Ecological Applications

Agricultural intensification is a major cause of population declines in farmland birds and insects worldwide. While these declines are expected to disrupt trophic interactions through density-dependent cascading effects, examples outside of crop pest control or involving more than two trophic levels remain poorly documented. Here we quantify such cascading effects across three trophic levels involving a declining aerial insectivore, the Tree Swallow (Tachycineta bicolor), which breeding success decreases with agricultural intensity, Protocalliphora bird blowflies (Diptera: Calliphoridae) that parasitize its nestlings, and Nasonia parasitoid jewel wasps (Hymenoptera: Pteromalidae) that feed upon blowfly pupae within swallow nests. Agriculture intensity may affect each of these actors either directly via, for instance, toxicological effects from pesticide use, or indirectly through density-dependent trophic interactions, which can exacerbate or mitigate one another. Using Bayesian models within a causal inference framework, we quantified how nestling host density, meteorological conditions, and agricultural landscape context affect Nasonia parasitoid infestation of Protocalliphora pupae, and estimated Protocalliphora emergence success. Analyses were based on 3,340 Protocalliphora puparia collected from 248 Tree Swallow nests over a 16-year period (2004-2019) across a 10,200-km2 agricultural intensity gradient in Southern Quebec, Canada. Model predictions indicated that Protocalliphora emergence probability increased steeply with nestling host availability (i.e., nestling-days). Whereas Nasonia parasitoid infestation occurrence at the nest level increased with Protocalliphora host availability, the proportion of infested Protocalliphora pupae within nest decreased and led to a dilution effect at the individual level. Although Protocalliphora abundance within nests decreased with agricultural intensity, their emergence probability peaked in agrointensive landscapes. This increase was associated with reduced Nasonia infestation rates, suggesting that agricultural intensity indirectly mitigated parasitoid pressure on Protocalliphora host populations. Our results highlight how agricultural intensification can shape multitrophic interactions and life-history traits (emergence success and infestation rates) by simultaneously reducing host availability and weakening top-down control by parasitoids.

1. Common dolphins (Delphinus delphis) are the most abundant cetaceans off mainland Portugal and a species of conservation and bycatch concern, so reliable abundance estimates are a management priority. Yet no single survey provides adequate spatiotemporal coverage: dedicated programmes offer sparse snapshots, while opportunistic programmes are spatially constrained by their routes. Integrating them is methodologically demanding, and the existing methods that do so in a single model estimate the density of animal groups, not of the individual animals that management often requires. 2. We develop a spatiotemporal marked log-Gaussian Cox process that integrates four structurally distinct surveys through a shared intensity surface, comprising environmental covariates, a latent spatial field, and survey-specific detection functions. Group size enters as a zero-truncated negative binomial mark with its own spatiotemporal field. We apply it to a dedicated aerial survey and three opportunistic ship-based programmes off mainland Portugal, comprising 162,514 km of on-effort transects and 1,756 sightings of 17,000 animals. We fit the model in a Bayesian framework with integrated nested Laplace approximations, yielding seasonally resolved group and animal density surfaces across the Portuguese Exclusive Economic Zone, and abundance estimates with fully propagated uncertainty. 3. Predicted animal density concentrated over the shelf and upper slope in every season, peaking northwest, and increased in shallower, cooler, more productive waters and over steeper seabed. Abundance nearly doubled from summer (77,000 [95% credible interval: 60,000, 98,000]) to winter (146,000 [99,000, 208,000]). Seasons shared 56% of the spatial field's variance, so effort from any programme in any season informed all others, and the seasonal contrast remained estimable despite uneven coverage. 4. Synthesis and applications. Our framework allows managers to combine dedicated surveys with existing platforms of opportunity to estimate animal density by season. Because group size is modelled explicitly, densities are estimated in animals rather than groups, as required for bycatch risk assessment and marine spatial planning. Because each survey enters through its own observation model, the approach accommodates programmes that differ in platform and protocol and transfers to any species or region where several surveys each cover part of a population.

