Global Ecology and Biogeography

Aimto characterize the evolution of climatic niches during the diversification of the Phyllotis darwini species group, in order to assess the extent to which divergences involved in radiation were associated with patterns of conservatism or divergence of climatic niches, and whether the differentiation found among climatic niches correlated with species phylogenetic relationships. Locationsouth-central Andes, surrounding lowlands, and Patagonia, South America. Methodsspecies climatic niches were characterized by sampling contemporaneous precipitation and temperature conditions across occurrence locations and entire distributional ranges. Climatic niches were analyzed and modeled using multivariate statistics (PCA, PERMANOVA), a maximum entropy-based algorithm, and novel methods developed to explore levels of differentiation (niche overlap test) and divergence (niche divergence test) between realized and fundamental niches. Comparative phylogenetic methods were applied using a time-calibrated phylogeny and integrating climate niche data to estimate ancestral environmental niches within geographic and environmental spaces. Resultscomparisons revealed low levels of climatic niche overlap, both among species realized niches and among their fundamental niches, suggesting high levels of niche differentiation during the diversification of Phyllotis species. Quantifications of niche overlap further showed that observed differences among species lay primarily in the multidimensional nature of climatic niches, as unidimensional quantifications exhibited higher levels of overlap. Evolved differences among species climatic niches were better fitted to a Brownian motion model of evolution, but lacked phylogenetic signal and showed no significant association with species phylogenetic distances. Main conclusionslow levels of differentiation between ancestral climatic niches suggest that the early radiation of species in the Phyllotis darwini species group was promoted by geographic isolation, whereas the more recent diversification of extant species was accompanied by climatic niche differentiation, possibly involving local adaptation to regional ecoclimatic changes associated with Quaternary glacial cycles. The spatial separation of sister species, the complete divergence of their climatic niches, and the lack of phylogenetic signal in niche differences suggest a scenario of diversification in which divergences were prompted by the spatial isolation, but also by the divergent selection exerted by regional climatic differences.

Recurring patterns in biosphere dynamics are anchored in daily and seasonal oscillations in abiotic variables driven by Earths obliquity, rotation, and orbit. While circadian and annual biotic cycles are well studied, persistent supra- or subannual cycles in biotic systems are rarely documented globally. Here, we apply a machine learning approach to DNA metabarcoding time series and detect a biotic semi-annual cycle expressed across aquatic communities in temperate regions across taxonomic domains. We propose that this dynamic reflects a semi-annual mode in insolation and is suppressed under conditions of limited nutrients or sunlight. Our results suggest photoautotrophs are central for the aetiology of the biotic SAM, while demonstrating that it is a community-level phenomena not attributable to single species. The regularity of the biotic SAM suggests value for anticipating less predictable ecological events, including phytoplankton blooms. Overall, our results highlight Earth system-scale forcing of local dynamics and reinforce coupling patterns.

Forests play a crucial role in mitigating climate change as primary terrestrial carbon sinks. While some studies suggest that global warming enhances forest productivity, a growing body of evidence highlights detrimental impact primarily driven by increased water stress. Yet the extent to which positive effects of climate change offset its negative impacts on tree species productivity remains unclear at large spatial extents. We assessed forest growth and mortality for the 21 most abundant tree species in Europe using National Forest Inventory data from more than 50,000 plots and 700,000 trees to disentangle the relative importance of climate and forest structure. Specifically, we examined how vapor pressure deficit (VPD) anomalies across species climatic edges and stand developmental stages affect forest growth and mortality occurrence and intensity (i.e. whether mortality occurred and the amount of basal area lost). Then, we aggregated the responses across species and separately for broad-leaved and needle-leaved species to assess whether forest growth and mortality differed between major functional groups. Although the importance of forest growth and mortality drivers varied markedly among species, climate had a stronger influence on mortality than on growth, particularly in needle-leaved species. Forest growth declined and mortality increased along VPD anomaly in most species and forests studied. Responses were most pronounced at arid species edges in early-stage broad-leaved forests and at wet edges in late-stage needle-leaved forests, where differences between functional groups were also highest. We evidence the need to parametrise species-specific models of forest growth and mortality across large spatial extents to better understand and predict effects of climate change on forest productivity. In addition, our results emphasize the importance of improving the understanding of forest mortality processes given the strong influence of climate on mortality, while also further studying vulnerable populations to climate change in arid edges of species distributions.

