Ecology

Biological rates, like growth, tend to have unimodal (hump-shaped) responses to temperature, and these relationships can vary among species and biological processes. In most systems, full thermal performance relationships are rarely characterized for interacting species (e.g., consumer-resource or host-pathogen pairs), making it challenging to predict how their interactions, and subsequently, how communities, will shift with climate change. We investigated how the thermal responses of eelgrass (Zostera marina, an important marine foundation species in the N. hemisphere) and an isopod grazer (Pentidotea resecata), which putatively acts as an indirect vector of eelgrass wasting disease, interact to affect eelgrass productivity and wasting disease dynamics. In a laboratory experiment crossing five temperatures, two grazing, and two disease exposure treatments, across various metrics, eelgrass growth responded unimodally to temperature in the absence of grazers. Grazers depressed plant growth and flattened its thermal performance curves. Thermal performance curves for isopods indicated that increases in grazing and survival at intermediate temperatures negated concurrent gains in plant growth at these temperatures, while decreased isopod survival at high temperatures reduced their top-down effect on eelgrass. Isopods had negligible effects on plant disease responses, but warming reduced the time to disease onset and increased final disease severity. Overall, whole-plant disease severity remained low and did not substantially affect eelgrass leaf elongation, net growth, or rhizome dry mass. However, disease-treatment plants grew more new leaves at intermediate temperatures, possibly to combat losses in photosynthetic capacity in diseased leaf tissue. These results indicate that climate change-associated warming will likely increase eelgrass vulnerability to wasting disease. However, in sublethal outbreaks, disease could have less of an impact on eelgrass productivity than warming-induced increases in grazing. Thus, ignoring grazer responses to temperature could result in unreliable predictions of eelgrass productivity under climate change.

Mortality-inducing disturbances are important, ubiquitous drivers of community composition and function. Importantly, human activities and climate change are increasingly altering disturbance regimes. Most disturbance studies focus on the effects of current disturbance regimes, rarely considering those of historical regimes. However, recent theoretical work predicts that historical regimes can leave persistent legacies, modulating the communitys response to novel disturbances and invasive species. Here, we complement this theoretical approach using a model bacterial system that experienced disturbance regimes for [~]120 generations, followed by novel regimes and invasions for another [~]120 generations. Our results show persistent effects of historical legacies on disturbance-diversity relationships. Furthermore, some combinations of past and novel regimes promote invasion with increasing resident diversity, while others prevent it; legacies may explain conflicting diversity-invasibility relationships. These findings demonstrate the importance of historical legacies in disturbance-prone ecosystems, and underscore the challenges in predicting future community responses to disturbance regime changes.

O_LIForests are vertically structured ecosystems where light attenuation, microclimatic buffering and resource availability occur along continuous gradients from the canopy to the understorey layers. Despite this complexity, studies rarely integrate trophic interactions across vertical layers, overlooking how vertical forest structure shapes consumer communities through abiotic and biotic pathways. C_LIO_LIIn this study, we combined layer-specific measurements of plant diversity, structure and microclimate with arthropod sampling in the canopy and understorey, as well as bird survey data, in a temperate forest. Applying Bayesian structural equation models with explicitly defined directional pathways, we modelled both consumer biomass and abundance across trophic levels and vertical layers. C_LIO_LIAbundance measures were predominantly filtered by local layer conditions, while biomass responded to conditions across layers, reflecting stand-level energy flow. This suggests that these two metrics capture fundamentally different ecological processes. Canopy conditions consistently predicted understorey arthropod abundance across trophic levels, while the reverse was not observed, suggesting a strong asymmetric downward propagation of canopy-driven effects. Furthermore, trophic interactions between arthropod primary and secondary consumers remained largely stratified within vertical layers, suggesting a vertical food web compartmentalisation rarely shown in structurally complex aboveground systems. C_LIO_LIPlant diversity, structure and microclimate shaped consumer communities mainly through the modulation of resource availability and plant apparency, with effects varying across vertical layers, trophic levels and taxonomic groups. Through complementary mechanisms, plant diversity likely determined the variability of resources available to consumers at different trophic levels. Structural properties, in contrast, potentially drove the spatial redistribution of these resources through light attenuation and microclimatic buffering, which in turn influenced the physiological capacity of consumers to access and exploit available resources. C_LIO_LIThese findings demonstrate that vertical stratification mediates trophic pathways in a highly directional manner, with canopy characteristics playing a disproportionate role in structuring the forest community across layers. Integrating layer-specific structural and trophic indicators into forest biodiversity assessments and management strategies is therefore essential to fully evaluate biodiversity dynamics and multifunctionality in structurally complex forest ecosystems. C_LI

