Remote sensing of artisanal and small-scale mining: A review of scalable mapping approaches.

Artisanal and small-scale mining (ASM) significantly influences the socio-economic development of many low-to-middle-income countries, albeit sometimes at the expense of environmental and human health. Characterized by its labor-intensive extraction from confined (<5 ha) or peripheral mineral reserves, congregated ASM practices can rival the spatial footprint of industrial mines. The unregulated and informal nature of many ASM activities presents monitoring challenges that remote sensing (RS) methods aim to address. While local-scale ASM mapping has seen success, scaling these methods to regional or global levels remains unclear. We review literature on mapping ASM to determine: (1) if studies represent the global distribution and diversity of ASM activities, (2) how ASM's unique characteristics influence the choice of RS methods, and (3) which RS approaches are the most accurate and cost-effective. We found current studies disproportionately focused on ASM regions in Africa, which highlights the need to extend the research to other regions with unique ASM characteristics, such as coal and sand mining in India and China. The selection of RS approaches is heavily influenced by local ASM contexts, the scale of analysis, and resource constraints such as funding for high-resolution imagery and validation data availability. We argue that accurate regional-scale ASM mapping (>100,000 km2) requires innovative combinations of data and methods to overcome data management and storage challenges. Local community participation, including miners, is vital for on-ground mapping and monitoring capacity. We outline a research agenda needed to develop a range of approaches for mapping and monitoring ASM in under-studied regions. By synthesizing effective methods, we provide a foundation for generating accurate and comprehensive spatial data, addressing the issues of inaccurate and incomplete data that global ASM platforms aim to resolve. This spatial data can guide policymakers, NGOs, and businesses in making informed decisions and targeted interventions to improve ASM sector safety, sustainability, and efficiency. Leveraging cloud-based geoprocessing platforms, with regularly updated global satellite image archives, combined with crowd-sourced on-ground information offers a potential solution for sustained regional-scale monitoring.

CamTrapAsia: A dataset of tropical forest vertebrate communities from 239 camera trapping studies.

Information on tropical Asian vertebrates has traditionally been sparse, particularly when it comes to cryptic species inhabiting the dense forests of the region. Vertebrate populations are declining globally due to land-use change and hunting, the latter frequently referred as "defaunation." This is especially true in tropical Asia where there is extensive land-use change and high human densities. Robust monitoring requires that large volumes of vertebrate population data be made available for use by the scientific and applied communities. Camera traps have emerged as an effective, non-invasive, widespread, and common approach to surveying vertebrates in their natural habitats. However, camera-derived datasets remain scattered across a wide array of sources, including published scientific literature, gray literature, and unpublished works, making it challenging for researchers to harness the full potential of cameras for ecology, conservation, and management. In response, we collated and standardized observations from 239 camera trap studies conducted in tropical Asia. There were 278,260 independent records of 371 distinct species, comprising 232 mammals, 132 birds, and seven reptiles. The total trapping effort accumulated in this data paper consisted of 876,606 trap nights, distributed among Indonesia, Singapore, Malaysia, Bhutan, Thailand, Myanmar, Cambodia, Laos, Vietnam, Nepal, and far eastern India. The relatively standardized deployment methods in the region provide a consistent, reliable, and rich count data set relative to other large-scale pressence-only data sets, such as the Global Biodiversity Information Facility (GBIF) or citizen science repositories (e.g., iNaturalist), and is thus most similar to eBird. To facilitate the use of these data, we also provide mammalian species trait information and 13 environmental covariates calculated at three spatial scales around the camera survey centroids (within 10-, 20-, and 30-km buffers). We will update the dataset to include broader coverage of temperate Asia and add newer surveys and covariates as they become available. This dataset unlocks immense opportunities for single-species ecological or conservation studies as well as applied ecology, community ecology, and macroecology investigations. The data are fully available to the public for utilization and research. Please cite this data paper when utilizing the data.

The ecology of the banded civet (Hemigalus derbyanus) in Southeast Asia with implications for mesopredator release, zoonotic diseases, and conservation.

Habitat loss and degradation threaten forest specialist wildlife species, but some generalist mesopredators exploit disturbed areas and human-derived food, which brings them into closer contact with humans. Mesopredator release is also important for human health for known zoonotic disease reservoirs, such as Asian civets (Viverridae family), since this group includes the intermediator species for the SARS-CoV-1 outbreak. Here we use camera trapping to evaluate the habitat associations of the widespread banded civet (Hemigalus derbyanus) across its range in Southeast Asia. At the regional scale, banded civet detections among published studies were positively associated with forest cover and negatively associated with human population. At the local scale (within a landscape), hierarchical modeling of new camera trapping showed that abundance was negatively associated with forest loss and positively associated with distance to rivers. These results do not support mesopredator release and suggest a low likelihood overlap with humans in degraded habitats and, therefore, a low risk of zoonotic disease transmission from this species in the wild. We also estimate that banded civet distribution has contracted to under 21% of its currently recognized IUCN Red List range, only 12% of which falls within protected areas, and a precipitous recent decline in population size. Accordingly, we suggest the banded civet's Red List status should be re-evaluated in light of our findings.

Common palm civets Paradoxurus hermaphroditus are positively associated with humans and forest degradation with implications for seed dispersal and zoonotic diseases.

Habitat loss and degradation can undermine wildlife communities and ecosystem functioning. However, certain generalist wildlife species like mesopredators and omnivores can exploit these disturbed habitats, sometimes leading to population increases (e.g. 'mesopredator release' in degraded areas). Although mesopredator release may cause negative effects on food webs and zoonotic disease management, some disturbance-tolerant species may help perpetuate important ecological interactions, such as seed dispersal. We evaluated the habitat associations of common palm civets Paradoxurus hermaphroditus, which are widespread generalist mesopredators in Southeast Asia. Common palm civets are also high-quality seed dispersers, and potential zoonotic disease hosts. We used published and new camera trapping data to map their probability of presence across Southeast Asia and evaluate regional-scale associations between capture rates and habitat variables such as elevation, ecoregion intactness and Human Footprint Index, among others. We also assessed the influence of habitat variables on their relative abundance at the local scale. At the regional scale, we found that common palm civets showed significant positive associations with landscapes characterized by lower ecoregion intactness, higher Human Footprint Index and lower elevations. At the local scale, their relative abundance showed a significant positive association with higher Human Footprint Index, but only to a certain point, after which it started decreasing. They also favoured lower elevations at the local scale. These multi-scale results indicate that common palm civets' abundance can increase under certain levels of human disturbances, consistent with the 'mesopredator release' hypothesis. This suggests they may be crucial seed dispersers in degraded forest landscapes, especially where more sensitive seed dispersers have disappeared. Our results are also consistent with previous studies reporting that habitat degradation increases populations of potential zoonotic disease hosts, and thus risks of transmission to humans.