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Understanding the effects of climate change on ecological communities has been limited by a lack of general theory for how temperature affects competition. To fill this knowledge gap, we integrated Modern Coexistence Theory and the Metabolic Theory of Ecology by incorporating empirically derived temperature sensitivities into Modern Coexistence Theory's central model. We then simulated warming in consumer-resource systems and found that warming reduced both niche and fitness differences, making species more ecologically similar and competitive interactions more neutral. The greatest shifts in competition occurred when temperature sensitivities among species were highly asymmetrical. Effects of warming on competition via niche differences were comparable to those on fitness differences, suggesting that the emphasis on vital rates in global change research may overlook key biodiversity drivers. This general theory expands the domains of two prominent ecological theories and provides predictions for how warming may alter competition even in benign regions of species' thermal niches.

Accurate prediction of community assembly is a central goal in ecology but is challenging because assembly is governed by numerous mechanisms. Few theoretical models explicitly incorporate or test multiple mechanisms at once. We empirically tested the predictive performance of a plant community assembly model built using all possible combinations of four 'mechanisms' (soil resource competition, dispersal and colonisation, spatiotemporal niche differentiation, population growth rates) and 11 underlying 'attributes' based on measured traits (e.g., fecundity, phenology). The full model accurately predicted out-of-sample biomass observations of five grasses sown in mixture along a soil nitrogen gradient (overall R2 = 0.65). Alternative model variants, parameterised using subsets of the mechanisms and their nested attributes, still retained high explanatory power if the model included at least three of the four mechanisms. Our results suggest that plant community composition is determined by simultaneous effects of multiple mechanisms, and simpler theories have much lower predictive abilities.

Z. Tao, K. Zhang, R.M. Callaway, E. Siemann, Y. Liu, and W. Huang, "Native Plant Diversity Generates Microbial Legacies That Either Promote or Suppress Non-Natives, Depending on Drought History," Ecology Letters 27, no. 9 (2024): e14504, https://doi.org/10.1111/ele.14504. The above article, published online on 2 October 2024 in Wiley Online Library (http://onlinelibrary.wiley.com/), has been retracted by agreement between the journal Editor-in-Chief, Peter H. Thrall; and John Wiley & Sons Ltd. Concerns about the data were raised by one of the journal editors. Following publication, the editors identified unusual repetitive patterns in the data underlying the study. The editors concluded that the patterns, identified using common statistical analysis tools, were unlikely to have occurred by chance from a typical environmental data collection effort. When asked about the concerns, the authors shared some raw data but were unable to provide a satisfactory explanation to the editors for the patterns in the published data that the editors could not reconcile with the study's conclusions. When later presented with the possibility of retraction and a draft retraction statement, the authors disagreed strongly and provided a detailed rebuttal of the editors' assessment. They argued in part that the software tools the editors used to identify the duplication patterns had not been peer reviewed or otherwise validated. As part of an extensive investigation of the authors' rebuttal claims, the publisher consulted an anonymous and independent subject matter expert (SME), who confirmed the findings of the editors and noted that the repetitive patterns observed in the underlying data were inconsistent with the reliability required to support the article's conclusions. As a result of the post-publication review by the SME, the editors affirm that they have lost confidence in the results and conclusions. In line with the journal's editorial policies, the editors determined that unresolved concerns regarding data reliability warranted retraction. The authors disagree with the retraction.

The niche concept is central to ecology, evolution, and conservation biology. To assess resource dynamics in biological communities, the most widely used niche metrics are niche breadth and niche overlap. Colwell and Futuyma (1971) were the first to propose niche metrics that incorporated resource distinctness. In their framework, niche breadth and overlap are calculated using either a relative weighting factor d j or an absolute weighting factor δ j . Hanski (1978) later introduced an alternative weighting factor δ j ∗ , which accounts for both the quality and quantity of resource states in niche calculations. However, metrics based on d j , δ j and δ j ∗ have inherent mathematical and conceptual limitations. To overcome these issues, the present study introduces modified forms of these factors ( e d j , e δ j and e δ j ∗ ) and evaluates their performance using eight hypothetical and one empirical (ecological) resource matrix. The findings indicate that niche metrics incorporating the e d j factor represent the most coherent and biologically meaningful option.

