Trends in ecology & evolution最新文献

The rationale behind trait-based ecology is that shifting focus from species' taxonomic names to their measurable characteristics ('functional traits') leads to greater generality and predictive power. This idea has been applied to one of ecology's most intractable problems: the coexistence of competing species. But after 20 years, we lack clear evidence that functional traits effectively predict coexistence. Here, we present a theory-based argument for why this might be the case. Specifically, we argue that coexistence often depends on special quantities called 'process-informed metrics' (PIMs), which combine multiple traits and demographic characteristics in non-intuitive ways, obscuring any direct ties between individual traits and coexistence. We then lay a path forward for trait-based coexistence research that builds on mechanistic models of competition.

Comprehensive assessments of functional diversity are needed to understand ecosystem alterations under global changes. The 'Fun-eDNA' approach characterises functional diversity by assigning traits to taxonomic units obtained through environmental DNA (eDNA) sampling. By simultaneously analysing an unprecedented number of taxa over broad spatial scales, the approach provides a whole-ecosystem perspective of functional diversity. Fun-eDNA is increasingly used to tackle multiple questions, but aligning eDNA with traits poses several conceptual and technical challenges. Enhancing trait databases, improving the annotation of eDNA-based taxonomic inventories, interdisciplinary collaboration, and conceptual harmonisation of traits are key steps to achieve a comprehensive assessment of diverse taxa. Overcoming these challenges can unlock the full potential of eDNA in leveraging measures of ecosystem functions from multi-taxa assessments.

We reframe the idea of balancing career and non-career interests for ecologists specifically. We introduce the concept of a dynamic work-life equilibrium (WLE) and draw parallels between ecological processes and processes affecting our continuously fluctuating sense of balance, with an aim at encouraging self-reflection and improving WLE mentoring in ecological disciplines.

Decades of empirical ecological research have focused on understanding ecological dynamics at local scales. Remote sensing products can help to scale-up ecological understanding to support management actions that need to be implemented across large spatial extents. This new avenue for remote sensing applications requires careful consideration of sources of potential bias that can lead to spurious causal relationships. We propose that causal inference techniques can help to mitigate biases arising from confounding variables and measurement errors that are inherent in remote sensing products. Adopting these statistical techniques will require interdisciplinary collaborations between local ecologists, remote sensing specialists, and experts in causal inference. The insights from integrating 'big' observational data from remote sensing with causal inference could be essential for bridging biodiversity science and conservation.

Fungi are crucial for terrestrial ecosystems, yet the role of fungal diversity in ecosystem functions remains unclear. We synthesize fungal biodiversity and ecosystem function (BEF) relationships, focusing on plant biomass production, carbon storage, decomposition, and pathogen or parasite resistance. The observed BEF relationships for these ecosystem functions vary in strength and direction, complicating generalizations. Strong positive relationships are generally observed when multiple ecosystem functions are addressed simultaneously. Often, fungal community composition outperforms species richness in predicting ecosystem functions. For more comprehensive fungal BEF research, we recommend studying natural communities, considering the simultaneous functions of a broader array of fungal guilds across spatiotemporal scales, and integrating community assembly concepts into BEF research. For this, we propose a conceptual framework and testable hypotheses.

Science × art collaborations can effectively convey scientific insights to a wide audience. Throughout history, art has interpreted the natural world, offering vast, underexplored sources of biodiversity data. These artistic efforts also hold potential as valuable tools for understanding biodiversity.

Human-commensalism has been intuitively characterised as an interspecific interaction whereby non-human individuals benefit from tight associations with anthropogenic environments. However, a clear definition of human-commensalism, rooted within an ecological and evolutionary framework, has yet to be proposed. Here, we define human-commensalism as a population-level dependence on anthropogenic resources, associated with genetic differentiation from the ancestral, non-commensal form. Such a definition helps us to understand the origins of human-commensalism and the pace and form of adaptation to anthropogenic niches, and may enable the prediction of future evolution in an increasingly human-modified world. Our discussion encourages greater consideration of the spatial and temporal complexity in anthropogenic niches, promoting a nuanced consideration of human-commensal populations when formulating research questions.