collected specimen data: Stored in Mendeley Data. Title “Biodiversity of Coral Rubble Beds in Turks and Caicos Island”. References Aburto-Oropeza, O., & Balart, E. F. (2001). Community Structure of Reef Fish in Several Habitats of a Rocky Reef in the Gulf of California. Marine Ecology , 22 (4), 283–305. https://doi.org/10.1046/j.1439-0485.2001.01747.x Alexander, T. J. (2013). Cryptic invertebrates on subtidal rocky reefs vary with microhabitat structure and protection from fishing. 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Effects of habitat structure on the epifaunal community in Mussismilia corals: Does coral morphology influence the richness and abundance of associated crustacean fauna? Helgoland Marine Research , 69 (2), 221–229. https://doi.org/10.1007/s10152-015-0431-x Oakley-Cogan, A., Tebbett, S. B., & Bellwood, D. R. (2020). Habitat zonation on coral reefs: Structural complexity, nutritional resources and herbivorous fish distributions. PLOS ONE , 15 (6), e0233498. https://doi.org/10.1371/journal.pone.0233498 Perry, C. T., & Hepburn, L. J. (2008). Syn-depositional alteration of coral reef framework through bioerosion, encrustation and cementation: Taphonomic signatures of reef accretion and reef depositional events . 86 (1–4), 106–144. Raes, M., Decraemer, W., & Vanreusel, A. (2008). Walking with worms: Coral-associated epifaunal nematodes. Journal of Biogeography . Risk, M. J. (1972). Fish Diversity on a Coral Reef in the Virgin Islands. 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Frontiers in Marine Science , 8 , 643381. https://doi.org/10.3389/fmars.2021.643381 Saeedi, H., Warren, D., & Brandt, A. (2022). The Environmental Drivers of Benthic Fauna Diversity and Community Composition. Frontiers in Marine Science , 9 . https://doi.org/10.3389/fmars.2022.804019 Sammarco, P. W., & Andrews, J. C. (1988). Localized dispersal and recruitment in great barrier reef corals: The helix experiment. Science (New York, N.Y.) , 239 (4846), 1422–1424. https://doi.org/10.1126/science.239.4846.1422 Scherle, W. (1970). A simple method for volumetry of organs in quantitative stereology. Mikroskopie , 26 (1), 57–60. Scoffin, T. P. (1992). Taphonomy of coral reefs: A review. Coral Reefs , 11 (2), 57–77. https://doi.org/10.1007/BF00357423 Serrano, A., & Preciado, I. (2007). Environmental factors structuring polychaete communities in shallow rocky habitats: Role of physical stress versus habitat complexity. Helgoland Marine Research , 61 (1), Article 1. https://doi.org/10.1007/s10152-006-0050-7 Somma, E., Terlizzi, A., Costantini, M., Madeira, M., & Zupo, V. (2023). Global Changes Alter the Successions of Early Colonizers of Benthic Surfaces. Journal of Marine Science and Engineering , 11 (6), Article 6. https://doi.org/10.3390/jmse11061232 Souter, D., Planes, S., Wicquart, J., Logan, M., Obura, D., & Staub, F. (2020). Status of Coral Reefs of the World: 2020 . Taylor, R. B. (1998). Density, biomass and productivity of animals in four subtidal rocky reef habitats: The importance of small mobile invertebrates. Marine Ecology Progress Series , 172 , 37–51. https://doi.org/10.3354/meps172037 Ticzon, V. S., Mumby, P. J., Samaniego, B. R., Bejarano-Chavarro, S., & David, L. T. (2012). Microhabitat use of juvenile coral reef fish in Palau. Environmental Biology of Fishes , 95 (3), 355–370. https://doi.org/10.1007/s10641-012-0010-9 Underwood, A. J., & Chapman, M. G. (1996). Scales of spatial patterns of distribution of intertidal invertebrates. Oecologia , 107 (2), 212–224. https://doi.org/10.1007/BF00327905 Vercammen, A., McGowan, J., Knight, A. T., Pardede, S., Muttaqin, E., Harris, J., Ahmadia, G., Estradivari, Dallison, T., Selig, E., & Beger, M. (2019). Evaluating the impact of accounting for coral cover in large‐scale marine conservation prioritizations. Diversity and Distributions , 25 , 1564–1574. https://doi.org/10.1111/ddi.12957 Villegas-Hernández, H., González-Salas, C., Guillén-Hernández, S., & Poot-López, G. (2022). Recruitment dynamics and microhabitat selectivity of coral-reef fishes at three sites in the Mexican Caribbean. Environmental Biology of Fishes , 105 (6), 753–773. https://doi.org/10.1007/s10641-022-01291-z Wehrberger, F., & Herler, J. (2014). Microhabitat characteristics influence shape and size of coral-associated fishes. Marine Ecology Progress Series , 500 . https://doi.org/10.3354/meps10689 Wilson, S. K., Burgess, S. C., Cheal, A. J., Emslie, M., Fisher, R., Miller, I., Polunin, N. V. C., & Sweatman, H. P. A. (2008). Habitat utilization by coral reef fish: Implications for specialists vs. generalists in a changing environment. Journal of Animal Ecology , 77 (2), 220–228. https://doi.org/10.1111/j.1365-2656.2007.01341.x Wintle, B. A., Kujala, H., Whitehead, A., Cameron, A., Veloz, V., Kukkala, A., Moilanen, M., Gordon, A., Lentini, P. E., Cadenhead, N. C. R., & Bekessy, S. A. (2019). Global synthesis of conservation studies reveals the importance of small habitat patches for biodiversity. Proceedings of the National Academy of Sciences of the United States of America , 116 (3). https://doi.org/10.1073/pnas.1813051115 Worsaae, K., Kerbl, A., Domenico, M. D., Gonzalez, B. C., Bekkouche, N., & Martínez, A. (2021). Interstitial Annelida. Diversity , 13 (2), 77. https://doi.org/10.3390/d13020077 Additional Declarations No competing interests reported. Supplementary Files DifferencesincoralrubblebedbiodiversityCRSM.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 11 May, 2026 Reviewers agreed at journal 04 May, 2026 Reviewers invited by journal 04 May, 2026 Editor assigned by journal 02 May, 2026 Submission checks completed at journal 29 Apr, 2026 First submitted to journal 28 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9550127","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":638012341,"identity":"f50c25fc-bd35-485f-8a0b-6f78539c7d6d","order_by":0,"name":"Michelle E Taylor","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIie3PMQrCMBTG8VcCcYl0TRDqCYQngergYeri5ODoICgIdSnO9RyCs1CIS0FvYEHo3NFBxaibQ5tuIvlvb/jx8QBstl+MAAWY9MH9nJ4pQQ4ifJ/SaOdDUJmSzorkWYHck+dlXhRTBLd1OJUSP6G9boxc+orKTZwiiPV4UkEYbTHkw51ihDTDG2DKgmpyQz7fhprcH2hI9PsBUk2cxYs09lW/+CJC3o3VSDqRQiYiVirAPyY5v04HbXeZXOA6Q89ljazcfKcnGNYjurorNpvN9u89AUR/OWbBkb+wAAAAAElFTkSuQmCC","orcid":"","institution":"University of Aberdeen","correspondingAuthor":true,"prefix":"","firstName":"Michelle","middleName":"E","lastName":"Taylor","suffix":""},{"id":638012342,"identity":"a25ec45e-0c2d-43db-9c77-753849df6587","order_by":1,"name":"Alizee Zimmermann","email":"","orcid":"","institution":"Turks and Caicos Reef Fund","correspondingAuthor":false,"prefix":"","firstName":"Alizee","middleName":"","lastName":"Zimmermann","suffix":""},{"id":638012343,"identity":"2158403d-5ffb-407f-b1e2-904783bcc0ed","order_by":2,"name":"Maria Beger","email":"","orcid":"","institution":"University of Leeds","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Beger","suffix":""}],"badges":[],"createdAt":"2026-04-28 07:25:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9550127/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9550127/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109172268,"identity":"581f6fa9-54d8-4454-ba67-f09e6dde6344","added_by":"auto","created_at":"2026-05-13 09:05:55","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":122579,"visible":true,"origin":"","legend":"\u003cp\u003eA map of the study area showing the 53 coral rubble bed sample site locations in Turks and Caicos Islands. Inset map shows the Caribbean Sea with Turks and Caicos Islands labelled.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9550127/v1/fac6df16b813f31cb823dbb7.jpg"},{"id":109172267,"identity":"ad565683-b13c-4b5f-abcf-cbf8cb7a4d02","added_by":"auto","created_at":"2026-05-13 09:05:55","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":110777,"visible":true,"origin":"","legend":"\u003cp\u003eDiagrammatic sketch of methods used in data collection. (a) A 0.09 cm\u003csup\u003e2\u003c/sup\u003e quadrat is placed on the rubble matrix, (b) rubble fragments and infauna collected into a WhirlPak bag, (c) each collected specimen was individually photographed, (d) all collected rubble fragments were laid out and photographed before being measured, (e) the displacement method was used to determine the volume of each rubble fragment, (f) schematic visualisation of how interstitial space was calculated.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9550127/v1/bfe890c079e7f58076e5da5d.jpg"},{"id":109172270,"identity":"1059c3cf-2fb3-49f6-807f-b479c5a95a2a","added_by":"auto","created_at":"2026-05-13 09:05:56","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":253136,"visible":true,"origin":"","legend":"\u003cp\u003eCollected rubble pieces showing the categories used to determine rubble type; (a) massive rubble fragment, (b) shell, (c) branching rubble fragment, (d) rock piece, and (e) other/unidentifiable rubble fragment.