Ecology Letters

Knowledge of species interactions unlocks our understanding of how ecological communities respond to climate change or habitat loss, explaining their resilience and robustness. Such knowledge requires inferring the presence, sign, and per capita strength of species interactions, as well as species intrinsic growth rates. While various studies have attempted to infer these parameters in isolation, none have successfully inferred them simultaneously. Here, we solve this grand challenge using an integrative approach combining ecological mechanistic models and statistical inference to simultaneously infer these parameters across time, capturing environmental variation and seasonality. We validate our approach on synthetic data in constant and changing environments, highlighting its ability to detect high-probability weak interactions - the key contribution of our method, and proving our ability to detect environmental changes. Applied to empirical data, it recovers the expectations from biological knowledge and unveils network rewiring. Our approach takes one step further to bridge the gap between mechanistic models and empirical ecology. It advances the understanding of ecological networks and their dynamics, thereby helping to validate existing hypotheses, spark new theories, and help guide ecological management and conservation.

The Biodiversity-Ecosystem Functioning (BEF) literature has shown species diversity to be essential for ecosystem functioning and services. Yet although acquiring information through interspecific networks can impact ecosystem functioning, it is unclear how it is modulated by species diversity. Eliciting vocal responses using predator models across a latitudinal gradient, we first show that the species diversity of birds increases public information about predation both in the low-cost system of mobbing and in the higher-cost system of alarm calls. A similar result was also found across a fragment area gradient for mobbing; this system was then used to test how species diversity affects interspecific information flow in mobbing communities. We set up two BEF playback experiments, manipulating the species richness level of the playback sound files by varying the number of species producing mobbing calls (one, two, four, eight species). In an experiment in which the call rate across treatments was held constant, and only heterospecific responses were counted, increasing species richness of the sound files increased the number of species and individuals responding, the number of calls produced and their frequency range, and decreased latency to call. An experiment in which call rate increased with the addition of species in each treatment showed a similar, but stronger pattern. There was little evidence that the signals of one particular species changed responses. This supports the hypothesis that the species diversity of a community is a key component influencing the quantity and quality of information flow inside it.

Theory predicts that demographic performance should peak at the core of species ranges and decrease toward their limits. Yet, empirical correlations between population growth rate and species distribution remain weak for most tree species. Part of the problem may arise from the difficulty of integrating multiple demographic processes across the complex life cycle of a forest, and from the significant variability among individuals and locations. It remains unclear if the mismatch between performance and distribution arises from modelling limitations or if climate is simply a poor predictor of species performance across distributions. Here, rather than asking whether demographic performance correlates with species distributions, we ask how climate and competition jointly shape population growth rate for 31 tree species across eastern North America. By combining flexible nonlinear hierarchical models for growth, survival, and recruitment with explicit uncertainty propagation, we use Integral Projection Models to address key gaps in previous studies. Perturbation analyses revealed that population growth rate was consistently more sensitive to mean annual temperature than to conspecific or heterospecific competition across all species. We further examined how sensitivities to climate and competition varied across species thermal ranges. The dominance of climate over competition increased toward both cold and hot range limits, while sensitivity to competition generally declined from cold to hot limits. Notably, these patterns emerged along the continental thermal gradient shared across species rather than within each species individual range, suggesting that range-edge demographic responses may arise as a community-level phenomenon. Across species, the largest source of variability remained the local plot conditions captured by random effects, likely reflecting differences in soil conditions, drainage, and disturbance history. Together, these results may provide a mechanistic pathway underlying the performance declines predicted by range-limit theories, and offer a basis for understanding how forest populations and communities may reorganize in response to ongoing climate change and shifting disturbance regimes.

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.

Natural populations are often nonlinear and exhibit substantial variability. A central question is how stochasticity interacts with density-dependent regulation to shape population stability. We address this using four long-term time series of Trinidadian guppies and find that their dynamics are well described by a stochastic logistic model with multiplicative environmental noise. The model predicts that stochasticity does not merely add fluctuations around deterministic carrying capacity, but alters the equilibrium structure. Using stochastic bifurcation theory, we show that increasing noise shifts the most-probable population size below the deterministic equilibrium and can push populations closer to a noise-induced bifurcation, even when mean growth rates remain positive. The effects of stochasticity across populations align with known ecological differences among streams, particularly the effects of light level and seasonality. The analysis also identifies populations most sensitive to perturbations, which are not detected by standard early warning indicators. Temporal and spectral analyses further show that intrinsic growth rate governs local recovery, while seasonal variation interacts with density-dependence to shape longer-term population fluctuations. Together, our results show that stochasticity can alter resilience and vulnerability by reshaping ecological stability landscapes.

