Environmental conditions such as temperature and resource availability can shape disease transmission by altering contact rates and/or the probability of infection given contact. However, interactive effects of these factors on transmission processes remain poorly understood. Here, we develop mechanistic models and fit them to experimental data to uncover how temperature and resources jointly affect transmission of fungal parasites (Metschnikowia bicuspidata) in zooplankton hosts (Daphnia dentifera). Model competition revealed interactive effects of temperature and resources on both contact rates (host foraging) and the probability of infection given contact (per-parasite susceptibility). Foraging rates increased with temperature and decreased with resources (via type-II foraging), but this resource effect weakened at warmer temperature due to shorter handling times. Per-parasite susceptibility increased with resources at cooler temperatures but remained consistently high when warmer. Our analysis demonstrates that temperature and resources interact to shape transmission processes and provides a general theoretical framework for other host-parasite systems.

not-yet-known not-yet-known not-yet-known unknown Zoonotic pathogens causing emerging infectious diseases pose escalating threats to global health, agriculture, and ecosystems. Avian influenza viruses (AIVs) are of particular concern due to their pandemic potential and complex dynamics at the wildlife–livestock–human interface. We constructed a bird species–AIV subtype bipartite network based on global wild bird infection records (1974-2024, 9,964 records). The network exhibits scale-free characteristics, indicating that different bird species vary in their importance within the network. We identified 23 hub species, all waterfowl from the orders Anseriformes and Charadriiformes, that likely play key roles in AIV transmission and reassortment. Interpretable machine learning showed that birds with strong flight ability, longer time foraging on water surfaces, greater longevity and higher diversification rates are more likely to be hub species. This study advances our understanding of the mechanisms underlying AIV transmission and provides guidance for designing more precise surveillance and control strategies.

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.

We investigated the decomposition of diverse root-associated fungi, their influence on native soil carbon dynamics and the relationship of these processes with fungal traits. We quantified the decomposition of 13C-labelled mycelium of fourteen species, their priming of native soil carbon, impact on functional soil carbon pools, microbial use of carbon and microbial community size and composition and evaluated chemical, morphological, and physiological traits of the fungi to investigate their potential to control carbon processes. Fungal C/N, melanin and growth rates were linked to necromass decomposability and its stabilisation. Necromass addition commonly caused suppression of native soil carbon decomposition (negative priming), including that of the resistant pool, and this suppression was stronger as fungal decomposability decreased. We provide novel, clear evidence of linkages between root-associated fungal traits, necromass decomposition, microbial C use and soil C stability which builds our mechanistic understanding of the role of dead fungi on soil C storage.

In June 2023, the United Nations adopted the High Seas Treaty. Two years later, signatories are poised to ratify this treaty and create a legal instrument to implement marine protected areas (MPAs) in our greatest global commons, ocean areas beyond national jurisdiction. Protection of the open and deep ocean is timely: we stand at the precipice of an industrial revolution in Earth’s largest remaining wilderness. Deciding where to strategically implement high seas MPAs under this treaty requires robust biodiversity information, yet publicly accessible data is sparse, particularly at depth. There is now an opportunity for collective science action to support this collective policy action. Realizing this opportunity necessitates swift solutions to 1) support and incentivize standardized public sharing of existing biodiversity data; 2) broaden the scope of participatory science to process ocean observations into biodiversity data; and 3) equitably implement new data collection with research partners across our global community.

Allometry, the scaling traits or biological rates with body mass, is central to a wide range of ecological research including dynamic food web modelling. There has been extensive focus on exponents (3/4 scaling laws), but little on the coefficients (normalisation constants). Current coefficients for metabolism and production are derived from limited data and dated methodologies. Here, we expand these data to over 1000 genera with body mass spanning 10 orders of magnitude. We updated metabolism and production coefficients deriving new genus and metabolic group levels estimates with phylogenetic hierarchical modelling providing robust inference. Our coefficients were mostly lower than those previously estimated, with increased uncertainty estimates. We then used the Bioenergetic Food Web Model to evaluate their impact, finding increased biomass and species persistence but no change in stability. Our coefficients pave the way for future simulations that take advantage of subsets of genus and metabolic group data.

Adaptation to abiotic stresses generally relies on traits that are not independent from those affecting species interactions. Still, the impact of such evolutionary processes on coexistence remains elusive. Here, we studied two spider mite species evolving separately on tomato plants that either hyper-accumulated cadmium, a stressful environment for the mites, or on control plants without cadmium. Through combining experimental evolution and structural stability theory, we found that adaptation to cadmium of both species shifted predictions from exclusion to coexistence. This shift occured due to a simultaneous increase in intra and a decrease in interspecific competition, but only in cadmium environments. These predictions were further confirmed with complementary experiments of population dynamics, underscoring that evolution of single species in a new environment, even in absence of interspecific competitors, shapes species coexistence. Hence, population shifts to novel environments may have unforeseen evolutionary consequences for community composition and the maintenance of species diversity.