The storage effect is a general explanation for ecological coexistence, wherein different species specialise on different states of a fluctuating environment, for example, hot versus cold years. Despite the storage effect's prominence in theoretical ecology, we lack evidence on whether it maintains biodiversity in nature. Here, we examine five storage effect pathways in a community of 11 coral species from the Great Barrier Reef, using detailed size-structured demographic data collected over 5 years. We parameterize integral projection models, simulate coral communities, and quantify coexistence mechanisms through Modern Coexistence Theory. Fluctuations in survival and fecundity promote coexistence via the storage effect, but this stabilising mechanism is typically small compared to fitness differences. Despite exhibiting prerequisites for strong temporal niche partitioning, the storage effect cannot explain the coexistence of many species. Diversity maintenance likely requires large net contributions from other mechanisms, such as specialist natural enemies or spatial heterogeneity coupled with source-sink dynamics.

Although habitat area and isolation are considered key factors influencing plant disease and herbivory, their specific mechanisms remain underexplored within island biogeography. We investigated the direct and indirect effects (via community functional traits) of island area and isolation on plant disease and herbivory across 21 tropical islands in the South China Sea. Community-weighted mean leaf area (CWM LA) was the most significant functional predictor at the community level. Decomposing CWM LA revealed isolation primarily drove species turnover (LA_STE; 99.99% of the relative explanatory power), whereas area mainly influenced intraspecific variation (LA_ITV; 60.42% of the relative explanatory power). Isolation-mediated species turnover indirectly amplified disease and herbivory, likely through adaptive trait shifts favouring resource acquisition. Island area had no significant effect on disease and herbivory at the community level. This study reveals the complex roles of area and isolation in plant biotic risks, underscoring the utility of island biogeography theory.

Modern Coexistence Theory (MCT) has long aimed to predict community structure, but empirical support remains scattered across unconnected case-studies from a narrow subset of systems where it is possible to quantify niche and fitness differences (e.g., pairwise interactions between fast-growing plants or protists). We sought a framework to apply MCT to a broader range of ecological scenarios by combining eDNA dietary data with life-history traits of mammal herbivores from diverse communities across three African savannas. Although this first application of the framework treated dietary niche differentiation as the sole mechanism for coexistence, it unveiled three conclusions about multispecies coexistence. First, dietary niche differentiation promoted coexistence but was insufficient to explain observed coexistence for all species. Second, modelled coexistence patterns in herbivore communities could not be predicted from species-level traits or pairwise comparisons. Third, herbivore diversity is generally robust to reductions in the number of plant resources, particularly when there is more dietary specialisation.

Understanding how species assemble across landscapes requires integration of data representing evolutionary, ecological, and biogeographic processes. We developed a comparative macrogenetic framework, applying it across 22 co-distributed rainforest trees, to identify replicated landscape-level genetic signatures. Diversity-migration analyses and genogeographic clustering identified shared spatial dynamics in relation to refugial areas and genetic turnover, but with no direct relation to simple functional trait combinations. Three broad patterns emerged: Higher Northern Diversity with southward migration, Higher Southern Diversity with northward migration, and Homogeneous Diversity with no directional migration. We identified five (post hoc) species groups sharing gene flow and isolation-by-distance dynamics in relation to recognised biogeographic barriers. Replicated genetic signatures highlight how assembly processes emerge from interacting ecological and historical filters rather than single traits or biogeographic histories alone. We present a statistically replicable interpretational framework to identify shared evolutionary and ecological dynamics, offering scalable, management relevant tools to support restoration planning and biodiversity conservation under environmental change across all types of vegetation.

Tree species richness-productivity relationships (SPRs) at community level are generally positive but can weaken at individual levels due to increased competition. Using 12 years of growth data from a large forest biodiversity experiment, we examined effects of neighbourhood tree species richness, basal area, and niche differences on focal tree growth over time. As stands aged, the effect of greater neighbourhood basal area in more species-rich neighbourhoods on focal tree growth shifted from positive to negative, but this negative effect was offset by increasingly positive effects arising from greater niche differentiation between focal trees and their neighbours. Focal trees with acquisitive traits showed stronger growth responses to neighbourhood competition and niche difference; while the responses to neighbourhood richness were more positive in dry than in wet years. Our findings suggest that larger niche differences can balance increased competition in more species-rich forest stands, thus allowing these stands to maintain a greater total biomass than less diverse forest stands.