Aim: To test whether individual movement mechanisms inferred from animal tracking data can be scaled up to explain landscape-scale patterns of population density and improve predictions of population redistribution under future environmental change. Location: Texas Gulf Coast, USA Time Period: 2009-2018 Major Taxa Studied: Whooping Crane (Grus americana) Methods: We parameterized individual-level step-selection functions using 14,898 GPS locations from 22 Whooping Cranes and propagated the resulting movement and habitat-selection mechanisms across the landscape to derive steady-state distributions of space use. We compared these movement-informed predictions with correlative species distribution models fitted to the same data. Predictions were evaluated using withheld tracking observations and fully independent population-level aerial-survey data. We then projected both approaches under sea-level-rise scenarios to assess how future habitat loss and fragmentation alter crane space use. Results: Movement mechanisms derived from individual-level tracking data captured the mechanistic dependence of population density on habitat quality and spatial configuration. When projected across the landscape, these mechanisms reproduced fully independently observed density patterns and outperformed conventional species distribution models. Because predictions arose from movement mechanisms rather than occurrence-environment correlations, movement-informed models also captured the effects of habitat reconfiguration under sea-level rise. They projected pronounced population redistribution and an expansion of core space-use areas of up to 80% which conventional models missed. Main Conclusions: Individual movement mechanisms derived from biologging data can scale up to explain current population structure and predict future redistribution under environmental change. By mechanistically accounting for how habitat configuration constrains accessibility, movement-informed models reveal severe impacts of fragmentation that are missed by conventional distribution models. Rapidly expanding biologging datasets therefore offer a scalable basis for connecting individual behavior to macroecological patterns and improving biodiversity forecasts in changing landscapes.

Recent work on the design of spatial capture-recapture (SCR) studies has largely focused on settings with a single set of movement and detection parameters. In many applied contexts, however, populations are naturally stratified-for example, when different sexes exhibit markedly different movement scales and encounter processes, or when more than one focal species is monitored. Designs that perform well for one group may be inefficient or suboptimal for others, despite the substantial logistical effort typically required to implement an SCR survey. We describe several potential SCR design strategies for surveying multiple groups, and compare these using simulation. Designs considered include regular and optimised grids, clustered and lacework designs, and designs generated using genetic algorithms, including new approaches that optimise information from both groups and a recently published two-stage design. Using proximity detectors such as camera traps, we evaluate design performance in terms of precision, bias, and coverage, and examine how performance changes with the number of available resources. Our results show that multi-group SCR surveys can perform well even when focal groups differ greatly in movement scale and encounter rate, provided that some simple guidelines are followed. Systematic layouts accommodating more than one characteristic spacing e.g. cluster designs, performed consistently well and are a reliable default option. Regular grid designs with a single spacing between detectors are feasible when differences between groups are moderate but performed poorly as differences increased. Establishing when these designs become problematic adds unnecessary risk to the design process. Algorithmic designs did not outperform systematic designs even in highly-skewed scenarios expected to favour them. In practice, when there is more than one focal group we recommend identifying the smallest and largest plausible movement scales and rejecting potentially pathological designs, primarily those that cannot generate recaptures at the smaller scale or cover a substantial area at the larger scale.

Ecological responses to environmental stressors are increasingly shaped by interactions among anthropogenic and climatic drivers, yet the influence of prior exposure history on subsequent stress responses remains poorly integrated into multiple stressor ecology. Using the blue mussel (Mytilus edulis) as a model system, we experimentally tested whether prior exposure to environmental nanoplastics modifies responses to subsequent stressors, including copper contamination, nutrient enrichment, and salinity fluctuations, individually and in combination. Nanoplastic pre-exposure reduced survival across subsequent treatments and altered stressor interaction outcomes at the community level, shifting responses toward synergistic effects that amplified metabolic costs. These results demonstrate that exposure history can modify both the magnitude and direction of multi-stressor effects, with consequences extending beyond individual performance to ecosystem functioning. By incorporating temporal exposure dynamics into multiple stressor research, our study highlights how ecological responses to global change depend not only on the identity and intensity of stressors, but also on prior environmental conditions shaping subsequent organismal and ecosystem health status and responses.

