Successional Divergence of Taxonomic and Functional Beta Diversity in Marine Nematodes after Pulse--Press Disturbance

Successional Divergence of Taxonomic and Functional Beta Diversity in Marine Nematodes after Pulse--Press Disturbance | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 19 June 2025 V1 Latest version Share on Successional Divergence of Taxonomic and Functional Beta Diversity in Marine Nematodes after Pulse--Press Disturbance Authors : Anastasios Varkoulis 0000-0002-4089-6636 [email protected] , Konstantinos Voulgaris , and Dimitris Vafidis Authors Info & Affiliations https://doi.org/10.22541/au.175033996.61448367/v1 170 views 104 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Extreme weather events (EWEs) are intensifying in frequency and severity, posing complex pulse and press disturbances to coastal ecosystems. While each disturbance type has been studied in isolation, empirical data on their combined effects under realistic field conditions are virtually absent. Here, we examine how compound pulse–press disturbances shape the successional dynamics of taxonomic and functional beta diversity in free-living marine nematodes, a group well suited for detecting community reassembly due to their short generation times, ecological sensitivity, and trait diversity. Following two EWEs in central Greece, we monitored eight sites at 0-, 6-, and 12-months post-disturbance. Beta diversity was partitioned into turnover and nestedness components using presence–absence and abundance data. Taxonomic beta diversity was shaped predominantly by turnover and responded strongly to disturbance intensity and time, whereas functional beta diversity showed subtle responses, likely reflecting high trait redundancy. Early stages reflected spatially structured legacies, mid-stages showed deterministic environmental filtering, and late stages revealed decoupling between taxonomic and functional trajectories. This study provides the first comprehensive empirical evidence of how compound pulse–press disturbances drive divergent successional dynamics in marine sediments, and highlights nematodes as powerful yet underutilized model organisms of post-disturbance reassembly. Abstract Extreme weather events (EWEs) are intensifying in frequency and severity, posing complex pulse and press disturbances to coastal ecosystems. While each disturbance type has been studied in isolation, empirical data on their combined effects under realistic field conditions are virtually absent. Here, we examine how compound pulse–press disturbances shape the successional dynamics of taxonomic and functional beta diversity in free-living marine nematodes, a group well suited for detecting community reassembly due to their short generation times, ecological sensitivity, and trait diversity. Following two EWEs in central Greece, we monitored eight sites at 0-, 6-, and 12-months post-disturbance. Beta diversity was partitioned into turnover and nestedness components using presence–absence and abundance data. Taxonomic beta diversity was shaped predominantly by turnover and responded strongly to disturbance intensity and time, whereas functional beta diversity showed subtle responses, likely reflecting high trait redundancy. Early stages reflected spatially structured legacies, mid-stages showed deterministic environmental filtering, and late stages revealed decoupling between taxonomic and functional trajectories. This study provides the first comprehensive empirical evidence of how compound pulse–press disturbances drive divergent successional dynamics in marine sediments, and highlights nematodes as powerful yet underutilized model organisms of post-disturbance reassembly. Introduction Coastal ecosystems worldwide are increasingly subjected to climate change-induced extreme weather events (EWEs), such as intense storms and flash floods that lead to pulse disturbances, significantly affecting coastal communities. Depending on the regime they can mobilize sediments, nutrients, and contaminants into nearshore waters (Thrush et al. 2004, Doody 2013). Climate models project an increase in both the frequency and intensity of such EWEs under continued greenhouse-gas forcing, compounding pre-existing anthropogenic pressures and accelerating habitat degradation (Harley et al. 2006, Doney et al. 2012, Coumou and Rahmstorf 2012, Intergovernmental Panel On Climate Change (Ipcc) 2023). Despite growing recognition of these compound disturbances, our predictive capacity for post-EWE succession in shallow marine systems remains limited, with few studies linking EWEs to long-term community reassembly (Underwood 2000, Gutiérrez C et al. 2018). Intense pulse disturbances can potentially magnify pre-existing anthropogenic stressors by mobilizing sediments, nutrients, and contaminants from agricultural, industrial, and urban catchments into the coastal zone (Thrush et al. 2004, Rabalais et al. 2009). These inputs establish persistent press effects related to gradual changes in abiotic conditions