An oak tree conundrum: Field research versus big data in the history of American ecology

Background/Question/Methods

In a 2011 presentation at the American Society for Environmental History annual meetings, ecologist James Collins made the claim that ecologists of the near future would know an oak tree not through field research but rather through analysis of massive, freely available data sets. In short, a graduate student in ecology could do all her research and analysis without ever going into the field or the lab. This provocative statement did not portend some distant future; it came in the context of discussing the history of a new National Science Foundation (NSF) program called the National Ecological Observation Network (NEON). NEON has brought many tensions in American ecology into sharp collision as ecologists vie for limited financial resources and debate the future trajectories of their science. Yet ecology is certainly not the first science to experience this rough transition to becoming a Big Data science; an analysis of other sciences that have transitioned to Big Data reveals more about what a Big Data ecology may look like.

Results/Conclusions

First I will argue that he history of American ecology since the late-19th century reveals a strong tension between place-based research and desires to model ecosystems at a global level through centrally-organized, large-scale data collection efforts.

I will then link the history of ecology in the United States to the current conflict between two NSF-funded “big ecology” projects – the Long Term Ecological Research Network (LTER) and NEON.

Finally, I will place this current conflict in ecology into the context of other sciences that have made the transition to Big Data analysis, offering some insights into how this transition might open a space for both LTER-style and NEON-style ecological research.