Systematic mapping shows monitoring, evaluation, and engagement are needed to build an evidence base for rewilding

Abstract

Rewilding is a landscape recovery approach that seeks to enhance functioning of degraded ecosystems by reinstating natural processes and is increasingly being adopted by organisations and landowners. Despite its popularity, there is no accepted way to assess rewildings impacts. This is due in part to inconsistent monitoring and evaluation. Here we report the results from a systematic map of the academic and grey literature on monitoring and evaluation in rewilding case studies. We find that researchers and practitioners are focused on different aspects of rewilding, and that limited recording of case study details and lack of robust experimental design make it difficult to pool and compare data. We identify challenges facing researchers and rewilding practitioners seeking to build a robust evidence base from which to evaluate rewilding outcomes. These challenges include resources as well as spatial and time constraints, which all limit the consistency of data gathering among projects. More comparisons across rewilding projects, better standardisation of data collection and data recording methods, and increased collaboration between researchers and practitioners could go some way to remedy this. We provide recommendations for planning and implementing studies of rewilded landscapes to aid monitoring and evaluation. These include the broad adoption of low-cost and scalable survey designs with greater focus on comparisons across sites, and continued effort towards open-source data storage.