Detecting gold mining impacts on insect biodiversity in a tropical mining frontier with SmallSat imagery

Abstract

Gold mining is a major driver of Amazonian forest loss and degradation. As mining activity encroaches on primary forest in remote and inaccessible 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 satellite-derived land cover change and biodiversity impacts of gold mining. In this study, we set out to detect artisanal gold mining using high-resolution imagery and relate mining land cover to insects, a taxonomic group that accounts for the majority of faunal biodiversity in tropical forests. We applied an object-based image analysis (OBIA) to classify mined areas 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. Our OBIA was able to identify mined objects with high accuracy (>90% balanced accuracy). Field plots with a higher proportion of OBIA-derived mine cover had significantly lower insect family richness. The effects of mine cover on individual insect taxa 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 advent of 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 of gold mining in remote landscapes.

Keywords: Artisanal gold mining; Guyana; PlanetScope imagery; biodiversity monitoring; insect bioindicators.

Figure 1

Map of study area. The upper right‐hand map shows the location of the study area within the Guiana Shield. The shaded green color represents forest cover across South America from MDA Systems Ltd. The color image is clipped to the Indigenous territory of Campbelltown in Guyana and represents PlanetScope imagery acquired on 19 September 2019. [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 2

Land cover classification from PlanetScope imagery. The map on the left shows the location of Landsat‐derived forest loss units (n = 21), which each include five field plots (one center plot and four plots in the cardinal directions) where presence of insect families was surveyed in January 2020. The map panels show the land cover classification in the vicinity of a cluster of field plots, including mine cover. The bottom map panel displays the original PlanetScope imagery used to develop the classification. [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 3

Landscape context of field plots. These photographs were taken in sampled field plots and illustrate range of mining‐related degradation from severely degraded mining pits (foreground, panel A), to forest regrowth on abandoned mine (panel B), to a fragment of old‐growth forest (background, panel A). Photographs by Trevor Caughlin. [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 4

Negative effect of mine cover on probability of insect family occurrence for the average insect family at an average site. The thick black line shows predicted mean response of an average insect family in an average site to mine cover. The dashed lines represent 95% credibility intervals. [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 5

Range of effects of mining cover on insect family occurrence. Effect size represents posterior draws from the random slope parameters of the binomial generalized linear mixed model. Positive effects indicate species with increased presence in sites with high mine cover. Overlap with zero indicates uncertainty in effect size estimates, while negative effects indicate decreased presence in sites with high mine cover. The 28 families represented are those with 50% CI (credibility intervals) that did not overlap zero. Dots reveal posterior medians for each insect family, while thick gray lines indicate 50% CI and thin lines indicate 95% CI. Different colored dots indicate different insect orders, as shown in the legend. [Colour figure can be viewed at wileyonlinelibrary.com]

Figure 6

Negative effect of mine cover on insect family richness. Each gray dot represents the observed level of insect family richness at a given site. The thick black line represents mean predicted effect of mine cover on insect family richness, while dashed lines represent 95% CI. [Colour figure can be viewed at wileyonlinelibrary.com]