Development and Application of the NorWeST
Regional Stream Temperature Model for Bull
Trout Climate Assessments and Monitoring
Dan Isaak, Seth Wenger1, Erin Peterson2, Jay Ver Hoef3 Charlie Luce,
Steve Hostetler4, Jason Dunham4, Jeff Kershner4, Brett Roper, Dave
Nagel, Dona Horan, Gwynne Chandler, Sharon Parkes, Sherry Wollrab
U.S. Forest Service
1Trout Unlimited
2CSIRO
3NOAA
4USGS
How Will Global Climate Change
Affect My Streams & Favorite Fish?
Global climate
River network
temperatures
Regional
climate
Stream
reach
General outline:
1) The Rieman et al. (2007) regional bull trout
climate assessment
2) The NorWeST regional stream temperature
database, model, and climate scenarios
3) Uses of NorWeST products for bull trout
conservation and management
4) Key uncertainties for bull trout in a warming
world
Bull Trout Climate Model:
What Are the Historical Patterns?
76 streams with longitudinal surveys
Bull trout elevation boundaries
2500
Elevation
(m)
Elevation (m)
113-114
115-116
117-118
>119
Longitude
2000
1500
1000
500
41
Juvenile Bull Trout Lower Elevation Limit
Y = 18693 - 191(latitude) + 73.6(longitude)
(R2
43
45
Latitude
47
49
Latitude
= 0.74)
1 lat = -191 m; 1 long = 73.6 m change in bull trout elevation limit
Mean Annual Air Temperature (R2 = 0.89)
Y = 67 – 0.86(latitude) + 0.12(longitude) - 0.0062(elevation)
1 lat = - 138 m; 1 long = 88 m change in isotherm elevation
Rieman et al. 2007. TAFS 136:1552-1565
Bull Trout Climate Model:
Lots of Habitat at Risk
Rieman et al. 2007. TAFS 136:1552-1565
Proportion
Remaining
Spatial Variation in Habitat Loss
1.0
0.8
+ 1.6 ˚C
0.6
0.4
0.2
0.0
1
Rieman et al. 2007. TAFS 136:1552-1565
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
3rd Code HUC Subregion
Key BioClimate Model Assumption:
Time 1
16 °C isotherm
Elevation
Elevation
Critical isotherm delimits species/population boundary…
…& boundaries will
track this isotherm
Time 2
16 °C isotherm
Existing Fish-Climate Models Are Coarse…
Based on air temperatures
PRISM Air
Map
•Meisner 1988, 1990
•Eaton & Schaller 1996
•Keleher & Rahel 1996
•Rahel et al. 1996
•Mohseni et al. 2003
•Flebbe et al. 2006
•Rieman et al. 2007
•Kennedy et al. 2008
•Williams et al. 2009
•Wenger et al. 2011
•Almodovar et al. 2011
•Etc.
