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bioRxiv2025

Phylogeny, ecology, and allometry: hierarchical controls of insect elemental composition

Elemental composition links organismal physiology to biogeochemical cycles, yet the relative importance of evolutionary and ecological drivers remains unresolved for insects. Integrating a global stoichiometric database with a comprehensive phylogenetic backbone, we demonstrate hierarchical control of insect stoichiometry, with phylogeny accounting for [~]50% of variation in C:N:P ratios, followed by temperature, body mass, trophic group and habitat. We also identify nutrient enrichment in terrestrial lineages relative to aquatic ones. Our work offers a general framework for partitioning evolutionary, ecological, and physiological influences on organismal stoichiometry, highlighting new avenues to link macroevolutionary patterns to underlying processes.

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bioRxiv2026

Large language models unlock the ecology of species interactions

Species interactions shape population dynamics, geographic distributions, evolutionary trajectories, and responses to environmental change. Yet data on these interactions remain scarce across broad spatial, temporal, and taxonomic scales because they are difficult to collect in the field. One promising source of interaction data is citizen science platforms, which contain billions of biodiversity observations, often accompanied by unstructured text comments that may document interactions among organisms. Advances in large language models (LLMs) make it increasingly feasible to identify, extract, and categorize biotic interactions from these unstructured data at scale. Here, we present an LLM workflow that collects species interaction observations from multilingual citizen science comments. Using two case studies--bird-bird and plant-pollinator interactions--we show that LLMs can rapidly extract interaction types and participating species with high accuracy. These data can greatly expand the spatial, temporal, and taxonomic coverage and resolution of species interactions data, enable new tests of long-standing ecological questions, and improve our ability to track ecological changes. With appropriate validation, expert review, and attention to data privacy for both users and sensitive species, this approach opens new opportunities to characterize, forecast, and conserve biodiversity under global change.

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bioRxiv2026

Historical ecology and stakeholder perspectives can inform peatland fire management

Climate change is increasing wildfire risk globally and peatlands have become increasingly vulnerable to fire in recent decades. We combine social research methods with analysis of historical ecological (palaeoecological) records to understand links between fire, climate, vegetation and land use. Stakeholders in the Peak District (UK) highlight the need for scientific research and local knowledge to be more frequently embedded into policy. Analyses of historical ecological datasets reveal regime shifts in moorland vegetation following periods of fire activity and managed burning. This type of disturbance can lead to dominance of grasses, which may have a negative impact on peatland carbon balance under warmer climatic conditions. Recent fires are contributing to the loss of Sphagnum moss and greater dominance of heath and grass. Restoring peatlands, through re-establishing native woodland and improving peat bog hydrological conditions, alongside careful planning around controlled burning, are key measures to enhance resilience to future fire events.

ecology↗

bioRxiv2026

Temperature station matching for elevation-standardised ecological meta-analysis

O_LIStandardising temperature data across heterogeneous study sites is essential for ecological meta-analyses, yet elevation-driven lapse rates often confound direct comparisons of coarse-grid climate data. Ecological studies frequently document only site altitude - particularly historical datasets - limiting analysis of thermal influences on spatial organism distribution. C_LIO_LIA dual-approach protocol was developed to derive regional correction factors ({Delta}H) from altitude-temperature regressions (Lapse Rate Method: SW Germany/Italian Alps, n=33 stations) and cross-regional station pairs (TAV Matching Method, n=27) with closely aligned long-term mean temperatures ({Delta}TAV [≤] 1.2{degrees}C). Applied to 109 Ixodes ricinus study sites across nine European regions, correction factors were calculated only for regions with consistent altitude shifts ({Delta}H > 100m) relative to Southwest German reference stations. C_LIO_LIRegional correction factors ({Delta}H) from both methods included +1300 m (Finland, TAV Matching), +370 m (Netherlands/NE Germany, TAV Matching), and -220 m (Italian Alps, Lapse Rate Method) across five regions. In total, 27 cross-regional TAV matched pairs demonstrated high matching precision (median {Delta}TAV = 0.05{degrees}C, 89 % [≤] 0.2{degrees}C). These factors standardised site altitudes to a common SW German thermal reference frame, enabling cross-site comparability. C_LIO_LIThe dual-method protocol requires no automation and is applicable to any taxa with documented site altitudes. The complete methodological workflow - including station data, lapse rate regressions, matching decisions, and correction calculations is publicly available at Zenodo [DOI 10.5281/zenodo.18835116], providing ecologists with a pragmatic, fully reproducible template for elevation-standardised temperature estimation in meta-analyses. C_LI