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9550127/v1/38367223b0296a185991d13c.jpg"},{"id":109172269,"identity":"38c49f77-7b0a-4526-9169-bb80fa95cc15","added_by":"auto","created_at":"2026-05-13 09:05:55","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":83690,"visible":true,"origin":"","legend":"\u003cp\u003eThe relative abundance of phyla present in coral rubble bed infauna by (a) rubble patch size, where rubble patches were categorised as small S (≤ 1 m\u003csup\u003e2\u003c/sup\u003e), medium M (1 ≤ 10 m\u003csup\u003e2\u003c/sup\u003e), large L (10 \u0026lt; 100 m\u003csup\u003e2\u003c/sup\u003e) or extra-large XL (≥ 100 m\u003csup\u003e2\u003c/sup\u003e); and (b) adjacent habitat, which was determined by measuring the distance to all adjacent habitats (live coral, rock, sand, and seagrass). When multiple habitats were equal distance to the sampled quadrat the category used was a combination (coral/rock, sand/rock, and sand/rock/seagrass). When the sampled quadrat had no adjacent habitat within 25 m (quadrat was within a very large rubble patch) the adjacent habitat was categorised as rubble.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9550127/v1/3ac7ee23c989a0873d65a5b0.jpg"},{"id":109205336,"identity":"3a2ac378-3b09-4d99-8d13-4d470d52a491","added_by":"auto","created_at":"2026-05-13 15:04:16","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":74632,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis for variance in organism abundance in Turks and Caicos Island coral rubble beds showing (a) phyla abundance by patch size, (b) phyla abundance by adjacent habitat. The nine phyla (grey arrows) are shown on each plot.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9550127/v1/2e8cb5c46e90a21abd12b5ae.jpg"},{"id":109206674,"identity":"b4ee1212-4c46-423f-b72d-93c031dbc5b9","added_by":"auto","created_at":"2026-05-13 15:15:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":971882,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9550127/v1/ababbc2e-a1c4-40dc-b0df-47764f57fbbf.pdf"},{"id":109172266,"identity":"94a5d480-35e3-488a-8e02-5419fa8f5c05","added_by":"auto","created_at":"2026-05-13 09:05:55","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":95020,"visible":true,"origin":"","legend":"","description":"","filename":"DifferencesincoralrubblebedbiodiversityCRSM.docx","url":"https://assets-eu.researchsquare.com/files/rs-9550127/v1/6cba59fc25cd717eea739190.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Both small-scale microhabitat preference and large-scale spatial complexity influence coral rubble bed infauna","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIncreasing anthropogenic impacts are causing declines of the natural world globally; coral reefs are no exception (IPBES, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Ocean acidification, increased frequency and intensity of marine heatwaves, and increased frequency and power of tropical storms have contributed to the loss of almost 14% of coral from coral reefs worldwide between 2009 and 2018 (Souter et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Following coral mortality, often combined with physical damage from storms or dredging and blast fishing, the living coral framework can become dismantled, resulting in the formation of coral rubble comprised of dead broken corals (Hampton-Smith et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kopecky et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These fragments of coral skeleton can then form into semi-consolidated structures known as coral rubble beds (Kenyon, Doropoulos, et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kenyon, Harris, et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite them originating from coral reef degradation, coral rubble still provides an important habitat to many marine organisms (Enochs \u0026amp; Manzello, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCoral rubble is a natural habitat that has existed for as long as live coral has (Perry \u0026amp; Hepburn, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Scoffin, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1992\u003c/span\u003e), and coral rubble beds exist in all regions where live coral cover is present. Of the Allen Coral Atlas benthically mapped area, coral rubble extends for half the area of coral reef globally (8.2% and 16% respectively) (Roelfsema et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), demonstrating its importance as a marine habitat. In the Caribbean region, coral rubble covers approximately one third of the area of coral reef (2300 km\u003csup\u003e2\u003c/sup\u003e and 7600 km\u003csup\u003e2\u003c/sup\u003e respectively) (Allen Coral Atlas, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). While efforts to restore coral reefs have been successful (Lamont et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the high costs involved means that restoration is not feasible everywhere (Bayraktarov et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lange et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Therefore, research into unconsolidated coral rubble beds and their inhabitants is urgently needed as the prevalence of coral rubble beds continues to increase.\u003c/p\u003e \u003cp\u003eCoral reefs naturally contain microhabitats, providing distinct niches (Beese et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Graham \u0026amp; Nash, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Risk, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1972\u003c/span\u003e), which might hold distinct community structures. The characteristics of these microhabitats, including the branch length and interbranch distance of coral structures, benthic type (soft coral, sand, and rubble), available foraging space, and reef type (reef lagoon and reef front), influence the biodiversity and size structure of species found (Depczynski \u0026amp; Bellwood, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Ticzon et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Villegas-Hern\u0026aacute;ndez et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wehrberger \u0026amp; Herler, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Coral rubble bed structures are not homogenous, even on small scales within the same reef area (Masucci et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, edge effect predicts that abundance and species richness should be higher in larger habitat patches (Conor \u0026amp; McCoy, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It is therefore plausible, but unknown, that differences in coral rubble bed characteristics (rubble type, interstitial space, and mobility) could drive variation in the community structure of associated infauna.\u003c/p\u003e \u003cp\u003eMarine organisms have a wide range of habitat requirements that structure habitat partitioning (Ceia et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Fairclough, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lin et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Nanami, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). On coral reefs, scleractinian coral species that offer different microhabitats support very different fish communities (Messmer et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), illustrating that coral reef fish diversity is influenced by individual coral species presence. Both juvenile and adult reef fishes require shelter from predators, often favouring different coral morphologies that reflect the size of refuge provided (Wilson et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). For herbivorous fishes, the available surface area of grazing structure is strongly associated with distribution, indicating that a primary factor driving the distribution is food resource availability (Oakley-Cogan et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Vercammen et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Marine invertebrates also require numerous resources, such as shelter, breeding grounds, and nutrition, from their habitat in order to thrive and contribute to the ecosystem services and function (Asante et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Bugnot et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Essential resources of food, refuge from predators, and access to mates are widely available on live coral reefs (Hatcher, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Kerry \u0026amp; Bellwood, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Despite the degraded structure of coral rubble beds, many of these services provided by live coral to coral-associated species may also be able to be provided by coral rubble. Therefore, fully establishing the function of coral rubble beds is essential to understand their role in the wider coral reef ecosystem.