Stream Temperature (˚C)
Air Temp ≠ Stream Temp
20
r² = 0.26
15
10
5
8
12
16
20
24
Wildfires
Glaciation
PRISM Air Temperature (˚C)
Groundwater
buffering
Riparian differences
Accurate Landscape Level Information
Needed to Empower Local Decision Makers
Tactical execution
Strategic
assessment
I’m going to invest here…
…instead of here
Developing a River Network Temperature
Model from Application of Spatial Statistics
to an Interagency Database
Dan Isaak, Charlie Luce, Bruce Rieman,
Dave Nagel, Erin Peterson1, Dona Horan,
Sharon Parkes, and Gwynne Chandler
Boise Aquatic Sciences Lab
U.S. Forest Service
Rocky Mountain Research Station
Boise, ID 83702
1CSIRO
Mathematical and Information Sciences
Indooroopilly, Queensland, Australia
Boise River Temperature Database
Stream Temperature Database
14 year period (1993 – 2006)
780 observations
518 unique locations
Watershed Characteristics
Elevation range 900 – 3300 m
Fish bearing streams ~2,500 km
Watershed area = 6,900 km2
Spatial Statistical Stream
Models are Dot Connectors
Valid interpolation on networks
& aggregation of datasets
Advantages:
-flexible & valid covariance structures
by accommodating network topology
-weighting by stream size
-improved predictive ability & parameter
estimates relative to non spatial models
Ver Hoef et al. 2006; Peterson & Ver Hoef 2010; Ver Hoef & Peterson 2010
Spatial Statistical Network Models Work
the Way that Streams Do…
Gradual trends within networks…
…but also changes at
tributary confluences
…& are significantly better mousetraps
SO4 level
Training on left
2007 validation on right
Data from 200
Boise River Temperature Model
19
Predicted (C°)
14
9
4
4
30
25
20
15
10
5
Parameter
estimates are
because 19
9different14
of autocorrelation
MWMT
in database
y = 0.86x + 2.43
Spatial Stream Temp =
– 0.0045*Elevation (m)
+ 0.0085*Radiation
+ 0.48*AirTemp (°C)
– 0.11*Flow (m3/s)
icted (C°) Predicted ( C)
SummerStream
Mean Temp =
Non-spatial
– 0.0064*Elevation
(m)
y = 0.93x
+ 0.830
+ 0.0104*Radiation
+ 0.39*AirTemp (°C)
– 0.17*Flow (m3/s)
Mean Summer
Temp
SummerStream
Mean
0.68x +RMSE
3.82
r2 y==0.68;
= 1.54°C
19
14
Training on left
2007 va
9
Non-spatial Model
Summer Mean
4
4
19
30
9
14
2
ry ==0.93x
0.93;
RMSE
= 0.74°C
+ 0.830
MWMT
y = 0.55x + 7.79
25
14
20
9
15
4
10
5
19
Spatial Model
4
Isaak et al. 2010. Ecol. Apps. 20:1350-1371
30
9
14
19
MWMT
Observed
( C)
River Temperature Status Map
2006 Mean Summer Temperatures
Temperature ( C)
Trend Assessment = Change in
Status Between Time 1 & Time 2
Summer Air Temperature
Summer
Air(C)
(C)
Summer Mean
Mean Air
22
20
18
Study
period
1976-2006
+0.44°C/decade
16
14
1970
1975
1980
1985
1990
1995
2000
2005
2010
Recent Wildfires
Summer Stream Flow
Summer
Discharge
Summer discharge
(m3/s)
30
14% burned during 93–06 study period
30% burned from 92-08
Study
period
25
20
15
10
5
0
1945
1946–2006
-4.8%/decade
1955
1965
1975
1985
1995
2005
Climate Change Map – Thermal Gains 93-06
Change in Summer Temperature Status
Temperature ( C)
Isaak et al. 2010. Eco. Apps. 20:1350-1371
Effects of Climate Change on
Bull Trout Habitats (1993-2006)
Decreasing at 8% - 16%/decade
Isaak et al. 2010. Eco. Apps. 20:1350-1371
Loss
No change
>45,000,000 hourly records
>15,000 unique stream sites
>60 agencies
$10,000,000
Regional Temperature Model
Accurate temperature
models
+
Cross-jurisdictional “maps”
of stream temperatures
Consistent datum for
strategic assessments
across 400,000 stream
kilometers
Example: Clearwater River Basin
Data extracted from NorWeST
16,700 stream km
•4,487 August means
•746 stream sites
•19 summers (1993-2011)
Clearwater R.
•Temperature site
Example: Clearwater River Basin
Data extracted from NorWeST
16,700 stream km
•4,487 August means
•746 stream sites
•19 summers (1993-2011)
Clearwater R.
