Journal of Animal Ecology

O_LISeasonal forcing is a dominant factor shaping host-pathogen interactions and disease dynamics across many wildlife systems, including species impacted by environmentally transmitted parasites. How seasonality in parasite dynamics translates to the host when the infection and disease impacts operate at different timescales, however, remains poorly understood. C_LIO_LIWe investigate how seasonality shapes sarcoptic mange in bare-nosed wombats, Vombatus ursinus, a disease caused by the environmentally transmitted parasitic mite Sarcoptes scabiei, causing a protracted clinical time-course in the host. Using an empirically informed state-based deterministic model we explore how wombat population trajectories are influenced by (i) seasonal constraints to mite survival and (ii) in context of host-pathogen encounter rates, as measured by the ratio of burrows to wombats. C_LIO_LIWe demonstrate three long-term outcomes of wombat-mange: host and parasite extinction, endemic disease, and disease-free. We find seasonal environments narrow the range of host-pathogen encounter rates that support S. scabiei persistence relative to stable environments, and prevalence and population sizes vary more in seasonal compared to stable environments except under moderate host-pathogen encounter rates when seasonal effects are less apparent. We also find that a protracted infectious period is essential for host-parasite coexistence in the wombat-mange system. C_LIO_LIOur seasonal model results are consistent with field observations, such that mange prevalence in natural populations increases during seasons of longer off-host mite survival. Application of these findings suggest management efforts could reduce host population impacts through disease management in seasons with longer off-host parasite survival or reduce the environmental reservoir through disease management in seasons with shorter off-host survival. C_LIO_LIWe provide novel, mechanistic explanations for distinctive population trajectories that arise from a seasonally forced wildlife disease, including climate factors that operate independently on parasites, host demography, and disparate timescales over which seasonality affects parasites and hosts. Broadly, linking seasonality to long-term population dynamics can improve the predictability and management of wildlife diseases, but requires an understanding of how local intrinsic factors interact with seasonal pressures over time. C_LI

O_LISeasonal migration in birds involves a substantial spatial redistribution of avian biodiversity each year and drives seasonal changes in community composition. Migrants experience different combinations of species interactions over space and time, generating regular disassembly and reassembly of bird communities throughout their annual cycles. However, the effects of seasonal migration on phylogenetic community structure remain poorly understood. C_LIO_LIWe assess spatiotemporal variation in phylogenetic community structure of North American passerines to test how seasonal migration restructures the evolutionary relatedness and dominant assembly mechanisms in bird communities throughout the annual cycle. Using distributional projections, we calculated metrics describing the phylogenetic dispersion of passerine communities each week of the year. We then tested the relationship between seasonal turnover in community phylogenetic dispersion and seasonal variation in species richness and proportion of migratory species. C_LIO_LISeasonal migration, by changing spatial patterns of avian diversity, simultaneously drives a complex continental redistribution of phylogenetic community structure. We find evidence of taxonomic scale dependency to our results, wherein throughout North America, the seasonal influx of migrant passerines yields communities that are overall more phylogenetically clustered, yet also exhibit greater phylogenetic overdispersion at smaller taxonomic scales. C_LIO_LISeasonal shifts in phylogenetic dispersion, though complex, track changes in diversity, manifesting as fluctuations in phylogenetic dispersion between northern and southern regions as seasonal migrants move between these regions. Our findings reveal a dynamic continental landscape of phylogenetic community structure directed by the movements of seasonal migrants. C_LI

Wildlife diseases cause well-documented and often dramatic reductions in host survival. However, the impact of infectious diseases on host reproduction remains understudied, especially with respect to effects of prior and/or current pathogen exposure on reproductive development. Here we experimentally tested how prior and/or current infection with a common bacterial pathogen, Mycoplasma gallisepticum ( MG), alters reproductive development for female versus male house finches (Haemorhous mexicanus). Finches were inoculated with either MG or sterile media while in wintering condition and subsequently received one of these treatments while in breeding condition. In females, MG exposure had both immediate and carry-over effects on reproduction: controls had higher odds of laying eggs compared to females inoculated with MG in spring only, higher odds than females inoculated in both winter and spring, and higher odds than females given MG in the winter only. Conversely, breeding-condition males inoculated with MG in spring had higher testosterone levels than males receiving only control inoculations, and there were no carryover effects of winter MG inoculation or inoculations during both seasons on testosterone. Sex bias in the reproductive impacts of infectious diseases may have important knock-on effects on the epidemiology and population-regulating effects of pathogens, thereby warranting further study.

