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Dispersal is a key life‐history trait for most species and is essential to ensure connectivity and gene flow between populations and facilitate population viability in variable environments. Despite the increasing importance of range shifts due to global change, dispersal has proved difficult to quantify, limiting empirical understanding of this phenotypic trait and wider synthesis.Here, we introduce a statistical framework to estimate standardised dispersal kernels from biased data. Based on this, we compare empirical dispersal kernels for European breeding birds considering age (average dispersal; natal, before first breeding; and breeding dispersal, between subsequent breeding attempts) and sex (females and males) and test whether different dispersal properties are phylogenetically conserved.We standardised and analysed data from an extensive volunteer‐based bird ring‐recoveries database in Europe (EURING) by accounting for biases related to different censoring thresholds in reporting between countries and to migratory movements. Then, we fitted four widely used probability density functions in a Bayesian framework to compare and provide the best statistical descriptions of the different age and sex‐specific dispersal kernels for each bird species.The dispersal movements of the 234 European bird species analysed were statistically best explained by heavy‐tailed kernels, meaning that while most individuals disperse over short distances, long‐distance dispersal is a prevalent phenomenon in almost all bird species. The phylogenetic signal in both median and long dispersal distances estimated from the best‐fitted kernel was low (Pagel's λ < 0.25), while it reached high values (Pagel's λ >0.7) when comparing dispersal distance estimates for fat‐tailed dispersal kernels. As expected in birds, natal dispersal was on average 5 km greater than breeding dispersal, but sex‐biased dispersal was not detected.Our robust analytical framework allows sound use of widely available mark‐recapture data in standardised dispersal estimates. We found strong evidence that long‐distance dispersal is common among European breeding bird species and across life stages. The dispersal estimates offer a first guide to selecting appropriate dispersal kernels in range expansion studies and provide new avenues to improve our understanding of the mechanisms and rules underlying dispersal events. [ABSTRACT FROM AUTHOR]

Background and Aims It is widely accepted that changes in the environment affect mean trait expression, but little is known about how the environment shapes intra-individual and intra-population variance. Theory suggests that intra-individual variance might be plastic and under natural selection, rather than reflecting developmental noise, but evidence for this hypothesis is scarce. Here, we experimentally tested whether differences in intrinsic environmental predictability affect intra-individual and intra-population variability of different reproductive traits, and whether intra-individual variability is under selection. Methods Under field conditions, we subjected Onobrychis viciifolia to more and less predictable precipitation over 4 generations and 4 years. We analysed effects on the coefficient of intra-individual variation (CVi-i) and the coefficient of intra-population variation (CVi-p), assessed whether the coefficients of intra-individual variation (CsVi-i) are under natural selection and tested for transgenerational responses (ancestor environmental effects on offspring). Key Results Less predictable precipitation led to higher CsVi-i and CsVi-p, consistent with plastic responses. The CsVi-i of all studied traits were under consistent stabilizing selection, and precipitation predictability affected the strength of selection and the location of the optimal CVi-i of a single trait. All CsVi-i differed from the optimal CVi-i and the maternal and offspring CsVi-i were positively correlated, showing that there was scope for change. Nevertheless, no consistent transgenerational effects were found in any of the three descendant generations, which contrasts with recent studies that detected rapid transgenerational responses in the trait means of different plant species. This suggests that changes in intra-individual variability take longer to evolve than changes in trait means, which may explain why high intra-individual variability is maintained, despite the stabilizing selection. Conclusions The results indicate that plastic changes of intra-individual variability are an important determinant of whether plants will be able to cope with changes in environmental predictability induced by the currently observed climatic change. [ABSTRACT FROM AUTHOR]

