|Title||Big data, local science: Not an oxymoron|
|Publication Type||Conference Paper|
|Year of Publication||2020|
|Authors||Bestelmeyer B, McCord S, Webb N, Brown J, Herrick J, Peters D|
|Conference Name||Ecological Society of America|
|Conference Location||Virtual Conference|
|ARIS Log Number||378846|
Collaborative natural resource management (CNRM) projects are increasingly a common approach to link science to decision-making in rangelands, forests, and fisheries. Such approaches emphasize interactions among scientists from a variety of disciplines with stakeholders to manage adaptively. The availability of human and data resources, however, limit the initiation of CNRM projects and their benefits to stakeholders and ecosystems. We propose a “big data” framework for catalyzing and supporting CNRM projects based on standardized monitoring, open access databases, gridded spatial data products, data-model integration, and mobile applications.