Determining the drivers of ecological stability amid accelerating global environmental change is a critical goal of contemporary ecology. Various candidate drivers have been suggested, with recent attention turning to response diversity--the variation among organism-environment responses. However, despite conceptual interest in response diversity as a driver of stability, there remain few field tests of this relationship. Using multi-species competitive communities of floating aquatic macrophytes as an experimental model for measuring temporal stability and response diversity to nutrient loading, we show that response diversity does not promote temporal stability of total macrophyte cover, but that communities with an uneven distribution of species responses were more resistant to an exogenous shock. To quantify macrophyte composition and growth dynamics from photographic time series of our experimental communities, we developed an open-source, scalable, machine learning workflow (LeafMosaic) capable of classifying four species from noisy field data including variable lighting, resolution, and plant morphology. We measured response diversity as the balance of positive and negative biomass growth responses to dissolved nitrate concentration, weighted by species relative contributions to biomass, and tested its effect on temporal stability and resistance to an unexpected pulse disturbance (a large typhoon that disrupted our outdoor mesocosms). Response imbalance predicted typhoon resistance, but species asynchrony and mean population stability best predicted community stability, with no direct or indirect effect of species responses. Overall, our results provide new experimental evidence for how the structure of species responses promotes stability, and we aim our LeafMosaic workflow to empower future field experiments using floating macrophytes to study response diversity and ecological stability.

1Ecosystem functioning can be maintained in species-rich communities even under fairly severe perturbations. This is because communities with high richness include variation both in species functional roles (functional diversity) and in their responses to environmental changes (response diversity). Response diversity has been proposed as a key mechanism underpinning the stabilising role of biodiversity in variable environments. However, less understood is the role of response diversity in stabilising communities against perturbations and thus preserving ecosystem function. Here, we employ community data from 76 reservoirs across the broad latitudinal gradient of the Japanese archipelago to show that zooplankton assemblages with higher variability in responses to environmental variables can retain functional diversity as species are removed, but that the result depends on the variable examined. We combine empirically derived occurrence data for 47 zooplankton species with biotic and abiotic variables in a joint species distribution model to derive species-specific environmental responses, then measure response diversity to environmental axes including fish community structure and water temperature. We also measure functional trait diversity of zooplankton assemblages and simulate sequential species extinctions, capturing the extinction thresholds beyond which half the functional diversity is lost. Finally, we combine these data streams to show that response diversity can predict higher functional robustness in zooplankton assemblages, but not consistently. The role of response diversity in predicting functional robustness was contingent on the specific metric and environmental variable considered. We found that a balance of positive and negative species responses to water temperature was a significant predictor of robustness, though other metrics and environmental variables mainly yielded non-significant relationships. Overall, we show that response diversity can confer stability to perturbations such as species extinctions, and we demonstrate the utility of species distribution models for measuring response diversity, overcoming mechanistic data limitations and expanding the toolkit available for studying response diversity in natural systems.

Identifying optimal grazing intensities for sustainable population growth is crucial for informing management strategies. Community-level studies frequently find that biodiversity peaks at intermediate grazing intensities, known as the Intermediate Disturbance Hypothesis. However, whether this hypothesis applies to population-level performance remains untested. Our stochastic integral projection models, parameterized with five-year demographic data of two co-occurring species, Morina chinensis and Deyeuxia flavens, on the Tibetan Plateau grasslands., indeed show a hump-shaped response in stochastic population growth rate ({lambda}S) to grazing intensities, providing empiral support for the Intermediate Disturbance Hypothesis at population level. Furthermore, populations with demographic compensation among vital rates are better able to buffer temporal variation in annual population growth rate and exhibit a much smaller decline in {lambda}S under heavy grazing. Our study provides mechanistic insights into demographic processes driving population dynamics across grazing levels, thereby better informing grazing management strategies.

