Understanding ecosystem-wide responses to anthropogenic pressure

Human-induced environmental pressures are altering ecological communities in ways not fully understood. In the face of a biodiversity loss crisis, understanding the impact of these pressures is crucial for future conservation efforts. In this thesis, I investigate wildlife responses to anthropogenic pressure and consider how biodiversity monitoring methods could be optimised. I use macro-ecological datasets and a field study in Nepal to investigate different methods used for biodiversity monitoring at varying spatial and ecological scales. I utilise cutting-edge machine learning technology to create an efficient pipeline for analysing camera trap data, providing metrics on behaviour change and community composition in response to anthropogenic pressure. In addition, novel automated methods for analysing camera trap data without species identification are proposed and explored. The findings presented in this thesis address the paradoxical needs of global biodiversity monitoring, where comprehensive global metrics must simultaneously account for the nuances of species' responses to different pressures.