•Temperature site
Climatic Variability in Historical Record
Extreme years include mid-21st-Century “averages”
18
Air Temp (C)
Discharge (m3/s)
60
50
16
Δ = 4°C
14
12
30
10
3x change
20
8
6
1992
40
10
1997
2002
Year
2007
2012
Discharge
Air Temperature (˚C)
20
Clearwater River Temp Model
n = 4,487
1. Elevation (m)
2. Canopy (%)
3. Stream slope (%)
4. Ave Precipitation (mm)
5. Latitude (km)
6. Lakes upstream (%)
7. Baseflow Index
8. Watershed size (km2)
Predicted ( C)
Covariate Predictors
Mean August Temperature
25
r2 = 0.95; RMSE = 0.60°C
20
15
10
Spatial Model
5
5
10
15
20
25
Observed ( C)
9. Discharge (m3/s)
USGS gage data
10. Air Temperature (˚C)
RegCM3 NCEP reanalysis
Hostetler et al. 2011
16,000 stream kilometers
Salmon River Temperature Model
Covariate Predictors
1. Elevation (m)
2. Canopy (%)
3. Stream slope (%)
4. Ave Precipitation (mm)
5. Latitude (km)
6. Lakes upstream (%)
7. Baseflow Index
8. Watershed size (km2)
Mean August Temperature
Predicted ( C)
n = 4,401
25
r2 = 0.89; RMSE = 0.86°C
20
15
10
Spatial Model
5
5
10
15
20
25
Observed ( C)
9. Discharge (m3/s)
USGS gage data
10. Air Temperature (˚C)
RegCM3 NCEP reanalysis
Hostetler et al. 2011
21,000 stream kilometers
SpoKoot River Temp Model
n = 5,482
1. Elevation (m)
2. Canopy (%)
3. Stream slope (%)
4. Ave Precipitation (mm)
5. Latitude (km)
6. Lakes upstream (%)
7. Baseflow Index
8. Watershed size (km2)
Predicted ( C)
Covariate Predictors
Mean August Temperature
25
r2 = 0.90; RMSE = 0.97°C
20
15
10
Spatial Model
5
5
10
15
20
25
Observed ( C)
9. Discharge (m3/s)
USGS gage data
10. Air Temperature (˚C)
RegCM3 NCEP reanalysis
Hostetler et al. 2011
55,000 stream kilometers
Upper Missouri River Temp Model
n = 1,145
1. Elevation (m)
2. Canopy (%)
3. Stream slope (%)
4. Ave Precipitation (mm)
5. Latitude (km)
6. Lakes upstream (%)
7. Baseflow Index
8. Watershed size (km2)
Predicted ( C)
Covariate Predictors
Mean August Temperature
25
r2 = 0.91; RMSE = 1.17°C
20
15
10
Spatial Model
5
5
10
15
20
25
Observed ( C)
9. Discharge (m3/s)
USGS gage data
10. Air Temperature (˚C)
RegCM3 NCEP reanalysis
Hostetler et al. 2011
25,000 stream kilometers
Models Enable Climate Scenario Mapping
Many possibilities exist…
Adjust…
• air temp
• discharge
• %canopy
values to
represent
scenarios
Climate Scenario Descriptions
Scenario
S1_93_11
S2_02_11
S3_1993
S4_1994
Description
Historical scenario representing 19 year average
August mean stream temperatures for 1993-2011
Historical scenario representing 10 year average
August mean stream temperatures for 2002-2011
Historical scenario representing August mean
stream temperatures for 1993
Historical scenario representing August mean
stream temperatures for 1994
Etc…
S21_2011
S22_025C
S23_050C
Etc…
S33_300C
S34_PredSE
Historical scenario representing August mean
stream temperatures for 2011
Future scenario adds 0.25˚C to S1_93-11
Future scenario adds 0.50˚C to S1_93-11
Future scenario adds 3.00˚C to S1_93-11
Standard errors of stream temperature predictions
Historical Year Sequence (1993-2011)
Mean August Temperature - Clearwater Basin
So format these consistently, then save as .emf to reduce size and embed
25
Predicted
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
Clearwater R.
