Central tendency statistics may not capture relevant or desired characteristics about the variability of continuous phenomena and thus, they may not completely track temporal patterns of change. Here, we present two methodological approaches to identify long-term changes in environmental regimes. First, we use higher statistical moments (skewness and kurtosis) to examine potential changes of empirical distributions at decadal scale. Second, we adapt an outlier detection procedure combining a

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... -metric multidimensional scaling technique and higher density region plots to detect anomalous years. We illustrate the use of these approaches by examining long-term stream temperature data from minimally and highly human-influenced streams. In particular, we contrast predictions about thermal regime responses to changing climates and human-related water uses. Using these methods, we effectively diagnose years with unusual thermal variability, patterns in variability through time, and spatial variability linked to regional and local factors that influence stream temperature. Our findings highlight the complexity of responses of thermal regimes of streams and reveal a differentiated vulnerability to both the climate warming and human-related water uses. The two approaches presented here can be applied with a variety of other continuous phenomena to address historical changes, extreme events, and their associated ecological responses.