Global biodiversity is under high and rising anthropogenic pressure. Yet, how the taxonomic, phylogenetic, and functional facets of biodiversity are affected by different threats over time is unclear. This is particularly true for the two main drivers of the current biodiversity crisis: habitat destruction and overexploitation. We provide the first long‐term assessment of multifaceted biodiversity changes caused by these threats for any tropical region. Focussing on larger mammals in South America's 1.1 million km2 Gran Chaco region, we assessed changes in multiple biodiversity facets between 1985 and 2015, determined which threats drive those changes, and identified remaining key areas for all biodiversity facets. Using habitat and threat maps, we found, first, that between 1985 and 2015 taxonomic (TD), phylogenetic (PD) and functional (FD) diversity all declined drastically across over half of the area assessed. FD declined about 50% faster than TD and PD, and these declines were mainly driven by species loss, rather than species turnover. Second, habitat destruction, hunting, and both threats together contributed ~57%, ~37%, and ~6% to overall facet declines, respectively. However, hunting pressure increased where TD and PD declined most strongly, whereas habitat destruction disproportionally contributed to FD declines. Third, just 23% of the Chaco would have to be protected to safeguard the top 17% of all three facets. Our findings uncover a widespread impoverishment of mammal species richness, evolutionary history, and ecological functions across broad areas of the Chaco due to increasing habitat destruction and hunting. Moreover, our results pinpoint key areas that should be preserved and managed to maintain all facets of mammalian diversity across the Chaco. More generally, our work highlights how long‐term changes in biodiversity facets can be assessed and attributed to specific threats, to better understand human impacts on biodiversity and to guide conservation planning to mitigate them. [ABSTRACT FROM AUTHOR]

Seasonal animal migration is a widespread phenomenon. At the species level, it has been shown that many migratory animal species track similar climatic conditions throughout the year. However, it remains unclear whether such a niche tracking pattern is a direct consequence of individual behaviour or emerges at the population or species level through behavioural variability. Here, we estimated seasonal niche overlap and seasonal niche tracking at the individual and population level of central European white storks (Ciconia ciconia). We quantified niche tracking for both weather and climate conditions to control for the different spatio-temporal scales over which ecological processes may operate. Our results indicate that niche tracking is a bottom-up process. Individuals mainly track weather conditions while climatic niche tracking mainly emerges at the population level. This result may be partially explained by a high degree of intra- and inter-individual variation in niche overlap between seasons. Understanding how migratory individuals, populations and species respond to seasonal environments is key for anticipating the impacts of global environmental changes. [ABSTRACT FROM AUTHOR]

Seasonal animal migration is a widespread phenomenon. At the species level, it has been shown that many migratory animal species track similar climatic conditions throughout the year. However, it remains unclear whether such a niche tracking pattern is a direct consequence of individual behaviour or emerges at the population or species level through behavioural variability. Here, we estimated seasonal niche overlap and seasonal niche tracking at the individual and population level of central European white storks (Ciconia ciconia). We quantified niche tracking for both weather and climate conditions to control for the different spatio-temporal scales over which ecological processes may operate. Our results indicate that niche tracking is a bottom-up process. Individuals mainly track weather conditions while climatic niche tracking mainly emerges at the population level. This result may be partially explained by a high degree of intra- and inter-individual variation in niche overlap between seasons. Understanding how migratory individuals, populations and species respond to seasonal environments is key for anticipating the impacts of global environmental changes. [ABSTRACT FROM AUTHOR]

Although domestic carnivores are frequently considered a threat to wildlife inside and around urban areas, little is known about the incursions of these animals from urban areas to the surrounding habitats. To explore this, we sampled carnivores in wooded areas surrounding four villages located in the mountains north of Madrid by using 40 camera-trapping stations. They were distributed at regular distances within a perpendicular transect distributed from 10 to 2000 m from the urban border. The results suggest that the incidence of domestic carnivores (cats and dogs) was constrained to <400 m from the urban border, and that the presence of domestic carnivores did not interfere with the distribution of wild carnivores (foxes, beech martens, badgers, genets, etc.), which show random distribution patterns around villages. This means that overpredation at the village edges could mainly be due to the effect of domestic animals and not to that of wild carnivores attracted to urban areas. [ABSTRACT FROM AUTHOR]

