Ecology Letters最新文献

Evolutionary rescue allows populations to adapt and persist despite severe environmental change. While well studied under density-independent conditions, the role of density dependence, including competition, remains unclear. Theoretical models offer conflicting predictions, with density dependence either increasing extinction risk or enhancing adaptation. We empirically tested how density dependence influences evolutionary rescue by exposing experimental populations to a stressful environment for six generations under density-dependent or independent conditions, with populations where either evolution was possible or was prevented by replacing individuals each generation. Density dependence suppressed population size and increased extinction risk, whereas density independence enabled rapid growth, especially in genetically diverse populations where evolution was possible. Although density dependence raises extinction risk, it does not prevent populations from responding to selection, since surviving density-dependent populations still exhibited increased intrinsic and realised fitness. These findings reconcile theoretical discrepancies, showing density dependence can simultaneously increase extinction risk but may favour adaptation. Our results underscore the importance of considering density dependence in conservation strategies.

Animal movements contribute to the spread of infectious diseases and are driven in part by environmental conditions. We investigated the links among the environment, animal movement, and infectious disease dynamics in waterfowl, which are among the primary wildlife hosts of avian influenza viruses. By combining telemetry data on 4606 individuals from 26 waterfowl species with data on land cover, weather, and vegetation, we found that waterfowl moved less in areas of higher land cover heterogeneity and higher human population density. Moreover, predicted waterfowl movement distances were weakly but positively correlated with distances between detections of H5N1 highly pathogenic avian influenza in wild waterfowl, suggesting that environmental conditions might contribute to the spread of this disease via their effects on bird movements. By considering wildlife movements alongside other drivers of infectious disease dynamics, such as livestock production and human mobility, we move closer to predicting outbreaks and informing interventions.

Traits that reduce predation success may evolve together, leading to repeated evolution of similar anti-predator syndromes. In butterflies, predation likely shapes wing shape and colour patterns, promoting either aposematic or deflective features. Here, we studied the evolution of hindwing tail shape and colour pattern across swallowtail butterflies. Using standardised museum specimen photographs, we quantified colour variation via computer vision and tail shape with geometric morphometrics. We found significant evolutionary correlations between colour patterns and hindwing tail shapes across the phylogeny. Long tails were linked to high-contrast stripes and marginal spots, while short tails were associated with simple, spotted patterns. While accounting for developmental constraints, we show that stripes, spots, and long tails evolved in correlation and likely form a visual syndrome promoted by natural selection to deflect predator attacks. These results provide evidence that selection can drive the coordinated evolution of complex anti-predator traits over large evolutionary timescales.

Biodiversity at the metacommunity scale is typically influenced by numerous environmental, spatial, biotic, and stochastic factors. These factors can simultaneously impact evolution in individual species, due to site-varying local selection pressures and the impact of connectivity for gene flow and genetic drift. Joint species distribution models (JSDMs) can estimate the relative impacts of environmental, spatial, biotic, and other drivers on community composition, but these models do not currently consider the impact of contemporary evolutionary change. We applied a JSDM to analyse simulated and experimental populations and communities that experience contemporary trait evolution. We found that it successfully partitioned variance contributed by environmental, spatial, and evolving phenotypic drivers, and also estimated site- and time-specific covariance. We further demonstrated how the model-estimated effect sizes of trait evolution for community composition can be used to test predictions about the underlying mechanistic drivers of eco-evolutionary dynamics in communities.

Despite widespread recognition of the dynamic nature of ecological interactions, the consequences for community persistence of the observed year-to-year changes in species interactions have remained overlooked. Our research bridges this gap, leveraging a uniquely high-quality dataset spanning 8 years and 12 independent sites—offering unparalleled resolution to examine plant-pollinator interactions. Here, we characterise year-to-year variation in plant-pollinator interactions and compare their structural stability (a robust theoretical measure describing species persistence) with that of null models simulating random rewiring. We discover that although most interaction changes (80%) are caused by species turnover, it is the temporal rewiring among permanent species that primarily enhances pollinator persistence. This interaction rewiring is not random and effectively boosts pollinator persistence despite being primarily determined by changes in the phenologies and abundances of the permanent pollinator species. While not fully optimised, these adaptive responses underscore the vital role of rewiring in fostering ecological stability amid a changing world.

Desallais, M., Arnoldi, J.-F. and Loreau, M. 2025. “Partitioning Net Biodiversity Effects on Ecosystem Resistance and Resilience.” Ecology Letters 28, no. 11: e70249. https://doi.org/10.1111/ele.70249.

In the author byline of the above published article, the last author (Michel Loreau) was only affiliated with Peking University and had only a (2) in superscript next to his name, even though he is affiliated with both institutions listed in the article. He should therefore have (1) added next to his name to indicate his affiliation with the CNRS and be listed as ‘Michel Loreau ^1,2’.

The published article has also been updated to reflect this correction.

We apologise for this error.