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bioRxiv2026

Defining ecologically realistic biodiversity offset multipliers with the Response-based Habitat Hectare Assessment of Biodiversity Gains (REHAB)

In biodiversity offsetting, balancing biodiversity losses with gains can be achieved by using multipliers that define the ratio between the magnitude of biodiversity loss and the area required to deliver equivalent biodiversity gains. Although there is broad scientific consensus that multipliers should be calibrated to deliver no net loss or a net gain for biodiversity, they are often applied without quantitative assessment of the ecological outcomes of offset actions. Here we operationalise the Response-based Habitat Hectare Assessment of Biodiversity Gains (REHAB), a framework where multipliers are informed by an understanding of habitat-specific ecological responses to offset action. To support Finlands national biodiversity offsetting scheme, we harnessed the knowledge of 111 experts to compile ecological attributes and condition matrices for all 388 Finnish habitat types and derive 346 offset action multipliers that represent ecological response functions for 216 habitat type-specific offset actions including restoration, management and passive recovery. Our analysis reveals substantial variation in response-functions, resulting in offset multipliers between 1.3-4,000 across offset actions and habitat types. We find that the fixed multipliers commonly used in offset schemes would result in net loss in 60% of the cases if action- habitat specific responses were not considered. This variability underscores that fixed multipliers cannot deliver reliable biodiversity outcomes and should be avoided in offsetting schemes. The REHAB framework has already been integrated into Finlands national offsetting policy. Other potential areas of application include informing ecosystem restoration planning and assessing biodiversity gains linked to credit issuance in emerging nature-credit markets.

ecology↗

bioRxiv2026

Lessons from local ecological knowledge: cumulative stressors and governance constraints in Spanish clam fisheries

Spanish clam fisheries have contracted sharply over the past two decades, with repeated closures and declining landings affecting coastal livelihoods. Using local ecological knowledge (LEK), we examine how fishers, fishers guild leaders and regional managers interpret (i) ecological change and (ii) the institutional conditions shaping management outcomes in Spains main clam fisheries, focusing on wedge clam (Donax trunculus), striped venus clam (Chamelea gallina) and smooth clam (Callista chione). We conducted 94 semi-structured interviews (April 2024-August 2025) across the Spanish Mediterranean and the south Atlantic coast (Catalonia, Valencian Community, Balearic Islands, Murcia and Andalusia). Stakeholders characterised declines as a cumulative process driven by interacting stressors: climate variability and extremes, coastal habitat alteration, pollution, episodic disease events and fishing pressure intensified by illegal extraction and informal marketing. Governance assessments were predominantly negative, emphasising fragmented authority across administrative scales, delayed or reactive measures, uneven rules among gears exploiting shared stocks, limited user influence in decision-making, and chronic monitoring and enforcement gaps, especially for shore-based fisheries operating outside port-based control points. Overall, LEK closely aligns with scientific evidence on cumulative stressors, suggesting that persistent declines reflect less a lack of ecological understanding than institutional constraints that hinder timely, legitimate and enforceable responses. Policy priorities include climate-adaptive harvest rules linked to environmental indicators, co-produced monitoring, strengthened traceability and compliance, harmonised rules across gears and management units, and improved cross-sector coordination to reduce conflict and safeguard nearshore habitats. HighlightsO_LIStakeholders across Spain describe clam declines as the outcome of interacting ecological, climatic, and governance stressors rather than as the consequence of isolated drivers. C_LIO_LIPerceived drivers differ regionally: climate- and habitat-related pressures dominate the Mediterranean, while effort, illegal fishing, and market dynamics are more salient in the Gulf of Cadiz. C_LIO_LIMost interviewees view management and governance as ineffective, citing fragmented authority, uneven rules among gears and regions, and weak enforcement. C_LIO_LIInformal practices (off-auction sales and poaching) are repeatedly identified as mechanisms undermining legitimacy, traceability, and effort controls--particularly in nearshore wedge clam fisheries. C_LIO_LIPolicy pathways include harmonising cross-scale rules, strengthening monitoring and compliance, and institutionalising co-management that integrates LEK with science. C_LI

ecology↗

bioRxiv2026

Prophage activity shapes the thermal ecology and evolution of a marine bacterial host

