Effects of summer weather and heatwaves on wild boar activity

Climate change threatens wildlife species, negatively affecting their fitness through environmental change, i.e., through increased severity of droughts and summer heatwaves. Wild boar, a species with limited physiological thermoregulation abilities, is potentially vulnerable to high temperatures during summer. Yet, little is known about the behavioural reactions of this species to heat stress. A detailed understanding of wild boar behavioural adaptations to their environment might help understand their future population growth and change in the geographical range. We used multisensory collars on 24 individual wild boar in the Czech Republic, calculating the dynamic body acceleration as a proxy for energy expenditure to detect activity changes in response to high temperatures on two temporal scales (daily and seasonal) and heatwaves. Our results revealed that overall, under higher temperatures, wild boar reduce their activity, unless it rained. Heatwave intensity did not affect wild boar activity. We suggest that wild boars adapt their activity to weather conditions and presume the importance of sufficient precipitation for thermoregulation in this species. Additionally, this research shows the potential of remote-sensing technologies to monitor wildlife behaviour, particularly in challenging observational scenarios, offering valuable insights into the behavioural responses of wildlife in the face of a changing climate.

Methods
We collected tri-axial acceleration data from multisensory collars mounted on free-ranging wild boar. The tags (Wildbytes Technologies Ltd.) recorded data in 10 Herz frequency. The raw data was then processed using the supporting DDMT software (Wildbytes Technologies Ltd.) and exported as 30-minute sums of the vectorial sum of the dynamic body acceleration (VeDBA). All further processing was performed within the R environment (R version 4.2.2). Weather data was downloaded from the Visual Crossing Weather Query Builder. We first build a data set containing the hourly sums of the VeDBA, the hourly temperature, and the hourly sum of precipitation volume. In the second data set, we generated the average daily VeDBA, adding the daily maximum and mean temperature, the sum of precipitation, and if the date fell within or outside of heatwaves (days over 24 degrees Celsius). The third data set contains the average daily mean of VeDBA only within heatwaves, as well as the length of the heatwave, the maximum temperature within each heatwave, and the total precipitation. 

Ultimately, we used Generalised Additive Mixed Models (GAMMs) and Generalised Linear Mixed Models (GLMMs) to statistically test the effects of weather on the VeDBA in two temporal scales and the intensity of heatwaves.