Ecology Letters

A recent study by Van Dyke et al.1 paired experimental drought manipulations with demographic models and trait measurements to project major shifts in coexistence among a number of annual plant taxa. However, re-analysis of the data under alternative, more predictive competition models reveals that the authors original conclusions are very sensitive to slight variations in model form. Furthermore, propagating model parameter error into coexistence predictions results in relatively weak support for the majority of coexistence shifts predicted by the authors original model. These results highlight the need for increased statistical rigor when treating binary predictions of species coexistence as observed experimental outcomes, as is commonly practiced in empirical coexistence studies.

Predicting the outcome and strength of species interactions is a central goal of community ecology. Researchers have proposed that outcomes of species interactions (competitive exclusion and coexistence) are a function of both phylogenetic relatedness and functional similarity. Studies relating phylogenetic distance to competition strength have shown conflicting results. Work investigating the role of phylogenetic relatedness and functional similarity in driving competitive outcomes has been limited in terms of the breadth of taxa and ecological contexts examined, which makes the generality of these studies unclear. Consequently, we gathered 1,748 pairwise competition effect sizes from 269 species and 424 unique species pairs with divergence times ranging from 1.14 to 1,275 million years and used meta-regression and model selection approaches to investigate the importance of phylogenetic relatedness and functional similarity to competition across ecological contexts. We revealed that functional similarity, but not phylogenetic relatedness, predicted the relative strength of interspecific competition (defined as the strength of interspecific competition relative to intraspecific competition). Further, we found that the presence of predators, certain habitats, increasing density of competitors, and decreasing spatial grain of experiments were all associated with more intense interspecific competition relative to intraspecific competition. Our results demonstrate that functional similarity, not phylogenetic relatedness, may explain patterns of competition-associated community assembly, highlighting the value of trait-based approaches in clarifying biotic assembly dynamics.

Ecological communities are often composed of many species, each interacting in complex ways. This complexity makes predictions of species responses to disturbances challenging. Here, we analyze dynamical community models and reveal an unexpectedly simple principle: species stability is governed by a single metric--self-regulation loss (SL). SL quantifies the importance of self-regulatory processes in species population dynamics. In effect, SL captures a collective outcome of species interactions, organizing how individual species respond to disturbances. When applied to data from protist community experiments, SL accurately forecasts species responses to temperature changes. Our work reveals that, despite the complexity of ecological systems, species stability follows a remarkably simple organizing principle.

The timing of life-cycle events (phenology) is key to organism ecology and success. Climate change is shifting phenology to earlier dates globally, but generalizable trends of how phenological change impacts demography are still unknown. Therefore, we conducted a meta-analysis to quantify the effects of interannual phenological variation and phenological shifts on demographic vital rates (survival, growth, and reproduction). Our dataset includes 138 taxa from 83 studies, representing different study approaches (observational and experimental) for plants and animals. Using these data, we asked three primary questions: 1). How does phenological variation affect demographic vital rates? 2). Are directional shifts in phenology predictive of changes in demographic vital rates? 3.) Do relationships between phenology and demography depend on taxa, vital rate, and study type? For studies of phenological variation, earlier events conferred demographic benefits whereas later events were associated with demographic costs, with most of the evidence coming from bird and reproduction-focused studies. In contrast, directional phenological shifts were not predictive of demographic responses over time or in experiments. While there was evidence that phenological events shifted earlier through time, there was not significant change in demographic vital rates over those same time periods. These results are consistent with the hypothesis that organisms may be able to track environmental conditions to maintain demographic performance by shifting their phenology to earlier dates under climate change. Critically, our meta-analysis clarifies that while earlier phenological events tend to confer demographic benefits in the context of phenological variation, directional phenological shifts to earlier timing did not show demographic benefits.

