Biological Reviews

High Pathogenicity Avian Influenza (HPAI) H5N1 clade 2.3.4.4b has spread beyond birds to affect seals across the Southern Ocean and sub-Antarctic region, with southern elephant seals (Mirounga leonina) particularly devastated. The virus, likely introduced via spillover from infected migratory birds, has killed tens of thousands of adult seals and pups throughout most of their range, though Macquarie Island remains unaffected so far. We used twenty years of elephant seal movement data from the southern Indian and Pacific oceans to assess whether seal-to-seal transmission could spread HPAI H5N1 between breeding colonies, despite the vast distances separating them (Marion Island, Iles Crozet, Iles Kerguelen, and Macquarie Island). There was substantial overlap in seals' at-sea distributions during their winter post-moult trips, when seals travel for weeks at average speeds of 3.5 km/h. Two transmission pathways were examined: (1) terrestrial "stepping stone" routes, where infected seals could pass the virus between colonies during short intervals to remain infectious were feasible from Marion Island to Kerguelen but not from Kerguelen to Macquarie Island; and (2) at-sea encounters between seals, which occurred frequently enough to enable transmission. The findings suggest that once established at Macquarie Island, the virus could potentially spread further to New Zealand's sub-Antarctic islands and mainland New Zealand. While seal-to-seal transmission appears possible, we conclude this is unlikely. Nonetheless, understanding at-sea contact rates enhances knowledge of H5N1 epidemiology and demonstrates the value of combining long-term population monitoring with movement data to understand wildlife disease dynamics.

Despite the ecological importance of ungulate migrations, we lack a complete understanding of why some ungulates migrate and others do not. Though progress has been made towards understanding differences across species and between populations, migratory behavior varies even within populations: in many populations, some individuals remain behind as residents (partial migration). Theoretical population-level work has suggested that these different migratory tactics can coexist, but such approaches stop short of providing insights into how individuals make the decision to stay or go each year. Using long-term data from three ungulate populations, we find that individuals probabilities of migrating are highly variable across years, which points to a non-trivial context-dependent decision-making process, whose underlying mechanisms must be probed via individual-level modeling. Drawing on existing knowledge, we propose a decision-making model of ungulate migration onset wherein individuals probabilistically decide to start migrating based on the local intensity of environmental and/or social cues. Residents arise as a robust collective organization phenomenon in our model. At sufficiently large population sizes, the number of residents is invariant with total population size, consistent with empirical patterns. Instead, resident numbers are influenced by the severity of the bad season, by relevant character differences among individuals, and by how individuals contribute and respond to environmental and/or social cues; for instance, when social cues contribute to decision-making in addition to environmental ones, fewer residents result, and migration is more likely to be complete. Overall, our model provides a potential mechanistic explanation for how residents might emerge within migratory ungulate populations.

Aim: To forecast near-future arrivals of non-native terrestrial and freshwater vertebrates at the regional level. Location: Global (geopolitical regions worldwide, including countries and main administrative divisions). Methods: We compiled first regional record data and assembled functional and macroecological variables for 1,931 non-native vertebrate species. For each region, we identified recently arrived non-native species using retrospective windows of thirty and twenty years ending in 2015 (1986-2015; 1996-2015). We then fitted region-specific random-forest models classifying recently arrived species versus those not yet arrived using as predictors: (i) harmonised species traits (e.g., habitat, diet, body size and native-range attributes) and (ii) spread history, capturing time since first record elsewhere. Predictive performance was evaluated using leave-one-out cross-validation, comparing full models with trait-only and spread-only variants. We also assessed relationships between predictive accuracy, predictor importance, and the geographic positioning and trade connectedness of regions. Finally, we predicted region-specific probabilities of arrival for species not yet recorded. Results: Forecasting accuracy was consistently high across regions and taxa, with AUC values above 0.9 in more than half of the focal regions. Full models substantially outperformed models using either predictor set alone, and spread-history-only models typically exceeded trait-only models. Relative importance of spread-history predictors declined with geographic distance to the focal region, whereas predictability was lower in highly trade-connected regions. Predicted near-future high-risk arrivals were dominated by birds and freshwater fishes and showed strong regional structuring. A small set of species ranked highly across many regions (e.g., birds: Phasianus colchicus, Acridotheres tristis, Amandava amandava, Colinus virginianus, Corvus splendens and Lonchura malacca; fishes: Coregonus peled and Oreochromis mossambicus; mammal: Oryctolagus cuniculus), suggesting substantial unrealised spread potential. Main conclusions: Near-future regional arrivals of non-native vertebrates are predictable from spread history and species traits. This enables scalable, updateable regional watchlists to support prevention, early detection and horizon scanning.