Investigating the factors that stabilize biological communities is a central topic in ecology. Response diversity, defined as variation in species responses to environmental change, has been proposed as a key mechanism underlying the biodiversity-ecosystem functional stability (BEFS) relationship, whereby greater species diversity enhances ecological stability. Previous studies have shown that response diversity promotes ecological stability by generating asynchronous population fluctuations and the resulting compensatory dynamics. Although several metrics have been proposed to quantify response diversity, they do not explicitly consider the presence of insensitive species whose performance is unaffected by current environmental conditions. To examine how insensitive species influence response diversity, species persistence, and ecological stability, we conducted numerical simulations of a generalized Lotka-Volterra model under environmental forcing. We first confirmed that increasing variation among sensitive species increased the response diversity index and stabilized community dynamics. We then examined a scenario in which response diversity depended solely on the proportion of sensitive and insensitive species, assuming that all sensitive species responded identically to environmental change. Under this assumption, the response diversity index was maximized when sensitive and insensitive species occurred in equal proportions, whereas increasing the number of sensitive species monotonically destabilized community dynamics. Consequently, the relationship between response diversity and community stability depended on how response diversity was generated, such that higher response diversity could even be associated with lower community stability. These findings demonstrate that overlooking environmentally insensitive species can obscure the mechanisms linking response diversity and ecological stability. More broadly, our results reveal that response diversity comprises at least two distinct biological components--species sensitivity and response variation among sensitive species--that can have contrasting consequences for community stability. We therefore highlight the need to quantify sensitive species empirically and to develop response diversity metrics that distinguish these components. Author SummaryUnderstanding why some communities remain stable despite environmental change is a longstanding goal in ecology. Response diversity, which refers to differences in how species respond to environmental change, has been proposed as a key mechanism explaining why greater biodiversity (species richness) can promote ecological stability. Because species respond differently to changing environments, declines in some species can be compensated by increases in others, helping to stabilize community dynamics. However, previous studies have rarely considered species that are insensitive to current environmental changes. Using a mathematical model, we show that response diversity can arise from two distinct biological components--the number of sensitive species and variation in their responses--and that these components can have contrasting effects on ecological stability. When response diversity reflects variation among sensitive species, greater response diversity stabilizes community dynamics, as expected. In contrast, when response diversity changes only because of the proportions of sensitive and insensitive species, higher response diversity can be associated with lower community stability. Our findings highlight the importance of quantifying the number of sensitive species and developing response diversity metrics that distinguish species sensitivity from variation in responses among sensitive species.

Many species of animals undergo senescence, impacting predator-prey relationships, yet how senescing prey adjust their risk-taking behavior is poorly understood. We used integrated step selection analysis to quantify risk-taking from empirical data. A graphical framework of age-dependent adaptive risk-taking predicted - and our empirical analysis found - a reduction in female elk (Cervus canadensis) risk-taking with age toward wolves (Canis lupus) but not cougars (Puma concolor), underscoring the role of predator hunting mode in ecological dynamics. We estimated average risk-taking toward wolves would be 42% lower in a population with median age 10 versus 4 years, highlighting how a prey populations age structure likely impacts risk-induced trait responses and the potential emergence of predation-risk effects. Our findings suggest that altered risk-taking may be an adaptive behavioral shift rather than a passive consequence of physical decline. Such adaptive changes to risk-taking may represent an underappreciated link between individual behavior and community-level coexistence.