Understanding the drivers of species coexistence is an important objective in ecology. Yet, the multitude of methods to study coexistence hampers cross-community comparisons. Here, we standardized niche and fitness differences (i.e how species limit themselves compared to others and their competitive ability, respectively) across 1018 species pairs to investigate species coexistence across ecological groups and methodological settings (experimental setup, natural co-occurrence, population model used, and growth method). We find that, first, coexistence is driven by large niche differences, not by small fitness differences. Second, species group into clear clusters of coexisting and non-coexisting species along the niche axis. Finally, these clusters are not driven by ecological or methodological settings. This suggests differences between coexisting and non-coexisting communities transcending those measured in our empirical systems. Overall, our results show that species coexistence is mainly influenced by mechanisms acting on niche differences.

Analysis of long-term trends in abundance provide insights into population dynamics. Population growth rates are the emergent interplay of fertility, survival, and dispersal, but the density feedbacks on some vital rates (component) can be decoupled from density feedback on population growth rates (ensemble). However, the mechanisms responsible for this decoupling are poorly understood. We simulated component density feedbacks on survival in age-structured populations of long-living vertebrates and quantified how imposed nonstationarity (density-independent mortality and variation in carrying-capacity) modified the ensemble feedback signal estimated from logistic-growth models to the simulated abundance time series. The statistical detection of ensemble density feedback was largely unaffected by density-independent processes, but catastrophic and proportional mortality eroded the effect of density-dependent survival on ensemble-feedback strength more strongly than variation in carrying capacity. Thus, phenomenological models offer a robust approach to capture density feedbacks from nonstationary census data when density-independent mortality is low.

Ecological communities are assembled by colonization and extinction events, that may be regulated by ecological niches1-5. The most parsimonious explanation of local community assembly is the Dynamic Equilibrium (DE) model, which assumes that community dynamics is shaped by random colonization and extinctions events, effectively ignoring the effects of niches1, 6. Despite its empirical success in explaining diversity patterns1, 5, 7, it is unknown to what extent the assembly dynamics of communities around the globe are consistent with this model. Using a newly developed methodology, we show that in 4989 communities from 49 different datasets, representing multiple taxa, biomes and locations, changes in richness and composition are larger than expected by DE. All the fundamental assumptions of DE are violated, but the large changes in species richness and composition primarily stem from the synchrony in the dynamics of different species. These results indicate that temporal changes in communities are predominantly driven by shared responses of co-occurring species to environmental changes, rather than by inter-specific competition. This finding is in sharp contrast to the long-term recognition of competition as a primary driver of species assembly8-12. While ecological niches are often thought to stabilize species diversity and composition4, 13, 14, we found that they promote large changes in ecological communities.

Increases in land use intensity (LUI) reduce species richness. However, we have a poor understanding of how underlying coexistence mechanisms are altered by land use and whether diversity loss occurs due to changes in plant-plant interactions (competition and facilitation) or in species intrinsic growth rates. We expect that LUI could reduce stabilizing niche differences and the indirect interactions that promote coexistence (e.g., intransitivity), while increasing competitive inequalities between species. To test the importance of these different processes, we use 8-yr time series from 150 grasslands differing in LUI to evaluate the role of direct and indirect interactions in promoting coexistence between 50 plant species. We show that LUI reduces the number of coexisting species mostly by causing a non-linear reduction in niche differences, rather than by enhancing competitive inequalities. However, surprisingly, niche differences remained important in stabilizing coexistence between those species remaining at high LUI. Indirect interactions were generally less important than direct ones, and played a moderate role in promoting coexistence in smaller assemblages of species at intermediate LUI. Our models could accurately reproduce the decline in diversity seen with LUI, indicating that our time series approach captures the important interactions between species. By analyzing land use effects through recent advances in structural stability applied to community ecology we provide a more mechanistic understanding of its effects. Our results highlight the importance of identifying the niche differences that are lost with increasing LUI, to better predict and manage effects of land use on biodiversity. Significant statementHuman land use is a major threat to grassland biodiversity. Grasslands with high rates of fertilization, grazing and mowing, contain many fewer plant species. Knowing the underlying causes is necessary for a better management of biodiversity. Here we apply ecological theory to spatiotemporal data on changes in plant abundance in managed grasslands in central Europe. We show that the observed decline in diversity can be explained by how interactions among plant species change with increases in land use intensity. In particular, intensive land use removes the stabilizing effect of self-limiting processes that buffer species against extinction as well as limit competitive dominance. Therefore, actions to promote these stabilizing dynamics among interacting species seem key to restore plant diversity.