AimHuman land-use change contributes to biodiversity declines, but also creates new niches that facilitate novel biotic interactions. These interactions can reshape ecological communities and ecosystem function, yet remain poorly understood. Swiftlets and swallows in Southeast Asia present a classic example: coexistence is facilitated by fine-scale diet partitioning, with population sizes historically limited by available nesting substrates. However, several species now nest on manmade structures, particularly "nest farms" built to harvest edible swiftlet nests. We evaluated whether land-use change, especially the spread of nest farms, is leading to breakdowns in niche partitioning and increased competition among six sympatric swiftlets and swallows. LocationNorthern Borneo MethodsWe calculated geographic niche overlap using species distribution models (SDMs) with different environmental predictors, hypothesizing greater overlap when land-use variables were included. We then implemented joint species distribution models (JSDMs) to partition shared environmental responses from potential biotic interactions, predicting that competition would emerge as negative residual correlations. We used sightings from citizen-science datasets and structured surveys to evaluate the influence of climate, land-use, nest farms, morphology, and foraging behavior on species occurrences. ResultsSDMs that included land-use variables showed high niche overlap, suggesting that human activity homogenizes niches. The optimal JSDM, based on structured survey data, identified distance to nest farms as the strongest predictor of occurrence for all species, with species showing both positive and negative responses. Morphology and behavior had small effects, and residual correlations were weak, indicating limited unexplained biotic interactions. Main conclusionsHuman activity, through the creation of artificial nesting sites, broadly drives co-occurrence of swallows and swiftlets across our study region. These effects appear to operate primarily through environmental filtering rather than direct competition. Our findings reveal substantial and complex impacts of land-use change and anthropogenic nest sites on the distribution and composition of aerial insectivore communities.

O_LIAnimal-mediated seed dispersal is key for the maintenance and functioning of tropical ecosystems. Specifically, in the Cerrado, the largest Neotropical savanna and a global biodiversity hotspot, nearly 60% of plant species rely on animals for dispersal. C_LIO_LIClimate change threatens these interactions by affecting species distributions, reshaping communities, and potentially decoupling plants from their dispersers. Anticipating how such disruptions may alter seed dispersal networks is particularly relevant for understanding the resilience of future tropical ecosystems. C_LIO_LIHere, we combined empirical data on 139 pairwise plant-frugivore interactions with species distribution forecasts to build probabilistic interaction matrices under present and future climate scenarios, which were then used to construct 6,221 local seed dispersal networks. Using ecological niche modelling, we tested how climate change influences species range size and centroid displacement. Then, we evaluated whether such changes translate into losses of pairwise plant-frugivore co-occurrence. Finally, we investigated how these changes in occurrence overlap may affect key structural properties of future local seed dispersal networks. C_LIO_LIWe forecast that by the 2070s, under a business-as-usual climate scenario, species are likely to contract their ranges by 56 {+/-} 33% and shift their distribution centroids by 88 {+/-} 57 km within the Cerrado, leading to a 27 {+/-} 29% loss in plant-frugivore co-occurrence mainly driven by reductions in plant species distributions. At the community level, these losses will lead to smaller and more nested networks and specialized, indicating a structural simplification of seed dispersal systems in the Cerrado. C_LIO_LISynthesis: By combining empirical data on animal-mediated seed dispersal with forecasts of species distributions, we found that climate change may simplify frugivore-plant interaction networks in the Cerrado by decreasing species ranges and co-occurrence of partners. Our study demonstrates that future climate may pose a threat not only to species distributions but also to ecological interactions, such as seed dispersal, that are key to enabling climate-tracking by plants. Thus, preventing the simplification of interaction networks will be essential to conserve biodiversity in species-rich regions. C_LI