Human-wildlife conflict is a major conservation challenge worldwide, with negative consequences for people and wildlife alike. Large carnivores, despite their key role in ecosystem functioning, are persecuted throughout their ranges as a response to perceived or actual risks to livestock and humans. To promote human-carnivore coexistence, a better understanding of the determinants of conflict is necessary. A range of factors have been hypothesized to influence livestock depredation risk, including carnivore habitat suitability and connectivity, prey availability, and anthropogenic factors. Yet, the relative importance of these factors is often unclear. We analyzed and mapped livestock depredation risk for the Persian leopard (Panthera pardus tulliana) in southern Iran using a species distribution modeling framework. We used livestock depredation reports and interviews (n = 199) from 25 randomly selected villages together with predictors capturing leopard habitat suitability, movement corridors, wild and domestic prey, and anthropogenic pressure. Our leopard habitat suitability and connectivity analyses predicted 28 core habitat patches (>250km2) associated with mountainous and conserved areas, with partly severed corridors between them. Our risk mapping indicated that the chance of livestock depredation increased in areas with higher leopard habitat suitability. Conversely, depredation risk was lower in areas with more wild prey. We predicted the highest depredation risk in about 12 % of the landscape where urgent conflict mitigation measures would be most beneficial. More generally, our study shows that while conservation areas provide refuge for carnivores, these areas can also lead to higher levels of conflict, hence mitigation measures should be prioritized in their surroundings. [ABSTRACT FROM AUTHOR]

Artificial light at night (ALAN) is increasing in extent and intensity across the globe. It has been shown to interfere with animal sensory systems, orientation and distribution, with the potential to cause significant ecological impacts. We analysed the locations of 102 mountain lions (Puma concolor) in a light-polluted region in California. We modelled their distribution relative to environmental and human-disturbance variables, including upward radiance (nearby lights), zenith brightness (sky glow) and natural illumination from moonlight. We found that mountain lion probability of presence was highly related to upward radiance, that is, related to lights within approximately 500 m. Despite a general pattern of avoidance of locations with high upward radiance, there were large differences in degree of avoidance among individuals. The amount of light from artificial sky glow was not influential when included together with upward radiance in the models, and illumination from moonlight was not influential at all. Our results suggest that changes in visibility associated with lunar cycles and sky glow are less important for mountain lions in their selection of light landscapes than avoiding potential interactions with humans represented by the presence of nearby lights on the ground. This article is part of the theme issue 'Light pollution in complex ecological systems'. [ABSTRACT FROM AUTHOR]

Most of Spain is managed for game hunting, an economic activity that is commonly related to predator control. This practice can affect the diversity and abundance of wild carnivores if, despite that hunting is legally focused on some target species, other species are illegally removed. This note evaluates the changes in the structure of carnivore assemblage between wildlife refuges (no predator control) and private areas managed for game production where, because of little regulation, foxes and crows can be eliminated. Our aim is to test if predator control produces a significant change in the presence of foxes (the target species) or whether it also affects other carnivores. [ABSTRACT FROM AUTHOR]

The formation of independent evolutionary lineages involves neutral and selective factors, and understanding their relative roles in population divergence is a fundamental goal of speciation research. Correlations between allele frequencies and environmental variability can reveal the role of selection, yet the relative contribution of drift can be difficult to establish. Recently diversified taxa like the Oregon junco (Aves, Passerellidae, Junco hyemalis oreganus) of western North America provide ideal scenarios to apply genetic‐environment association analyses (GEA) while controlling for population structure. Analysis of genome‐wide SNP loci revealed marked genetic structure consisting of differentiated populations in isolated, dry southern mountain ranges, and less divergent, recently expanded populations in humid northern latitudes. We used correlations between genomic and environmental variance to test for three specific modes of evolutionary divergence: (a) drift in geographic isolation, (b) differentiation along continuous selective gradients and (c) isolation‐by‐adaptation. We found evidence of strong drift in southern mountains, but also signals of local adaptation driven by temperature, precipitation, elevation and vegetation, especially when controlling for population history. We identified numerous variants under selection scattered across the genome, suggesting that local adaptation can promote rapid differentiation when acting over multiple independent loci. [ABSTRACT FROM AUTHOR]