1993
1994
1995
1996
1997
1998
2006
2008
2009
2011
1999
2000
2002
2003
2004
2005
2007
2010
2001
r²
r² == 0.87
0.88
0.92
0.89
0.97
0.96
0.95
0.94
0.98
0.93
20
15
10
5
0
0
5
10
15
20
25
Observed
20
Air Temp (C)
Discharge (m3/s)
18
60
50
16
Temperature ( C)
14
40
12
30
10
20
8
6
1992
10
1997
2002
2007
2012
Future Scenarios (S1, S25, S29)
1993-2011, +1.0˚C, +2.0˚C
+2.00˚C
+1.00˚C
1993-2011
Clearwater R.
Temperature ( C)
Historic Scenario: SpoKoot Unit (S1_93-11)
1993-2011 mean August stream temperatures
Kootenai R.
Bitteroot R.
1 kilometer resolution
55,000 stream kilometers
Historic Scenario: SpoKoot Unit (S1_93-11)
1993-2011 mean August stream temperatures
Kootenai R.
Scenarios are GIS
layers for easy
display & query
Bitteroot R.
1 kilometer resolution
55,000 stream kilometers
Regionally Consistent Thermal
Niche Definitions Regional fish survey
databases (n ~ 30,000)
Occurrence
probability
Stream temperature maps
Temperature (C)
Wenger et al. 2011a. PNAS 108:14175-14180
Wenger et al. 2011b. CJFAS 68:988-1008; Wenger et al., In Preparation
Thermal Niches For All Stream Critters
Just need georeferenced biological survey data
Too warm…Too cold…Just right
Bull Trout Thermal Criteria & Patches
•Dunham et al. 2003
•Selong et al. 2001
•McMahon et al. 2007
•Mesa et al. 2012
•Many others…
•Dunham et al. 2002
Range-wide bull trout vulnerability
assessment (Dunham and co.)
Computer algorithm delineates consistent
set of patches based on thermal criteria
Patching routine
Too Warm
>xoC
≤xoC
Cold Patch
1 kilometer NorWeST
predictions
Patch 1
Accurate census of
thermally suitable habitat
<xoC
>xoC
Patch 2
Simple Salmon River Example
2002-2011 Historical
11.2 ˚C isotherm
Suitable
Unsuitable
Simple Salmon River Example
+1˚C Stream Temperature
11.2 ˚C isotherm
Suitable
Unsuitable
Simple Salmon River Example
+2˚C Stream Temperature
11.2 ˚C isotherm
Suitable
Unsuitable
Spatial Variation in Habitat Loss
2002-2011 historical scenario
EFK. Salmon
White Clouds
11.2 ˚C isotherm
Spatial Variation in Habitat Loss
+1˚C stream temperature scenario
EFK. Salmon
White Clouds
11.2 ˚C isotherm
?
Difference Map Shows Vulnerable Habitats
+1˚C stream temperature scenario
11.2 ˚C isotherm
Where to invest?
Precise Information Regarding Potential
Species Invasions & Population Extirpations
1) How much time
is left on the clock?
Elevation
2) Where & how fast
could invasions occur?
Small headwater
populations may
face thermal
extirpation this
century
Precise Targeting of Assisted Migrations
& Reintroduction Efforts
This big patch doesn’t
have bull trout
Climate-Smart Strategic Prioritization
•Maintaining/restoring flow…
•Maintaining/restoring riparian…
•Restoring channel form/function…
•Prescribed burns limit wildfire risks…
•Non-native species control…
•Improve/impede fish passage…
High
Priority
Low
Priority
NorWeST is a “Crowd-Sourced” Model
Developed from Everyone’s Data
GCM
Coordinated
Management
Responses?
