Carola Gómez‐Rodríguez

Aim: Ecological uniqueness quantifies how different a community is relative to all other communities within the study. This broad‐sense definition of uniqueness makes it dependent on the choice of the dissimilarity metric used to quantify differences between communities. Moreover, under a narrow‐sense definition of the concept, a uniqueness metric should indicate the proportion of species in the community that are unique to that community, i.e., absent from other communities. Here we develop and assess the key properties of a reliable metric for the quantification of uniqueness and compare the behaviour of two widely used approaches: (i) average pairwise dissimilarity between the focal community and all others and (ii) Local Contribution to Beta Diversity (LCBD). Innovation: We introduce two new metrics to compute ecological uniqueness using presence/absence ( U _rlb ) and abundance data ( U _rlb.ab ), based on asymmetric Ruggiero dissimilarity ( β _rlb ) and a new abundance‐based asymmetric dissimilarity index ( β _rlb.ab ), respectively. We also identify two key properties for the quantification of uniqueness under a narrow definition of the concept: pairwise index asymmetry and independence from the number of non‐focal sites included in the study. Pairwise asymmetry refers to the possibility that the dissimilarity between community A and B differs from the dissimilarity between B and A. To show this, we provide conceptual and simulated examples assessing the behaviour of uniqueness when quantified as LCBD (Hellinger and Sørensen), as average symmetric dissimilarity (Sørensen and Simpson) and as average asymmetric dissimilarity (Ruggiero) using presence/absence data. We also include a case study using real data on European longhorn beetles. We show that both approaches (average dissimilarity and LCBD) are conceptually and mathematically equivalent, but only average dissimilarity can be interpreted in absolute terms as it accounts for the overall beta diversity (i.e., community differentiation) within the region and does not depend on the number of non‐focal communities. Conclusion: Our results show that only average dissimilarity values based on an asymmetric index allow the quantification of uniqueness that is consistent with its ecological narrow‐sense concept. Uniqueness thus emerges as an important ecological attribute that, if properly quantified, can be used to identify highly valuable communities, containing many species exclusive to them. Consequently, by focusing on uniqueness, conservation efforts can target large‐scale conservation goals with a site‐focused perspective.

Aim: Resilience is a crucial property of ecosystems experiencing accelerated degradation in natural environments. While the functional characteristics of ecosystems play a significant role in shaping their resilience, the development of functional approaches in marine conservation has been largely overlooked. In light of this deficiency, we simultaneously consider the functional richness and redundancy of marine fish communities associated with rocky reefs to uncover and characterise the thriving and struggling areas. Location: Five marine ecoregions in southern Europe. Methods: We collected data on the density of reef‐associated marine fish species using the Reef Life Survey's standardised protocol. Based on these data, we estimated the functional richness and redundancy using four key functional traits: dietary patterns, gregariousness, position in the water column, and substrate preference. Next, we applied a predictive approach by using the XGBoost algorithm to estimate these functional metrics across the study area, including areas where in situ data were unavailable. Subsequently, to identify threshold points in the predictions, we employed decision trees, enabling us to unveil thriving and struggling areas. Results: Our results indicate that the proportion of thriving areas (26.7%) is similar to that of struggling areas (26.5%), and that their distribution is heterogeneous across the ecoregions. We also find that these thriving areas are distinguished by lower values of human density, fishing pressure, chlorophyll concentrations, and they also exhibit a higher protection status compared to struggling areas. Main Conclusions: In the current context of declining resilience, it is essential to address the functional dimension of biodiversity to unveil thriving and struggling areas, thereby highlighting the regions that require prioritisation in conservation and restoration efforts. Our findings offer critical information for policymakers and governments at local, regional, and national levels, pinpointing priority areas to enhance marine resilience and prevent the ongoing loss of this vital ecosystem property.

