Ecology

Ecologists remotely track movement steps of animals (e.g., via global positioning systems) and use step selection functions to study the effect of environmental factors upon their movement decisions. Constructing such functions requires pairing each observed step with some number of unobserved but feasible comparison steps. Larger numbers of comparison steps generally yield better estimates but also incur potentially challenging computational demands. Thus, it is important to determine an appropriate number of comparison steps. No established guidance exists for this decision. Here, we use simulated tracks to assess how many comparison steps are needed, fitting each set of steps to a conditional logistic regression model. We monitor errors in estimated effects for several classes of tracks, identifying the number of comparison steps for which mean relative absolute error in estimated effects is consistently low. By this criterion, 32 comparison steps per observed step are needed for our primary class of simulated tracks. Tracks in more homogeneous landscapes, tracks with shorter mean step lengths, or shorter tracks generally require more comparison steps (ranging from 64 to 128 per observed step) to achieve the same level of accuracy. Longer tracks generally require fewer comparison steps (16 per observed step). These results clearly demonstrate that the number of comparison steps influences how well step selection functions estimate covariate effects and provides initial direction in a research area that currently lacks quantitative guidance. Movement ecologists should take care when selecting the number of comparison steps paired with each observed step because those decisions matter.

Heritable bacterial symbionts are pervasive in terrestrial arthropods, often imposing reproductive manipulations to promote their own spread within host populations. Co-infections are common, potentially allowing symbiont co-infectors to hitchhike through a host population. However, adverse thermal conditions can disrupt these communities, particularly when co-infectors vary in their thermal sensitivity. We used a multi-generation experiment to test whether warm (29 {degrees}C) conditions disrupted spread of heritable symbionts through uninfected populations of the spider, Mermessus fradeorum. We tested two common infection combinations: a single infection with a cytoplasmic incompatibility (CI) inducing Rickettsiella or a feminizing co-infection that included a feminizing Wolbachia, the same Rickettsiella, and up to three apparent hitchhikers (two additional Wolbachia strains and Tisiphia). We initiated replicate populations with 1/3 of one infection type and 2/3 uninfected spiders, evaluating population infection rate over 5 spider generations under different temperature regimes. Under cool (21{degrees}C) conditions, Wolbachia feminization drove co-infection to 88% and Rickettsiella CI drove single infection to 83% of host populations. Vertical transmission for all symbionts was high (97-99%) and hitchhiking symbionts also spread effectively. Under warm conditions, feminization and CI efficacy were reduced, and symbionts suffered variably reduced vertical transmission. Warm conditions ultimately destroyed the co-infecting symbiont consortium and impeded symbiont spread. On its own, though, Rickettsiella was still able to increase, despite reduced strength of CI. We hypothesize that contrasting tensions between feminizing spread of the symbiont consortium versus environmentally driven loss of function and transmission may explain observed patterns of mixed infections in field populations of this spider.

Urbanization is reshaping freshwater ecosystems, with well-documented effects across gradients of land-use change, hydrologic alteration, and habitat degradation. However, how biodiversity is organized among neighboring urban aquatic habitats that differ in hydrologic connectivity, disturbance transmission, residence time, management history, and opportunities for species movement is often less clear. This creates a challenge for interpreting urban fish communities at local scales as species occurrence may reflect both contemporary habitat filtering and historical contingencies including native persistence, interbasin transfer, stocking, and nonindigenous introductions. Here we use eDNA detections, historical records, phylogenetic information, and species trait data to investigate the fish assemblages of the Charlotte metropolitan region. We detect a highly mixed fauna that also depicts a strong signature of structured biodiversity profiles across taxonomic, phylogenetic, functional, and life-history dimensions between habitat types. In particular, bounded habitats contained assemblages with larger-bodied species that are fecund and faster to reproduce relative to free-flowing habitats. Species-level occurrence models did not support a simple trait-by-habitat rule. Instead our results demonstrate that urban aquatic habitats can sort historically mixed regional species pools into predictable assemblage-level life-history profiles while simultaneously retaining signatures of evolutionary and historical biogeographic contingency.

