Most plant thermal tolerance studies focus on single critical thresholds, which limit the capacity to generalise across studies and predict heat stress under natural conditions. In animals and microbes, thermal tolerance landscapes describe the more realistic, cumulative effects of temperature. We tested this in plants by measuring the decline in leaf photosynthetic efficiency (FV/FM) following a combination of temperatures and exposure times, then modelled these physiological indices alongside recorded environmental temperatures. We demonstrate that a general relationship between stressful temperatures and exposure durations can be effectively employed to quantify and compare heat tolerance within and across plant species and over time. Importantly, we show how FV/FM curves translate to plants under natural conditions, suggesting that environmental temperatures often impair photosynthetic function. Our findings provide more robust descriptors of heat tolerance in plants and suggest that heat tolerance in disparate groups of organisms can be studied with a single predictive framework.

Generative artificial intelligence (AI) models will have broad impacts on society including the scientific enterprise; ecology and environmental science will be no exception. Here we discuss the potential opportunities and risks of advanced generative AI for visual material (images and video) for ecology and the environment. There are clearly opportunities for positive impacts, related to improved communication, for example; we also see possibilities for ecological research to profit from generative AI (e.g., image gap filling, biodiversity surveys, and improved citizen science). However, there are also risks, threatening to undermine the credibility of our science, mostly related to actions of bad actors, for example in terms of spreading fake information or committing fraud. Risks need to be mitigated at the level of government regulatory measures, but we also highlight what can be done right now, including discussing issues with the next generation of ecologists, and transforming towards radically open science workflows.

Metabolism underpins all life-sustaining processes and varies profoundly with body size, temperature, and locomotor activity. A current theory explains some of the size-dependence of metabolic rate (its mass exponent, b) through changes in metabolic level (L). We propose two predictive advances that: (a) combine the above theory with the evolved avoidance of oxygen limitation in water-breathers experiencing warming, and (b) quantify the overall magnitude of combined temperatures and degrees of locomotion on metabolic scaling across air- and water-breathers. We use intraspecific metabolic scaling responses to temperature (523 regressions) and activity (281 regressions) in diverse ectothermic vertebrates (fish, reptiles and amphibians) to show that b decreases with temperature-increased L in water-breathers, supporting surface area-related avoidance of oxygen limitation, whereas b increases with activity-increased L in air-breathers, following volume-related influences. This new theoretical integration quantitatively incorporates different influences (warming, locomotion) and respiration modes (aquatic, terrestrial) on animal energetics.

The publish-or-perish culture in academia has catalysed the development of an unethical publishing system. This system is characterised by the proliferation of journals and publishers—unaffiliated with learned societies or universities—that maintain extremely large revenues and profit margins diverting funds away from the academic community. Early career researchers (ECRs) are particularly vulnerable to the consequences of this publishing system because of intersecting factors, including pressure to pursue high impact publications, rising publication costs and job insecurity. Moving towards a more ethical system requires that scientists advocate for structural change by making career choices that come with risks, many of which disproportionately impact ECRs. We illuminate major issues facing ECRs in Ecology and Evolution under the current publishing system, and propose a portfolio of actions to promote systemic change that can be implemented by ECRs and established researchers.

The enemy release hypothesis (ERH) is the best-known hypothesis explaining high performance (e.g., rapid population growth) of exotic species. However, the current framing of the ERH does not explicitly link evidence of enemy release with exotic performance. This leads to uncertainty regarding the role of enemy release in biological invasions. Here we demonstrate that the effect of enemy release on exotic performance is the product of three factors: enemy impact, enemy diversity, and host adaptation. These factors are modulated by seven contexts: time since introduction, resource availability, phylogenetic relatedness of exotic and native species, host-enemy asynchronicity, number of introduction events, type of enemy, and strength of growth-defence trade-offs. ERH-focused studies frequently test different factors under different contexts, leading to inconsistent findings, which characterise current evidence for the ERH. For example, over 80% of meta-analyses fail to consider ecological contexts that can modulate study findings; we demonstrate this by re-analysing a recent ERH synthesis. Structuring the ERH around factors and contexts promotes generalisable predictions about when and where exotic species may benefit from enemy release, empowering effective management. Our mechanistic factor-context framework clearly lays out the evidence required to support the ERH, unifies many enemy-related invasion hypotheses and enhances predictive capacity.

