Ecology Letters最新文献

Using data on bird species elevational distributions from the world's mountain ranges, bird diets, and the distribution of the ant genus Oecophylla, we report that global patterns in bird elevational diversity show signals of competition with ants. Oecophylla is an abundant and effective predator of invertebrates, preying on the same species that invertivorous birds feed on. In mountain ranges with Oecophylla present in the foothills, the maximum species richness of invertivorous birds (but not other trophic guilds) occurs, on average, at 960 m, ca. 450 m higher than in mountain ranges without Oecophylla, resulting in a mid-elevation peak in bird species richness. Where Oecophylla is absent, bird species richness for all guilds generally show monotonic declines with increasing elevation. We argue that Oecophylla reduces prey density for invertivorous birds and that low prey abundance reduces invertivorous bird density, which in turn is correlated with lower bird species richness. These findngs suggest that competition between distantly related taxa can set range limits, leading to emergent diversity patterns over large scales.

Species' traits and interactions are products of evolutionary history. Despite the long-standing hypothesis that closely related species possess similar traits, and thus experience stronger competition, measuring the effect of evolutionary history on the ecology of natural communities remains challenging. We propose a novel framework to test whether phylogeny influences patterns of coexistence and abundance of species assemblages. In our approach, phylogenetic trees are used to parameterize species' interactions, which in turn determine the abundance of species in a given assemblage. We use likelihoods to score models parameterized with a given phylogeny, and contrast them with models built using random trees, allowing us to test whether phylogenetic information helps to predict species' abundances. Our statistical framework reveals that interactions are indeed structured by phylogeny in a large set of experimental plant communities. Our results confirm that evolutionary history can help predict, and potentially manage or conserve, the structure and function of complex ecological communities.

Protecting populations contending with co-occurring stressors requires a better understanding of how multiple early-life stressors affect the fitness of natural systems. However, the complexity of such research has limited its advancement and prevented us from answering new questions. In human studies, cumulative risk models predict adult health risk based on early adversity exposure. We apply a similar framework in wild yellow-bellied marmots (Marmota flaviventer). We tested cumulative adversity indices (CAIs) across different adversity types and time windows. All CAIs were associated with decreased pup survival and were well supported. Moderate and acute, but not standardized CAIs were associated with decreased lifespan, supporting the cumulative stress hypothesis and the endurance of early adversity. Multivariate models showed that differences in lifespan were driven by weaning date, precipitation, and maternal loss, but they performed poorly compared with CAI models. We highlight the development, utility, and insights of CAI approaches for ecology and conservation.

Invasions are commonly found to benefit from disturbance events. However, the importance of the relative timing of the invasion and disturbance for invader success and impact on community composition remains uncertain. Here, we experimentally test this by invading a five-species bacterial community on eight separate occasions—four before a disturbance and four after. Invader success and impact on community composition was greatest when the invasion immediately followed the disturbance. However, the subsequent invasions had negligible success or impact. Pre-disturbance, invader success and impact was greatest when the invader was added just before the disturbance. Importantly, however, the first three pre-disturbance invasion events had significantly greater success than the last three post-disturbance invasions. Moreover, these findings were consistent across a range of propagule pressures. Overall, we demonstrate that timing is highly important for both the success and impact on community composition of an invader, with both being lower as time since disturbance progresses.

Introduction history, including propagule pressure and residence time, has been proposed as a primary driver of biological invasions. However, it is unclear whether introduction history increases the likelihood that a species will be invasive or only the likelihood that it will be established. Using a dataset of non-native species historically available as ornamental plants in the conterminous United States, we investigated how introduction history relates to these stages of invasion. Introduction history was highly significant and a strong predictor of establishment, but only marginally significant and a poor predictor of invasive success. Propagule pressure predicted establishment better than residence time, with species likely to be established if they were introduced to only eight locations. These findings suggest that ongoing plant introductions will lead to widespread establishment but may not directly increase invasive success. Instead, other characteristics, like plant traits and local scale processes, may better predict whether a species becomes invasive.