Minimum viable populations (MVPs) are population levels large enough to surmount risk from demographic, environmental, and genetic stochasticity. MVPs are estimated by biologists to guide conservation practices. However, MVPs are generally estimated for a target population without regard for how they interact with intra- and inter-species population dynamics in the broader ecological community. Thus, how and why population dynamics interact with MVPs imposed by conservation biologists remain unclear. When MVPs are imposed on a continuous population model, traditional analyses fail to capture the range of possible outcomes those MVPs create. Here, we describe viability space decomposition (VSD) as a mathematical tool to systematically analyze the potential crossing of MVPs during population dynamics. We demonstrate that different extinction and survival outcomes can be recovered from a model with imposed MVPs using three VSD concepts in junction with a traditional phase portrait: mortality manifolds which separate conditions that lead to different existential outcomes, ordering manifolds which determine the order of extinction events for multiple populations, and collapse manifolds which determine the survival or extinction of one species given the loss of another. We employ these methods with a standard consumer-resource model, and the methods can be scaled to systems with more species. VSD is a useful tool for conservation biologists and community ecologists concerned with boundary crossing problems in any dynamical system.

Plankton are essential to marine ecosystems, supporting food webs and mediating biogeochemical processes such as carbon export to depth. Their spatial distribution influences ecosystem dynamics and serves as an indicator of environmental change. Although drifting plankton could be expected to exhibit random distribution, numerous studies have revealed significant heterogeneity in their spatial patterns. However, very few studies targeted plankton distribution at the centimeter scale in situ, despite its importance for understanding biological processes. We argue that centimeter-scale distances in plankton could reveal potential ecological interactions. Using an extensive in situ dataset of 18 million planktonic organisms collected by the In Situ Ichthyoplankton Imaging System (ISIIS), which images multiple organisms simultaneously and preserves their positions in the water column, we analyzed centimeter-scale distances in plankton. By comparing observed distances with those expected under a random distribution, we assessed potential interactions at three levels: among all organisms, within plankton groups and across groups. Our results show that planktonic organisms exhibit non-random distributions at the centimeter scale, with smaller distances than expected, suggesting potential ecological interactions. Notably, distances up to 11 cm were the most informative, which is much larger than typical interaction distances in plankton. Additionally, observed distances were compatible with a simple attraction model. Finally, we propose the non-randomness of distances as a novel metric of interaction strength in plankton ecological networks and compare it against classical empirical or co-occurrence networks. These results offer new insights into in situ interactions and how they shape plankton distribution at centimeter scale. Significance statementThis study reveals that planktonic organisms exhibit non-random spatial distributions at the centimeter scale, highlighting the importance of ecological interactions in shaping their distribution at this scale. By analyzing an extensive in situ plankton imaging dataset, we introduce a novel metric of interaction strength based on the non-randomness of distances between organisms, and compare it to common interaction metrics. These findings challenge the traditional view of plankton as passive drifters by highlighting that their distribution at microscale is shaped not just by physical processes such as turbulence but also by ecological interactions. Author contributionsJOI contributed to data acquisition. TP processed the data under the supervision of JOI. TP, JOI and BBC designed the study. TP conducted the analyses under the supervision of MF, JOI and BBC. TP wrote the initial draft of the manuscript. All authors contributed to the interpretation of results, supported manuscript preparation and approved the final submitted version.

A central challenge in characterizing species niches is ensuring that foraging data accurately capture both the resources used and their relative importance, and the role of resource abundance in shaping foraging patterns. Most studies infer diet breadth and resource-use patterns from observational records, yet such data can mask resource-specific decisions when animals forage with different goals. Here, we test this experimentally using individually identifiable bees in controlled resource communities to quantify foraging decisions between nectar (for sustenance) and pollen (for offspring provisioning). Combining observations, pollen DNA metabarcoding, and pollen microscopy, we show that observed visitation patterns misrepresent the floral resources most important for offspring provisioning, which ultimately determines offspring survival and population persistence. We further show that interaction patterns are structured from processes beyond resource abundance. Our results demonstrate that commonly used observational approaches can mischaracterize diet breadth, potentially challenging conclusions about species generalization.