While Antarctic terrestrial ecosystems support low metazoan diversity, the surrounding marine macrobenthos is rich. However, marine meiofauna remains historically neglected, leaving its diversity patterns unclear. In this study, we used 18S rRNA gene metabarcoding alongside an enhanced taxonomic annotation pipeline to characterize marine meiofauna diversity in the Ross Sea, comparing it to global datasets. We evaluated how depth, habitat type, and mesh size influence community structures to test if habitat heterogeneity drives diversity despite the harsh Southern Ocean conditions. Our results revealed exceptionally high diversity, with metazoans richness comparable to or higher than temperate regions. Although environmental variables had limited effects on taxonomic richness, they significantly shaped community composition, with habitat type explaining the highest proportion of variance. Interestingly, we detected several ASVs 100% identical to North Sea and North Atlantic sequences, likely reflecting the limited taxonomic resolution of the 18S marker rather than global dispersal (the "meiofaunal paradox"). Overall, these findings demonstrate that Antarctic marine sediments host rich meiofaunal communities where ecological processes operate similarly to other global regions, contrasting sharply with depauperate continental Antarctic ecosystems.

The ongoing decline in biodiversity highlights the need for understanding the causes of population changes. This study uses 25-year, large-scale monitoring dataset to investigate the influence of climate and landscape structure on the annual population growth rates of 84 bird species across Poland. Our methodological framework involves the spatiotemporal decomposition of these environmental drivers to decouple demographic effects of long-term carrying capacities from the short-term effects of environmental perturbations. Using species-specific demographic models followed by a community-wide meta-analysis, we evaluated how individual species responses scale up to shape community-level dynamics. The results reveal significant variation in species-specific responses to individual drivers. At the community level, our findings suggest that bird populations are mainly regulated by the long-term spatial constraints rather than short-term disturbances. Persistent environmental heterogeneity had the strongest positive demographic effect on birds, followed by temperature, forest dominance over croplands, and precipitation. In contrast, rapid temporal shifts in environmental heterogeneity and precipitation anomalies negatively affected population growth, whereas urbanisation consistently exerted a negative effect across both spatiotemporal dimensions. Our results highlight the significance of protecting existing heterogeneous and ecotonal habitats, as well as the need to incorporate features that enhance habitat heterogeneity into urban development. Article impact statementPreserving heterogeneous habitats is essential for the conservation of bird populations.

O_LIA productivity-driven higher nutrient demand of trees in diverse mixtures is frequently reported. Yet, it remains unclear how tree diversity influences microorganisms-plants interactions, in which microbes facilitate tree nutrient acquisition in exchange for carbon (C) to meet the resource demand of both. C_LIO_LIUsing a long-term tree diversity experiment in the subtropics, we assessed microbial investment in C-, nitrogen (N)-, and phosphorus (P)-acquiring enzymes in litter and mineral soil, testing the effects of tree species richness and mycorrhizal type (arbuscular (AM)- vs. ectomycorrhizal (EcM)-associated tree species). C_LIO_LIWith increasing tree species richness, microbial investment in C acquisition decreased, while investment in N and/or P acquisition increased in litter and in mineral soil. In mineral soil of AM-associated tree mixtures, ecoenzymatic stoichiometry revealed a shift from microbial investment in C toward P acquisition as tree species richness increased. C_LIO_LIOur findings suggest that tree diversity strengthens microbe-tree interactions in terms of C-for-nutrient exchange. This highlights the key role of soil microorganisms, particularly in AM symbiosis, shaping tree diversity-biogeochemical feedbacks. C_LI

