Ecology Letters

Environmental change alters species growth rates and, through species interactions, can produce complex effects on community functioning and composition. Because functional traits mediate both environmental responses and competition, rapid trait adaptation may modify these effects, but its consequences in multispecies communities remain unclear. We used a trait-based model of competitive communities to test how adaptation affects the mean and diversity of species growth responses to environmental change, and how this influences functional and compositional resistance (how unaffected the community is by the environmental change) and resilience (how well it recovers after it has acclimated to the altered environment). Adaptation altered response variance more strongly than the mean by changing the balance between environmental optimisation and competition-driven trait divergence. As a result, adaptation strongly increased compositional stability, but had less clear effects on abundance. Adaptation also generated a trade-off between resistance and resilience: faster adaptation improved resistance but reduced resilience as communities were displaced less by the environmental change and thus recovered less. Overall, adaptation can be stabilising, but higher adaptation rates do not necessarily produce greater stability across all stability components.

1. Plant-soil feedback (PSF) is increasingly recognized as an important mechanism influencing plant coexistence, but most studies have examined PSF in isolation under controlled conditions. Under natural conditions, PSF operates together with other processes such as resource competition, yet how these processes jointly shape plant coexistence across environmental gradients remains poorly understood. 2. We combined field and greenhouse experiments to assess the contribution of PSF to plant coexistence at low- and high-elevation sites in the Swiss Alps. In the field, we quantified total niche and fitness differences and predicted interaction outcomes for nine plant species pairs, integrating PSF, resource competition, and other processes. In a complementary greenhouse experiment, we used soil microbial communities conditioned during the field experiment to isolate PSF-driven niche and fitness differences for the same species pairs. 3. PSF alone generated strong fitness differences but weak niche differences in the greenhouse experiment, predominantly predicting competitive exclusion. Interaction outcomes predicted from PSF alone corresponded poorly with those in the field, suggesting that PSF in isolation poorly explain plant coexistence under natural conditions. Nevertheless, PSF-driven niche and fitness differences were related to those quantified in the field, which were likely driven largely by resource competition, suggesting that PSF may contribute to coexistence by reinforcing or counteracting other ecological processes. These relationships varied between elevations, highlighting the context dependence of PSF contributions to coexistence. 4. Synthesis. Our study shows that the impacts of plant-soil feedback on plant coexistence cannot be understood from their effects in isolation. Instead, their contribution depends on how they interact with other ecological processes and on the environmental context in which these processes operate. Together, our findings emphasize the need to move beyond studying PSF in isolation towards quantifying how it combines with other mechanisms that drives coexistence under natural conditions.

Ecologists have long investigated how community complexity affects ecological stability, yet how community complexity influences multistability, defined as the presence of alternative stable states, remains poorly understood. We developed a novel framework integrating stochastic community assembly with stability landscape analysis to quantify multistability from species interaction matrices. Using this framework, we systematically explored how species interaction properties shape the relationship between species diversity (species pool size) and the number of alternative stable states. Mean interaction strength was the primary determinant: competitive interactions amplified the positive relationship between species diversity and the number of alternative stable states. In competitive communities, a greater number of alternative stable states was associated with lower community uncertainty, a measure of the long-term unpredictability of community assembly dynamics. These results highlight the importance of characterizing the entire stability landscape. Our framework provides a general approach for understanding and quantifying multistability in complex ecological communities.

Physical disturbance is pervasive across ecosystems, yet how it shapes diversity remains unresolved. For over five decades, two major hypotheses offer contrasting explanations. One proposes that disturbance weakens heterospecific competition, whereas the other argues that it reduces intrinsic demographic rates thereby delaying competitive exclusion. We established 210 experimental plant communities, applied early- or late-season clipping, and used a Bayesian model with counterfactual simulations to separate these pathways. Only early clipping increased diversity across timescales; late clipping reduced it during the experiment and had no effect at equilibrium. The logic of the demographic hypothesis was supported: higher intrinsic demographic rates reduced diversity. Surprisingly, disturbance generally increased rather than reduced these rates, causing the demographic pathway to decrease diversity. In accordance with the competition hypothesis, disturbance weakened heterospecific competition across the interaction matrix, increasing diversity under both regimes. Yet nearly all this competition-mediated diversity increase was captured by weakened competitive effects of the two dominant grasses on the rest of the community. Together with disturbance-induced changes in the grasses' own dynamics, these effects nearly reproduced the full diversity response. Diversity increased only under early clipping because competitive release outweighed opposing changes in dominant-grass dynamics; under late clipping it did not. More broadly, disturbance effects on diversity emerge from opposing changes in intrinsic demography and competition, with their balance determining whether diversity increases or declines.

