Beyond biodiversity: the role of Paramuricea clavata forests in supporting ecosystem functioning

Beyond biodiversity: the role of Paramuricea clavata forests in supporting ecosystem functioning | 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 Article Beyond biodiversity: the role of Paramuricea clavata forests in supporting ecosystem functioning Alberto Colletti, Luca Licciardi, Erika Fabbrizzi, Antonia Chiarore, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6277481/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Marine animal forests, composed of sessile suspension feeders such as gorgonians are known to host rich communities that support important ecosystem functions and services. These habitats are undergoing dramatic loss due to multiple pressures, with potential cascading effects on ecosystem dynamics that remain poorly understood. To address this critical knowledge gap, we used fine-scale data to assess the role of Paramuricea clavata forests in supporting biodiversity and ecosystem functioning at multiple locations, on a regional scale. Through functional trait analysis, we compared taxonomic and functional diversity of benthic assemblages inside and outside P. clavata forests and investigated the loss of traits as a consequence of forest loss. Analyses revealed significant enhancements in both taxonomic and functional diversity within P. clavata forests, with observed increased species and functional richness. Trait-based investigations revealed a higher abundance of colonial heterotrophic species within forests, while outside, assemblages were dominated by low-longevity autotrophs, suggesting that P. clavata modifies environmental variables creating unique ecological conditions that favor specific traits. β-diversity measurements demonstrated increased compositional and functional turnover inside forests, indicating that P. clavata provides more available niches, supporting the replacement of species and functions. Our findings offer insights into how marine animal forests can structure marine communities, with broader implications for understanding biodiversity loss in changing marine ecosystems. Biological sciences/Ecology/Biodiversity Biological sciences/Ecology/Community ecology Biological sciences/Ecology Earth and environmental sciences/Ecology habitat-forming species functional ecology functional traits β-diversity turnover biodiversity loss Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Biodiversity loss is pervasive across ecosystems, with expected large-scale ecological consequences for ecosystem functioning and the benefits nature provides to people [ 1 ]. A major concern is the loss of species that form forests, as these species directly regulate resource availability for themselves and for other species. In terrestrial ecosystems, this process has been well-documented, with clear evidence that widespread deforestation drastically reduces biodiversity, alters species composition and traits, and has significant effects on various ecological processes [ 2 ]. On the contrary, the response of marine ecosystems to the loss of habitat-forming species is less documented. Recent studies have indicated that marine macroalgal forests and seagrass meadows are at risk [ 3 , 4 , 5 ], with alarming projections for their future [ 6 ]. Dramatic loss in the biomass and biodiversity of ‘animal forests’ has also been globally observed [ 7 , 8 ], driven by multiple stressors ranging from local to global changes [ 9 ]. Sessile suspension feeders, such as gorgonians, dominate these communities and generate complex, three-dimensional structures similar to trees in terrestrial forests [ 7 ]. Their role in providing food, protection and nursery to associated species, as well as contributing to the blue carbon budget, is well recognized [ 10 ]. As habitat-forming organisms, their loss is expected to reduce biodiversity and erode species traits, thereby disrupting important ecosystem services [ 11 ]. The Mediterranean Sea, considered a miniature ocean [ 12 ], is a hotspot of biodiversity although one of the most impacted areas of the planet, where pollution, overfishing, habitat destruction and non-indigenous species introductions are producing large effects at basin scale [ 13 , 14 ]. Climate change is severely affecting Mediterranean marine ecosystems faster than expected [ 15 ], with unprecedented loss of habitat formers [ 16 ]. In this respect, Paramuricea clavata Risso (1827) is a paradigmatic example. It is a long-lived species listed as a vulnerable species by the International Union for Conservation of Nature [ 17 ], with slow growth rate, annual recruitment and late reproductive maturity, making it particularly vulnerable to human disturbances [ 18 , 19 ]. It shows a large-scale distribution [ 20 ] living at depths ranging from 15 to 200 meters [ 21 , 22 ] and contributing to the three-dimensional complexity of coralligenous outcrops, a Mediterranean biogenic temperate reef formed by complex and heterogeneous benthic assemblages. Paramuricea clavata has a critical functional role since it is supposed to stabilize key environmental variables such as light intensity, water flows, and sedimentation rate, thus supporting the settlement and growth of underlying benthic species [ 23 , 24 ]. Several studies have reported mass mortality events of P. clavata populations due to increasing frequency of extreme climate events (marine heat waves, storms) together with other sources of disturbance such as fishing pressure, ultimately affecting population's resilience and resistance [ 9 , 25 , 26 , 27 , 28 , 29 ], also highlighting dramatic effects on the associated community [ 9 , 30 , 31 ]. However, despite the importance of this species, the consequences of its loss are still little known. Fine-scale data are needed to understand if the presence of P. clavata forests support assemblages with distinct structural and ecological features able to provide specific ecosystem processes and associated ecosystem services. Such data are essential for predicting future changes in this habitat and the associated ecological processes under global change scenarios, addressing the long-term ecological implications of the decline and loss of P. clavata . Simultaneously exploring taxonomic and functional aspects of biodiversity provides a more comprehensive understanding of community assembly processes [ 32 ]. Functional traits are those specific characteristics or attributes of organisms that influence their performance and interactions within ecosystems [ 33 ]. The unique combination of traits in a species identifies a functional entity (FE) meaning that species that share the same traits belong to the same FE [ 34 , 35 ]. The functional trait approach presents some limitations, since there is a deep gap of knowledge on trait-specific information which leads to their simplification by scientific experts. Nevertheless, this methodology can provide valuable insights to complement taxonomic analyses and to assess changes in ecosystem functioning [ 36 ]. Recently, trait-based indices have been introduced as an alternative ‘functional’ approach to assess the relationships between biodiversity and human disturbances. Indeed, these indices have the potential to determine the cause of change in systems by investigating the type of traits affected. Evidence showed that human pressures selectively remove a distinct suite of traits from assemblages [ 37 , 38 ]. For instance, ocean acidification reduces the abundance of calcifying species with three-like morphologies, favoring low-lying fast-growing species across different habitats [ 39 ]. Also, mechanical disturbances such as bottom trawling have negative effects on large epifaunal filter feeders, which are more sensitive to physical stressors, and are replaced by mobile infaunal scavengers [ 40 , 41 ]. This approach enables to identify the most vulnerable traits to a specific source of disturbance, allowing to anticipate potential shifts in ecosystem properties. β-diversity refers to the variations in species composition across different habitats or spatial units and it can be partitioned into species replacement (turnover) and richness differences (nestedness), allowing to disentangle the contribution of the two mechanisms to the heterogeneity and thus to understand causes generating differences in species composition [ 42 ]. While research has primarily focused on compositional β-diversity, combining both compositional and functional β-diversity provides a valuable lens for understanding how ecological processes and human pressures drive species assemblages and distribution, offering key insights for species conservation and ecosystem management [ 43 ]. Because functional traits reflect species’ adaptive strategies to the environment, numerous studies on functional β-diversity have rapidly emerged over the past two decades. These studies show contrasting turnover and nestedness-resultant components of compositional and functional β-diversities [ 44 ] and demonstrate the importance of considering the multifaceted nature of biodiversity when examining community assembly [ 32 ]. Recently, Verdura et al. (2019) [ 9 ] revealed the role of P. clavata as a habitat-forming species, able to mitigate the effects of warming by maintaining the original assemblage dominated by macroinvertebrates and delaying the spread of the invasive species. Gomez et al. (2021) [ 31 ] documented how marine heatwaves (MHWs) can affect the functional structure of P. clavata dominated assemblages with detrimental consequences on several ecological processes and their associated ecosystem functions. In this study, we use fine-scale data from replicated locations in the central Mediterranean Sea, applying both taxonomic and functional approaches to test the hypothesis that the understory assemblages associated with P. clavata forests exhibit distinct features compared to coralligenous assemblages where the forests are absent. Traits analysed in this study include ‘effect’ traits ( e.g. morphological, physiological and phenological features of species involved in the understory) and ‘response’ traits ( e.g. reproductive and dispersal strategies) for understanding the potential contribution of P. clavata assemblages to the functioning of Mediterranean coastal ecosystems. 2. Material and methods 2.1 Study area The Gulf of Naples (Italy) is a semi-enclosed embayment nestled within the southeastern Tyrrhenian Sea (Mediterranean Sea). The basin is South-West oriented and bounded by the islands of Procida and Ischia to the North, and by the island of Capri and the Sorrento peninsula to the South. Six locations were sampled based on prior knowledge of the presence of P. clavata forests within the operative depth of recreational scuba diving of 30–40 meters. The selected locations were: Ischia (Punta Sant’Angelo) (1) and Procida (Punta Pizzaco) (2), located within the Regno di Nettuno Marine Protected Area; Scoglio Penna (3) and Scoglio del Vervece (5), within the Punta Campanella MPA; Banco di Santa Croce (6), area protected by Ministerial Decree of June 15, 1993 and the location of Capri (4), out of protection boundaries (Fig. 1 ). For each location, we randomly selected two sites (A, B) about 50 m apart from each other, with similar slope and exposition. In each site, data were collected from both the conditions considered in the study (inside and outside P. clavata forests). 