Using large, open datasets to understand spatial and temporal patterns in lotic ecosystems: NEON case studies

Abstract

AbstractLeveraging big, open data is the next frontier in ecology. The National Ecological Observatory Network (NEON) is a network of monitoring sites collecting ecological data from across the United States. Using a case study approach, we provide examples of how NEON data can be applied to address a few big questions in aquatic ecology. First, we examined spatial patterns in stream water chemistry, to determine whether sites tend to cluster into regions based on geographic proximity. We found that this was not the case, likely because the hydrologic, geologic, and anthropogenic factors that drive heterogeneity in stream water chemistry vary across smaller spatial scales. Second, we examined temporal variability in stream water chemistry. We determined that the majority of catchments are relatively chemostatic (i.e., discharge varies by orders of magnitude more than concentrations) and that differences between catchments are likely to shift across decades due to changes in network conductivity. Third, we tested predictions of the River Continuum Concept (RCC) along a gradient from a second‐order stream to a seventh‐order river. We found that longitudinal patterns in metabolism, carbon chemistry, and macroinvertebrate community composition generally follow the patterns predicted by the RCC. NEON is only in its third year of full operations, with a planned 30‐year life. The studies presented here show the utility of NEON data, while only using a subset of the many data products that NEON produces. The massive amounts and types of data NEON generates, in conjunction with other national‐scale datasets, will allow the research community to better understand how aquatic ecosystems function and respond to drivers of long‐term change.