Aim The investigation of phenotypic diversity across geographical gradients is pivotal to understanding the evolution and adaptive functions of alternative phenotypes. The aim of the present study was to investigate whether the polymorphism in ventral plumage colouration observed in the cosmopolitan common barn owl group is determined by climatic factors, such as temperature and rainfall, consistent with Gloger’s and Bogert’s biogeographical rules. Location World. Time period 1809–2017. Major taxa studied Tyto alba species complex. Methods We analysed the variation in heritable melanin‐based plumage colour according to annual temperature and rainfall in 9,110 individuals of the cosmopolitan barn owl, with three distinct evolutionary lineages representing its entire distribution range: the Afro‐European Tyto alba, occurring between Scandinavia and South Africa, the American Tyto furcata, found from southern Canada to Patagonia, and the Australasian Tyto javanica, living between the Himalayan Plateau and Tasmania. Results Although the geographical distribution of colour morphs is heterogeneous among the lineages, in all of them plumage colour becomes darker with increasing annual rainfall, indicating a convergent selection of darker morphs in humid habitats possibly to improve camouflage against the dark environment and/or to repel water more efficiently. Moreover, in T. alba and T. furcata, melanization increases at decreasing temperature, suggesting its possible role in thermoregulation. Discussion These findings provide convincing evidence of repeated evolution of similar body colouration patterns at a worldwide scale compatible with the main biogeographical rules, while emphasizing the possible role of melanin‐based traits in animal adaptation to climate change.

Animal tracking data are being collected more frequently, in greater detail, and on smaller taxa than ever before. These data hold the promise to increase the relevance of animal movement for understanding ecological processes, but this potential will only be fully realized if their accompanying location error is properly addressed. Historically, coarsely-sampled movement data have proved invaluable for understanding large scale processes (e.g., home range, habitat selection, etc.), but modern fine-scale data promise to unlock far more ecological information. While location error can often be ignored in coarsely sampled data, fine-scale data require much more care, and tools to do this have been lacking. Current approaches to dealing with location error largely fall into two categories—either discarding the least accurate location estimates prior to analysis or simultaneously fitting movement and error parameters in a hidden-state model. Unfortunately, both of these approaches have serious flaws. Here, we provide a general framework to account for location error in the analysis of animal tracking data, so that their potential can be unlocked. We apply our error-model-selection framework to 190 GPS, cellular, and acoustic devices representing 27 models from 14 manufacturers. Collectively, these devices are used to track a wide range of animal species comprising birds, fish, reptiles, and mammals of different sizes and with different behaviors, in urban, suburban, and wild settings. Then, using empirical data on tracked individuals from multiple species, we provide an overview of modern, error-informed movement analyses, including continuous-time path reconstruction, home-range distribution, home-range overlap, speed and distance estimation. Adding to these techniques, we introduce new error-informed estimators for outlier detection and autocorrelation visualization. We furthermore demonstrate how error-informed analyses on calibrated tracking data can be necessary to ensure that estimates are accurate and insensitive to location error, and allow researchers to use all of their data. Because error-induced biases depend on so many factors—sampling schedule, movement characteristics, tracking device, habitat, etc.—differential bias can easily confound biological inference and lead researchers to draw false conclusions.

Background The intensification of agricultural practices over the twentieth century led to a cascade of detrimental effects on ecosystems. In Europe, agri-environment schemes (AES) have since been adopted to counter the decrease in farmland biodiversity, with the promotion of extensive habitats such as wildflower strips and extensive meadows. Despite having beneficial effects documented for multiple taxa, their profitability for top farmland predators, like raptors, is still debated. Such species with high movement capabilities have large home ranges with fluctuation in habitat use depending on specific needs. Methods Using GPS devices, we recorded positions for 134 barn owls (Tyto alba) breeding in Swiss farmland and distinguished three main behavioural modes with the Expectation-Maximization binary Clustering (EMbC) method: perching, hunting and commuting. We described barn owl habitat use at different levels during the breeding season by combining step and path selection functions. In particular, we examined the association between behavioural modes and habitat type, with special consideration for AES habitat structures. Results Despite a preference for the most common habitats at the home range level, behaviour-specific analyses revealed more specific habitat use depending on the behavioural mode. During the day, owls roosted almost exclusively in buildings, while pastures, meadows and forest edges were preferred as nocturnal perching sites. For hunting, barn owls preferentially used AES habitat structures though without neglecting more intensively exploited areas. For commuting, open habitats were preferred over wooded areas. Conclusions The behaviour-specific approach used here provides a comprehensive breakdown of barn owl habitat selection during the reproductive season and highlights its importance to understand complex animal habitat preferences. Our results highlight the importance of AES in restoring and maintaining functional trophic chains in farmland.

We are grateful to Roberto Ambrosini and Alexandre H. Hirzel for their invaluable help in statistical analyses and map production.

The Moon cycle exposes nocturnal life to variation in environmental light. However, whether moonlight shapes the fitness of nocturnal species with distinct colour variants remains unknown. Combining long-term monitoring, high-resolution GPS tracking, and experiments on prey, we show that barn owls ( Tyto alba ) with distinct plumage colourations are differently affected by moonlight. The reddest owls are less successful hunting and providing food to their offspring during moonlit nights, which associates with lower body mass and survival of the youngest nestlings and with female mates starting to lay eggs at low moonlight levels. Although moonlight should make white owls more conspicuous to prey, hunting and fitness of the whitest owls are positively or un-affected by moonlight. We experimentally show that, under full-moon conditions, white plumages trigger longer freezing times in the prey, which should facilitate prey catchability. We propose that the barn owl’s white plumage, a rare trait among nocturnal predators, exploits the known aversion of rodents to bright light, explaining why, counterintuitively, moonlight impacts less the whitest owls. Our study provides evidence for the long-suspected influence of the Moon on the evolution of colouration in nocturnal species, highlighting the importance of colour in nocturnal ecosystems.