Enhancing biodiversity monitoring in impact assessment follow-up through landscape metrics

Field-based monitoring may be insufficient to detect biodiversity trends across scales, especially in projects that have the potential to impact extensive areas. Despite its importance, landscape-scale data collection is rare in impact monitoring practice. In this research, we tested landscape metrics to evaluate their contribution to enhancing forest biodiversity monitoring in the EIA follow-up process, using a case study of a bauxite mine in the Brazilian Amazon. The research combined literature review and a case study to select, apply, and compare landscape metrics with local-scale field-based biodiversity monitoring. Metrics related to the amount and quality of habitats, fragmentation, edge effect extent and connectivity of landscape were selected and evaluated. We found that they can be easily incorporated into EIA follow-up, as they rely on readily available remote sensing time series, enabling the construction of historical baselines even prior to project approval. Also, landscape metrics can complement field-based surveys by detecting spatial patterns and offering opportunities for integrated multi-scale biodiversity assessments. Furthermore, they provide valuable inputs for identifying, planning, and spatially allocating offsets and additional conservation actions, thereby contributing to more effective impact mitigation and supporting stronger biodiversity outcomes.