Predicting the response of populations to thermal change is challenging due to temperature-dependent interspecific interactions, such as those between bacteria and their integrated viruses (prophages). Temperature is known to modulate prophage activity, raising the question of whether and how prophages alter host responses to temperature. In this work, we explored how prophage infection shapes host thermal ecology and evolution in a novel marine bacterial isolate carrying a spontaneously inducing prophage. We first characterized the effect of temperature on bacteria and phage population dynamics, finding that high temperatures led to bacterial population crashes and reduced yield, with abundant phage production across all temperatures. To then determine the causal impacts of this phage, we infected a conspecific susceptible strain and found that performance in the novel lysogen was reduced across all temperatures and indistinguishable from the naturally infected strain. Further, we found that evolutionary rescue mutants of the naturally infected strain with an expanded upper thermal limit gained high temperature adaptation through a reduction in prophage activity. Overall, we found that intraspecific variation in thermal ecology was explained by prophage infection, and that adaptation to nonpermissive temperature occurred through modifications to prophage dynamics. This work demonstrates a critical link between viral mobile genetic elements and bacterial thermal responses, and emphasizes the importance of ecological interactions in thermal ecology and evolution.

ecology↗

bioRxiv2026

Ecological predictability emerges at the population level in phytoplankton communities

Predicting the composition and dynamics of ecological communities is challenging because complexity increases rapidly with species richness. A common strategy is to adopt a reductionist framework in which community dynamics are inferred from simpler components, such as population-level parameters or organismal traits. However, it remains unclear at which level of biological organization ecological predictability emerges. Here we experimentally test this reductionist cascade in marine phytoplankton communities. We first ask whether multispecies dynamics can be quantitatively predicted from demographic parameters measured in monocultures and species pairs. We then test whether these predictive parameters can themselves be inferred from organismal traits, focusing on cell size. We find that community composition is highly reproducible and can be accurately predicted from population-level parameters measured in simpler experimental settings. In contrast, these parameters do not show systematic relationships with cell size and cannot be predicted from this commonly used trait. These results demonstrate that ecological predictability emerges at the population level, where demographic parameters capture the combined effects of underlying biological processes, but resist further reduction to simple trait-based descriptions, suggesting that ecological interactions reshape organismal performance across levels of organisation.

ecology↗

bioRxiv2026

Energetic constraints shape the diversity of feasible ecological networks

The relationship between energy supply and biodiversity is a longstanding question in ecology. Although a monotonic increase in diversity with energy availability is often assumed, unimodal species-energy relationships have been widely documented across ecosystems, and their origin from first principles remains unclear. Here, we develop a geometric framework that recasts ecological feasibility in explicitly energetic terms. By treating total energy supply as a system-level constraint on an energy-based network model, we define nested feasibility domains in the space of energy capture rates and quantify feasibility probabilities as their volume ratios. We show that the probability of initializing a feasible network increases monotonically and saturates with energy supply, whereas the probability of sustaining steady-state biomass follows a unimodal relationship--revealing a bounded energetic window within which network maturation is most likely. Extending this analysis to all candidate subcommunities via feasibility partitions, we find that different community sizes are most feasible at different energy levels, and that average diversity itself peaks at intermediate supply. Together, these results suggest that energetic constraints determine the diversity of ecological networks not through energy scarcity alone, but through the geometric interplay between external energy supply and internal energy exchange. Author SummaryWhy do many ecosystems show the highest biodiversity not where energy is most abundant, but at intermediate levels? This unimodal species-energy relationship has been documented across grasslands, wetlands, and rainforests, yet its origin from first principles has remained unclear. We approached this question by developing a simplified model that treats ecological networks as energy-processing systems. In this model, each species captures energy from the environment and exchanges it with others, and the total energy available to the network is explicitly limited. By measuring how the likelihood of species coexistence changes with energy supply within this framework, we found that while a minimum energy threshold is needed for any community to persist, too much energy can paradoxically reduce the chance of long-term coexistence. This creates a bounded energy window most favorable for community persistence. When we extended the analysis to all possible subsets of species, we found that different-sized communities are most likely to persist at different energy levels, and that overall expected diversity peaks at intermediate supply. These results suggest a possible geometric origin for why more energy does not always support more species, providing a theoretical baseline for connecting the structure of energy flow within networks to observed biodiversity patterns.