Biodiversity is commonly summarized by macroecological mean patterns, most prominently the species-area relationship (SAR) linking habitat area to expected species richness. Yet conservation, policy, and economic decisions increasingly require risk metrics: probabilities of rare but consequential biodiversity shortfalls, including local collapse. Such tail risks are central in finance and insurance but remain difficult to quantify in ecology because the data needed to estimate full richness distributions are rarely available at decision scales. Here we provide a mechanistic route from species-area relationships to biodiversity risk metrics. We show that when regional species abundances are well approximated by Fishers log-series, a minimal immigration-extinction mechanism yields a closed-form stationary distribution for local richness whose structure tightly couples the mean SAR to richness variability and lower-tail probabilities. This coupling implies exact fluctuation-response identities and an explicit integral transform that reconstructs collapse probabilities and other tail risk measures directly from the mean SAR. These results define ecological analogues of financial risk metrics--such as collapse probability and lower-tail quantiles--without requiring direct estimation of the full richness distribution. Using high-resolution ForestGEO tree censuses spanning tropical, subtropical, and temperate forests, we find empirical support for these predictions across spatial scales. Together, our results show how widely measurable species-area relationships can be elevated from descriptive averages to operational tools for biodiversity risk assessment and reliability-based conservation planning.

Regeneration failure is a bottleneck in Mediterranean oak woodlands. Cattle can hinder or promote recruitment, depending on grazing location, timing and intensity. Herbivory theory predicts that repeated defoliation and trampling deplete seedling reserves, whereas resprouting can extend survival; yet field studies rarely separate intensity from recency or combine long-run grazing records with individual fates and microhabitat/climate context. We test how management-driven heterogeneity shapes cork oak seedling survival and resprouting by combining 12 years of paddock-level grazing records with individual tracking of 8431 seedlings across 24 paddocks. Bayesian mixed-effects survival models related seedling lifespan to grazing history x pressure (moderate [≤]150; high >150 LSU ha-1 days yr-1) and to key covariates, including seedling height, resprouting status, shrub distance, cattle dung counts (as a proxy of very recent grazing), and 1-month SPEI (as recent water balance). Bayesianlogistic mixed models were then used to relate resprouting probability to grazing treatments. Survival was lower in grazed than ungrazed paddocks and declined along management gradients: median lifespan fell from 460 (moderate grazing) to 256 days (high), and from 460 (old grazing; two-year absence) to 199 days (recent). A two-year cattle absence increased survival under moderate pressure but was insufficient where pressure was high, indicating legacy effects and that recovery windows must scale with pressure. Resprouting dominated persistence: resprouters lived >5x longer than non-resprouters (2351 vs 460 days). Taller seedlings lived longer, and shrub proximity conferred a modest benefit. Climate modulated outcomes: wetter recent periods (higher SPEI) markedly boosted survival. Cattle reduced the odds of resprouting, with the strongest penalty under recent use. By disentangling grazing intensity from recency and linking both to seedling survival and resprouting, we show why recruitment falters under continuous, heavy grazing and when it can recover. Because drought intensifies cattle impacts, managers should combine moderate stocking rates with multi-year rest periods to rebuild oak bud banks and below-ground reserves; a two-year hiatus can help under moderate pressure but appears insufficient where pressure is high. Aligning rotational plans with drought outlooks and tracking simple field cues (seedling height, recent resprouting) offers a practical path to reconcile production with regeneration in Mediterranean wood-pastures. HighlightsO_LITwelve years of grazing records linked to 8431 cork oak seedling fates C_LIO_LIRecent grazing reduced survival and resprouting versus a two-year cattle absence C_LIO_LIHigh grazing shortened lifespan; two-year rest helped only under moderate pressure C_LIO_LIResprouting was the strongest survival correlate; resprouters lived over 5x longer C_LIO_LIWetter short-term water balance increased cork oak seedling longevity C_LI

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.

