The secret life of wild animals revealed by accelerometer data: How landscape diversity and seasonality influence the behavioural types of European hares

Abstract

Context: Landscape composition and configuration, as well as seasonal landscape dynamics shape the behaviour, movement and energy expenditure in animals, i.e. foraging, hiding or fleeing, and ultimately survival. Especially in highly modified agricultural systems it is crucial to gain an understanding of how animal behaviour is influenced by landscape composition and configuration to ensure sustainable land management concepts. Objectives: We show how landscape composition and configuration and seasonal dynamics affect animal behavioural types, accounting for the different life-history events in both sexes. Methods: We investigated 34 European hares in two contrasting agricultural landscapes differing in landscape composition and configuration (simple vs. complex) by using tri-axial accelerometer data to classify the animals’ behaviour into five categories: resting, foraging, moving, grooming and standing upright (i.e. vigilance behaviour). We then tested whether the amount of behaviours per category changed with landscape composition and configuration, season and sex. Results: During peak breeding, hares in areas of high habitat diversity rested more, moved less and spent less time searching for resources. In winter, however, hares moved more and rested less in areas of high habitat diversity.Conclusions: High habitat diversity is particularly important during the breeding season, allowing animals to allocate enough energy into reproduction. In winter hares in areas of low habitat diversity may not find enough thermal and anti-predator shelter to move as much as they would need to cover their requirements. Hence, high habitat diversity guarantees species persistence in human-altered agricultural areas throughout the year.

Survival, movements, home range size and dispersal of hares after coursing and/or translocation

“…The total sample size (40 hares) was restricted by the logistical considerations of how many animals could be tracked simultaneously and funding. The sample size exceeded the number of individual hares GPS-radio tagged in other recent studies of wild hare behaviour (for example, 25 hares in [9]; 32 hares in [10] and 34 hares in [11]).…”

“…In common with daily movements, daily home range size (95% kernel/24hrs) decreased in area throughout the first week (Day: F df = 1,215 = 16.877, p<0.001) from an average of 60 (38-84) hectares during Day 0 to an average of 14 (10)(11)(12)(13)(14)(15)(16)(17) A single individual translocated uncoursed hare (a male) made a notably unusual and very large exploratory movement over the course of the night during Day 2. During this excursion, it crossed a river twice (outbound and inbound journeys) in locations where there were no bridges and navigated throughout unfamiliar territory circumnavigating the entire study site before returning to near its release site.…”

Identifying animal behaviours from accelerometers: Improving predictive accuracy of machine learning by refining the variables selected, data frequency, and sample duration

“…Animal-attached tri-axial accelerometer loggers, which measure both gravitational and inertial acceleration at high frequency, provide a useful means of recording wild animal behaviours (Gooden et al, 2024;Wilmers et al, 2015) as well as those of animals in captivity and agriculture (Alvarenga et al, 2016;Hathaway et al, 2023). This informs many aspects of species' biology such as their ecology and movements (Bidder et al, 2020;Ullmann et al, 2023), energetics (Dunford et al, 2020;Pagano & Williams, 2019), diel activity patterns (Bryce et al, 2022;Migli et al, 2021), conservation and management (McGowan et al, 2022;Wijers et al, 2018) and welfare (Barbour et al, 2019;Soltis et al, 2012).…”