The small mammals in the tropical savannas of northern Australia, have undergone a degree of change in recent decades, best documented in the Northern Territory. Data is limited from northern Queensland and though the same trends are assumed, the topographic and climatic features differ substantially. In this study we examined data systematically collected from 725 sites between 1998-2012 in three bioregions representing a climatic gradient: from semi-arid to monsoon tropical savannas. We investigated via information-theoretic models and model averaging, the relationship between five mammal groupings and three landscape variables (fractional cover green, elevation and vegetation diversity) to elucidate any consistent or different patterns in the mammal fauna. Key patterns included relationships with increasing elevation (critical weight range species richness positively associated with elevation, rodent species richness negatively associated), increasing rodent and dasyurid species richness with vegetation diversity, and lower macropod and dasyurids abundance with increasing fractional cover green. These relationships underscore a need to consider mammal conservation in Queensland with more nuance than in the more topographically inert Northern Territory. Management strategies need to be more attuned to taxonomic and regional differences, to prevent perverse outcomes.

BackgroundA structural governance failure sits at the intersection of international biodiversity law and the digital genomics revolution. The Convention on Biological Diversity (CBD) and the Nagoya Protocol on Access and Benefit-Sharing (ABS) were designed to ensure that countries of biological origin share equitably in commercial benefits from their genetic resources. Critically, these instruments apply exclusively to non-human genetic resources: plants, animals, fungi, and microbiota. Human genetic resources are deliberately excluded from the CBD and Nagoya ABS framework and are governed separately through bioethics instruments, including the World Health Organization (WHO) framework and the Declaration of Helsinki. This study focuses on non-human digital sequence information (DSI), nucleotide and protein sequence data derived from non-human organisms deposited in open-access databases, which underpins industries generating over USD 1.56 trillion in annual revenue. Africa, hosting approximately 25% of global terrestrial species and nine of the worlds 36 biodiversity hotspots, provides a disproportionate share of the genetic resources from which non-human DSI is derived, yet receives negligible monetary returns because digitisation severs the traceability chain that ABS governance requires. Human genomic data is presented here solely as a secondary indicator of Africas broader infrastructure; it does not constitute the legal basis for Africas modelled allocation share under the Cali Fund. ObjectivesThis study systematically characterises (i) Africas non-human biodiversity endowment as the basis for Cali Fund claims; (ii) ABS governance readiness across 54 African Union (AU) member states; (iii) the commercial trajectories of non-human DSI-dependent industries and projected Cali Fund benefit-sharing flows; and (iv) Africas human genomic representation as a secondary infrastructure indicator, explicitly distinguished from the non-human DSI benefit-sharing argument. MethodsA structured evidence synthesis was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 reporting elements, where applicable to a secondary data analysis design. Literature was searched across PubMed, Scopus, Web of Science, Google Scholar, and official repositories of the CBD, Food and Agriculture Organization of the United Nations (FAO), International Union for Conservation of Nature (IUCN), and United Nations Environment Programme (UNEP). The search was restricted to January 2022 - April 2026 to capture post-Kunming-Montreal Global Biodiversity Framework (KMGBF) literature. A total of 412 records were identified before screening; 34 peer-reviewed articles and 19 institutional documents met all inclusion criteria. Quantitative Cali Fund scenario modelling used the United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) and KPMG (2024) non-human DSI sector revenue baseline (CBD/WGDSI/2/2/Add.2). The 12.5% net profit margin is a cross-sector proxy from that study; actual margins vary by sector. Africas modelled allocation share (20-25%) is the authors analytical construct based on Africas non-human species richness and hotspot share; it is not an internationally agreed formula. ResultsAfricas non-human biodiversity endowment is exceptional: 25% of terrestrial species, nine of 36 biodiversity hotspots, and the worlds second-largest tropical forest system. Non-human DSI from African genetic resources is a critical input to industries generating USD 1.56 trillion annually, yet Africa contributes a marginal and unmeasured fraction of International Nucleotide Sequence Database Collaboration (INSDC) sequences. As a secondary indicator, 94.48% of genome-wide association study (GWAS) participants as of 2024 were of European ancestry (Corpas et al., 2025); this human genomic data is presented for contextual illustration only and is not the basis for Africas Cali Fund modelled allocation share. Zero African Union member states have enacted legislation explicitly covering non-human DSI in their ABS framework. Africas modelled allocation share ranges from USD 312 million (Scenario A, 20% weight) to USD 5.83 billion (Scenario C, 25% weight) annually. ConclusionsAfrica is among the most biologically rich continents on Earth for non-human life, yet structurally excluded from the benefit-sharing framework the CBD intended to create. The Cali Fund represents the first mechanism capable of correcting this at scale. Realising Africas modelled allocation share requires urgent legislative reform, institutional capacity investment, sequencing infrastructure development, and a coordinated African position at COP17 scheduled in Yerevan, October 2026.