Substantial anthropogenic changes to the environment have motivated efforts to quantify temporal trends in population dynamics. While most ecological research has focused on the mean and variance of population density and reproduction, the frequency of these fluctuations through time may also be changing. We analyzed 1,563 datasets of population density and 1,456 datasets of plant reproduction (masting) across the globe. The average frequency of fluctuations increased by [~] 0.5 - 3% per decade within each time series, representing a moderate change (Cohens d {approx} 0.4) over a period of 60 years. We tested four hypothesized mediators of this trend: increased temperature, increased frequency of environmental forcing, increased intrinsic growth rate, and increased distance from a saddle at zero density. Although all hypotheses were rejected, changes in the frequency of environmental forcing and intrinsic growth rate exhibited positive correlations with changes in population fluctuation frequency as expected. Our results suggest that successive peaks in population and masting density fluctuations are becoming closer in time, which may reduce the effectiveness of predator satiation, resilience of food-webs, and the risk of critical transitions, such as population extinction. We suggest some alternative hypotheses for what may underlie this surprising global pattern.

Model microbial communities are regularly used to test ecological and evolutionary theory as they are easy to manipulate and have fast generation times, allowing for large-scale, high throughput experiments. A key assumption for most model microbial communities is that they stably coexist, but this is rarely tested experimentally. Here we report the (dis)assembly of a five-species microbial community from a metacommunity of soil microbes that can be used for future experiments. Using reciprocal invasion from rare experiments we show that all species can coexist and we demonstrate that the community is stable for a long time ([~]600 generations). Crucially for future work, we show that each species can be identified by their plate morphologies, even after >1 year in co-culture. We characterise pairwise species interactions and produce high-quality reference genomes for each species. This stable five-species community can be used to test key questions in microbial ecology and evolution.

The relative arrival time of species can affect their interactions and thus determine which species persist in a community. Although this phenomenon, called priority effect, is widespread in natural communities, it is unclear how it depends on the length of growing season. Using a seasonal stage-structured model, we show that differences in stages of interacting species could generate priority effects by altering the strength of stabilizing and equalizing coexistence mechanisms, changing outcomes between exclusion, coexistence, and positive frequency dependence. However, these priority effects are strongest in systems with just one or a few generations per season and diminish in systems where many overlapping generations per season dilute the importance of stage-specific interactions. Our model reveals a novel link between the number of generations in a season and the consequences of priority effects, suggesting that consequences of phenological shifts driven by climate change should depend on specific life histories of organisms.

Theory and experiments show that diverse ecosystems often have higher levels of function (for instance, biomass production), yet it remains challenging to identify the biological mechanisms responsible. We synthesize developments in coexistence theory into a general theoretical framework linking community coexistence to ecosystem function. Our framework, which we term functional coexistence theory, identifies three components determining the total function of a community of coexisting species. The first component directly corresponds to the niche differences that enable pairwise species coexistence, and to the complementarity component from the additive partition of biodiversity effects. The second component measures whether higher functioning species also have higher competitive fitness, providing a missing link between the additive partitions selection effect and modern coexistence theorys concept of equalization. The third component is least well-studied: reducing functional imbalances between species increases niche differences positive effect on function. Using a mechanistic model of resource competition, we show that our framework can identify how traits drive the effect of competition on productivity, and confirm our theoretical expectations by fitting this model to data from a classic plant competition experiment. Furthermore, we apply our framework to simulations of communities with multiple ecosystem functions or more than two species, demonstrating that relationships between niche, fitness, and function also predict total function beyond the case studied by classical theory. Taken together, our results highlight fundamental links between species coexistence and its consequences for ecosystem function, providing an avenue towards a predictive theory of community-ecosystem feedbacks.

