Conceptual framework for the implementation of the Species Threat Abatement and Restoration metric's threat abatement component

Abstract One important goal of the Kunming–Montreal Global Biodiversity Framework (KMGBF) aims to halt extinction of species and reduce extinction risk 10‐fold by 2050. To help ensure that the actions taken under the targets of the KMGBF contribute to reducing species’ extinction risk, the Species Threat Abatement and Restoration (STAR) metric was designed to enable science‐based target setting for species. STAR quantifies the potential contribution of threat abatement actions or habitat restoration to reducing species’ extinction risk in an area. To support the effective implementation of STAR, we developed a framework to move from determining the threat abatement component of STAR (STAR T ) using global data to calibrating STAR T using local data to setting targets and calculating realized STAR T scores to measure progress. The framework outlines the specific approaches that can be implemented to calculate these different STAR T metrics. First, estimated STAR T scores use global data to provide an initial indication of the species and threats expected to be present within an area. Then, calibrated STAR T scores involve confirming the local presence of species and threats, and the locally verified data allow for setting robust threat abatement targets, which can be articulated as target STAR T scores. Calibrated STAR T can also inform both reactive and proactive threat management. Finally, changes in threat intensity are then monitored and used to calculate realized STAR T . Achieving realized STAR T requires actors to not only reduce existing threats but also prevent additional threats emerging within the area. This framework provides a means for all potential actors, working across varying spatial scales, to quantify, plan, monitor, and deliver interventions to address species threats and then report the impact of the interventions using a consistent method and metric that are comparable and aggregable across actors and locations.