Human activities have increased the intensity and frequency of natural stressors and created novel stressors, altering host-pathogen interactions, and changing the risk of emerging infectious diseases. Despite the ubiquity of such anthropogenic impacts, predicting the directionality of outcomes has proven challenging. Here, we conduct a review and meta-analysis to determine the primary mechanisms through which stressors affect host-pathogen interactions and to evaluate the impacts stress has on host fitness (survival and fecundity) and pathogen infectivity (prevalence and intensity). We assessed 891 effect sizes from 71 host species (representing seven taxonomic groups) and 78 parasite taxa from 98 studies. We found that infected and uninfected hosts had similar sensitivity to stressors and that responses varied according to stressor type. Specifically, limited resources compromised host fecundity and decreased pathogen intensity, while abiotic environmental stressors (e.g., temperature and salinity) decreased host survivorship and increased pathogen intensity, and pollution increased mortality but decreased pathogen prevalence. We then used our meta-analysis results to develop Susceptible-Infected theoretical models to illustrate scenarios where infection rates are expected to increase or decrease in response to resource limitation or environmental stress gradients. Our results carry implications for conservation and disease emergence and reveal areas for future work.

Plant-microbe interactions in the rhizosphere shape carbon and nitrogen cycling in soil organic matter (SOM). However, there is conflicting evidence on whether these interactions lead to a net loss or increase of SOM. In part, this conflict is driven by uncertainty in how living roots and microbes alter SOM formation or loss in the field. To address these uncertainties, we traced the fate of isotopically labeled litter into SOM using root and fungal ingrowth cores incubated in a Miscanthus x giganteus field . Roots stimulated litter decomposition, but balanced this loss by transferring carbon into more persistent, aggregate associated SOM. Further, roots selectively mobilized nitrogen from litter without additional carbon release. Overall, our fundings suggest that roots can efficiently mine nitrogen and build persistent soil carbon.

Understanding the evolutionary mechanisms underlying the maintenance of individual differences in behavior and physiology is a fundamental goal in ecology and evolution. The Pace-of-life syndrome hypothesis is often invoked to explain the maintenance of such within-population variation. This hypothesis predicts that behavioral traits are part of a suite of correlated traits that collectively determine an individual’s propensity to prioritize reproduction or survival. A key assumption of this hypothesis is that these traits are underpinned by genetic trade-offs among life-history traits: genetic variants that increase fertility, reproduction and growth might also reduce lifespan. We performed a systematic literature review and meta-analysis to summarize the evidence for the existence of genetic trade-offs between five key life-history traits: survival, growth rate, body size, maturation rate, and fertility. Counter to our predictions, we found an overall positive genetic correlation between survival and other life-history traits and no evidence for any genetic correlations between the non-survival life-history traits. This finding was generally consistent across pairs of life-history traits, sexes, life stages, lab vs field studies, and narrow- vs broad-sense correlation estimates. Our study highlights that genetic trade-offs may not be as common, or at least not as easily quantifiable, in animals as often assumed.

Rapidly changing environments combined with increasing global restoration initiatives require improved seed sourcing strategies for native revegetation. Sourcing seed from local populations (local provenancing) has been the long-standing default for native revegetation for numerous eco-evolutionary reasons including local adaptation and species co-evolution. However, the evidence-base has shifted, revealing risks for both non-local and local provenancing in changing environments. As alternative strategies gain interest, we argue for effective decision-making that weighs the risks of changing and not changing seed sourcing strategies in a changing environment that transcends a default position and the polarising local vs. non-local debate.

Species coexistence attracts wide interest in ecology. Modern coexistence theory (MCT) identifies coexistence mechanisms, one of which, storage effects, hinges on relationships between fluctuations in environmental and competitive pressures. However, such relationships are typically measured using covariance, which does not account for the possibility that environment and competition may be more related to each other when they are strong than when weak, or vice versa. Recent work showed that such ‘asymmetric tail associations’ (ATAs) are common between ecological variables, and are important for extinction risk, ecosystem stability, and other phenomena. We extend the MCT, decomposing storage effects to show the influence of ATAs. Analysis of a simple model and an empirical example using diatoms illustrate that ATA influences can be comparable in magnitude to other mechanisms of coexistence, and that ATAs can make the difference between species coexistence and competitive exclusion. ATA influences are an important new mechanism of coexistence.

Understand the mechanisms underlying diversity-productivity relationships (DPRs) is crucial to mitigating the effects of forest biodiversity loss. Tree-tree interactions in diverse communities are fundamental in driving growth rates, potentially shaping the emergent DPRs, yet remains poorly explored. Here, using data from a large-scale forest biodiversity experiment in subtropical China, we demonstrated that changes in individual tree productivity were driven by species-specific pairwise interactions, with higher positive net pairwise interaction effects on trees in more diverse neighbourhoods. The aggregated interaction effects subsequently determined the community DPRs. We further revealed that the positive differences between inter- and intra-specific interactions were the critical determinant for the emergence of positive DPRs. Surprisingly, the condition for positive DPRs corresponded to the condition for coexistence. Our results thus provide a novel insight into how pairwise tree interactions regulate DPRs, with implications for identifying the tree mixtures with maximised productivity to guide forest restoration and reforestation efforts.