Understanding how global biodiversity patterns arise is a central theme of biogeography, with contemporary theory recognising the roles of both dispersal and vicariance. Genera that are broadly distributed can provide important systems for disentangling the relative influence of these processes across evolutionary timescales. However, many lesser-studied groups, particularly those in the tropics, lack a densely sampled phylogeny which hinders robust inference of their evolutionary and biogeographic history. This study investigates the global diversification and systematics of the putative pantropical moth genus Parasa Moore (Lepidoptera: Limacodidae), with the aim of assessing the relative importance of dispersal and vicariance in shaping its distribution. Medium-coverage whole genome sequencing of specimens predominantly from museum collections were used to generate a globally sampled time-calibrated phylogeny of Parasa and associated genera (the Parasa-complex). Ancestral range estimation analyses were employed to infer geographical origins and possible dispersal times between bioregions. The Parasa-complex originated in Africa in the late Oligocene ([~]24 Ma) and, through a series of long-distance dispersal events during the early-mid Miocene, expanded into Asia ([~]23 Ma) and the Americas ([~]21 Ma). Across all regions, dispersal was the dominant process shaping present-day distributions, with a limited role of vicariance in some subregions. Phylogenetic analyses further demonstrated that Parasa is not monophyletic, with multiple independent lineages contributing to its apparent pantropical distribution. These findings highlight a central role of long-distance dispersal in generating certain global distributions. The results support a dynamic model of range evolution involving rapid Miocene dispersal and subsequent regional diversification. In addition, the non-monophyly of Parasa requires substantial taxonomic revision, underscoring the importance of robust phylogenetic frameworks for interpreting global biodiversity patterns.

All organisms interact with other organisms, directly, and indirectly through different ecological relationships involving multiple types of interactions. Yet at broad continental scales, we lack comprehensive information on biotic interactions, which has hindered our ability to answer macroecological and eco-evolutionary questions across scales and to fully quantify the diversity of biotic interactions as an important dimension of biodiversity. Here, we help fill these gaps with an open and comprehensive dataset and data workflow of 25,907 pairwise, directional interspecific interactions among birds spanning a continental scale. All data are empirically documented and comprise bird-bird interactions across both breeding and non-breeding ranges of 731 focal avian taxa, covering all birds in the focal region of Canada and the continental United States, including Alaska. These data also include 1,258 additional avian taxa interacting with the focal taxa outside the focal region, resulting in 1,989 avian taxa altogether. The continental scale and breadth of interspecific interactions within these data fill fundamental knowledge gaps and enable scientists and practitioners to address a myriad of questions at broader scales than were previously possible.

Effective biodiversity conservation requires tools that can identify priority areas under growing human pressures. Building on the concept of global biodiversity hotspots, we present a transparent and repeatable approach to mapping conservation priorities using data for 33,604 species of terrestrial vertebrates from the IUCN Red List. This framework expands the taxonomic scope of previous efforts and integrates updated information on key human-driven threats to biodiversity. We identify that around 13% of Earths terrestrial surface qualifies as vertebrate conservation hotspots, often shaped by distinct combinations of species groups and threats. These results highlight the need for tailored, context-specific conservation strategies. By providing a robust method to guide spatial prioritization, our work supports more effective implementation of conservation targets in a rapidly changing world.