Oxygen limitation is a widespread environmental constraint that shapes physiological and evolutionary responses across ecosystems. A central unresolved question is whether tolerance to hypoxia reflects generalized stress responses or coordinated regulatory strategies shaped by long-term environmental exposure. Here, we use comparative transcriptomic analyses to examine gene expression responses to low oxygen in two aquifer-dwelling stoneflies (Isocapnia sp. and Paraperla frontalis) and one benthic species (Sweltsa sp.) under controlled conditions. Time-series analysis in Isocapnia sp. revealed a multi-phase transcriptional response involving early regulatory activation, metabolic reorganization, and late-stage cellular stabilization. Across aquifer taxa, hypoxia was associated with downregulation of energy-demanding processes and upregulation of pathways related to oxidative stress mitigation, metabolite transport, and protein folding, consistent with coordinated cellular adjustment to oxygen limitation. In contrast, the river benthic species exhibited transcriptional profiles dominated by neural signaling, ion channel activity, and structural remodeling, which are patterns consistent with acute physiological stress rather than coordinated regulation. Despite these differences, all taxa showed modulation of ion transport and calcium signaling pathways, suggesting conserved mechanisms of hypoxia sensing. Together, these results indicate that transcriptional responses to hypoxia differ systematically with habitat and are consistent with the evolution of distinct regulatory strategies in chronically hypoxic environments. Significant statementOxygen limitation is a common environmental challenge that affects organisms across aquatic and terrestrial ecosystems, yet the mechanisms by which species cope with low oxygen remain incompletely understood. A key question is whether tolerance to hypoxia reflects common stress responses or the evolution of coordinated metabolic regulatory strategies under chronic exposure. By comparing gene expression responses in closely related aquatic insects from oxygen-variable underground aquifers and oxygen-rich river habitats, we show that species that evolved under persistent hypoxia exhibit transcriptional patterns consistent with energy conservation and cellular stabilization, whereas those experiencing hypoxia as a transient stress display signature of physiological disruption. These findings highlight fundamental differences between evolutionarily adaptive and acute stress-driven responses to environmental change and provide insight into how organisms may respond to increasing hypoxia under global change.

A recurring question across biological systems is when gains accrued by one part of a system also benefit the whole, and when they instead impose a collective cost. In ecological communities, consumers can increase their energetic gains through trophic interactions, yet those same interactions also determine whether all species persist. Here we show that food-web architecture governs whether predator advantage supports collective persistence, and that omnivory is a key condition under which the two diverge. Using a Lotka- Volterra-type food-web model formulated in terms of energy fluxes, we compare predator output power with the probability of feasibility, which quantifies the range of growth conditions compatible with positive coexistence. In two-species systems, these objectives show no generic alignment. In trophic chains, by contrast, increasing encounter rates makes predator advantage and coexistence mutually reinforcing. Basal omnivory reverses this pattern by shifting the power optimum towards the boundary of coexistence, where the intermediate consumer is lost. This pattern persists in larger networks, under heterogeneous encounter rates, and with saturating functional responses. Our results identify food-web architecture as the determinant of whether local energetic advantage scales up as collective persistence or instead becomes a coexistence cost.

Darwinian fitness is equated here with invasion fitness and defined as the quantity determining the fate--certain extinction or possible spread--of a single mutant type. We derive it, together with its phenotypic derivative, for evolution in group-structured populations under limited genetic mixing, where the demography of the focal species and its environment is modeled as a discrete-time stochastic process. Reproduction, physiological development, dispersal, and survival are influenced by interactions within and between groups and by environmental fluctuations within and across generations. Using multitype branching processes in random environments, we show that invasion fitness is predicted by a stochastic growth rate that can be represented biologically in two meaningful genealogical ways. First, as the long-term geometric mean of the expected per-capita number of mutant copies produced per time step by a representative member of the mutant lineage. Second, as the the long-term geometric mean of the expected reproductive-value-weighted per-capita number of mutant copies produced by such an individual. This latter representation is useful for computing the phenotypic directional derivative of invasion fitness. Moreover, this derivative can be written as an actor-centered inclusive-fitness effect derived from properties of the resident population process. This effect depends on class-specific fitness differentials, relatedness, reproductive values, and class frequencies. However, unless generation- and class-specific fitness defines a stochastic matrix, the derivative does not separate stochastic reproductive values from relatedness and class frequencies, and must be evaluated by simulations. In summary, we formalize invasion fitness biologically quite generally and show how Hamiltons marginal rule is deduced from it.

