Spatial cognitive ability is associated with transitory movement speed but not straightness during the early stages of exploration

Wild cognition - linking form and function of cognitive abilities within a natural context

Interest in studying cognitive ecology has moved the field of animal cognition into the wild. Animals face many challenges such as finding food and other resources, avoiding and deterring predators and choosing the best mate to increase their reproductive success. To solve these dilemmas, animals need to rely on a range of cognitive abilities. Studying cognition in natural settings is a powerful approach revealing the link between adaptive form and biological function. Recent technological and analytical advances opened up completely new opportunities and research directions for studying animal cognition. Such innovative studies were able to disclose the variety in cognitive processes that animals use to survive and reproduce. Cognition indeed plays a major role in the daily lives of wild animals, in which the integration of many different types of information using a diverse range of cognitive processes enhances fitness.

Big-data approaches lead to an increased understanding of the ecology of animal movement

Understanding animal movement is essential to elucidate how animals interact, survive, and thrive in a changing world. Recent technological advances in data collection and management have transformed our understanding of animal "movement ecology" (the integrated study of organismal movement), creating a big-data discipline that benefits from rapid, cost-effective generation of large amounts of data on movements of animals in the wild. These high-throughput wildlife tracking systems now allow more thorough investigation of variation among individuals and species across space and time, the nature of biological interactions, and behavioral responses to the environment. Movement ecology is rapidly expanding scientific frontiers through large interdisciplinary and collaborative frameworks, providing improved opportunities for conservation and insights into the movements of wild animals, and their causes and consequences.

A guide to pre-processing high-throughput animal tracking data

Modern, high‐throughput animal tracking increasingly yields ‘big data’ at very fine temporal scales. At these scales, location error can exceed the animal's step size, leading to mis‐estimation of behaviours inferred from movement. ‘Cleaning’ the data to reduce location errors is one of the main ways to deal with position uncertainty. Although data cleaning is widely recommended, inclusive, uniform guidance on this crucial step, and on how to organise the cleaning of massive datasets, is relatively scarce.

A pipeline for cleaning massive high‐throughput datasets must balance ease of use and computationally efficiency, in which location errors are rejected while preserving valid animal movements. Another useful feature of a pre‐processing pipeline is efficiently segmenting and clustering location data for statistical methods while also being scalable to large datasets and robust to imperfect sampling. Manual methods being prohibitively time‐consuming, and to boost reproducibility, pre‐processing pipelines must be automated.

We provide guidance on building pipelines for pre‐processing high‐throughput animal tracking data to prepare it for subsequent analyses. We apply our proposed pipeline to simulated movement data with location errors, and also show how large volumes of cleaned data can be transformed into biologically meaningful ‘residence patches’, for exploratory inference on animal space use. We use tracking data from the Wadden Sea ATLAS system (WATLAS) to show how pre‐processing improves its quality, and to verify the usefulness of the residence patch method. Finally, with tracks from Egyptian fruit bats Rousettus aegyptiacus, we demonstrate the pre‐processing pipeline and residence patch method in a fully worked out example.

To help with fast implementation of standardised methods, we developed the R package atlastools, which we also introduce here. Our pre‐processing pipeline and atlastools can be used with any high‐throughput animal movement data in which the high data‐volume combined with knowledge of the tracked individuals' movement capacity can be used to reduce location errors. atlastools is easy to use for beginners while providing a template for further development. The common use of simple yet robust pre‐processing steps promotes standardised methods in the field of movement ecology and leads to better inferences from data.

The effects of released pheasants on invertebrate populations in and around woodland release sites

The release of gamebirds for recreational shooting exerts a series of effects on the ecosystems into which they are placed. Pheasants (Phasianus colchicus) are omnivorous and eat invertebrates, especially when young or, if females, when breeding. Consequently, the release of large numbers of pheasants into woodland release pens may affect local invertebrate populations. Previous studies have reported mixed evidence. We conducted pitfall trapping at 13 sites (49 pens) in central England over 2 years (totaling 65 pen measures), comprising three surveys annually, immediately prior to releases in mid-summer, 4 weeks later when most birds were still in the pens, and another 5 weeks later when most birds had dispersed. We compared traps inside and 25 m outside pens in the same wood. We considered release densities and whether the birds had prior experience of eating invertebrates. While accounting for overall seasonal declines in invertebrates trapped, we detected changes for total invertebrate biomass and total counts indicative of released pheasants causing local decreases inside pens, either directly by predation or indirectly by modifying vegetation. There were also relative decreases outside pens when the pheasants start to disperse, suggesting that the released pheasants may be affecting invertebrates in those nearby areas or that their earlier effects inside the pen, modifying vegetation or increasing invertebrate activity, increased the relative susceptibility of invertebrates there to trapping. However, these effects were not seen for specific invertebrate groups believed to be especially susceptible to pheasants. For slugs and detritivores, we detected small population increases inside pens. Across the study period, decreases for most measures were greater outside pens than inside them. We conclude that any effects pheasants have on invertebrate communities at release sites in woodlands are complex and that long-term and taxon-specific studies should be considered to understand the local net ecological effects of gamebird releases on invertebrates.