2.2 Data collection Data collection has been carried out during scuba diving surveys in summer 2022. Within each site, photographic sampling of benthic assemblages was conducted using ten random replicate quadrats of 25x25 cm for each of the two conditions: inside P. clavata forest and in the adjacent zone outside P. clavata forest. Additionally, six random quadrats of 50x50 cm were used in each site within the forest to count P. clavata colonies to later assess the density and population structure. Each P. clavata colony inside these quadrats has been measured with a ruler from the base to the end of the farthest tip [ 45 ]. The sampling unit of six 50x50 cm was chosen following Linares et al. (2008) [ 19 ], who found the stabilization of the s.e.m. (standard error of the mean) as a proportion of the mean colony density with a sample size of 1.5 m². The photographic sampling was carried out using Canon G7X Mk III in Nauticam housing and equipped with two strobe lights. The percentage cover of sessile organisms was quantified using the photoQuad_v1_4 software [ 46 ]. During the analysis, each species has been identified at the lowest possible taxonomic level, and when specific identifications were not feasible, a morpho-functional group has been assigned ( e.g. algal turf, encrusting sponge). 2.3 Data analysis 2.3.1 Paramuricea clavata forests To assess the health status of P. clavata forests, mean height, density and biomass of each colony have been calculated for each site. Height measurements collected in the field were used to estimate the biomass using the relationship B = 0.002H²∙⁶¹ reported by Coma et al. (1998) [ 47 ] and corrected by Linares et al. (2008) [ 19 ], where B is the biomass of dry weight (DW) in grams and H is the colony height in centimeters. The population structure was assessed by assigning each colony to a size class with a 10 cm range and then reporting the frequency distribution of each size class across sites. Size distribution was analysed using the skewness and kurtosis coefficients [ 19 , 48 ]. Skewness measures the asymmetry of a distribution relative to its mean. When skewness is significant, it indicates that the distribution is not symmetrical. Positive skewness suggests a predominance of smaller size classes within the population, while negative skewness indicates a dominance of larger size classes. Kurtosis assesses the sharpness of the distribution's peak around its central mode. A significant kurtosis value implies that the distribution has longer tails compared to a normal distribution, reflecting a higher prevalence of certain size classes within the population. Skewness and kurtosis coefficients are considered significant if the ratio of their values to their standard error exceeds 2 [ 48 ]. Population dynamics of marine animal forests are regulated by density-dependent processes determined by the intra-specific competition for the use of resources such as food and space [ 49 ]. As a result of this self-thinning mechanism, pristine populations are characterized by large colonies, while in young or impacted populations, high densities of small colonies saturate the space [ 19 , 50 ]. We assessed the relation between biomass and density of P. clavata populations through a linear regression with the log-log model as a descriptor of population conservation status [ 19 ]. 2.3.2 Experimental design and statistical analysis Statistical analyses were performed to test the hypothesis that P. clavata forests have the role of increasing local compositional and functional diversity. To test these hypotheses, we applied a multifactorial design consisting of three factors: location (Lo, 6 levels, random), site (Si, 2 levels, random and nested in location) and condition (Co, 2 levels, fixed and orthogonal), with n = 10 replicates. The analyses are described in the sections below 2.3.2.1 Functional traits and trait space Twelve categorical and/or ordinal functional traits were identified on the base of previous studies on benthic assemblages [ 35 , 43 ]: (1) Morphology, (2) Coloniality, (3) Maximum longevity, (4) Size, (5) Epibiosis, (6) Energetic resource, (7) Major photosynthetic pigment, (8) Feeding strategy, (9) Potential of asexual reproduction, (10) Growth rates, (11) Defences, (12) Propagules (Table S1 ). Functional traits were subdivided into categories, and, for each species, a category was assigned based on the relative trait determined through extensive bibliographic research (see supplementary materials) on biological and ecological characteristics of that species (Table S1 ). Subsequently, each species has been classified into a functional entity (FE) ( i.e. groups of species with unique combinations of functional traits) [ 34 ]. The functional richness (FRic) has been calculated as the percentage of the volume of the multidimensional trait space occupied by all FEs in a community within the functional space [ 37 ]. To create this multidimensional trait space, a Principal Coordinates analysis (PCO) was performed on FEs, based on a Gower dissimilarity matrix, chosen since it allows the analysis of mixed types of data while giving them equal weight [ 51 ]. Seven PCO dimensions were selected, based on the lowest mean squared-deviation index value (mSD = 0.0022), to ensure a faithful representation of trait-based differences between species. The coordinates of each FE obtained by PCO were used to calculate the FRic for each quadrat sampled during the study to assess statistically significant differences between conditions, and across sites and locations. These coordinates were also used to visualize spatial differences in functional richness. To examine differences in trait composition and abundance between conditions in space, Community-Weighted Mean (CWM) was calculated as the average of trait values for species at each quadrat weighted by the relative abundance of each species possessing that trait. CWM of traits is a valuable index for evaluating shifts in mean trait values within communities due to environmental selection for specific functional traits [ 52 , 53 ]. 2.3.2.2 Univariate and multivariate analyses A three-way univariate analysis of variance was carried out using PERMANOVA based on Euclidean distances of untransformed data [ 54 ] to assess differences in species richness, in the number of FEs and in the FRic, between conditions and across locations and sites. Each term was tested using a maximum of 999 permutations. To investigate the effect of P. clavata on taxonomic and functional structure, and CWM, multivariate analyses were performed using PERMANOVA based on the Bray-Curtis resemblance matrix calculated on fourth root transformed data to reduce the differential between dominant and rare species. Each term was tested using a maximum of 999 random permutations of the appropriate units [ 55 ]. Non-metric multidimensional scaling ordinations were carried out on CWM to display differences on functional diversity between conditions at the scale of sites, since the interaction term Si(Lo)×Co was found significant in the multivariate analysis. Statistical analysis has been performed using PRIMER software (v.7). 2.3.2.3 Compositional and functional β-diversity According to Villéger et al. (2011) [ 56 ], compositional β-diversity is calculated as the ratio of species not shared between assemblages relative to the total number of species. By analogy, the functional β-diversity is quantified as the ratio of FEs not shared between assemblages relative to the total FEs. Compositional and functional β-diversity analyses, based on the Jaccard resemblance matrix on presence/absence transformed data, were carried out within condition and partitioned into the two β-diversity component nestedness and turnover. Turnover can be defined as the degree of species replacement reflecting the selective differentiation of species among assemblages because of environmental sorting [ 42 , 57 ]. Nestedness, on the other hand, refers to the hierarchical arrangement of species assemblages, wherein species present in species-poor habitats are subsets of those found in species-rich habitats, often in response to environmental gradients [ 58 ]. A permutational analysis of multivariate dispersion (PERMDISP) [ 54 ] was then carried out to test statistically significant differences in the heterogeneity between conditions (In vs. Out). PCO based on Jaccard dissimilarity matrix was performed for compositional and functional β-diversity and its components to visualize differences in terms of community heterogeneity between conditions. FRic, CWM and β-diversity analyses were performed using the R functions from the 'FD', 'tripack', 'geometry', 'matrixStats' and 'betapart' R package (R v 3.4.1, R development Core Team, 2017) [ 59 , 60 , 61 , 62 , 63 ]. 3. Results 3.1 Paramuricea clavata forests The mean P. clavata density ranged from 27.3 ± 5.9 to 65.3 ± 27.1 colonies/m² ± s.e.m., while lowest and highest biomass values corresponded to 100.1 ± 89.7 and 505.4 ± 367.7 g dry weight/m² ± s.e.m., respectively (Table S2 ). Small colonies (< 10 cm) were the most represented in all investigated populations (Fig. 2 ). Skewness coefficients confirmed that most of the size class distributions (11 out of 12 sites) were significantly positively skewed, indicating the prevalence of small size classes. The kurtosis coefficients also showed a significantly positive trend in 10 out of the 12 sites, highlighting the presence of long tails in the size class distribution of P. clavata colonies among sites. Paramuricea clavata populations showed no significant relationship between density and biomass (R² = 0.097; p = 0.3234) (Fig. S1 ). 3.2 Species richness, functional entities and functional richness of the understory assemblages in presence and in absence of the forests A total of 80 species/taxa were found in the understory assemblages and grouped in 63 FEs. Univariate analyses revealed the effect of the presence of P. clavata forests on the number of species ( p = 0.012), the number of functional entities (FEs, p = 0.009) and functional richness (FRic, p = 0.042) (Table S3). Differences were consistent across sites and locations for the three variables (Table S3). More specifically, the mean number of species and FEs were higher inside the forests (9 ± 0.3 s.e.m.; 8.8 ± 0.2 s.e.m. respectively) compared to the areas outside (7.5 ± 0.2 s.e.m.; 7.5 ± 0.2 s.e.m. respectively). Additionally, FRic was also higher inside the forests at all locations (Fig. 3 ), with a higher mean value (20.9 ± 3.2 s.e.m.) compared to the areas outside (9.3 ± 2.1 s.e.m.). 3.3 Structural and functional changes in the understory assemblages in presence and in absence of the forests The multivariate analysis showed a significant effect of the forests on the taxonomic structure of the understory assemblages, differing across sites ( p = 0.001) (Table S4). However, a posteriori pairwise comparisons indicated that in almost all sites (11 out of 12) a distinct community structure inside vs. outside the forest was found (Table S5). Differences between conditions were mainly driven by the presence of invertebrates ( e.g. Cliona viridis , Crambe crambe, Pleraplysilla spinifera, Schizomavella mamillata ) inside the forests, while algal species ( e.g. Dictyotales and the non-indigenous species Caulerpa cylindracea and Lophocladia trichoclados ), mucilage and sediments were more abundant outside the forests. A significant effect of the forests was also found on the functional structure of the assemblages in terms of composition and relative abundance of FEs ( p = 0.001) (Table S4), and a posteriori pairwise comparisons show significant differences in 10 out of the 12 sites included in the analysis (Table S5). The multivariate analysis showed a significant effect of P. clavata forests on the CWM of traits but not consistently across sites ( p = 0.012) (Table S6). A posteriori pairwise comparisons indicated that the functional traits differed between conditions in 7 out of 12 sites (Table S7). The nMDS analyses carried separately for each site reported that colonial heterotrophs, with lecithotrophic larvae, physical and chemical defences and non-photosynthetic pigments were more abundant within the forests, while low-longevity autotrophs that mainly use phycoerythrin pigments ( e.g. , rhodophytes) and reproduce via spores characterized communities outside the forests (Fig. S2 ). 