Population dynamics and their component vital rates may be driven by weather, climate teleconnections between sea and air (e.g. ENSO), or biotic interactions. These drivers operate directly or indirectly and on different temporal scales. We used a Bayesian structural equation model to characterize effects among weather, climate, and incidental intraguild predation (IGP) on the butterfly Euphydryas gillettii's vital rate of pre-diapause survival, using an 18 year dataset. IGP was a major determinant of pre-diapause survival, along with direct and indirect effects of weather and spring climate teleconnections. The direction of climate effects was reversed when mediated through IGP. Our analysis illustrates the need for sequential hypotheses to capture the cascading effects of abiotic factors via biotic interactions. Using sequential hypotheses addresses the debate on weather -- climate teleconnection roles by disentangling their contributions from one another. Finally, vital rates must be decomposed to component rates in order to detect their drivers.

The black-legged tick (Ixodes scapularis), a key vector of Lyme disease, anaplasmosis, and babesiosis, exhibits regionally distinct patterns of seasonal activity driven by climate. Consequently, the relative timing of larval and nymphal activity varies across geographic locations, influencing pathogen transmission dynamics. Early-emerging nymphs may increase pathogen transmission, whereas early-emerging larvae may reduce transmission. In addition, synchrony between the two life-stages facilitates co-feeding transmission, which contributes to pathogen maintenance and coinfection risk. Temperature is thought to be an important driver of tick phenology, but existing mechanistic models that incorporate temperature fail to accurately capture the timing of larval and nymphal tick activity. To address this limitation, we developed a mechanistic model that includes two additional factors: humidity-dependent questing and low rates of overwinter development. To assess the value of these factors for explaining real-world patterns, we fitted alternative models to tick collection data from the National Ecological Observatory Network. In doing so, we found that explicitly incorporating humidity is necessary to reproduce observed tick phenology, with larval ticks being especially sensitive to relative humidity compared to other life stages. In addition, we found that accounting for humidity had a larger effect at Mid-Atlantic sites than at Northeastern sites, underscoring the importance of region-specific interactions between temperature and humidity in shaping I. scapularis phenology. By more accurately capturing tick seasonality compared to existing mechanistic models, our model illustrates the importance of accounting for factors beyond temperature for investigating how climate variability influences seasonal tick activity and pathogen transmission.

BACKGROUND: Varroa destructor is the major ectoparasite of honey bees and a vector of viral pathogens. Because pathogen transmission and exposure to contact-active acaricides depend on mite host contacts, understanding the factors governing host residence time is important for both disease epidemiology and pest management. We quantified host residence time under varying bee densities and host-type compositions. RESULTS: Mean residence time was 9.48 h across 312 host-residence events. Mites remained on individual hosts for only 2.36 h on Day 1 but approximately 11-14 h from Day 2 onward. A generalized linear mixed model showed a strong positive effect of day on residence time ({beta} = 0.341, SE = 0.044, P < 0.001), corresponding to an approximately 41% increase in residence time per day. Excluding Day 1 eliminated this effect (P = 0.16), indicating that the temporal pattern was driven primarily by the initial exposure period. Reconstructing Day 1 observations to an 8-hour schedule confirmed that this pattern was not an artifact of observation frequency. Neither host type nor bee density affected residence time, and mite occupancy of nurse bees matched host availability. CONCLUSION: Host residence time was governed primarily by initial exposure rather than host identity or moderate crowding. The results identify a previously undescribed exploratory phase immediately after mites enter a novel adult-bee population. Because shorter residence times imply more frequent host switching, these findings improve our understanding of pathogen transmission dynamics and may help explain variation in the performance of contact-based Varroa control strategies.

