Detecting Gold Mining Impacts on Insect Biodiversity in a Tropical Mining Frontier with SmallSat imagery

Eric Stoll, Anand Roopsind, Gyanpriya Maharaj, Sandra Velazco, and T. Trevor Caughlin

• URC22 Abstract • 

Published: May 16, 2022Book of Abstracts of the 4th Undergraduate Research Conference. University of Guyana, Office for Undergraduate Research.


Eric Stoll ✉️ Gyanpriya Maharaj Faculty of Natural Sciences. University of Guyana–Turkeyen Campus. Greater Georgetown, Guyana. 

Anand Roopsind Department: Natural Climate Solutions. Conservation International. Arlington, Virginia, USA.

Gyanpriya Maharaj Centre for the Study of Biological Diversity. University of Guyana-Turkeyen Campus. Greater Georgetown, Guyana.

Sandra Velazco, T. Trevor Caughlin Department of Biology. Boise State University. Boise, Idaho, USA.

Gold mining is a major driver of Amazonian forest loss and degradation. As mining activity encroaches on primary forest in remote areas, satellite imagery provides crucial data for monitoring mining-related deforestation. High-resolution imagery, in particular, has shown promise for detecting artisanal gold mining at the forest frontier. An important next step will be to establish relationships between data on satellite-derived land cover change and biodiversity impacts of gold mining for rapid assessments, using a taxonomic group that accounts for the majority of faunal biodiversity in tropical forests. In this study, we set out to detect artisanal gold mining using high-resolution imagery and relate mining land cover to insects’ diversity and abundance. We applied an object-based image analysis (OBIA) to classify mined areas based on vegetation in an Indigenous territory in Guyana, using PlanetScope imagery with ~3.7 m resolution. We complemented our OBIA with field surveys of insect family presence or absence in field plots (n = 105) that captured a wide range of mining disturbances from active to abandoned mines, then compared the degree of disturbance with insect diversity and abundance. Our OBIA was able to identify mined localities with high accuracy (>90% balanced accuracy). Field plots that fell within areas of higher proportion of OBIA-derived mine cover had significantly lower insect family richness. The effects of mine cover on individual insect taxa encountered were highly variable. Insect groups that respond strongly to mining disturbance could potentially serve as bioindicators for monitoring ecosystem health during and after gold mining. With the new or more global partnerships that provide universal access to PlanetScope imagery for tropical forest monitoring, our approach represents a low-cost and rapid way to assess the biodiversity impacts from gold mining in remote landscapes.

Keywords: Gold mining, PlanetScope, Bioindicators, Remote sensing

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The 4th Undergraduate Research Conference (URC22) was hosted by the University of Guyana’s Office for Undergraduate Research on May 18-20, 2022.