Skip to main content
Dryad logo

Data for: Thermal vulnerability in a mountain stream network: Temporal, spatial, and biological data

Citation

Leathers, Kyle; Herbst, David; Safeeq, Mohammad; Ruhi, Albert (2022), Data for: Thermal vulnerability in a mountain stream network: Temporal, spatial, and biological data, Dryad, Dataset, https://doi.org/10.6078/D14D92

Abstract

As climate change continues to increase air temperature in high-altitude ecosystems, it has become critical to understand the controls and scales of aquatic habitat vulnerability to warming. Here we used a nested array of high-frequency sensors, and advances in time-series models, to examine spatiotemporal variation in thermal vulnerability in a model Sierra Nevada watershed. Stream thermal sensitivity to atmospheric warming fluctuated strongly over the year and peaked in spring and summer—when hot days threaten invertebrate communities most. The reach scale (~50 m) best captured variation in summer thermal regimes. Elevation, discharge, and conductivity were important correlates of summer water temperature across reaches, but upstream water temperature was the paramount driver—supporting that cascading warming occurs downstream in the network. Finally, we used our estimated summer thermal sensitivity and downscaled projections of summer air temperature to forecast end-of-the-century stream warming, when extreme drought years like 2020-2021 become the norm. We found that 25.5% of cold-water habitat may be lost under business-as-usual RCP 8.5 (or 7.9% under mitigated RCP 4.5). This estimated reduction suggests that 27.2% of stream macroinvertebrate biodiversity (11.9% under the mitigated scenario) will be stressed or threatened in what was previously cold‑water habitat. Our quantitative approach is transferrable to other watersheds with spatially‑replicated time series and illustrates the importance of considering variation in the vulnerability of mountain streams to warming over both space and time. This approach may inform watershed conservation efforts by helping identify, and potentially mitigate, sites and time windows of peak vulnerability.

Methods

Please see the README.md document.

Usage Notes

Please see the README.md document.

Funding

National Science Foundation, Award: 1802714