\u003c/p\u003e \u003cp\u003eSpecimen sampling of infauna from coral rubble beds has been limited and has thus far produced contradictory results. Extrapolating patterns from live coral, it would be expected that more complex structures should host a higher abundance and diversity of reef fishes (Almany, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Graham \u0026amp; Nash, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, the fish species richness and total abundance on coral reefs at Lizard Island, Great Barrier Reef, Australia, were only weakly correlated to topographic complexity (Komyakova et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The internal volume of interpolyp space was the most important factor influencing the abundance and richness of crustaceans on coral reefs in Brazil (Nogueira et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and in the Mexican Tropical Pacific, the highest abundance of Mollusca was recorded on coral substrate (Barrientos-Luj\u0026aacute;n et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, reef complexity accounts for very little variability in Arthropoda, Annelida, and Porifera (Newman et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), while sea urchin densities are negatively correlated with structural complexity (Graham \u0026amp; Nash, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These differing preferences of marine organisms showcase the complex interactions between coral reef structure and the infauna communities present.\u003c/p\u003e \u003cp\u003eContrary to expectations, the abundance and diversity of macro-crustaceans is higher on degraded reefs than on a coral reef composed of living \u003cem\u003eAcropora palmata\u003c/em\u003e in the Mexican Caribbean (Gonz\u0026aacute;lez-G\u0026oacute;mez et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In Kenya, nematode communities had a higher diversity in dead coral fragments compared to coral gravel (small, indistinct pieces of coral skeleton), however the coral morphotype did not have an effect on community structure (Raes et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Crustacean abundance, biomass and estimated productivity was higher in dead coral and coral rubble when compared to sand, epilithic algal matrix, and fine-branching live coral microhabitats on sites at Lizard Island (Kramer et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The gastropod \u003cem\u003eConus\u003c/em\u003e preferentially shelter in sand- and rubble-filled depressions on reefs during the day before utilising other microhabitats for feeding (Kohn, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e1983\u003c/span\u003e). On the Caribbean coast of Panama, dead coral habitats support a more diverse and abundant mobile invertebrate assemblage than live coral (Nelson et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Dissolving collected coral skeletons from SW Indian Ocean seamounts found that 34 families of polychaetes lived within the structures (Narayanaswamy et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This illustrates that further investigations into the inhabitants of dead coral frameworks are essential to fully determine the biodiversity of coral rubble beds. These studies show the importance of these degraded habitats to multiple marine phyla.\u003c/p\u003e \u003cp\u003eLimited surveys of coral rubble bed cryptofauna has given us a baseline biodiversity inventory for a minimal number of locations globally. However, the factors influencing differences in community structure remain unknown. This research aims to rectify this by analysing rubble type, depth, adjacent habitats, and interstitial space to determine what factors drive biodiversity differences in coral rubble beds.\u003c/p\u003e \u003cp\u003eHere, we conduct the first species diversity analysis of Caribbean coral rubble beds, using the Turks and Caicos Islands as a study site. Specifically, our objectives are to (a) determine what factors influence the total specimen number found within coral rubble; (b) ascertain the factors influencing the presence likelihood of individual phyla in coral rubble; (c) establish what factors affect the abundance of individual phyla within coral rubble, thereby determining if the biodiversity in coral rubble beds is homogeneous across sites.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSampling area and experimental design\u003c/h2\u003e \u003cp\u003eWe conducted our field study during the summer of 2022 and 2023 in the Turks and Caicos Islands which are located in the northern Caribbean. We selected 53 coral rubble sites from around five of the islands within the archipelago \u0026ndash; East Caicos, Grand Turk, North Caicos, Providenciales, and South Caicos (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The sites were chosen to cover a variety of water depths and a range of adjacent habitats (live coral, sand, seagrass, and rock). Due to the geographical spread of the sample sites, localised anthropogenic factors differed at each of the islands.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eUsing a 30 cm x 30 cm quadrat, we collected three replicate samples of coral rubble and associated infauna on each SCUBA dive from water depths of 1.1 to 18.7 m. Rubble fragments and infauna were collected to a depth of approximately 15 cm and the depth of collected matrix was measured to allow the volume of coral rubble to be calculated. Due to the small patch size of the coral rubble beds, we were unable to use a systematic sampling design. To ensure the samples were independent, we did not remove more than one sample per rubble patch if the area was less than 1 m\u003csup\u003e2\u003c/sup\u003e. All coral rubble bed quadrats that we sampled from one site were taken from within a 100 m\u003csup\u003e2\u003c/sup\u003e area. Each site was at least 100 m away from any other sites sampled.\u003c/p\u003e \u003cp\u003eOnce the quadrat had been randomly placed on the coral rubble (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea), we noted the water depth, before photographing the quadrat and surrounding area to analyse for coral rubble type (branching, massive, or a mixture) and the presence of interstitial spaces. Following the American Veterinary Medical Association euthanasia guidelines, we sprayed a mixture of ethanol (95%) and clove bud oil over the quadrat and into the matrix of the coral rubble to temporarily stun the infauna and allow collection of the specimens. We then collected all the coral rubble fragments and organisms that were inside the quadrat and sealed them into a WhirlPak bag, to ensure the mobile animals did not escape whilst we brought them to the surface (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). This collection method will slightly underestimate the abundance and diversity of the coral rubble infauna, as numerous motile organisms were able to move through the matrix to avoid capture. We particularly noted that Ophiuroidea (brittle stars) were barely affected by the clove bud oil and were very difficult to collect, because they quickly moved out of the quadrat area into the surrounding coral rubble. Most reef fishes moved out of the collection area as the divers approached, so any fish collected were opportunistic and do not give a true representation of the species using the habitat.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOnce the coral rubble and infauna were collected from the quadrat, we then measured the depth of rubble that had been collected to give a total volume of the sample (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Finally, we mapped and measured the coral rubble patch size and distance of the sampled quadrats to the adjacent habitats. Rubble patches were categorised as small S (\u0026le;\u0026thinsp;1 m\u003csup\u003e2\u003c/sup\u003e), medium M (1\u0026thinsp;\u0026le;\u0026thinsp;10 m\u003csup\u003e2\u003c/sup\u003e), large L (10\u0026thinsp;\u0026lt;\u0026thinsp;100 m\u003csup\u003e2\u003c/sup\u003e), or extra-large XL (\u0026ge;\u0026thinsp;100 m\u003csup\u003e2\u003c/sup\u003e). The adjacent habitats were categorised as either live coral reef, rock, seagrass bed, or sand. If two habitats were equidistant to the sampled quadrat, we combined them as a category (coral/rock, sand/rock, sand/rock/seagrass).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOn the surface, we removed each coral rubble fragment from the WhirlPak bag and rinsed the pieces with fresh water over a 75 \u0026micro;m mesh filter to collect all visible organisms. We used tweezers to remove algae from the fragments to ensure no organisms were missed in the collection. Each collected specimen was given a unique identification number and photographed individually (Bresser USB digital microscope DST-1028) before being preserved in 99% ethanol and identified to the lowest taxonomic group possible (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). We anticipate that all organisms over 0.5 mm in length were collected. We then selected 950 of the collected specimens (from Annelida, Arthropoda, Chordata, Cnidaria, Echinodermata, Mollusca, and Porifera phyla) to be DNA barcoded at the Canadian Centre for DNA Barcoding (CCDB) at the University of Guelph, Canada. Specimens were selected to give a comprehensive representation of the collected organisms. We used a variety of primers (selected for their specimen phylum relevance) and targeted the COI mitochondrial gene (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). All our collected specimens have now been curated into the permanent collection at the Natural History Museum of Los Angeles County.