3.4 Patterns of heterogeneity in the understory assemblages in presence and in absence of the forests PERMDISP analysis revealed significant differences in community heterogeneity between the two conditions, both at the compositional and functional level ( p = 0.001) (Fig. 4 ). More specifically, a higher heterogeneity was observed inside the forests than outside for both compositional (0.683 ± 0.001 s.e.m. inside vs. 0.612 ± 0.002 s.e.m. outside) and functional (0.673 ± 0.001 s.e.m. inside vs. 0.610 ± 0.002 s.e.m. outside) analyses (Fig. 5 ), suggesting less variability in the patterns of distribution of benthic assemblages in absence of P . clavata . The breakdown into the two components revealed that turnover is the major component of the pattern of heterogeneity for both conditions. Even in this case, the turnover component of community heterogeneity was higher inside the forests than outside, both at the compositional (0.555 ± 0.002 s.e.m. inside vs. 0.486 ± 0.002 s.e.m. outside) and functional level (0.546 ± 0.002 s.e.m. inside vs. 0.482 ± 0.002 s.e.m. outside) (Fig. 5 ) and both differences were statistically significant ( p = 0.01) (Fig. 4 ). In other words, rather than having a gain or loss of species/functions going from one condition to another, communities associated with P. clavata compose a distinct and heterogeneous assemblage from both compositional and functional point of view. A summary of the results obteined from univariate and multivariate analyses is reported in Table 1 . Table 1 Summary of statistical analysis results for each response variable. Sp = species richness; FE = FEs richness; FRic = functional richness; TS = taxonomic structure; FS = functional structure; CWM = Community-Weighted Mean; FR = fourth root. Significant differences are shown as follow * P < 0.05.** P < 0.01.*** P < 0.001. Sp FEs FRic TS FS CWM Lo ** Co * ** * Si(Lo) ** ** ** Lo×Co * * Si(Lo)×Co *** *** * Transformation None None None FR FR FR 4. Discussion In temperate regions, the decline and loss of habitat-forming species in response to multiple anthropogenic stressors is increasingly documented [ 6 ], with indications of the drivers behind these changes and their consequences in terms of species composition and relative abundance. Among habitat formers, marine animal forests are recognized as biodiversity hot-spot for different communities including meiofauna, infauna, sessile and vagile species, epibionts and ichthyofauna [ 7 , 64 , 65 , 66 , 67 , 68 ]. However, the limited quantitative knowledge about their distribution and functional role hampers our understanding of the underlying causes of their increasing loss and our ability to predict future changes, which could lead to regime shifts and alterations of associated biodiversity [ 69 ]. By using fine-scale data, we document that the presence of P. clavata forests favors the development of distinct benthic assemblages, characterized by consistently higher species richness and different community structures compared to areas where forests are absent. However, small, non-reproductive P. clavata colonies dominating the population structure might be associated with the presence of ongoing stressors affecting subtidal assemblages [ 19 ]. The Gulf of Naples is an urbanized coastal region, and multiple stressors such as fishing and climate-related events may affect the status of P. clavata forests [ 13 , 70 , 71 , 72 ]. Our study represents a baseline for this area of the Mediterranean Sea and expands current knowledge on biodiversity associated with these forests, which has been sparse and fragmented across very few Mediterranean regions, already documenting that the loss of P. clavata forests can lead to significant changes in recruitment patterns in the understory assemblages [ 65 , 73 ] resulting in lower species diversity and richness [ 9 , 38 ]. Systematic efforts and long-term monitoring focused on improving knowledge of marine animal forests and associated biodiversity are needed to quantitatively assess the status and the effects of different combinations of stressors across the basin. This information is particularly urgent, given that cnidarians are more affected than any other group by strong thermal anomalies, which are leading to mass mortality events at the Mediterranean scale [ 16 ]. Our findings also show that the presence of the forest supports a different functional structure with more functional entities and higher functional richness and that results are consistent at both the scales of tens' meters and kilometres. A broader occupation of the functional trait space indicates a more diverse set of ecological roles and processes being supported under the forests. Heterotrophy, coloniality and the presence of species with defined physical and chemical defenses are prevalent within the forests. Outside the forests, fast-growing and low-longevity primary producers replace heterotrophs, possibly altering ecological processes involved in energy fluxes, such as productivity and benthic-pelagic coupling, with cascade effects across biodiversity levels [ 74 ]. Food provision and carbon sequestration can be also affected by this functional shift [ 10 , 75 , 76 , 77 , 78 ]. These patterns correspond to those reported for P. clavata and Corallium rubrum before and after the occurrence of marine heat waves, when fast-growing autotrophic species ( e.g. algal turf, Caulerpa cylindracea ) rapidly colonized the free spaces after mass mortality events at the expense of morphologically complex and long-lived heterotrophs [ 31 ]. This evidence highlights the importance of animal forests in influencing environmental variables, creating unique habitat conditions that selectively favor the settlement of certain species [ 23 , 79 ]. Additionally, the physical structure of P. clavata colonies has been observed to act as a filter for mucilage accumulation and to reduce water flow, limiting sediment resuspension and deposition [ 24 , 73 ]. A higher abundance of mucilage, sediments and of non-indigenous species L. trichoclados and C. cylindracea was recorded outside P. clavata populations. This function is vital for preventing the establishment of invasive species such as Caulerpa cylindracea , which thrives in sediment-rich and disturbed conditions [ 35 , 73 , 80 ]. Nevertheless, while the presence of P. clavata protects the associated community from the spread of the mucilage and the resulting negative aspects on the community itself, mucilage that remains attached to the colony can induce necrosis, generating a diffused oxidative stress in the entire P. clavata colony and affecting its physiological processes [ 81 ]. The results, so far, are also in accordance with the biotic resistance hypothesis, which states that more diverse communities are more resistant to invasion due to the complementary use of resources by natives (complementary effects) or the higher probability of including highly competitive native species which limit the use of resources by invaders [ 82 , 83 ]. The specific environmental conditions created by P. clavata likely represent also the driver of the high heterogeneity assessed inside the forest, as has been documented for other habitat-forming species [ 84 ]. β-diversity analysis contributed to identifying P. clavata forests as hot-spots of temperate reef biodiversity, with greater total compositional and functional β-diversity inside the forest compared to adjacent zones. Outside the forests, the less heterogeneous patterns of distribution found include both compositional and functional β-diversity. Here, biotic homogenization could be driven by the presence of stressors such as invasive species, sediments and mucilage, leading to species loss and decrease of more vulnerable species ( e.g. Myriapora truncata, Smittina cervicornis ) [ 85 , 86 ]. Thus, areas outside the forest reflect the characteristics of more disturbed conditions than assemblages associated with P. clavata , featured by the gain of species and functions which foster the recovery or resistance to disturbances like biological invasions [ 87 , 88 ]. The breakdown into the two components revealed that species replacement dominates both compositional and functional β-diversity. Turnover in species composition translates into functional turnover when communities have low functional redundancy ( i.e. low number of species performing similar functions) [ 89 ]. The positive correlation between these complementary aspects of β-diversity may be related to the high variability of environmental conditions, which lead species to a differential partitioning of resources, resulting in a high turnover of species performing different functions. This pattern has also been observed in shallow subtidal habitats, where environmental factors ( e.g. temperature, light exposition, hydrodynamism) are highly variable and likely drive the species sorting [ 43 ]. In contrast, environmental homogenization can induce functional nestedness even though compositional turnover represent the dominant component [ 43 , 89 ]. In our study, the increase of the compositional and functional turnover inside the forests suggests that the presence of P. clavata drives the replacement of species and functions [ 90 ], possibly arising from differences in niche features between the two conditions [ 32 ]. The high habitat complexity created by the forests allows the colonization by organisms with different ecological needs, compared to more simple habitats [ 91 ]. Therefore, preserving the integrity of the P. clavata populations is crucial to ensure the maintenance of the habitat complexity which in turn is vital to support compositional and functional diversity. Results of our study highlight the need of improving the conservation effort for this species. Currently, only 18% of P. clavata potential habitat at the Mediterranean scale is under protection regimes [ 22 ]. Considering the increasing pressures related to climate change, local threats need to be removed to limit cumulative and synergistic negative impacts on animal forests and associated assemblages [ 28 ]. Present efforts to achieve the 30% conservation target set by the new EU Biodiversity Strategy for 2030 should translate into specific strategies for the inclusion of P. clavata forests within Marine Protected Areas [ 92 ], an effective tool to protect this habitat and enhance its resilience [ 93 ]. Quantitative information and fine-scale data on the distribution and status of P. clavata are also relevant for the Nature Restoration Law (NRL). The NRL constitutes the EU’s long-term strategy to restore biodiversity and ecosystem services over the next decades [ 94 ], recently approved by the EU with the objective to halt and reverse biodiversity loss. However, the NRL sets very ambitious quantitative targets in terms of both the areas to restore and the timeframe for their restoration, considering the current poor knowledge about the distribution and status of several species and habitats across the EU, including P. clavata forests. Achieving these targets requires urgent development of knowledge, methodologies, tools, and best practices to monitor progress and ensure success. This work addresses these gaps to consolidate existing knowledge for a successful implementation of EU Directives. Declarations Competing interests The authors declare no competing interests. Author Contribution S.F. and Al.Co. conceived the study; Al.Co., L.L., An.Ch., S.D., M.M., S.M.S.M., C.S. participated in the field work; L.L., Al.Co., S.F. and E.F. performed the data analyses; S.F., Al.Co. and L.L. led the writing of the manuscript with the contributions from E.F., An.Ch., S.D., M.M., S.M.S.M., C.S., P.S; Al.Co. and L.L. are authors with equal contribution. Acknowledgement The authors thank the projects “National Biodiversity Future Center - NBFC”, project code CN_00000033, Concession Decree No. 