Comparing headwater stream thermal sensitivity across two distinct regions in Northern California

Abstract

Thermal regimes in headwater streams are critical for freshwater ecological condition and habitat resilience to disturbance, and to inform sustainable forest management. However, stream temperatures vary depending on characteristics of the stream, catchment, or region. To improve our knowledge of stream thermal regimes, we collected stream and air temperature data along eight headwater streams in two regions in Northern California. Five streams were in the Coast Range, which is characterized by permeable sandstone lithology, rain dominated precipitation regime, and dense coast redwood forests. Three streams were in the Cascade Range, which is characterized by fractured and resistant basalt lithology, snow dominated precipitation, and low to moderate density pine forests. We instrumented each stream with 12 stream temperature and four air temperature sensors during summer 2018. We compared stream thermal regimes and thermal sensitivity—slope of the linear regression between daily stream and air temperature—within and between study regions. Mean daily stream temperatures were ~4.7°C warmer in the Coast Range but were less variable (SD = 0.7°C) compared to the Cascade Range (SD = 2.3°C). Median thermal sensitivity was 0.33°C °C−1 in the Coast Range and 0.23°C °C−1 in the Cascade Range. We posit that the volcanic lithology underlying the Cascade streams likely supported discrete groundwater discharge locations of cold snowmelt water, which dampened thermal sensitivity. At locations of apparent groundwater discharge in these streams, median stream temperatures rapidly decreased by 2.0–7.0°C relative to locations 70–90 m upstream. In contrast, thin friable soils in the Coast Range likely contributed warmer, rain dominated baseflow from shallow subsurface sources, which strongly co‐varied with air temperature and generally warmed downstream (up to 2.1°C km−1). Our study revealed distinct longitudinal thermal regimes in streams with contrasting lithology, precipitation regimes, and stand densities suggesting that streams in these different regions may respond differentially to forest disturbances or climate change.

Dynamic, downstream‐propagating thermal vulnerability in a mountain stream network: Implications for biodiversity in the face of climate change

“…This relationship is further supported by H‐2 having the lowest maximum water temperature and the lowest conductivity. Similar to our study, Wissler et al (2022) found that in the Cascade Range (North of the Sierra Nevada) thermal regimes were heavily influenced by groundwater and potentially snowmelt. Wissler et al (2022) also found that the rain‐dominated Coast Range had warmer water temperatures despite cooler air temperatures and more riparian cover, possibly because of reduced groundwater influence.…”

“…Similar to our study, Wissler et al (2022) found that in the Cascade Range (North of the Sierra Nevada) thermal regimes were heavily influenced by groundwater and potentially snowmelt. Wissler et al (2022) also found that the rain‐dominated Coast Range had warmer water temperatures despite cooler air temperatures and more riparian cover, possibly because of reduced groundwater influence. The observed negative relationship between discharge and maximum temperature supports the notion that reduced thermal buffering in smaller streams could leave some headwaters especially vulnerable to climate‐change induced low flows.…”

The heat is on: Predicting urban stream temperature responses to summer storms

“…It thus remains to be seen whether such patterns would hold at broad scales, which would require a comparison of a substantially larger number of sites than the six investigated here. While other studies have investigated how site characteristics, such as shading, stream width, and drainage area, are related to temperature changes (Nelson & Palmer, 2007; Somers et al, 2013; Wissler et al, 2022; Zahn et al, 2021), our study uniquely links these behaviours to event characteristics and identified hydrograph metrics (e.g., , ) as important predictors for the temperature patterns (Figures 3 and 4).…”

Stabilising effects of karstic groundwater on stream fish communities

“…We estimated the thermal sensitivity for each site from the linear regression slope of the daily mean air‐water temperature relationship (Kelleher et al, 2012; Snyder et al, 2015; Wissler et al, 2022). Air temperature data were collected from a geographically centralised weather station (Eastern West Virginia Regional Airport, GHCND:USW00013734) and adjusted to expected air temperatures for each site based on a lapse rate of 9.8°C per km of elevation change (Stull, 1988).…”

“…We estimated the thermal sensitivity for each site from the linear regression slope of the daily mean air-water temperature relationship (Kelleher et al, 2012;Snyder et al, 2015;Wissler et al, 2022).…”