ecology↗

bioRxiv2026

A novel pipeline for the rapid expansion of ecological trait databases using LLMs

This paper presents a novel workflow leveraging Large Language Models (LLMs) to rapidly extract trait data from fungal species descriptions, addressing a significant bottleneck in ecological research. We developed and evaluated an LLM pipeline to extract morphological trait data from arbuscular mycorrhizal fungi, comparing performance against a manually curated dataset (TraitAM). Results demonstrate the potential of LLMs for automated trait data acquisition, though accuracy varies by trait and model, with systematic biases observed. This framework offers a blueprint for building trait databases across diverse taxa and domains, significantly accelerating ecological research and conservation efforts.

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bioRxiv2026

Ecological context unmasks cryptic effects of glyphosate tolerance on soybean metabolism and performance of the virus vector Epilachna varivestis

O_LIGlyphosate-tolerant Roundup Ready (RR) soybean, engineered with the CP4 EPSPS gene, is one of the worlds most widely cultivated GM crops, yet its ecological consequences under realistic multi-species biotic conditions remain poorly understood. We investigated how RR soybean and its near-isogenic non-GM counterpart respond to concurrent colonization by two rhizobacteria, Bradyrhizobium japonicum and Delftia acidovorans, infection by Bean pod mottle virus (BPMV), and feeding by the virus vector Epilachna varivestis. C_LIO_LIUsing a fully factorial multi-species design, we combined LC-MS/GC-MS metabolomics, weighted co-expression network analysis (WGCNA), and herbivore performance bioassays to assess genotype-dependent shifts in soybean metabolism and their consequences for herbivore performance. C_LIO_LIUnder baseline conditions, RR and non-GM plants were metabolically indistinguishable. Under concurrent microbial and viral stress, RR plants diverged markedly, prioritizing selective isoflavonoid accumulation and lipid remodeling over broad-spectrum defenses, and showing attenuated rhizobacteria-mediated benefits for herbivore survival. These genotype-specific effects were entirely absent in single-species treatments. C_LIO_LITransgene effects on soybean metabolism and tritrophic interactions are cryptic under simplified experimental conditions but emerge clearly under ecologically realistic multi-species stress, with direct implications for how GM crops are evaluated in agricultural and regulatory contexts. C_LI

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bioRxiv2026

Co-occurrence networks can preserve emergent properties of ecological communities

Interaction networks, in which nodes represent species and edges represent direct interactions between species, have a long and impactful history in community ecology. However, co-occurrence networks, where edges represent statistical relationships among species presences or abundances, are often easier to construct from lab and field data. It is clear that co-occurrence edges often do not represent direct interactions, but frameworks for the interpretation of co-occurrence networks have not kept pace with their generation. It is therefore unclear when and how these networks can be used to gain insight into community dynamics. Here, we use a Generalized Lotka-Volterra-based model to explore the contexts in which emergent properties of species interaction networks are identifiable in their resulting co-occurrence networks. We find that, in spite of many differences in direct edges, key features of the true interaction network, such as unipartite modularity, high-degree nodes (hubs), and bipartite modularity and nestedness, can be preserved in co-occurrence networks. In contrast, node degree distributions are not preserved even in the most idealized scenarios. We propose that networks derived from large co-occurrence datasets could therefore be used in future empirical work to test existing hypotheses of how emergent network structures drive ecological community dynamics.

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bioRxiv2026

Complex trait responses to complex environments: how do larval amphibians navigate co-occurring ecological demands that influence the same traits?