Animals face a fundamental trade-off between food-related competition and predation risk in how they allocate time and behavior. Nocturnal mammals offer a particularly tractable system for testing this trade-off because moonlight creates a natural, quantifiable gradient in both predation risk and the visibility needed for safe movement. We used minute-by-minute focal observations of nine kinkajous (Potos flavus; 4 female, 5 male) in Panama to test how fruit abundance and moonlight predicted nocturnal activity budgets (percent time traveling, feeding, resting) and nightly travel distance. Beta-family generalized linear mixed models and a linear mixed model of log travel distance showed that fruit abundance was positively associated with percent time traveling and with nightly travel distance, and negatively associated with percent time feeding: kinkajous traveled more and fed less per hour when fruit was abundant, consistent with movement between many nearby productive trees rather than prolonged feeding at a few. Males traveled less as moonlight increased, while females traveled more. Rainfall had no independent effect. We interpret the sex-reversed moonlight response as evidence that moonlight elevates predation risk for males while facilitating movement for the more food-limited females of this frugivorous carnivore.

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.

Species exhibit variation in their circadian activity rhythms, including being active during the day (diurnal), the night (nocturnal), or the twilight periods (crepuscular). While the influence of environmental factors such as light on entraining and controlling activity patterns is well known, it is unclear how social and abiotic factors affect circadian behaviors. The daily activity patterns of Lake Tanganyikan cichlid fish are diverse, and may be associated with species diversification. Intriguingly, some shell-dwelling cichlid species, which anecdotal observation suggests are diurnal, displayed strong nocturnal activity when assayed in a "common garden" lab setup. Here, by integrating field and lab-based studies, we provide three lines of evidence that social and environmental cues mask underlying circadian rhythms in shell-dwelling cichlids. First, we demonstrate that shell-dwelling cichlids are diurnal in their natural habitat, but convert to nocturnal activity when assayed alone in a common garden. Second, we identify that in the presence of a shell and conspecifics the highly social N. multifasciatus becomes diurnal. In contrast, the circadian activity pattern of a closely related, but sub-social species, N. brevis, is masked only by a shell, and unaffected by the presence of conspecifics. Third, we demonstrate that the masking effect of shells and conspecifics is circadian and continues in the absence of light. Fourth, we identify that the response to these cues is influenced by sex, with greater effects in female fish, and by pedigree, with stronger effects in individuals bred and raised in captivity compared to those captured in the wild. Together, these experiments reveal new relationships between circadian rhythms and sociality in these fishes, offering broader insights into the ecological and evolutionary drivers of these behaviours.

Animal personality is the expression of consistent among-individual variation in a behavioural trait across time and context. The application of this theory to behavioural research provides a valuable framework to investigate the among- and within-individual variation in behaviour. The animal personality theory is particularly relevant to understand and diagnostic fish welfare. It can be integrated within the nature-based welfare framework, which emphasizes the expression of species-specific behaviours and the maintenance of consistent behavioural patterns over time. Because behavioural trait such as boldness may be closely linked to other functional phenotypes, such associations reflect the broader concept of animal personality, whereby a behavioural trait can covary with another phenotypic trait to support an adaptive responses to environmental conditions. Although these relationships are both species and context dependent, they are consistently shaped by environmental conditions and environmental complexity tend to promote species specific behaviours and reduce maladaptive traits. Here we examined how structural environmental complexity shapes personality in Arctic charr and their covarying functional phenotypes, specifically growth rate and brain size. We propose that environmental complexity promotes alternative behavioural and functional phenotypes through multivariate phenotypic plasticity. We found that environmental complexity did not influence mean boldness between both treatments, but repeatability of boldness in the complex environment was remarkably consistent over a longer-term period, while estimates collapse after seven days in the plain treatment. Our findings are a clear evidence that environmental complexity foster stable behavioural trait expression and that a plain environment may suppress personality. Our results provide compelling evidence that behavioural structure and dynamics are embedded within patterns of behavioural variance. Although we found no support for behavioural covariation or associations with growth rate and brain size, we suggest that the animal personality framework may offer a valuable approach for diagnosing fish welfare issues through the partitioning of behavioural variance.