Global biodiversity recovery demands restoration at landscape scales, where ecological outcomes are shaped not only by habitat amount but also spatial arrangement. Alternative landscape restoration strategies can increase habitat amount, improve quality, and alter configuration in fundamentally different ways and may therefore vary in their efficiency. Here, we conceptualise five landscape restoration strategies and use a spatially explicit metapopulation framework to compare their ability to increase predicted species persistence across heterogeneous landscapes and trait space defined by dispersal ability and specialisation. We find that restoration outcomes are strongly trait-dependent, with restoration of existing degraded habitats yielding the highest benefits - particularly for specialists. Improvement of the landscape matrix to create low-quality habitat primarily benefits generalists, while strategies creating new habitat patches or enlarging patches provide more consistent but modest gains. These results reveal fundamental trade-offs among restoration strategies and highlight the utility of trait-explicit approaches to inform their implementation and evaluation.

1. Soil invertebrate biomass is closely linked to ecosystem processes, yet its routine quantification remains constrained by the effort required to weigh large numbers of small individuals. Length-mass relationships provide an indirect alternative, but body length can be difficult to standardise and extract automatically from images of curved, coiled or contracted organisms. Projected body area may provide a more tractable image-derived predictor, but its performance across diverse soil-faunal taxa and at the community scale remains insufficiently evaluated. 2. Here, we developed a framework using projected body area and contour length to estimate fresh and dry mass from measurements of 1,792 soil invertebrates representing 15 higher-level taxa. We fitted taxon-specific models for six well-represented groups and general models across taxa, and evaluated predictive performance using leave-one-out cross-validation. We then assessed cross-dataset transferability by comparing our data with those of Lemoine et al. (2026) and pooled the two datasets to derive combined models. Finally, we tested whether individual predictions could be scaled to independently measured community biomass. 3. Taxon-specific models generally reduced prediction error relative to general models, with mean absolute percentage error (MAPE) values of 6.9-37.3% for fresh mass and 7.6-30.2% for dry mass. General models retained MAPEs of 27.2% and 22.4%, respectively. Comparisons of our dataset with that of Lemoine et al. (2026) showed no detectable differences in six of eight taxon-by-mass slopes. Although intercepts frequently differed, no overall dataset effect was detected after accounting for taxa. Pooling both datasets broadened model development, while taxon-specific models generally retained lower error than the combined general model. Finally, community-level predictions tracked measured biomass across all model sets (R2 = 0.87-0.99), but absolute error varied among models and faunal groups (MAPE = 9.6-52.5%). 4. Body area and contour length extracted from images therefore provide a practical basis for scaling soil invertebrate biomass estimation from individuals to communities. Integration with automated imaging and segmentation tools such as flatbug, BIODISCOVER and CollembolAI could extend soil invertebrate monitoring at larger scales beyond abundance and taxonomic composition to biomass, while providing scalable inputs for analyses of food webs and general ecosystem ecology.