O_LIMany organisms alter phenotypically plastic traits in response to environmental cues to match their phenotypes with variable environments. In larval amphibians, development and growth rates respond to spatiotemporally variable mortality risk from predation, wetland drying, or resource limitation. However, these rates are also temperature-dependent for ectotherms. Although wild animals experience these factors simultaneously (e.g., thermal regimes, predation risk, resource limitation), most studies investigate their impacts in isolation, limiting our understanding of how they interact across ecological contexts. C_LIO_LIHere we simultaneously exposed larval Plains Leopard Frogs (Lithobates blairi) to varying resource levels and predation risk treatments across a thermal regime to investigate the joint effects of these ecological drivers on growth and development rates and their consequences for size and vagility after metamorphosis. We crossed two predation treatments (waterborne cues from Procambarus gracilis fed L. blairi larvae, control water) with three food resource levels (5%, 25%, 50% of body mass) and six thermal regimes (diel {+/-} 3{degrees}C cycles of 15, 20, 22, 24, 26, 28{degrees}C), replicating each combination five times for a total of 180 individuals. We recorded growth and development rates and completion of metamorphosis, then measured juvenile body size and jumping performance. C_LIO_LIThe number of larvae completing metamorphosis was primarily determined by temperature and temperature-dependent effects of resource limitation. Percent metamorphosis peaked at intermediate temperatures when resources were high and were higher in predation-risk treatments at the warmest temperatures. Under high resources, development and growth rates showed unimodal thermal responses that were absent when resources were constrained. Higher resources increased development rates, but proportional increases in growth maintained constant body size across temperatures. Post-metamorphic body size differed only by predation treatment, with predator-exposed individuals being smaller. Juvenile jumping performance increased with body size and individuals raised with high resources without predator cues exhibited the highest performance. C_LIO_LIThe absence of temperature effects on size at metamorphosis reflected unexpected coupling of growth and development rates across treatments, producing uniform body sizes. This pattern contrasts with the temperature-size rule and suggests that plastic responses may exhibit selection for a minimum viable size at metamorphosis. C_LI

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bioRxiv2026

Regional ecological variation drives isotopic niche divergence in Pacific nautiloids

Nautiloids, the only surviving externally shelled cephalopods, persist in isolated Indo-Pacific reef slopes despite life-history traits that limit dispersal and recovery. Yet the ecological basis of their persistence remains poorly understood. Here, we compare carbon ({delta}13C) and nitrogen ({delta}15N) isotope values from seven nautiloid populations (including Nautilus and Allonautilus) spanning the Pacific. Isotopic niches varied strongly among locations, but only weakly among species, suggesting that geographic context rather than phylogenetic identity is the primary driver of trophic differentiation. Populations from the Bismarck Sea and American Samoa exhibited elevated {delta}15N, consistent with regional nutrient cycling and nitrogen fixation, whereas Great Barrier Reef (GBR) nautiloids displayed unusually broad {delta}13C ranges linked to possible reef-derived carbon subsidies. These results reveal how local oceanography and resource availability shape isotopic niches in long-isolated populations, providing a framework for understanding both the ecological resilience and evolutionary divergence of ancient cephalopods in modern oceans.

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bioRxiv2026

The centrality of ecotones: How scale, sex, and ontogeny shape the spatial ecology of a solitary carnivore

