ABSTRACT Introduction and Aim Understanding the spatial distribution of intraspecific genetic variation in trees is essential for conservation and management of forest genetic resources. In pedunculate oak ( Quercus robur ), an economically and ecologically important European tree, southern and southeastern provenances are considered to be putative reservoirs of local adaptations to warm and dry climates, yet remain underrepresented in range‐wide population genetic studies. Herein, we analyse nuclear and chloroplast population genetic structure of Q. robur across central and southeastern Europe, including the subspecies robur and pedunculiflora contact zone, and assess contributions of postglacial recolonization, geographic barriers, fine‐scale topography and human influence to contemporary diversity. Location Transect from west‐central Europe, north of the Alps to the Black Sea. Methods We genotyped 1500 individuals from 56 populations using 16 nuclear (nSSRs) and 8 chloroplast (cpSSRs) microsatellites. We assessed nuclear genetic structure and diversity with Bayesian and spatial multivariate analyses, quantified differentiation (AMOVA, F ST ) and inferred chloroplast lineages/haplotypes differentiation and phylogeographic structure. Results nSSRs revealed low but significant among‐population differentiation and a pattern with three clusters: west‐central Europe, Dinaric Alps–Pannonian Basin and southeastern Balkans. Genetic diversity increased from west to southeastern Europe. Chloroplast haplotype variation showed pronounced spatial structure congruent with glacial refugia and migration routes. The two subspecies were weakly differentiated, shared chloroplast lineages across the contact zone, indicating substantial gene flow. Main Conclusions Postglacial recolonization and landscape features structured genetic variation in Q. robur . Southeastern populations retain deep lineage structure and high regional allelic richness with many private haplotypes/alleles, consistent with the rear‐edge position of postglacial expansion. Elevated diversity in contact zones along the northern Alps indicates admixture among recolonization routes, compatible with cryptic late‐glacial microrefugia near the Alpine–Carpathian corridor. Integrating nuclear and chloroplast patterns, we recommend safeguarding southeastern gene pools, maintaining connectivity across contact zones and aligning Genetic Conservation Units with clusters identified.
ABSTRACT Aim Species associations are increasingly recognized as an effective way to improve species distribution model (SDM) predictions by integrating biotic and abiotic information that is difficult to measure in situ. This approach appears promising for monitoring communities where biodiversity and environmental data are sparse or limited. To evaluate its applicability to such communities and to test whether associations estimated in narrow spatial context can capture useful information and be transferred to predict spatial distributions across larger regions, we focused on macroalgal communities in beach wrack. Location France. Methods To estimate the information captured by macroalgae species associations, we assessed the predictive improvement they provide when added to models of increasing complexity using a random forest approach. We also examined how species traits influence association patterns among 58 species observed at 130 sites in Brittany, western France. Finally, we quantified the improvement in predictive performance when applying these associations to species distribution models across 402 sites along the French Atlantic coast. Results We found that species associations both complement and substitute remote sensing and fine‐scale habitat descriptors in predicting individual species distributions. Association patterns were related to certain macroalgae traits (e.g., buoyancy status, initial benthic habitats). They significantly improved large‐scale predictive performance, despite being derived from limited sample sizes and narrow spatial contexts, confirming that such associations capture more than initial or local environmental factors. Main Conclusions Using macroalgal communities in beach wrack, we illustrate that species associations can serve as alternative predictors for communities where biotic and abiotic data are scarce or hard to access. We also highlight their usefulness for predicting at broader spatial scales than those used for their estimation. Leveraging these associations offers promising tools to enhance spatial conservation planning, identify sampling biases and guide efficient surveys (e.g., in exotic or rare species of high conservation concern).
