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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., (© 2022 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.)

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., (© 2021 John Wiley & Sons Ltd.)

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.

Migratory birds spend periods of the year in different locations as a response to seasonal changes in environmental suitability. They are classified as either 'niche‐trackers' or 'niche‐switchers', depending on whether they track or switch environmental conditions throughout the year. However, the relationship between these strategies and their migratory behaviour is still unclear. Here we examine whether migratory European Robins Erithacus rubecula and Eurasian Blackcaps Sylvia atricapilla track environmental conditions between breeding and wintering areas and whether their behaviour differs from that of their sedentary counterparts. We used ringing data for both migratory and sedentary individuals wintering sympatrically in the Iberian Peninsula to assess the environmental conditions relating to their seasonal distributions. We explored seasonal niche‐tracking using two multivariate analyses with alternative sets of predictor variables (landscape and climate) to generate different environmental scenarios. Our results show that migratory individuals track similar climatic conditions throughout their seasonal distributions, whereas sedentary birds cope with great variation in climate over the course of the year. In addition, migratory birds show less seasonal overlap in the landscape structure of their chosen habitats compared with sedentary individuals. These results suggest that there is a trade‐off between, on the one hand, the cost for migrants of travelling long distances and, on the other, the increased flexibility required by sedentary birds if they are to tolerate a wider suite of environmental conditions within their permanent ranges. Given that sedentary populations in the southern Iberian Peninsula seem to be linked to populations of migratory individuals of these two species that started to move northwards after the last glacial cycle, the observed patterns suggest that migrant birds represent a fraction of the southern population that is specialized in the exploitation of a narrower range of environmental conditions. [ABSTRACT FROM AUTHOR]