ContextAnimals balance resource acquisition with risk mitigation. These trade-offs are rarely uniform, being mediated by spatial scale, demographic traits, and environmental constraints. Understanding these divergent spatial behaviors is critical for management across human-dominated landscapes. ObjectivesWe investigated how sexual dimorphism and ontogeny interact with landscape structure to influence scale-dependent resource selection. Specifically, we sought to determine how these demographic factors mediate spatial trade-offs between optimal foraging habitats, top-down intraguild predation risk, and bottom-up severe winter weather. MethodsWe examined the spatial ecology of a solitary carnivore, the bobcat (Lynx rufus), across a heterogeneous, human-modified landscape in northern Minnesota, USA. Using spatial data derived from harvested adult and juvenile individuals, we evaluated multi-scale selection relative to land cover, structural ecotones, intraguild predator activity, and winter severity. ResultsHabitat selection was scale-dependent and partitioned demographically. Whereas bobcats universally selected for ecotones and avoided homogeneous open habitats at fine scales, responses to other features diverged by sex and age. Females actively avoided areas with high coyote activity and freezing temperatures; males exhibited high risk tolerance, apparently indifferent to coyote activity and tolerant of freezing temperatures. We identified a distinct ontogenetic spatial shift among females. Subordinate juveniles were competitively excluded from optimal natural ecotones, forcing them into riskier, anthropogenic agricultural edges. In contrast, adult females optimized foraging opportunities by selecting productive ecotones at the intersection of woody vegetation and semi-natural grasslands. ConclusionsOur findings demonstrate that habitat selection is not a static species-level trait, but instead a dynamic process resulting from the interaction between ontogeny, sex, and landscape heterogeneity. The reliance of vulnerable demographic groups on marginal or anthropogenic habitats highlights how human land-use changes can inadvertently produce ecological winners and losers within the same species. Consequently, landscape management and conservation planning for solitary carnivores must shift from broad, population-wide habitat prescriptions to strategies that explicitly accommodate the divergent spatial requirements of specific demographic cohorts.

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bioRxiv2026

STEM-LM: Spatio-Temporal Ecological Modeling via Masked Language Model for Joint Species Distribution

Joint species distribution models (JSDMs) are central to biodiversity forecasting and conservation decision-making. As ecological datasets grow in size, dimensionality, and spatio-temporal resolution, there is a need for flexible yet scalable JSDMs tailored to large-scale species observation data. Recent advances in masked language modeling for text and genomics suggest a natural alternative: by treating each species presence or absence as a token, and a sites species assemblage together with its spatio-temporal and ecological covariates as a sentence, we can learn joint co-occurrence structure by reconstructing masked species from their neighboring sites. We propose STEM-LM1, a Transformer-based JSDM that frames joint species distribution modeling as masked language modeling. By varying the masking rate during training, a single trained model supports both purely spatiotemporal/ecological prediction and conditioning on arbitrary subsets of observed species for joint co-occurrence inference at a given site. On a North American butterfly and a global plant distribution dataset, STEM-LM performs better or on par with other statistical and deep-learning based methods in terms of discriminative ranking, while producing substantially better rank-calibrated occurrence probabilities. Utilizing partial species observations at the same site greatly enhances prediction performance.

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bioRxiv2026

Scouting ecological drivers of natural enemies in citrus orchards: implications for biological control in the Corsican agricultural landscape

O_LIEffective pest control requires a better understanding of natural enemy ecology, particularly how their distribution responds to landscape structure and local management. Agricultural intensification has simplified landscapes, reducing biodiversity and constraining pest control. Landscape-scale surveys are therefore needed to identify strategies that support natural enemies in agricultural systems. C_LIO_LIFrom 2021 to 2022, over three seasons, we surveyed 25 clementine orchards across a gradient of landscape complexity in Corsica. We modelled the tree-level occurrence of four natural enemy species in relation to ecological context across multiple spatial and temporal scales. Site-level evenness, reflecting differences in species occurrence frequencies, was also estimated to assess how natural enemy assemblages vary across local management and landscape gradients. C_LIO_LIClimate and local management were the primary drivers of species occurrence, with additional contributions from landscape factors. Species displayed distinct responses, while model performance increased with the number of sampled trees, plateauing at around half of the sampling effort. C_LIO_LISite-level evenness was higher in organic orchards than in conventional orchards. In conventional orchards, it responded to landscape structure in a scale-dependent manner, increasing at the larger scale with the heterogeneity and spatial continuity of semi-natural habitats. C_LIO_LISynthesis and applications. Organic farming enhances natural enemy presence and diversity in Corsican citrus orchards, while the naturalness and complexity of surrounding landscape can mitigate species scarcity in conventional orchards. We recommend continued long-term monitoring of arthropod communities in these systems, prioritizing the number of sampling sites and years while reducing the number of trees sampled per site to optimize effort. C_LI