Understanding how species traits shape community properties is a central goal in ecology. But whether traits drive consistent patterns of dominance and assembly regardless of initial species abundances (evenness) remains unclear. We addressed this question using phytoplankton microcosm experiments to disentangle the effects of evenness and traits on community assembly and functioning, focusing on traits related to energy use (photosynthesis, size) alongside demographic parameters. Community assembly was highly deterministic, indicating that initial evenness had little influence on species dominance and final community structure. Instead, evenness drove community functioning. Demography was a stronger predictor of dominance than photosynthetic rates or individual size, suggesting that growth and competitive success depend on multiple metabolic processes that cannot be reduced to simpler proxies. These results show that community structure can emerge predictably across a range of initial conditions, and highlight the importance of demographic metrics over simpler metabolic descriptors for forecasting community outcomes.

In natural ecosystems, community dynamics are driven by diverse interactions operating through both ecological and reproductive processes. Although theory predicts that these processes jointly generate complex and contingent dynamics through the interplay of stabilizing (negative frequency dependence arising from niche differences) and destabilizing effects (positive frequency dependence caused by reproductive interference), empirical tests of this prediction remain scarce. Here, we combined experimental and theoretical approaches to investigate the dynamics of two congeneric annual plant species (Commelina) experiencing both ecological competition and reproductive interference. Our empirically parameterized model revealed a large niche difference and mutual reproductive interference. However, the reproductive interference was not strong enough to generate pronounced contingency of community dynamics on initial conditions. Instead, coexistence was the most likely outcome regardless of initial species composition. Parameter exploration indicated that the weak contingency arose because reproductive assurance strategies of Commelina species buffered the minority disadvantage caused by reproductive interference. These findings provide empirical evidence that reproductive interference does not necessarily destabilize coexistence and that it may be outweighed by ecological niche and fitness differences. Our study highlights the importance of integrating ecological and reproductive processes towards better prediction of community dynamics.

Environmental variability influences the evolution of phenotypic plasticity and the ecological interactions among species in communities, but it is unclear how these processes interact to affect ecological systems across scales. We investigate models describing how plasticity evolves in competitive communities exposed to seasonal variation in abiotic conditions. We conducted eco-evolutionary analyses to identify communities of coexisting species with evolutionarily stable plasticity traits. These analyses revealed that the presence of interspecific competitors constrained the evolution of plasticity in some species, which instead evolved to be specialists. Plasticity often impaired species coexistence by allowing individual species to control more niche space. Communities containing plastic species were usually less species-rich but more productive and less variable. Similar results were obtained when plasticity rate was evolutionarily labile, but plasticity rate altered the patterning of temporal niche partitioning. This work shows how plasticity and competition combine to shape ecological and trait responses to environmental variability.

Why species coexist and how diversity sustains ecosystem functioning are usually studied apart. A long-established concept captures both: the complementarity effect---the additional biomass produced by species in mixture. Here, we demonstrate that mixtures of species with negative complementarity are almost always either unfeasible or unstable, whereas a strong positive complementarity indicates a large potential for coexistence. Because a community's total yield settles long before the community composition does, this signal can be read as a predictor in communities still in flux: our analyses of four long-term biodiversity experiments show that transient negative complementarity precedes species loss. Thus, stable coexistence and higher productivity are intrinsically linked in multispecies communities. Biodiversity does not merely have beneficial effects on average; biodiversity that endures can only improve ecosystem functioning.

Plant-pollinator communities are typically represented as bipartite networks, whose edges are taken directly from field records of visits. These visits, however, are only a proxy for the object of ecological interest: the latent mutualistic preference between two species. While counts are shaped by preference, they also carry confounding factors such as species abundances, sampling effort, and site- or time-specific conditions. We introduce a hierarchical Bayesian framework that treats visit counts as a realisation of a Poisson process and, on the log scale, decomposes the corresponding pairwise rate into a baseline (community-wide activity together with sampling effort), individual species effects representing abundance, and pairwise mutualistic preferences. The model extends to data replicated across sites and time points, and to the inclusion of environmental or experimental covariates. Because the whole system is fitted jointly, we obtain posterior not only for the preferences but for every latent quantity, each carrying ecological signal of its own, with uncertainty propagated through every level of the model, down to any derived network metric. On synthetic data, we show that common practices, such as reading preferences off raw counts or aggregating replicated observations into a single network, confound abundance with preference. In contrast, our framework recovers the underlying preference structure. On empirical datasets, including a seasonal multi-site pollination study where urbanisation level enters as a covariate, the inferred preference network departs markedly from the observed visits, revealing structure hidden in the raw counts: how species vary across sites and time, and which parts of the community respond most to the covariate. When communities are compared along the urbanisation gradient, standard network metrics on the preference layer revise the conclusions drawn from visits alone. The framework offers a principled way to move from networks of observed visits to networks of underlying mutualistic preferences, carrying uncertainty from the data through to the ecological conclusions and accommodating the spatial, temporal, and covariate structure of modern plant-pollinator datasets. Because it acts on the foundational step of network construction, its implications are broad, placing network-based approaches on firmer ground.

