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Incorporating Thermal Heterogeneity into Climate Vulnerability Assessments for Coastal Pacific Rivers
Aimee Fullerton, Se-Yeun Lee,C. Torgersen, and J. Lawler
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Thermal regimes vary dramatically over time and those temporal signals vary over space
Steel et al. 2017
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• Land use activities
• Climate change
Humans have altered riverine thermal landscapes
°C
1940 to 2010
July water temperature
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Tem
pera
ture
J F M A M J J A S O N D
Salmon are affected by water temperature in each life stage
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At broad spatial scales, water temperature influences species distributions
D. Isaak, US Forest Service
At fine spatial scales, water temperature influences growth, survival and connectivity among essential habitats
R. Faux, Quantum Spatial
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Consequences of thermal stress
• Adults:• Decreased fitness• Straying or delay• Prespawn mortality
• Juveniles/smolts:• Altered growth rates• Altered ecological interactions
• Both:• Susceptibility to disease• Shifts in phenology
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Keefer et al. 2015
Salmon can seek cooler water
Adult steelhead use cold tributaries during upstream migration
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Juveniles also thermoregulate
Photo: J. Ebersole, USEPA
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Managing for coldwater habitats
• Primer for locating existing and potential cold water refuges
• Need to consider how coldwater habitat may change in the future
• Ultimate goal is to understand and manage “sufficient” coldwater habitat for salmonids
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Objectives
1. Characterize thermal heterogeneity (“patchiness”) in rivers
2. Assess potential future thermal heterogeneity
3. Illustrate salmon vulnerability to loss of cold patches
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Larger rivers, summer
afternoons
Snoqualmie
Siletz
Airborne thermal infrared (TIR)
surveys of rivers
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Thermal patterns at different
spatial scales
SpacingLength
Δ Temp.
Distance upstream (km)
Reach
Localized inputs
Channel unit
Profile shape
Distance upstream (km)
Wa
ter t
emp
era
ture
(C)
Segment
Networkrange
diversity
migration
refuge
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Distance upstream (km)
Wa
ter t
emp
era
ture
(ºC
)
>20 °C15-20 °C<15 °C
cool patches
too hot
Within-river thermal heterogeneity
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downstream upstream
• Lots of warm habitat, but also a huge amount of thermal diversity among and within rivers
• Many small cool patches distributed throughout warmer habitat, mostly in upstream reaches
• Cool patches generally large enough and within swimming distance for salmon in many (but not all!) rivers
>20 °C 15-20 °C <15 °C
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Resolution (km)
raw data
3-km
1-km
Patch density
Patch length
Patch spacing
What if we don’t have spatially continuous data?
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There may also be relative refuges
Distance upstream (km)
Wat
er te
mpe
ratu
re (º
C)
10-km moving average
Warmer than average
Cooler than average
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cooling reach (100-m)
warming reach
Localized cooling/warming trends
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s1s2
s3
c1
Tail-up
Spatial Stream Network Model
Ver Hoef and Peterson 2010
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Wat
er te
mpe
ratu
re (º
C)
WA OR CA
Distance upstream (km)
Observed (remotely sensed)
Predicted (NorWeST)
Example long profile comparisons
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Snoqualmie
Siletz
10 km
10 km
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Snoqualmie
Siletz
Remotely-sensed(TIR)
NorWeST
10 km
10 km
cool patches (<15 ºC)
downstream-most patch
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Objectives
1. Characterize thermal heterogeneity in rivers
2. Assess potential future thermal heterogeneity
3. Illustrate salmon vulnerability to loss of cold patches
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How might climate change alter results?