that can last for months to years (Kemp et al. 2005, Howarth et al. 2011). Free-living marine nematodes rank among the most abundant and functionally diverse marine invertebrates in coastal sediments, with generation times measured in days to weeks and well-characterized feeding guilds and life-history strategies, while also being sensitive to changes in sediment chemistry, organic loading, and hydrodynamic regimes (Heip et al. 1985, Bongers et al. 1999). Despite over four decades of use as bioindicators of pollution and habitat quality, they have been largely neglected in studies of community assembly and successional dynamics (WARWICK 1989, Ridall and Ingels 2021). This neglect reflects a historical emphasis on α-diversity metrics and indicator taxa (Gray 2002), the technical challenges of meiofaunal taxonomy (Platt and Warwick 1983), and only recent maturation of β-diversity theory and its partitioning into turnover and nestedness components (Baselga 2010, Legendre and De Cáceres 2013). In Pagasitikos Gulf (Greece), two successive EWEs scoured benthic habitats (pulse) that led to spatially heterogeneous chronic alterations (press) driven by land-use patterns. Both meiofaunal and nematode communities exhibited much higher recovery times than previously reported (Altaff et al. 2005, Grzelak et al. 2009, Sugumaran et al. 2019, Mohan and Dhivya n.d.,Varkoulis et al. 2025). The authors hypothesized that the additional press disturbance could have affected the successional trajectories of the communities. Despite evidence that compounded pulse–press disturbances can reshuffle community assembly rules (Collins et al. 2020), no study has applied a β-diversity framework to examine the partitioning of taxonomic and functional turnover and nestedness to ecological succession after EWEs. Moreover, the degree to which disturbance intensity gradients modulate these successional trajectories remains unexplored. Given the nematodes’ rapid life cycles and trait-based sensitivity, they offer an unparalleled “fast-forward” model to resolve how pulse events magnify anthropogenic pressures into lasting press effects and steer community reassembly over months to years. Here we test the hypothesis that successional stages will be governed by different community assembly mechanisms, while intensity of disturbance will significantly affect the observed patterns in beta taxonomic and functional diversity. Specifically, we expect that during the early-stage taxonomic dissimilarity will be high, while functional dissimilarity will be low, due to a combination of local extinctions and the retention of tolerant traits (Olden and Rooney 2006, Clavel et al. 2011, Socolar et al. 2016). In the intermediate stage environmental filtering will take place resulting in different communities with shared functional traits (Kraft et al. 2011, Braghin et al. 2018). Communities in the late stage will have reached successional equilibrium, converging in composition, with priority effects re-introducing site-specific idiosyncrasies with a narrow trait envelope (Purschke et al. 2013, Fukami 2015). Increased intensity of disturbance is hypothesized to result in primary succession trajectories, thus homogenizing communities, leading to more similar communities, while the three examined time slices are expected to show differences in the explained variance by environmental and spatial factors, for all beta diversity components (Legendre and Legendre 2012, Heino 2013, Dray et al. 2014). 2. Materials and Methods 2.1 Data source To examine the spatio – temporal patterns of taxonomic and functional beta diversity following disturbance, we analyzed data obtained from the monitoring of eight sites in Pagasitikos Gulf (Aegean Sea, Greece) in response to two EWEs. These datasets include replicate samples for eight sites along the gulf (0.5m average depth) at three time slices following the EWEs, specifically at 0, 6 and 12 months. Based on the intensity of disturbance sites are classified to high and low levels of intensity. Abiotic measurements regarding the water and sediment parameters were also used. For more details regarding the regime of the events, as well as the methods used, see Varkoulis et al (2025). 2.2 Functional traits Fourteen functional traits related to the life history, trophic status, male and female reproduction, general morphology and habitat preference were selected (Supporting information). All traits were qualitative, either binary (presence – absence of a character), nominal (e.g. type of cuticle) or ordinal. The values for each trait were determined mainly at genus level, or in case of missing data at family level, from various sources (Wieser 1953, Bongers 1990, Moens et al. 2014, Ahyong et al. 2025, Nemys eds. 2025, Daché et al. 2025). Only biological traits that had entries for more than 50% of the genera were used in this study, thus size of spicule was ignored (Usseglio-Polatera et al. 2000). Prior to examining the functional β-diversity, the Gower dissimilarity was constructed ( daisy function from “cluster” package). To ensure euclidean representation we used the Cailliez correction method for negative eigenvalues during the Principal Coordinate analysis (PCoA) (Cailliez 1983; package ‘ade4’, Dray and Dufour 2007). Due to computational restrictions related to the “betapart” package and after comparing results from the first three and four PCoAs we found the use of the first three PCoAs does not undermine the quality of our results. 