\u003c/p\u003e \u003cp\u003eWe also photographed all the collected coral rubble pieces to allow size measurements to be taken (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). Using Image J (version 1.54p), we measured the length (longest span in any direction) and width (perpendicular to length) to the nearest 1 mm. We categorised the rubble fragments as branching (identified by rubble shape), massive (identified by size and/or presence of coral polyps that indicated the coral genus), shell (included mollusc shells and worm tubes), rock (where it was clear calcification had occurred), or other (where the source was not clear) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). We measured the volume of the coral rubble fragments using the displacement method (Frings et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Scherle, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e1970\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee), allowing the interstitial space that was present in the coral rubble bed before the fragments were removed to be estimated (Gee \u0026amp; Bauder, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). Using the depth of rubble collected and the approximate volume of the individual rubble pieces, we were able to create an estimate of free space within the matrix of each rubble sample site (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef). This approach then allowed each quadrat to be categorised both in terms of most prevalent rubble type present and in volume of interstitial space available to mobile cryptofauna.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eTo determine the factors which influence the total specimen abundance, we ran a linear model and Tukey post hoc tests. We used a logistical regression model to investigate the relationship between factors and the presence/absence of individual phyla. We used multivariable logistical regression to compare multiple predictors to individual phyla presence likelihood. Then to compare the abundance of individual phyla to rubble patch size and adjacent habitat, we used a two-way ANOVA and Tukey pairwise post hoc test (using the \u0026ldquo;emmeans\u0026rdquo; package version 1.11.1). Finally, we used principal component analysis and PERMANOVA (Bray-Curtis dissimilarity) (using \u0026ldquo;vegan\u0026rdquo; package version 2.6-4) to investigate the effect of rubble patch size and adjacent habitat on the phyla composition. All statistical analyses were carried out in R (version 4.3.1). We determined significance at a 95% confidence level.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eTotal specimen number\u003c/h2\u003e \u003cp\u003eIn total, 2,769 specimens were collected from the coral rubble beds in the Turks and Caicos Islands, with a total organism density of 193.5 organisms m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e. With 1,887 specimens (68.1%), Annelida was the most abundant phylum, followed by Arthropoda (224; 8.8%), Mollusca (230; 8.3%) and Echinodermata (213; 7.7%). Chordata, Cnidaria, Nemertea, Porifera or unidentified composed the remaining 7.2% of collected specimens.\u003c/p\u003e \u003cp\u003eThe total number of coral rubble infauna specimens per site was influenced by a number of factors. Total specimen abundance decreased with increasing rubble patch size (F\u0026thinsp;=\u0026thinsp;18.88, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with XL rubble patches (\u0026ge;\u0026thinsp;100 m\u003csup\u003e2\u003c/sup\u003e) having almost half the number of specimens on average (10.9 specimens per 0.09 m\u003csup\u003e2\u003c/sup\u003e quadrat) compared to all patches smaller than 100 m\u003csup\u003e2\u003c/sup\u003e (19.3\u0026ndash;19.6 collected specimens per 0.09 m\u003csup\u003e2\u003c/sup\u003e quadrat). The percentage of each rubble type within the quadrat also influenced the total number of collected specimens. With increasing percentage of \u0026ldquo;other\u0026rdquo; (usually small rubble fragments with unidentifiable morphology), there was a significant increase in specimen count (F\u0026thinsp;=\u0026thinsp;4.86, p\u0026thinsp;=\u0026thinsp;0.029). A higher percentage presence of rock pieces within the sampled quadrat was linked to slight decrease in total specimen count (F\u0026thinsp;=\u0026thinsp;4.16, p\u0026thinsp;=\u0026thinsp;0.043). There was no significant difference in total specimen count when compared to the percentage of branching and massive rubble pieces present.\u003c/p\u003e \u003cp\u003eThe adjacent habitat to the sampled coral rubble was significant in driving the total number of specimens collected. The highest mean number of specimens collected were from quadrats that had live coral as the closest adjacent habitat (mean\u0026thinsp;=\u0026thinsp;23.7 specimens per 0.09 m\u003csup\u003e2\u003c/sup\u003e quadrat), while quadrats that lacked an adjacent habitat within 25 m, because they were in large rubble patches, had the lowest number of specimens (mean\u0026thinsp;=\u0026thinsp;4.5 specimens per 0.09 m\u003csup\u003e2\u003c/sup\u003e quadrat). Rubble patches with sand as the closest adjacent habitat had fewer specimens (mean\u0026thinsp;=\u0026thinsp;7.2 specimens per 0.09 m\u003csup\u003e2\u003c/sup\u003e quadrat) than live coral (mean\u0026thinsp;=\u0026thinsp;23.7 specimens per 0.09 m\u003csup\u003e2\u003c/sup\u003e quadrat; p\u0026thinsp;=\u0026thinsp;0.0003), equally distanced live coral and rock (mean\u0026thinsp;=\u0026thinsp;19.7 specimens per 0.09 m\u003csup\u003e2\u003c/sup\u003e quadrat; p\u0026thinsp;=\u0026thinsp;0.039), and rock (mean\u0026thinsp;=\u0026thinsp;18.3 specimens per 0.09 m\u003csup\u003e2\u003c/sup\u003e quadrat; p\u0026thinsp;=\u0026thinsp;0.013). However, the distance from the sampled quadrat to the closest live coral does not affect the total number of specimens found within coral rubble (individual coral colonies: p\u0026thinsp;=\u0026thinsp;0.055; coral reef: p\u0026thinsp;=\u0026thinsp;0.22). With increasing distance from the sampled quadrat to sand, we observed a slight increase in the total number of specimens collected (p\u0026thinsp;=\u0026thinsp;0.025), while with increasing distance to hard bedrock, the total number of specimens decreased (p\u0026thinsp;=\u0026thinsp;0.028). Distance to the closest individual coral colony, reef, and/or seagrass did not influence total specimen abundance.\u003c/p\u003e \u003cp\u003eThe overall quadrat volume and total volume of rubble fragments within the quadrat were both very strong predictors of the total number of specimens present. Increased quadrat volume (cm\u003csup\u003e3\u003c/sup\u003e) and rubble volume (cm\u003csup\u003e3\u003c/sup\u003e) increases the total number of specimens (F\u0026thinsp;=\u0026thinsp;32,720, p\u0026thinsp;\u0026lt;\u0026thinsp;2.2e-16 and F\u0026thinsp;=\u0026thinsp;31,360, p\u0026thinsp;\u0026lt;\u0026thinsp;2.2e-16 respectively). However, despite varying widely, the mean volume, length, and width of individual rubble pieces, number of rubble fragments within the quadrat, volume of interstitial space, percentage of available space within the rubble matrix, and water depth did not affect the total number of specimens (Supplementary Table S2). Differences in total specimen count exist between individual sites but not between islands surveyed.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePresence likelihood of individual phyla\u003c/h3\u003e\n\u003cp\u003eIndividual phyla presence is determined by various factors (Supplementary Table S3). Prevalence of the collected phyla showed the same pattern as abundance. Annelida was the most prevalent phylum, being collected from 96.2% of the sites, followed by Arthropoda (94.3%), Mollusca (92.5%), Echinodermata (77.4%), Porifera (49.1%), Chordata (41.5%), Nemertea (15.1%), and Cnidaria (7.5%).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAnnelida\u003c/h2\u003e \u003cp\u003eThe likelihood of Annelida presence in coral rubble increases as the quadrat volume (depth of rubble surveyed) increases (β\u0026thinsp;=\u0026thinsp;0.0008, p\u0026thinsp;=\u0026thinsp;0.0015), and as the rubble patch size decreases (β = -0.0008, p\u0026thinsp;=\u0026thinsp;0.034). Likelihood of Annelida presence also increases with increased mean rubble fragment volume (β\u0026thinsp;=\u0026thinsp;0.0114, p\u0026thinsp;=\u0026thinsp;0.021), increased mean rubble fragment length (β\u0026thinsp;=\u0026thinsp;0.814, p\u0026thinsp;=\u0026thinsp;0.031), and larger mean rubble fragment width (β\u0026thinsp;=\u0026thinsp;1.466, p\u0026thinsp;=\u0026thinsp;0.040).