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.

O_LISeasonal migration in birds involves a substantial spatial redistribution of avian biodiversity each year and drives seasonal changes in community composition. Migrants experience different combinations of species interactions over space and time, generating regular disassembly and reassembly of bird communities throughout their annual cycles. However, the effects of seasonal migration on phylogenetic community structure remain poorly understood. C_LIO_LIWe assess spatiotemporal variation in phylogenetic community structure of North American passerines to test how seasonal migration restructures the evolutionary relatedness and dominant assembly mechanisms in bird communities throughout the annual cycle. Using distributional projections, we calculated metrics describing the phylogenetic dispersion of passerine communities each week of the year. We then tested the relationship between seasonal turnover in community phylogenetic dispersion and seasonal variation in species richness and proportion of migratory species. C_LIO_LISeasonal migration, by changing spatial patterns of avian diversity, simultaneously drives a complex continental redistribution of phylogenetic community structure. We find evidence of taxonomic scale dependency to our results, wherein throughout North America, the seasonal influx of migrant passerines yields communities that are overall more phylogenetically clustered, yet also exhibit greater phylogenetic overdispersion at smaller taxonomic scales. C_LIO_LISeasonal shifts in phylogenetic dispersion, though complex, track changes in diversity, manifesting as fluctuations in phylogenetic dispersion between northern and southern regions as seasonal migrants move between these regions. Our findings reveal a dynamic continental landscape of phylogenetic community structure directed by the movements of seasonal migrants. C_LI

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.

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.

Short-term population dynamics are shaped by both external environmental stochasticity and endogenous ecological dynamics. The extent to which population trajectories maintain predictable temporal structure reflects underlying determinism and sets limits on inherent forecastability. Permutation entropy quantifies this intrinsic predictability using the relative frequency of short fluctuation motifs. However, requirements for long timeseries have restricted ecological applications. Here, I introduce a Bayesian hierarchical regression framework, incorporating entropy-neutral priors, that estimates expected permutation entropy from shorter, spatially-distributed ecological datasets. I validate the approach's capacity to detect the impact of increasing environmental variance through simulations. Applied to four decades of UK butterfly data, the approach identified increasing permutation entropy across 35 species, consistent with an increasing role of stochastic weather events. Outlier weather events did not have a consistent relationship with permutation entropy, highlighting the potential for environmental forcing to both disrupt and constrain trajectories. With this flexible approach, permutation entropy offers complementary perspectives on longstanding questions around forecasting and population dynamics.

Equivalent numbers represent biodiversity as the effective number of equally distinct units, typically species, and can be partitioned across scales. In practice, they summarize each unit of biodiversity by a single value and compare units pairwise, misrepresenting units that are better described as distributions and the relationships between several units that share the same space. We introduce an equivalent-number index for assemblages of units represented as probability density functions (PDFs) over a continuous space, estimated as the integral of the pointwise maximum across abundance-weighted PDFs. Resulting equivalent PDF numbers fulfil elementary properties of classical equivalent numbers, and support additive partitioning across any number of nested scales. We illustrate the framework with case studies across three domains: (1) measuring trait diversity considering intraspecific variability in grasslands, (2) partitioning realized bioclimatic niches among clades of Carnivora, and (3) understanding seasonal changes in the partitioning of fish home ranges in geographic space.

The shape of density-dependence governs species persistence, and ecosystem stability. Yet, whether per-capita growth declines sublinearily, or superlinearily with density remains hotly debated. Growth rates across the tree of life have been shown to decline sublinearly with density, whereas theory founded on resource competition predicts the opposite. Here, we resolve this discrepancy and show that sublinearity can readily emerge from geometric constraints on consumer interactions. By linking inter individual spacing, movement and interference rates, we derive two limiting-interference regimes, one of which the well-mixed limit recovers the form of classic Beddington DeAngelis interference response. We then developed an individual-based model from first principles which reproduces the derived sublinearity response, and further use empirical data from published consumer-resource experiments that also bears the signature of sublinear density-dependence. Further, embedding the interference mechanisms underlying the emergence of sublinear density-dependence in coexistence theory opens a new regime for species coexistence where classical theory fails to predict. Our framework indicates that non-consumptive interactions are not merely a correction to resource competition but might be a distinct axis along which diverse communities may potentially coexist.

