scientific motivation of the champ project: how champ data can be used to answer fish and habitat...
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![Page 1: Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and habitat management questions Chris Jordan – NOAA-Fisheries Brice](https://reader035.vdocuments.net/reader035/viewer/2022062422/56649de45503460f94adb157/html5/thumbnails/1.jpg)
Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and
habitat management questions
Chris Jordan – NOAA-FisheriesBrice Semmens – Quantitative Consultants Inc.Carol Volk – South Fork Research Inc.
CHaMP and ISEMP staff, collaborators, and project managers
![Page 2: Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and habitat management questions Chris Jordan – NOAA-Fisheries Brice](https://reader035.vdocuments.net/reader035/viewer/2022062422/56649de45503460f94adb157/html5/thumbnails/2.jpg)
Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and
habitat management questions
Off-site mitigation strategy of the FCRPS Biological Opinion – stream habitat restoration can result in beneficial changes in salmon and steelhead populations.
![Page 3: Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and habitat management questions Chris Jordan – NOAA-Fisheries Brice](https://reader035.vdocuments.net/reader035/viewer/2022062422/56649de45503460f94adb157/html5/thumbnails/3.jpg)
How to show connection between habitat quantity and quality and freshwater survival?
•Formal, experimental manipulation of stream habitat at fish response variable scale (population or major, closed section of population).
•Mechanistic / process model to project population benefit based on per project change in habitat quality/quantity, habitat status, and fish response to habitat condition.
•Correlation of habitat quality/quantity status and fish status across gradient of actions and confounding covariates.
![Page 4: Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and habitat management questions Chris Jordan – NOAA-Fisheries Brice](https://reader035.vdocuments.net/reader035/viewer/2022062422/56649de45503460f94adb157/html5/thumbnails/4.jpg)
How to show connection between habitat quantity and quality and freshwater survival?
•Formal, experimental manipulation of stream habitat at fish response variable scale (population or major, closed section of population)
•Mechanistic / process model to project population benefit based on per project change in habitat quality/quantity, habitat status, and fish response to habitat condition.
•Correlation of habitat quality/quantity status and fish status across gradient of actions and confounding covariates.
•All need Habitat Quality and Quantity data• Indicators of habitat quality• Indicators of habitat quantity• Indicators of change
![Page 5: Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and habitat management questions Chris Jordan – NOAA-Fisheries Brice](https://reader035.vdocuments.net/reader035/viewer/2022062422/56649de45503460f94adb157/html5/thumbnails/5.jpg)
How to show connection between habitat quantity and quality and freshwater survival?
•Formal, experimental manipulation of stream habitat at fish response variable scale (population or major, closed section of population)
•Mechanistic / process model to project population benefit based on per project change in habitat quality/quantity, habitat status, and, fish response to habitat condition.
•Correlation of habitat quality/quantity status and fish status across gradient of actions and confounding covariates.
•All need Habitat Quality and Quantity data• Indicators of habitat quality• Indicators of habitat quantity• Indicators of change
![Page 6: Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and habitat management questions Chris Jordan – NOAA-Fisheries Brice](https://reader035.vdocuments.net/reader035/viewer/2022062422/56649de45503460f94adb157/html5/thumbnails/6.jpg)
Geographic
•Upper Columbia• Wenatchee/Entiat
•Mid Columbia• John Day
•Snake• Salmon
ISEMP Experimental Watersheds
Topical
•Status/Trends• Population / Habitat
•Effectiveness Monitoring• IMWs and extensive
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Bridge Creek IMW
Murderers Creek
Bear C
reek
Gab
le C
reek
TreatmentControl
10 km
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Entiat River
IMW
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Lemhi River
IMW
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123456123456123456123456123456123456123456123456123456123456123456123456123456123456
1D
1E
1F
1G
2A
2C
3A
3C
1 2 3 4 5 6
10 11
1 2 3 4 5
3D
3F
MAD
M1
M2
M3
ENTI
AT
1B/1C
1 2 3 4 5 6 7 8 9
7 8 9 10 11
6
1 2 3 4 5 6
13
1 2 3 4 5 6 7 8 9
7 8 9 10 11 12
7 8 9 10 11 12
10 11 12
14
1 2 3 4 5
13
1 2 3 4 5
14
7 8
13
0
3 4 5 6
14
7 81 2 3 4 5 6
1 2 3 4 5 6 7 8
1 2
0
0 0 0 0 0
0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0
0
0 0 0 0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0 0 0 0 0
0 0 0
0 0 0 0 0 0
0 0 0 0 0 0
0
0 0 0 0 0 0
0 0 0
0 0 0
0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
Restoration applied 1 = YAT or year after treatment
Entiat IMW Experimental Design
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How to show connection between habitat quantity and quality and freshwater survival?