A rapidly warming climate is driving changes in biodiversity worldwide, and its impact on insect communities is critical given their outsized role in ecosystem function and services. We use a long-term dataset of North American bumble bee species occurrences to determine whether the community temperature index (CTI), a measure of the balance of warm- and cool-adapted species in a community, has increased given warming temperatures. CTI has increased by an average of 0.99°C in strong association with warming maximum summer temperatures over the last 30 years with the areas exhibiting the largest increases including mid- to high latitudes as well as low and high elevations—areas relatively shielded from other intensive global changes. CTI shifts have been driven by the decline of cold-adapted species and increases in warm-adapted species within bumble bee communities. Our results show the pervasive impacts and ecological implications warming temperatures pose to insects.

In the realm of biological image analysis, deep learning (DL) has become a core toolkit, for example for segmentation and classification. However, conventional DL methods are challenged by large biodiversity datasets characterized by unbalanced classes and hard-to-distinguish phenotypic differences between them. Here we present BioEncoder, a user-friendly toolkit for metric learning, which overcomes these challenges by focussing on learning relationships between individual data points rather than on the separability of classes. BioEncoder is released as a Python package, created for ease of use and flexibility across diverse datasets. It features taxon-agnostic data loaders, custom augmentation options, and simple hyperparameter adjustments through text-based configuration files. The toolkit's significance lies in its potential to unlock new research avenues in biological image analysis while democratizing access to advanced deep metric learning techniques. BioEncoder focuses on the urgent need for toolkits bridging the gap between complex DL pipelines and practical applications in biological research.

Tracking climatic conditions throughout the year is often assumed to be an adaptive behaviour underlying seasonal migration patterns in animal populations. We investigate this hypothesis using genetic markers data to map migratory connectivity for 27 genetically distinct bird populations from 7 species. We found that the variation in seasonal climate tracking across our suite of populations at a continental scale is more likely a consequence, rather than a direct driver, of migratory connectivity, which is primarily shaped by energy efficiency—i.e., optimizing the balance between accessing available resources and movement costs. However, our results also suggest that regional-scale seasonal precipitation tracking affects population migration destinations, thus revealing a potential scale dependency of ecological processes driving migration. Our results have implications for the conservation of these migratory species under climate change, as populations tracking climate seasonally are potentially at higher risk if they adapt to a narrow range of climatic conditions.

Animals interact with nutrient cycles by consuming and depositing nutrients, interactions studied separately in nutritional ecology and zoogeochemistry. Recent theoretical work bridges these disciplines, highlighting that animal-driven nutrient recycling could be crucial in helping animals meet their nutritional needs. When animals exhibit site fidelity, they consistently deposit nutrients, potentially improving vegetation quality. We investigated this potential feedback by analysing changes in forage nitrogen stocks following simulated caribou calving. We found that forage nitrogen stocks increased after 2 weeks and remained elevated after 1 year, a change due to increased forage quality, not quantity. We also developed a nutrient budget within calving grounds, demonstrating that natal fluid and calf carcasses contribute substantial nitrogen subsidies. We, thus, highlight a positive zoogeochemical feedback whereby nutrients deposited during calving become bioavailable during lactation and provide evidence that site fidelity creates a biogeochemical boomerang in which animals deposit nutrients that can be reused later.

The Arctic is warming four times faster than the rest of the world, threatening the persistence of many Arctic species. It is uncertain if Arctic wildlife will have sufficient time to adapt to such rapidly warming environments. We used genetic forecasting to measure the risk of maladaptation to warming temperatures and sea ice loss in polar bears (Ursus maritimus) sampled across the Canadian Arctic. We found evidence for local adaptation to sea ice conditions and temperature. Forecasting of genome-environment mismatches for predicted climate scenarios suggested that polar bears in the Canadian high Arctic had the greatest risk of becoming maladapted to climate warming. While Canadian high Arctic bears may be the most likely to become maladapted, all polar bears face potentially negative outcomes to climate change. Given the importance of the sea ice habitat to polar bears, we expect that maladaptation to future warming is already widespread across Canada.