Although cities are increasingly recognized as ecological islands, a unified framework explaining their susceptibility to alien plant invasion remains lacking. Using the most recent and comprehensive global dataset of urban alien plants, we modelled alien richness, mimicking island biogeography theory (IBT). Across all models, neither city size nor geographic isolation independently explained alien richness. Instead, richness was consistently associated with their interaction, supporting the central IBT prediction. However, the strength of this interaction depends on how city size was quantified, with socio-economic dimensions exhibiting stronger positive interactions with geographic isolation than physical measures of city size. Introduction-hub identity further modified these relationships. North America was the only hub for which the interaction between city size and isolation was consistently weakened, indicating that donor regions of alien plants are not ecologically equivalent. Simulations of simultaneous increases in city size and isolation showed that larger, more connected cities generally accumulated more alien plants despite increasing geographic distance, but the magnitude and direction of these responses are hub dependent. Our findings inspire an extension of classical IBT to a mechanistic explanation for global variation in urban alien plant richness in this increasingly urbanized and globally connected world.

Understanding how species interactions, ecological drift, and immigration jointly shape community composition is a central goal of community ecology. These processes determine not only average community composition, but also how often different community states occur. Here, we ask how competition reshapes the neutral distribution of community composition generated by drift and immigration. We analyze a stochastic two-species competition model with immigration and derive the stationary distribution of relative species composition near neutrality. The stationary distribution shows when communities are usually balanced and when they are instead dominated by one species. Species dominance can become common even when the corresponding deterministic model predicts stable coexistence, particularly in smaller communities. Balanced and dominance states can also occur together, producing a trimodal distribution. Competitive asymmetry further biases the distribution toward the competitively favored species. Thus, the interplay between competition, ecological drift, and immigration determines not only how much community composition varies, but also which community states are most likely to be observed. Our results provide an analytical bridge between neutral and competition theory and a framework for interpreting variation in community composition.

Translating Tilman resource-ratio model (R) to the metacommunity scale bridges local plant competition and landscape dynamics, moving ecological niche theory beyond controlled experiments. By incorporating scale dependence, stochasticity, dispersal limitation, and the stress-disturbance dichotomy, this framework also accounts for the drivers of both alpha and beta diversity. To achieve this integration, this work presents the Metacommunity Resource-Ratio Model (MetcommR) and its graphical tool, the Patchwork Biplot. This approach adapts the traditional continuous plane with a granular patch space, where each patch represents a discrete community with its area and internal variability, tracking net vectors of resource consumption and release relative to species-limiting isoclines. MetcommR articulates two fundamental regimes. In disturbance-governed metacommunities, biomass loss releases resources, interrupting depletion and preventing competitive exclusion, which promotes coexistence via the competition-colonization trade-off and maintains alpha and beta diversity. Conversely, in stress-governed systems, biomass accumulation and severe resource scarcity push communities toward isoclines, favoring the monodominance of tolerant species through competitive exclusion under the tolerance-fecundity trade-off. We demonstrate the model's empirical utility through a Cerrado case study in the Paraopeba Reserve. Analyzing canopy openness (light) and soil nitrogen reveals that long-term fire suppression induces light stress, elevating competitive exclusion risks for shade-intolerant species. Consequently, the Patchwork Biplot serves as a tool for evaluating ecological dynamics and vulnerabilities to guide management and conservation strategies.

Early-life phenotypes frequently predict adult phenotypes through developmental 'silver-spoon' carry-over effects, but how strongly and under what circumstances? Using 40 years of individual-based data from a great tit (Parus major) population, we used covariance reaction norms to understand how the natal-to-adult body mass association shifts across temperature, rainfall, and population density gradients during both life stages. We show that the natal-adult mass correlation is substantial (r {approx} 0.7) but strongly environment-dependent. Reaction norm shapes across climatic and density axes point to distinct mechanisms, including compensatory growth under benign adult conditions and density-dependent modulation of early-life differences. We further show that the conditions experienced in adulthood largely drive these patterns and determine whether early-life advantages are retained, even when explicitly tested within an environmental-matching paradigm. Decomposing the correlation using 38 generations of pedigree data revealed no evidence of gene-by-environment interactions. Instead, the observed phenotypic correlation reaction norms could be attributed almost entirely to environmentally-sensitive non-genetic individual differences. Overall, our findings show that climatic and demographic shifts can substantially reshape developmental carry-over without altering the genetic architecture tying body mass across life stages, with implications for how reliably early-life mass can predict individual quality and adult traits in wild animal populations.