Distinct biological communities have high conservation value because they harbour species that cannot be preserved elsewhere. However, community uniqueness is scale‐dependent: irreplaceability depends on whether community dissimilarity emerges at small or large spatial scales. To assess conservation value, here we integrate phylogenetic endemism with the spatial scaling of phylogenetic uniqueness in terrestrial vertebrates. We show that phylogenetic endemism is the most efficient single criterion to maximise global phylogenetic diversity within the smallest land area. Moreover, the spatial scaling of phylogenetic uniqueness allows distinguishing globally distinct but regionally less unique sites ‘(evolutionary hills)’, from highly irreplaceable sites even at small scales ‘(evolutionary islands)’, which support lower local diversity but host species that are both evolutionarily unique and threatened. This approach provides a non‐heuristic and stable baseline to identify high‐value biodiversity areas and offers a powerful tool for prioritising conservation efforts to safeguard evolutionary heritage effectively.

Synergic effects between climate change and invasive species may alter soil microbial diversity and functioning, as well as cause major shifts in physicochemical properties. Moreover, some of these ecological impacts may manifest even after the removal of the invasive species. We have conducted a field experiment to assess such effects on soil microbial communities (fungi and bacteria) and physicochemical properties seven months after the removal of Carpobrotus edulis (L.), an invasive plant of coastal dune ecosystems. C. edulis grew on the experimental plots for 14 months under current (“invasive species treatment”) and increased warming and drought conditions (“combined treatment”). Then, all plant parts (above and belowground biomass) were removed with a non-aggressive eradication method and soil samples were collected seven months later in the experimental and control plots (no invasive species and current climatic conditions). We predicted a general compositional shift in microbial communities in response to the presence of the invasive species. Moreover, given that water is the most limiting factor in this type of ecosystem, we also predicted a more pronounced compositional shift in the treatment combining invader presence and climate change. While species richness was similar amongst treatments, we observed some taxonomic and functional variation in soil microbial communities. Notably, fungal and bacterial communities exhibited contrasting responses. The species composition of bacteria differed significantly between the “invasive species” and “control” treatments, while, in the case of fungi, the most substantial difference occurred between the “invasive species” treatment and the combined treatment of “invasive species and climate change”. Some chemical properties, such as carbon and nitrogen content or pH, strongly differed amongst treatments, with the “invasive species” showing a different response compared to the other two treatments. Overall, our study suggests smaller short-term effects on the microbial community compared to soil chemical properties. Furthermore and contrary to our initial expectations, the potential impact on the soil microbiome seemed to be weaker in the face of rising temperatures and drought conditions predicted by climate change. This outcome highlights the remarkable complexity of the impact of invasive species and climate change on belowground microbial communities.

Unified models of biological diversity across organizational levels (genes, species, communities) provide key insight into fundamental ecological processes. Theory predicts that the strength of the correlation between species abundance and genetic diversity should be related to community age in closed communities (i.e. abundant species accumulate more genetic diversity over time than rare species). Following this rationale, we hypothesize that historical climatic events are expected to impact assembly processes, hence affecting both the species abundance distribution (SAD) and the species genetic distribution (SGD) in continental communities. Therefore, we predict that, if the congruence between SADs and SGDs depends on community age, then higher congruence would be observed in localities where climate has been more stable since the Last Glacial Maximum (LGM). We tested this prediction using relative abundance and nucleotide diversity ( cox1 ‐5′) data from 20 communities of leaf beetles along a latitudinal transect in the Iberian Peninsula. We observed that the congruence between SAD and SGD curves, measured as the correlation between the species' rank orders in both distributions, was significantly related to the change in mean annual temperature since the LGM, but not to current climatic conditions. Our results suggest that, despite the high connectivity of continental communities, historical climatic stability is still a relevant predictor of the congruence between species abundance and genetic diversity. Hence, the degree of congruence between SADs and SGDs could be used as a proxy of community stability, related not only to historical climatic variation but also to any other disrupting factors, including human pressure.