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research; the Horizon Europe CLIMAREST Project (Coastal Climate Resilience and Marine Restoration Tools for the Arctic Atlantic basin) (GA no. 101093865) and the European Union’s Horizon Europe Research and Innovation Programme ACTNOW (Advancing understanding of Cumulative Impacts on European marine biodiversity, ecosystem functions and services for human wellbeing), GA no. 101060072 for funding. 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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-6277481","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":437318573,"identity":"83e36f4f-22be-47a1-9a7e-d470a2e13fec","order_by":0,"name":"Alberto Colletti","email":"","orcid":"","institution":"University of Naples Federico II","correspondingAuthor":false,"prefix":"","firstName":"Alberto","middleName":"","lastName":"Colletti","suffix":""},{"id":437318575,"identity":"acbdfe08-3d69-4af3-96d2-47ba3cad78c2","order_by":1,"name":"Luca Licciardi","email":"","orcid":"","institution":"University of Naples Federico II","correspondingAuthor":false,"prefix":"","firstName":"Luca","middleName":"","lastName":"Licciardi","suffix":""},{"id":437318577,"identity":"d9a09ae6-7901-4ccc-965f-35d692275745","order_by":2,"name":"Erika Fabbrizzi","email":"","orcid":"","institution":"University of Naples Federico II","correspondingAuthor":false,"prefix":"","firstName":"Erika","middleName":"","lastName":"Fabbrizzi","suffix":""},{"id":437318578,"identity":"85854b6b-f9dc-440a-b499-723af2f716b3","order_by":3,"name":"Antonia Chiarore","email":"","orcid":"","institution":"Stazione Zoologica Anton Dohrn, Ischia Marine Centre","correspondingAuthor":false,"prefix":"","firstName":"Antonia","middleName":"","lastName":"Chiarore","suffix":""},{"id":437318579,"identity":"6400ecbb-2e17-46b0-a52c-d3cb50fd66c4","order_by":4,"name":"Sara Benedictis","email":"","orcid":"","institution":"University of Naples Federico II","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Benedictis","suffix":""},{"id":437318580,"identity":"8f2ae21d-0c00-4461-b212-fdb45e00c496","order_by":5,"name":"Marco Munari","email":"","orcid":"","institution":"University of Padova","correspondingAuthor":false,"prefix":"","firstName":"Marco","middleName":"","lastName":"Munari","suffix":""},{"id":437318581,"identity":"66bf1b2a-083a-4718-ae5b-aa673ef448f8","order_by":6,"name":"Simone Maria Santo Musumeci","email":"","orcid":"","institution":"University of Naples Federico II","correspondingAuthor":false,"prefix":"","firstName":"Simone","middleName":"Maria Santo","lastName":"Musumeci","suffix":""},{"id":437318582,"identity":"d575d594-2614-4989-a72c-5911480b1149","order_by":7,"name":"Chiara Silvestrini","email":"","orcid":"","institution":"University of Naples Federico II","correspondingAuthor":false,"prefix":"","firstName":"Chiara","middleName":"","lastName":"Silvestrini","suffix":""},{"id":437318583,"identity":"b7430571-9493-4329-88b4-180320f32d05","order_by":8,"name":"Patrizia Stipcich","email":"","orcid":"","institution":"University of Naples Federico II","correspondingAuthor":false,"prefix":"","firstName":"Patrizia","middleName":"","lastName":"Stipcich","suffix":""},{"id":437318584,"identity":"17e3b71b-13a9-483f-b049-8fbb6545f97f","order_by":9,"name":"Simonetta Fraschetti","email":"data:image/png;base64,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","orcid":"","institution":"University of Naples Federico II","correspondingAuthor":true,"prefix":"","firstName":"Simonetta","middleName":"","lastName":"Fraschetti","suffix":""}],"badges":[],"createdAt":"2025-03-21 12:08:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6277481/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6277481/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-26902-4","type":"published","date":"2025-11-28T15:57:54+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80879945,"identity":"3d5564c2-42ba-4934-9139-a4d3839edcf5","added_by":"auto","created_at":"2025-04-18 07:30:46","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51730,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the sampling locations in the study area. Mean density and biomass values of the \u003cem\u003eP. clavata \u003c/em\u003ecolonies are represented as different circle colours (biomass) and dimensions (density).\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6277481/v1/19438593004bdb00987b8e5b.jpg"},{"id":80879944,"identity":"0bb2ef34-d8fb-4e7f-a661-3501a090aee2","added_by":"auto","created_at":"2025-04-18 07:30:46","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":40847,"visible":true,"origin":"","legend":"\u003cp\u003ePopulation structure. \u003cem\u003eParamuricea clavata \u003c/em\u003epopulation structure for site A (grey) and B (white) of assessed locations.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6277481/v1/7b604cdfb711bbe59f9019f1.jpg"},{"id":80879947,"identity":"d1566327-47da-4efe-b5f7-50da8504c440","added_by":"auto","created_at":"2025-04-18 07:30:46","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":39387,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional richness inside (red) \u003cem\u003evs. \u003c/em\u003eoutside (green) the forests. The total functional space given by all FEs found in this study is represented as a grey polygon. Vi: volume inside the forest; Vo: volume outside. NbFEs(In): total number of FEs within the location inside the forest; NbFEs(Out): total number of FEs within the locality outside the forest. The axes PCO1 and PCO2 represent the first two dimensions of the 7D functional space and cumulatively explain 69.1% of the total variance.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6277481/v1/84543d5ce6265d2ac652a407.jpg"},{"id":80879951,"identity":"45124765-7503-49b1-bec6-f55cfd507c90","added_by":"auto","created_at":"2025-04-18 07:30:46","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":54070,"visible":true,"origin":"","legend":"\u003cp\u003eheterogeneity (PERMDISP) of the two conditions (In and Out). PCO based on Jaccard dissimilarity matrix of compositional and functional total β-diversity and the turnover component inside (red) \u003cem\u003evs.\u003c/em\u003e outside (green) the forests.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6277481/v1/9a30449f8d818dc1b4ec5350.jpg"},{"id":80880763,"identity":"a6f83a41-7828-4acf-aa2d-c2d0cd5a28e8","added_by":"auto","created_at":"2025-04-18 07:38:47","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":21783,"visible":true,"origin":"","legend":"\u003cp\u003eβ-diversity. Compositional and functional β-diversity within condition and their partitioning into the two components of turnover and nestedness. Error bars represent s.e.m.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6277481/v1/de812fb6a159f3b17ba1ab46.jpg"},{"id":97179382,"identity":"4d055b12-3db3-4cbd-a1ad-fc28bd3557ad","added_by":"auto","created_at":"2025-12-01 16:15:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1342379,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6277481/v1/a496e75d-1d3d-4e5c-94e9-4999d3a1320a.pdf"},{"id":80879949,"identity":"4dc44a40-1c89-400b-8fed-f1d7f355c158","added_by":"auto","created_at":"2025-04-18 07:30:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1028055,"visible":true,"origin":"","legend":"","description":"","filename":"Collettietal.supplementarymaterials.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6277481/v1/f387b1b643dbd5921be079c9.pdf"},{"id":80879950,"identity":"81efb7fb-4973-4089-8ae6-e1118a964ed8","added_by":"auto","created_at":"2025-04-18 07:30:46","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":174698,"visible":true,"origin":"","legend":"","description":"","filename":"rawdata.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6277481/v1/400b78be95c4b5f2ba65c5e8.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Beyond biodiversity: the role of Paramuricea clavata forests in supporting ecosystem functioning","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eBiodiversity loss is pervasive across ecosystems, with expected large-scale ecological consequences for ecosystem functioning and the benefits nature provides to people [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A major concern is the loss of species that form forests, as these species directly regulate resource availability for themselves and for other species. In terrestrial ecosystems, this process has been well-documented, with clear evidence that widespread deforestation drastically reduces biodiversity, alters species composition and traits, and has significant effects on various ecological processes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. On the contrary, the response of marine ecosystems to the loss of habitat-forming species is less documented. Recent studies have indicated that marine macroalgal forests and seagrass meadows are at risk [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], with alarming projections for their future [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Dramatic loss in the biomass and biodiversity of \u0026lsquo;animal forests\u0026rsquo; has also been globally observed [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], driven by multiple stressors ranging from local to global changes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Sessile suspension feeders, such as gorgonians, dominate these communities and generate complex, three-dimensional structures similar to trees in terrestrial forests [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Their role in providing food, protection and nursery to associated species, as well as contributing to the blue carbon budget, is well recognized [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. As habitat-forming organisms, their loss is expected to reduce biodiversity and erode species traits, thereby disrupting important ecosystem services [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Mediterranean Sea, considered a miniature ocean [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], is a hotspot of biodiversity although one of the most impacted areas of the planet, where pollution, overfishing, habitat destruction and non-indigenous species introductions are producing large effects at basin scale [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Climate change is severely affecting Mediterranean