The exchange of energy and organisms across habitat boundaries links aquatic and terrestrial ecosystems and sustains ecosystem functioning. Although disturbance may disrupt these linkages, the mechanisms at play remain poorly understood. Here, we investigated the extent to which flow intermittency may disrupt riparian-aquatic ecosystem linkages by altering consumer communities in the recipient ecosystem or by altering resource quality in the donor ecosystem. We ran an experiment in an intermittent river network in California, focusing on a critical forest-to-river subsidy (organic matter in the form of leaf litter), its transformation, and its reciprocal benefit (aquatic insect production). Using three riparian species (willow, cottonwood, and oak) at sites spanning a gradient of flow permanence, we quantified intraspecific plasticity in leaf traits (specific leaf area, nitrogen and phosphorus concentrations, and {delta}13C), measured decomposition rates, and estimated the secondary production of aquatic shredders (Plecoptera). Across all leaf species, decomposition rates were 16-36% lower at intermittent than perennial sites, an effect largely driven by intraspecific leaf trait plasticity rather than changes in consumer abundance. At high flow intermittency, willow experienced water stress (enriched {delta}13C) and reduced specific leaf area, while cottonwood showed primarily stoichiometric responses (reduced leaf nitrogen and phosphorus). Despite these divergent strategies, all species produced lower-quality litter at intermittent sites. Variance partitioning confirmed that initial litter quality uniquely explained 51.5% of variation in decomposition rates, more than double the contribution of invertebrate community metrics; and structural equation modeling revealed that both leaf traits and stonefly (Plecoptera) secondary production significantly predicted decomposition rates, with leaf traits exerting the stronger effect. Notably, stonefly secondary production was 37-98% lower at intermittent sites across leaf species. Because these insects later emerge as terrestrial adults, they provide a significant energy flux to riparian predators, and, thus, impoverished litter quality suppresses the reciprocal transfer of energy back to terrestrial food webs. As drought intensifies globally, the decoupling of terrestrial-aquatic linkages may begin in the riparian canopy.

Disentangling causation from correlation is the foundation of the scientific method. Yet, growing evidence suggests that much observational ecology research has not correctly made this distinction due to inappropriate statistical modelling and unappreciated time-delays. Here, we apply time-lagged causal inference techniques to assess the drivers of seabird declines, using multi-decadal North Atlantic seabird data across the behaviour, mass, survival, reproduction and population size of two species ecology (Atlantic puffin, Fratercula arctica, and black-legged kittiwake, Rissa tridactyla). We demonstrate that both climate and anthropogenic activity can suppress breeding success and cause population declines. Moreover, population size is specifically impacted by delayed recruitment effects where both species decline after a lag corresponding to their estimated age of first reproduction. These North Atlantic seabirds are therefore at risk from future environmental and anthropogenic changes, as time-delays may result in populations already on an extinction trajectory prior to changes being detectable in their abundance.

As ecosystems face a growing number of threats, coextinctions (resultant extinctions following a primary extinction) are expected to proliferate. However, less is known about the conditions under which coextinctions could outpace primary extinctions. Because coextinctions often occur through lost species interactions, we posit that aspects of food web structure and complexity can help predict differences in vulnerability to coextinction across ecosystems. To test this, we leverage Bayesian network models to assess the extent to which variation in ecosystem vulnerability to coextinction varies with food web structure. We find that food webs with high maximum trophic level are most vulnerable to coextinction, and that maximum trophic level is a better predictor than other aspects of food web structure, such as species richness or trophic connectance. Extending this approach, we also find that maximum trophic level uncovers the relative vulnerability of ecosystem services to species coextinction across 12 empirical food webs.

Defaunation, defined as the loss or severe decline of animal populations, is increasingly recognized as a major dimension of global environmental change, yet its role in zoonotic disease ecology remains poorly understood. Although defaunation significantly influences ecological dynamics, current metrics often focus on species loss without fully addressing its cascading impacts, which can affect ecological processes such as zoonotic disease transmission. In this perspective, we propose a defaunation-cascade framework linking anthropogenic pressure to zoonotic pathogen dynamics through four ecological steps: host trait filtering, abundance restructuring, interaction rewiring, and altered pathogen circulation or proliferation, and potential spillover hazard. We illustrate this framework by using a global review of empirical studies and combining georeferenced data on disease prevalence with environmental and human-related factors. Our exploratory models suggest pathogen-specific associations: parasitic and bacterial prevalence were more strongly associated with anthropogenic pressure and mammal diversity metrics, whereas viral prevalence showed weaker support. We contend that incorporating defaunation cascades into One Health surveillance will improve ecological understanding of pathogen circulation and enhance the ecological accuracy and predictive power of zoonotic disease models, thereby identifying landscapes where faunal simplification may elevate spillover hazard.