1. Species monitoring programmes regularly encounter missing data, which complicates tasks such as estimating population size or detecting temporal trends. Selecting an imputation method suited to the properties of the data is therefore an important practical challenge, particularly for species exhibiting overdispersion and zero-inflation. 2. We compare seventeen imputation methods, comprising thirteen Poisson-based statistical models (accounting for overdispersion and zero-inflation, with fixed, random and multivariate structures) and four contrast-based approaches (LORI, MICE, missForest, correspondence analysis). Using four complete monitoring datasets of waterbird species surveyed across France and Italy over 21 years, illustrating a variety of abundance distributions, we introduced missing observations under a realistic Missing At Random mechanism, at rates from 5% to 70%. We evaluated all methods on computational burden, prediction accuracy for positive and null counts, quantification of uncertainty, and accuracy of population-size estimates. 3. No single method dominates across all criteria. Statistical models and contrast-based approaches yield similar point predictions, but only statistical models provide a genuine measure of uncertainty. Models that jointly account for overdispersion and zero-inflation perform best at predicting zero counts and achieving reliable prediction intervals, and the most suitable method ultimately depends on the abundance distribution of the target species. 4. These results provide practical guidance for ecologists selecting an imputation strategy for incomplete count data, highlighting the trade-offs between predictive accuracy, computational cost, and the ability to propagate uncertainty through subsequent ecological analyses such as population-trend estimation.

Climate change poses a major threat to marine mammal populations, many of which remain vulnerable after years of overexploitation during the 17th to 20th centuries. Extreme climate events have grown in both frequency and severity in recent decades, and this trend is projected to accelerate under continued greenhouse gas emissions. Here, we assess how this intensification affects a top marine predator at the epicentre of extreme El Nino events - the Peruvian population of Otaria byronia (South American sea lion). We first apply a Bayesian population model that best predicts observed population dynamics to reconstruct female O. byronia population trends, estimate vital rates, and evaluate the effects of environmental drivers on survival and reproduction. We then use the same model to project extirpation risk under multiple future climate scenarios reflecting anticipated increases in both the intensity and frequency of extreme El Nino events. Our reconstruction reveals that the Peruvian O. byronia population has shown considerable resilience to episodic El Nino events over the past quarter-century, likely sustained by high female survival during normal and favourable years. However, under a scenario of moderate increases in El Nino frequency and intensity, the probability of extirpation over the next 50 years is 83.4% higher than under current conditions. As disturbance regimes intensify globally, we suggest that resilience-oriented management frameworks, grounded in species-specific demographic data and environmental context, as demonstrated here, will be essential for safeguarding marine mammal populations against an increasingly volatile climate.

Morphological variation in insects can indicate responses to habitat change and land use intensification, with potential consequences for trophic interactions. In insect host-parasitoid systems, host body is often a key determinant of offspring development and emergence success, as well as parasitoid host-selection behavior. Yet, most studies in agricultural landscapes have focused on size variation in crop-associated insects (i.e.: pests, pollinators and enemies), leaving those relying on non-crop resources largely unexplored. Here, we investigated how agroenvironmental contexts and trophic resource availability influence puparial size in Protocalliphora sialia (Diptera: Calliphoridae), an obligate hematophagous ectoparasite of Tree Swallow (Tachycineta bicolor) nestlings. We further tested whether puparial size affects emergence probability and risk of parasitoidism by Nasonia spp. (Hymenoptera: Pteromalidae) jewel wasps. Using 1,513 P. sialia puparia from 88 nests within a nest-box monitoring system spanning a 10,200-km^2 east-west intensification gradient in southern Quebec, Canada, we evaluated how agrointensive contexts, avian host availability, and ectoparasite densities influence puparial size, parasitoidism risk, and emergence success. The agricultural context appears to shape puparial size through survival biases and/or altered growth rates. In agroextensive contexts (i.e.: pastures, forages with high tree cover), where Protocalliphora are more numerous, P. sialia puparia were smaller and exhibited greater size variation. Conversely, in agrointensive environments (maize and soybeans monocultures with higher doses of pesticides), where Protocalliphora are fewer, small individuals were underrepresented, suggesting a selective mortality in P. sialia population. However, puparial size explained less than 10% of the variation in emergence or parasitism, likely reflecting consistently high parasitic pressure from Nasonia wasps, which infested 50-90% of puparia, depending on site and year. Our findings highlight the importance of selective mortality in structuring trait distributions and modulating multi-trophic interactions in human-modified landscapes.