Management
Decisions
Data Collected by
Local Bios & Hydros
Website Distributes Scenarios &
Temperature Data as GIS Layers
1) GIS shapefiles of stream
temperature scenarios
3) Temperature data summaries
2) GIS shapefiles of stream temperature
model prediction precision
+ = Thermograph
= Prediction SE
Google “NorWeST” or go here…
http://www.fs.fed.us/rm/boise/AWAE/projects/NorWeST.shtml
The Blob is Growing…
 15,515 summers of data swallowed
 117,000 stream kilometers of
thermal ooze mapped
NorWeST Schedule
Mid
NorWeST Facilitating Related Projects
•Regional bull trout climate vulnerability
assessment (J. Dunham)
•Cutthroat & bull trout climate decision
support tools (Peterson et al., 2013)
•Landscape-scale bull trout monitoring
protocol (Isaak et al. 2009)
•Consistent thermal niche definitions &
more accurate bioclimatic models for
trout & nongame fishes (S. Wenger, In
Prep.)
•Efficient stream temperature
monitoring designs
Tip of the
Iceberg
Bull Trout Climate Decision Support Tool
Tool runs on regionally
consistent data layers
1G LCC
Downscaled Stream Scenarios
Streamflow
New monitoring sites can
be updated rapidly & new
apps rapidly scaled
Stream Temperature
Peterson et al. 2013. Fisheries 38:112-127.
VIC Streamflow Scenarios
Ecological Flow Metrics
A1B IPCC Scenarios
for the western U.S.
NHD+ stream segment resolution
Google “Stream flow Metrics”
Website: http://www.fs.fed.us/rm/boise/AWAE/projects/modeled_str
eam_flow_metrics.shtml
Wenger et al. 2010. Water Resources Research 46, W09513
Efficient Biological Monitoring
Bull trout distributional status & trend
=
Map
Accurate habitat maps
from stream models
Probabilistic sample
(i.e., EMAP GRTS)
Precise, representative sample
Proportion
Biological
survey
Optimizing Biological Monitoring:
Covariate Effects on Detection Efficiencies
Prior probabilities
of occurrence
p = 0.35
≤ 17.5 °C
> 17.5 °C
Stream MWMT
Bull trout occurrence
Habitat Suitability Curves
p = 0.20
p = 0.50
p = 0.60
Habitat size
p=
0.10
Modified false absence rates
False Absence Rate
0.5
p = 0.50
p = 0.80
0.2
0.5
0.8
0.4
Prior probability
of occurrence
0.3
0.2
0.1
0
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17
Sample
size
Sample Number
Peterson & Dunham 2003
How many claims to stake?
Regionally Consistent Framework
Bull trout status & trend monitoring
USFWS 2008; Isaak et al. 2009
Inverse
Similarity
Efficient Temperature Monitoring
Summer Stream Temperature
Redundant
information
Distance between samples (km)
Optimize Sampling
Too few…
Just
right
Too many…
Spatially Explicit Maps of Prediction
Model
Uncertainty (S34_PredSE)
Predictions
Temperature Prediction SE’s
+ = Thermograph
= SE
Salmon River
SE’s are small near sites with
temperature measurements
Block-krige Accurate Stream Temperature
Estimates at User Defined Scales
Temperature (˚C)
Bear Valley Creek
Mean Temperature
Random
Sampling
Precise & unbiased estimates
Does this reach exceed the TMDL standard?
Spatial Stream Models are Generalizable…
Distribution
& abundance
Response
Metrics
•Gaussian
•Poissan
•Binomial
Stream
Temperature
Statistical stream models
Genetic
Attributes
Water Quality
Parameters
Climate Is Happening…
Distributions are Shifting in Many Species
Average distribution shift
6.1 km/decade poleward
OR
6.1 m/decade higher elevation
Parmesan and Yohe. 2003. Nature 421:37-42.
Time 1
16 °C isotherm
Elevation
Elevation
…but how fast is it happening to fish?
