Development of a water temperature model to predict life- history expression and production of Oncorhynchus mykiss in the John Day River basin, Oregon Jeff Falke & Kris McNyset National Research Council & NOAA-Fisheries Chris Jordan NOAA-Fisheries NRCRAP

Conservation and Management Threatened Species of concern Proposed threatened Listing not warranted John Day basin Current DPS Status O. mykiss life histories Anadromous form listed Resident form not listed VSP & recovery ( McElhany et al. 2000) Population size Population growth rate Spatial structure Diversity Diversity benefits Ability to exploit habitat across scales Persist through disturbances Stay viable under long-term environmental changes Sockeye salmon (Greene et al. 2009)

Environment and Life History Expression Life history expression in O. mykiss Little genetic evidence of reproductive isolation Migration a flexible response to variable environment Growth rate & efficiency, energy allocation control decision to migrate Need for a spatially and temporally continuous temperature model Matches broad scales at which fish carry out their life histories Entire life cycle influenced by cumulative temperature effects over time Spawn timing Emergence Juvenile rearing Migrant Temperature Resident “Decision”

John Day River, OR Study Area

Water Temperature Data Large spatial extent (584 sampling sites) Long time period (1991 – 2009) Lots of data! (~1757 loggers) Mean daily water temperature (MDWT) John Day River basin

Land Surface Temperature (LST) NASA MODIS Satellite Data (NASA) Measures land surface emissivity (LST) Spatially and temporally continuous July 26, 2001

Stream Network Spatial grain – stream segment (1-10 km) DEM (30 m) & NHD (1:100k) Network – ArcGIS and FLoWs v 9.2 Reach contributing area (RCA) Catchment area Linked temperature data to RCA

Modeling Stream Temperature LST Interpolated for cloud cover  temporal interpolation Looked at time lags in daily data  none Aligned Land Surface Temperature to Mean Daily Water Temperature Water Temperature QA/QC – excluded problem sites and/or days 170 sites available in 2001 Filtered data >150 days Modeled 50 sites Photo: J. Monroe

Modeling Stream Temperature Observed data Missing data Temporal prediction

Modeling Stream Temperature LST Interpolated for cloud cover  spatially and temporally Looked at time lags  0 Aligned Land Surface Temperature to Mean Daily Water Temperature Water Temperature QA/QC – excluded problem sites and/or days Training data >150 days (50 sites) Linear model for each RCA MDWT = β 0 + β 1 (LST) Fit daily for entire year at 50 locations Photo: J. Monroe

Model Results

Photo: J. Monroe

Model Results Photo: J. McMillan

Predictions Mean daily water temperature (°C) < > 20

Predictions Mean daily water temperature (°C) < > 20

Predictions Mean daily water temperature (°C) < > 20

Discussion Potential covariates to add? Physical aspects (Static) Elevation Catchment area Gradient Benefits of continuous predictive temperature models Large-scale prediction useful for conservation and management Identify gaps in conservation efforts Map species distributions Assess human impacts Target restoration opportunities Calculate useful metrics for fish biology GSDD (Spawning timing & Emergence) Classify thermal regimes Bioenergetics Climate (Dynamic) Precipitation Runoff Snowmelt timing Photo: J. Monroe

Future Directions Stream TemperatureFood Availability Growth Potential Riverscape Bioenergetics Life-history Expression

Acknowledgments Funding Data/Analysis/Ideas Carol Volk (NWFSC), Jon Malmstedt (NWFSC) Marc Weber (EPA), Tom Kincaid (EPA) Jason Dunham (USGS), Gordon Reeves (USFS)

Photo: J. McMillan Questions?

Predictions Mean daily water temperature (°C) < > 20