Insights into short- and long-term crop-foraging strategies in a chacma baboon (Papio ursinus) from GPS and accelerometer data

Disgust in animals and the application of disease avoidance to wildlife management and conservation

Disgust is an adaptive system hypothesized to have evolved to reduce the risk of becoming sick. It is associated with behavioural, cognitive and physiological responses tuned to allow animals to avoid and/or get rid of parasites, pathogens and toxins. Little is known about the mechanisms and outcomes of disease avoidance in wild animals. Furthermore, given the escalation of negative human-wildlife interactions, the translation of such knowledge into the design of evolutionarily relevant conservation and wildlife management strategies is becoming urgent. Contemporary methods in animal ecology and related fields, using direct (sensory cues) or indirect (remote sensing technologies and machine learning) means, provide a flexible toolbox for testing and applying disgust at individual and collective levels. In this review/perspective paper, we provide an empirical framework for testing the adaptive function of disgust and its associated disease avoidance behaviours across species, from the least to the most social, in different habitats. We predict various trade-offs to be at play depending on the social system and ecology of the species. We propose five contexts in which disgust-related avoidance behaviours could be applied, including endangered species rehabilitation, invasive species, crop-raiding, urban pests and animal tourism. We highlight some of the perspectives and current challenges of testing disgust in the wild. In particular, we recommend future studies to consider together disease, predation and competition risks. We discuss the ethics associated with disgust experiments in the above contexts. Finally, we promote the creation of a database gathering disease avoidance evidence in animals and its applications.

Camera traps and guard observations as an alternative to researcher observation for studying anthropogenic foraging

Foraging by wildlife on anthropogenic foods can have negative impacts on both humans and wildlife. Addressing this issue requires reliable data on the patterns of anthropogenic foraging by wild animals, but while direct observation by researchers can be highly accurate, this method is also costly and labor‐intensive, making it impractical in the long‐term or over large spatial areas. Camera traps and observations by guards employed to deter animals from fields could be efficient alternative methods of data collection for understanding patterns of foraging by wildlife in crop fields. Here, we investigated how data on crop‐foraging by chacma baboons and vervet monkeys collected by camera traps and crop guards predicted data collected by researchers, on a commercial farm in South Africa. We found that data from camera traps and field guard observations predicted crop loss and the frequency of crop‐foraging events from researcher observations for crop‐foraging by baboons and to a lesser extent for vervets. The effectiveness of cameras at capturing crop‐foraging events was dependent on their position on the field edge. We believe that these alternatives to direct observation by researchers represent an efficient and low‐cost method for long‐term and large‐scale monitoring of foraging by wildlife on crops.