A major challenge in ecology is to understand how different species interact to determine ecosystem function, particularly in communities with large numbers of co-occurring species. We use a trait-based model of microbial litter decomposition to quantify how different taxa impact ecosystem function. Further, we build a novel framework that highlights the interplay between taxon traits and environmental conditions, focusing on their combined influence on community interactions and ecosystem function. Our results suggest that the impact of a taxon is driven by its resource acquisition traits and the community functional capacity, but that physiological stress amplifies the impact of both positive and negative interactions. Further, net positive impacts on ecosystem function can arise even as microbes have negative pairwise interactions with other taxa. As communities shift in response to global climate change, our findings reveal the potential to predict the biogeochemical functioning of communities from taxon traits and interactions.

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.

Accurately representing the relationships between nitrogen supply and photosynthesis is crucial for reliably predicting carbon-nitrogen cycle coupling in Earth System Models (ESMs). Most ESMs assume positive correlations among soil nitrogen supply, leaf nitrogen content, and photosynthetic capacity. However, leaf photosynthetic nitrogen demand may influence the leaf nitrogen response to soil nitrogen supply, thus responses to nitrogen supply are expected to be largest in environments where demand is greatest. Using a nutrient addition experiment replicated at 26 sites spanning four continents, we demonstrated that climate variables were stronger predictors of leaf nitrogen content than soil nutrient supply. Leaf nitrogen increased more strongly with soil nitrogen supply in regions with highest theoretical leaf nitrogen demand, increasing more in colder and drier environments than warmer and wetter ones. Thus, leaf nitrogen responses to nitrogen supply are primarily influenced by climatic gradients in photosynthetic nitrogen demand, an insight that will improve ESM predictions.

Changing CO2 concentrations have and will continue to affect plant growth with consequences for ecosystem functioning. The adaptive capacity of C3 photosynthesis to changes in atmospheric CO2 concentrations is, however, insufficiently investigated so far. Here we focused on the phylogenetic dynamics of maximum carboxylation rate (Vcmax) and maximum electron transport rate (Jmax) – two key determinants of photosynthetic efficiency in C3 plants – and their relation to deep-time dynamics in species diversification, speciation and atmospheric CO2 concentrations during the last 120 million years. We observed very strong positive relationships between photosynthetic efficiency and species diversification as well as speciation rates. Vcmax as well as species speciation and diversification furthermore increased during periods of low prehistoric CO2 concentrations. From our results we conclude strong links between photosynthetic efficiency and evolutionary dynamics in C3 plants. We furthermore conclude, that increasing future CO2 concentrations might rather hinder than facilitate evolutionary dynamics in C3 plants.

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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.

Climate change can influence populations of monogamous species by affecting pair-bond dynamics. This study examined the impact of climate on widowhood and divorce, and the subsequent effects on individual vital rates and life-history outcomes over 54 years in a snow petrel (Pagodroma nivea) population. We found that environmental conditions can affect pair-bond dynamics both directly and indirectly. Divorce was adaptive, occurring more frequently after breeding failure and leading to improved breeding success. Divorce probabilities also increased under severe climatic conditions, regardless of prior breeding success, supporting the ”Habitat-mediated” mechanisms. Generally, pair-bond disruptions reduced subsequent vital rates and lifetime outcomes. Climate forecasts from an Atmosphere-Ocean General Circulation Model projected increased male widowhood rates due to decreased sea ice negatively affecting female survival, despite considerable uncertainty. These findings highlight the importance of environmentally induced changes in demographic and pair-bond disruption rates as crucial factors shaping demographic responses to climate change.