2.3 Data analysis All analyses were conducted using R, version 3.4.3 (R Core Team 2024). For the decomposition of beta taxonomic and functional diversity the “betapart” package was used (Baselga et al. 2018). We conducted analyses on beta taxonomic diversity using both presence-absence and abundance data, with Sørensen and Bray-Curtis dissimilarities as family indices, respectively. The ‘betapart’ package decomposes beta diversity into three components, namely total dissimilarity (β sor ), turnover (β sim ), and nestedness (β sne ) as proposed by Baselga (2010). Pairwise measurements of β-diversity are indicated by a lowercase subscript (e.g. β sor ) and multi-site measurements of β-diversity are indicated by an uppercase subscript (e.g. β SOR ). β sor results from both genera turnover and differences in genera richness, β sim is limited to only the replacement of genera and βsne is the dissimilarity produced by nestedness (i.e. the degree to which a community can be considered a subset of a second community) and is calculated as the difference between βsor and βsim (Baselga 2010). βsne does not directly reflect the degree of nestedness, but is rather a metric for the portion of the overall dissimilarity that cannot be explained by taxa replacement (Baselga 2010, Baselga and Orme 2012). Abundance-based beta diversity can be decomposed into three components: overall dissimilarity (β Bray ), balanced variation in abundance (β bal ), that accounts for the substitution of individuals belonging to some genera in one site by the same number of individuals of different genera in another site and abundance gradients (β gra ), whereby some individuals are lost from one site to the other and abundances vary between the sites (Baselga 2012, Baselga and Orme 2012). β gra is calculated as the difference between total β dissimilarity and the component of replacement (β bal ). To test whether beta taxonomic and functional diversity significantly differed between levels of intensity of disturbance (high vs low) and among time slices (T1: immediately after (0 months), T2: after 6 months, T3: after 12 months), we used the functions beta.sample , beta.sample.abund and a modified function of beta.sample ( fun.beta.sample ), to calculate the overall beta taxonomic diversity based on presence-absence, abundance and the overall functional beta diversity, respectively (Krynak et al. 2019). We also examined the site-specific temporal beta taxonomic diversity using presence-absence data in a pairwise manner. Heatmaps were then constructed combined with hierarchical clustering, using the Manhattan distance and average clustering method. Regarding the functional beta diversity, the number of sites was chosen based on the number of genera, as only sites with N genera > N PCoA can be used. This was particularly important for T1, where acute disturbance significantly decreased both the number of genera and number of individuals. Thus, we decided to pool the replicates for each site. The number of iterations of random resampling was n=300 for taxonomic and n=100 for functional beta diversity, due to increased computational requirements. After acquiring the estimates, we used pairwise probability tests based on the density plots to compare the means (Baselga and Orme 2012, Baselga 2017). Comparisons of pairwise beta diversity were also conducted to determine whether the degree to which sites vary in taxonomic and functional diversity changes with intensity of disturbance and time. These comparisons were carried out using Kruskal-Wallis tests on pairwise beta components, coupled with Wilcoxon post-hoc tests with Bonferroni correction for multiple comparisons. The pairwise beta diversity components for each time slice were visualized using ternary plots. To test the effect of abiotic and spatial factors on pairwise β-diversity, a distance-based db-RDA was employed, couple with variation partitioning (package ‘vegan’, Oksanen et al. 2019). Prior to the db-RDA, spatial variables were constructed by transforming site coordinates to a site-to-site distance matrix using the ‘sp’ package (Pebesma and Bivand 2005, Bivand et al. 2013) and then transformed to a rectangular matrix using Principal Coordinates of Neighborhood Matrix (PCNM, Borcard and Legendre 2002, Dray et al. 2006) with the ‘vegan’ package. Due to the close proximity of some sites (<5km) we first projected the geographic coordinates from degrees to meters using a suitable to the study region Universal Transverse Mercator (UTM) reprojection (in this case UTM Zone 34N). Environmental and spatial variable groups were individually tested for significance using a permutation test (999 permutations) within the db-RDA framework. If the model was significant, variable selection was refined through a forward selection approach, following two stopping criteria: an adjusted R 2 higher than the global model and a p-value threshold of 0.05 (Blanchet et al. 2008). Significant variables from each group were then combined for the final db-RDA and variation partitioning analyses. Additionally, conditional tests were performed. This procedure was applied to all three β-diversity components for both taxonomic β-diversity (based on presence-absence data) and functional β-diversity. 