Agro-Ecosystem Research Results with Big Data and a Modified Scientific Method

Abstract:

Long-term studies of agro-ecosystems at the continental scale are providing an extraordinary understanding of regional environmental dynamics. The new Long-Term Agro-ecosystem Research (LTAR) network (established in 2013) has designed an explicit research program with multiple USDA experimental watersheds, ranges and forests for cross-site studies. Here, we report results from studies using a modified scientific method implemented over the past five years with long-term data from USDA experimental sites in coordination with other networks. The method provides a flexible structure to transform an idea to a hypothesis and come to conclusion with the valuable expertise and full participation of the data providers. The results offer a compelling argument for the LTAR concept of combining bottom-up site-based expertise and top-down network-wide coordination to arrive at more accurate scientific conclusions. Simply put, without site-based expertise and cross-site communication, the interpretations and conclusions of these studies would have been incomplete, if not incorrect. Further, the up-front time commitment to data processing and analytics above the time dedicated to place-based studies increased the productivity of the team and the impact of the research, unlike the common perception that cross-site research might be less efficient. In turn, this supported a non-traditional system of credit for co-authors based on publication impact with less regard for author order. The LTAR network has embraced this modified scientific method in its Shared Research Strategy and Common Experiment to address the problematic issues of data quality, co-author credit, research efficiency, and scientific impact in data intensive research. The initial success expressed here with USDA experimental sites bodes well for the LTAR and other such networks going forward.