Time 2
16 °C isotherm
Stream Distance
Evidence for Freshwater Fish
Populations is Weak
•Meisner 1988, 1990
•Eaton & Schaller 1996
•Keleher & Rahel 1996
•Rahel et al. 1996
•Mohseni et al. 2003
•Flebbe et al. 2006
•Rieman et al. 2007
•Kennedy et al. 2008
•Williams et al. 2009
•Wenger et al. 2011
•Almodovar et al. 2011
•Etc.
Lots of predicting,
not much validating
Distribution Shifts in French Streams
Difference in stream fish
distributions (1980’s vs 2000’s)
Survey sites
(n = 3,500)
32 species
March of the fishes…
Change in Elevation (m)
Comte & Grenouillet. 2013. Do stream fish track climate change? Assessing
distribution shifts in recent decades. Ecography doi: 10.1111/j.16000587.2013.00282.x
Distribution Shifts in Montana Bull
Trout Populations
Standardized
elevation
Probability (95%CI)
Extirpation probability (95%CI)
• Resurveyed Rich et al. 2003
Best predictors
sites 20 years later
• 77 sites, 500 m in length
• Modeled extirpations/colonizations
accounting for detection efficiency
Extirpations (15)
Fire Severity
None/low
Moderate/high
Colonizations (5)
Eby et al. In Review. Evidence of climate-induced range contractions for bull trout
Standardized
to cooler,
higher elevation sites in a Rocky Mountain watershed, U.S.A. Global
Changetemperature
Biology
More Resurveys Needed to Understand
Potential Breadth of Declines
?
?
?
?
Is the
Bitterroot
Indicative of
other Areas?
?
?
?
Additional Questions:
Elevation
Elevation
At what rate are bull trout distributions shifting?
Time 1
Average distribution shift
across taxa =
6.1 km/decade poleward OR
6.1 m/decade higher
Time 2
Stream Distance
Parmesan and Yohe. 2003.
Nature 421:37-42.
Isotherm shift rate (km/decade)
How do biological shifts relate to isotherm shifts?
Isotherm Shift Rate Curves Stream warming rate
409.6
+0.1 C/decade
+0.2 C/decade
+0.3 C/decade
+0.4 C/decade
+0.5 C/decade
204.8
102.4
51.2
25.6
(y = 1.25x-1)
(y = 2.50x-1)
(y = 3.75x-1)
(y = 5.00x-1)
(y = 6.25x-1)
12.8
6.4
3.2
1.6
0.8
0.4
Low gradient
stream
0.2
Steep
Stream
0.1
0.1
0.2
0.4
0.8
1.6
3.2
Stream slope (%)
6.4
12.8
Isaak & Rieman. 2013. Stream isotherm shifts from climate change and implications for
distributions of ectothermic organisms. Global Change Biology 19:742-751.
Bull trout occurrence
How Much Habitat is Needed to Persist?
Rieman & McIntyre 1995
Dunham and Rieman 1999
Dunham et al. 2002
Isaak et al. 2010
1
0.5
Occurrence
Watershed
area (ha)
Stream
length (km)
p > 0.5
~3,000
~13
p > 0.9
~10,000
~40
0
0
10000
20000
Habitat patch size (ha)
30000
Occupied Patch
Unoccupied Patch
What’s our Future Habitat Fudge Factor?
Larger Habitats Needed to Accommodate Larger Disturbances
Jentsch et al. 2007
How Will Climate Factors Interact?
Warmer temperatures
Reduced summer flows
Fire & debris flows
Winter flooding
Non-native invasions
The Bull Trout Vise
Where Are the “Bombproof” Habitats?
Should These Have Additional Protections to
Provide a Foundation for a Bull Trout
Reserve System?
Isaak et al. 2012. Fisheries 37: 542-556.
We’ll Soon Have The Necessary
Information but…
Invest
Here
Not
here?
Sorry Charlie
…no guarantees humans
are rational creatures
& future uncertainties will be large…
2.5 °C
By 2050
1.0 °C
0.6 °C …so far
We can’t save everything, but the
sooner (& smarter) we act, the
bigger the long-term impact
The End