The Value, Limitations, and Challenges of Employing Local Experts in Conservation Research

Evidence suggests that the involvement of local people in conservation work increases a project's chances of success. Involving citizen scientists in research, however, raises questions about data quality. As a tool to better assess potential participants for conservation projects, we developed a knowledge gradient, K, along which community members occupy different positions on the basis of their experience with and knowledge of a research subject. This gradient can be used to refine the citizen-science concept and allow researchers to differentiate between community members with expert knowledge and those with little knowledge. We propose that work would benefit from the inclusion of select local experts because it would allow researchers to harness the benefits of local involvement while maintaining or improving data quality. We used a case study from the DeHoop Nature Preserve, South Africa, in which we conducted multiple interviews, identified and employed a local expert animal tracker, evaluated the expert's knowledge, and analyzed the data collected by the expert. The expert animal tracker J.J. created his own sampling design and gathered data on mammals. He patrolled 4653 km in 214 days and recorded 4684 mammals. He worked from a central location, and his patrols formed overlapping loops; however, his data proved neither spatially nor temporally autocorrelated. The distinctive data collected by J.J. are consistent with the notion that involving local experts can produce reliable data. We developed a conceptual model to help identify the appropriate participants for a given project on the basis of research budget, knowledge or skills needed, technical literacy requirements, and scope of the project. Las evidencias sugieren que la participación de habitantes locales en el trabajo de conservación incrementa la probabilidad de éxito de unproyecto. Sin embargo, involucrar a científicos ciudadanos genera interrogantes sobre la calidad de los datos. Como una herramienta para evaluar a potenciales participantes en proyectos de conservación, desarrollamos un gradiente de conocimiento, K, en el que los miembros de la comunidad ocupan diferentes posiciones con base en su experiencia y conocimiento de un tema de investigación. Este gradiente puede ser utilizado para refinar el concepto de ciencia-ciudadana y permite que los investigadores diferencien a los miembros de la comunidad con conocimiento experto de los que tienen poco conocimiento. Proponemos que el t