Collective movement requires coordination between individuals, yet how this emerges during early interactions remains poorly understood. We investigated how partner familiarity influences coordination, leader-follower dynamics, and learning in homing pigeon pairs navigating from novel sites. Birds were released repeatedly with either familiar or unfamiliar partners, followed by solo releases to assess learning. By quantifying bidirectional information flow, we found familiarity influenced information-transfer dynamics during the first release: familiar pairs exhibited more asymmetric information transfer, likely reflecting established leader-follower relationships, whereas unfamiliar pairs showed more symmetric exchange. These differences disappeared after one release. Conversely, familiarity had little effect on cohesion or navigational performance. There was some evidence for an influence on learning: birds from familiar pairings had higher homing efficiency on a subsequent solo release. Finally, across partnerships, followership was more predictable than leadership with respect to individual identity and flight speed, indicating stable variation in individuals' tendency to follow rather than lead. This suggests that a shift in emphasis from leadership to followership might enhance our understanding of collective decision-making dynamics. Our results demonstrate how flight partners rapidly coordinate, producing limited downstream effects on navigation and learning, with implications for many animals that travel in fission-fusion transitory collectives.

One of the most intuitive ideas in ecology is that diversity at lower trophic levels in food webs provides niches to support diversity at higher trophic levels. This accumulation of diversity can be limited by survival of species in the landscape, but revealing these limits has been challenging. We analyze spatial turnover in a hyperdiverse parasitoid-caterpillar-plant food web across 75,000 km2 of continuous lowland rainforest in Papua New Guinea. Species turnover across sites is higher in parasitoids than in their caterpillar hosts. Furthermore, turnover of interactions is also higher in parasitoid-caterpillar than caterpillar-plant networks. Spatial turnover thus amplifies upwards across trophic levels, forcing parasitoids to live closer to spatial persistence limits. Consequently, progressing rainforest fragmentation can especially endanger parasitoids.

Vocalizations are increasingly proposed as indicators of affective state in animal welfare research. Yet many studies assign context-derived affective valence to vocalizations and then classify these using machine learning according to those context-derived labels. This circular dependence makes it unclear whether successful classification reflects affective state itself, broader contextual or acoustic differences, or the interpretive categories imposed by the task. Therefore, we examined human organization of pig vocalizations using free-classification and forced-choice tasks, and compared these patterns with acoustic structure recovered by convolutional neural network models. In a free-classification task, 224 participants sorted 2,192 pig vocalizations into self-defined categories. Next, in two forced-choice tasks, 159 participants recruited in a second wave classified vocalizations using predefined context and valence categories. Free classification revealed reproducible but broad perceptual structure rather than recovery of discrete recording contexts. Participant-generated labels for pig vocalizations were predominantly descriptive and spontaneous valence-related labeling was limited (19.6%) yet primarily negative. Forced-choice classification of recording context was weak (8.0% exact accuracy) and showed only slight agreement with source contexts. Valence judgments were more structured (60.1% exact accuracy), but agreement with the valence categories used to characterize the recording contexts was modest and largely driven by highly aversive situations such as castration, restraint, fighting, and crushing. After excluding pig vocalizations from these contexts, agreement with context-associated valence categories disappeared. Human-derived perceptual structure closely corresponded to convolutional neural network embedding spaces, indicating that human listeners and machine-learning models recovered similar acoustic organization. These findings suggest that pig vocalizations contain robust and recoverable acoustic organization, but that this organization only partially aligns with the contextual and valence frameworks commonly used to interpret it. More broadly, the results highlight a distinction between recovering acoustic structure and establishing its biological meaning, with implications for affective research and animal welfare assessment.