Animals often attempt to resolve the trade-off between foraging and predation by regulating their activity timings and patterns. Driven by individual energetic requirements and the local environment, onset of activity in a species varies across space and time. These differences are particularly enhanced on a latitudinal gradient, influenced by varying lengths of daylight, temperature and seasonality. For a nocturnal mammal like the bat, such patterns translate to shorter activity windows at higher latitudes, both on a nightly and a seasonal basis. This constructs the timing of activity onset as a crucial variable for a successful night of foraging. While roost exit timings and influence of local conditions on bat activity have been extensively studied across species inhabiting a variety of locations around the world, our understanding of bat emergence behaviour on a global scale remains limited. To investigate emergence patterns in bats across a latitudinal gradient, we conducted a meta-analysis spanning 91 species from across 13 Chiropteran families. We evaluated how timing and luminosity (i.e., sun altitude) at exit varied across latitudes and species. Results revealed that bats across the globe tended to emerge under conserved thresholds of brightness, a pattern that was facilitated by a temporal delay in roost exits at higher latitudes. By maintaining emergence within the confines of nautical twilight (sun altitude between 0{degrees} to -12{degrees}), bats across the phylogeny thus seemed to balance the dilemma of predation versus foraging. This pattern was mirrored across the two broad dietary types (frugivores and insectivores) as well as different social structures (maternal v. non-maternal colonies). Furthermore, our models indicated that while local conditions dictate final exit decisions, shared ancestry was potentially influencing the extent of plasticity seen in emergence patterns. Taken together, these results highlight how broad-scale latitudinal gradients of light can influence the foraging strategies in a globally distributed nocturnal mammal.

1. Migration is a widespread phenomenon across taxa, yet the ecological mechanisms underlying its evolution and maintenance, particularly whether migratory behaviors are primarily driven by access to spatially restricted breeding sites or by seasonal tracking of trophic resources, remain poorly documented outside birds and large mammals. Despite increasing evidence that reptiles perform seasonal migrations, the ecological mechanisms underlying these movements have rarely been formally tested. 2. The critically endangered Galapagos pink land iguana (Conolophus marthae), endemic to Wolf Volcano, Isabela Island, exhibits partial migration along a steep altitudinal gradient, providing an opportunity to disentangle the relative roles of breeding-site availability, trophic resource dynamics, and thermoregulatory conditions as drivers of migration. 3. We used GPS tracking data from 22 individuals (7 males, 15 females) monitored between 2019 and 2023, combined with high-resolution spatio-temporal models of vegetation productivity and air temperature across the species' altitudinal range, to characterize population-level movement patterns and evaluate competing hypotheses explaining the evolution of this migratory behavior. 4. Movement models revealed a clear pattern of partial migration: 16 out of 22 tracked individuals performed seasonal altitudinal movements between a restricted high-elevation mating area and a larger dispersal area at lower elevation, with males reaching the mating area approximately 48 days earlier than females. The dispersal area remained consistently more productive than the mating area throughout the year, rejecting the prediction that individuals should track the shifting trophic resource peaks. Instead, the mating season coincided with the local productivity peak within the mating area, whereas temperature differences between areas were small (ca. 2{degrees}C) and did not explain migration timing. 5. These results support a site-dependent hypothesis of partial migration over a resource-tracking hypothesis, indicating that access to spatially restricted breeding sites is the primary driver of migration in this species, with local trophic resource dynamics fine-tuning reproductive timing. Providing empirical evidence for the ecological mechanisms underlying migration in a large terrestrial reptile, our results extend site-dependent theories of migration beyond birds and mammals and identify breeding-site availability as a key ecological driver of migratory behaviors across taxa.

