Ecology Letters

Ecological theory states that the geographic ranges and coexistence of species are determined by fundamental and realized niches - the sets of environments where a species intrinsic population growth rate is positive in the absence and presence of competitors, respectively. Yet large-scale tests of niche theory have been hampered by the challenge to obtain sufficient data on demography and competition. Here, we quantify fundamental and realized niches by combining data on variation in fundamental demographic rates, community composition and the abiotic environment across the global geographic ranges of 29 shrub species from the South African Fynbos biome (a global biodiversity hotspot). Estimated pairwise competition coefficients and fundamental-realized niche contrasts reveal multi-scale mechanisms of species coexistence. At small scales, species generally exert stronger competition on themselves than on other species. At biogeographical scales, more competitive species have narrower fundamental niches but are not significantly better dispersed, which provides evidence for a generalist-specialist trade-off rather than a competition-colonization trade-off. Under both present and future climates, interspecific competition more strongly limits the realized niches and geographic ranges of generalist species. The large-scale application of niche theory thus identifies key forces shaping biodiversity and indicates that generalist species may be more strongly impacted by climate change than previously thought.

Environmental change affects demographic rates through perturbations that differ in magnitude, duration, and frequency, yet their consequences for population vulnerability, i.e., potential population reduction, remain only partly understood. Here, we develop a general demographic framework that unifies pulse and press perturbations to better understand how life-history strategy shapes population declines across the fast-slow continuum. Using matrix population models for 12 plant and animal species with diverse generation time and life history strategies, we simulated perturbations acting independently on adult survival, juvenile survival, and fecundity, and measured their demographic consequences over comparable life-history timescales. We then integrated impacts across perturbation regimes to derive a novel comparative vulnerability metric and related this metric to species life-history descriptors. Across taxa, perturbations to adult survival consistently produced the strongest demographic impacts, with vulnerability increasing markedly towards slower life histories. Juvenile survival emerged as the main axis of demographic differentiation among species, whereas the effects of perturbations on fecundity were weaker and comparatively homogeneous across the continuum. Generation time strongly predicted vulnerability to survival perturbations, but not to reproductive output. Consistent with previous theoretical and empirical work, our results show that vulnerability is not a fixed species property, but an emergent outcome of the interaction between the perturbed vital rate, the temporal structure of environmental forcing, and the underlying life-history strategy. Importantly, as the vulnerability metric can be compared both across populations under a given perturbation regime and within populations across perturbation types and demographic targets, the framework also provides a basis for stage-specific and regime-specific management.

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.

Climate warming is altering the timing of seasonal events across ecosystems, impacting the temporal synchrony of interactions among species1,2. For trophic interactions, the match-mismatch hypothesis predicts that when consumers become phenologically asynchronous with key ephemeral resources their fitness will decline3-5. Most studies of mismatch focus on single resource-consumer species pairs, and implicitly assume trophic specialisation. However, many consumers exploit more than one resource species, giving rise to several mechanisms whereby the negative impacts of mismatch on individuals and populations could be buffered6. Here we experimentally manipulate phenological asynchrony across 48 plant-caterpillar interactions in a spring woodland food-web system and assay caterpillar performance. As asynchrony increases, we find strong evidence for a decline in survival that generalises across host-caterpillar interactions, whereas caterpillar growth and development are largely unaffected. We also show that focus in the literature on a single model interaction (Oak-Winter Moth)7,8 has likely overestimated the general impact asynchrony in this system. The strength of the effect of mismatch varies markedly among host-plants, caterpillars, and their interactions--with a small number of interactions showing little or no decline in consumer performance despite substantial asynchrony. Our results demonstrate that the fitness consequences of phenological mismatch are widespread but interaction-specific, revealing substantial heterogeneity in how trophic interactions are expected to respond to climate-driven shifts in seasonal timing. This variation in response could allow resource diversity and resource switching to buffer consumer guilds against the phenological impacts of ongoing climate change, stabilising the abundance of caterpillars for higher trophic levels.