Host diversity can strongly influence disease prevalence, but whether it dilutes or amplifies disease remains debated. We applied community assembly theory to examine whether conditionality from abiotic and biotic filtering could explain variation in rodent diversity and Sin Nombre hantavirus (SNV) prevalence across 24 locations in the southwestern United States. Overall, community composition, not diversity per se, drove diversity-disease relationships. Environmental factors determined community composition, which regulated primary host abundance and SNV infection via resource competition. Across roughly half the communities, dilution effects emerged because added species increased dietary overlap, reducing focal host abundance and SNV infection. In other communities, environmental and biotic structuring favoured competitors, suppressing host abundance and SNV infection across diversity levels. Our results highlight how environmental structuring and substitutive assembly processes interact to influence diversity-disease patterns. Community assembly theory provides a framework for integrating abiotic and biotic processes to inform landscape-scale disease patterns.

Biological community dynamics arise from both deterministic and stochastic processes. While species' responses to environmental factors define attractors of community structure, stochasticity, particularly during early assembly, can redirect ecological trajectories. However, quantifying such roles of stochasticity in community assembly has remained challenging. We tracked community assembly in two multi-replicated experimental systems, each with four levels of founding community size, analysing > 3000 samples across four time points. Stronger initial stochasticity led to greater divergence of both population- and community-level consequences. Strikingly, conspicuous differentiation into alternative trajectories of community assembly occurred when the absolute number of founding prokaryotic cells was less than the order of 104. Thus, quantitative differences in stochasticity produced qualitative differences in community fate. These results demonstrate that early stochastic events can have enduring impacts on ecological dynamics. Deeper quantitative insights into stochasticity will reorganise our views on biological invasions, agroecosystem microbiome management, and therapeutics of human-associated microbiomes.

Ecological forecasting is increasingly important for conservation. Predicting nocturnal bird migration events is a promising vehicle for forecasts but isn't often explored at fine temporal scales. We use weather surveillance radar to examine dynamic drivers of migration in 2-h periods throughout a night. We assess the relative importance of terrestrial, atmospheric and sampling predictors (which relate to radar position and scan timing) across spring and fall. Atmospheric conditions were consistently strong predictors. In contrast, terrestrial predictors contributed relatively little to explaining variation in activity. Sampling variables, such as time after sunset, varied in importance, with the highest influence shortly after sunset. We highlight the temporal variability in predictors of migration, emphasising it as a dynamic process, involving continuous decisions and adjustments rather than following fixed routes. We underscore the value of radar for capturing transitions between habitats while revealing key limitations and opportunities for understanding fine-scale migratory behaviour.

Clonality, the process of vegetative reproduction through belowground organs (rhizomes, stolons), occurs in about half of all plant species. It influences key ecological and evolutionary phenomena, including effective population size, meiosis frequency and genet longevity, which may affect diversification rates. This study investigates how clonality impacts diversification in angiosperms by comparing clonal, mixed and non-clonal genera. Using genus-level phylogeny and data on clonal status of 16,465 species across 2997 genera, we estimated speciation and net diversification rates for each genus with MoM, DR and BAMM. Our results reveal lower diversification rates in clonal genera in non-phylogenetic models, consistent with the hypothesis that clonality constrains diversification. This effect weakens when accounting for phylogenetic non-independence but remains significant overall. We show that monocots show a slightly stronger effect of clonality on diversification than eudicots. Our findings suggest that clonality may limit long-term diversification in angiosperms, influencing evolutionary dynamics where clonal reproduction predominates.

Collisions with anthropogenic structures kill billions of birds annually, yet risk factors remain poorly understood. Behavioural plasticity generally increases survival in changing environments, but its protective effects may be context-dependent. We assessed the link between behavioural innovation, a proxy for plasticity and collision incidence across 854 species and 259,873 lethal collision events involving buildings, communication towers and wind turbines. Overall, we found a significant positive residual correlation between innovation rate and collision incidence, independent of ecological covariates and phylogenetic relationships. However, this relationship was hazard-specific: innovativeness positively correlated with building collisions but showed no relationship with communication towers or wind turbines. Furthermore, collision risk was driven by food-related rather than technical innovations. Rather than demonstrating a universal mortality cost of cognitive capacity, our results suggest that opportunistic foraging behaviours may create ecological traps in structurally dense environments. Ultimately, behavioural plasticity can drive fitness consequences, but this risk is fundamentally context-dependent.