Forecasting infectious disease dynamics is important for ecological management and emerging disease preparedness, yet many systems lack the long-term datasets required to develop reliable predictions. Spatial replication may provide an alternative by allowing information to be shared among populations, but the extent to which this improves forecasting remains unclear. Here, I used epidemic and temperature data from 20 replicated semi-natural Daphnia-parasite pond populations monitored across four seasons (80 epidemics) to test whether information from multiple populations improves forecasts and whether environmental similarity identifies informative populations. I forecasted disease prevalence, infected host density, and healthy host density using a benchmark model, autoregressive integrated moving average (ARIMA), and time-series regression models. Models were trained using focal-population data alone, mean dynamics across other populations, or temperature-weighted mean dynamics from environmentally similar populations. Epidemics showed strong seasonal structure, with prevalence and infected host density generally peaking during the warmest period of the season. However, no forecasting approach consistently outperformed others across all variables. Temperature improved forecasts of prevalence and infected host density but not healthy host density. Multi-population training improved forecasts in some cases, particularly for ARIMA models, whereas temperature-weighted averaging provided no additional benefit over simple averaging. Regression models consistently produced the most accurate forecasts of healthy host density. These results show that borrowing information among populations can improve forecasts under specific conditions but is not universally beneficial, highlighting the importance of matching forecasting approaches and data sources to the ecological processes being predicted.

Management of marine protected areas (MPAs) require long-term monitoring and evaluation that is often limited by the cost and effort of conventional visual based surveys. We evaluated a community science-based eDNA approach to MPA monitoring over two years in the Point Dume State Marine Reserve, the Point Dume State Marine Conservation Area, and two paired unprotected reference sites. Across the sampling period, we detected 119 species of fish and marine mammals, including 19 of the 22 regional management-priority species for Southern CA MPAs. Protected and unprotected comparison sites were broadly similar in overall assemblage with 93 species shared across all sites. Multivariate analyses revealed site-level differences, although season and year explained more variation than protection status. Species presence also shifted during a La-Nina transition, highlighting the importance of long-term monitoring under different climatological contexts. Community scientists greatly expanded the temporal and spatial scope of eDNA sampling and generated high-quality data. Subsampling analysis showed that quarterly sampling, with three sample replicates and sequencing depths between 700k-990k, recovered 95% of observed biodiversity of the full time series. These results demonstrate that a community science-based eDNA program could provide a standardized, scalable, low-cost, and management-relevant approach for long-term monitoring across California's MPA network.

(1) Kelp forests support ecologically, commercially, and culturally important species, yet their benthic communities remain difficult to monitor consistently across space and time. Scientific SCUBA surveys provide valuable observations but can be constrained by safety, bottom time, depth, and the spatial extent that divers can efficiently cover, motivating complementary approaches for collecting standardized benthic imagery. (2) We developed and field-tested a standardized, open-source framework for benthic visual-imaging surveys using a small, modular remotely operated vehicle (ROV). Across four cost-scalable hardware configurations, we integrated navigation sensors, custom BlueOS Extensions, and our surftrak contribution to ArduSub, which enables fixed-altitude flight above the seafloor, and developed two open-source desktop applications that streamline field operations (rov_flight_ops) and imagery processing (rov_imagery_processing). We also evaluated power supplies, benthic lighting, camera settings, field protocols, and telemetry-processing workflows over 303 transects conducted on 64 survey days from 2022 to 2026. (3) The ROV operated across soft-sediment and rocky habitats, currents of 0-3 kt, and underwater visibility of 0-10 m. surftrak held the ROV within 0.2 m of its target altitude for 96% of 21 h of survey transects, producing an approximately 1 m^2 standardized image footprint. Sufficient illumination and optimized camera settings yielded high-resolution imagery in visibility below 2 m, while topside power increased endurance and operational flexibility. Combining Doppler velocity log and underwater acoustic positioning data through the vehicle's extended Kalman filter improved navigation and post hoc transect reconstruction. During 2026 surveys, rov_flight_ops and rov_imagery_processing automated flight logging, log retrieval, fault diagnosis, and the sorting, development, and telemetry annotation of survey imagery. Dense kelp canopies nevertheless constrained vehicle operation, and downward-facing imagery provided limited observations of cryptic or obscured organisms. (4) We provide configuration-specific bills of materials, hardware and wiring documentation, software and firmware inventories, camera settings, open-source field and imagery-processing software, step-by-step field protocols, and pre- and post-dive checklists to support replication and adaptation of the framework. Together, these resources provide a field-tested starting point for expanding standardized benthic imaging while complementing diver surveys across kelp forests and other shallow coastal ecosystems.