3. Results Taxonomic beta diversity significantly varied between levels of intensity regarding all components for both presence-absence and abundance data, with the exception of abundance-based nestedness (β GRA ) (Supporting information). However, there was an inverse trend between presence-absence and abundance metrics (Supporting information). Differences between time slices were also observed, predominantly between T1 and T2, where only the turnover (βsim) showed no significant differences (Supporting information). Between T1 and T3, differences were reported only for the total dissimilarities (β SOR , β BRAY ), while differences between T2 and T3 were evident only for β BRAY (Supporting information) Regarding the taxonomic beta diversity within levels of disturbance intensity, no significant differences were observed, however when examining within-level variation for time slices T1 appeared to be significantly different compared to T2 and T3, although only for β sor . Hierarchical clustering of the temporal pairwise taxonomic diversity always grouped T1-T2 together with T1-T3 for all beta components (Supporting information). The two most disturbed sites (KSR and PLK, Varkoulis et al., 2025) were clustered together for all three beta components, however there was some degree of site-specific temporal beta diversity for the rest of the sites, with the range of β SOR , β SIM and β sne being 0.5-1, 0.3-1 and 0.1-0.4, respectively (Supporting information). Most of the pairwise similarity for all three time slices exhibited values ranging between 20% and 40%, with the average similarity showing a gradual increase from T1 towards T3. The average taxonomic turnover did not show any significant variation, however there was high variability for individual values ranging from 0 to 100% in T1, while most of the values for T2 fell within 40% to 60%. High variability was also observed for T3 with most values being within the range of 40% and 80% (Figure 1 A, B, C). Average nestedness was always less than average turnover, while greatest pairwise variability was observed in T1, with most values ranging between 0 and 80%. No significant changes in the overall trend of nestedness between T2 and T3 was found, with most values being less than 40% (Figure 1 A, B, C). Functional beta diversity did not vary between intensity levels for any of its components, while functional beta dissimilarity was significantly different among all three time slices, with T2 exhibiting highest functional Fβ SOR , followed by T1 and T3 (Supporting information). The same trend was observed for functional beta turnover (Fβ SIM ), although with no statistical differences between T1 and T3. Functional beta nestedness (Fβ SNE ) presented highest values for T1 followed by T2 and T3, with no significant differences between the two latter time slices. Pairwise functional beta diversity within levels of intensity showed significant differences for all components when comparing levels of intensity but only exhibited statistical differences with time for functional beta dissimilarity (Fβ sor ) between T1 and T2 (Supporting information). Pairwise functional beta similarity between sites was lowest in T1, where most values ranged between 0-20 %, while they ranged between 20-80 % for T2 and T3 (Fig 1 D, E, F). High variability was observed for both functional turnover and nestedness in T1 with values generally ranging from 40 to 100 % and 0 to 80 %, respectively. For T2 and T3, less variability was observed for nestedness, with values ranging between 0-40% and 0-20%, respectively, while for turnover most values fell into the range of 0-40 % for T2 and 20-80% for T3. The average values for pairwise similarity were lowest in T1 followed by T2 and T3. T2 showed the lowest average turnover, followed by T3 and T1, while average nestedness was lowest in T3 followed by T1 and T2 (Fig. 1 D, E, F). The relationship of the taxonomic beta diversity components with spatial and environmental predictors varied across the three captured successional stages. The significant spatial and environmental variables for each beta component are reported in Table 3. The environmental effect alone explained more variance compared to either the spatial effect or the combined effects of spatial parameters and environmental