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Chemical cues play an important role in mammalian communication, often reflecting an individual's physiological state. Non-invasive sampling of such informative cues holds great potential for wildlife monitoring. Endangered apex predators such as big cats are elusive and challenging to monitor. While existing monitoring techniques estimate numbers or densities, they often fail to provide crucial demographic and physiological information. We adapted a headspace solid-phase field sampling technique adapted for sampling volatiles from urine and faeces of captive Bengal tigers and Indian leopards of known age and sex, and from urine of identified wild Bengal tigers of known age, sex, and reproductive status. Volatiles extracted from these samples were analysed using Thermal Desorption- Gas Chromatography-Mass Spectrometry. The random forest algorithm was used to identify compounds that might be cues for species, age, sex, and reproductive state. Species classification accuracy was consistently high with both urine (0.79 + 0.009) and scat (0.75 + 0.029) volatiles. Classification accuracy of urine volatiles was high for females and young individuals in leopards and tigers, but lower for males and old individuals. Scat volatiles performed better across groups. We also identified putative chemical markers for epilepsy and reproductive state in tigers. This study presents the first chemical characterization of tiger and leopard scats and the first sampling of tiger odours from the wild. Our simple and cost-effective method of sampling tiger and leopard odours offers a novel method of chemical fingerprinting to monitor populations in situ. Importantly, this sampling method and analytical pipeline is broadly applicable to other mammalian species for conservation and ecological studies.

Plants employ multiple strategies to adapt to their growth environment. Characterizing key dimensions in plant trait space is important for understanding functional diversity within ecosystems. Leaf and root functional traits have been studied in the context of resource economics, but whether they covary, and through which mechanisms, is still debated. We investigated this in subtropical forests by sampling root and leaf traits on individuals of co-existing species in two communities with different resource availability. We found largely non-correlated variation between leaf and fine root traits both across and within communities, and a clear decoupling between leaf economic spectrum and root economic space, independent of evolutionary history. Our results suggest that leaf-root trait relationships are shaped by an interplay between microenvironmental heterogeneity that drives decoupling and shared selection pressures promoting covariation. The interplay explains the weak observed coordination and highlights the importance of environmental context in predicting above- and below-ground plant functions.

Ecologists increasingly use complex models to predict and understand ecological systems and their responses to external drivers or anthropogenic pressures. An ongoing challenge in this context is quantifying and reducing uncertainty in model inputs, parameters and structure and understanding their implications for model predictions. Three major methodological fields have emerged in this context: sensitivity analysis, uncertainty analysis and model inversion or calibration. While these three methods are an integral part of any modelling or forecasting process, the corresponding literature is often scattered, and distinct terminology and definitions are used in different methodological and scientific contexts. Here, we review and connect these three fields and discuss best practices for their practical implementation with a focus on complex ecological models. We classify relevant types of uncertainty, discuss the complementary roles of sensitivity and uncertainty analyses, give an overview of available calibration methods and emphasize the importance of effective communication of uncertainty. We conclude that using state-of-the-art methods for understanding model behaviour as well as consistently accounting for all uncertainties is essential for correctly understanding model predictions and thus forms the basis for a responsible use of models in ecological decision making.

Cooperation in public goods is expected to evolve more rapidly in smaller groups than in larger groups because individuals receive a larger share of the benefits, reducing the benefits of freeloading. However, experimental evidence for this hypothesis remains limited to microorganisms, restricting our understanding of the evolution of cooperative traits. Here, we show that in the collectively defending larvae of Neodiprion sertifer, survival against predation is higher in cooperative groups, with benefits of cooperation more pronounced in small groups (5 larvae) than in large groups (20 larvae). Individuals also participate less in collective defence in larger groups, not because of higher life-history costs resulting from increased resource competition but because they adjust their contribution according to group size. These results provide novel empirical evidence that selection for cooperation in collective goods is group size-dependent, promoting cooperation in smaller groups, whereas the relative fitness of freeloaders is higher in larger groups.