Novel approaches to monitoring and evaluating conservation's cornerstones: Assessing protected area performance from functional perspectives

Protected areas are an important tool for conservation efforts around the world; however, their effectiveness at conserving biodiversity varies. Our understanding of this variation is based on a few metrics, such as species abundance, species richness and land cover. In contrast, there has been little consideration of protected area performance for conserving more functional aspects of biodiversity; for example, functional diversity of species assemblages and multiple dimensions of ecosystem functionality. This doctoral research seeks to address evidence gaps in this space of protected area performance for conserving functional aspects of biodiversity.

This doctoral research has three parts. The first part has involved assessing protected area performance at conserving functional diversity, which corresponds to the diversity of what species do. This part has focused on 23 protected areas across Tanzania, and it has used camera trap data and functional trait information to calculate the functional diversity metric, and satellite remote sensing data to determine and so account for land cover. Its findings have suggested that protected areas with greater protection have been more effective at conserving functional diversity. The second and third parts will investigate the impacts of manifestations of climate change on multiple dimensions of ecosystem functionality in protected areas across Eastern and Southern Africa. The second part will consider trends in climate change and ecosystem functionality over time (c.2000-2024) and the third part will focus on the resilience of ecosystem functioning to droughts and floods. Together, the second and third parts will provide us with a richer picture of climate change impacts on ecosystems and their functionality, as well as flag areas that may face the greatest threats from climate change and so need further interventions. The the second and third parts will both use satellite remote sensing data and large climate datasets.