This preprint of a book chapter presents the newly proposed Equilibrium Theory of Biodiversity Dynamics (ETBD), whose aim is to conceptualize large-scale dynamics of species richness via addressing the population size-dependence of speciation and extinction rates, the resulting diversity-dependence of these rates, and their modulation by the environment. It provides the most general framework for understanding large-scale biodiversity patterns such as the latitudinal diversity gradient (LDG) and temporal patterns of biodiversity changes. The theory has been published elsewhere in its full form that includes all the derivations (Okie & Storch 2004, American Naturalist https://doi.org/10.1086/733103), but here it is presented in a simpler and user-friendly way, focusing on its major implications comprising macroecological scaling relationships between energy (or resource) availability, species richness and community abundance.

A recent paper by Enquist and colleagues1 took a very important step in predicting the ecosystemic effects of species losses on a global scale. Using Metabolic Scaling Theory (MST), they concluded that large-sized species contribute disproportionately to several ecosystem functions. One of their key predictions is that total biomass of animals in a trophic level (MTot, using their notation) should increase more than proportionally with its maximum body size (mmax), following the relationship MTot {propto} mmax5/4. Here I argue that this superlinear scaling results from an incorrect representation of the individual size distribution and that the exponent should be 1/4, implying a sublinear scaling. The same reasoning applies to total energy flux or metabolism BTot, which should be invariant to maximum size according to the energetic equivalence and perfect compensatory responses entailed by MST.

Despite its global importance, our ability to predict the impacts of temperature change on the community dynamics of heterotrophic microbes remains limited. Here, we develop a metabolic trait-based mathematical framework to predict the temperature dependence of pairwise interactions among heterotrophic microbial consumers, accounting for their resource environment and community composition. Applying this framework leads to two general predictions. First, microbial species interactions are typically more thermally sensitive than the underlying metabolic traits. Second, temperature systematically reshapes intra- and interspecific interactions: their variance peaks at intermediate temperatures, while mean interaction strengths increase with warming more rapidly than interspecific interaction strengths. We show that these features of temperature-dependent interactions have far-reaching implications for the temperature responses of community coexistence, diversity, and stability. Our framework provides a mechanistic foundation for predicting how temperature affects the dynamics of heterotrophic microbial communities across diverse biological and environmental contexts. SignificanceCommunities of heterotrophic microbes, including bacteria, archaea, protists, and fungi, play a fundamental role in human health, bioprocessing, and global biogeochemical cycles. Predicting their responses to environmental change is a major challenge, with a key missing link being the effects of temperature on species interactions that ultimately shape community dynamics. By integrating metabolic constraints into consumer-resource theory, we derive general predictions about how interactions among heterotrophic microbial species respond to temperature changes. We show that interactions are more sensitive to warming than individual metabolic traits and undergo systematic temperature-dependent changes that alter community-level coexistence, diversity, and stability. These results hold across diverse environmental contexts and heterotrophic systems, providing a foundation for predicting how microbial community dynamics respond to environmental temperature, from biotechnological applications to natural ecosystems.

Numerous studies have shown that nutrient enrichment causes the loss of plant diversity in different grasslands across the globe. Thus far, three main hypotheses (niche dimension, competitive asymmetry, and soil acidification) have been proposed to account for this general phenomenon, but our knowledge of the underlying mechanisms remains rather vague. To reveal the cryptic mechanisms, we analyzed the famous long-term Park Grass Experiment (1856-) under modern coexistence theory by fitting Lotka-Volterra competition models with time-series data from the different treatments (15 different combinations of nutrient addition fully crossed with four levels of soil pH) to quantitatively test the three competing hypotheses. Supportive of the competitive asymmetry and soil acidification hypotheses, both nutrient addition and soil acidification overall decreased intrinsic population growth rates (r) and intensified competitive differences or asymmetries dramatically, which mostly favored grasses over forbs and legumes (and also forbs over legumes). These changes in r and competitive differences or asymmetries are generally consistent with the abundance changes of different functional groups following the various treatments. Moreover, the altered r (determining species existence) and competitive differences (affecting species coexistence) effectively explained the diversity loss and recovery (after nitrogen addition was withheld). However, while nutrient addition significantly decreased per-capita intra- and inter-specific competition (which indicates that belowground competition becomes less important when soil nutrients are more abundant), it did not decrease niche differences as predicted, poorly supporting the niche dimension hypothesis. These findings advance our understanding of fundamental mechanisms driving the response of plant communities to nutrient deposition in nature. Significance StatementAn unresolved fundamental scientific mystery with the crucial applied value in ecology is what causes the general loss of biodiversity following nutrient enrichment in the Anthropocene. In this study, we combined the recent advance in coexistence theory with the longest-running experiment existing in the world to wrestle with this conundrum. Our major results, which highlight the critical role of both existence and coexistence, are helpful in settling the debate between the three popular hypotheses and also, for the first time, provide quantitative explanations for the general findings in numerous nutrient-addition experiments. Our study shows the importance of applying modern coexistence theory to more quantitatively explain, predict and cope with the responses of ecological communities to global change factors in nature.