\u003c/p\u003e \u003cp\u003eRubble type significantly influences the presence of Annelida, with an increased likelihood of Annelida occurrence in branching rubble (β\u0026thinsp;=\u0026thinsp;2.890, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and a decreased likelihood in shell/branching rubble (β = -2.890, p\u0026thinsp;=\u0026thinsp;0.019). The composition of the rubble fragments also influences the likelihood of Annelida presence. With increasing proportion of shells (β\u0026thinsp;=\u0026thinsp;0.064, p\u0026thinsp;=\u0026thinsp;0.0006), and rock fragments (β = -0.402, p\u0026thinsp;=\u0026thinsp;0.001) the likelihood of Annelida presence decreases. There is a significant positive association between \u0026ldquo;other\u0026rdquo; (unidentifiable) rubble pieces and Annelida presence (β\u0026thinsp;=\u0026thinsp;0.043, p\u0026thinsp;=\u0026thinsp;0.014). However, when compared in a multivariable logistical regression model, the proportion of rubble composed of shell and rock fragments was significantly negatively associated with Annelida presence (shell: β = -0.070, p\u0026thinsp;=\u0026thinsp;0.0014; rock: β = -0.049, p\u0026thinsp;=\u0026thinsp;0.0011), while the proportion of the unidentifiable fragments did not show a significant result (β\u0026thinsp;=\u0026thinsp;0.047, p\u0026thinsp;=\u0026thinsp;0.101).\u003c/p\u003e \u003cp\u003eThe likelihood of Annelida presence also is influenced by distance to adjacent habitats. With increasing distance from coral and rock, the likelihood of Annelida presence decreases significantly (β = -0.313, p\u0026thinsp;=\u0026thinsp;0.003 and β = -0.348, p\u0026thinsp;=\u0026thinsp;0.006 respectively). Annelida are also more likely to be present when interstitial space is increased (β\u0026thinsp;=\u0026thinsp;0.0006, p\u0026thinsp;=\u0026thinsp;0.004), rubble volume is increase (β\u0026thinsp;=\u0026thinsp;0.0009, p\u0026thinsp;=\u0026thinsp;0.041), and number of rubble fragments within the quadrat decreases (β = -0.041, p\u0026thinsp;=\u0026thinsp;0.002).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eArthropoda\u003c/h3\u003e\n\u003cp\u003eThe only factor with a significant influence on the likelihood of Arthropoda presence is adjacent habitat type. Arthropoda presence was significantly lower in samples adjacent to rubble (within large rubble beds with no other habitat within 25 m) (β = -2.485, p\u0026thinsp;=\u0026thinsp;0.045) and sand (β = -2.213, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), compared to the coral reference. Rock and seagrass did not influence Arthropoda presence (β = -0.945, p\u0026thinsp;=\u0026thinsp;0.069 and β = -1.792, p\u0026thinsp;=\u0026thinsp;0.079, respectively).\u003c/p\u003e\n\u003ch3\u003eChordata\u003c/h3\u003e\n\u003cp\u003eChordata presence is not significantly influenced by rubble patch size, rubble type, water depth, quadrat volume, rubble fragment abundance, interstitial space, or rubble fragment size. The mean volume of shell fragments within the sampled quadrat does have a significant influence on Chordata presence, with increasing mean volume increasing the likelihood of presence (β\u0026thinsp;=\u0026thinsp;0.022, p\u0026thinsp;=\u0026thinsp;0.034). However, the small sample size of Chordata is likely to have affected these results.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCnidaria\u003c/h2\u003e \u003cp\u003eCnidaria presence is not significantly influenced by rubble patch size, rubble type, water depth, quadrat volume, rubble fragment abundance, interstitial space, or rubble fragment size. The percentage of available space within the sampled quadrat does have a significant influence on Cnidaria presence, with increasing percentage of available space the likelihood of Cnidaria presence decreases (β = -0.053, p\u0026thinsp;=\u0026thinsp;0.014). However, the small sample size of Cnidaria is likely to have affected these results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEchinodermata\u003c/h2\u003e \u003cp\u003eThere is a significant negative relationship between rubble patch size and the presence of Echinodermata (β = -0.0007, p\u0026thinsp;=\u0026thinsp;0.0025). However, Echinodermata presence is not significantly affected by rubble type, water depth, quadrat volume, rubble fragment abundance, interstitial space, or rubble fragment size.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMollusca\u003c/h2\u003e \u003cp\u003eThere is a significant negative relationship between rubble patch size and the presence of Mollusca (β = -0.0006, p\u0026thinsp;=\u0026thinsp;0.0042). Rubble patches\u0026thinsp;\u0026ge;\u0026thinsp;100 m\u003csup\u003e2\u003c/sup\u003e (category XL) were significantly less likely to contain Mollusca (p\u0026thinsp;=\u0026thinsp;0.031). Conversely, Mollusca presence is not significantly affected by rubble type, water depth, quadrat volume, rubble fragment abundance, interstitial space, or rubble fragment size.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eNemertea\u003c/h2\u003e \u003cp\u003eThere is a significant positive relationship between the number of rubble fragments within a sample quadrat and the presence of Nemertea. As the number of rubble fragments increases the likelihood of Nemertea presence also increases (β\u0026thinsp;=\u0026thinsp;0.003, p\u0026thinsp;=\u0026thinsp;0.041). There is also a significant negative association between mean length of rubble fragment pieces and Nemertea presence, with likelihood decreasing as mean length increases (β = -1.054, p\u0026thinsp;=\u0026thinsp;0.043). However, due to the small sample size these influences are weak. Nemertea presence is not significantly affected by rubble type, water depth, quadrat volume, interstitial space, rubble patch size, or rubble fragment size.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePorifera\u003c/h2\u003e \u003cp\u003eThere is a statistically significant positive relationship between interstitial space and Porifera presence (β\u0026thinsp;=\u0026thinsp;0.00012, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049), indicating that Porifera are more likely to occur in areas with greater interstitial space. Adjacent habitat type also has a significant influence on the likelihood of Porifera presence. Porifera presence was significantly lower in samples adjacent to rock (β = -1.147, p\u0026thinsp;=\u0026thinsp;0.014). Likelihood of presence is increased with decreasing distance to the nearest live coral colony (β = -0.336, p\u0026thinsp;=\u0026thinsp;0.021). No other factors influenced the likelihood of Porifera presence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eOther (unidentifiable specimens)\u003c/h2\u003e \u003cp\u003eWater depth has a significant negative association with presence of \u0026ldquo;other\u0026rdquo; phyla (β = -0.215, p\u0026thinsp;=\u0026thinsp;0.0009). A rubble patch size of 1.1\u0026ndash;10 m\u003csup\u003e2\u003c/sup\u003e (category M) has a lower likelihood of \u0026ldquo;other\u0026rdquo; phyla presence when compared to the other size categories (p\u0026thinsp;=\u0026thinsp;0.046). The smallest rubble patch size category (\u0026le;\u0026thinsp;1 m\u003csup\u003e2\u003c/sup\u003e) also shows a marginal negative association with the presence of \u0026ldquo;other\u0026rdquo; phyla, but it is not significant (p\u0026thinsp;=\u0026thinsp;0.077). Quadrats containing mostly massive rubble pieces also showed a lower likelihood of \u0026ldquo;other\u0026rdquo; phyla presence (p\u0026thinsp;=\u0026thinsp;0.031). No other factors influenced the likelihood of \u0026ldquo;other\u0026rdquo; phyla presence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePhyla abundance\u003c/h2\u003e \u003cp\u003eIndividual phyla abundance is affected by different factors. Significant differences in organism count exist among patch sizes (F (3, 1395)\u0026thinsp;=\u0026thinsp;4.80, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and as an interaction of patch size and phylum (F (24, 1395)\u0026thinsp;=\u0026thinsp;3.07, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Supplementary Table\u0026nbsp;4) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Each rubble patch size has a distinct phyla composition (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea), with significant differences between extra-large XL rubble patches (\u0026ge;\u0026thinsp;100 m\u003csup\u003e2\u003c/sup\u003e) and small S (\u0026le;\u0026thinsp;1 m\u003csup\u003e2\u003c/sup\u003e) (p\u0026thinsp;=\u0026thinsp;0.007), medium M (1\u0026thinsp;\u0026le;\u0026thinsp;10 m\u003csup\u003e2\u003c/sup\u003e) (p\u0026thinsp;=\u0026thinsp;0.009), and large L (10\u0026thinsp;\u0026lt;\u0026thinsp;100 m\u003csup\u003e2\u003c/sup\u003e) (p\u0026thinsp;=\u0026thinsp;0.019). Both PC1 and PC2 axes explain gradients in the community structure (62.64% and 25.87% respectively), with PC1 being primarily driven by the relative abundance of Chordata, Mollusca, and Porifera, while variation along PC2 was driven by Cnidaria and Echinodermata (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). A PERMANOVA (Bray-Curtis dissimilarity) shows marginal differences in species composition across patch types (F\u0026thinsp;=\u0026thinsp;1.53, R\u0026sup2; = 0.03, p\u0026thinsp;=\u0026thinsp;0.094), indicating that patch size explains a small but potentially meaningful proportion of variation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAdjacent habitat also has a significant effect on organism abundance (F (7, 1359)\u0026thinsp;=\u0026thinsp;5.