CLAS Lecture Series
Winter Quarter 2015
Friday, January 9, 2015
Dr. Jose Manuel V Fragoso, Senior Scientist, Biology Department, Stanford University
Environmental monitoring helps us understand how we interact with the Earth. It also generates large amounts of funding for NGOs, government agencies, universities and the private sector. Scientists with university degrees usually do this monitoring. In the north, non-scientists also successfully contribute monitoring efforts as citizen scientists. In the tropics, rural and indigenous communities may also monitor natural resources, but usually only for their own needs; for example, the local management of wildlife and other forest products. Rarely do communities benefit financially from the funding available for monitoring and conservation on their own lands, because their local data remain unconnected to national and international information centers. When efforts are made to connect them, scientists and the broader monitoring community view data collected by “locals” as suspect. I contend that the generation of high quality data by communities is possible and desirable, that it can provide key information for national needs as well as for the communities themselves, and that communities should therefore benefit financially from national and international conservation funding (if they wish to do so). A truly participatory approach that includes professional researchers as well as local environmental monitors can help overcome these problems and generate data that is useful for all. Using three case studies from the Amazon and the Cerrado of Brazil, we describe the challenges for generating reliable data faced by indigenous people as they monitored biodiversity, hunting and other resource use on their lands. Impediments to generating high quality data included conflict between local values and data quality needs, irregular sampling efforts, data fabrication and lack of transparency and commitment by partner institutions. I discuss approaches for overcoming these common problems, including how to treat data sets to ensure their validity. Generating high quality data that meets local, national and international needs can generate incomes for indigenous and other local people, as well as ensure high quality, culturally appropriate and locally adapted management solutions.