Changepoint detection methods as a practical tool for assessment of ecological restoration

Mengyi Gong, Simone Conte, Tom Jameson, Rebecca Killick, James C. Bull, Luca Börger, Rachel McCrea

1. A key aim of many conservation initiatives is to induce a change, however detecting change from monitoring data can be challenging. Here, we introduce statistical methods for changepoint detection, demonstrating how this under-utilised analytical approach can provide practitioners and researchers insight and help in planning ecological restoration projects.
2. We show why it is important to consider the stage of an ecological intervention as well as the design of the study and how this impacts the power of detecting a change in observed data.
3. Practical Implication: We provide user-friendly software and guidance that can be used to explore and quantify the data needed to detect change, under different settings. This enables practitioners to understand data requirements before planning monitoring studies, and effectively manage ongoing projects through all stages.