Emerging infectious diseases (EIDs) threaten biodiversity, yet identifying key host species in complex ecological communities remains a major challenge. Here, we develop a quantitative framework combining field data, epidemiological modelling, simulations, and Bayesian inference to pinpoint key viral hosts in multispecies bee communities. Using flower–visitor interaction data and molecular virus screening, we estimate species-specific basic reproduction numbers (R₀) and assess the role of key hosts in virus transmission and persistence by testing two competing hypotheses: viral spread driven by a key host versus community-wide traits (e.g. network connectance). We show that, while honeybees often act as primary reservoirs, others, such as the red-tailed bumblebee, can drive the spread of specific viruses. Viral dynamics are primarily explained by exposure to key hosts, while the community effects are highly variable. Identification of non-honeybee key hosts challenges existing assumptions and highlights drivers of transmission and pathogen persistence in complex host–pathogen networks.

The routine generation of species distribution data \textit{at scale} remains a challenge. We used aquatic environmental DNA metabarcoding to sample vertebrate species across the 30,000 sqkm Gaoligongshan region along the China-Myanmar border. In just 56 calendar days (33 researcher-field-days + 69 researcher-lab-days), we detected 389 vertebrate species, of which 35 are Red-Listed. We introduce the ‘eDNA-aware’ OccPlus occupancy model, which accounts for false-negative and false-positive error in the field and lab. OccPlus leverages the taxonomic breadth of eDNA datasets by using ordination to estimate species occupancies. We recover known biogeographic patterns and find that native terrestrial and fish species have higher occupancies inside protected areas while domesticated species and non-native fishes have higher occupancies outside them. Our study demonstrates how eDNA metabarcoding can obtain high-quality, granular, timely, trustworthy, and efficient species distribution data to facilitate nature conservation and restoration.

Population recovery following environmental stress is known to depend on demographic structure, life-history and evolutionary dynamics. However, it is unclear how evolution of traits shaped by sexual selection affect population dynamics and recovery. We examined this by manipulating presence/absence of males expressing either a non-aggressive “scrambler” phenotype or an aggressive and lethally armed “fighter” phenotype in soil mite populations of different size. We experimentally altered the male phenotype in populations, subjected them to heat stress, and analyzed their population dynamics and recovery. We show that populations with fighter males exhibited i) reduced population size and stability, ii) greater decline in response to heat stress in larger populations, iii) higher rate of growth, and iv) incomplete population recovery. Such reduced population stability and recovery linked with armed and aggressive phenotypes underlines the importance of sexual selection in mediating population dynamics and resilience to environmental change with implications for managing natural populations.

The grey wolf (Canis lupus L., 1758) exemplifies ecological resilience, surviving major climatic fluctuations since the Middle Pleistocene. Once the world’s most widely distributed mammal, its range has been drastically reduced by human-driven habitat loss, persecution, and competition for resources. Although globally listed as Least Concern by the IUCN, the omission of climate change as a threat raises critical questions about long-term resilience. This study investigates the dietary flexibility of European grey wolves across interglacials using dental microwear texture analysis (DMTA). We compare modern Polish wolves with fossils from two contrasting British interglacials: the Last Interglacial (MIS 5e) and penultimate interglacial (MIS 7a–c). By integrating palaeodietary data with palaeoenvironmental and palaeoclimatic evidence, we evaluate how past adaptive strategies may buffer wolves against future change. Results demonstrate deep-time dietary plasticity and recurrent behavioural shifts, suggesting that while the grey wolf is resilient, future warming winters may significantly reshape wolf diets in the mid-latitudes.

Freezing tolerance plays a pivotal role in shaping the distribution and diversification of organisms. We investigated the dynamics of adaptation to climate and potential trade-offs between stem freezing tolerance and growth rate in 48 Quercus species. Species from colder regions exhibited higher freezing tolerance, lower growth rates and higher winter-acclimation potential than species from warmer climates. Despite an evolutionary lag, freezing tolerance in oaks is closely aligned with its optimal state. Deciduous species showed marked variability in freezing tolerance across their broad climatic range while evergreen species, confined to warm climates, displayed low freezing tolerance. Annual growth rates were constrained in all deciduous species but those that evolved in warm latitudes lost freezing tolerance precluding a trade-off between freezing tolerance and growth. We provide evidence that capacity to adapt to a wide range of thermal environments was critical to adaptive radiation and current dominance of the North American oaks.

Global change is complex and multidimensional, making it challenging to understand how human activities affect ecosystem processes. A critical gap in this understanding is how drivers of global change broadly affect food webs. While an industry of studies documents shifts in energy pathways within food webs in response to anthropogenic pressures, a synthesis that links these shifts to structural and functional changes in food webs is lacking. To address this, we review studies across diverse ecosystems that use stable isotope analysis, energetic food web modelling, and gut content analysis to reveal the prevalence of asymmetric rewiring---a phenomenon whereby anthropogenic pressures differentially impact habitats across space, altering some energy pathways relative to others. We then highlight several examples from the literature to illustrate how this process unfolds. To explore its broader consequences, we use a simple food web model to demonstrate how asymmetric rewiring alters resilience and key ecosystem functions, such as primary and secondary production. Our synthesis uncovers a remarkably general response in food web structure to global environmental change that needs to be better understood to protect nature and the services that human societies rely on in a rapidly changing world.