marine ecosystems faster than expected [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], with unprecedented loss of habitat formers [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In this respect, \u003cem\u003eParamuricea clavata\u003c/em\u003e Risso (1827) is a paradigmatic example. It is a long-lived species listed as a vulnerable species by the International Union for Conservation of Nature [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], with slow growth rate, annual recruitment and late reproductive maturity, making it particularly vulnerable to human disturbances [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. It shows a large-scale distribution [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] living at depths ranging from 15 to 200 meters [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and contributing to the three-dimensional complexity of coralligenous outcrops, a Mediterranean biogenic temperate reef formed by complex and heterogeneous benthic assemblages. \u003cem\u003eParamuricea clavata\u003c/em\u003e has a critical functional role since it is supposed to stabilize key environmental variables such as light intensity, water flows, and sedimentation rate, thus supporting the settlement and growth of underlying benthic species [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Several studies have reported mass mortality events of \u003cem\u003eP. clavata\u003c/em\u003e populations due to increasing frequency of extreme climate events (marine heat waves, storms) together with other sources of disturbance such as fishing pressure, ultimately affecting population's resilience and resistance [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], also highlighting dramatic effects on the associated community [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, despite the importance of this species, the consequences of its loss are still little known. Fine-scale data are needed to understand if the presence of \u003cem\u003eP. clavata\u003c/em\u003e forests support assemblages with distinct structural and ecological features able to provide specific ecosystem processes and associated ecosystem services. Such data are essential for predicting future changes in this habitat and the associated ecological processes under global change scenarios, addressing the long-term ecological implications of the decline and loss of \u003cem\u003eP. clavata\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eSimultaneously exploring taxonomic and functional aspects of biodiversity provides a more comprehensive understanding of community assembly processes [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Functional traits are those specific characteristics or attributes of organisms that influence their performance and interactions within ecosystems [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The unique combination of traits in a species identifies a functional entity (FE) meaning that species that share the same traits belong to the same FE [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The functional trait approach presents some limitations, since there is a deep gap of knowledge on trait-specific information which leads to their simplification by scientific experts. Nevertheless, this methodology can provide valuable insights to complement taxonomic analyses and to assess changes in ecosystem functioning [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Recently, trait-based indices have been introduced as an alternative \u0026lsquo;functional\u0026rsquo; approach to assess the relationships between biodiversity and human disturbances. Indeed, these indices have the potential to determine the cause of change in systems by investigating the type of traits affected. Evidence showed that human pressures selectively remove a distinct suite of traits from assemblages [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. For instance, ocean acidification reduces the abundance of calcifying species with three-like morphologies, favoring low-lying fast-growing species across different habitats [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Also, mechanical disturbances such as bottom trawling have negative effects on large epifaunal filter feeders, which are more sensitive to physical stressors, and are replaced by mobile infaunal scavengers [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. This approach enables to identify the most vulnerable traits to a specific source of disturbance, allowing to anticipate potential shifts in ecosystem properties.\u003c/p\u003e \u003cp\u003eβ-diversity refers to the variations in species composition across different habitats or spatial units and it can be partitioned into species replacement (turnover) and richness differences (nestedness), allowing to disentangle the contribution of the two mechanisms to the heterogeneity and thus to understand causes generating differences in species composition [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. While research has primarily focused on compositional β-diversity, combining both compositional and functional β-diversity provides a valuable lens for understanding how ecological processes and human pressures drive species assemblages and distribution, offering key insights for species conservation and ecosystem management [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Because functional traits reflect species\u0026rsquo; adaptive strategies to the environment, numerous studies on functional β-diversity have rapidly emerged over the past two decades. These studies show contrasting turnover and nestedness-resultant components of compositional and functional β-diversities [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] and demonstrate the importance of considering the multifaceted nature of biodiversity when examining community assembly [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecently, Verdura et al. (2019) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] revealed the role of \u003cem\u003eP. clavata\u003c/em\u003e as a habitat-forming species, able to mitigate the effects of warming by maintaining the original assemblage dominated by macroinvertebrates and delaying the spread of the invasive species. Gomez et al. (2021) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] documented how marine heatwaves (MHWs) can affect the functional structure of \u003cem\u003eP. clavata\u003c/em\u003e dominated assemblages with detrimental consequences on several ecological processes and their associated ecosystem functions. In this study, we use fine-scale data from replicated locations in the central Mediterranean Sea, applying both taxonomic and functional approaches to test the hypothesis that the understory assemblages associated with \u003cem\u003eP. clavata\u003c/em\u003e forests exhibit distinct features compared to coralligenous assemblages where the forests are absent. Traits analysed in this study include \u0026lsquo;effect\u0026rsquo; traits (\u003cem\u003ee.g.\u003c/em\u003e morphological, physiological and phenological features of species involved in the understory) and \u0026lsquo;response\u0026rsquo; traits (\u003cem\u003ee.g.\u003c/em\u003e reproductive and dispersal strategies) for understanding the potential contribution of \u003cem\u003eP. clavata\u003c/em\u003e assemblages to the functioning of Mediterranean coastal ecosystems.\u003c/p\u003e"},{"header":"2. Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area\u003c/h2\u003e \u003cp\u003eThe Gulf of Naples (Italy) is a semi-enclosed embayment nestled within the southeastern Tyrrhenian Sea (Mediterranean Sea). The basin is South-West oriented and bounded by the islands of Procida and Ischia to the North, and by the island of Capri and the Sorrento peninsula to the South. Six locations were sampled based on prior knowledge of the presence of \u003cem\u003eP. clavata\u003c/em\u003e forests within the operative depth of recreational scuba diving of 30\u0026ndash;40 meters. The selected locations were: Ischia (Punta Sant\u0026rsquo;Angelo) (1) and Procida (Punta Pizzaco) (2), located within the Regno di Nettuno Marine Protected Area; Scoglio Penna (3) and Scoglio del Vervece (5), within the Punta Campanella MPA; Banco di Santa Croce (6), area protected by Ministerial Decree of June 15, 1993 and the location of Capri (4), out of protection boundaries (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For each location, we randomly selected two sites (A, B) about 50 m apart from each other, with similar slope and exposition. In each site, data were collected from both the conditions considered in the study (inside and outside \u003cem\u003eP. clavata\u003c/em\u003e forests).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data collection\u003c/h2\u003e \u003cp\u003eData collection has been carried out during scuba diving surveys in summer 2022. Within each site, photographic sampling of benthic assemblages was conducted using ten random replicate quadrats of 25x25 cm for each of the two conditions: inside \u003cem\u003eP. clavata\u003c/em\u003e forest and in the adjacent zone outside \u003cem\u003eP. clavata\u003c/em\u003e forest. Additionally, six random quadrats of 50x50 cm were used in each site within the forest to count \u003cem\u003eP. clavata\u003c/em\u003e colonies to later assess the density and population structure. Each \u003cem\u003eP. clavata\u003c/em\u003e colony inside these quadrats has been measured with a ruler from the base to the end of the farthest tip [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The sampling unit of six 50x50 cm was chosen following Linares et al. (2008) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], who found the stabilization of the s.e.m. (standard error of the mean) as a proportion of the mean colony density with a sample size of 1.5 m\u0026sup2;. The photographic sampling was carried out using Canon G7X Mk III in Nauticam housing and equipped with two strobe lights. The percentage cover of sessile organisms was quantified using the photoQuad_v1_4 software [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. During the analysis, each species has been identified at the lowest possible taxonomic level, and when specific identifications were not feasible, a morpho-functional group has been assigned (\u003cem\u003ee.g.\u003c/em\u003e algal turf, encrusting sponge).