Animal movements can transport materials across ecosystem boundaries, while simultaneously modifying habitats through physical engineering. We integrated GPS telemetry, camera trapping, sediment measurements and physicochemical sampling of ponds on Santa Cruz Island, Galapagos, to evaluate how giant tortoises connect and shape terrestrial and freshwater ecosystems. Telemetry revealed 2,254 visits by 21 tortoises to 12 ponds, with visits lasting up to 21.38 h and showing strong seasonal and diel variation, while camera traps showed peak pond use in January and during early morning and late afternoon. Greater tortoise abundance was associated with higher ammonium, dissolved organic carbon and total phosphorus concentrations, while ponds with persistently greater tortoise abundance had higher total suspended solids. Departing tortoises carried a mean 505.9 g of sediment, yielding a conservative potential export of 8.20 kg per tortoise per year and tens of tonnes annually. These findings identify giant tortoises as mobile zoogeochemical engineers linking terrestrial and freshwater ecosystems through physical and biogeochemical pathways.

1. Grassland biodiversity restoration efforts have largely focused on re-establishing diverse plant communities, with less attention paid to higher trophic levels such as invertebrates. 2. We established a controlled, field-scale restoration experiment across twelve lowland grassland sites in Switzerland in close collaboration with farmers. We manipulated seed addition (hay transfer, directly harvested seeds, or multiplied seed mixtures) and soil disturbance (shallow or deep tillage), with treatments applied to meadows covering, on average, 0.5 ha. Four to six years after restoration, we quantified the components of species richness change (lost, persisting, gained from site surroundings, and gained from donors), and estimated dark diversity (species that are absent from a location but could potentially occur there) for plants, Auchenorrhyncha and Orthoptera. 3. Compared to plants, invertebrates exhibited greater species turnover, with higher proportions of species lost and gained from the surroundings, but much lower contributions from the donor meadows. However, species persistence was high across taxa. Restoration operations strongly influenced components of species richness change in plants but had weaker effects on invertebrates. In particular, multiplied seed mixtures + deep tillage had the highest proportion of plant species not transferred, suggesting that many species in the seed mixture were poorly suited to local conditions. In both plants and Auchenorrhyncha, components of species richness change were strongly mediated by site characteristics, with initial species richness in both receiver and donor emerging as the strongest predictors. 4. Within each taxonomic group, 41% of species not transferred from the donor belonged to the dark diversity, suggesting substantial unrealized restoration potential. Restoration operations impacted dark diversity for plants and Auchenorrhyncha but not for Orthoptera. In plants, dark diversity was substantially lower under multiplied seed mixtures + deep tillage than under other treatments. The probability of a species belonging to dark diversity was associated with specific leaf area in plants and initial relative abundance in Auchenorrhyncha. 5. Synthesis and applications. Components of species richness change were influenced by both restoration operations and site characteristics, with their relative importance varying among taxa, underscoring the need for multi-taxon restoration strategies.