Gut microbiome responses to anthropogenic disturbance vary across wildlife species, even within similarly disturbed landscapes. What drives this variation is unclear: whether it reflects anthropogenic exposure itself or broader ecological differences among hosts. We tested this using three macaque species with contrasting ecology, Bonnet, Rhesus, and Lion-tailed macaques, sampled across 12 sites in southern India spanning contrasting anthropogenic exposure, using 16S rRNA gene sequencing (n = 127) and shotgun metagenomics on a subset of samples. The two synurbanized species exhibited a similar magnitude of microbiome restructuring but differed in the taxa underlying these changes; no differentially abundant amplicon sequence variants were shared across all three species, indicating that shared anthropogenic exposure did not produce uniform microbial responses across hosts. The specialist Lion-tailed macaque showed a more extensive response, characterized by reduced diversity and phylogenetically structured compositional change. The Bonnet macaque showed greater microbial similarity with the Rhesus macaque than with the Lion-tailed macaque during sympatric co-occurrence. Despite taxonomic divergence, functional pathway architecture was broadly conserved across species and habitats, with selective shifts in pathways including vitamin B6 biosynthesis and fermentation. Together, these findings show that microbiome responses to anthropogenic environments are jointly shaped by ecological context and host ecology, with host differences in diet, habitat use, and ecological history influencing the magnitude and nature of microbial restructuring. These findings show that taxonomic diversity and functional potential respond as partially decoupled axes under anthropogenic pressure, with implications for assessing microbiome resilience across ecologically heterogeneous wildlife.

Many Sockeye salmon (Oncorhynchus nerka) populations have declined over recent decades, and climate change is likely to exacerbate these declines through direct and indirect ecological effects. The response to the associated environmental changes is likely to vary among life stages, populations, and regions. Quantitative estimates of climate change driven impacts that account for this variability could fill a critical gap and provide forward-looking insights into how sockeye are expected to respond to future climate-driven change across their lifecycle. To address this need we developed a hierarchical population dynamics model parameterized with juvenile, adult return and spawner abundance data from 13 sockeye salmon populations from Washington State to northern British Columbia. We used a formal causal inference framework that paired salmon abundance data with a suite of environmental covariates hypothesized to represent ecological conditions across the lifecycle. We used the model to estimate population-specific responses to each environmental driver, then combined parameter estimates with projections from down-scaled climate change models to estimate productivity responses to anticipated environmental change. We found that historical sockeye productivity was strongly associated with environmental covariates, which explained more interannual variability in return abundance than spawner abundance in most populations. However, the life stages and specific environmental covariates with the largest impacts differed among populations and regions, often displaying a latitudinal gradient. Increases in coastal ocean temperatures and mixed layer depth generally had negative effects though they varied among regions. Increased freshwater summer rearing and return migration temperatures had weaker but consistently negative effects. Under future climate conditions, projected changes in these environmental covariates are expected to result in substantial declines in productivity across most populations. Sockeye salmon display varying degrees of sensitivity to climate change across life stages, populations, and regions. Effective future management will require explicitly accounting for these life stage and population-specific responses.