The shape of density-dependence governs species persistence, and ecosystem stability. Yet, whether per-capita growth declines sublinearily, or superlinearily with density remains hotly debated. Growth rates across the tree of life have been shown to decline sublinearly with density, whereas theory founded on resource competition predicts the opposite. Here, we resolve this discrepancy and show that sublinearity can readily emerge from geometric constraints on consumer interactions. By linking inter individual spacing, movement and interference rates, we derive two limiting-interference regimes, one of which the well-mixed limit recovers the form of classic Beddington DeAngelis interference response. We then developed an individual-based model from first principles which reproduces the derived sublinearity response, and further use empirical data from published consumer-resource experiments that also bears the signature of sublinear density-dependence. Further, embedding the interference mechanisms underlying the emergence of sublinear density-dependence in coexistence theory opens a new regime for species coexistence where classical theory fails to predict. Our framework indicates that non-consumptive interactions are not merely a correction to resource competition but might be a distinct axis along which diverse communities may potentially coexist.

Squid abundance has been reported to increase globally between 1970 and 2010. This increase has been hypothesized to result from two primary factors: the loss of top predators due to overfishing and rising ocean temperatures. The decline in apex predators may lead to the expansion of squid populations either through reduced predation pressure or diminished competition with juvenile predators. Concurrently, increased temperatures could enhance the somatic growth rates of squid, thereby accelerating their population growth. However, empirically disentangling the impacts of predator loss and temperature on squid biomass remains challenging, especially in a food-web context. In this study, we used a size- and trait-based model of upper trophic levels that resolves the ecosystem structure -- biomass and trophic interactions of fish and squid -- for varying depth, temperature, and secondary production, to investigate two hypotheses of the historical expansion of squid, i.e., the effects of predator depletion from fishing and rising temperatures on squid biomass. Our model reveals that intensified fishing of squid predators -- specifically large demersal fish in shelf systems and large pelagic fish in open oceans -- leads to a slight increase in squid biomass. Conversely, elevated temperatures are associated with a decline in squid biomass. This temperature-driven reduction in biomass is attributed to an increased metabolism of squids beyond the available food supply. If historic overfishing on large marine predators continues to be curtailed, we expect a corresponding reduction in global squid biomass and fisheries potential, which could be further exacerbated by rising temperatures.

Intertidal mudflats are low hydrodynamic energy environments hosting microphytobenthic communities that experience strong spatiotemporal variability in light regimes, including changes in spectral quality and light intensity that can lead to cellular photooxidative stress. To cope with these fluctuations, autotrophs exhibit diverse and highly plastic adaptations that are often species-dependent and shaped by their ecological niches. This study investigates photophysiological responses and metabolic remodeling in a diatom assemblage originating from a natural winter microphytobenthic biofilm under contrasting red and blue light intensities. To this end, photosynthetic parameters were monitored alongside changes in lipophilic metabolites, including untargeted lipids and lipophilic pigments. While few metabolites showed temporal remodeling, rapid and contrasting changes were observed within 30 minutes in response to both spectral quality and light intensity. Red light treatments induced broader remodeling of lipophilic metabolites than blue light, whereas blue light appeared to have a greater impact on photosynthetic parameters. Moreover, red light induced xanthophyll-cycle responses comparable to those observed under blue light at equivalent incident intensity. We discuss these metabolic responses in relation to diatom photoadaptive strategies, placing these findings within the intertidal environmental framework. This work further underlines the importance of understanding rapid metabolic plasticity in coping with light fluctuations, providing new insights into the photoregulatory strategies of natural microphytobenthic communities.

