Contrasting impacts of gold mining and oil palm expansion on ecosystem functioning in the Peruvian Amazon

Castillo H.; Guerra J.C.; Sakaguchi F.; Cano D.; Baldassini P. · Remote Sensing Applications: Society and Environment (2026) · DOI: 10.1016/j.rsase.2026.102098

Resumen

Gold mining and oil palm expansion are major drivers of forest conversion in the Peruvian Amazon, yet their long-term biophysical consequences remain unevenly quantified. We assessed post-conversion trajectories (2001–2024) of four ecosystem functioning variables, NDVI (a proxy for vegetation greenness and an indirect indicator of ecosystem productivity), evapotranspiration (ET), albedo, and land surface temperature (LST), using MODIS products across 300 1-km grid-aligned sites in Madre de Dios (gold mining) and Ucayali (oil palm plantations), with regional forest areas used as controls. Conversion impacts were estimated using a Before–After Control–Impact (BACI) framework, while temporal dynamics were evaluated using segmented regressions and event-study analyses. Gold mining caused strong and persistent biophysical degradation: NDVI and ET decreased markedly (median BACI = −0.647 and −0.66 mm day−1), while albedo and LST increased (median BACI = +0.045 and + 2.84 °C; all p < 0.001). In contrast, oil palm plantations showed smaller but significant shifts (NDVI −0.074; ET −0.151 mm day−1; albedo +0.036; LST +1.83 °C; p < 0.001), followed by partial biophysical recovery in NDVI and ET after establishment (breakpoint ∼2014). However, plantations did not recover pre-conversion forest conditions, indicating that increases in vegetation greenness do not imply recovery of the ecological complexity and functions of native forests. These contrasting trajectories reveal fundamentally different pathways of ecosystem transformation between extractive and managed land uses. By integrating vegetation, water, energy, and radiative indicators, this study provides scalable metrics that can support environmental agencies, restoration planners, and decision-makers in monitoring land-use impacts and prioritizing restoration actions in the Peruvian Amazon.

Instituciones: Universidad de Huánuco