ecology↗

bioRxiv2026

A Multi-Scale Ecological Approach to Assessing Antimicrobial Resistance in a Freshwater Fish

Antimicrobial resistance (AMR) genes are increasingly recognized as an emerging environmental contaminant. Yet, the ecological mechanisms shaping their distribution across natural landscapes remain poorly understood. Here, we quantified AMR gene abundances in microbial communities sampled from wild fish from eight freshwater lakes on Vancouver Island and paired these gene-level measurements with fine-scale limnological and land-use data. Using droplet digital PCR, field surveys, and an iterative spatial forecasting framework that integrates Random Forest models with regression kriging, we explored how watershed-scale processes relate to variation in AMR genes across lakes. Our analyses reveal potential associations between elevated AMR gene levels, changes in water quality, deforestation, and geographic proximity to salmon aquaculture. By integrating data across biological and spatial scales, from genes within microbial communities to lake-level conditions and landscape patterns, this study illustrates the value of combining quantitative molecular measurements with geospatial modeling to identify environmental factors that may promote antimicrobial resistance in natural systems. Our approach provides a proof-of-concept and a general predictive framework for generating hypotheses and informing future monitoring efforts aimed at understanding, managing, and forecasting environmental reservoirs of resistance. SignificanceAntimicrobial resistance (AMR) genes are ancient components of environmental microbiomes. Yet, the mechanisms that generate modern hotspots of resistance across natural landscapes remain unclear. Here, we reveal how watershed-scale environmental change, including water quality metrics linked with deforestation and proximity to salmon aquaculture, predicts elevated AMR gene levels in the microbiomes of wild fish populations. By combining quantitative droplet digital PCR with ecological data and geospatial modeling, we move beyond isolated surveillance data to identify ecological mechanisms that promote antimicrobial resistance in freshwater ecosystems. This integrative approach provides mechanistic insight into why certain habitats, and the organisms within them, become reservoirs of resistance while others do not. Our findings highlight the importance of ecological context in understanding resistance evolution and offer a predictive tool for informing proactive monitoring and management strategies.

ecology↗

bioRxiv2026

Still Lost in Definitions: How Resilience Is Used in Ecology

Resilience is a central concept in ecology and environmental policy, yet its meaning and quantification remain inconsistent across subfields. Clarifying how resilience is defined and measured across the subfields of ecology is therefore a critical step towards delivering coordinated efforts to strengthen resilience research. Here, we analyse 594 studies published between 1977 and 2025 to determine how resilience is quantified across ecological contexts. Using large language models to extract structured data and conditional inference forests to assess predictors of metric choice, we show that resilience is most commonly ([~]25%) quantified using recovery rate and recovery degree, but no single metric dominates. Crucially, study attributes like organisational level, methodological approach, and disturbance regime explain only a small fraction of variation in metric selection. Despite this apparent inconsistency, more than 90% of studies draw from a shared set of six quantitative dimensions of resilience. This combination of weak constraint and latent convergence suggests that resilience metrics function as a flexible but implicitly standardised toolkit rather than as context-specific constructs. We argue that this hidden structure provides a foundation for a unified, multidimensional resilience framework that can support synthesis across ecological systems and improve the translation of resilience science into conservation and policy.

ecology↗

bioRxiv2026

The rENM Framework: A Modular System for Reconstructing andAnalyzing Long-Term Ecological Niche Dynamics