salmonguy.org
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3 Methods
1. Simple Shift
2. Random forest models (statistical)
3. DHSVM-RBM (process-based model)
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Method 1: Simple Shift.Warm year patterns resemble cool year patterns
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<15 ºC
15-20 ºC
>20 ºC
TIR + 2 ºC Change
becomes >15 ºC
becomes >20 ºC
Simple shift
Remotely-sensed (TIR)
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Simple Shift
• More warm habitat, less cool habitat
• Some warm patches will get much larger as small intervening cool patches disappear
• Correspondingly, the distance between cool patches will increase for some rivers
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Simple Shift
Wat
er te
mpe
ratu
re (º
C)
Distance upstream (km)
TIR + 2 ºC
Snoqualmie
Siletz
>20 °C, stressful15-20 °C, tolerable<15 °C, optimal
Remotely-sensed (TIR)
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Simple Shift
10 km
10 km
Snoqualmie
Siletz
TIR + 2 ºCcool patches (<15 ºC)
downstream-most patchRemotely-sensed
(TIR)
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Δ Air temperature 2080s, rcp 8.5
Δ Probability of precipitation as snow 2060s, rcp 8.5
Δ Precipitation2080s, rcp 8.5
Method 2: Statistical modelingWe know climate varies spatially, so
incorporate expected climate predictions
Random forest
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1. Fit trend: WT~ climate variables
residuals
trend
3. Sum:
resid-uals
future trend
future heterogeneity
2. Predict future trend
Δ max air tempΔ mn ann pptΔ snow prob
Random forest
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Historical 2080s
Random forest
• Fewer patches 15-20 °C
• More variance in warm patch size (some become very large)
• Similar spacing(overall)
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>20 °C 15-20 °C <15 °C
downstream upstream
19992080s
20012080s
Random forest
Less cool habitat in the 2080sLocations of cool patches shift
Tualatin River; 121 km
Chiwawa River; 53 km
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(Source: Sun et al. 2015)
Water Temperature Model (RBM)
Hydrology Model(DHSVM)
Explicit representation of topography & vegetation Physically consistent picture of flow & temperature Resolution: 150 m and 3 hour time step
Method 3:Process-based model, DHSVM-RBM
DHSVM-RBM
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Calibration for the Siletz River
Historical SimulationObservation DHSVM-RBM
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Calibration for the Snoqualmie River
Historical SimulationObservation DHSVM-RBM
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Changes in Spatial Water Temp Patternfor the Siletz River
Future Patterns(2080s, RCP 8.5)
Historical Patterns
DHSVM-RBM
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Changes in Spatial Water Temp Patternfor the Siletz River
Future Patterns(the 2080s RCP 8.5)
Historical Patterns
DHSVM-RBM
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Historical Patterns
Changes in Spatial Water Temp Patternfor the Snoqualmie River
DHSVM-RBM
Future Patterns(the 2080s, RCP 8.5)
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Historical Simulation (1990s)2080s, RCP 8.5
Siletz River, OR Snoqualmie, WA
Changes in Streamflow
DHSVM-RBM
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Changes in coldwater patches
Siletz Snoqualmie
>20 °C, stressful15-20 °C, tolerable<15 °C, optimal
Historical
2080s, RCP 8.5
DHSVM-RBM
Wat
er te
mpe
ratu
re (º
C)
Distance upstream (km)
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Sim
ple
Shift
Rand
om F
ores
tDH
SVM
-RBM
Siletz Snoqualmie
Historical Simulation2080s, RCP 8.5
Changes in water temperaturepredicted by 3 different approaches
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Objectives
1. Characterize thermal heterogeneity in rivers
2. Assess potential future thermal heterogeneity
3. Illustrate salmon vulnerability to loss of cold patches
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• Many salmonids• TMDLs in development
Maximum water temperatureAugust 2001
Siletz River
Application: Cold-water Habitat Vulnerability Assessment
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Cold water patches, 2001 Cold water patches, 2080s
10 kmcool patches (<15 ºC)
downstream-most patch