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with a significant interaction between adjacent habitat and phylum also present (F (56, 1359)\u0026thinsp;=\u0026thinsp;2.96, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Supplementary Table S5) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Quadrats with seagrass, sand/rock/seagrass, sand/rock and rubble as the adjacent habitat are more closely related in phyla abundance than rock, sand, coral, and coral/rock (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Both PC1 and PC2 axes explain major variance in the taxonomic composition (80.82% and 14.8% respectively). PC1 captures the most significant pattern in community composition, with all phyla contributing in the positive direction. Mollusca is strongest driver of variation along PC2, with Cnidaria also notably contributing but in the negative direction (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). A PERMANOVA (Bray-Curtis dissimilarity) shows that adjacent habitat explains a small but significant proportion of the variation (F\u0026thinsp;=\u0026thinsp;1.70, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.08, p\u0026thinsp;=\u0026thinsp;0.009), confirming that the adjacent habitat to coral rubble influences differences in phyla composition.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eAnnelida\u003c/h2\u003e \u003cp\u003eAnnelids are more abundant in quadrats that are adjacent to coral (mean\u0026thinsp;=\u0026thinsp;16) than rock (mean\u0026thinsp;=\u0026thinsp;12.8, p\u0026thinsp;=\u0026thinsp;0.006), rubble (mean\u0026thinsp;=\u0026thinsp;3.5, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), sand (mean\u0026thinsp;=\u0026thinsp;4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and seagrass (mean\u0026thinsp;=\u0026thinsp;2.4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Annelids are also more abundant in quadrats which are adjacent to coral/rock (mean\u0026thinsp;=\u0026thinsp;14.2) than rubble (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), sand (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and seagrass (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Quadrats adjacent to rock contain more annelids than those adjacent to rubble (p\u0026thinsp;=\u0026thinsp;0.0001), sand (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and seagrass (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). However, annelids were more abundant in quadrats which were equal distance to sand and rock (mean\u0026thinsp;=\u0026thinsp;15.5) than rubble (p\u0026thinsp;=\u0026thinsp;0.0001), sand (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and seagrass (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Supplementary Table S6). The highest abundance of Annelida is in M sized rubble patches (mean\u0026thinsp;=\u0026thinsp;15.2), almost double of that found in XL sized rubble patches (mean\u0026thinsp;=\u0026thinsp;8). The XL rubble patch category has significantly less abundance of Annelida than S (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), M (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and L (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Supplementary Table S7).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eOther Phyla\u003c/h2\u003e \u003cp\u003eMultiple factors contribute to differences in abundance of Arthropoda, Chordata, Cnidaria, Echinodermata, Mollusca, Nemertea, Porifera and unidentified specimens. Despite differences in mean abundance when adjacent habitats are compared, none are significant (Supplementary Table S5). The abundance of individual phyla is also not significantly different when compared to rubble patch size (Supplementary Table S6). Some of the insignificant results are likely due to the small sample sizes.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCoral rubble beds support a high number of associated taxa which occupy the habitat. Here, we show that both rubble patch size and type, and adjacency to live habitat, influence the abundance and diversity of coral rubble bed infauna. Total specimen abundance was lowest in the extra-large rubble patches. High rubble fragment volume and deep quadrat depth correlated with high total specimen abundance. Rubble fragment type influenced the total specimen abundance, with a higher specimen count found in quadrats with a higher percentage of small, morphologically unidentifiable rubble fragments, compared to other types of fragments. The adjacent habitat to rubble patches significantly influenced the total specimen abundance, with most organisms present in rubble closest to live coral. Individual phyla abundance was driven by different factors, with only rubble patch size and number of fragments affecting the likelihood of multiple phyla being present.\u003c/p\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eTotal specimen abundance\u003c/h2\u003e \u003cp\u003eThe total abundance of coral rubble infauna is strongly influenced by various small-scale physical habitat characteristics. Small rubble patch size supports a significantly higher specimen count than larger patches, potentially suggesting higher habitat heterogeneity in the smaller rubble patches. Edge effect and the Area Per Se hypothesis would account for the opposite trend, with smaller patches having a lower abundance of specimens (Conor \u0026amp; McCoy, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). We show that extra-large XL (\u0026ge;\u0026thinsp;100 m\u003csup\u003e2\u003c/sup\u003e) rubble patch sizes had nearly half the infaunal density of smaller patches. Contrastingly, in algal beds, polychaetes, amphipods and ostracods occurred in low abundances in small patches following colonisation, which is also inconsistent with traditional predications using edge effect (Roberts \u0026amp; Poore, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Terrestrial habitats show the same pattern, with species richness and abundance increasing with patch size. This is likely due to resource limitation and competition (Lawrence et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and extinction probability decreasing with increasing patch size because large patch sizes can maintain large population sizes (MacArthur \u0026amp; Wilson, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Mortelliti et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Therefore, the differences in infaunal abundance in varying coral rubble bed patch sizes does not follow expected trends. Colonisation at remote sites is lower than at non-remote (Barnes, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), likely due to the dispersal challenges of reaching suitable habitat over long distances. The lower total specimen abundance found in larger rubble patches could also be explained by the increased distance infauna needs to cover to move into the area. Regardless of pelagic larval duration, both invertebrates and fish species have the most successful dispersal over short distances (Becker et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Conklin et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sammarco \u0026amp; Andrews, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). Therefore, low colonisation efficiency is likely to be driving the lower abundance in larger rubble patches.\u003c/p\u003e \u003cp\u003eRubble volume and quadrat depth were the most robust predictors of total specimen abundance, with rubble volume and quadrat depth being directly proportionally related to total specimen abundance, underscoring the importance of three-dimensional structure in coral rubble bed infaunal community assemblages. Previously, a comparison of 2D and 3D surveys on coral reefs showed the importance of including cryptic reef habitats to ensure representative biomass, abundance, and diversity estimates (Kornder et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), emphasising the importance of these cryptic species to the coral reef habitat. Typically, living corals create the large benthic structures that directly affect the ecosystem function of the habitat. Light availability, habitat provisioning, productivity, and ecosystem biodiversity is determined by the 3D structural complexity (Burns et al., 2019). The strongest and most consistent predictor of reef fish biomass, abundance, species richness and trophic structure is structural complexity and reef zone category (Darling et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Similarly, topographical complexity on coral reefs in the U.S. Virgin Islands explained the variation seen in the diversity of conspicuous invertebrates, however processes independent of coral traits also play an important role in determining the community structure (Idjadi \u0026amp; Edmunds, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The main structuring factor of polychaete populations is habitat structure, with the highest structural complexity at the microhabitat level containing the highest richness and diversity of polychaete species (Miri et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Serrano \u0026amp; Preciado, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Extrapolating the knowledge of structural complexity on coral reefs to coral rubble, it would be expected that samples with higher complexity should have a greater abundance of infauna. Since deep quadrat depth and high rubble volume could be described as a higher structural complexity, as more interstitial spaces create complex habitats in such rubble beds, it explains why a higher abundance of infauna is found in deep rubble with high rubble volume.