Trends in ecology & evolution最新文献

Understanding how natural communities and ecosystems are structured and respond to anthropogenic pressures in a rapidly changing world is key to successful management and conservation. A fundamental but often overlooked biological characteristic of organisms is sex. Sex-based responses are often considered when conducting studies at organismal and population levels, but are rarely investigated in community ecology. Focusing on kelp forests as a model system, and through a review of other marine and terrestrial ecosystems, we found evidence of widespread sex-based variation in species interactions. Sex-based variation in species interactions is expected to affect ecosystem structure and functioning via multiple trophic and nontrophic pathways. Understanding the drivers and consequences of sex-based variation in species interactions can inform more effective management and restoration.

By recognizing the role of animals as restoration drivers, we have a unique opportunity to combine climate and biodiversity policy frameworks and meet targets synergistically. About 25% of forest restoration projects could benefit from animals contributing to both frameworks. In 50% of projects, active actions are needed to improve outcomes.

The cognitive ecology of pollination is most often studied using simple rewards, yet flowers often contain multiple types of chemically complex rewards, each varying along multiple dimensions of quality. In this review we highlight ways in which reward complexity can impact pollinator cognition, demonstrating the need to consider ecologically realistic rewards to fully understand plant-pollinator interactions. We show that pollinators' reward preferences can be modulated by reward chemistry and the collection of multiple reward types. We also discuss how reward complexity can mediate pollinator learning through a variety of mechanisms, both with and without reward preference being altered. Finally, we show how an understanding of decision-making strategies is necessary to predict how pollinators' evaluation of reward options depends on the other options available.

Facilitative interactions play crucial roles in community organization, and the stress gradient hypothesis (SGH) provides a simple conceptual framework for the context-dependency of competitive and facilitative interactions. The idea is that positive interactions are more common under high physical and consumer stress, where species benefit from stress-tolerant neighbors, than in benign environments. We explore insights from the SGH into ecological generality, niche theory, community assembly, and diversity effects on ecosystem function and discuss how the SGH can inform our understanding of rapid evolution, mutualisms, exotic invasions, and facilitation cascades. We suggest that, with escalating global stresses, the SGH may provide a conceptual template for an interdependent perspective in ecology that can contribute to conservation and restoration efforts.

Heat extremes have become the new norm in the Anthropocene. Their potential to trigger major ecological responses is widely acknowledged, but their unprecedented severity hinders our ability to predict the magnitude of such responses, both during and after extreme heat events. To address this challenge we propose a conceptual framework inspired by the core concepts of ecological stability and thermal biology to depict how responses of populations and communities accumulate at three response stages (exposure, resistance, and recovery). Biological mechanisms mitigating responses at a given stage incur associated costs that only become apparent at other response stages; these are known as 'ecological debts'. We outline several scenarios for how ecological responses associate with debts to better understand biodiversity changes caused by heat extremes.

New digital and sensor technology provides a huge opportunity to revolutionise conservation, but we lack a plan for deploying the technologies effectively. I argue that environmental research should be concentrated at a small number of 'super-sites' and that the concentrated knowledge from super-sites should be used to develop holistic ecosystem models. These, in turn, should be morphed into digital twin ecosystems by live connecting them with automated environmental monitoring programmes. Data-driven simulations can then help select pathways to achieve locally determined conservation goals, and digital twins could revise and adapt those decisions in real-time. This technology-heavy vision for 'smart conservation' provides a map toward a future defined by more flexible, more responsive, and more efficient management of natural environments.

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.

Applying human concepts of self-awareness to animals often lacks anchoring in biologically meaningful contexts. We advocate a new, modular framework of self-representation, including body-awareness, which helps an individual to negotiate physical obstacles. We emphasize the importance of ecologically valid approaches that allow adaptivity-based hypotheses and discussion about self-representation.

Instruments attached to animals ('biologgers') have facilitated extensive discoveries about the patterns, causes, and consequences of animal behavior. Here, we present examples of how biologging can deepen our fundamental understanding of ecosystems and our applied understanding of global change impacts by enabling tests of ecological theory. Applying the iterative process of science to biologging has enabled a diverse set of insights, including social and experiential learning in long-distance migrants, state-dependent risk aversion in foraging predators, and resource abundance driving movement across taxa. Now, biologging is poised to tackle questions and refine ecological theories at increasing levels of complexity by integrating measurements from numerous individuals, merging datasets from multiple species and their environments, and spanning disciplines, including physiology, behavior and demography.

As biodiversity loss continues, targeted conservation interventions are increasingly necessary. Stemming species loss requires mechanistic understanding of the processes governing population dynamics. However, this information is unavailable for most animals because it requires data that are difficult to collect using traditional methods. Advances in animal tracking technology have generated an avalanche of high-resolution observations for a growing list of species around the globe. To date, most research using these data has focused on questions about animal behavior, with less emphasis on population processes. Here, we argue that tracking data are uniquely poised to bring powerful new insights to the urgent, global problem of halting species extinctions by revealing when, where, how, and why populations are changing.