Memory effects--defined as the capacity of system states to exert long-lasting influence on subsequent dynamics--are widely recognized as central features of complex living systems. In ecological systems, however, their consequences for stability and recovery dynamics remain poorly understood. To fill this gap, we develop a general theoretical framework that incorporates memory into the dynamics of species-rich ecological systems with complex interaction structures. Our analyses reveal that memory effects expand the stability domain, enabling systems that would otherwise be unstable to persist following perturbations, particularly in cases where instability involves oscillatory behavior. At the same time, memory can accelerate short-term recovery, allowing systems to return more rapidly toward equilibrium in the early stages after perturbation. These apparent benefits, however, come at a cost: memory effects markedly slow long-term recovery, thereby delaying full restoration, as memory retains the influence of past perturbations and hinders a full return to equilibrium. We further support these results by integrating empirical data into the framework. Together, these results reveal fundamental trade-offs mediated by memory--enhanced stability and faster short-term recovery at the expense of delayed full restoration--highlighting the dual role of memory in shaping resilience in complex ecological systems and, more broadly, complex living systems.

Under complex perturbation regimes, biodiversity dynamics show temporal variability in species and community abundance around long-term population trends. Many species indeed show long-term declines while other species increase, putting natural communities far from stationary regimes, while variability is often studied near equilibrium. We contribute to bridging this gap by investigating population and community variability during long-term trends caused by press perturbations in stochastic models of population dynamics. By estimating the deterministic changes in mean and variance during the transient regime, we show that population variability deviates from stationary expectations. Moreover, the deviation strongly depends on the sign of the population trends: increases generate excesses of variability while declines generate deficits. Scaling up to community variability, we propose a decomposition of community variability deviation, allowing to highlight that community variability in the transient regime depends on how the press perturbation is distributed within species relative abundances and growth rates. These results challenge the equilibrium assumption and open new perspectives for the study of the variability of ecological systems under multiple perturbation types.

O_LIChanges in community structure under shifting thermal regimes depend on how both local population dynamics and regional dispersal respond to temperature. Processes underlying dispersal, such as movement speed and density dependence, are constrained by temperature-dependent metabolic rates; however, the temperature dependence of population dispersal rate, and effect of this relationship on local and regional diversity patterns, have received little attention in the metabolic scaling literature. C_LIO_LIHere, we propose and experimentally test a framework that relates temperature effects on individual dispersal probability, to thermal performance curves (TPCs) for population dispersal rates, to colonization dynamics in metacommunities. Using multi-patch well plate microcosms, we measured thermal performance curves for dispersal rate in several naturally co-occurring ciliate species, and contrasted species-specific dispersal TPCs at different intra- and inter-specific densities and time scales. C_LIO_LIDispersal rate TPCs in monoculture differed at low versus high population densities, potentially suggesting distinct temperature effects on the density-independent (individual movement probability and speed) and density-dependent (quorum-sensing and resource competition) components of dispersal. C_LIO_LISpecies-specific dispersal rate TPCs in polyculture metacommunities explained differences in colonization dynamics across temperature treatments. Dispersal rate TPCs differed from intrinsic growth rate TPCs, such that better dispersers had higher-than-expected per capita population growth at the regional (whole-metacommunity) scale compared to predictions from standard growth TPCs measured in single-patch monoculture. C_LIO_LITogether, these results suggest that ignoring temperature-dependent dispersal can yield an incomplete understanding of biodiversity change in spatially structured systems exposed to warming. C_LI

The complexity-stability debate in ecology remains unresolved in part because its empirical basis is limited. Most evidence for the predicted decline of connectance with species richness comes from food webs, leaving unclear whether this pattern extends across the full spectrum of ecological interactions. Moreover, existing results remain conceptually unresolved: connectance decreases with diversity, yet both the total number of interactions and the number of interactions per species increase. Here, we analyze 1,500 ecological interaction networks spanning diverse habitats and interaction types. We show that these patterns are broadly shared across ecological interaction networks and can be interpreted through a recent theory of information dynamics in complex networks, in which sparsity is favored by a trade-off between signal propagation and response diversity. Our results suggest that the structural component of the debate may indeed reflect a general architectural regularity of ecological communities rather than a contradiction between theory and nature.