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bioRxiv2026

Prey diversity revealed by environmental DNA elucidates ecological specialisation and social structure in bottlenose dolphins

Human disturbance drives rapid biodiversity loss, yet how prey diversity shapes individual niche differentiation and scales up to structure social organisation remains poorly understood, particularly in marine systems where prey are largely invisible to observation. Here we mapped prey community structure ( prey fields) using environmental DNA metabarcoding, integrating these maps with stable isotope data and >20 years of behavioural observations on bottlenose dolphins. We show that dolphins specialised on specific prey fields to varying degrees, and that none of 471 tracked individuals changed their predominant prey field -- even through climate-driven habitat reorganisation. Isotope profiles confirmed dietary differentiation scaling with specialisation strength. Across four independent sex-subpopulation networks, prey field overlap predicted social affinity in non-foraging contexts, revealing that prey community structure organises social ties beyond foraging. These results expose a socio-ecological link between prey diversity, trophic ecology, and social organisation, providing a transferable eDNA framework for predators with elusive prey.

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bioRxiv2026

Ecological Cascades and Future Hantavirus Spillover Risk in a Changing Climate

Anthropogenic climate change is reshuffling global biodiversity and accelerating zoonotic spillover at the human-wildlife interface. The 2026 multi-country cruise ship outbreak of Andes virus highlights the unpredictable and globalized threat posed by rodent-borne orthohantaviruses, which cause severe, highly fatal human diseases worldwide. Despite this significant public health risk, macroecological synthesis linking environmental drivers to systemic shifts in hantavirus hazards has been lacking. Here, we implement an integrated ecological and machine learning framework combining 89 unique virus-host associations across 61 reservoir species with mechanistic Force-of-Infection (FOI) modeling to project global spillover hazards under current and future climate scenarios (SSP2-4.5 and SSP5-8.5) for 2041-2060. Our models demonstrate a spatially uneven but geographically extensive expansion of spillover hazards, with approximately 74.9% of modeled land area experiencing an increase in FOI. We identify three distinct high-hazard belts heavily concentrated in already-temperate reservoir ranges: western and central North America, central and northeastern Europe extending into western Russia, and discrete patches within central South America. Crucially, our findings reveal that hantavirus hazards are fundamentally shaped along virus-specific ecological axes. While thermal and precipitation anomalies predominate the transmission dynamics of Old and New World lineages like Sin-Nombre virus and Thailand virus, distinct urban-centric Profiles emerge for Seoul virus and Mamore virus, driven explicitly by fine-scale anthropogenic landscape modifications. These results reveal that climate change will not simply intensify viral spillover uniformly but will fundamentally restructure it across varied climatic and human-dominated environments. Our maps provide a critical baseline for targeted global surveillance and highlight the urgent need to integrate spatial conservation planning with public health preparedness.

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bioRxiv2026

Ecological Impacts of Additive-Enriched LDPE Microplastics in Agricultural Soils: Single and Multi-Species Assessments

Low-density polyethylene (LDPE) microplastics (MPs) are the most frequently sampled type of microplastic in agricultural soils, potentially threatening the soil environment. The majority of MPs that have been investigated are produced from standard polymer formulations, for which the nature of the added compounds is often unknown. Furthermore, standard ecotoxicity tests performed on model species are insufficient for assessing the ecological consequences of MPs contamination in soil. This study examined the responses of multiple keystone species to exposure to MPs in interaction with various additives. No significant effects on their growth were observed when organisms were exposed to MPs alone. However, significant reductions in growth occurred when organisms interacted within uncontaminated soil: the introduction of plants reduced potworm biomass by 49 {+/-} 4.1 % while the introduction of potworms reduced earthworm biomass by 41 {+/-} 5.2%. In MP-contaminated soil containing plants, the average individual biomass of potworm increased significantly from 1.16 {+/-} 0.09 mg in uncontaminated conditions to 2.01 {+/-} 0.27 mg. This suggests that MPs limited the negative effects of interactions. Similar patterns were observed for the potworm-earthworm interaction. MPs containing the highest concentrations of additives induced the strongest biological responses. Analysis of soil parameters revealed that these impacts are likely linked to the disruption of nitrogen cycling. Therefore, it is imperative to comprehensively address the interactions between soil organisms and the influence of additives on plastic ecotoxicity in order to better assess the ecological risk posed by MPs.