\u003c/p\u003e \u003cp\u003eThe composition of rubble type and size within the sample also affected infaunal abundance; for example, high percentages of small, morphologically unidentifiable rubble fragments were associated with a high total specimen count, while large proportions of rock fragments present in the quadrat were associated with modest declines. Studies on tropical invertebrate coral infauna influenced by habitat type and rugosity are lacking. However, density and biomass of epifauna\u0026thinsp;\u0026gt;\u0026thinsp;0.5 mm found in rocky reef habitats in New Zealand did show differences among different habitats, with highest values in sites with algal presence (Taylor, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Furthermore, reef fish assemblages on rocky reefs in the Gulf of California did not differ between habitats of different rock sizes (Aburto-Oropeza \u0026amp; Balart, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Microhabitat structure on subtidal rocky reefs influenced the variation of invertebrate assemblages, with larger surface area explaining the most variation (Alexander, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Similarly, within our samples, smaller fragments of rubble would have a larger surface area and thus could explain the higher specimen count observed. These findings highlight that both quantity and quality of the physical habitat is critical in shaping coral rubble bed infaunal assemblages.\u003c/p\u003e \u003cp\u003eBeyond the physical characteristics of the sampled rubble bed, the larger-scale spatial context of a coral rubble bed also played a key role in determining infaunal abundance. Quadrats closest to live coral yielded the highest specimen counts, while those lacking any adjacent habitat within 25 meters\u0026mdash;typically found in large and extra-large rubble fields\u0026mdash;had the lowest number of specimens. This finding suggests that recruitment and retention of species may be enhanced by adjacent habitats to rubble beds, potentially through spillover effects. Both larval dispersal and recruitment of marine invertebrates influences their abundance, diversity, and richness, which in turn influences ecological stability (Holstein, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Local and regional oceanographic patterns and biotic factors (such as abundance of microbial bio-films and proximity to conspecific adult) affect the recruitment of invertebrates (Hadfield, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Karlson \u0026amp; Hurd, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Monitoring recruitment of dead coral branches in the Central Mexican Pacific found that there is a temporal trend with higher recruitment in warmer months, however malacostracans, ostracods, gastropods and polychaetes were all commonly observed, regardless of water temperature (Rodr\u0026iacute;guez-Troncoso et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Our samples were all collected in the summer months (July and August), which might have been during the main recruitment phase, however we do not anticipate this to have affected the overall survey results.\u003c/p\u003e \u003cp\u003eAlthough proximity to live coral communities was important, the actual distance to the nearest colony did not significantly influence the total abundance of infauna, indicating that it is the presence not proximity of the coral habitat that is the influential factor. Therefore, small, isolated patches of coral rubble, even when they are not directly adjacent to live coral, may be the most important form of the habitat for reef regeneration and colonisation following disturbance, since the greatest abundance and diversity is found there. Overall, these results highlight the importance of both small-scale habitat complexity and large-scale location within the wider coral reef ecosystem, in determining the overall abundance of coral rubble bed infauna.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003ePhyla abundance\u003c/h2\u003e \u003cp\u003eMultiple factors were influential in the presence likelihood of different phyla; however, very few factors influenced more than one phylum. Twelve factors (quadrat volume (cm\u003csup\u003e3\u003c/sup\u003e), rubble type, rubble patch size (m\u003csup\u003e2\u003c/sup\u003e), percentage composition of rubble fragment types, number of rubble fragments, rubble volume (cm\u003csup\u003e3\u003c/sup\u003e), rubble fragment dimensions, and distance to adjacent habitat) were significantly influential in determining the likelihood of Annelida presence, whilst the other phyla were only determined by fewer than four factors: Arthropoda\u0026thinsp;=\u0026thinsp;2, Cnidaria\u0026thinsp;=\u0026thinsp;1, Chordata\u0026thinsp;=\u0026thinsp;1, Echinodermata\u0026thinsp;=\u0026thinsp;1, Mollusca\u0026thinsp;=\u0026thinsp;1, Nemertea\u0026thinsp;=\u0026thinsp;2, Porifera\u0026thinsp;=\u0026thinsp;3, Other\u0026thinsp;=\u0026thinsp;4. The low prevalence of Cnidaria, Chordata, and Nemertea are likely why there are limited significant determining factors. Only four factors determined the likelihood of presence of more than one phylum \u0026ndash; distance to nearest coral, interstitial space, number of rubble pieces within the quadrat, and rubble patch size. Small isolated patches are incredibly important for biodiversity conservation (Wintle et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), showcasing the need to understand and protect the infauna found in rubble patches of all sizes.\u003c/p\u003e \u003cp\u003eThe probability of detecting Annelida is significantly greater in quadrats with greater volume/depth, more available interstitial space, and when rubble pieces are larger and less numerous. In these situations, there is a greater surface area available for colonisation and an expanded habitat complexity is thus present. Colonisation of fresh rubble fragments after a disturbance will likely follow the typical coral reef succession pattern, with primary colonisers of bacteria, protozoans, diatoms, algae, and invertebrate larvae settling first (Somma et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A greater volume of benthic community will lead to a greater accumulation of organic matter over time, compared to a baseline. In deeper rubble there is also more space for organic matter accumulation, which provides a greater source of nutrition to the rubble inhabitants. Both, greater benthic community volume and the subsequent organic matter accumulation could be the driving influence for Annelida presence patterns seen in varying rubble depth and fragment size.\u003c/p\u003e \u003cp\u003eThe type and composition of fragments within the rubble also plays a critical role in the likelihood of phylum presence. A higher percentage of branching coral fragments within the matrix significantly supports Annelida occurrence, likely due to the high structural complexity it creates. A higher percentage of shell pieces and rock fragments within the matrix is less favourable for Annelida, potentially reflecting the substrate instability and reduced burrowing potential. Members of 11 annelid families almost exclusively exist in interstitial environments (Worsaae et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), highlighting the importance of available space to this group of marine organisms. Polychaete samples taken from Cabo Pulmo, Mexico, found 82 species belonging to 61 genera and 21 families in dead \u003cem\u003ePocillopora verrucosa\u003c/em\u003e coral (Bastida-Zavala, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1995\u003c/span\u003e), while 82 species from 19 families were found on coral reefs in Central America (Dean, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), showing the high diversity of Annelida that can inhabit coral rubble. The trends seen in Annelida presence likelihood highlights the specific microhabitat preferences within the coral rubble matrix and suggests that not all rubble complexes offer equal ecological value for this group. Polychaete abundance and size in the Mexican Caribbean is larger in the back reef, suggesting that increased rubble movement influences the community composition (Hepburn et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The percentage composition of rubble did not influence the presence likelihood of any other phyla. This does not mean that the other phyla have no microhabitat preferences, but likely is a result of limited sample specimens collected.