1. Forest canopies harbour strong microclimatic gradients that shape plant performance, species interactions and ecosystem processes. Yet, despite renewed interest sparked by global change, forest canopies remain difficult-to-access experimental spaces. 2. With the goal to expand access to tree canopies as experimental arenas, we designed, built, and tested TreeTOP, a standardized experimental platform that opens canopy space for manipulative ecological experiments, specifically with potted plants. TreeTOP features lightweight aluminum frames placed in mature tree canopies non-invasively, allowing potted plants to be placed in three different heights, ground level, shade canopy, and sun canopy. 3. We implemented TreeTOP using two contrasting infrastructure concepts to demonstrate its applicability in both highly equipped canopy research facilities and forests without permanent canopy infrastructure. One installation relied on a canopy crane, grid power and fully automated irrigation, whereas the second was built by certified tree climbers and was equipped with an autonomous solar-powered, battery-operated irrigation system. At both sites, environmental sensor networks monitor the experiment. 4. TreeTOP successfully reproduced characteristic canopy microclimatic gradients, including increasing light availability, daytime air temperatures and thermal extremes with canopy height. Despite differing infrastructures, both implementations generated comparable microclimatic patterns, demonstrating that standardized canopy experiments are feasible in forests with or without permanent canopy access. By opening canopy space for manipulative experiments, TreeTOP provides a transferable framework for investigating plant performance, phenology, species interactions and microbiome assembly under realistic forest conditions.

Most evidence of the consequences of climate change in natural systems has focussed on shifts in mean temperature (1,2), but the effects of extreme climatic events (ECEs) remain far less understood. This is particularly true for very severe ECEs that may occur only once every few decades. Understanding the consequences of these severe events for natural populations is nonetheless critical, since their frequency is predicted to rise under current climate change (3). Here we combine a unique long-term dataset spanning almost five decades of breeding (>20,000 events) and morphological data (>120,000 observations) in adult and nestling great tits (Parus major) and blue tits (Cyanistes caeruleus) with fine-scale temperature records to examine the effects of an unprecedented heatwave in May 2026 on breeding success and morphology. Average temperature during the heatwave (22-29 May 2026) was 7.85 C above the historical record, reaching +10.5 C (+4.32 SD) at its peak (25-26 May). These record-breaking temperatures significantly reduced adult breeding success and nestling bmass relative to expectation in the absence of a heat-wave. Given the heatwave was widespread (Fig. 1A), our findings from a single, exceptionally well-studied population are likely to generalise to other species exposed to the same event, providing key evidence that severe ECEs can substantially harm wild populations.

Rapid evolution allows populations to persist in environments where they would otherwise go extinct. This phenomenon, known as evolutionary rescue, is typically studied in the framework of biological evolution, yet adaptive traits can also arise and spread through cultural evolution. The present study developed a stochastic eco-evolutionary model to compare rescue probabilities through biological and cultural evolution. Transmission bias governed the rescue probability under cultural evolution by setting how readily a rare adaptive trait was copied. Conformity bias suppressed population persistence because a rare trait was the least likely to be copied. Content bias toward the adaptive trait enabled evolutionary rescue when social learning was rapid, but it typically yielded a lower rescue probability than biological evolution. Only anticonformity bias, together with a high social learning rate, exceeded the rescue probability of biological evolution by enabling the adaptive trait to be established more rapidly. These results demonstrate that transmission bias alters the demographic consequences of cultural evolution and highlight the importance of transmission processes in evolutionary rescue theory. Understanding how adaptive behaviours are socially transmitted may also improve predictions of animal population persistence and inform conservation efforts in rapidly changing environments.

Marine diatoms contribute to about 20% of global primary production. We present the first basin-scale, multiyear assessment of diatom communities in the North Pacific, combining taxonomically high-resolution RuBisCO large subunit gene (rbcL) metabarcoding with concurrent environmental measurements. Using a nine-year time series of daily samples resolved at the species level via ~500 bp rbcL fragments, we performed multivariate analyses across biogeographic provinces, identifying significant correlations between community structure and environmental drivers such as temperature and macronutrient availability. We report the prevalence of a previously overlooked centric diatom species in the North Pacific, Eunotogramma lunatum, which appears to be near-dominant even in subarctic high-nitrate, low-chlorophyll waters where pennate diatoms are typically favored. These results demonstrate the power of rbcL for large-scale ocean monitoring and provide a critical baseline for future studies of diatom population dynamics, climate change impacts, and ecosystem resilience in a key marine region.