Biodiversity is predicted to stabilize ecosystems if species have different environmental responses. How this response diversity is shaped by ecological and evolutionary processes remains poorly understood. We determine the drivers of thermal response diversity of 16 Swiss peri-alpine lake-fish communities. We report the first evidence that evolutionary diversification of lineages through adaptive radiation can increase the response diversity of an ecosystem. In-situ diversification increases response diversity in the cold-deep lake environment, but non-endemic and non-native species contributed only weakly to response diversity. The loss of endemic species during historical anthropogenic eutrophication led to a negative legacy on present thermal response diversity in cold and deep lake strata. Overall, the interplay of evolutionary diversification, ecological assembly and anthropogenic impacts drives variation in response diversity. Conserving and restoring processes that generate diversity may help maintain ecosystem stability beyond the Anthropocene.

Emerging infectious diseases threaten public health and biodiversity across the globe1,2. Disease outcomes are frequently dependent on local environmental conditions3-5, but how these factors shape host adaptation and long-term recovery are often unknown6. Here we combine two decades of population, disease, and environmental data with a common garden experiment to investigate the drivers of variable declines and recovery for remnant bat populations following the emergence of the fungal disease, white-nose syndrome. We find that initial declines were greater and faster in warmer sites (88.3% vs. 74.2% in cold sites), but these populations recovered more quickly and hosts developed higher resistance (1.5x reduction of fungal loads) than populations from colder sites that were buffered from initial impacts. Our experimental data suggest that warm sites served as hotspots of host adaptation where selective pressures were stronger because thermal conditions approached optimal growth for the pathogen, which eventually favored the development of high pathogen resistance. Populations in colder sites experienced weaker selective pressure and thus remain more susceptible, although bats from larger colonies were more likely to survive, suggesting that adaptive traits exist in these populations, but at much lower frequency. These findings show that the environmental conditions that initially buffer populations from collapse can simultaneously constrain their evolutionary response to emerging threats, and ultimately determine differential recovery following disease-induced declines.

Introgression following hybridization is increasingly recognized as a major driver of evolution. However, its importance depends on its frequency in nature, which remains to be quantified. To address this, we provide a snapshot of ongoing introgression in a whole species assemblage (4126 ant colonies). 23% of all 82 local species show signs of introgression, which is more than twice previous estimates. Introgression is typically subtle, yet we find that it contributes measurably to genetic diversity. Species divergence, rather than classical prezygotic reproductive barriers (mating phenology, ecological niche, fine-scale habitat use) constrains introgression, suggesting that the main reproductive barriers are postzygotic at this stage of divergence. Our results indicate that introgression may be a common but often overlooked feature of natural communities.

In order to feed a growing global population without silencing nature, conceiving agricultural management strategies reconciling yield and conservation goals is key. Using numerical simulations of a metacommunity model, we explore the possibilities for compromise offered by spatial management strategies of farmed areas. Each strategy is characterized by its farming intensity, the proportion of farmed lands and their spatial aggregation. We show that achieving equitable yield-biodiversity compromise is difficult. While conciliatory strategies offering top yield and biodiversity are typically not possible, accepting slightly lower yields (ie, "Pretty Good Yield strategies") allows to recover substantial biodiversity. Such reconciliation possibilities are limited for species with small dispersal. Yield increases mainly through farmland expansion, whereas farming intensity strongly influences biodiversity, increasing it at low intensity before decreasing with further intensification. Finally, we demonstrate that reconciliation is easier if agricultural production relies on biodiversity through ecosystem services.

