ABSTRACT
Monitoring wildlife populations to determine changing abundance is the basis for conservation strategies and interventions. Monitoring, however, is expensive, and we lack baseline data for countless species and landscapes around the globe. One solution is to utilize methods that leverage observations collected by everyday people. Humans are not only excellent sensors for diverse data, but possess a remarkable ability to process data and differentiate patterns with minimal training. Here, we explored the potential for people, including guides who work in tourism in southern Patagonia, to determine whether paired photographs of puma (Puma concolor puma) faces were the same individual, akin to a computer-led Siamese network analysis. Overall, participants performed well (average score of 92.2 %) and we detected no differences in local people versus those from the USA, or differences due to differential experience working with pumas. Based on these results, we built a historic capture-recapture dataset of individual pumas collected by local guides and report annual abundance for a portion of the Torres del Paine UNESCO Biosphere in southern Chile, an area lacking such data and of critical conservation for the species. Our results highlight the innate capabilities of human computers and their potential for contributing to wildlife surveys in novel ways to increase science capacity.