BackgroundThe Andean bear (Tremarctos ornatus), South Americas only ursid, is one of the worlds most elusive large mammals, making movement data collection exceptionally rare. Addressing this gap, we present the largest telemetry dataset ever assembled, spanning 19 individuals tracked across three Ecuadorian National Parks over two decades, paired with a novel analytical approach. MethodsWe integrated Continuous-Time Movement Models (CTMM), Auto-correlated Kernel Density Estimators (AKDEs), Hidden Markov Models (HMM) and a diel niche theoretical framework to mitigate biases previously unaccounted for the species in telemetry studies. Fine-scale AKDEs and non-linear movement metrics were calculated to understand seasonal space use and movement behaviors. Speed and diffusion from CTMM and behavioral states from HMM were modelled with environmental covariates to investigate which conditions shape diel and seasonal activity. ResultsPopulation mean home range was 138.2 km2 (95% Confidence Intervals 78.7-225.5), with males (239.8 km2; 182.8-307.5), significantly exceeding females (58.5 km2; 35.5-90.3). Notably, three females exhibited ranges comparable to some males. Weekly and monthly AKDEs uncovered cyclic home range dynamics potentially driven by resource availability, with contractions around corn harvests, mortino and achupalla fruiting, and expansions during paramo transitions. Decoupling speed from diffusion rates showed region-specific behaviors: intensive patch exploitation in Llanganates, broad exploratory ranging in Cayambe-Coca, and suppressed female locomotion in Cotacachi-Cayapas. Statistical analyses identified temperature as a key diel modulator and precipitation as the seasonal driver. Foraging probability increased between 2:00-6:00, large displacements between 7:00-14:00, and nocturnal movement rose significantly under colder conditions. Across diel hypothesis frameworks, bears were classified as cathemeral rather than strictly diurnal, corroborated by camera-trap records from Colombia, Ecuador, and Peru. ConclusionsWe propose a cathemeral diel phenotype that responds to thermal fluctuations and situates Andean bears within a broader ursid context of thermoregulatory niche plasticity. This dataset reveals unprecedented resolution of regional and sex specific behaviors that will facilitate and accelerate comparative studies in rapidly changing Andean landscapes. By releasing this long-term dataset as an open resource, we provide a foundation for climate-resilient conservation strategies. More broadly, we advocate for data democratization and invite collaboration.

Convolutional Neural Networks (CNNs) have become increasingly prominent in biodiversity monitoring due to their strong performance in accurately detecting species from sound recordings, overcoming some limitations of traditional methods such as point-counts. Yet, their use in urban ecosystems remains limited, highlighting the need for frameworks that identify modelling strategies to optimize their performance in these complex soundscapes. Here, we evaluated how preprocessing and labelling strategies, detection thresholds, sample size, and architecture affect the performance of CNNs for bird identification in urban tropical ecosystems. We also assessed its potential by comparing CNN-derived biodiversity estimates with those from point-counts and acoustic indices. For this, we used one week of recordings collected along urbanization gradients in five Colombian Andes cities to developed 11 multiclass CNN models varying in spectral representation, labelling strategies, training data source and backbone architecture. The best-performing model, evaluated with F1-scores, combined Log-Mel spectrograms, multispecies labels, ecosystem-specific recordings, a probability threshold of 0.3 and a ConvNeXt backbone with its performance generally improving with sample size. Although CNNs and point counts detected partially distinct assemblages, CNN-derived species richness was comparable to that estimated from point-counts. In addition, the Normalized Difference Soundscape Index (NDSI) was positively associated with richness, suggesting its potential as a biodiversity proxy in tropical urban soundscapes. Overall, by identifying effective modelling designs and monitoring strategies, our study advances the development of robust biodiversity assessment frameworks in urbanized ecosystems in the Neotropics whilst also providing methodological guidance for future research and practical insights for wildlife monitoring and conservation.

