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Mountain streams provide important habitats for many species, but their faunas are especially vulnerable to climate change because of ectothermic physiologies and movements that are constrained to linear networks that are easily fragmented. Effectively conserving biodiversity in these systems requires accurate downscaling of climatic trends to local habitat conditions, but downscaling is difficult in complex terrains given diverse microclimates and mediation of stream heat budgets by local conditions. We compiled a stream temperature database (n = 780) for a 2500-km river network in central Idaho to assess possible trends in summer temperatures and thermal habitat for two native salmonid species from 1993 to 2006....
Abstract The distribution and future fate of ectothermic organisms in a warming world will be dictated by thermalscapes across landscapes. That is particularly true for stream fishes and cold-water species like trout, salmon, and char that are already constrained to high elevations and latitudes. The extreme climates in those environments also preclude invasions by most non-native species, so identifying especially cold habitats capable of absorbing future climate change while still supporting native populations would highlight important refugia. By coupling crowd-sourced biological datasets with high-resolution stream temperature scenarios, we delineate network refugia across >250 000 stream km in the Northern...
Abstract (from http://onlinelibrary.wiley.com/doi/10.1111/jawr.12179/abstract): Freshwater mussels (order Unionida) are a highly imperiled group of organisms that are at risk from rising stream temperatures ( T ). There is a need to understand the potential effects of land use (LU) and climate change (CC) on stream T and have a measure of uncertainty. We used available downscaled climate projections and LU change simulations to simulate the potential effects on average daily stream T from 2020 to 2060. Monte Carlo simulations were run, and a novel technique to analyze results was used to assess changes in hydrologic and stream T response. Simulations of daily mean T were used as input to our stochastic...
Abstract (from http://onlinelibrary.wiley.com/doi/10.1111/jawr.12178/abstract): We developed a stochastic hourly stream temperature model (SHSTM) to estimate probability of exceeding given threshold temperature ( T ) for specified durations (24 and 96 h) to assess potential impacts on freshwater mussels in the upper Tar River, North Carolina. Simulated daily mean stream T from climate change (CC) and land-use (LU) change simulations for 2021-2030 and 2051-2060 were used as input to the SHSTM. Stream T observations in 2010 revealed only two sites with T above 30°C for >24 h and T s were never >31°C for more than 24 h at any site. The SHSTM suggests that the probability, P , that T will exceed 32°C for...
Abstract (from http://scholarworks.umass.edu/cee_ewre/72/): In the Northeast U.S. increasing stream temperatures due to climate change pose a serious threat to cool and cold water fish communities, as well as aquatic ecosystems as a whole. In this study, three stream temperature models were implemented for two different case-study basins in the Northeast Climate Science Center region. Two coupled hydrology-stream temperature (physical) models were used: VIC-RBM and SWAT-Ficklin et al. (2012). The third model implemented was a nonlinear regression (statistical) model developed by Mohseni et al. (1998). Metrics were developed to assess these models regarding their prediction skill, data input requirements, spatial...
Abstract: We measured stream temperature continuously during the 2011 summer run-off season (May through October) in nine watersheds of Southeast Alaska that provide spawning habitat for Pacific salmon. The nine watersheds have glacier coverage ranging from 0% to 63%. Our goal was to determine how air temperature and watershed land cover, particularly glacier coverage, influence stream temperature across the seasonal glacial meltwater hydrograph. Multiple linear regression models identified mean watershed elevation (related to glacier extent) and watershed lake coverage (%) as the strongest landscape controls on mean monthly stream temperature, with the weakest (May) and strongest (July) models explaining 86% and...
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Existing stream temperature data will be compiled from numerous federal, state, tribal, and private sources to develop an integrated regional database. Spatial statistical models for river networks will be applied to these data to develop an accurate model that predicts stream temperature for all fish-bearing streams in the US portion of the NPLCC. Differences between model outputs for historic and future climate scenarios will be used to assess spatial variation in the vulnerability of sensitive fish species across the NPLCC.
ABSTRACTWater temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE D 0:59 °C), identified a clear warming trend (0.63 °C...
    map background search result map search result map The cold-water climate shield: delineating refugia for preserving salmonid fishes through the 21st century - Publication The cold-water climate shield: delineating refugia for preserving salmonid fishes through the 21st century - Publication