•Formal, experimental manipulation of stream habitat at fish response variable scale (population or major, closed section of population)
•Mechanistic / process model to project population benefit based on per project change in habitat quality/quantity, habitat status, and, fish response to habitat condition.
•Correlation of habitat quality/quantity status and fish status across gradient of actions and confounding covariates.
•All need Habitat Quality and Quantity data• Indicators of habitat quality• Indicators of habitat quantity• Indicators of change
![Page 12: Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and habitat management questions Chris Jordan – NOAA-Fisheries Brice](https://reader035.vdocuments.net/reader035/viewer/2022062422/56649de45503460f94adb157/html5/thumbnails/12.jpg)
ISEMP Watershed Production Model
Habitat Quantity Habitat Quality
Channel Characteristics by Land Use Type: A. Relating habitat availability to capacity,
(ci) 13 and 14; B. Calibration using empirical and GIS data,
19-23; C. Hypothesis testing, 29 and 30 (cross-
sectional), 34-38 (pre/post).
Survival/Productivity by Life History Stage: A. Relating habitat quality to
survival/productivity, (pi) 15 and 16; B. Calibration using empirical estimates of
survival/productivity, 24-28; C. Hypothesis testing, 31 and 32 (cross-
sectional), 34-38 (pre/post).
Fry 1-3, (N3,t+1)
Parr 1-3, (N4,t+1)
Presmolt 1-3, (N5,t+1)
Smolt 1-3, (N6,t+2)
Egg 1-3, (N2,t)
Ocean Immature
Adult 8-10, (ot+x) 1-3, (N6,t+1)
Spawner 1-3, (N1,t)
Mature (Yes)
8-10, (ot+x)
Harvest (T)
11, (ot+x)
Survival (5-7), (Ot+x)
Mature (No)
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Pool
RiffleAvailable Habitat: 23.4 kmLWD per km: 83.7 m3 Fine Sediment: 18.3 %D50: 53.5 mm
Bohannon Creek
n = 2
Pool
Riffle
Glide
Available Habitat: 86.2 kmLWD per km: 24.7 m3 Fine Sediment: 26.6 %D50: 22.3 mm
Kenny Creek
n = 3
Pool
Glide
Riffle Available Habitat: 64.0 kmLWD per km: 70.7 m3 Fine Sediment: 34.2 %D50: 29.3 mm
Canyon Creek
n = 12
Pool
Glide
Riffle
Available Habitat: 103.0 kmLWD per km: 45.9 m3 Fine Sediment: 20.8 %D50: 44.9 mm
Big Timber
n = 11
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How to show connection between habitat quantity and quality and freshwater survival?
•Formal, experimental manipulation of stream habitat at fish response variable scale (population or major, closed section of population)
•Mechanistic / process model to project population benefit based on per project change in habitat quality/quantity, habitat status, and, fish response to habitat condition.
•Correlation of habitat quality/quantity status and fish status across gradient of actions and confounding covariates.