A central question in restoring degraded grasslands is whether grazing removal can sustain viable plant populations under both current and future warming conditions. Addressing this question requires demographic studies integrating vital rates responses to grazing removal and climate warming throughout a species life cycle. However, studies of this nature are rare. Using stochastic Integral Projection Models parameterized with four years (2020-2023) of demographic data, we find that nine years of grazing removal increases the stochastic population growth rate (log{lambda}S) of two coexisting herbaceous plants, Carex atrofusca and Sibirotrisetum sibiricum at two altitudes (3,700 m and 4,000 m) in an alpine grassland on the Tibetan Plateau. Although individual survival declines following grazing removal, these negative effects are overcompensated by enhanced plant growth, ultimately promoting log{lambda}S in both species. However, the benefits of grazing removal are cancelled under nine years of in situ active warming (+2{square}), where no demographic compensation occurred (i.e., vital rates change in the opposite directions among populations), and log{lambda}S are even lower than those under grazing. Our findings suggest that while grazing removal is a sustainable management strategy under current climate conditions, it may not remain effective under projected warming, providing valuable information for sustainable population management under global change.

Abundance correlations cannot reveal ecological interactions without an assumption about the covariance of environmental noise. A natural biological expectation is that similar species respond similarly to environmental fluctuations, generating positive correlations. Yet the same species also tend to overlap more strongly in resource use and therefore compete more intensely, generating negative correlations. The simplest plausible benchmark is thus to take environmental-response correlations proportional to niche overlap. We show that, under this assumption and across a broad class of stochastic community models, the two effects cancel exactly: equal-time abundance correlations vanish, independently of interaction strength, heterogeneity, and system size. Away from this matched point, the observed correlations measure primarily the mismatch between shared environmental response and competition, rather than the interaction matrix itself. Correlations can recover information about niche overlap when competitive feedback is delayed relative to environmental forcing, but the inference then depends on a resource-response timescale that is generally not determined by the abundance time series alone. When stochasticity enters through the mechanism that generates similarity itself--for example, through fluctuating shared resources--nonzero correlations may persist, but they reflect yield-depletion mismatch rather than niche overlap. Abundance correlations therefore report how environmental variability reaches the community at least as much as they report who competes with whom.

Field ecologists often rely on observational data to understand the impact of environmental stressors and management interventions on natural systems. Natural and anthropogenic events (e.g. wildfires, protected areas, nutrient deposition) do not occur randomly in space, however, which can introduce bias into observational studies--which we refer to as causal selection bias. Field study designs that ignore the non-random occurrence of stressors may yield biased estimates of stressor effects on ecosystems. Matching methods commonly used in economics, political science and epidemiology offer a powerful framework for controlling for causal selection bias by identifying more comparable treatment and control sites. Although these methods are increasingly used in conservation, they are rarely used in ecological field-based studies. Here we review how Propensity Score Matching (PSM) can improve field sampling designs in ecology and strengthen causal identification of stressor effects. Then we apply this approach to a case study examining wildfire effects on forest recovery in California. We conclude with practical recommendations for implementing PSM to improve causal identification of ecological change, which is particularly important for developing effective management interventions.

A central question in biodiversity conservation is whether species can sustain viable population under current and future atmospheric N deposition. Assessing species viability under N deposition requires demographic studies integrating species vital rates responses to long-term N deposition across different levels. However, studies of this nature are rare. Our integral projection models (IPMs), parameterized with demographic data, revealed differing responses of two functionally similar coexisting species, Stipa bungeana and Leymus secalinus, to 12 years of N deposition at low N addition levels (1.15 and 2.30 g N m-2 yr-1) and high N addition levels (4.60, 9.20, and 13.80 g N m-2 yr-1) on the Loess Plateau grasslands. We found that the reduced survival across N addition levels was partially compensated by increased contributions from growth, shrinkage, and fecundity, alleviating the population decline of S. bungeana (with a longer lifespan and generation time) under different N additions. Contrasting, more positive correlations among vital rate enabled the population of L. secalinus (with a shorter lifespan and generation time) to track N additions, with population growth under low N additions and population decline under high N additions. Our results illustrate that the demographic response to N deposition may vary considerably between functionally similar coexisting species, and species with demographic compensation can buffer populations against N deposition while with demographic lability enable populations to track N deposition. Furthermore, our study demonstrates the potential of using life-history traits to predict species viability under N deposition, thereby informing biodiversity conservation under global change.