Community assembly provides the foundation for applications in biodiversity conservation, climate change, invasion ecology, restoration ecology, and synthetic ecology. Predicting and prioritizing community assembly outcomes remains challenging. We address this challenge via a mechanism-free LOVE (Learning Outcomes Via Experiments) approach suitable for cases where little data or knowledge exist: we carry out actions (randomly-sampled combinations of species additions), measure abundance outcomes, and then train a model to predict arbitrary outcomes of actions, or prioritize actions that would yield the most desirable outcomes. When trained on <100 randomly-selected actions, LOVE predicts outcomes with 2-5% error across datasets, and prioritizes actions for maximizing richness, maximizing abundance, or minimizing abundances of unwanted species, with 94-99% true positive rate and 12-83% true negative rate across tasks. LOVE complements existing approaches for community ecology by providing a foundation for additional mechanism-first study, and may help address numerous ecological applications.

Invasions are commonly found to benefit from disturbance events. However, the importance of the relative timing and order of the invasion and disturbance for invader success 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 on average greater pre-disturbance.

Understanding microbial adaptation is crucial for predicting how soil carbon dynamics and global biogeochemical cycles will respond to climate change. This study employs the DEMENT model of microbial decomposition, along with empirical mutation and dispersal rates, to explore the roles of mutation and dispersal in adaptation of soil microbial populations to shifts in litter chemistry, changes that are anticipated with climate-driven vegetation dynamics. Following a change in litter chemistry, mutation generally allows for a higher rate of litter decomposition than dispersal, especially when dispersal predominantly introduces genotypes already present in the population. These findings challenge the common idea that mutation rates are too low to affect ecosystem processes on ecological timescales. These results demonstrate that evolutionary processes, such as mutation, can help maintain ecosystem functioning as the climate changes.

Many organisms show signs of deterioration with age, both in terms of survival and reproduction. Theory suggests that variation in such senescence patterns can be driven by resource availability or reproductive history. Here, we test this theory by manipulating nutritional stress and age at first reproduction and measuring age-dependent reproductive output in tsetse (Glossina morsitans morsitans), a viviparous fly with high maternal allocation. Across all treatments, offspring wet weight followed a bell-shaped curve with maternal age. Nutritionally stressed females had higher probability of abortion, produced smaller offspring with lower starvation tolerance. Despite this, there was no strong evidence of differences between treatments in the pattern of abortion probability, offspring wet weight or offspring starvation tolerance with age. Therefore, although we found strong evidence of general reproductive senescence in tsetse, variation in the onset and rate of senescence was not explained by resource allocation trade-offs or the costs of reproduction.

In tropical forests, trees strategically balance growth patterns to optimize fitness amid multiple environmental stressors. Wind poses the primary risk to a tree’s mechanical stability, prompting developments such as thicker trunks to withstand the bending forces. Therefore, a trade-off in resource allocation exists between diameter growth and vertical growth to compete for light. We explore this trade-off by measuring the relative wind mortality risk for 96 trees in a tropical forest in Panama and testing how it varies with tree size, species and wind exposure. Surprisingly, local wind exposure and tree size had minimal impact on wind mortality risk; instead, species wood density emerged as the crucial factor. Low wood density species exhibited a significantly greater wind mortality risk, suggesting a prioritization of competition for light over biomechanical stability. Our study highlights the pivotal role of wind safety in shaping the life-history strategy of trees and structuring diverse tropical forests.

Quantifying trade-offs within populations is important in life-history theory. However, most studies focusing on life-history trade-offs focus on two traits and assume trade-offs to be static. Our work provides a framework for understanding covariation among multiple traits and how population density influences the traits. Using detailed individual-based data for Soay sheep, we find density strongly shapes life-history trade-offs and distribution of lifetime reproductive success (LRS). At low density, a trade-off between juvenile survival and growth structures life-history variation whereas at equilibrium density (K), trade-off between reproduction and juvenile survival is the major structuring axes. Contrary to Lomnicki’s prediction, we find the distribution of LRS is highly constrained at K, with mothers of adult sizes contributing the most to reproduction. Our results offer insights into how high density limits diversity of individual life-histories, advance an understanding of dynamic nature of trade-offs and have implications for evolution via density-dependent selection.