Understanding how ecological communities respond to environmental change remains a key challenge for biodiversity monitoring. To characterize such responses, we need tools that capture how coherently species respond across a community, and to predict their consequences, we must account for ecological interactions. We first introduce the Ecological Coherence (EC) framework, which describes how species co-responses are structured within a community. Building on this foundation, we extend it to Ecological Network Coherence (ENC), which embeds co-responses within the network of interactions by restricting them to interacting species. Both are expressed through two complementary representations: a response correlation matrix and the distribution of its values. The first can reveal aspects such as coherent or incoherent modules and the roles species play in shaping coherence, whereas the second provides a profile whose shape may serve as an early-warning indicator of instability. These can be applied to both intrinsic responses (environmental performance) and realized responses (abundance dynamics), derived from currently available monitoring data. We illustrate this approach in two empirical systems: a tropical pollination network, where interacting mutualists were more coherent in their temperature responses than the broader community, and a marine food web, where coherence in abundance trends shifted during collapse. Using a Lotka-Volterra model, we further show that ENC distributions with higher variance--reflecting stronger positive and negative co-responses--increase the risk of instability or amplification in dynamics. We also find that species influential in both the correlation matrix and the interaction matrix are key drivers of major dynamic shifts. These results point to the importance of further exploring ENC distributions as potential early-warning indicators of ecological disruption.

Forecasting responses of natural populations to increasingly stochastic environments is a major challenge in Ecology and Conservation Biology. We now know that populations can modulate how their vital rates (e.g., survival, reproduction) change through time to minimise the negative impacts of environmental stochasticity. However, despite the important analytical and theoretical advances that have led to this knowledge, we still do not know (1) how much this ability of natural populations to buffer against environmental stochasticity can vary in nature, nor (2) the drivers of these strategies, with likely candidates including the environmental regimes themselves, as well as the life history traits and phylogenetic ancestry of the species of interest. To address these questions, we parameterised a Bayesian generalised linear mixed model with high-resolution vital rate data from 134 natural populations across 89 species of plants and animals. We show that population responses to environmental stochasticity vary three orders of magnitude along a demographic buffering continuum. Furthermore, the position of a given population along said continuum is predicted by a survival-reproduction trade-off and by the degree of aridity the population experiences. Our findings open a promising avenue of research to improve ecological forecasts and management of natural populations in the Anthropocene.

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.

The niche is a key concept that unifies ecology and evolutionary biology. However, empirical and theoretical treatments of the niche are mostly performed at the species level, neglecting individuals as important units of ecological and evolutionary processes. So far, a formal mathematical link between individual-level niches and higher organismal-level niches has been lacking, hampering the unification of ecological theories and more accurate forecasts of biodiversity change. To fill in this gap, we propose a bottom-up approach to derive population and higher organismal-level niches from individual niches. We demonstrate the power of our framework by showing that 1) the statistical properties of higher organismal-level niches (e.g. niche breadth, skewness etc.) can be partitioned into individual contributions; 2) the species-level niche shifts can be estimated by tracing the responses of individuals. Our method paves the way for a unifying niche theory and enables mechanistic assessments of organism-environment relationships across organismal scales.