Ecology Letters最新文献

Soil microorganisms mediate carbon and nutrient fluxes in soils, and—as all organisms—are subject to eco-evolutionary dynamics. Adaptation of soil microbial functionality to environmental conditions across space and time has consequences for biogeochemical fluxes that are often not explicitly considered in models describing soil organic matter (SOM) dynamics. Eco-evolutionary optimization (EEO) tries to anticipate the outcome of eco-evolutionary dynamics, and can inform on how microbial functional traits might adapt to environmental conditions based on the maximisation of different proxies of microbial fitness. While different approaches employ different fitness proxies, they all aim to increase realism and generality by grounding SOM models in eco-evolutionary theory and introducing constraints on model parametrization. Despite this potential, challenges for widely applying EEO approaches to advance SOM models persist and open questions remain, primarily concerning implicit assumptions, convergence of predictions, and empirical validation of the different EEO approaches. In this Synthesis, we review EEO approaches that have been applied to SOM models and provide an instructive primer to EEO approaches. We then propose a general categorization, aiming to make their underlying assumptions explicit and give an outlook for future research directions.

Predicting the effects of climate change on plant and animal populations is an urgent challenge for understanding the fate of biodiversity under global change. At the surface, quantifying how climate drives the vital rates that underlie population dynamics appears simple, yet many decisions are required to connect climate to demographic data. Competing approaches have emerged in the literature with little consensus around best practices. Here we provide a practical guide for how to best link vital rates to climate for the purposes of inference and projection of population dynamics. We first describe the sources of demographic and climate data underlying population models. We then focus on best practices to model the relationships between vital rates and climate, highlighting what we can learn from mechanistic and phenomenological models. Finally, we discuss the challenges of prediction and forecasting in the face of uncertainty about climate-demographic relationships as well as future climate. We conclude by suggesting ways forward to build this field of research into one that makes robust forecasts of population persistence, with opportunities for synthesis across species.

Freshwater species are facing massive declines, often driven by eutrophication. Identifying which facets of biodiversity are sensitive is crucial, as species loss does not always translate to reduced ecosystem functioning and functional diversity. We examined how assembly rules shape zooplankton functional diversity in hypereutrophic fishponds. Higher eutrophication was hypothesised to cause functional homogenization through reduced functional diversity, habitat filtering, and trait convergence. Higher eutrophication indeed reduced functional diversity metrics, whereas species richness was kept stable. Functional richness, dispersion, and dissimilarity shifted from limiting similarity, where niche partitioning and competition shape community structure, to random (incidence data) and habitat filtering (biomass) with increasing eutrophication. Functional divergence transitioned from random to habitat filtering, whereas redundancy increased at higher trophic states. Trait convergence was the dominant process, with the environment selecting species with similar traits. Biodiversity assessments and managers should consider how functional diversity and ecosystem functions respond to anthropogenic and environmental changes.

Individual movement is critical in shaping population dynamics. However, existing frameworks linking these two processes often rely on unrealistic assumptions or numerical simulations. To address this gap, we introduce the range-resident logistic model, an easy-to-simulate and mathematically tractable extension of the spatial logistic model that incorporates empirically supported range-resident movement. Our framework unifies non-spatial and (sessile) spatial formulations of the logistic model as limiting cases. Between these regimes, the long-term population size depends nonlinearly on home-range size and spatial distribution. Neglecting range residency can hence lead to under- or overestimating population carrying capacity. To better understand these results, we also introduce a novel crowding index that depends on movement parameters and can be estimated from tracking data. This index captures the influence of spatial structure on population size, and serves as a robust predictor of abundance. The range-resident logistic model is thus a unifying framework bridging movement and population ecology.

Defaunation of large-bodied animals threatens essential ecosystem functions, such as seed dispersal. However, the consequences of this human-induced downsizing of animal communities for plant-frugivore trait matching—the alignment between frugivory-related plant traits (e.g., fruit size) and frugivore traits (e.g., body mass)—remain unquantified at macroecological scales. Here, we examine how human disturbance and environmental conditions influence trait matching in tropical plant-frugivore networks. We compiled fruit size data for 1927 plant species from primary sources, along with body mass and dietary information for 1120 frugivorous animal species (birds, mammals and reptiles), and integrated these with 12,708 plant-frugivore interactions recorded across 102 networks. Using fourth-corner analyses and structural equation models (SEMs), we quantified how human disturbance and environmental conditions directly and indirectly affected trait matching strength (fruit-size-to-body-mass correlation) across networks. SEMs revealed that human disturbance weakened trait matching by reducing the range of frugivore body masses within networks, whereas wet and productive environments promoted a higher proportion of fruit in frugivore diets, leading to stronger trait matching. Our results demonstrate that human disturbance weakens plant-frugivore trait matching through the downsizing of animal communities, thereby providing a quantitative assessment of the decoupling of coevolved relationships between fruiting plants and their animal seed dispersers.