Retrospective ecological niche modeling (rENM) combines historical species occurrence records with historical environmental data to reconstruct the spatio-temporal dynamics of species-environment relationships under changing conditions. Despite growing recognition that those relationships can be nonstationary, time-series approaches to ecological niche modeling remain uncommon, and the tools to support them at scale are limited. Here, we describe the rENM Framework, an experimental, open-source suite of R packages that automates a complete rENM workflow spanning data preparation, ensemble time-series construction, trend analysis, AI interpretation, and report generation. The framework integrates eBird occurrence records with environmental variables derived from NASAs MERRA-2 reanalysis across a 45-year study period (1980-2024) and executes a complete analysis for any species with eBird data through a single function call. By treating climatic suitability as a dynamic ecological response surface rather than a static baseline, the framework produces the following analytical products that complement conventional ecological niche modeling approaches: suitability time series, long-term trend and acceleration maps, centroid displacement estimates, bioclimatic velocity metrics, variable contribution trajectories, and hotspot analyses identifying areas of accelerating suitability decline. We illustrate the frameworks outputs with a representative run for Cassins Sparrow (Peucaea cassinii), a grassland species of conservation concern in the arid southwestern United States and the focal species throughout our development work. The frameworks automated, unsupervised pipeline makes systematic application across large numbers of species tractable, with direct implications for conservation assessments, such as State Wildlife Action Plans, where species-specific analytical capacity is often limited by available resources. The rENM Framework is openly available on GitHub and archived on Zenodo.

ecology↗

bioRxiv2026

Bounded ecological memory in coral reefs: divergent demographic pathways under recurrent heatwaves and collapse under extreme thermal stress

Anthropogenic warming exposes coral reefs to recurrent marine heatwaves (MHWs), yet responses to comparable thermal stress remain highly variable. A central challenge is determining whether reduced bleaching reflects acclimatization-like persistence of existing colonies or mortality-driven filtering that produces demographically depleted assemblages. Using colony-level surveys across the Florida Reef Tract (2014-2023), we show bleaching sensitivity declined from 2014 through 2022, consistent with ecological memory. A spatial matched-event framework integrating bleaching severity and adult colony density resolved these reduced-bleaching outcomes into two distinct pathways: demographic persistence (stable/increasing density) and mortality-filtered tolerance (declining density). Persistence pathways were maintained under predictable exposure regimes characterized by lower interannual thermal variability. This persistence was driven by weedy life-history taxa (e.g., Porites spp.) replacing historical framework builders, indicating stability reflects ecological reassembly rather than uniform increases in thermal tolerance. Under the unprecedented extremes of the 2023 MHW, this acclimatization-like buffering broke down, causing widespread sensitization and collapse of previously persistent networks. These results support a bounded ecological memory framework; prior exposure reduces bleaching sensitivity under predictable thermal regimes but fails under extreme heat stress. Consequently, modern refugia are best defined by adult standing stock retention representing systems undergoing selective ecological reassembly rather than full functional recovery.

ecology↗

bioRxiv2026

Parameter non-identifiability limits ecological inference from historical plague mortality records

Historical plague mortality records provide unusually detailed temporal records of epidemic dynamics. However, the ecological processes underlying those dynamics are rarely observed. This creates a fundamental challenge for inference into ecological mechanisms, as multiple combinations of unobserved ecological parameters and initial conditions may produce similar mortality trajectories. We investigated this problem by examining the geometry of parameter compensation for models of the Barcelona plague outbreak of 1490. We fit a mechanistic rat-flea-human transmission model to daily human mortality data under three values of flea search efficiency, then characterized the resulting joint posterior distributions. We then used a phenomenological model in which human infection was driven by a time-varying external force of infection, allowing us to separate parameter dependencies arising from deterministic structure. The mechanistic model reproduced the broad temporal structure of the observed epidemic, but exhibited strong linear and nonlinear dependencies among transmission parameters and initial rat and flea conditions. Similar dependencies persisted in the phenomenological model, despite its substantially reduced complexity. However, fixing the timing of the external hazard substantially reduced these dependencies. These results demonstrate that detailed mortality records can constrain the temporal pattern of an epidemic without uniquely identifying the mechanisms that generated it. Rather than simply adding additional mortality records, improving mechanistic inference from historical epidemics may require recovering independent observations of upstream ecological processes, such as timing of rodent or flea dynamics as well as environmental drivers. Mechanistic models can therefore serve not only to reconstruct historical epidemics but also to identify which missing observations would most improve inference.