Land use change is widely recognized as a major driver of emerging zoonotic diseases. Yet, while forest plantations are expanding worldwide, their consequences on the circulation of infectious agents in wildlife remain poorly understood. We investigated how native pine plantations and broadleaved habitats shape rodent-associated infectious hazard in the generalist wood mouse (Apodemus sylvaticus), in southwestern France. Using a multi-season survey, we screened 424 wood mice for a broad range of infectious taxa and compared infection probability and infected-host abundance among pine plantation edges, broadleaved hedgerows embedded within pine plantations and broadleaved forests. Using a combination of linear mixed model and joint species distribution modelling, we tested whether infectious hazard differed between pine plantations and broadleaved forests, whether broadleaved hedgerows shifted these patterns towards those observed in broadleaved forests, and how these habitat-related patterns varied across seasons. We detected 22 potentially infectious taxa, including nine recognized zoonotic bacteria. Season strongly influenced infectious patterns, while habitat effects were taxa and season dependent. In spring, pine plantation edges increased infection probability for Bartonella grahamii and Neoerhlichia mikurensis compared to broadleaved forest, but their strong negative effect on wood mouse abundance resulted in consistently lower infected-host abundance for most infectious taxa. Broadleaved hedgerows showed distinct and season-dependent patterns with infectious profiles resembling those of pine edges in spring, but with higher infectious hazard than both other habitats for several taxa in autumn. Our results highlight that habitat effects on infectious hazard cannot be inferred from infection probability alone. Pine plantations may reduce rodent-associated zoonotic hazard through their strong negative effect on host abundance, despite increasing infection probability for some agents. Forest diversification and restoration initiatives, such as broadleaved hedgerows here, may have unforeseen epidemiological consequences, underscoring the need to integrate disease ecology into forest management and restoration to anticipate variation in zoonotic risks, while maximizing ecological benefits.

Information on the long-term dynamics of species distributions is essential for assessing global biodiversity change and its causes, and for informed conservation decisions. A valuable source of such historical information are atlases. They provide spatial standardisation, extensive geographic coverage, temporal replication, documented sampling protocols, and span multiple species. Here we present model-based occupancy probabilities for 1,055 bird and 58 butterfly species, derived from nine gridded atlas datasets spanning several editions over the past 50 years. These are: Japan, New Zealand, New York state (US), the states of Alberta, Quebec, and The Maritimes (Canada), Czech Republic, United Kingdom, and Europe. Despite standardisation and coordination during data collection, the raw atlas data still contain some variation in sampling effort. We accounted for this using a two-step process: (1) we estimated a proxy for sampling effort in each grid cell within each atlas period using the Frescalo Algorithm, and (2) we ran a Bayesian spatial occupancy model for each species and atlas period, using the estimated sampling effort as the single predictor of detection in the observation process of the model. As the main product, we provide occupancy probabilities for species across grid cells and atlas periods. We also report uncertainty around each probability estimate and flag ~21% (rare) species per atlas for which the model did not fit well. The probability distributions are fit for purpose and served in a user-friendly database with standardised geographic projection, metadata, and taxonomy.

Reef fish assemblages in the Veracruz Reef System National Park (VRSNP) are strongly structured along a pronounced north-south gradient, where environmental conditions, urban proximity, and protection levels interact to shape functional diversity and ecosystem functioning. This gradient creates contrasting ecological conditions between northern and southern reefs, providing a natural framework for evaluating how spatial variation influences resilience. Using a stationary visual census across ten reefs distributed latitudinally, we quantified functional entities based on six ecological traits and calculated functional richness, redundancy, over-redundancy, vulnerability, specialization, and originality. A two-way permutational ANOVA and redundancy analysis were used to detect spatial and temporal patterns and to link functional indices with environmental features. The southern sector displayed the most intense functional shifts. Nearshore southern reefs, strongly exposed to sedimentation, nutrient loading, and physical disturbance, exhibited reduced functional richness, fewer functional entities, and high functional vulnerability, indicating strong environmental filtering. Over time, these reefs shifted toward generalist-dominated assemblages with rising redundancy, suggesting functional convergence. In contrast, southern offshore reefs supported higher taxonomic and functional richness, buffered by greater habitat complexity and distance from shore, although they showed declining redundancy, likely reflecting sensitivity to regional climatic disturbances. In the northern sector, the gradient was moderated by effective protection, which reshaped functional configurations. Nearshore protected reefs such as Isla Sacrificios and Isla de Enmedio maintained high redundancy, low vulnerability, and high biomass of large-bodied fishes, resembling offshore systems rather than disturbed southern nearshore reefs. The northern offshore reef (Isla Verde) shared some of these attributes but exhibited temporal declines in richness, signaling emerging vulnerabilities along the gradient. Functional originality and specialization aligned with benthic states across the gradient, particularly where macroalgal or calcareous substrates prevailed. Overall, the north-south gradient is the primary axis of functional organization in VRSNP, revealing that resilience emerges from the interplay among reef geomorphology, urban influence, and governance effectiveness.