Wildlife re-identification (re-ID) is a widely used and powerful tool with diverse applications in animal ecology and conservation. Current automated methods typically operate on single images of a single body part of the animal. However, a single encounter may contain multiple images capturing different body regions, each providing complementary individual-specific information. In contrast to automated approaches, researchers often manually select the most suitable images and regions for identification based on factors like visibility, occlusion and image quality. This creates a mismatch between automated methods and field practice, limiting the practical adoption of current automated re-ID pipelines. Here, we address this by introducing an encounter-based, multi-body-part re-ID framework, using sea turtles as a model taxon. Our framework combines three elements: (1) An orientation-aware deep learning model, TurtleDetector, that in addition to the full bodies, it also automatically segments key body regions, i.e. heads, front and hind flippers, from images within an encounter; (2) a hybrid body-part-specific retrieval method, that sequentially combines a fast global-feature model (MiewID or DINOv3) with a more accurate but costlier local-feature model (ALIKED with LightGlue); and (3) a merged identity-prediction strategy that selects the highest calibrated similarity score across all available body parts and images of an encounter. We evaluate the framework on three long-term re-ID datasets spanning three species, loggerheads, greens, and hawksbill turtles, under an evaluation protocol that mirrors real-world, time-aware re-ID workflows. Across datasets, combining multiple body regions consistently improved identification performance over the best-performing single body region, resulting to an increase of 4-6% in top-1 accuracy. Interestingly, body regions traditionally underused in sea turtle re-ID, such as the hind flippers and carapaces, provided complementary identifying information that improved encounter-level re-ID when integrated through the hybrid retrieval method. Our findings demonstrate that automated wildlife re-ID can benefit from moving beyond single-image, single-body-part identification towards encounter-level integration of all available visual evidence. Our work further suggests that, where feasible, field photo-acquisition protocols should aim to capture multiple informative views of an individual during each encounter. Importantly, many species and taxa, including elephants, primates, cetaceans, and other large vertebrates, possess such individual-specific features across multiple body regions, highlighting the broad potential applicability of our framework.

Citizen science observations are abundant, but conservation requires turning uneven records into reliable predictions and directing new surveys to where information is missing. We developed a biodiversity platform for Japan that is updated monthly and integrates 2.32 million records to predict 8,297 species across seven taxonomic groups. Shared representation models outperformed species-specific models in four groups and extended predictions to species with few records. Five independent datasets, including structured monitoring, environmental DNA and complete forest inventories, confirmed that the models ranked observed species and occupied sites above alternatives, with median AUCs of 0.724 to 0.894 across sites and 0.650 to 0.841 across species. For any user-selected area, the platform returns candidate species, distribution predictions, a biodiversity map corrected for uneven observation effort, a conservation priority map for native species and a map recommending where to survey next. This map highlights places where species with few records are predicted to occur despite limited sampling. Independent observations showed that areas ranked highly by this predicted potential contained many such species, indicating that model predictions can help direct surveys toward knowledge gaps. New observations are incorporated into monthly updates, creating a national feedback system connecting citizen science, local conservation decisions and future surveys.

Extrafloral nectaries (EFNs) are a widespread plant defense mutualism trait and are highly convergent, appearing in hundreds of plant lineages worldwide. Here we investigate a report of possible EFNs in Erythranthe angulosa, a recently-described California wildflower. We integrate field observations, insect bioassays, an induction experiment, and microscopy to test for signatures of EFN function, finding no evidence that the distinctive axillary swellings produced by E. angulosa function as EFNs. We also uncovered two distinct morphs at the type locality of E. angulosa that diverge in the number of axillary swellings produced, as well as other shoot architecture traits such as stem thickness, leaf size, and branch number. Although the axillary swellings appear to not function as EFNs, they remain a compelling morphological variant within the yellow monkeyflowers that may perform storage or another unknown function.

Antibiotic-induced disruption of plant-associated microbiomes has the potential to alter host health beyond the directly exposed generation, yet whether the effects of dysbiosis are transmitted through the seed microbiome remains unknown. Here, we investigated the intergenerational impacts of streptomycin-induced dysbiosis in tomato (Solanum lycopersicum), demonstrated that seed microbiome transfer (SMT) restores progeny microbiome function and disease resistance, and characterized the underlying physiological and genetic mechanisms. Parental streptomycin exposure altered the composition of progeny rhizosphere bacterial communities, reduced expression of defense-associated genes, and increased susceptibility to Xanthomonas perforans. Suppression of immune gene expression was strongly associated with increased disease severity, indicating that parental dysbiosis impaired progeny plants ability to mount effective immune responses. Transfer of the seed microbiome from healthy plant donors partially restored rhizosphere community composition, reduced disease severity and recovered defense gene expression of three genes. Together, our findings demonstrated that antibiotic exposure microbiome disturbance generates intergenerational legacy effects that influence plant immunity and disease susceptibility and seed microbiome transfer can counteract this dysbiosis across generations.