•All need Habitat Quality and Quantity data• Indicators of habitat quality• Indicators of habitat quantity• Indicators of change
![Page 15: Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and habitat management questions Chris Jordan – NOAA-Fisheries Brice](https://reader035.vdocuments.net/reader035/viewer/2022062422/56649de45503460f94adb157/html5/thumbnails/15.jpg)
Monitoring must detect spatial and temporal patterns in habitat quality and quantity
within and across watersheds
•Average Alkalinity•Average Conductivity•Average pH•Growth Potential•Percent Below Summer T° Threshold •Percent Above Winter T° Threshold•Velocity Heterogeneity•Embeddedness of Fastwater Cobble•Pool Frequency•Channel Complexity•Channel Score
•Residual Pool Volume•Subsurface Fines•Total Drift Biomass•Bank Angle•LWD Volume•Fish Cover•Channel Unit Volume•Channel Unit Complexity•Riffle Particle Size •Riparian Structure•Solar Input
Survey design
Within watershed patterns
Between watershed patterns
ChaMP Habitat Quality and Quantity Indicators
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Wind River GRTS Master Sample
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Wind River CHaMP Survey Design
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Monitoring must detect spatial and temporal patterns in habitat quality and quantity
within and across watersheds
•Average Alkalinity•Average Conductivity•Average pH•Growth Potential•Percent Below Summer T° Threshold •Percent Above Winter T° Threshold•Velocity Heterogeneity•Embeddedness of Fastwater Cobble•Pool Frequency•Channel Complexity•Channel Score
•Residual Pool Volume•Subsurface Fines•Total Drift Biomass•Bank Angle•LWD Volume•Fish Cover•Channel Unit Volume•Channel Unit Complexity•Riffle Particle Size •Riparian Structure•Solar Input
Survey design
Within watershed patterns
Between watershed patterns
ChaMP Habitat Quality and Quantity Indicators
![Page 19: Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and habitat management questions Chris Jordan – NOAA-Fisheries Brice](https://reader035.vdocuments.net/reader035/viewer/2022062422/56649de45503460f94adb157/html5/thumbnails/19.jpg)
Analysis of habitat monitoring data
• Used 30 habitat metrics from ISEMP monitoring program in Wenachee Sub-basin
• 25 annual panel sites, visited 2004 - 2009• Included stream morphology, riparian veg., woody debris,
fish cover, pool features, sediment features, bank stability• Transformed and normalized
• Status -- Use PERMANOVA to partition variance in multivariate habitat data
• Trends -- Fit GLMMs to evaluate evidence of trends in habitat indicators through time across hierarchies of site organization
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Ordination By Ownershipwenachee repeats
NormaliseResemblance: D1 Euclidean distance
OwnershipPrivateFederal
2D Stress: 0.18
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Ordination By Strahlerwenachee repeats
NormaliseResemblance: D1 Euclidean distance
Strahler42135
2D Stress: 0.18
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Ordination By Watershedwenachee repeats
NormaliseResemblance: D1 Euclidean distance
watershedNason/TumwaterWhite RiverIcicle/ChumstickChiwawa RiverUpper Wenatchee RiverLower Wenatchee River
2D Stress: 0.18
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Ordination By Yearwenachee repeats
NormaliseResemblance: D1 Euclidean distance
Year200420052006200720082009
2D Stress: 0.18
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PERMANOVA With StrahlerSource df SS MS Pseudo-F P(perm)Year 5 314.33 62.866 7.567 0.001Strahler 4 502.6 125.65 1.382 0.031Ownership 1 371.7 371.7 2.2457 0.023YearxStrahler 20 145.73 7.2867 0.86424 0.839YearxOwnership 5 55.241 11.048 1.0397 0.443StrahlerxOwnership 2 326.84 163.42 1.7253 0.009SiteName(StrahlerxOwnership) 18 1688.4 93.802 11.29 0.001YearxStrahlerxOwnership 9 96.773 10.753 1.272 0.098YearxSiteName(StrahlerxOwnership) 78 659.68 8.4575 1.3526 0.001Res 60 375.18 6.2529 Total 202 6060
V(Year)6%
V(Strahler)5%
S(Ownership)16%
V(StrahlerxOwnership)16%
V(SiteName)35%
V(YearxStrahlerxOwnership)2%
V(YearxSiteName)4%
V(Res)16%
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What If We Only Use CHaMP Indicators (Subset Wenachee ISEMP data)?