ecology↗

bioRxiv2026

Forest-weighted causal correlation: A scalable framework for causal inference in ecological time series

1. Detecting causal relationships from ecological time series remains challenging because community dynamics are often nonlinear, high-dimensional, noisy, and strongly synchronized. These characteristics can reduce the reliability of existing causal inference methods and complicate the identification of ecological interactions in complex natural systems. 2. I introduce Forest-weighted Causal Correlation (FORCC), a machine-learning-based framework that infers directional causality from adaptive neighborhood structures learned by random forests. Rather than evaluating causal direction through cross-map reconstruction, FORCC quantifies directional dependence from the preservation of neighborhood structure using rank-based associations among forest-weight matrices. 3. Simulations of coupled nonlinear systems showed that FORCC accurately recovered causal direction while substantially reducing synchronization-induced false-positive detections relative to conventional convergent cross mapping. Chatterjee's {xi} exhibited the strongest resistance to synchronization-induced errors among the evaluated rank-based statistics. 4. Application to a 12-year marine community time series from Maizuru Bay, Japan, identified asymmetric relationships between individual taxa and community dynamics, revealing candidate driver-like and passenger-like roles that were not readily explained by seasonal synchrony alone. 5. By combining adaptive neighborhood learning with rank-based causal inference, FORCC provides a scalable framework for causal discovery in ecological time series. The method offers a practical tool for screening causal relationships, generating ecological hypotheses, and investigating complex interactions in multivariate natural systems.

ecology↗

bioRxiv2026

Land use and climate warming interact to reshape global avian biodiversity through ecological filtering and homogenisation

Land-use and climate change are dominant drivers of terrestrial biodiversity change, yet are usually analysed separately although they co-occur and may interact. We integrated global bird assemblage records from PREDICTS with temperature anomalies and species' ecological characteristics to test how land use modifies biodiversity responses to climate warming across three dimensions: local abundance and richness, compositional dissimilarity among assemblages, and species occurrence across ecological groups. Land use modified warming associations for both abundance and richness. Relative to primary vegetation, warming associations were more positive in low-intensity agriculture for both responses, but more negative for richness in high-intensity agriculture and urban land. Predicted richness remained below the reference, defined as primary vegetation at temperature anomaly 0, across all modified land uses, with the largest declines in high-intensity agriculture (-17.9%) and urban land (-21.8%). Within land-use classes, greater warming exposure was generally associated with higher compositional similarity, consistent with warming associated biotic homogenisation. Occurrence models revealed ecological filtering: broad-niched generalists were favoured in warmer modified habitats, whereas range-restricted habitat specialists were filtered out under intensive land use and warming. Conservation assessments should therefore integrate land-use-warming interactions with changes in assemblage composition and ecological strategies, particularly in agricultural and urban landscapes where warming further disadvantaged range-restricted specialists.

ecology↗

bioRxiv2026

Spatial segregation and multi-scale space-use adjustments to socio-ecological variables in western gorillas