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summer steelheadJan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Upstream migrationAdults hold
SpawnEggs incubate & fry emerge
Juveniles rearSmolts outmigrate
Assess spatial and temporal distribution of life stages by species
spawning & rearingrearing & migration
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Vulnerability (cold patch assessment)Species Current Future
Fall Chinook-adults 2.0 2.5-juveniles 2.2 2.7
Spring Chinook-adults 1.9 2.3-juveniles 1.7 2.1
Summer Steelhead-adults 4.2 4.2-juveniles 1.8 1.8
Winter Steelhead-adults 0 0-juveniles 1.8 2.3
Coho-adults 3.7 4.7-juveniles 1.9 2.3
Chum-adults 0 0-juveniles 0 0
V = SES = sensitivity (level of impairment at
water temperature)E = exposure; see below(and adaptability; not included)
p = life stage presence during Augustu = use of habitat during Augustn = cold patch abundance scores = cold patch spacing score
E = p(u + n + s)
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Takeaways• Stream temperature is diverse across
space and over time
• Spatiotemporal patterns in water temperature have biological and ecological consequences
• Many recent advances in data and tools predict how climate change may alter thermal landscapes and affect biota
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Management Applications
• Water temperature regulations (i.e., the TMDL planning process)
• 5-year status reviews and recovery plans for ESA-listed salmon and steelhead
• Prioritizing riparian and habitat restoration
• Climate-ready adaptation planning
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1. PLAN• Characterize historical distribution of suitable
habitats (a baseline for targeting restoration)• Evaluate the sufficiency of habitats for supporting
salmon migration and rearing• Identify impaired locations and time windows• Consider expectations given climate change
2. ACT• Prioritize actions according to threat/risk level• Implement conservation activities• Monitor and evaluate effectiveness and
biological response
What can we do to conserve thermal diversity in streams?
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Thanks to:
and to:
Emily AlfredJoe Ebersole
Russ FauxDan Miller
Ashley Steel
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Additional Resources• EPA Columbia River Cold Water Refuges Project
https://www.epa.gov/columbiariver/columbia-river-cold-water-refuges
• NW Power Planning Council Presentation https://www.nwcouncil.org/news/blog/cold-water-habitat-april-2017/
• EPA Primer for Identifying Cold Water Refuges https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=243611
Fullerton, A.H., C.E. Torgersen, J.J. Lawler, J.L. Ebersole, and S.Y. Lee. In Press. Longitudinal thermal heterogeneity in rivers and refugia for coldwater species: Effects of scale and climate change. Aquatic Sciences.
Fullerton, A.H. C.E. Torgersen, J.J. Lawler, R.N. Faux, E.A. Steel, T.J. Beechie, J.L. Ebersole, and S.G. Leibowitz. 2015. Rethinking the longitudinal stream temperature paradigm: region-wide comparison of thermal infrared imagery reveals unexpected complexity of river temperatures. Hydrological Processes 29:4719-4737.
Steel, E.A., T.J. Beechie, C.E. Torgersen, and A.H. Fullerton. 2017. Envisioning, quantifying, and managing thermal regimes on river networks. BioScience 67:506-522.
Isaak, D.J. et al. 2017. The NorWeST summer stream temperature model and scenarios for the western US: a crowd-sourced database and new geospatial tools foster a user community and predict broad climate warming of rivers and streams. Water Resources Research. DOI 10.1002/201WR020969.
Sun, N., J. Yearsley, N. Voisin, and D. P. Lettenmaier. 2015. A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds. Hydrological Processes 29:2331-2345.
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53
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10 km
steelheadJan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Upstream migration (summer)migration (winter)
SpawnEggs incubate & fry emerge
Juveniles rearSmolts outmigrate
Estuary
Cold water patches, 2006 Cold water patches, 2080s
Species Current FutureChinook
-adults 2.7 2.8-juveniles 2.5 2.5
Steelhead-adults 5.5 5.5-juveniles 3.0 3.0
Coho-adults 4.9 4.5-juveniles 2.5 2.5
Pink-adults 5.5 5.5-juveniles 0 0
Chum-adults 0 0-juveniles 0 0