Abstract

AbstractThermal regimes of rivers and streams profoundly affect aquatic ecosystems, but are poorly described and classified in many areas due to the limited availability of annual datasets from extensive and representative monitoring networks. By mining a new temperature database composed of >23,000 site records that spans the western United States (U.S.), we extract annual monitoring records at 578 sites on perennial streams to describe regimes in this diverse region. Records were summarized using 34 metrics that described regime aspects related to magnitude, variation, frequency, duration, and timing. The metrics were used in a multivariate cluster analysis to classify streams into seven distinct regime types and in a principal components analysis (PCA) to examine patterns of redundancy among metrics. The PCA indicated that 2–5 orthogonal PC axes accounted for 74%–89% of the variation in thermal regimes at the monitoring sites. Most of the variation in PC scores that defined the two dominant axes was in turn predictable from a suite of geospatial covariates in multiple linear regressions that included elevation, latitude, riparian canopy density, reach slope, precipitation, lake prevalence, and dam height. Our results have parallels to previous flow regime analyses that describe the utility of small numbers of PCs or allied metrics in regime characterization, and can be used to better understand and parsimoniously represent thermal regimes in the western U.S.

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