• Embeddedness of fast water cobble • Pool Frequency • Residual pool volume• LWD volume• Fish cover• Channel unit volume• Riffle particle size • Densiometer
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Ordination by Strahlerwenachee repeats
-6 -4 -2 0 2 4PC1
-6
-4
-2
0
2
4
PC
2
Strahler42135
FC_Total
TotalWoodVol_n_SiteLengthrAvgOfResidualPoolDepthr
AvgOfDensiometerReadingr
AvgOfStationEmbeddednessr
PercentCoarseGravelr
PoolsPerKmrSA_pools
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PERMANOVA With StrahlerSource df SS MS Pseudo-F P(perm)Year 5 141.91 28.381 15.193 0.001Strahler 4 149.63 37.409 1.708 0.018Ownership 1 38.731 38.731 0.59525 0.883YearxStrahler 20 32.347 1.6173 1.0857 0.339YearxOwnership 5 7.9161 1.5832 0.67774 0.845StrahlerxOwnership 2 137.41 68.707 3.0077 0.003SiteName(StrahlerxOwnership) 18 400.01 22.223 15.018 0.001YearxStrahlerxOwnership 9 21.308 2.3676 1.5875 0.035YearxSiteName(StrahlerxOwnership) 78 116.35 1.4917 1.1346 0.221Res 60 78.888 1.3148 Total 202 1616
V(Year)11% V(Strahler)
7%
V(StrahlerxOwnership)
36%V(SiteName)
30%
V(YearxStrahlerxOwnership)3%
V(YearxSiteName)1% V(Res)
12%
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2009: Within Site Variability (CHaMP Metrics Only)
• In 2009, all sites were surveyed multiple times (mostly 3 times) to get at observation error
wenachee repeats
NormaliseResemblance: D1 Euclidean distance
2D Stress: 0.13
V(Site)86%
V(Res)14%
Error Explained
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How Much Error Due to Surveys?
PoolFreq
PoolSA
ResidPoolVol
Embed
CoarseGravel
Densiometer
LWD
FishCover
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
SiteResid
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What About Trends?
• Consider only the CHaMP indicators
• Interested in exploring linear trends
• Account for random effects of watershed, ownership, Strahler order, and nested effects of sites within these factors
• Use maximum likelihood and General Linear Mixed Models (GLMMs)
• Evaluate model parsimony via AIC
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Fish cover• Best AIC: FC_Total~ Year + (1|ownership)+ (1|site)
Federal Private
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Large Woody Debris• Best AIC: LWD ~ (1 | Strahler) + (1 | site) + (1 | ownership)
1 2 3
4 5
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Relation to CHaMP?
• We expect reductions in observation error (residual error) associated with stream morphology when using total station to map stream features
• Demonstrates that coordinated monitoring yields a constellation of habitat data that, in concert, are powerful enough to detect differences among sites and changes though time at multiple levels of spatial organization
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Monitoring must detect spatial and temporal patterns in habitat quality and quantity
within and across watersheds
ChaMP Habitat Quality and Quantity Indicators
•Average Alkalinity•Average Conductivity•Average pH•Growth Potential•Percent Below Summer T° Threshold •Percent Above Winter T° Threshold•Velocity Heterogeneity•Embeddedness of Fastwater Cobble•Pool Frequency•Channel Complexity•Channel Score
•Residual Pool Volume•Subsurface Fines•Total Drift Biomass•Bank Angle•LWD Volume•Fish Cover•Channel Unit Volume•Channel Unit Complexity•Riffle Particle Size •Riparian Structure•Solar Input
Survey design
Within watershed patterns
Between watershed patterns
![Page 35: Scientific motivation of the CHaMP project: How CHaMP data can be used to answer fish and habitat management questions Chris Jordan – NOAA-Fisheries Brice](https://reader035.vdocuments.net/reader035/viewer/2022062422/56649de45503460f94adb157/html5/thumbnails/35.jpg)
Geomorphic & climate based watershed classification
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Human disturbance based watershed classification
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CHaMP watersheds relative to ICRB steelhead and sp/su Chinook population
CHaMP Watershed?Resemblance: D1 Euclidean distance
CHAMPyesno
2D Stress: 0.03
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Take Home Message
• To evaluate the status and trends in salmon tributary habitat across the Columbia River basin, a basin-scale, consistent monitoring approach is required.
• To evaluate the effectiveness of habitat restoration strategies in terms of fish population processes, a basin-scale, consistent monitoring approach is required.