Aim: Large carnivores are currently recolonizing parts of their historical ranges in Europe after centuries of persecution and habitat loss. Understanding the mechanisms driving these recolonizations is important for proactive conservation planning. Using the brown bear (Ursus arctos) and the Iberian lynx (Lynx pardinus) as examples, we explore where and when large carnivores are likely to expand into human‐dominated landscapes and how varying levels of resistance due to human pressure might impact this recolonization process. Location: Iberian Peninsula. Methods: We used ensembles of species distribution models to relate species occurrence data to climate, topography and satellite‐based land‐cover predictors at a 10 km spatial resolution. Resulting predictions of suitable habitat areas were fed into a dispersal model to simulate range expansion over the 10 time‐steps for different human pressure scenarios. Finally, we overlaid predictions with protected areas to highlight areas that are likely key for future connectivity, but where human pressures might hamper dispersal. Results: We found widespread suitable habitat for both species (bear: 30,000 km2, lynx: 170,000 km2), yet human pressure limits potential range expansions. For brown bears, core habitats between the Cantabrian and Pyrenean populations remained unconnected despite suitable habitat in between. For lynx, we predicted higher range expansion potential, although high human pressures in southern coastal Spain negatively affected expansion potential. Main conclusions: Our results highlight that the recolonization potential of brown bears and lynx in the Iberian Peninsula is likely more constrained by lower permeability of landscapes due to human pressure than by habitat availability, a situation likely emblematic for large carnivores in many parts of the world. More generally, our approach provides a simple tool for conservation planners and managers to identify where range expansion is likely to occur and where proactively managing to allow large carnivores to safely disperse through human‐dominated landscapes can contribute to viable large carnivore populations. [ABSTRACT FROM AUTHOR]

We studied the effect of climate change on the distribution of two insectivorous passerines (the meadow pipit Anthus pratensis and the chiffchaff Phylloscopus collybita) in wintering grounds of the Western Mediterranean basin. In this region, precipitation and temperature can affect the distribution of these birds through direct (thermoregulation costs) or indirect effects (primary productivity). Thus, it can be postulated that projected climate changes in the region will affect the extent and suitability of their wintering grounds. We studied pipit and chiffchaff abundance in several hundred localities along a belt crossing Spain and Morocco and assessed the effects of climate and other geographical and habitat predictors on bird distribution. Multivariate analyses reported a positive effect of temperature on the present distribution of the two species, with an additional effect of precipitation on the meadow pipit. These climate variables were used with Maxent to model the occurrence probabilities of species using ring recoveries as presence data. Abundance and occupancy of the two species in the study localities adjusted to the distribution models, with more birds in sectors of high climate suitability. After validation, these models were used to forecast the distribution of climate suitability according to climate projections for 2050–2070 (temperature increase and precipitation reduction). Results show an expansion of climatically suitable sectors into the highlands by the effect of warming on the two species, and a retreat of the meadow pipit from southern sectors related to rain reduction. The predicted patterns show a mean increase in climate suitability for the two species due to the warming of the large highland expanses typical of the western Mediterranean. [ABSTRACT FROM AUTHOR]