conditions for both β sor and β sim at all time slices except for taxonomic turnover in T1, where the combination of spatial and environmental predictors explained most of the variance (Figure 2). No significant spatial effect was observed for the turnover in T1. Taxonomic nestedness appeared to be influenced only by temperature in T1, while no significant relationship between β sne and any of the examined spatial and environmental predictors was found for T3 (Table 2). For T2 the spatial effect was not significant, while the joint effect explained the most variance (Figure 2). Regarding the functional beta diversity, none of the spatial and environmental factors could explain any of the components in T1 and T3, while PCNM1 was shown to influence functional dissimilarity (Fβ sor ) and Fβ sim was only affected by environmental variables in T2. Functional beta nestedness (Fβ sne) was significantly explained by both spatial and environmental predictors, with their joint effects explaining the most variance (Figure 2). 4. Discussion 4.1 Effects of the intensity of the disturbance on beta diversity Beta dissimilarity was mainly driven by turnover for both intensity levels, however increased dissimilarity and turnover were observed in the high intensity group, whereas the low intensity group showed higher values for nestedness, regarding the presence-absence based taxonomic beta diversity. The absence of data prior to the two EWEs complicates the interpretation of these findings, however the most plausible explanation is that previously shared nematode genera across high intensity sites were removed due to the physical pulse disturbance, while the same genera were, at least to some degree, retained at low intensity sites. Thus, two distinct modes of beta diversity might exist between high and low intensity levels, analogous to primary vs secondary successional processes, leading to separate successional trajectories (Staude et al. 2023). When examining abundance-based beta components between intensity levels, an inverted pattern emerged for Bray-Curtis dissimilarity (β BRAY ) and turnover (β BAL ). This is in accordance to existing literature reporting separate patterns between incidence- and abundance-based results (Baselga 2017). Lower beta Bray-Curtis dissimilarity and abundance balanced variation for the high intensity group suggest a degree of homogeneity among sites, caused by the initial disturbance. Since we pooled samples throughout the successional stages it probably also means that this homogenization persisted, at least partially, throughout the successional trajectory. The most probable cause would be an initial spatially synchronous pulse disturbance followed by, to some extent, similar environmental stress sources, as all sites belonging to the high intensity group were located in close proximity to fresh water outlets. This explanation would be in accordance to earlier work on the effect of spatial synchronization of disturbance leading to decreased community stability, while reducing fluctuations in community abundance (Mintrone et al. 2024). Functional beta dissimilarity was equally driven by both functional turnover and nestedness, while there were no differences between intensity levels, meaning that ecosystemic functioning was irresponsive to the degree of disturbance. However, this could in part be due to the limited and coarse functional trait information available for nematode communities, which could mask more subtle ecological responses to disturbance, although we attempted to collect important features related to various ecologically meaningful aspects (e.g. trophic guilds, reproductive organs, life-history strategy, type of environment). Thus, another possible explanation could be the fact that marine nematodes exhibit increased functional redundancy, which would be potentially expressed through similar patterns in functional beta diversity between levels of intensity (Semprucci et al. 2016, Grassi et al. 2023). At the early successional stage (T1), immediately following the extreme weather events, the combined effect of spatial and environmental predictors explained the highest proportion of variance in taxonomic beta diversity among all time slices, despite the fact that environmental effects alone were weak and spatial structure alone was non-significant. This suggests that the observed community patterns likely reflect the remnants of pre-existing populations rather than true recolonization processes, as nematode abundances were extremely low across sites. Following a major pulse disturbance, when abundances are drastically reduced, surviving individuals can form scattered and spatially structured remnants that are only weakly filtered by the new environmental conditions (Chase 2007, Vellend 2010). In such cases, the detected diversity patterns capture a transitional ”legacy” phase, where the previous community imprint is still evident, but a full reassembly through recolonization has not yet occurred (Connell and Slatyer 1977, Chase and Myers 2011). 