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data analysis\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e\u003cb\u003e2.3.1\u003c/b\u003e \u003cb\u003eParamuricea clavata\u003c/b\u003e \u003cb\u003eforests\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eTo assess the health status of \u003cem\u003eP. clavata\u003c/em\u003e forests, mean height, density and biomass of each colony have been calculated for each site. Height measurements collected in the field were used to estimate the biomass using the relationship B\u0026thinsp;=\u0026thinsp;0.002H\u0026sup2;∙⁶\u0026sup1; reported by Coma et al. (1998) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] and corrected by Linares et al. (2008) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], where B is the biomass of dry weight (DW) in grams and H is the colony height in centimeters. The population structure was assessed by assigning each colony to a size class with a 10 cm range and then reporting the frequency distribution of each size class across sites. Size distribution was analysed using the skewness and kurtosis coefficients [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Skewness measures the asymmetry of a distribution relative to its mean. When skewness is significant, it indicates that the distribution is not symmetrical. Positive skewness suggests a predominance of smaller size classes within the population, while negative skewness indicates a dominance of larger size classes. Kurtosis assesses the sharpness of the distribution's peak around its central mode. A significant kurtosis value implies that the distribution has longer tails compared to a normal distribution, reflecting a higher prevalence of certain size classes within the population. Skewness and kurtosis coefficients are considered significant if the ratio of their values to their standard error exceeds 2 [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Population dynamics of marine animal forests are regulated by density-dependent processes determined by the intra-specific competition for the use of resources such as food and space [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. As a result of this self-thinning mechanism, pristine populations are characterized by large colonies, while in young or impacted populations, high densities of small colonies saturate the space [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. We assessed the relation between biomass and density of \u003cem\u003eP. clavata\u003c/em\u003e populations through a linear regression with the log-log model as a descriptor of population conservation status [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Experimental design and statistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed to test the hypothesis that \u003cem\u003eP. clavata\u003c/em\u003e forests have the role of increasing local compositional and functional diversity. To test these hypotheses, we applied a multifactorial design consisting of three factors: \u003cem\u003elocation\u003c/em\u003e (Lo, 6 levels, random), \u003cem\u003esite\u003c/em\u003e (Si, 2 levels, random and nested in location) and \u003cem\u003econdition\u003c/em\u003e (Co, 2 levels, fixed and orthogonal), with \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10 replicates. The analyses are described in the sections below\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section4\"\u003e \u003ch2\u003e2.3.2.1 Functional traits and trait space\u003c/h2\u003e \u003cp\u003eTwelve categorical and/or ordinal functional traits were identified on the base of previous studies on benthic assemblages [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]: (1) Morphology, (2) Coloniality, (3) Maximum longevity, (4) Size, (5) Epibiosis, (6) Energetic resource, (7) Major photosynthetic pigment, (8) Feeding strategy, (9) Potential of asexual reproduction, (10) Growth rates, (11) Defences, (12) Propagules (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Functional traits were subdivided into categories, and, for each species, a category was assigned based on the relative trait determined through extensive bibliographic research (see supplementary materials) on biological and ecological characteristics of that species (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Subsequently, each species has been classified into a functional entity (FE) (\u003cem\u003ei.e.\u003c/em\u003e groups of species with unique combinations of functional traits) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The functional richness (FRic) has been calculated as the percentage of the volume of the multidimensional trait space occupied by all FEs in a community within the functional space [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. To create this multidimensional trait space, a Principal Coordinates analysis (PCO) was performed on FEs, based on a Gower dissimilarity matrix, chosen since it allows the analysis of mixed types of data while giving them equal weight [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Seven PCO dimensions were selected, based on the lowest mean squared-deviation index value (mSD\u0026thinsp;=\u0026thinsp;0.0022), to ensure a faithful representation of trait-based differences between species. The coordinates of each FE obtained by PCO were used to calculate the FRic for each quadrat sampled during the study to assess statistically significant differences between conditions, and across sites and locations. These coordinates were also used to visualize spatial differences in functional richness. To examine differences in trait composition and abundance between conditions in space, Community-Weighted Mean (CWM) was calculated as the average of trait values for species at each quadrat weighted by the relative abundance of each species possessing that trait. CWM of traits is a valuable index for evaluating shifts in mean trait values within communities due to environmental selection for specific functional traits [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section4\"\u003e \u003ch2\u003e2.3.2.2 Univariate and multivariate analyses\u003c/h2\u003e \u003cp\u003eA three-way univariate analysis of variance was carried out using PERMANOVA based on Euclidean distances of untransformed data [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] to assess differences in species richness, in the number of FEs and in the FRic, between conditions and across locations and sites. Each term was tested using a maximum of 999 permutations. To investigate the effect of \u003cem\u003eP. clavata\u003c/em\u003e on taxonomic and functional structure, and CWM, multivariate analyses were performed using PERMANOVA based on the Bray-Curtis resemblance matrix calculated on fourth root transformed data to reduce the differential between dominant and rare species. Each term was tested using a maximum of 999 random permutations of the appropriate units [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Non-metric multidimensional scaling ordinations were carried out on CWM to display differences on functional diversity between conditions at the scale of sites, since the interaction term Si(Lo)\u0026times;Co was found significant in the multivariate analysis. Statistical analysis has been performed using PRIMER software (v.7).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section4\"\u003e \u003ch2\u003e2.3.2.3 Compositional and functional β-diversity\u003c/h2\u003e \u003cp\u003eAccording to Vill\u0026eacute;ger et al. (2011) [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], compositional β-diversity is calculated as the ratio of species not shared between assemblages relative to the total number of species. By analogy, the functional β-diversity is quantified as the ratio of FEs not shared between assemblages relative to the total FEs. Compositional and functional β-diversity analyses, based on the Jaccard resemblance matrix on presence/absence transformed data, were carried out within condition and partitioned into the two β-diversity component nestedness and turnover. Turnover can be defined as the degree of species replacement reflecting the selective differentiation of species among assemblages because of environmental sorting [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Nestedness, on the other hand, refers to the hierarchical arrangement of species assemblages, wherein species present in species-poor habitats are subsets of those found in species-rich habitats, often in response to environmental gradients [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. A permutational analysis of multivariate dispersion (PERMDISP) [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] was then carried out to test statistically significant differences in the heterogeneity between conditions (In \u003cem\u003evs.\u003c/em\u003e Out). PCO based on Jaccard dissimilarity matrix was performed for compositional and functional β-diversity and its components to visualize differences in terms of community heterogeneity between conditions. FRic, CWM and β-diversity analyses were performed using the R functions from the 'FD', 'tripack', 'geometry', 'matrixStats' and 'betapart' R package (R v 3.4.1, R development Core Team, 2017) [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 \u003cem\u003eParamuricea clavata\u003c/em\u003e forests\u003c/h2\u003e \u003cp\u003eThe mean \u003cem\u003eP. clavata\u003c/em\u003e density ranged from 27.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9 to 65.3\u0026thinsp;\u0026plusmn;\u0026thinsp;27.1 colonies/m\u0026sup2; \u0026plusmn; s.e.m., while lowest and highest biomass values corresponded to 100.1\u0026thinsp;\u0026plusmn;\u0026thinsp;89.7 and 505.4\u0026thinsp;\u0026plusmn;\u0026thinsp;367.7 g dry weight/m\u0026sup2; \u0026plusmn; s.e.m., respectively (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Small colonies (\u0026lt;\u0026thinsp;10 cm) were the most represented in all investigated populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Skewness coefficients confirmed that most of the size class distributions (11 out of 12 sites) were significantly positively skewed, indicating the prevalence of small size classes. The kurtosis coefficients also showed a significantly positive trend in 10 out of the 12 sites, highlighting the presence of long tails in the size class distribution of \u003cem\u003eP. clavata\u003c/em\u003e colonies among sites. \u003cem\u003eParamuricea clavata\u003c/em\u003e populations showed no significant relationship between density and biomass (R\u0026sup2; = 0.097; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.3234) (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3.2 Species richness, functional entities and functional richness of the understory assemblages in presence and in absence of the forests\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA total of 80 species/taxa were found in the understory assemblages and grouped in 63 FEs. Univariate analyses revealed the effect of the presence of \u003cem\u003eP. clavata\u003c/em\u003e forests on the number of species (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012), the number of functional entities (FEs, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009) and functional richness (FRic, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.042) (Table S3). Differences were consistent across sites and locations for the three variables (Table S3). More specifically, the mean number of species and FEs were higher inside the forests (9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 s.e.m.; 8.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 s.e.m. respectively) compared to the areas outside (7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 s.e.m.; 7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 s.e.m. respectively). Additionally, FRic was also higher inside the forests at all locations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), with a higher mean value (20.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 s.e.m.) compared to the areas outside (9.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 s.e.m.).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3.3 Structural and functional changes in the understory assemblages in presence and in absence of the forests\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe multivariate analysis showed a significant effect of the forests on the taxonomic structure of the understory assemblages, differing across sites (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Table S4). However, \u003cem\u003ea posteriori\u003c/em\u003e pairwise comparisons indicated that in almost all sites (11 out of 12) a distinct community structure inside \u003cem\u003evs.