Principle components of thermal regimes in mountain river networks

Abstract

Abstract. Description of thermal regimes in flowing waters is key to understanding physical 6 processes, enhancing predictive abilities, and improving bioassessments. Spatially and temporally 7 sparse datasets, especially in logistically challenging mountain environments, have limited studies 8 on thermal regimes but inexpensive sensors coupled with crowd-sourced data collection efforts 9 provide efficient means of developing large datasets for robust analyses. Here, thermal regimes are 10 assessed using annual monitoring records spanning a five-year period (2011)(2012)(2013)(2014)(2015) at 226 sites 11 across several contiguous montane river networks in the northwestern U.S. Regimes were 12 summarized with 28 metrics and principle components analysis (PCA) was used to determine those 13 metrics which best explained thermal variation on a reduced set of orthogonal axes. Four principle 14 components (PC) accounted for 93.4% of the variation in the temperature metrics, with the first PC 15 (49% of variance) associated with metrics that represented magnitude and variability and the second 16 PC (29% of variance) associated with metrics representing the length and intensity of the winter 17 season. Another variant of PCA, T-mode analysis, was applied to daily temperature values and 18 revealed two distinct phases of spatial variance-a homogeneous phase during winter when daily 19 temperatures at all sites were < 3 °C and a heterogeneous phase throughout the year's remainder 20 when variation among sites was more pronounced. Phase transitions occurred in March and 21November, and coincided with the abatement and onset of subzero air temperatures across the study 22 area. S-mode PCA was conducted on the same matrix of daily temperature values after transposition 23 and indicated that two PCs accounted for 98% of the temporal variation among sites. The first S-24 mode PC was responsible for 96.7% of that variance and correlated with air temperature variation (r 25 = 0.92) whereas the second PC accounted for 1.3% of residual variance and was correlated with 26 discharge (r = 0.84). Thermal regimes in these mountain river networks were relatively simple and 27 responded coherently to external forcing factors, so sparse monitoring arrays and small sets of 28 summary metrics may be adequate for many aspects of their description. PCA provides a 29 computationally efficient means of extracting key information elements from large temperature 30 datasets and could be applied broadly to facilitate comparisons among more diverse stream types 31 and develop classification schemes for thermal regimes. 32 33

Life through a wider scope: Brook Trout (Salvelinus fontinalis) exhibit similar aerobic scope across a broad temperature range

“…The high heat tolerance of Brook Trout, shown by Morrison et al (2020), paired with the data from the current study show Brook Trout's ability to survive and maintain performance across a wide range of water temperatures. This wide range of temperature tolerance may prove beneficial to Brook Trout given that projected climate change scenarios for native streams in the eastern portions of Canada and the United States estimate increases in stream temperatures and major losses in suitable habitat (M. E. Clark et al, 2001;Flebbe et al, 2006;Isaak et al, 2018;Meisner, 1990;Meisner et al, 1988).…”

Modeling Seasonal Effects of River Flow on Water Temperatures in an Agriculturally Dominated California River

“…In our study streams, high flows had a strong cooling effect on stream temperatures in April-July, but less influence during other months. Multiple linear regression (MLR) models using monthly flow and air temperature at 239 Northwestern USA sites not regulated by dams (Isaak et al, 2018) and spatial stream network models for eight regions of the Western USA (FitzGerald et al, 2021) showed monthly timing and direction of flow effects on stream temperatures (Figures S9-S10) similar to our results (Figure 8b), with the exception of similar cooling in April and August whereas our models show weaker cooling in August than in April. Monthly MLR modeling in 17 sites in Canada's Frasier River Basin found flow-mediated cooling effects on summer water temperatures were stronger in July than August and weakest in September (Islam et al, 2019).…”

“…The Klamath Tribal Water Quality Consortium (Karuk Tribe, Yurok Tribe, Hoopa Valley Tribe, Quartz Valley Indian Reservation, and Resighini Rancheria) Isaak et al (2018) andFitzGerald et al (2021), respectively. WRR editors and reviewers provided comments that substantially improved this manuscript.…”

“…Violin plot (i.e., combination of box plot and density plot) of standardized coefficients for flow (Q) from multiple regression models of monthly stream temperatures at 239 river sites in the Northwestern U.S. where flow is not regulated by dams, fromIsaak et al's (2018) analysis. Within each month, horizontal lines are median values, gray points are coefficients for individual sites (jittered for legibility), and labels are the number of sites Isaak et al (2018). developed these models in the original units of m 3 /s.…”

Fourth Oregon climate assessment report. State of climate science : 2019

“…25,26 The record temperatures in 2015 were part of a long-term trend of declining low flows 27 and warming streams. 28,29 Increasing ocean temperatures and acidity also impact fish survival, species abundance, and predatorprey distribution and timing. 30 In 2015, the increased ocean temperatures were part of an ocean heat wave coined "the Blob," which fueled a coast-wide harmful algal bloom that affected commercial, recreation, and tribal subsistence fisheries (see Box 24.7) (see also Ch.…”