4.2 Post-disturbance trajectories and successional shifts Early stage (T1): Immediate consequences of pulse disturbance Following the initial pulse disturbance, average pairwise beta taxonomic and functional dissimilarities were the highest out of all successional stages, predominantly driven by turnover. Although this stands in accordance with several studies that found beta diversity to be highest in the early successional stages, turnover is not always the major component contributing to dissimilarities as was observed in intertidal invertebrate community changes following storms, where nestedness had a greater impact (Purschke et al. 2013, Corte et al. 2017). In our study we observed very high variability in pairwise nestedness and turnover associated with taxonomic beta diversity in T1. This could reflect a spatially asynchronous response, due to local differences related to the regime of the disturbance, although mainly influenced by the low intensity sites. Since spatial synchrony is mainly characterized by high similarity along, leading to the homogenization and subsequent destabilization of communities, the low similarity combined with high variability of the taxonomic beta components could potentially be related to the ability of meiofaunal nematodes to stabilize rapidly at community level in response to pulse disturbances, mainly due to their biological traits (small size, rapid reproduction, environmental tolerance) (Vanaverbeke et al. 2003, Schratzberger and Ingels 2018). Multi-site incidence and abundance-based results showed distinct results for the taxonomic beta diversity, with greatest β SOR but lowest β BRAY in this successional stage compared to the mid and late ones. This is probably explained by the high dissimilarity of genera among sites due to differences in pre-disturbance ecosystem legacy, coupled with low abundances caused by the initial pulse disturbance (James et al. 2007, Johnstone et al. 2016). The joint spatial-environmental signal at T1 likely reflects spatially structured survival rather than newly established community assembly. The absence of a strong spatial or environmental influence at the early successional stage suggests that processes such as random mortality, local extinctions, and dispersal bottlenecks can override deterministic assembly processes (Chase 2007, Dini-Andreote et al. 2015). Regarding the functional diversity the low pairwise similarity was unexpected, hinting to a highly heterogenous and dynamic succession between sites. However, at multi-site level our results are in accordance with the general successional theory that predicts functional similarity to be highest in the early successional stage (Römermann et al. 2009, Purschke et al. 2013). The low multi-site functional dissimilarity coupled with high functional nestedness is indicative of some degree of initial functional convergence along the gulf, probably due to certain traits showing resistance to the initial pulse disturbance, especially against increased hydrodynamic pressures (Smith et al. 2022)(Smith et al., 2022). Intermediate stage (T2): Press disturbance and environmental filtering This successional stage is mainly driven by the gradual and site-specific changes in environmental conditions. Both the taxonomic and functional pairwise beta similarities significantly increased compared to T1. Taxonomic pairwise beta diversity was mainly driven by turnover, while nestedness mainly contributed to the functional beta diversity. In other words, different genera perform similar functions across sites. A number of drivers have been identified as drivers of functional convergence and increased taxonomic turnover, ranging from environmental heterogeneity to random disturbances in food availability or isolation (Bender et al. 2017, Braghin et al. 2018, Diniz et al. 2021). The multi-site results showed an increase in taxonomic dissimilarity compared to T1 mainly due to turnover for incidence-based data, while the abundance-based approach also showed higher dissimilarity but due to nestedness. Functional multi-site beta diversity was the highest with increased turnover and decreased nestedness. These patterns indicate that, although local environmental filtering led to high taxonomic replacement but similar functions, functional beta diversity increased compared to T1, similarly to other studies reporting differences in taxonomic beta diversity across different scales (Menegotto et al. 2019). The reduced unexplained variance and strengthened explanatory power of environmental variables suggest that communities were beginning to reorganize in response to deterministic gradients (Kraft et al. 2011). This supports the idea that mid-successional stages often reflect a peak in predictability based on environmental conditions (Chase and Myers 2011). The fact that the functional beta diversity components were only explained by any of the examined factors in T2, further enhances the hypothesis that deterministic