Collembola (springtails) are among the most abundant and ecologically important soil arthropods, representing one of the oldest extant terrestrial hexapod lineages, with a fossil record extending to the early Devonian. Despite their relevance, phylogenetic relationships among the four extant orders (Entomobryomorpha, Poduromorpha, Symphypleona, and Neelipleona) have remained unresolved for over two decades. Here, we present the most comprehensive phylogenomic analysis of Collembola to date, comprising 1,127 single-copy orthologues from 145 taxa representing 19 families. To improve orthology inference, we developed a novel HMM-based filtering pipeline that significantly reduced hidden paralogy in BUSCO-derived datasets. Across multiple dataset configurations, gene-jackknife replicates, and various maximum-likelihood analyses, we consistently recovered Poduromorpha as the earliest-diverging lineage. Coalescent-based methods instead highlighted discordant arrangements characterised by extremely short internal branches and low quartet support, a pattern consistent with pervasive incomplete lineage sorting and reticulate evolutionary history. We further dissected the phylogenetic signal by exhaustively evaluating all possible inter-order topological arrangements, both on the full concatenated dataset and gene-by-gene, to identify the most phylogenetically informative loci. These analyses rejected the great majority of previously proposed hypotheses, narrowing support to only two statistically indistinguishable topologies (T11 and T4), with the Poduromorpha-first arrangement consistently favoured across both site-homogeneous and site-heterogeneous substitution models. Finally, with molecular dating, we estimated the origin of crown Collembola in the Early Devonian, with the diversification of the extant orders in the Carboniferous. Several extant genera were estimated to be older than many currently recognized families, highlighting the exceptional evolutionary persistence of springtail lineages and suggesting that lineage longevity should be considered when interpreting higher-level taxonomic diversity.

Protein language models (PLMs) score the effects of amino acid replacements as pseudo-probabilities, which are widely utilised to map protein fitness landscapes. However, because their training data relies on natural amino acid sequences, these models conflate protein structural constraints with nucleotide mutation biases and codon accessibility. Using the rapid emergence of the divergent influenza A H3N2 K lineage as a stress test, we investigate how base PLMs (ESM-2 and ESM-C) versus fine-tuned versions of these models capture mutational processes. We systematically implement a parameter sweep to explicitly couple (or decouple) empirical nucleotide mutational supply from PLM-assessed amino acid substitution pseudo-probabilities across evolutionary forecasting tasks. We find that base PLMs implicitly learn generic nucleotide-level mutational constraints, an effect strongly amplified by virus-specific fine-tuning. Incorporating explicit mutational accessibility significantly improves the binary prediction of observed amino acid changes. Conversely, when predicting the final circulating frequency of variants that have already emerged, adding mutational supply degrades performance, confirming that selection dominates post-emergence dynamics. Additionally, we perform amino-acid-level epistatic scanning to investigate protein structural constraints in the context of genetic background. This indicates the improbable antigenic substitution I160K is dependent on co-occurring S144N and N158D mutations in the H3N2 K lineage. Ultimately, current PLM pseudo-probabilities are a composite metric that conflates protein structural fitness with historical biases in mutational supply. Explicitly decoupling these independent evolutionary processes optimises predictive accuracy for real-world pathogen forecasting and isolates pure protein fitness for synthetic design pipelines.

Animal vocalisations can convey information about external events, but whether this goes beyond reflecting the emotional state elicited by these events is debated. To explore this, we studied the acoustic structure of common marmoset (Callithrix jacchus) phee (long-distance contact) and ek (alert/mobbing) calls produced in five treatments varying in the emotional valence and arousal they elicit (internal state), as well as food and social context (external events). We measured changes in arousal via nasal temperature and analysed both basic acoustic parameters and Mel-frequency cepstral coefficients (MFCCs) of the calls. Support Vector Machines combined with Linear Mixed effect models revealed that phee calls encode both external events and internal states, while eks reflected predominantly arousal. Notably, an acoustic signature related to food context was present in phees both when provided (positive valence) and teased with highly preferred food items (negative valence), and even when food was not physically present (food call playback treatment). This suggests marmoset long-distant phee calls encode external information beyond emotional arousal and valence, and independently of the presence of an immediately triggering stimulus.

Conjugative plasmids drive the dissemination of antimicrobial resistance genes and other conditionally beneficial accessory genes, but otherwise inflict fitness costs on their hosts that limit their spread. These costs can be ameliorated by compensatory mutations on the chromosome, the plasmid, or both combined (combined compensation). Mutants with plasmid-borne or chromosomal compensation differ in how they spread and compete, making the location of compensation an important determinant of plasmid and antimicrobial resistance (AMR) dynamics. We collate experimental data on plasmid-host co-evolution which, albeit limited, suggest compensatory benefits differ by location and are highest for combined compensation. We develop and analyse a mathematical model of compensatory evolution, finding that the long-term location of compensation is mainly determined by the highest cost reduction. Short term, however, succession dynamics arise from differences between locations: for instance, plasmid-borne compensation spreads horizontally, initially dominates, and can even facilitate the establishment of chromosomal or combined compensation. Strong trade-offs between compensation and either resistance or conjugation render compensation non-viable, but only conjugation trade-offs are location-dependent, disadvantaging plasmid-borne compensation and generating oscillatory dynamics. Our findings suggest plasmid-borne compensation may initially accelerate AMR-plasmid spread, whereas long-term chromosomal or combined compensation may enable hosts to accumulate multiple AMR-plasmids, promoting multidrug resistance.