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.

Ecosystems are rarely at steady state, yet most theory predicting universal biodiversity patterns assumes they are. Here, we test whether and how eco-evolutionary dynamics drive departures from steady state by combining arthropod community data from the geologic chronosequence of the Hawaiian Archipelago with the Maximum Entropy Theory of Ecology (METE), a minimalist steady-state framework that simultaneously predicts species abundance distributions (SADs) and individual metabolic rate distributions (IPDs). The chronosequence of the Hawaiian Archipelago has yielded insights into eco-evolutionary processes because ecosystems growing on different aged substrates offer snapshots of community assembly with different histories. We find that deviations from METE peak at geologically middle-aged sites (150 Kya-1.4 Mya), consistent with active adaptive radiation pushing communities away from statistical steady state. Within-site {beta}-diversity, which also peaks at middle-aged sites, robustly predicts deviations from METE across all sites, while the proportion of non-native species predicts deviations only after excluding the geologically youngest site. Partitioning {beta}-diversity between native and non-native species resolves this discrepancy: at the youngest site, non-native species are distributed homogeneously and do not elevate {beta}-diversity despite their high proportional representation. Together, these results are consistent with a trajectory from young, dispersal-assembled communities near statistical steady state, through an eco-evolutionary non-steady-state transition driven by diversification, to a new stable steady state at the oldest sites. Our findings suggest that periods of active diversification create windows of ecological instability that may facilitate biological invasion, with implications for understanding invasion dynamics in biodiversity hotspots.

The diversity of species responses to environmental change (response diversity) is a key mechanism of ecological stability. However, anticipating where strong or weak stabilizing responses emerge is challenging because species responses can depend on the local community and the specific stability metric. Whether species traits can consistently inform on how species respond to disturbances, enabling less context-dependent predictions, remains an open question. To address this gap, we use microcosm experiments on marine phytoplankton to test how response diversity supports multiple aspects of community stability under pulse temperature changes, testing both an increase (heatwave) and a decrease in temperature (coldspell). We then map species traits to their responses in a community to identify which traits modulate and predict species' sensitivities. Fundamental response diversity, based on the diversity of species responses to temperature measured in isolation, was a weak predictor of community stability, and relationships differed between disturbances (i.e., heatwave and coldspell). Instead, species traits were consistent predictors of species responses in communities. Small, fast-growing species were more tolerant and benefited from the disturbance, while large, slow-growing species were less tolerant and decreased in proportion - these patterns were consistent across disturbances and community compositions. These results suggest that strong trait-performance relationships might reduce the importance of response diversity for stability. But these findings also show that general species traits, such as size and growth rate, can predict which species, and how, contribute to community responses, providing an empirical basis to relate species traits to stability outcomes under climate change.

Understanding the mechanisms that link biodiversity to ecological stability is crucial for predicting ecosystem responses to global change. Using three decades of standardized monitoring data from eight subtropical estuaries, we analyze diversity components (richness, evenness, dissimilarity, and variance-mean scaling) and interpret stability patterns through synchrony or portfolio mechanisms. Regional {gamma}-diversity increased steadily over time, reflecting sustained gains in fish and invertebrate assemblages. Community stability, defined here as community invariability, was strongly and consistently predicted by Shannon diversity index but not by species richness, underscoring the stabilizing role of evenness. Portfolio effects were robust, with community stability averaging approximately threefold higher than mean population stability, and the strength of this effect more than doubled with each unit increase in Shannon diversity. Structural equation models paired with a null model revealed that shared environmental forcing synchronizes estuarine populations. Shannon diversity generated a large portfolio effect that stabilized the community despite this environmental forcing, whereas richness effects were weak or absent. Taylors law scaling confirmed that abundant, persistent taxa such as blue crab (Callinectes sapidus), brown shrimp (Farfantepenaeus aztecus), and pinfish (Lagodon rhomboides) exhibited higher baseline invariability, contributing to community buffering, while rarer, more variable taxa introduced volatility. In contrast, compositional turnover strongly eroded stability, with high Bray-Curtis dissimilarity predicting reductions in community stability. Together, these results show that long-term estuarine community stability emerges from the interplay of portfolio averaging, demographic variance scaling of dominant species, and the persistence of community composition, highlighting the central role of evenness in biodiversity-stability relationships.