processes rather than stochasticity mainly drive this successional stage. Late stage (T3): Communities reaching equilibrium At the late successional stage (T3), one year after the two extreme weather events, taxonomic pairwise beta diversity remained similar to that observed during the intermediate stage (T2). However, functional beta diversity showed increased turnover and decreased nestedness, suggesting that while the taxonomic dissimilarity between sites plateaued, species replacement within sites (temporal turnover) likely occurred, altering the functional structure of communities (Anderson et al. 2011, Mori et al. 2018). This decoupling between taxonomic and functional beta diversity implies that newly arriving or recovering species, although taxonomically distinct, may have been functionally dissimilar, potentially reflecting divergent successional trajectories under stabilized but site-specific environmental conditions. Importantly, incidence- and abundance-based multi-site metrics revealed contrasting patterns: multi-site taxonomic beta dissimilarity was lowest for the incidence-based approach but highest for the abundance-based one (i.e., Bray-Curtis), indicating a potential evenness gradient among sites. This suggests that while species presence became more homogenized across sites (low βSOR), differences in relative abundances increased (high βBRAY), possibly reflecting site-specific recovery dynamics or shifts in dominance structures rather than composition alone (Baselga 2010, Chase and Myers 2011). By T3, direct environmental filtering weakened, as environmental conditions stabilized across most sites, albeit under potentially different abiotic baselines. In the absence of strong deterministic filters, stochastic processes such as ecological drift, dispersal limitation, and priority effects may have played a greater role in structuring communities (Hubbell et al. 2001, Viana et al. 2022). The observed increase in functional turnover, despite stable taxonomic dissimilarity, is thus consistent with theories of late-successional divergence shaped by neutral or historical contingencies, where community assembly is influenced more by colonization sequences and local legacies than by environmental constraints (Fukami 2015, Tucker et al. 2016). The decrease in explained variance by either spatial or environmental predictors in T3 hints at the idea that the nested subset structure was only temporarily structured by environmental filters in T2, while this drop may reflect community stabilization or increasing ecological drift as succession progresses (Vellend 2010, Chase and Myers 2011). In T3 species losses and additions probably became more idiosyncratic, possibly driven by random colonization, priority effects, or legacy effects from earlier stages (Fukami 2015, Zhou and Ning 2017). 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Taxonomic T1 βsor PCNM1, PCNM3 O2, NH4, pH βsim PCNM1, PCNM3 O2, NH4, pH βsne Temperature T2 βsor PCNM1, PCNM3 NH4, NO3, TOC, Rsed, O2 βsim PCNM3, PCNM1 SiO2, O2, OC, pH, NO3 βsne PCNM1 Oxygen T3 βsor PCNM1, PCNM3 Tsed, NO3, Oxygen, Salinity βsim PCNM1, PCNM3 Tsed, NO3, Oxygen Functional T2 Fβsor PCNM1 Fβsim Silt, NO3, Salinity Fβsne PCNM1 NO3 Figure 1. Ternary plots of the taxonomic (left) and functional (right) beta diversity components for the three time slices. Each point represents a value, while the dashed red lines indicate the average value for each component. Figure 2. Venn plots representing variance partitioning of spatial, environmental, and shared (overlapping) contributions to taxonomic and functional beta diversity components across three time slices (T1, T2, T3). Components include total dissimilarity ( βsor ), turnover (β sim ) and nestedness (β sne ) for taxonomic beta diversity, and functional nestedness (Fβ sne ) for functional beta diversity. Only components with significant explained variation are shown. Residual variation is indicated in each panel. Negative values and non-significant models are excluded from the plots. Information & Authors Information Version history V1 Version 1 19 June 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords beta diversity partitioning community reassembly environmental filtering extreme weather events (ewes) pulse-press disturbance successional dynamics Authors Affiliations Anastasios Varkoulis 0000-0002-4089-6636 [email protected] University of Thessaly Department Of Ichthyology and Aquatic Environment View all articles by this author Konstantinos Voulgaris University of Thessaly View all articles by this author Dimitris Vafidis University of Thessaly View all articles by this author Metrics & Citations Metrics Article Usage 170 views 104 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Anastasios Varkoulis, Konstantinos Voulgaris, Dimitris Vafidis. Successional Divergence of Taxonomic and Functional Beta Diversity in Marine Nematodes after Pulse--Press Disturbance. Authorea . 19 June 2025. 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