\u003c/p\u003e \u003cp\u003eWhile depth is widely recognized as a key driver of marine community structure, its limited influence in this study suggests that biological interactions may play a more dominant role in shaping phylum-level assemblages. Water depth drives assemblage structure of fish, invertebrate, and benthic communities (Bergen et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Costa et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Heidmann et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Saeedi et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, it was unexpected that water depth was only a significant influencer on the presence likelihood of \u0026ldquo;other\u0026rdquo; phyla. In over 94% of the sites (almost 84% of individually sampled quadrats), Annelida was the most abundant phylum collected (Taylor, Zimmermann \u0026amp; Beger, 2026 in prep). In sandy beach sediment, the presence of polychaete \u003cem\u003eScolelepis squamata\u003c/em\u003e inhibited the density development of Nemertea species (Maria et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), suggesting that fauna abundance and diversity can be controlled by biological interactions. In the sampled coral rubble beds, the high abundance of Annelida may have been dominating the habitat, reducing the abundance of other phyla.\u003c/p\u003e \u003cp\u003eThe differences seen in organism abundance by rubble patch size, adjacent habitat, and the interaction of patch size and adjacent habitat with phylum indicates that both are key factors influencing the abundance patterns in coral rubble beds. Annelida abundance was greatest in rubble patches which were adjacent to coral than another other habitat, and in category medium M patch sizes (1.1\u0026ndash;10 m\u003csup\u003e2\u003c/sup\u003e), and lowest in extra-large XL patch sizes (\u0026ge;\u0026thinsp;100 m\u003csup\u003e2\u003c/sup\u003e) and quadrats with seagrass, sand or rubble as the adjacent habitat. No other phyla had a significant difference in abundance in different rubble patch sizes or samples taken from rubble with differing adjacent habitats. Although the influence of patch size and adjacent habitat on Annelida abundance is consistent with the total specimen abundance, it is likely that the high proportion of Annelida in the total specimen count accounts for this.\u003c/p\u003e \u003cp\u003eSpatial patterns of intertidal invertebrate abundance vary on scales of centimetres to hundreds of metres. Small scale differences are likely due to behavioural responses to microhabitats, whilst large-scale differences are influenced by recruitment and mortality due to the limited adult dispersal (Underwood \u0026amp; Chapman, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). In coral rubble, we are likely seeing the effect of small-scale microhabitat preference within the rubble patches. Yet, among patches, the abundance and distribution of species is probably driven by recruitment from nearby adjacent habitats when the rubble is first formed and then from within the rubble once the patch is established. Surveys on \u003cem\u003ePanulirus guttatus\u003c/em\u003e (Caribbean spiny lobster) in Mexico showed that lobster density did not vary with reef complexity, however their diet included significantly more crustaceans in the less complex reef patch (Lozano-\u0026Aacute;lvarez et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This suggests that although shelter is an important driver in microhabitat preference, it is likely not the most influential.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOverall, our results emphasise that coral rubble bed infaunal communities are shaped not only by microhabitat complexity, but also by the surrounding habitat matrix. The physical rubble fragment characteristics are important to both the presence likelihood and abundance of multiple phyla. Whilst the broader spatial context of coral rubble is highly influential in both the total abundance of infauna and in individual phylum occurrence. Additional studies including more samples of the less dominant marine groups are needed to fully understand the effects of the physical, biological, and ecological characteristics of coral rubble beds on their associated infauna.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eCompeting Interest Statement:\u003c/strong\u003e \u003cp\u003eNo competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by M.E.T. Funding acquisitions were made by M.E.T. and A.Z. The first draft of the manuscript was written by M.E.T. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to thank the staff and interns at the Turks and Caicos Reef Fund for their assistance in the field data collection. We would also like to thank L. Harris, G. Paulay, J. Lang and G. Hendler for their assistance in identifying the collected specimens.Research was conducted under the Department of Environment and Coastal Resources (DECR) Turks and Caicos Islands Scientific Research Permit #2023-04-17-20 and #2022-06-07-27.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData deposition information itemGenetic data: Stored in BOLD Systems. Code \u0026ldquo;TCICR\u0026rdquo;. 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Interstitial Annelida. \u003cem\u003eDiversity\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(2), 77. https://doi.org/10.3390/d13020077\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"coral-reefs","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"core","sideBox":"Learn more about [Coral Reefs](http://link.springer.com/journal/338)","snPcode":"338","submissionUrl":"https://submission.nature.com/new-submission/338/3","title":"Coral Reefs","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Benthic ecology, reef degradation, reef rubble, spatial heterogeneity","lastPublishedDoi":"10.21203/rs.3.rs-9550127/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9550127/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGlobally, coral rubble beds are becoming more prevalent and abundant due to increasing anthropogenic impacts. Despite this, our understanding of the biodiversity and community composition differences of coral rubble organisms is severely lacking. Here, we aim to determine the factors influencing infaunal communities in coral rubble beds in the Turks and Caicos Islands. We collected coral rubble and its associated infauna from 53 sites across the archipelago. Following identification of the specimens, we used logistical regressions models, principal component analyses, and two-way ANOVA to determine if differences in coral rubble biodiversity are influenced by abiotic factors, such as rubble patch size, volume of space within the matrix, and type of rubble present, or biotic factors, such as adjacent habitat. Analysis of the almost 2800 specimens discovered that the highest total specimen abundance is found in smaller rubble patches, and in those with live coral as the closest adjacent habitat. The likelihood of individual phyla presence was influenced by different factors, with very few driving differences in more than one phylum. Our results highlight the complexity of community composition within coral rubble beds and demonstrate that small rubble patches form a valid part of the coral reef ecosystem.\u003c/p\u003e","manuscriptTitle":"Both small-scale microhabitat preference and large-scale spatial complexity influence coral rubble bed infauna","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-13 09:05:42","doi":"10.21203/rs.3.rs-9550127/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"17677023764501027168046996155292933768","date":"2026-05-11T07:26:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"11452380156692290135854073212612100017","date":"2026-05-05T03:25:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-05T03:24:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-03T01:02:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-29T15:41:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Coral Reefs","date":"2026-04-28T07:19:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"coral-reefs","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"core","sideBox":"Learn more about [Coral Reefs](http://link.springer.com/journal/338)","snPcode":"338","submissionUrl":"https://submission.nature.com/new-submission/338/3","title":"Coral Reefs","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"faf5d73e-b2e2-43ee-ac92-d8c3683ac231","owner":[],"postedDate":"May 13th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"17677023764501027168046996155292933768","date":"2026-05-11T07:26:39+00:00","index":9,"fulltext":""},{"type":"reviewerAgreed","content":"11452380156692290135854073212612100017","date":"2026-05-05T03:25:36+00:00","index":7,"fulltext":""},{"type":"reviewersInvited","content":"4","date":"2026-05-05T03:24:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-03T01:02:56+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T09:05:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-13 09:05:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9550127","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9550127","identity":"rs-9550127","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}