Given the sensitivity of mountain biodiversity to human pressure, it is essential to quantify changes in montane biological communities and contrast them with expectations based on potential drivers of change. This need is particularly pressing for biological groups representing important but little‐studied fractions of biodiversity, such as insects. We analyze the temporal changes (between 1998 and 2015) of leaf beetle communities in an altitudinal gradient in the Sierra de Ancares (NW Spain). Our results show temporal changes in the composition of local communities, with a tendency to assemblage thermophilization, as well as a homogenization of the spatial turnover pattern, mostly driven by an increased similarity between communities at the lower and intermediate altitudes. These temporal changes in community composition and in the spatial structure of biodiversity were associated with upward shifts of the upper altitudinal limit of warm‐adapted species and with downward shifts of the lower altitudinal limit of cold‐adapted species. While this upward shift is consistent with expectations of climate change effects, the observed downward shift suggests a land‐use change effect. Our results point to the joint effect of multiple factors (climate and land‐use change) behind temporal changes of these leaf beetle communities, which result in compositional reorganization and biotic homogenization, rather than a mere coherent displacement toward higher altitudes. More generally, we show that understanding temporal change of biodiversity requires assessing multiple community‐level metrics (e.g., variation in assemblage composition and/or changes in spatial turnover) for the detection of tendencies among the species‐specific signals (e.g., altitudinal range shifts).

Aim: To assess the relative relevance of dispersal limitation and species sorting as drivers of spatial turnover between spider faunas of European territories.Location: Continental Europe.Time period: Present.Major taxa studied: Spiders (Order Araneae).Methods: We analysed how distance‐decay patterns differ between northern and southern Europe (broadly, territories covered vs. not covered by ice sheets during the last glacial maximum, respectively) in 15 spider families, using standardized distances to allow a direct comparison between parameters (i.e. slope and intercept) of climatic and spatial distance‐decay models. Thus, we assessed North–South differences in parameters of spatial and, independently, climatic distance‐decay models, and whether those differences are explained by family‐specific traits related to dispersal ability.Results: Climatic and spatial distance‐decay patterns are very similar in northern Europe, where climatic and spatial distances are highly correlated. In contrast, slopes are steeper in spatial than in climatic distance‐decay curves in southern Europe, where climatic and spatial distances are decoupled. Moreover, family traits related to dispersal ability explained the North–South difference in spatial distance‐decay slopes, as well as the amount of nestedness‐resultant dissimilarity between southern and northern spider faunas.Main conclusions: Our results suggest that differences in beta diversity patterns between northern and southern Europe reflect the strength of dispersal limitation in spiders, which varies across families and leads to different degrees of disequilibrium with current climatic conditions depending on the taxon. Moreover, in the South of Europe, where spatial and climatic distances are uncorrelated, spatial distance‐decay models are steeper and have larger explanatory power than climatic distance‐decay models, which suggests that dispersal limitation is the main factor shaping current beta diversity patterns of European spiders at the continental scale.

Aim: To test whether spatial turnover patterns of mountain madicolous insect communities in the Southern Hemisphere support the ‘mountain passes are higher in the Tropic’ hypothesis (MPHT). To do this, we compared madicolous communities in the Amazon Mountains (equator) and the Atlantic Forest Mountains (23°S).Location: Brazil.Methods: We characterized madicolous insect communities in two elevational gradients between 90 to 3000 m a.s.l. separated by 23° of latitude, totalling 108 sampling sites. Since the MPHT predicts a more intense turnover along elevational gradients at lower latitudes than at higher latitudes, we evaluated beta diversity in the Amazon mountains, at the equator, and in the Atlantic Forest mountains, in the subtropical region. We quantified multiple‐site abundance‐based dissimilarity to assess whether beta diversity was different between both regions. We also performed constrained ordination (db‐RDA) analyses to assess whether community dissimilarity (balanced variation in abundances) was uniquely or jointly explained by environmental, spatial and/or elevational predictors. Additionally, we independently assessed the relationship between community dissimilarity and altitudinal difference in each region and tested for differences in model parameters between regions.Results: Although we found high species turnover in both regions, the community variation explained by environmental factors and altitude was higher in the Amazon than in the Atlantic Forest, as evidenced by db‐RDA and altitudinal difference models. In general, communities were remarkably constrained by spatial predictors, which result from low dispersion capacity of most madicolous insects and low connectivity of madicolous systems. Consequently, the composition of madicolous insects notably diverged between regions, highlighting the complementarity and high conservation value of both systems.Main Conclusions: Our results indicate that the MPHT explains, at the community level, the differences between low‐ and high‐latitude mountain systems in community turnover along elevational gradients, even within a relatively short latitudinal distance in the Southern Hemisphere.