Current global changes are driving many species towards extinction, making the early detection of threatened species a priority for efficient conservation actions. However, the threat status of many species remains unknown due to insufficient data on updated distributions, population sizes and population trends, and using ecological indicator traits, such as range size, is not always straightforward. Recent advances suggest that macroevolutionary indicators (rates of extinction, net diversification or niche evolution) could provide novel insights into extinction risk based on the assumption that macroevolutionary rates can serve as proxies for extinction-promoting traits (small range size, narrow niche breadth or low evolutionary potential). However, this assumption has not yet been sufficiently investigated to use this approach. Here, we assess current understanding of the assumptions underlying the relationship between macroevolutionary indices and contemporary extinction risk. We find that only past extinction rates can be reliable predictors of current extinction risk due to their correlation with inherited extinction-promoting traits. Assumptions underlying relationships between current extinction risk and diversification and niche evolution rates vary by taxon or ecological conditions, and require further investigation through targeted studies. When underlying assumptions are validated, macroevolutionary indicators could be promising tools complementing trait-based approaches in identifying inherent extinction risk.

Debates over whether and how populations are regulated have recently shifted away from detecting and instead towards quantifying the strength of density-dependence and its variation among systems. Yet, the degree of variation in density-dependent mortality and the factors driving this variation remain poorly understood. Here, we conducted a meta-analysis of 38 reef fish species across 56 studies, which yielded 147 estimates of intraspecific density-dependent mortality, primarily during early or small life stages. The magnitude of density-dependent mortality (the increase in the per capita mortality rate due to one fish per unit area of habitat) was surprisingly inconsistent both within and among species. Several factors emerged as drivers of variation. Predators amplified the negative effects of density, and density-dependent mortality was greater for species that typically colonize at low densities or achieve larger maximum size. However, even within a single species, the strength of density-dependent mortality varied dramatically — often by several orders of magnitude — and sometimes changed sign. This remarkable heterogeneity suggests that environmental variation might overshadow species-specific traits or that methodological variation among studies constrains our ability to perceive drivers. Our results underscore the need for future efforts to identify the factors that drive this variability in population regulation.

Climate change is increasing extreme heating events and the potential for disease outbreaks. Whether hosts can adapt to infection with rising temperatures is important for forecasting species persistence. We tested whether warming -- at different host life-stages -- affects the ecological and evolutionary dynamics of resistance in Caenhorabditis elegans infected by a wild bacterial pathogen. We competed genotypes across 10 passages and tracked the spread of resistance in the population. Infection and prolonged warming strongly selected for the resistant genotype. Warming during host development induced plastic defenses against infection, reducing the selective pressure for costly genetic-based resistance. Resistance was lost under ambient temperatures and periodic warming. Selection for resistance was likely weakened at ambient temperatures by the dilution effect, whereby resistant genotype reduced pathogen transmission. Evolutionary dynamics of resistance depend on the balance among pathogen virulence, costs of genetic-based resistance, the dilution effect, and plastic defenses induced by temperature stress.

Plant-microbe interactions are critical in shaping forest dynamics, yet molecular functions through which foliar endophytic fungi (FEF) influence seedling survival and coexistence remain unresolved. Combining FEF transcriptomics with seedling dynamics in a subtropical forest, we tested whether FEF molecular functions regulate seedling survival via host fitness differences and niche differentiation under modern coexistence theory. We found FEF transcripts diversity strongly associated with host divergence time and maximum height, and FEF functions significantly enhance seedling survival through fitness-related and niche-related processes. Among these FEF functions, gene ontology (GO) terms with high host-phylogeny dependence enhance seedling survival through fitness differences associated with stimulus responses and multi-organism interactions, and those with high host-trait dependence enhanced seedling survival through fitness differences related to basic life processes. For GOs independent to host-phylogeny and host-trait, they enhance seedling survival via increased niche differentiation. Our findings bridge microbial functional genomics with modern coexistence theory in natural forests.

Accurate prediction of community assembly is a central goal in ecology but is challenging because assembly could be governed by numerous mechanisms. Few theoretical models explicitly incorporate or test multiple mechanisms at once. We empirically tested the predictive performance of a plant community assembly model built using all possible combinations of four mechanisms (resource competition, spatiotemporal niche differentiation, dispersal and colonization, population growth rates) and 11 underlying attributes based on measured plant traits (e.g. fecundity, phenology). The full model accurately predicted out-of-sample observations of five grasses sown in mixture along a soil nitrogen gradient (overall R2 = 0.65). Alternative model variants, parameterized using subsets of the mechanisms and their nested attributes, still retained high explanatory power if the model included at least three of the four mechanisms. Our results suggest that plant community composition is determined by simultaneous effects of multiple mechanisms, and simpler theories have much lower predictive abilities.