Forest regeneration depends not only on how many seeds trees produce, but on the physiological quality of those seeds. Yet while climate-driven shifts in seed quantity and masting have received sustained attention, the parallel question of whether climate change degrades seed quality remains poorly resolved. Using a nationwide dataset of seed mass and viability in European beech (Fagus sylvatica L.) collected between 1996 and 2024 (13,349 seed lots from 381 forest districts across Poland), with climate-quality analyses focused on 5,374 freshly harvested seed lots from 353 districts (2004-2023), we asked whether the two components of seed quality respond to different seasonal climatic windows, and whether harvest-year climate also shapes seed performance during long-term cold storage. Seed mass and seed viability were only weakly correlated (Spearmans {rho} = 0.15), acting as two independent dimensions of seed quality. Both revealed substantial temporal variation over the study period, but along distinct trajectories. Seed mass declined markedly between segmented-regression breakpoints in 2009 and 2019, more steeply at higher latitudes, coinciding spatially and temporally with the masting breakdown reported at the species northeastern range margin. Climatic associations were correspondingly divergent. Viability was positively associated with previous summer temperature, consistent with temperature-cued flower initiation, and negatively with spring temperature in the harvest year, plausibly reflecting thermal disruption of early embryogenesis. Seed mass showed no significant association with any seasonal climatic predictor, indicating control by slower or unmeasured processes. Storage duration progressively reduced viability, and this decline was further modulated by climate during seed development, with seeds developing under climatically suboptimal conditions losing viability faster. These results expose a hidden decoupling between seed quantity and seed quality under contemporary climate change, with direct consequences for forest regeneration and for ex situ conservation strategies that assume mast-year seeds will remain viable for decades.

AO_SCPLOWBSTRACTC_SCPLOWO_LIAirborne imaging spectroscopy enables species-level classification in hyperdiverse tropical forests, but accuracy varies enormously among species. We asked which ecological and evolutionary attributes make a tropical tree species spectrally separable. C_LIO_LIUsing 3,256 field-verified crowns spanning 169 species in a hyperdiverse moist forest in French Guiana, we tested seven hypothesised determinants of classification accuracy at species, pairwise, and individual-crown scales using random forest, beta regression, elastic net, and binomial GLMM analyses. C_LIO_LIPhenological regularity - the strength and consistency of seasonal leaf-cycling - was the single strongest predictor of separability, emerging as the top-ranked variable across all analyses. The presence of congeneric species in the classification pool also reduced accuracy, while broader phylogenetic isolation contributed in multivariate models. At the crown level, crown area was the strongest predictor of correct classification, while liana infestation reduced odds of correct identification by 38%. Leaf chemical traits did not predict separability. C_LIO_LIIt is the consistency of a species ecological signal - its phenological rhythm, spatial sampling, and freedom from canopy contamination - rather than any single functional trait, that determines whether it can be reliably mapped from imaging spectroscopy. C_LI