To make adaptive foraging decisions, naive individuals need to gather information about the local prey community. Besides sampling prey personally, the young could gather information about prey profitability by observing the foraging behaviour of other individuals, and parental provisioning provides the first opportunity to acquire this social information. Still, previous research on vertical transmission of prey preferences from parents has provided mixed results that are often confounded with other information sources, such as siblings and peers. It is also not known whether information from parents can change potential innate biases against certain prey types, such as avoidance of warningly coloured insects. Here, we tested whether social information acquired by offspring during parental provisioning influences the development of prey preferences in a generalist predator, the Great Tit (Parus major). We brought 15 great tit broods and their parents into captivity at late nestling stage (14 days old) and divided them into three social information treatments where parents were provided with either brown, red or yellow palatable maggots to feed to their dependent young for 8 days. Once foraging independently from parents, we conducted a preference test where juveniles were offered the full array of coloured maggots. Regardless of palatable exposure to typical warning-coloured maggots (i.e. red and yellow), juveniles consistently preferred yellow over red, and preferred brown maggots the most (i.e. lacking warning coloration). This supports the existence of innate biases against typical warning colours, and that social information from parents is unlikely to override these, at least when alternative prey is easily available.

Predators are often considered regulators of disease in prey populations, a concept central to the "healthy herd hypothesis". This hypothesis suggests that by preferentially removing infected individuals, predators can reduce parasite prevalence. However, predators may also act as disease vectors, facilitating the spread of parasites. We investigated whether stickleback fish (Gasterosteus aculeatus) can act as vectors for the transmission of the obligate bacterial parasite Pasteuria ramosa to its Daphnia host, a widespread freshwater zooplanktor. We fed infected D. magna to sticklebacks, and subsequently analysed faecal samples for the presence, viability, and infectivity of parasite transmission stages (= spores). We recovered approximately 60% of the consumed spores from fish faeces and these spores did not suffer from reduced infectivity to D. magna. Additionally, spores associated with sloppy feeding did not reduce infection rates. Thus, consumption of infected hosts by fish does not eliminate the parasite, but in contrary, may contribute to the spread and persistence of P. ramosa in natural populations, potentially influencing parasite dynamics in natural freshwater ecosystems.

Effective conservation depends on demographic metrics that reliably reflect species status, particularly population abundance. For elusive species occurring at low densities, however, such metrics remain difficult to obtain. Spatial capture-recapture (SCR) models are the standardized approach for estimating density in marked populations, but their data requirements, especially the need for multiple spatial recaptures across individuals, often limit applicability in small or data-poor populations. This constraint has resulted in knowledge gaps for some of the most vulnerable species, undermining evidence-based conservation planning and management. Using camera-trap data and SCR-derived density estimates from data-rich populations, we evaluated alternative, less data-demanding metrics and tested the hypothesis: Space to Event (STE), Mean Local Abundance (MLA), and Relative Abundance Index (RAI) exhibit predictable relationships with SCR-derived density; if supported, these metrics can reliably estimate density in populations where SCR models cannot be implemented. We applied this framework to the European wildcat (Felis silvestris), an elusive small felid with highly fragmented populations across Europe, for which density estimates are largely lacking despite growing conservation concern. Across 21 study areas spanning most of the species' range, our results indicate that European wildcats generally occur at lower densities than previously reported. SCR-derived estimates (n=10) averaged 10.32 {+/-} 11.56 inds/100km2, while STE enabled density estimation in five additional data-poor areas (mean 5.52 {+/-} 5.33 inds/100km2). STE showed a strong linear relationship with SCR-derived density (R2=0.98), supporting its use as a viable alternative when SCR is infeasible, although it tended to underestimate compared to SCR, especially at higher densities. In contrast, MLA and RAI showed weaker and non-linear relationships with SCR-derived density (R2=0.65), indicating substantially lower explanatory power and suggesting their estimates are more strongly influenced by confounding processes. By explicitly calibrating alternative metrics across a wide density gradient throughout most of the species' distribution, this study provides a transferable methodological framework for estimating density in low-density wildlife populations and the first continent-wide, standardized density assessment of a carnivore species. From a management perspective, our findings identify populations that may be most vulnerable, particularly those with the lowest densities, and highlight the need to prioritize absolute abundance monitoring.

