Sensemaking in the Wild: A Review of Practitioner Collected Geospatial Data and its Synthesis within Protected Areas for Poaching Mitigation

A key challenge for mitigating poaching within protected areas is to understand the geospatial data that are collected by practitioners in protected areas and to characterize the ability to synthesize those data with landscape-level data to form a holistic picture of the movement patterns of humans and animals. Literature reviewed from the past 15 years on geospatial data collected by practitioners to mitigate wildlife poaching reveals a gap in our knowledge on how protected area practitioners make sense of geospatial data that are collected within protected areas. Geospatial data collected within protected areas provide an understanding of movement patterns of humans and animals, which can provide insight on best practices for poaching mitigation, to include where to emplace new geospatial sensors. We classify these data as device-based and human-generated, and their potential to provide geospatially referenced information that forms patterns of poaching activity. This article examines two primary types of geospatial data collected in protected areas, highlights the challenges associated with this data, and discusses knowledge gaps regarding how protected areas make sense of spatial data. We conclude with recommendations for future research on characterizing how geospatial data is represented in protected areas, and filling knowledge gaps on how protected area personnel use those data.