Background: Identifying the mechanisms that shape space-use dynamics and the scale at which they operate can provide insights into the socio-ecology of numerous animal species. This is crucial for addressing both applied (e.g., conservation) and theoretical questions (e.g., the coexistence or segregation of individuals). Yet, longitudinal views of the space-use dynamics are generally rare. Taking advantage of a long-term movement dataset (up to 8 years) on five habituated groups of wild western gorillas (Gorilla gorilla) in Central Africa, we investigated the dynamics of their space use in relation to the socio-ecological variables from everyday movement to home range shifts. Methods: We looked at which temporal scale their ranging movements are stationary to highlight the dynamics of home range settling and shifts. We also studied how daily space use is shaped by (i) foraging and intra-group constraints (i.e., diet, group size, presence of offspring), and by (ii) inter-group competition (direct or indirect), quantifying static and dynamic interactions in neighbouring group-dyads. Results: Gorilla groups shifted the centre of their home range 0.17 times per year by a distance larger than the mean home range radius. Movements within the home range were highly dependent on the group composition and the ecological features (with larger daily-travelled distances in the high-fruit season compared to the low-fruit season). The presence of dependent infants affected the daily-travel distance: the larger their number, the smaller the daily-travel distance. Furthermore, the frequently visited sites of the home range were also used the longest, but their locations differed seasonally, suggesting space use flexibility. Although there was little overlap between the home ranges of neighbouring groups, these groups did not seem to avoid each other more than expected at random. They could even venture into, and slept in, the central part of the home range of a neighbouring group. Conclusion: Our study suggests that spatial segregation should be the simple consequence of avoidance of depleted areas rather than of territorial behaviour. It shows how socio-ecological constraints may shape the space-use patterns at different scales in a non-territorial species, and questions the role of cognition in space-use dynamics.

ecology↗

bioRxiv2015

Ancestral genome reconstruction reveals the history of ecological diversification in Agrobacterium.

Horizontal gene transfer (HGT) is considered as a major source of innovation in bacteria, and as such is expected to drive adaptation to new ecological niches. However, among the many genes acquired through HGT along the diversification history of genomes, only a fraction may have actively contributed to sustained ecological adaptation. We used a phylogenetic approach accounting for the transfer of genes (or groups of genes) to estimate the history of genomes in Agrobacterium biovar 1, a diverse group of soil and plant-dwelling bacterial species. We identified clade-specific blocks of co-transferred genes encoding coherent biochemical pathways that may have contributed to the evolutionary success of key Agrobacterium clades. This pattern of gene co-evolution rejects a neutral model of transfer, in which neighbouring genes would be transferred independently of their function and rather suggests purifying selection on collectively coded acquired pathways. The acquisition of these synapomorphic blocks of co-functioning genes probably drove the ecological diversification of Agrobacterium and defined features of ancestral ecological niches, which consistently hint at a strong selective role of host plant rhizospheres.

Evolutionary Biology↗

bioRxiv2016

A tradeoff between the ecological and evolutionary stabilities of public goods genes in microbial populations

Microbial populations often rely on the cooperative production of extracellular \"public goods\" molecules. The cooperative nature of public good production may lead to minimum viable population sizes, below which populations collapse. In addition, \"cooperator\" public goods producing cells face evolutionary competition from non-producing mutants, or \"freeloaders\". Thus, public goods cooperators have to be stable not only to the invasion of freeloaders, but also to ecological perturbations that may push their numbers too small to be sustainable. Through a combination of experiments with microbial populations and mathematical analysis of the Ecological Public Goods Game, we show that game parameters and experimental conditions that improve the evolutionary stability of cooperators also lead to a low ecological stability of the cooperator population. Complex regulatory strategies mimicking those used by microbes in nature may allow cooperators to beat this eco-evolutionary stability tradeoff and become resistant to freeloaders while at the same time maximizing their ecological stability. Our results thus identify the coupled eco-evolutionary stability as being key for the long-term viability of microbial public goods cooperators.

Evolutionary Biology↗

bioRxiv2016

Genomic and Metagenomic Analyses Reveal Parallel Ecological Divergence in Heliosperma pusillum (Caryophyllaceae)

