Owen Forbes, Peter H. Thrall, Andrew G. Young, Cheng Soon Ong
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引用次数: 0
Abstract
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.
期刊介绍:
Ecology Letters serves as a platform for the rapid publication of innovative research in ecology. It considers manuscripts across all taxa, biomes, and geographic regions, prioritizing papers that investigate clearly stated hypotheses. The journal publishes concise papers of high originality and general interest, contributing to new developments in ecology. Purely descriptive papers and those that only confirm or extend previous results are discouraged.