\u003c/em\u003e outside the forest was found (Table S5). Differences between conditions were mainly driven by the presence of invertebrates (\u003cem\u003ee.g. Cliona viridis\u003c/em\u003e, \u003cem\u003eCrambe crambe, Pleraplysilla spinifera, Schizomavella mamillata\u003c/em\u003e) inside the forests, while algal species (\u003cem\u003ee.g.\u003c/em\u003e Dictyotales and the non-indigenous species \u003cem\u003eCaulerpa cylindracea\u003c/em\u003e and \u003cem\u003eLophocladia trichoclados\u003c/em\u003e), mucilage and sediments were more abundant outside the forests. A significant effect of the forests was also found on the functional structure of the assemblages in terms of composition and relative abundance of FEs (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Table S4), and \u003cem\u003ea posteriori\u003c/em\u003e pairwise comparisons show significant differences in 10 out of the 12 sites included in the analysis (Table S5).\u003c/p\u003e \u003cp\u003eThe multivariate analysis showed a significant effect of \u003cem\u003eP. clavata\u003c/em\u003e forests on the CWM of traits but not consistently across sites (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.012) (Table S6). \u003cem\u003eA posteriori\u003c/em\u003e pairwise comparisons indicated that the functional traits differed between conditions in 7 out of 12 sites (Table S7). The nMDS analyses carried separately for each site reported that colonial heterotrophs, with lecithotrophic larvae, physical and chemical defences and non-photosynthetic pigments were more abundant within the forests, while low-longevity autotrophs that mainly use phycoerythrin pigments (\u003cem\u003ee.g.\u003c/em\u003e, rhodophytes) and reproduce via spores characterized communities outside the forests (Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e3.4 Patterns of heterogeneity in the understory assemblages in presence and in absence of the forests\u003c/b\u003e\u003c/h2\u003e \u003cp\u003ePERMDISP analysis revealed significant differences in community heterogeneity between the two conditions, both at the compositional and functional level (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). More specifically, a higher heterogeneity was observed inside the forests than outside for both compositional (0.683\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001 s.e.m. inside \u003cem\u003evs.\u003c/em\u003e 0.612\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002 s.e.m. outside) and functional (0.673\u0026thinsp;\u0026plusmn;\u0026thinsp;0.001 s.e.m. inside \u003cem\u003evs.\u003c/em\u003e 0.610\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002 s.e.m. outside) analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), suggesting less variability in the patterns of distribution of benthic assemblages in absence of \u003cem\u003eP\u003c/em\u003e. \u003cem\u003eclavata\u003c/em\u003e. The breakdown into the two components revealed that turnover is the major component of the pattern of heterogeneity for both conditions. Even in this case, the turnover component of community heterogeneity was higher inside the forests than outside, both at the compositional (0.555\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002 s.e.m. inside \u003cem\u003evs.\u003c/em\u003e 0.486\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002 s.e.m. outside) and functional level (0.546\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002 s.e.m. inside \u003cem\u003evs.\u003c/em\u003e 0.482\u0026thinsp;\u0026plusmn;\u0026thinsp;0.002 s.e.m. outside) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) and both differences were statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In other words, rather than having a gain or loss of species/functions going from one condition to another, communities associated with \u003cem\u003eP. clavata\u003c/em\u003e compose a distinct and heterogeneous assemblage from both compositional and functional point of view. A summary of the results obteined from univariate and multivariate analyses is reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of statistical analysis results for each response variable. Sp\u0026thinsp;=\u0026thinsp;species richness; FE\u0026thinsp;=\u0026thinsp;FEs richness; FRic\u0026thinsp;=\u0026thinsp;functional richness; TS\u0026thinsp;=\u0026thinsp;taxonomic structure; FS\u0026thinsp;=\u0026thinsp;functional structure; CWM\u0026thinsp;=\u0026thinsp;Community-Weighted Mean; FR\u0026thinsp;=\u0026thinsp;fourth root. Significant differences are shown as follow * P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.** P\u0026thinsp;\u0026lt;\u0026thinsp;0.01.*** P\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSp\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFEs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFRic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCWM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSi(Lo)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLo\u0026times;Co\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSi(Lo)\u0026times;Co\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransformation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn temperate regions, the decline and loss of habitat-forming species in response to multiple anthropogenic stressors is increasingly documented [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], with indications of the drivers behind these changes and their consequences in terms of species composition and relative abundance. Among habitat formers, marine animal forests are recognized as biodiversity hot-spot for different communities including meiofauna, infauna, sessile and vagile species, epibionts and ichthyofauna [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. However, the limited quantitative knowledge about their distribution and functional role hampers our understanding of the underlying causes of their increasing loss and our ability to predict future changes, which could lead to regime shifts and alterations of associated biodiversity [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. By using fine-scale data, we document that the presence of \u003cem\u003eP. clavata\u003c/em\u003e forests favors the development of distinct benthic assemblages, characterized by consistently higher species richness and different community structures compared to areas where forests are absent. However, small, non-reproductive \u003cem\u003eP. clavata\u003c/em\u003e colonies dominating the population structure might be associated with the presence of ongoing stressors affecting subtidal assemblages [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The Gulf of Naples is an urbanized coastal region, and multiple stressors such as fishing and climate-related events may affect the status of \u003cem\u003eP. clavata\u003c/em\u003e forests [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study represents a baseline for this area of the Mediterranean Sea and expands current knowledge on biodiversity associated with these forests, which has been sparse and fragmented across very few Mediterranean regions, already documenting that the loss of \u003cem\u003eP. clavata\u003c/em\u003e forests can lead to significant changes in recruitment patterns in the understory assemblages [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e] resulting in lower species diversity and richness [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Systematic efforts and long-term monitoring focused on improving knowledge of marine animal forests and associated biodiversity are needed to quantitatively assess the status and the effects of different combinations of stressors across the basin. This information is particularly urgent, given that cnidarians are more affected than any other group by strong thermal anomalies, which are leading to mass mortality events at the Mediterranean scale [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur findings also show that the presence of the forest supports a different functional structure with more functional entities and higher functional richness and that results are consistent at both the scales of tens' meters and kilometres. A broader occupation of the functional trait space indicates a more diverse set of ecological roles and processes being supported under the forests. Heterotrophy, coloniality and the presence of species with defined physical and chemical defenses are prevalent within the forests. Outside the forests, fast-growing and low-longevity primary producers replace heterotrophs, possibly altering ecological processes involved in energy fluxes, such as productivity and benthic-pelagic coupling, with cascade effects across biodiversity levels [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Food provision and carbon sequestration can be also affected by this functional shift [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. These patterns correspond to those reported for \u003cem\u003eP. clavata\u003c/em\u003e and \u003cem\u003eCorallium rubrum\u003c/em\u003e before and after the occurrence of marine heat waves, when fast-growing autotrophic species (\u003cem\u003ee.g.\u003c/em\u003e algal turf, \u003cem\u003eCaulerpa cylindracea\u003c/em\u003e) rapidly colonized the free spaces after mass mortality events at the expense of morphologically complex and long-lived heterotrophs [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This evidence highlights the importance of animal forests in influencing environmental variables, creating unique habitat conditions that selectively favor the settlement of certain species [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Additionally, the physical structure of \u003cem\u003eP. clavata\u003c/em\u003e colonies has been observed to act as a filter for mucilage accumulation and to reduce water flow, limiting sediment resuspension and deposition [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. A higher abundance of mucilage, sediments and of non-indigenous species \u003cem\u003eL. trichoclados\u003c/em\u003e and \u003cem\u003eC. cylindracea\u003c/em\u003e was recorded outside \u003cem\u003eP. clavata\u003c/em\u003e populations. This function is vital for preventing the establishment of invasive species such as \u003cem\u003eCaulerpa cylindracea\u003c/em\u003e, which thrives in sediment-rich and disturbed conditions [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Nevertheless, while the presence of \u003cem\u003eP. clavata\u003c/em\u003e protects the associated community from the spread of the mucilage and the resulting negative aspects on the community itself, mucilage that remains attached to the colony can induce necrosis, generating a diffused oxidative stress in the entire \u003cem\u003eP. clavata\u003c/em\u003e colony and affecting its physiological processes [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. The results, so far, are also in accordance with the biotic resistance hypothesis, which states that more diverse communities are more resistant to invasion due to the complementary use of resources by natives (complementary effects) or the higher probability of including highly competitive native species which limit the use of resources by invaders [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe specific environmental conditions created by \u003cem\u003eP. clavata\u003c/em\u003e likely represent also the driver of the high heterogeneity assessed inside the forest, as has been documented for other habitat-forming species [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. β-diversity analysis contributed to identifying \u003cem\u003eP. clavata\u003c/em\u003e forests as hot-spots of temperate reef biodiversity, with greater total compositional and functional β-diversity inside the forest compared to adjacent zones. Outside the forests, the less heterogeneous patterns of distribution found include both compositional and functional β-diversity. Here, biotic homogenization could be driven by the presence of stressors such as invasive species, sediments and mucilage, leading to species loss and decrease of more vulnerable species (\u003cem\u003ee.g. Myriapora truncata, Smittina cervicornis\u003c/em\u003e) [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. Thus, areas outside the forest reflect the characteristics of more disturbed conditions than assemblages associated with \u003cem\u003eP. clavata\u003c/em\u003e, featured by the gain of species and functions which foster the recovery or resistance to disturbances like biological invasions [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. The breakdown into the two components revealed that species replacement dominates both compositional and functional β-diversity. Turnover in species composition translates into functional turnover when communities have low functional redundancy (\u003cem\u003ei.e.