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.

Whether species-rich communities erode gradually or collapse abruptly under environmental change is a central question in ecology [1]. Classical pairwise theory predicts that coexistence is always lost gradually, through smooth declines to extinction [2], yet real ecological interactions are often strongly state-dependent - shaped by nonlinearities that fixed pairwise coefficients cannot capture [3]. Here we show that higher-order (nonlinear) interactions make abrupt, irreversible loss of coexistence a typical route to community collapse: across diverse random communities, the equilibrium supporting coexistence disappears suddenly at a fold bifurcation. Using polynomial homotopy continuation [4] to track equilibria as environmental conditions change, we find that folds progressively dominate the boundary of the coexistence domain as nonlinearity strengthens, replacing the gradual extinctions of pairwise theory. Furthermore, the sign structure of higher-order interactions controls both the onset of tipping-points and whether biodiversity buffers or amplifies collapse. Because higher-order and nonlinear interactions are intimately linked, tipping points also arise generically in pairwise models with strong nonlinearity. Applying our continuation framework to a canonical model of plant-pollinator collapse [5], we formally resolve its bifurcation structure as fold-mediated, and we show that fold bifurcations are typical across published multispecies models spanning mutualistic, competitive, and consumer-resource interactions. These results challenge the expectation that monitoring abundances suffices to anticipate collapse, and unify structural-stability theory, which delineates the safe operating space for coexistence, with critical transition theory, which characterizes the nature of its boundaries.

Frequency-dependent predation helps maintain bacterial diversity, but its stabilizing role may be compromised under climate warming. Whereas theory suggests that warming can weaken predator-prey interactions and destabilize prey coexistence, it remains unclear whether constant and variable warming regimes differentially disrupt predation and alter coexistence outcomes in bacterial communities. Here, we experimentally tested how constant and variable warming (both +4{degrees}C above ambient, but negligible versus high thermal variance) affect the coexistence of two Pseudomonas species in the presence of their lytic phage. Phage predation increased competitive symmetry between the two bacterial species and promoted bacterial coexistence. Under constant warming (negligible variance), this phage-mediated frequency dependence buffered competitive asymmetries and often promoted persistence of the otherwise inferior P. putida, thereby magnifying coexistence. In contrast, variable warming (high variance) weakened phage control, shifted the advantage to P. protegens, and increased competitive exclusion events. The erosion of top-down control under variable warming was consistent with strong thermal sensitivity of phage infection rates, revealed by thermal performance curves. Our findings demonstrate that phage reduction of competitive asymmetry between bacterial hosts is amplified under constant warming but undermined under variable warming, conditions that are becoming increasingly frequent under climate change.

Most theory and empirical research on range expansion assumes populations spread into empty landscapes with abundant resources, however expanding populations are likely to compete with residents. In mathematical models, interspecific competition can lead to pushed wave dynamics, where expansions are driven mainly by individuals dispersing from the core, leading to steeper wavefronts and increased genetic diversity at the edge. These predictions are yet to be tested empirically, and the role of interspecific competition in mediating evolution during range expansion is unclear. We used an experimental system with two duckweed species to ask if interspecific competition leads to pushed-like dynamics and to assess how competition alters evolution during range expansion. We found that competition with a resident reduced expansion speed and absolute variance among replicate expansions, suggesting competition makes expansion speed more predictable. Interspecific competition also changed the relative frequencies of genotypes at the leading edge. While competition was associated with some features of pushed waves, genotype diversity did not vary between treatments. Our results demonstrate that demographic and evolutionary patterns associated with pushed waves may not be universal, and that incorporating selective pressures into future research on eco-evolutionary dynamics of range expansion is key to understanding spreading populations in nature.