AimA comprehensive understanding of the spatial distribution of biodiversity is hindered by fragmented datasets, sampling biases, and inconsistent observation protocols. Here, we present a workflow that integrates disparate datasets to produce large scale maps of biodiversity metrics as a basis for management-relevant information tools. We use integrated species distribution modeling (iSDM) to account for sampling biases and disparate data collection techniques, taking advantage of the vast numbers of open datasets available in data aggregators like GBIF. LocationNorway (excluding Svalbard and Jan Mayen) TaxonVascular plants MethodsThe workflow consists of four main steps: data acquisition, data integration, integrated species distribution modelling (iSDM), and the production of derived outputs. Input data include structured surveys, opportunistic observations, and environmental covariates. These are standardised and integrated into a point-processed based iSDM framework to produce species richness maps, associated uncertainties, and sampling effort maps. The outputs are further processed to identify biodiversity hotspots or to summarise species-environment relationships. The workflow used vascular plant data from Norway, combining occurrence-only and presence-absence datasets with environmental covariates. Outputs were generated at a spatial resolution of 500 x 500 meters, balancing accuracy, computational feasibility and relevance for management decisions. High-performance computing resources were utilized for model fitting and predictions. A subset of available data was used to validate the species richness maps. ResultsWe produced detailed maps of species richness, uncertainties and sampling intensity across Norways heterogeneous landscape, incorporating 1218 species in our final results. The species richness patterns highlight patterns consistent with previous mapping efforts. Validation showed an increase in model accuracy when compared to models which did not use an iSDM framework. The workflow highlights limitations in the infrastructure of the currently openly accessible data, particularly the need for more structured presence-absence datasets and standardized metadata. Main conclusionsThis study underscores the potential of workflows that integrate disparate datasets for biodiversity modeling. To maximize accuracy and utility, future efforts should focus on improving data standardization, the publication and collection of more structured data, and fostering data-sharing collaborations. Advances in the workflow itself, including optimising modelling covariates and integrating more comprehensive spatio-temporal aspects, will also increase the relevance of the outputs. These advances will increase our ability to estimate species richness with a precision and accuracy that can reliably inform conservation and management decisions.

O_LICliffs are environmentally extreme yet biodiversity-rich ecosystems that harbour specialist plants, many endemic and threatened. Plant persistence in these nutrient-poor substrates may depend on tightly linked soil- and root-associated microbial communities, which remain poorly understood. These interactions may become increasingly important with the global expansion of recreational climbing. While physical climbing impacts on vegetation are documented, potential chemical effects, from the use of climbing chalk (magnesium carbonate), on soil properties and plant-associated microbiota remain unknown. C_LIO_LIWe sampled soils and roots beneath cliff-specialist and generalist plants, and unvegetated soils, across climbed and unclimbed routes in northern, central, and southern Spain. Soil physicochemical properties were quantified, fungal communities were characterized using ITS-metabarcoding, and structural equation modelling was used to disentangle direct and indirect effects. C_LIO_LIClimbing increased soil pH and altered soil chemical properties, driving shifts in fungal diversity and functional composition in soil and roots. The relative read abundance of root-associated symbiotrophic fungi declined, whereas arbuscular mycorrhizal fungi and pathogens increased in climbed cliffs. Overall effects were consistent, with cliff-specialist plants mediating nutrient and fungal shifts. C_LIO_LIur findings show that climbing can reshape cliff soil chemistry and fungal communities, with potential cascading consequences for plant functional performance, nutrient dynamics, and ecosystem resilience. C_LI

A major goal of community ecology lies in the deciphering of the processes underlying species distribution. A widespread approach to this question is to identify patterns in species community data and relate them to possible processes. Joint Species Distribution Models (JS-DMs) offer one way to do so through the infernece of association networks that describe patterns of statistical correlations and dependencies between species, but it is unclear what processes can explain the presence of such correlations. While it has now been established that there is no equivalence between JSDM-inferred associations and biotic interactions, the later remain one possible explanation, among others, for the former. However, to our knowledge, there is no specific study of the statistical patterns induced by different types of interactions or of the conditions under which they may or may not appear as statistical correlations / dependencies in species communities. To explore these questions, we propose a "virtual ecologist" approach that consists in simulating community data based on abiotic and biotic processes with the VirtualCom model that emulates the effects of environmental processes and of competition and facilitation interactions. Then, we study to what extent JSDMs retrieve correlations between species that match the simulated interactions. We show that these interactions are better identified when using JSDMs that model partial correlations between species rather than marginal ones. We further demonstrate how critical it is to correctly model abiotic effects in order to identify biotic ones and that the "correct modelling" of these effects depend on the type of interactions at stake.