Aim: (i) To assess the dependence between the form of the decrease in biological similarity with distance (distance‐decay) and species range size and (ii) to introduce the use of a sigmoidal model, the Gompertz function, as a flexible alternative able to fit distance‐decay models under a wide variety of species range sizes.Location: Applicable worldwide.Methods: We computed distance‐decay curves from simulated communities to assess how the species range sizes shape the functional form of distance‐decay patterns (i.e. negative exponential, power‐law or sigmoidal [Gompertz] relationships). Simulations were performed using different sample sizes and species detection probabilities. We also used distribution data of South American mammals to explore the relationship between species range size and the distance‐decay form in an empirical dataset.Results: Our simulations showed that the power‐law is the best supported model when range sizes tend to be small. An increase in range sizes leads to a negative exponential relationship, taking the shape of a sigmoidal (Gompertz) relationship with the largest range size values. Similar results have been found in the distance‐decay pattern of South American mammals. Remarkably, the Gompertz function fits the data reasonably well in all scenarios.Main conclusions: The functional form of distance‐decay patterns depends on a key biogeographical attribute: species range size. This dependence makes it an interesting tool to detect biodiversity threats associated with species range expansion, such as the biotic homogenization of faunas. The Gompertz function is the mathematical model that best accommodates different frequency distributions of species range size and, thus, allows cross‐taxa comparison of this biogeographical and ecological pattern.

Aim: Modelling how community similarity decays with spatial distance is a key tool for the study of the processes behind community variation (beta diversity). Distance‐decay models are computed from pairwise metrics (i.e. community similarity and spatial distance between localities) and hence suffer from pairwise dependence in the data, precluding the use of standard significance tests. Besides, distance‐decay patterns are inherently nonlinear because similarity is bounded between 1 and 0. However, the only standard method to assess model significance under pairwise dependency is the Mantel test, which considers a linear model. To allow the use of nonlinear models in the assessment of distance‐decay patterns, we introduce here a nonlinear significance test combining a pseudo‐R² statistic with either permutations or block‐site resampling with replacement.Location: Global.Taxon: Applicable to any taxon.Methods: To assess the performance of the pseudo‐R² significance test (i.e. type I error and statistical power), we have applied this method to exponential and power‐law generalized linear models of simulated distance‐decay data. We compared its performance with the one of a linear model (i.e. Mantel test) and illustrated its use with real data.Results: The pseudo‐R² significance test has generally good type I error and statistical power, even for highly nonlinear relationships. The Mantel test shows an adequate empirical approximation of type I error, but presents lower statistical power when the distance‐decay relationship highly departs from linearity.Main conclusions: The proposed pseudo‐R² significance test for nonlinear models is adequate for exponential and power‐law models of distance‐decay of similarity and should be preferred over the linear Mantel test. Furthermore, this significance test could also be used in other nonlinear distance‐based regressions. The novel site‐block resampling method could also be applied to other statistical questions related to distance‐decay models that cannot be tackled using permutations, such as estimating the variance of model parameters.