The NSW Biodiversity Conservation Trust (BCT) works with private landholders in New South Wales to promote and protect biodiversity on private land through conservation agreements. To effectively manage biodiversity and implement best practices for adaptive management, the BCT needs knowledge of which management actions work for managing threatened species.

This project develops the decision-support tools to help them find out how they can design cost-effective experiments so that they can quickly find which management actions work and which ones do not. The tool will help them integrate prior knowledge, generate suitable counterfactuals to evaluate the net (overall) impact of managing biodiversity, determine appropriate effect sizes of experiments, and prioritize experimental effort.

This project will develop an AI tool that finds ways to design better experiments and generate explainable predictions using eXplainable AI (XAI) methods.