Anthropogenic activities expose many ecosystems to multiple novel disturbances simultaneously. Despite this, how biodiversity responds to simultaneous disturbances remains unclear, with conflicting empirical results on their interactive effects. Here, we experimentally test how one disturbance (an invasive species) affects the diversity of a community over multiple levels of another disturbance regime (pulse mortality). Specifically, we invade stably coexisting bacterial communities under four different pulse frequencies, and compare their final resident diversity to uninvaded communities under the same pulse mortality regimes. Our experiment shows that the disturbances synergistically interact, such that the invader significantly reduces resident diversity at high pulse frequency, but not at low. This work therefore highlights the need to study simultaneous disturbance effects over multiple disturbance regimes as well as to carefully document unmanipulated disturbances, and may help explain the conflicting results seen in previous multiple-disturbance work.

A document by Julian Lilkendey. Click on the document to view its contents.

Animal migration impacts organismal health and disease transmission: migrants are simultaneously exposed to parasites and able to reduce infection at the population and individual levels. However, these dynamics are difficult to study; empirical studies reveal disparate results while existing theory makes assumptions that simplify natural complexity. Here, we systematically review empirical studies of migration and infection across taxa, highlighting key gaps in our understanding. Next, we develop a unified evolutionary framework incorporating different mechanisms of parasite-migration interactions while accounting for ecological complexity that goes beyond previous theory. Our framework generates diverse migration-infection patterns paralleling those seen in empirical systems, including partial and differential migration. Finally, we generate predictions about which mechanisms dominate which empirical systems to guide future studies. Our framework provides an overarching understanding of selective pressures shaping migration patterns in the context of animal health and disease, which is critical for predicting how environmental change may threaten migration.

Biodiversity is diminishing at alarming rates due to multiple anthropogenic drivers. To mitigate these drivers, their impacts must be quantified accurately and comparably across drivers. To enable that, we present a generally applicable framework introducing fundamental principles of ecological impact quantification, including the quantification of interactions between multiple drivers. The framework contrasts biodiversity variables in impacted against those in unimpacted or other reference situations, while accounting for their temporal dynamics through modelling. Properly accounting for temporal dynamics reduces biases in impact quantification and comparison. The framework addresses key questions around ecological impacts in global change science, namely, how to compare impacts under temporal dynamics across stressors, how to account for stressor interactions in such comparisons, and how to compare the success of management actions over time.

Metabolomics provides an unprecedented window on diverse plant secondary metabolites that represent a potentially critical niche dimension in tropical forests underlying co-existence. Here, we used untargeted metabolomics to evaluate the chemical composition of 358 tree species and its relationship to phylogeny and variation in light environment, soil nutrients, and insect-herbivore leaf damage in a tropical rain forest plot. We found that tree species that co-occur locally are less chemically similar than random, and that local chemical dispersion and metabolite diversity reduce herbivory, especially that of specialist insect herbivores. Our results suggest that plant secondary metabolites have the potential to mediate plant-herbivore interactions in a manner consistent with diversity maintenance at the community scale.

Vector-borne diseases cause significant financial and human loss, with billions of dollars spent on control. Arthropod vectors experience a complex suite of environmental factors that affect fitness, population growth, and species interactions across multiple spatial and temporal scales. Temperature and water availability are two of the most important abiotic variables influencing their distributions and abundances. While extensive research on temperature exists, the influence of humidity on vector and pathogen parameters affecting disease dynamics are less understood. Humidity is often underemphasized, and when considered, is often treated as independent of temperature even though desiccation likely contributes to declines in trait performance at warmer temperatures. This Perspectives explores how humidity shapes the thermal performance of mosquito-borne pathogen transmission. We summarize what is known about its effects and propose a conceptual model for how temperature and humidity interact to shape the range of temperatures across which mosquitoes persist and achieve high transmission potential. We discuss how failing to account for these interactions hinders efforts to forecast transmission dynamics and respond to epidemics of mosquito-borne infections. We outline future research areas that will ground the effects of humidity on the thermal biology of pathogen transmission in a theoretical and empirical framework to improve spatial and temporal prediction of vector-borne pathogen transmission.

Seed production and dispersal are crucial ecological processes impacting plant demography, species distributions, and community assembly. Plant-animal interactions commonly mediate both seed production and seed dispersal, but current research often examines pollination and seed dispersal separately, which hinders our understanding of how pollination services affect downstream dispersal services. To fill this gap, we propose a conceptual framework exploring how pollen limitation can impact the effectiveness of seed dispersal for endozoochorous and myrmecochorous plant species. We summarize the quantitative and qualitative effects of pollen limitation on plant reproduction and use Optimal Foraging Theory to predict its impact on the foraging behavior of seed dispersers. In doing so, we offer a new framework that poses numerous hypotheses and empirical tests to investigate downstream effects of pollen limitation on seed dispersal effectiveness and, consequently, post-dispersal ecological processes occurring at different levels of biological organization. Finally, considering the importance of pollination and seed dispersal outcomes to plant eco-evolutionary dynamics, we discussed the implications of our framework for future studies exploring the demographic and evolutionary impacts of pollen limitation for animal-dispersed plants.