Fruit resource availability can influence the local abundance of avian frugivores through bottom-up regulation, but whether greater resource availability translates into higher visitation rates to fruiting trees remains poorly understood. Greater fruit availability could increase visitation by supporting larger frugivore populations, or reduce visitation to individual trees if increases in frugivore abundance are not proportionate to those in fruit availability or if frugivores distribute their foraging effort. Understanding these relationships can provide insights into the relative role of abundance and trait-based mechanisms in structuring plant-frugivore communities. We compared fruit availability, avian frugivore abundance, and frugivore visitation rates on fruiting trees across two protected wet tropical forest sites: Anamalai Tiger Reserve in the Western Ghats and Namdapha Tiger Reserve in the Eastern Himalaya. Specifically, we quantified the availability of bird-consumed fruits across one-ha patches, estimated local abundances of major frugivore groups, and tested whether visitation rates on individual fruiting trees were related to frugivore abundance, body mass, and degree of frugivory. We found that small-seeded fruit availability was significantly higher in Anamalai than in Namdapha. Local abundances of several relatively small-bodied frugivore groups, including bulbuls, barbets, fairy-bluebirds, and mynas, were also higher in Anamalai. However, visitation rates of several frugivore groups on individual fruiting trees were higher in Namdapha. Visitation rates across all avian frugivore species were associated with frugivore abundances only in Anamalai, and not associated with body mass or degree of frugivory in either site. Thus, although greater fruit availability was likely associated with higher frugivore abundance, this increase in abundance did not consistently translate into higher visitation rates at individual fruiting trees, which provides some support for the resource dilution hypothesis. Our results highlight the importance of considering fruit resource availability and frugivore abundance when examining variation in tropical plant-frugivore interactions.

In Baltic grey seals (Halichoerus grypus), interannual variation in sea-ice availability can alter the proportion of females breeding on land, generating substantial variation in local breeding density among years. We investigated preweaning survival, post-weaning residence, and weaning body condition at a Baltic grey seal land-breeding colony over two years with contrasting colony densities. Drone imagery provided repeated counts of pups in distinct developmental stages and estimates of moulting pup mass as an index of weaning body condition. A Bayesian state-space population model estimated substantially greater pup production in the high- (282.5 [95% CrI = 252.8 to 320.9] pups) than the low-density (188.3 [95% CrI =168.9 to 210.8] pups) year, but similar preweaning survival (0.66 [95% CrI = 0.53 to 0.81] and 0.67 [95% CrI = 0.56 to 0.79], respectively). In contrast, post-weaning residence differed substantially between the high- (11.8 [95% CrI = 9.2 to 15.7] days) and low-density (30.3 [95% CrI = 23.1 to 39.1] days) years. Greater exposure to other pups during early life was associated with lower weaning body mass ({beta} = -0.45 [-0.89 to -0.01], P[{beta} < 0] = 0.98). Together, these results suggest that the consequences of higher breeding density may emerge through poorer weaning condition and altered post-weaning residence even when effects on preweaning survival are not detectable.