\u003c/em\u003e low number of species performing similar functions) [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. The positive correlation between these complementary aspects of β-diversity may be related to the high variability of environmental conditions, which lead species to a differential partitioning of resources, resulting in a high turnover of species performing different functions. This pattern has also been observed in shallow subtidal habitats, where environmental factors (\u003cem\u003ee.g.\u003c/em\u003e temperature, light exposition, hydrodynamism) are highly variable and likely drive the species sorting [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In contrast, environmental homogenization can induce functional nestedness even though compositional turnover represent the dominant component [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. In our study, the increase of the compositional and functional turnover inside the forests suggests that the presence of \u003cem\u003eP. clavata\u003c/em\u003e drives the replacement of species and functions [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e], possibly arising from differences in niche features between the two conditions [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The high habitat complexity created by the forests allows the colonization by organisms with different ecological needs, compared to more simple habitats [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e]. Therefore, preserving the integrity of the \u003cem\u003eP. clavata\u003c/em\u003e populations is crucial to ensure the maintenance of the habitat complexity which in turn is vital to support compositional and functional diversity.\u003c/p\u003e \u003cp\u003eResults of our study highlight the need of improving the conservation effort for this species. Currently, only 18% of \u003cem\u003eP. clavata\u003c/em\u003e potential habitat at the Mediterranean scale is under protection regimes [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Considering the increasing pressures related to climate change, local threats need to be removed to limit cumulative and synergistic negative impacts on animal forests and associated assemblages [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Present efforts to achieve the 30% conservation target set by the new EU Biodiversity Strategy for 2030 should translate into specific strategies for the inclusion of \u003cem\u003eP. clavata\u003c/em\u003e forests within Marine Protected Areas [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e], an effective tool to protect this habitat and enhance its resilience [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. Quantitative information and fine-scale data on the distribution and status of \u003cem\u003eP. clavata\u003c/em\u003e are also relevant for the Nature Restoration Law (NRL). The NRL constitutes the EU\u0026rsquo;s long-term strategy to restore biodiversity and ecosystem services over the next decades [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e], recently approved by the EU with the objective to halt and reverse biodiversity loss. However, the NRL sets very ambitious quantitative targets in terms of both the areas to restore and the timeframe for their restoration, considering the current poor knowledge about the distribution and status of several species and habitats across the EU, including \u003cem\u003eP. clavata\u003c/em\u003e forests. Achieving these targets requires urgent development of knowledge, methodologies, tools, and best practices to monitor progress and ensure success. This work addresses these gaps to consolidate existing knowledge for a successful implementation of EU Directives.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eS.F. and Al.Co. conceived the study; Al.Co., L.L., An.Ch., S.D., M.M., S.M.S.M., C.S. participated in the field work; L.L., Al.Co., S.F. and E.F. performed the data analyses; S.F., Al.Co. and L.L. led the writing of the manuscript with the contributions from E.F., An.Ch., S.D., M.M., S.M.S.M., C.S., P.S; Al.Co. and L.L. are authors with equal contribution.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank the projects \u0026ldquo;National Biodiversity Future Center - NBFC\u0026rdquo;, project code CN_00000033, Concession Decree No. 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research; the Horizon Europe CLIMAREST Project (Coastal Climate Resilience and Marine Restoration Tools for the Arctic Atlantic basin) (GA no. 101093865) and the European Union\u0026rsquo;s Horizon Europe Research and Innovation Programme ACTNOW (Advancing understanding of Cumulative Impacts on European marine biodiversity, ecosystem functions and services for human wellbeing), GA no. 101060072 for funding. The authors also thank Daniel G\u0026oacute;mez-Gras and Stanislao Bevilacqua for their support in the data analysis.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data generated or analysed during this study are included in this published article (and its supplementary information files).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eIsbell, F. et al. Expert perspectives on global biodiversity loss and its drivers and impacts on people. \u003cem\u003eFront. Ecol. Environ.\u003c/em\u003e \u003cstrong\u003e21\u003cem\u003e \u003c/em\u003e(2),\u003c/strong\u003e 94-103. https://doi.org/10.1002/fee.2536 (2023).\u003c/li\u003e\n\u003cli\u003eFaria, D. et al. The breakdown of ecosystem functionality driven by deforestation in a global biodiversity hotspot. \u003cem\u003eBiol. 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Securing success for the nature restoration law. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e382,\u003c/strong\u003e 1248-1250. https://doi.org/10.1126/science.adk1658 (2023).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"habitat-forming species, functional ecology, functional traits, β-diversity, turnover, biodiversity loss","lastPublishedDoi":"10.21203/rs.3.rs-6277481/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6277481/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMarine animal forests, composed of sessile suspension feeders such as gorgonians are known to host rich communities that support important ecosystem functions and services. These habitats are undergoing dramatic loss due to multiple pressures, with potential cascading effects on ecosystem dynamics that remain poorly understood. To address this critical knowledge gap, we used fine-scale data to assess the role of \u003cem\u003eParamuricea clavata\u003c/em\u003e forests in supporting biodiversity and ecosystem functioning at multiple locations, on a regional scale. Through functional trait analysis, we compared taxonomic and functional diversity of benthic assemblages inside and outside \u003cem\u003eP. clavata\u003c/em\u003e forests and investigated the loss of traits as a consequence of forest loss. Analyses revealed significant enhancements in both taxonomic and functional diversity within \u003cem\u003eP. clavata\u003c/em\u003e forests, with observed increased species and functional richness. Trait-based investigations revealed a higher abundance of colonial heterotrophic species within forests, while outside, assemblages were dominated by low-longevity autotrophs, suggesting that \u003cem\u003eP. clavata\u003c/em\u003e modifies environmental variables creating unique ecological conditions that favor specific traits. β-diversity measurements demonstrated increased compositional and functional turnover inside forests, indicating that \u003cem\u003eP. clavata\u003c/em\u003e provides more available niches, supporting the replacement of species and functions. Our findings offer insights into how marine animal forests can structure marine communities, with broader implications for understanding biodiversity loss in changing marine ecosystems.\u003c/p\u003e","manuscriptTitle":"Beyond biodiversity: the role of Paramuricea clavata forests in supporting ecosystem functioning","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-18 07:30:42","doi":"10.21203/rs.3.rs-6277481/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-18T17:27:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-14T22:27:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"179925796702671665901024318456051874304","date":"2025-07-02T12:39:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-18T07:55:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308167677335784755014577441772004719035","date":"2025-04-02T09:00:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"226304301208037966964820852032124301177","date":"2025-04-01T11:29:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-30T03:14:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-30T03:10:52+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-25T07:00:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-21T13:26:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-21T12:01:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"28ba90c4-cf7c-42be-8439-edbbea5a8a2f","owner":[],"postedDate":"April 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46564359,"name":"Biological sciences/Ecology/Biodiversity"},{"id":46564360,"name":"Biological sciences/Ecology/Community ecology"},{"id":46564361,"name":"Biological sciences/Ecology"},{"id":46564362,"name":"Earth and environmental sciences/Ecology"}],"tags":[],"updatedAt":"2025-12-01T16:09:40+00:00","versionOfRecord":{"articleIdentity":"rs-6277481","link":"https://doi.org/10.1038/s41598-025-26902-4","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-28 15:57:54","publishedOnDateReadable":"November 28th, 2025"},"versionCreatedAt":"2025-04-18 07:30:42","video":"","vorDoi":"10.1038/s41598-025-26902-4","vorDoiUrl":"https://doi.org/10.1038/s41598-025-26902-4","workflowStages":[]},"version":"v1","identity":"rs-6277481","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6277481","identity":"rs-6277481","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}