1. Large-scale community-composition datasets, especially from microbiome studies, increasingly provide opportunities to identify major community compositional types (e.g., enterotypes in human microbiomes) and potential transitions depending on environmental factors. Energy landscape analysis based on maximum entropy models has emerged as a promising framework for characterizing such multi-stability in ecological communities. However, its application to diverse, high-dimensional compositional datasets remains limited by computational inefficiency, insufficient evaluation of predictability, and lack of systematic assessment of uncertainty. 2. Here, we present a computationally tractable inference framework for energy landscape analysis of multispecies communities, implemented in the R package ELAplus. We introduce a framework combining cross-validation-based selection of optimization settings, enabling accurate and computationally efficient model fitting across a wide range of simulated community datasets. In addition, we incorporate a bootstrap-based approach to quantify the reliability of inferred stable states, providing a systematic measure of uncertainty in landscape structures. 3. Simulation analyses demonstrate improved predictive performance and robustness compared to existing implementations. Applications to empirical datasets further illustrate how the framework can reveal stable states, basins of attraction, and potential tipping points under varying environmental conditions. The package also provides visualization tools, including disconnectivity graphs and energy surface plots, to facilitate intuitive interpretation of complex ecological landscapes. 4. Our framework enables robust and computationally efficient inference of ecological stability from compositional and environmental data, expanding the applicability of energy landscape approaches in diverse natural communities.

When individual preferences for collective outcomes diverge, cohesive animal groups often coalesce on the majority opinion. However, majority-based decision rules may be counterbalanced by other factors, particularly in heterogeneous groups with differentiated social relationships, and these factors could produce inequality in social influence. We used multi-sensor tracking collars to collect detailed and simultaneous data on the movements and vocalizations of almost all members of three wild white-nosed coati (Nasua narica) groups, and analyzed 2,401 individual decisions between conflicting travel directions. Decision-making was shared: individuals favored directions that had majority support, and we found evidence that they used acoustic signals and movement cues to infer majority support. Individuals were also more likely to choose directions favored by closer kin and by groupmates in more frontward spatial positions. Although decisions were shared, influence was not equally distributed across individuals. During directional conflicts, individuals who were more likely to form majorities or who were advantaged by frontward spatial positions had higher influence over travel direction. By explicitly linking decisions by individual followers to emergent patterns of influence among potential leaders, our results suggest that influence is a complex product of higher-order interactions that are likely dependent on group demography and socio-spatial structure.

Mixed-species groups (MSGs) pose a particular challenge for our understanding of sociality in animals. Though MSGs are widespread social assemblages that form to enhance foraging success and reduce predation risk of participants, the role of traits in mediating grouping has received less attention. In particular, the role of body colour has not been tested quantitatively, despite the fact that visual similarity can reduce individual predation risk. Here, we examine whether plumage colour structures mixed-species bird flocks (MSFs) at a global scale. Using data spanning four continents, we developed a new metric that quantifies colour similarity among flock participants and compared observed flocks to null assemblages constructed from all flocking species at each site. We further examined whether MSF participants represented a colour subset of the available colours in the regional species pool. We found striking evidence that birds in MSFs were more similar in colour than expected by chance across all sites, indicating that plumage colour is a non-random structuring trait that shapes assembly of flocks globally. The strength and prevalence of colour structuring varied across geographies, but not flock size. Within communities, MSF participants differed systematically in colour composition from the regional species pool, occupying a restricted region of colour space dominated by yellow and brown plumage. Thus, plumage colour affects MSFs influencing both overall flock participation as well as species co-occurrence within flocks. Our findings illustrate the importance of visual traits in structuring interspecific social systems, by highlighting that birds of a feather do indeed flock together.

Retrospective ecological niche modeling (rENM) combines historical species occurrence records with historical environmental data to reconstruct the spatio-temporal dynamics of species-environment relationships under changing conditions. Despite growing recognition that those relationships can be nonstationary, time-series approaches to ecological niche modeling remain uncommon, and the tools to support them at scale are limited. Here, we describe the rENM Framework, an experimental, open-source suite of R packages that automates a complete rENM workflow spanning data preparation, ensemble time-series construction, trend analysis, AI interpretation, and report generation. The framework integrates eBird occurrence records with environmental variables derived from NASAs MERRA-2 reanalysis across a 45-year study period (1980-2024) and executes a complete analysis for any species with eBird data through a single function call. By treating climatic suitability as a dynamic ecological response surface rather than a static baseline, the framework produces the following analytical products that complement conventional ecological niche modeling approaches: suitability time series, long-term trend and acceleration maps, centroid displacement estimates, bioclimatic velocity metrics, variable contribution trajectories, and hotspot analyses identifying areas of accelerating suitability decline. We illustrate the frameworks outputs with a representative run for Cassins Sparrow (Peucaea cassinii), a grassland species of conservation concern in the arid southwestern United States and the focal species throughout our development work. The frameworks automated, unsupervised pipeline makes systematic application across large numbers of species tractable, with direct implications for conservation assessments, such as State Wildlife Action Plans, where species-specific analytical capacity is often limited by available resources. The rENM Framework is openly available on GitHub and archived on Zenodo.