Cases of parallel ecological divergence in closely related taxa offer an invaluable material to study the processes of ecological speciation. Applying a combination of population genetic and metagenomic tools on a high-coverage RAD sequencing dataset, we test for parallel evolution across six population pairs of Heliosperma pusillum and H. veselskyi (Caryophyllaceae), two plant species found in the south-eastern Alps and characterized by clear morphological (glabrous vs. hairy) and ecological (alpine vs. montane, wet vs. dry) differentiation. Our analyses support a scenario of multiple independent instances of divergence between these species during the last 10,000 years. Structure analyses and simulations show that interspecific gene flow in each population pair is very low. A single locus, annotated as E3 ubiquitin ligase, an enzyme involved in plant innate immunity, shows a pattern of non-random segregation across populations of both species. A metagenomic analysis revealed information about contaminant exogenous DNA present in RAD sequencing libraries obtained from leaf material. Results of this analysis show clearly divergent bacterial and fungal phyllosphere communities between the species, but consistent communities across populations within each species. A similar set of biotic interactions is involved, together with abiotic factors, in shaping common selective regimes at different growing sites of each species. Different occurrences of H. veselskyi appear now genetically isolated from H. pusillum and from each other, and may independently proceed along the speciation continuum. Our work supports the hypothesis that repeated ecological divergence, observed here at an early stage, may be a common process of species diversification.

Evolutionary Biology↗

bioRxiv2020

Ecological niche models as hypothesis generators of functional genetic differentiation and potential local adaptation in a Mediterranean alpine ecosystem

Geographically disparate populations within a species range may show important differences including variation in ecological, demographic, genetic and phenotypic characteristics. Based on the Center-Periphery Hypothesis, it is often assumed that environmental conditions are optimal in the geographic center of the range and stressful or suboptimal at the periphery, implying ecological marginality is concordant with geographic periphery. But this assumption has been challenged as geographical and ecological gradients are not necessarily concordant. The conservation value of populations inhabiting environmentally marginal areas is still under debate and is closely related with their evolutionary potential. Strong selective pressures caused by stressful conditions may generate novel adaptations in marginal areas, conferring these populations distinct evolutionary potential. But populations inhabiting marginal areas may also show reductions in neutral and adaptive genetic diversity via drift and inbreeding. In this work we explore the potential of ecological niche models (ENMs) to identify environmentally optimal and marginal areas, as well as the principal putative selective pressures likely to act. To do so, we built a carefully parameterized ENM of Silene ciliata, a dominant plant species of Mediterranean alpine habitats. Complementarily, we selected wild populations inhabiting contrasting environmental conditions and carried out common garden experiments to detect genetic differentiation among populations associated with functional traits. With the resulting information, we tested whether environmentally marginal populations defined by the ENM had genetically differentiated phenotypes that are potentially adaptive and, thus, of conservation value. We found genetically based phenotypic differentiation of phenological traits between populations inhabiting areas identified by the ENM as marginal and optimal, as well as between populations with different habitat suitability values. Results supported ENMs as powerful tools for determining environmental marginality and identifying selection pressures, and thus also as hypothesis generators for divergent selection. Furthermore, genetically based phenotypic differentiation found underlines the potential adaptive value of populations inhabiting marginal areas. The approach developed here provides a theoretically justified and practical way to study adaptive processes and provide insights about the conservation value of marginal populations.

evolutionary biology↗

bioRxiv2020

Cold adaptation drives population genomic divergence in the ecological specialist, Drosophila montana

Detecting signatures of ecological adaptation in comparative genomics is challenging, but analysing population samples with characterised geographic distributions, such as clinal variation, can help identify genes showing covariation with important ecological variation. Here we analysed patterns of geographic variation in the cold-adapted species Drosophila montana across phenotypes, genotypes and environmental conditions and tested for signatures of cold adaptation in population genomic divergence. We first derived the climatic variables associated with the geographic distribution of 24 populations across two continents to trace the scale of environmental variation experienced by the species, and measured variation in the cold tolerance of the flies of six populations from different geographic contexts. We then performed pooled whole genome sequencing of these six populations, and used Bayesian methods to identify SNPs where genetic differentiation is associated with both climatic variables and the population phenotypic measurements, while controlling for effects of demography and population structure. The top candidate SNPs were enriched on the X and 4th chromosomes, and they also lay near genes implicated in other studies of cold tolerance and population divergence in this species and its close relatives. We conclude that ecological adaptation has contributed to the divergence of D. montana populations throughout the genome and in particular on the X and 4th chromosomes, which also showed highest interpopulation FST. This study demonstrates that ecological selection can drive genomic divergence at different scales, from candidate genes to chromosome-wide effects.

evolutionary biology↗