Ecologists remotely track movement steps of animals (e.g., via global positioning systems) and use step selection functions to study the effect of environmental factors upon their movement decisions. Constructing such functions requires pairing each observed step with some number of unobserved but feasible comparison steps. Larger numbers of comparison steps generally yield better estimates but also incur potentially challenging computational demands. Thus, it is important to determine an appropriate number of comparison steps. No established guidance exists for this decision. Here, we use simulated tracks to assess how many comparison steps are needed, fitting each set of steps to a conditional logistic regression model. We monitor errors in estimated effects for several classes of tracks, identifying the number of comparison steps for which mean relative absolute error in estimated effects is consistently low. By this criterion, 32 comparison steps per observed step are needed for our primary class of simulated tracks. Tracks in more homogeneous landscapes, tracks with shorter mean step lengths, or shorter tracks generally require more comparison steps (ranging from 64 to 128 per observed step) to achieve the same level of accuracy. Longer tracks generally require fewer comparison steps (16 per observed step). These results clearly demonstrate that the number of comparison steps influences how well step selection functions estimate covariate effects and provides initial direction in a research area that currently lacks quantitative guidance. Movement ecologists should take care when selecting the number of comparison steps paired with each observed step because those decisions matter.

Biodiversity is predicted to stabilize ecosystems if species have different environmental responses. How this response diversity is shaped by ecological and evolutionary processes remains poorly understood. We determine the drivers of thermal response diversity of 16 Swiss peri-alpine lake-fish communities. We report the first evidence that evolutionary diversification of lineages through adaptive radiation can increase the response diversity of an ecosystem. In-situ diversification increases response diversity in the cold-deep lake environment, but non-endemic and non-native species contributed only weakly to response diversity. The loss of endemic species during historical anthropogenic eutrophication led to a negative legacy on present thermal response diversity in cold and deep lake strata. Overall, the interplay of evolutionary diversification, ecological assembly and anthropogenic impacts drives variation in response diversity. Conserving and restoring processes that generate diversity may help maintain ecosystem stability beyond the Anthropocene.

Successional communities often recover slowly because progression stalls at persistent stages that resist replacement. Here, we show that resilience in such systems is frequently governed by a single bottleneck stage with the lowest effective exit rate. Using empirical transition ma-trices from intertidal and plant communities, we demonstrate that altering the bottleneck has a much larger effect on resilience than modifying any other stage. We then show that this bottle-neck principle emerges naturally from both Markov and continuous-time models of succession. Specifically that the slowest return to equilibrium is controlled primarily by the stage with the smallest effective exit rate, which also dominates the mean first-passage time to late succession. These results provide a simple biological interpretation of resilience in successional communities and suggest that management efforts are most effective when they target the stage that limits the pace of succession.

Secondary forest succession following agricultural abandonment is a dominant land-use transition across the tropics, yet whether soil microbial communities recover toward old-growth forest reference states remains poorly understood, particularly in West Africa. Here, we investigated the successional dynamics of bacterial and arbuscular mycorrhizal (AM) fungal communities along post-agricultural chronosequences spanning 1 to 43 years across six classified forests in Cote dIvoire, using Bayesian hierarchical models applied to amplicon sequencing data. Both guilds attained moderate to high alpha diversity within the first decade of succession; AM fungal diversity showed moderate evidence of age-related increase thereafter while bacterial diversity showed no directional trend. Pairwise turnover analyses revealed progressive internal convergence in AM fungal communities with plots farther apart in successional time becoming more compositionally similar, while bacterial communities showed only a weak and uncertain tendency in the same direction. Beta-dispersion modelling further indicated progressive within-forest homogenisation of AM fungal communities across abundance-weighted metrics, while bacterial assemblages showed no such stabilisation. Despite this internal convergence, compositional distances to old-growth reference plots remained persistently high for both guilds throughout the chronosequence, with no statistical evidence of recovery toward old-growth states across any dissimilarity metric or guild within the 40-year window. Indicator species analysis identified no robust stage-specific taxa after correction for multiple testing. These results indicate that microbial succession in post-agricultural West African forests is characterised by rapid early reorganisation followed by stabilisation into site-specific assemblages that remain persistently distinct from old-growth reference communities. This outcome challenges the direct application of classical vegetation successional theory to soil microbiomes and suggests that passive regeneration alone is unlikely to restore old-growth microbial communities within restoration-relevant timescales.