Biodiversity monitoring is a key element of impact assessment follow-up activities, as it has the potential to generate relevant information about the actual impacts of approved projects on the environment. However, the effectiveness of such monitoring programs depends on issues such as technical quality. The extent to which this issue actually affects biodiversity monitoring is unclear. This knowledge gap was addressed in this study, whose main objective was to analyze the technical quality of fauna monitoring, using empirical data from large-scale mining enterprises in the state of Minas Gerais in southeastern Brazil. More specifically, this study aimed at analyzing: 1) whether license conditions related to fauna monitoring programs were being met by mining companies; 2) the extent to which fauna monitoring programs met a set of technical quality criteria; 3) whether there were significant differences among taxonomic groups; and, finally, 4) how fauna monitoring programs can be made more meaningful to decision-makers. A total of 236 fauna monitoring reports were analyzed. Findings indicated that, while companies complied with all license conditions, their fauna programs met, on average, 32% of the desirable technical requirements, and there were no significant differences among taxonomic groups. The main technical quality gaps were found to be lack of driving questions, hypothesis-testing and conceptual models, as well as lack of comparisons between control and impacted areas. Overall, findings indicated that the data generated in such programs have very limited value to decision-makers as they do not shed sufficient light on the actual impacts of mining activities on biodiversity. The study discusses a number of barriers to more meaningful fauna monitoring programs, and highlights the urgent need for revising current Terms of Reference.
Keywords: Biodiversity; EIA follow-up; Fauna monitoring; Impact assessment; Mining; Technical quality.
Copyright © 2018. Published by Elsevier B.V.