Global epistasis refers to the observation that the effect of a mutation or modification depends on the state of a biological system, not its detailed composition. Such patterns have been reported across biological scales, from proteins to organisms and ecosystems. In its simplest form, global epistasis appears as a linear relationship between the change in function or fitness due to a perturbation, and the background level of function or fitness. The mechanistic basis of global epistasis, particularly in ecological systems, remains unresolved. Here, we propose that in microbial communities, global epistasis describing the impact of adding a species to a community on function arises generically from constraints imposed by shared resource pools. We illustrate this mechanism in a single-species system growing on multiple substitutable resources, where global epistasis follows directly from nutrient limitation by an essential non-substitutable resource. We then extend this framework to multi-species communities competing for a single resource and show that the marginal effect of adding a species depends linearly on background community function, with a slope determined by the fraction of the resource claimed by the added species. We show that global epistasis persists in trophic cascades, but that facilitation and niche partitioning qualitatively break the linear dependence. This study provides a simple explanation for the appearance of global epistasis in ecosystems, and suggests that global epistasis should be a null expectation in ecosystems governed by competition. Our results propose that coupling between perturbations and shared resource pools might also help explain global epistasis at the organismal level.

Existing theory examining the coevolutionary dynamics of species range borders assumes random dispersal, which causes maladaptive gene flow from the range core to the range margins and contributes to the formation of range limits. However, dispersal is unlikely to be random for many organisms in nature, calling into question existing theoretical predictions. For example, if individuals exhibit phenotype-dependent adaptive dispersal strategies such as matching habitat choice, then the resulting adaptive gene flow toward species range margins could facilitate range expansions and potentially prevent the formation of range limits by interspecific competition. To test this idea, we use a comprehensive mathematical model to develop a quantitative theory of range border coevolution that incorporates phenotype-optimal dispersal--a particular form of matching habitat choice in which individuals follow the gradient in an environmental optimum phenotype to settle in the habit best suited for their phenotype. We find that instead of preventing competitively formed range limits, adaptive dispersal leads to sharper range limits and reduced character displacement in sympatry. These differences are particularly remarkable when natural selection is weak, when individuals are specialized in their resource use, or when individuals are highly sensitive to environmental conditions. We show that matching habitat choice causes backward edge-to-core movements which dynamically interact with the effects of interspecific competition to establish the range limits. Thus, the formation of range limits by interspecific competition is robust to assumptions about individual dispersal. Further, our results identify the competitive advantage of evolving matching habitat choice in steep environmental gradients, especially for slowly-growing species in rapidly fluctuating climates.

Winter can affect animal population dynamics by limiting resource availability and increasing energetic costs of movement caused by deep snow. Given the rapid alteration of snowpack properties due to climate change, quantifying how snow characteristics influence reproduction and physical condition is critical. We evaluated how snow cover duration, depth, and density affect spring body mass, reproduction probability, and subsequent autumn body mass of bighorn sheep (Ovis canadensis) using 45 years of individual-based data at Ram Mountain, Alberta, Canada, along with historical snow records reconstructed via the SNOWPACK model. Using Bayesian structural equation modeling, we quantified the direct and indirect effects of snow across different sex and age classes. Long and deep snow covers reduced spring body mass across all demographic groups, with yearlings, especially males, losing up to 0.12 kg per additional cm of snow depth. Harsh snow conditions reduced the probability of reproduction for adult females and generated a compensatory indirect effect on mass by avoiding the energetic costs of reproduction. In contrast, yearlings showed no compensatory responses and entered the following autumn in poor condition (up to 14% lighter for males and 8% for females following the deepest snow years). The impact of snow density on autumn mass of adult males was density-dependent, shifting from beneficial at low density (+0.09 kg per kg/m3) to detrimental at high density (-0.04 kg per kg/m3). The effects of snow conditions generate persistent, context-dependent carry-over effects across seasons. Our study suggests that distinct demographic groups rely on different mechanisms to cope with environmental constraints, highlighting complex, time-lagged consequences of changing winter climate on alpine herbivore populations.