Understanding how closely related species coexist in highly seasonal and unpredictable environments is central to studies of ecological differentiation and niche partitioning. We investigated the feeding ecology of sympatric populations of Microcebus murinus and M. griseorufus within a contact zone in Andohahela National Park, southeastern Madagascar, across dry and wet seasons. Using a combination of direct behavioral observations (1,611 feeding records), fecal sample analyses (n = 56), and vegetation phenology surveys, we quantified dietary composition, seasonal shifts in resource use, and habitat-related variation. Seasonal changes in diet were pronounced, with dry-season feeding dominated by exudates and wet-season diets incorporating greater proportions of fruit and flowers, closely tracking phenological patterns at both sites. Diets of both species were dominated by plant resources, but consistent interspecific differences in dietary strategy were evident. Although both species consumed comparable proportions of insect prey, M. murinus showed pronounced wet-season increases in the use of high-sugar, carbohydrate-rich floral resources (15.9%) and hemipteran-associated honeydew (30.6%). In contrast, M. griseorufus relied more consistently on predictable exudates throughout the year. Fecal analyses supported observational data but revealed differences in the detectability of dietary components, with increased representation of invertebrates in the wet season and seeds in the dry season. These results indicate substantial dietary overlap but consistent differences in resource use, suggesting that coexistence is facilitated by fine-scale trophic differentiation within a broadly shared omnivorous niche. Such subtle but persistent differences in feeding strategy likely reduce competitive overlap and enable continued sympatry in a climatically variable and resource-limited system.

1. Natal dispersal is a key process in population ecology because it links local demographic processes to broader-scale population dynamics by redistributing individuals. When using capture-recapture data, multistate capture-recapture models using discrete spatial units as states are the gold standard for estimating natal dispersal among spatial units while accounting for spatial variation in survival, recruitment and imperfect detection. However, because their computational cost increases rapidly with the number of spatial units, applications have been limited to a small number of units. Therefore, in practice, these models cannot provide spatially detailed inference on natal dispersal across large landscapes. 2. We develop a computationally efficient Bayesian capture-recapture model, called the efficient natal dispersal (END) model, to estimate natal dispersal among discrete spatial units jointly with spatial variation in demographic parameters and detection probabilities. The END model relies on two key structural features: juveniles and breeders are separated into two arrays, and resightings outside the natal spatial unit are aggregated over time for individuals released as juveniles. 3. Using simulations, we show that the END model is considerably (up to 30 times) more computationally efficient than a conventional multistate model, while maintaining comparable parameter accuracy. We then apply the END model to white stork (Ciconia ciconia) capture-recapture data from Germany across 101 hexagonal spatial units, a spatial resolution at which a conventional multistate model is computationally infeasible. We estimate natal dispersal among units jointly with spatial variation in survival and recruitment. This allows us to identify areas of lower or higher survival, earlier or delayed recruitment, and dispersal probabilities among all units. By combining estimated dispersal probabilities with existing data on the number of juveniles born in each spatial unit, we estimate natal dispersal in terms of numbers of individuals and identify units with positive or negative net migration, sources and sinks. 4. Overall, our approach moves capture-recapture analyses from estimating natal dispersal among a few spatial units to inferring dispersal networks and assessing their demographic consequences across large domains. Our approach is applicable to many spatially structured capture-recapture datasets, opening new opportunities for studying spatial population dynamics.