2025/08/01 by Owen Forbes, Peter H. Thrall, Andrew G. Young +1 · 1 voice · 1 citation
Environmental Science · #Species Distribution and Climate Change #Wildlife Ecology and Conservation #Ecology and Vegetation Dynamics Studies
paper · pdf · doi:10.1111/ele.70188
Natural history collections face a critical juncture as environmental change and biodiversity crises accelerate. While collections data are key components of eco-evolutionary and environmental research in both fundamental and applied contexts, collecting strategies remain primarily taxonomically motivated. We argue that sampling strategies must evolve to better address broader ecological challenges, through emerging applications enabled by advances in data science and digital technology. Here, we propose a flexible framework using modern statistical approaches to optimise sampling design and research prioritisation. By considering biodiversity, environmental, spatial and temporal dimensions, we demonstrate how information theory and decision science tools can support strategic collecting, databasing and digitisation efforts. Our framework provides an evidence-based pathway for collections to enhance their role as critical research infrastructure for addressing 21st century environmental challenges. To illustrate this data-driven approach to research prioritisation, we present an example based on sampling design for wombats (Vombatus ursinus) in Australia.