Sexual selection is a major evolutionary force, yet its demographic consequences remain unclear. While experimental studies often report positive effects of sexual selection on traits linked to population performance, comparative studies often find null or negative associations with population persistence. One explanation for this discrepancy is that the demographic consequences of sexual selection depend on ecological context, particularly variation in mortality and fecundity. Here, we used six decades of abundance data and test whether sexual selection predicts population trends across 738 bird species from Europe and North America. We quantify sexual selection using complementary proxies capturing different components of sexual selection: mating system, sexual dichromatism, sexual size dimorphism and relative testes mass. We further assess whether the effect of sexual selection in population trends is mediated by mortality and fecundity. Across all proxies, we found no evidence that sexual selection is associated with population trends. This result is consistent across continents and robust to variation in mortality and fecundity. Our findings suggest that, despite its central role in shaping phenotypic evolution, sexual selection does not translate into consistent effects on long-term population trends at macroecological scales. More broadly, these results highlight a potential disconnect between evolutionary processes and population dynamics.

Global changes in land use and nutrient cycling are transforming ecosystems at unprecedented rates, with significant consequences for infectious disease dynamics. Aquatic environments are particularly vulnerable because the interplay of habitat modification, nutrient enrichment, and biodiversity loss can drive pronounced changes in the community composition of food webs, including hosts and parasites. Yet, despite well-documented effects of habitat modification on aquatic communities and food webs, the mechanisms through which these changes influence infectious disease dynamics remain poorly resolved. This gap arises, in part, because it remains challenging to disentangle how multiple stressors interact to shape disease outcomes and quantify parasite levels and host densities from field-collected samples. Here, we illustrate two tools that might help address these challenges. First, highly sensitive droplet digital PCR can quantify infection loads even when the signal:noise ratio is low. Second, stepwise Bayesian path analyses can identify the direct and indirect pathways connecting land-use changes to infectious disease dynamics. As a case study, we examined cyclopoid copepods and their helminth parasite, Schistocephalus solidus, across 47 freshwater lakes on Vancouver Island, a region strongly shaped by commercial logging, including widespread clear-cutting of old-growth forests. Our results reveal a positive correlation between copepod density and deforestation, potentially mediated by associated changes in water quality and calanoid copepods, key competitors of the focal host. ddPCR enabled sensitive detection of extremely low parasite signals in field-collected copepods. We detected positive infections in only 19.5% of the lakes surveyed, highlighting the difficulty of assessing disease dynamics in natural populations. Nonetheless, this study highlights the challenges of linking land-use change to disease outcomes, while also demonstrating that sensitive molecular and statistical tools offer new ways to reveal these hidden connections.

ContextAnimals balance resource acquisition with risk mitigation. These trade-offs are rarely uniform, being mediated by spatial scale, demographic traits, and environmental constraints. Understanding these divergent spatial behaviors is critical for management across human-dominated landscapes. ObjectivesWe investigated how sexual dimorphism and ontogeny interact with landscape structure to influence scale-dependent resource selection. Specifically, we sought to determine how these demographic factors mediate spatial trade-offs between optimal foraging habitats, top-down intraguild predation risk, and bottom-up severe winter weather. MethodsWe examined the spatial ecology of a solitary carnivore, the bobcat (Lynx rufus), across a heterogeneous, human-modified landscape in northern Minnesota, USA. Using spatial data derived from harvested adult and juvenile individuals, we evaluated multi-scale selection relative to land cover, structural ecotones, intraguild predator activity, and winter severity. ResultsHabitat selection was scale-dependent and partitioned demographically. Whereas bobcats universally selected for ecotones and avoided homogeneous open habitats at fine scales, responses to other features diverged by sex and age. Females actively avoided areas with high coyote activity and freezing temperatures; males exhibited high risk tolerance, apparently indifferent to coyote activity and tolerant of freezing temperatures. We identified a distinct ontogenetic spatial shift among females. Subordinate juveniles were competitively excluded from optimal natural ecotones, forcing them into riskier, anthropogenic agricultural edges. In contrast, adult females optimized foraging opportunities by selecting productive ecotones at the intersection of woody vegetation and semi-natural grasslands. ConclusionsOur findings demonstrate that habitat selection is not a static species-level trait, but instead a dynamic process resulting from the interaction between ontogeny, sex, and landscape heterogeneity. The reliance of vulnerable demographic groups on marginal or anthropogenic habitats highlights how human land-use changes can inadvertently produce ecological winners and losers within the same species. Consequently, landscape management and conservation planning for solitary carnivores must shift from broad, population-wide habitat prescriptions to strategies that explicitly accommodate the divergent spatial requirements of specific demographic cohorts.