Search for: All records

Stream metabolism, encompassing gross primary production and ecosystem respiration, reflects the fundamental energetic dynamics of freshwater ecosystems. These processes regulate the concentrations of dissolved gases like oxygen and carbon dioxide, which in turn shape aquatic food webs and ecosystem responses to stressors such as floods, drought, and nutrient loading. Historically difficult to quantify, stream metabolism is now measurable at high temporal resolution thanks to advances in sensor technology and modeling. The StreamPULSE dataset includes high-frequency sensor data, metadata, and modeled estimates of ecosystem metabolism. This living dataset contributes to a growing body of open-access data characterizing the metabolic pulse of stream ecosystems worldwide. To contribute to StreamPULSE, visit data.streampulse.org. All data contributed to StreamPULSE become public after an optional embargo period. Use this publication to access annual data releases, or use data.streampulse.org to download new data as they become available. 

Abstract Freshwater salinization of rivers is occurring across the globe because of nonpoint source loading of salts from anthropogenic activities such as agriculture, urbanization, and resource extraction that accelerate weathering and release salts. Multidecadal trends in river salinity are well characterized, yet our understanding of annual regimes of salinity in rivers draining diverse central and western U.S. landscapes and their associated catchment attributes is limited. We classified annual salinity regimes in 242 stream locations through dynamic time warping and fuzzy c‐medoids clustering of salinity time series. We found two dominant regimes in salinity characterized by an annualsummer–fall peakorspring decline. Using random forest regression, we found that precipitation amount, stream slope, and soil salinity were the most important predictors of salinity regime classification. Advancing our understanding of salinity regimes in rivers will improve our ability to predict and mitigate the effects of salinization in freshwater ecosystems through management interventions. 

Abstract High‐resolution data are improving our ability to resolve temporal patterns and controls on river productivity, but we still know little about the emergent patterns of primary production at river‐network scales. Here, we estimate daily and annual river‐network gross primary production (GPP) by applying characteristic temporal patterns of GPP (i.e., regimes) representing distinct river functional types to simulated river networks. A defined envelope of possible productivity regimes emerges at the network‐scale, but the amount and timing of network GPP can vary widely within this range depending on watershed size, productivity in larger rivers, and reach‐scale variation in light within headwater streams. Larger rivers become more influential on network‐scale GPP as watershed size increases, but small streams with relatively low productivity disproportionately influence network GPP due to their large collective surface area. Our initial predictions of network‐scale productivity provide mechanistic understanding of the factors that shape aquatic ecosystem function at broad scales.