Traits determine species responses to climate change, as most eastern U.S. trees shift westward following moisture change.

As ecology enters a critical era, more comprehensive studies are needed to improve our understanding of the key themes, major trends, and potential gaps within the discipline. However, as the number of published scientific papers continues to grow, tracking the ever‐expanding body of work becomes increasingly challenging. To identify trends in ecological research, we used recently developed machine learning techniques to perform an automated content analysis on over 84,841 articles published in 33 top‐ranked scientific journals over the past four decades. We detected a clear decline in the relative frequency of classical theoretical research, and increases in data‐intensive research at both micro‐ and macroscales and on anthropogenic themes. Scattered around the periphery of the expanding thematic space, themes such as microbial ecology, genetics, biogeochemistry, and management and policy have all increased in relative frequency. New educational and research frameworks, as well as funding priorities, should incorporate these contemporary themes so that the field of ecology can better address societal challenges.

No abstract

Aim Much is known about the elevational diversity patterns of native species and about the mechanisms that drive these patterns. A similar level of understanding is needed for non‐native species. Using published data, we examine elevational diversity patterns of non‐native plants and compare the resulting patterns with those observed for native plants. Location Global. Methods We compiled data from 65 case studies on elevational diversity patterns of non‐native plants around the world (including 32 cases in which both non‐native and native plants were sampled). We compared the elevational distributions (upper and lower limits, and extents) and diversity patterns of non‐native and native species. Results Compared to native plant species, the elevational diversity patterns of non‐native plant species were more negative (47% vs. 13%) and less unimodal (44% vs. 84%). That is, non‐native species richness tended to be highest at lower elevations, whereas native species richness peaked at mid‐elevations. In cases where species richness for both non‐native and native species on the same mountains showed unimodal patterns in relation to elevation, maximum values in species richness occurred at lower elevations for non‐native species. Main conclusions At present levels of invasion, non‐native and native species show different patterns in both distribution and diversity along elevational gradients worldwide. However, our observations constitute a snapshot of ongoing, long‐term invasion processes. As non‐native species typically show strong associations with human activities, future changes in human population (e.g. growth and migration), land use and climate change may promote upward spread of non‐native species and may thus increase risks of impact on native species and communities.

The physical structure of vegetation is thought to be closely related to ecosystem function, but little is known of its pertinence across geographic regions. Here, we used data from over three million trees in continental North America to evaluate structural diversity – the volumetric capacity and physical arrangement of biotic components in ecosystems – as a predictor of productivity. We show that structural diversity is a robust predictor of forest productivity and consistently outperforms the traditional measure – species diversity – across climate conditions in North America. Moreover, structural diversity appears to be a better surrogate of niche occupancy because it captures variation in size that can be used to measure realized niche space. Structural diversity offers an easily measured metric to direct restoration and management decision making to maximize ecosystem productivity and carbon sequestration.