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bioRxiv2026

Nocturnal pollination services as an ecological safety net for papaya production in a tropical biodiversity hotspot

Pollination is of key importance for tropical agriculture, yet a bee-centred perspective often overlooks the critical role of nocturnal insects in pollination services. We evaluated the relative contributions of diurnal and nocturnal pollinators to papaya yields on subsistence farms in the Taita Hills, Kenya, a globally important biodiversity hotspot. We combined flower visitor observations with five experimental treatments: open pollination, wind-only (closed), hand pollination, and temporal exclusions for day-only and night-only services. Our results reveal complete temporal niche partitioning between diurnal bees and nocturnal hawkmoths (Sphingidae). We found that diurnal and nocturnal pollinators provide additive, rather than redundant, services, contributing to papaya fruit set and weight to a similar extent. Despite these contributions, supplementary hand-pollination experiments indicated a significant yield gap (36.9% lower fruit set), suggesting substantial pollinator limitation. While landscape-scale factors had no significant effects, nocturnal pollinators responded positively to organic management, whereas diurnal visitors did not. This indicates that local habitat quality and ecological intensification are more critical for sustaining specialised pollinators than landscape composition. Our study highlights the vital role of nocturnal insects as an ecological safety net and emphasises that their conservation through local organic practices is essential for securing yield quantity and quality in tropical papaya farming systems.

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bioRxiv2026

Time-lagged causal inference corroborates presumed drivers of North Atlantic seabird ecology

Disentangling causation from correlation is the foundation of the scientific method. Yet, growing evidence suggests that much observational ecology research has not correctly made this distinction due to inappropriate statistical modelling and unappreciated time-delays. Here, we apply time-lagged causal inference techniques to assess the drivers of seabird declines, using multi-decadal North Atlantic seabird data across the behaviour, mass, survival, reproduction and population size of two species ecology (Atlantic puffin, Fratercula arctica, and black-legged kittiwake, Rissa tridactyla). We demonstrate that both climate and anthropogenic activity can suppress breeding success and cause population declines. Moreover, population size is specifically impacted by delayed recruitment effects where both species decline after a lag corresponding to their estimated age of first reproduction. These North Atlantic seabirds are therefore at risk from future environmental and anthropogenic changes, as time-delays may result in populations already on an extinction trajectory prior to changes being detectable in their abundance.

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bioRxiv2026

Exploring the use of state of nature metrics to screen global business operations for ecological sensitivity and to select priority sites for disclosure

Businesses are increasingly encouraged to disclose their nature-related dependencies, impacts, risks and opportunities. A common component of sustainability reporting is screening operational sites for ecologically sensitivity to identify locations for further evaluation and action. However, with 600+ biodiversity metrics available, selecting and interpreting appropriate metrics remains challenging for business. We developed a simple screening framework informed by the Taskforce for Nature-Related Financial Disclosures guidance, grouping eleven widely used global biodiversity metrics into four complementary [&prime]baskets[&prime], representing different aspects of biodiversity. We created hypothetical but realistic mining, onshore wind energy and agricultural companies, to assess how metric choice, buffer size, scoring approach and sensitivity thresholds influence screening outcomes. Our basket framework consistently identified similar high-priority sites across metric combinations, but site rankings varied with methodological choices. We recommend clearer guidance on metric selection and application, alongside greater transparency from business regarding assumptions, methods and limitations when screening sites for ecological sensitivity.

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