ABSTRACT Aim To identify microbial hotspots and investigate the spatial distribution and assembly mechanisms of soil bacterial and archaeal communities across a coastal ecosystem, and to assess implications for biodiversity conservation and sustainable land management. Location Yellow River Delta, China (YRD, ~13,680 km 2 coastal plain). Methods A total of 112 sites were sampled across diverse land‐use types along strong gradients of salinity, moisture and nutrients. At each site, soils were collected from three depth intervals (0–20, 20–40 and 40–100 cm), yielding a total of 336 samples for analysis. Microbial community composition and diversity were analysed using high‐throughput sequencing, and spatial patterns were evaluated using diversity mapping, distance–decay relationships (DDR) and community assembly modelling. Results Hotspot analysis revealed that microbial diversity exhibited marked spatial heterogeneity, with these hotspots primarily located in agricultural and grassland soils characterized by high soil organic matter (SOM) and low salinity. Hotspots became increasingly fragmented with depth. DDR analysis revealed weak but significant patterns: community turnover in the surface layer was primarily associated with nestedness (i.e., species loss), whereas in subsoils, turnover showed a weak positive association with species replacement. Community assembly was consistently shaped by a mixture of homogeneous selection (~40%), dispersal limitation (30%–31%) and drift (22%–24%), but the dominant environmental drivers transitioned from nutrient‐based filtering in topsoil to more complex multivariate constraints in deeper layers. Main Conclusions Spatially structured and depth‐dependent microbial processes reveal that surface‐layer diversity hotspots, though accounting for only 7%–13% of the region, harbour up to 40% of microbial taxa and 83% of total abundance. These findings, based on taxonomic diversity, highlight the need for depth‐resolved conservation planning that considers both hotspots and the unique taxa in peripheral areas to sustain microbial contributions to ecosystem functions in coastal systems undergoing rapid environmental change.
ABSTRACT Aim Marine species are increasingly impacted by climate change, forcing them to adapt or redistribute to remain within their environmental niches. How the combined effects of environmental gradients and species traits influence the distribution of species with distinct biogeographic affinities remains poorly understood. The goal of this study is to identify the role of the environment, as mediated by species' traits, in shaping the fish communities of a high latitude marine environment with a clear biogeographic transition zone. Location The Barents Sea, a Subarctic ecosystem. Methods We fit a hierarchical model of species communities (HMSC) using 19 years (2004–2022) of bottom trawl survey data for 67 fish species in the Barents Sea. We incorporated environmental covariates (depth, temperature, salinity, mixed layer depth, and sea ice extent), species' traits (maximum body size, fecundity, and trophic level), and taxonomic relationships to quantify spatially structured community responses to environmental variation. Results Temperature, sea ice, and depth were the primary drivers of species' distributions across the Barents Sea. Arctic species were associated with cooler, deeper, and ice‐covered waters, while boreal species occupied warmer, ice‐free areas and exhibited more diverse responses to environmental gradients pointing towards a wider ecological niche. Clear spatial patterns for traits emerged across the polar front, in which smaller, less fecund, and lower trophic level species dominated the north, and larger, more fecund, higher trophic level species dominated the south. Main Conclusions These findings show that integrating environmental gradients, functional traits, and phylogenetic structure provides a robust framework for understanding fish biogeography and anticipating climate‐driven community changes. Our findings are relevant for the continued effective management of this ecologically and economically significant fish community, especially as climate change progresses in this rapidly warming region.
ABSTRACT Aim Rare species increase diversity, provide unique ecosystem functions and serve as barometers of habitat health. However, many habitats are losing their rare species due to the pressures of climate change, habitat loss and fragmentation. Robust ecological data on the distribution of rare species, the causes of their rarity, their ecological requirements and their population dynamics are needed to enact effective conservation practices. Species Distribution Models (SDMs) are increasingly used to inform conservation interventions; yet several challenges limit their widespread application to rare plant species. These include limited access to up‐to‐date species occurrence records and environmental predictors reflecting species' ecological niche, particularly at an ecologically relevant resolution. Methods We systematically review 61 scientific papers that use SDMs to model suitable habitats for rare species. We synthesise various SDM applications used in these papers to identify causes of rarity and inform the conservation of rare species. We use Rabinowitz's Seven Forms of Rarity as a framework to evaluate the effectiveness of these SDM applications for different forms of rarity. Results SDMs can estimate the geographic range of species, their placement within this range, shifts and contractions. They can guide field surveys to detect new populations, estimate their size or identify stressors. SDMs can advance our understanding of the habitat requirements of species and how those vary with space, which remains unknown for many rare species. However, some of these applications are better suited for certain types of rarity. Further, we discuss how assessments of population dynamics, genetics and physiology can be combined with various SDM outputs to clarify the causes of rarity and inform conservation. Conclusions We suggest research directions to help managers identify the SDM applications best suited to various forms of rarity and conclude that SDMs can advance our ecological knowledge of rare species, many of which are understudied.