Models are useful tools for understanding and predicting ecological patterns and processes. Under ongoing climate and biodiversity change, they can greatly facilitate decision‐making in conservation and restoration and help designing adequate management strategies for an uncertain future. Here, we review the use of spatially explicit models for decision support and to identify key gaps in current modelling in conservation and restoration. Of 650 reviewed publications, 217 publications had a clear management application and were included in our quantitative analyses. Overall, modelling studies were biased towards static models (79%), towards the species and population level (80%) and towards conservation (rather than restoration) applications (71%). Correlative niche models were the most widely used model type. Dynamic models as well as the gene‐to‐individual level and the community‐to‐ecosystem level were underrepresented, and explicit cost optimisation approaches were only used in 10% of the studies. We present a new model typology for selecting models for animal conservation and restoration, characterising model types according to organisational levels, biological processes of interest and desired management applications. This typology will help to more closely link models to management goals. Additionally, future efforts need to overcome important challenges related to data integration, model integration and decision‐making. We conclude with five key recommendations, suggesting that wider usage of spatially explicit models for decision support can be achieved by 1) developing a toolbox with multiple, easier‐to‐use methods, 2) improving calibration and validation of dynamic modelling approaches and 3) developing best‐practise guidelines for applying these models. Further, more robust decision‐making can be achieved by 4) combining multiple modelling approaches to assess uncertainty, and 5) placing models at the core of adaptive management. These efforts must be accompanied by long‐term funding for modelling and monitoring, and improved communication between research and practise to ensure optimal conservation and restoration outcomes. [ABSTRACT FROM AUTHOR]

Predictions of species' current and future ranges are needed to effectively manage species under environmental change. Species ranges are typically estimated using correlative species distribution models (SDMs), which have been criticized for their static nature. In contrast, dynamic occupancy models (DOMs) explicitily describe temporal changes in species' occupancy via colonization and local extinction probabilities, estimated from time series of occurrence data. Yet, tests of whether these models improve predictive accuracy under current or future conditions are rare. Using a long‐term data set on 69 Swiss birds, we tested whether DOMs improve the predictions of distribution changes over time compared to SDMs. We evaluated the accuracy of spatial predictions and their ability to detect population trends. We also explored how predictions differed when we accounted for imperfect detection and parameterized models using calibration data sets of different time series lengths. All model types had high spatial predictive performance when assessed across all sites (mean AUC > 0.8), with flexible machine learning SDM algorithms outperforming parametric static and DOMs. However, none of the models performed well at identifying sites where range changes are likely to occur. In terms of estimating population trends, DOMs performed best, particularly for species with strong population changes and when fit with sufficient data, while static SDMs performed very poorly. Overall, our study highlights the importance of considering what aspects of performance matter most when selecting a modelling method for a particular application and the need for further research to improve model utility. While DOMs show promise for capturing range dynamics and inferring population trends when fitted with sufficient data, computational constraints on variable selection and model fitting can lead to reduced spatial accuracy of predictions, an area warranting more attention. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) constitute the most common class of models across ecology, evolution and conservation. The advent of ready‐to‐use software packages and increasing availability of digital geoinformation have considerably assisted the application of SDMs in the past decade, greatly enabling their broader use for informing conservation and management, and for quantifying impacts from global change. However, models must be fit for purpose, with all important aspects of their development and applications properly considered. Despite the widespread use of SDMs, standardisation and documentation of modelling protocols remain limited, which makes it hard to assess whether development steps are appropriate for end use. To address these issues, we propose a standard protocol for reporting SDMs, with an emphasis on describing how a study's objective is achieved through a series of modeling decisions. We call this the ODMAP (Overview, Data, Model, Assessment and Prediction) protocol, as its components reflect the main steps involved in building SDMs and other empirically‐based biodiversity models. The ODMAP protocol serves two main purposes. First, it provides a checklist for authors, detailing key steps for model building and analyses, and thus represents a quick guide and generic workflow for modern SDMs. Second, it introduces a structured format for documenting and communicating the models, ensuring transparency and reproducibility, facilitating peer review and expert evaluation of model quality, as well as meta‐analyses. We detail all elements of ODMAP, and explain how it can be used for different model objectives and applications, and how it complements efforts to store associated metadata and define modelling standards. We illustrate its utility by revisiting nine previously published case studies, and provide an interactive web‐based application to facilitate its use. We plan to advance ODMAP by encouraging its further refinement and adoption by the scientific community. [ABSTRACT FROM AUTHOR]