Context Pumping stations pose a threat to fish globally through land use change, habitat fragmentation and entrainment risk, with the catadromous and critically endangered European eel particularly impacted. Objectives/methods Establish, model, assess and understand the present-day distribution of European eel and resident fishes in 152 pumping station catchments in a once extensive wetland (The Fens) using eDNA metabarcoding (855 samples over two and half years), with specific focus on anthropogenic influences on hydrological connectivity and habitat quality. A removal survey design maximised confidence in negative results while minimising time and consumable costs. Results Eel occurrence upstream of pumping stations was low (occupancy = 28.3%) and positively associated with catchment area, fish species richness and natural hydrological connectivity (gravity drainage or flooding) and negatively associated with distance from the tidal limit. Fish species richness replaced catchment area and improved model performance, potentially acting as a biotic indicator of habitat quality and connectivity. Pumped catchments with manually operated upstream water transfers had reduced eel presence, potentially linked to the direction of water flow or the timing of operation. By contrast, fish species richness increased in these catchments during summer, suggesting displacement into unsuitable long-term habitats. Physical habitat maintenance had no detectable effect on eel occurrence or fish species richness. Conclusions This study provides the first landscape-scale assessment of European eel distribution and drivers of occurrence in pumped river catchments. The highly novel and comprehensive insights have implications for European eel conservation as well as infrastructure and catchment management, including compliance with legislation (EC Regulation No. 1100/2007).

The southern sea otter (Enhydra lutris nereis) population at San Nicolas Island, California, has been monitored annually since the translocation of 140 sea otters to the island was completed in 1990. Monitoring efforts have varied in frequency and method across years. In 2017, in accordance with the National Defense Authorization Act for Fiscal Year 2016, the U.S. Navy and the U.S. Fish and Wildlife Service formally initiated a sea otter monitoring and research plan to determine the effects of military readiness activities on the growth or decline of the southern sea otter population at San Nicolas Island. The monitoring program, at its basic level, includes quarterly seasonal surveys of population abundance, distribution, and foraging activity. This report presents data from the program with a focus on the recent three years from winter 2023 through winter (February) 2026. From 2023 to 2026, we measured an 8.1-percent per annum decrease in population abundance (95-percent confidence interval =1.1-14.6 percent), with 106 total individuals counted as of February 2026. Historically, sea otter habitat usage at San Nicolas Island was concentrated on the west end of the island. Between 2017 and 2019, we observed increased seasonal usage of the north and south sides of the island, and in 2020-2022, a large (approximately 30-40 individuals) group of sea otters (raft) took up residence off the east end. During 2023-2026 the east end raft disappeared, and sea otters returned to their historical habitat usage patterns at the west end of the island. Foraging data were collected from summer 2023 to winter 2026 on a total of 461 foraging dives in 32 foraging bouts, and the majority of identified prey on successful dives (n=325) were sea urchins (124) followed by snails (48), bivalves (41) and crabs (23). One lobster and one octopus were also identified among the sea otter prey items. We combined these data with data from 2020-2022 to estimate overall energy intake rates that averaged 7.7 kilocalories per minute (95-percent credible interval =6.6-9.1 kilocalories per minute). These results can be useful to the planning of future monitoring and research of sea otters at San Nicolas Island.