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.

AO_SCPLOWBSTRACTC_SCPLOWO_LICommunity assembly graphs (CAGs) summarize which species combinations can coexist and how single-species invasions drive transitions between them, encoding the pathways, alternative endpoints, and cycles that make up a communitys assembly history. Constructing CAGs from dynamical models requires methods that are both computationally tractable and faithful to the underlying ecological dynamics. However, existing methods rely on restrictive assumptions, such as global stability, that exclude alternative stable states and non-equilibrium dynamics known to occur in empirical systems. C_LIO_LIWe develop a computational pipeline that constructs CAGs from any generalized Lotka-Volterra model. Building on the invasion graph framework and its connection to permanence, the pipeline verifies that community dynamics are bounded, identifies which subsets of species coexist in the sense of permanence, determines which single-species invasions are dynamically realized, and assigns each community a topographic height equal to the length of the longest assembly path leading to it. We also provide a numerical algorithm to simulate the dynamics of community assembly. C_LIO_LIWe prove several general properties of the resulting graphs, including that a successful invader is never subsequently excluded and that, in the absence of assembly cycles, permanent communities can be reassembled by introducing their species one at a time in the right order. We prove that the CAG faithfully reproduces the compositional shifts seen in the numerically simulated dynamics of assembly. Applying the pipeline to three empirically based models (a New Zealand grassland, a European pasture, and a Puerto Rican ant community), we show how competition strength and mutualistic feedbacks reshape the assembly landscape and how intransitive competition generates assembly cycles. C_LIO_LIOur approach accommodates alternative stable states and non-equilibrium dynamics without requiring global stability, and it turns the long-standing landscape metaphor into a quantitative, mechanistically grounded object by resolving what "height" means. More broadly, it makes the topography of the assembly pathways measurable, providing a way to compare the historical contingency and predictability of the assembly in ecological systems. C_LI

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.

Phenological shifts under climate change often arise through phenotypic plasticity and, where this is insufficient to track shifts in optimum timing, genetic adaptation may also play a role. Understanding the contributions of these two processes is critical for predicting species persistence in a changing climate. While many species show phenological plasticity, we know surprisingly little about the contributions that genetic adaptation of the plasticity reaction norm elevation (timing in the mean environment) and slope (shift in timing as a response to temperature) make to phenological shifts. With the aim of disentangling plasticity from adaptation in temperature-phenology reaction norms, we applied a statistical approach to long-term first egg-laying data from 44 Finnish bird species represented by 69 populations spanning six decades. Applying phylogenetic meta-analysis to parameter estimates obtained from the individual time series, we estimated average plasticity and adaptation effect sizes and tested whether migratory strategy, generation length, and mean laying-date explained among-species variation. Egg-laying phenology was strongly plastic, advancing by 2.5 days {degrees}C{square}{superscript 1}. We found no evidence for a steeper reaction norm between 5-year periods versus within them, consistent with no adaptation of the reaction norm elevation. However, we detected a significant steepening of slopes over time (-0.04 days {degrees}C{square}{superscript 1} year{square}{superscript 1}), consistent with plasticity across the whole study area increasing from -2.5 to -5.1 days {degrees}C{square}{superscript 1} and in the northernmost area (-0.07 days {degrees}C{square}{superscript 1} year{square}{superscript 1}) from -2 to -6.5 days {degrees}C{square}{superscript 1} over the 64-year study period. Trait analyses revealed no significant effect of migratory strategy, generation length, nor mean phenology on adaptation. We show that plasticity enables substantial short-term tracking of warming accompanied by noteworthy evidence consistent with widespread evolution of. Our approach demonstrates how observational data can help reveal evolutionary signals, offering a tool for improved understanding of the processes that underpin phenological responses.