The global invasion of the Asian tiger mosquito Aedes albopictus has led to an increase in arboviral disease, including within Mesoamerica. Understanding vector invasion routes is important for public health because it directs biosecurity and identifies sources of adaptive allele spread. Panama is an important hub of global trade with opportunities for Aedes introduction through both maritime and overland routes but dispersal into the Isthmus has not yet been investigated. We therefore sought to investigate the population structure and invasion history of Ae. albopictus into Panama, targeting both its mitogenome and associated Wolbachia. Historical demographic analysis with Bayesian phylogeographic diffusion models and estimates of divergence revealed that Panamanian Ae. albopictus and its associated Wolbachia have a convergent evolutionary history resulting from multiple introductions. Both could be traced to Asian-derived lineages introduced via the Americas, with invasion primarily through the maritime trade of the Panama Canal rather than overland dispersal from neighboring Costa Rica. An investigation of the relative density of Wolbachia in Panama revealed that both the strains wAlbB and wAlbA were at a notably lower density compared to other worldwide locations. This finding has implications for arbovirus transmission and raises important questions about how Wolbachia density is impacted by the environment and impacts on population control. Overall, the Panama Canal is a key route for vector introductions into Mesoamerica.

Under complex perturbation regimes, biodiversity dynamics show temporal variability in species and community abundance around long-term population trends. Many species indeed show long-term declines while other species increase, putting natural communities far from stationary regimes, while variability is often studied near equilibrium. We contribute to bridging this gap by investigating population and community variability during long-term trends caused by press perturbations in stochastic models of population dynamics. By estimating the deterministic changes in mean and variance during the transient regime, we show that population variability deviates from stationary expectations. Moreover, the deviation strongly depends on the sign of the population trends: increases generate excesses of variability while declines generate deficits. Scaling up to community variability, we propose a decomposition of community variability deviation, allowing to highlight that community variability in the transient regime depends on how the press perturbation is distributed within species relative abundances and growth rates. These results challenge the equilibrium assumption and open new perspectives for the study of the variability of ecological systems under multiple perturbation types.

The deepest ocean is one of the most extreme environments for life on our planet, combining near-freezing temperatures, low oxygen levels, and hydrostatic pressures reaching 111 MPa (1100 atm). Extreme pressures are predicted to alter many aspects of biology, including the physical properties of biological hydrogels, protein structure, and the solubility of gases in water. How organisms have adapted to live in these conditions is poorly understood. Studying these organisms in situ is difficult and requires specialized deep-sea equipment capable of withstanding the extreme pressure; raising these organisms in captivity is also challenging due to their extreme habitat requirements. Given these difficulties in studying deep-sea organisms, we set out to identify the problems shallow-dwelling organisms face due to increased pressure. These can provide insights into how organisms tolerate life in the deepest parts of the ocean. This project aims to take embryos of the shallow-dwelling aquatic organism Xenopus laevis, determine how surface-dwelling organisms fail under high hydrostatic pressure, and identify a means to survive this deadly pressure. We have designed a system to expose different embryonic stages of X. laevis to high pressures and observe its effects. After identifying the limits of survivability, we sought to understand how these embryos can acclimate to changing pressures. Comparative RNA-seq and cross-species analyses revealed a conserved, pressure-induced transcriptional response across phyla, with the heat shock pathway among the most strongly activated. Pre-activation of this pathway via prior pressure or other stressors enhances survival under otherwise lethal hydrostatic conditions.