Plant cold acclimation emerges from coordinated adjustments in photosynthesis, primary metabolism, and intracellular carbon allocation. Yet, the regulatory role of subcellular metabolite compartmentation in natural variation of cold acclimation remains insufficiently understood. Here, we investigated four Arabidopsis thaliana accessions grown either individually or in bulk to determine how growth configuration and genotype shape the metabolism of sugars and organic acids during cold exposure. Using non-aqueous fractionation, we quantified plastidial, cytosolic, and vacuolar sugar pools alongside whole-cell carbohydrates, organic acids, enzyme activities, photosynthetic parameters, and stress markers. A neural-network classifier revealed that subcellular sugar distribution together with sugar amounts and organic acids provided the strongest discriminatory power among accessions, surpassing photosynthetic traits and enzyme activities. Our findings demonstrate that natural variation in cold acclimation is strongly determined by genotype-specific subcellular metabolite architectures, and that the cultivation strategy modulates these intracellular signatures. We conclude that subcellular compartmentation of metabolites represents a cellular control layer for natural variation of cold acclimation and resilience in Arabidopsis thaliana.

All living organisms rely on the movement of ions across cell membranes as the fundamental physical basis of their internal energy and signaling, and plants are no exception. Plants perceive, integrate, and respond to environmental stimuli through electrical signals, classified as action, variation, and system potentials, that are coupled with calcium waves, reactive oxygen species, and hydraulic and hormonal changes to coordinate whole-organism responses despite the absence of a nervous system. Yet most studies characterize these signals using a single feature, such as amplitude or spike duration, in a single tissue, an approach that cannot establish how such signals correspond to the underlying ionic activity, mobility, and structural complexity of the signaling environment, or how this correspondence varies across organs. Here, we correlate plant bioelectrical signals with potential ionic energy flow using a multi-domain framework, combining discrete spike events, continuous waveform properties, spectral composition, and signal complexity applied to leaf, stem, and root recordings from tomato (Solanum lycopersicum) exposed to different stimulus. Electrical activity with increased stimulus strength, likely reflecting increased ionic flow, with the root showing the largest response. This suggests plant electrical signaling works as a distributed, ion-based information system, useful for stress monitoring and bio-inspired sensor design.

Water-use efficiency (WUE), the ratio of accumulated plant biomass to water lost through transpiration has conventionally been determined using a destructive single-point measurement. Recent advances in high-throughput phenotyping now enable repeated, non-destructive estimation of biomass and WUE. However, these digital measurements must be statistically validated against conventional destructive methods to validate their use as reliable proxies. Therefore, we compared digital biomass determined point clouds produced from multispectral camera scanners with destructive harvests across eight harvests using Samsun tobacco grown under both drought and high-water conditions. WUE efficiency, calculated using the digital biomass estimated from a point cloud and gravimetric water use determinations, were compared to destructive harvest determinations. The coefficient of variation (CV) showed there were no significant differences in digital and destructive measurements for either biomass or WUE. Indicating that digital measurements can be used in place of destructive measurements. Drought plants used significantly less water and were significantly smaller than high-water plants from Harvests 4 through 8. However, there were no significant differences in the ratio of evapotranspiration to leaf area or WUE, indicating that drought plants were simply smaller and used less water than the high-water plants. This work validates that estimating plant biomass from a digital point coupled with continuous gravimetric determination of water use provides a reliable nondestructive measure of WUE in high-throughput measurements across the full plant life cycle.

Anterograde and retrograde signalling establish bidirectional communication between the nucleus and chloroplasts. Retrograde signals from chloroplasts regulate nuclear gene expression while anterograde signals from the nucleus coordinate chloroplast development and maintain cellular homeostasis. How this bidirectional signalling framework extends beyond locus-specific regulation to shape the global spatial organization of nuclear chromatin across tissues remains unclear. Although anaesthesia can alter chromatin organisation, the role of chloroplast dysfunction in these changes remains unclear. Here, we investigate how chloroplast dysfunction and anaesthesia influence euchromatin and heterochromatin organisation in Solanum lycopersicum seedlings across tissues with contrasting photosynthetic competence. Using confocal and super-resolution radial fluctuation (SRRF) imaging with quantitative multiparameter analysis, we identify distinct, tissue-specific chromatin responses to chloroplast disruption and anaesthesia. Notably, anaesthesia induces distinct spatial chromatin changes across tissues that are independent of chloroplast dysfunction, suggesting a direct nuclear response to anaesthesia rather than a chloroplast-mediated retrograde effect. These findings highlight chromatin topology as a potential quantitative biomarker of cellular disruption and provide a framework for investigating anterograde chloroplast-nucleus coordination and stress-responsive nuclear organisation in plants.