Chris Jordan – NOAA-Fisheries Brice Semmens – Quantitative Consultants Inc.

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

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.

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.

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

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

Geographic

•Upper Columbia• Wenatchee/Entiat

•Mid Columbia• John Day

•Snake• Salmon

ISEMP Experimental Watersheds

Topical

•Status/Trends• Population / Habitat

•Effectiveness Monitoring• IMWs and extensive

Bridge Creek IMW

Murderers Creek

Bear C

reek

Gable

Creek

TreatmentControl

10 km

Entiat River IMW

Lemhi River IMW

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

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

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)

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

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

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

Wind River GRTS Master Sample

Wind River CHaMP Survey Design

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

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

Ordination By Ownershipwenachee repeats

NormaliseResemblance: D1 Euclidean distance

OwnershipPrivateFederal

2D Stress: 0.18

Ordination By Strahlerwenachee repeats

NormaliseResemblance: D1 Euclidean distance

Strahler42135

2D Stress: 0.18

Ordination By Watershedwenachee repeats

NormaliseResemblance: D1 Euclidean distance

watershedNason/TumwaterWhite RiverIcicle/ChumstickChiwawa RiverUpper Wenatchee RiverLower Wenatchee River

2D Stress: 0.18

Ordination By Yearwenachee repeats

NormaliseResemblance: D1 Euclidean distance

Year200420052006200720082009

2D Stress: 0.18

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%

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

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

AvgOfStationEmbeddednessrPercentCoarseGravelr

PoolsPerKmrSA_pools

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%

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

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

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

Fish cover• Best AIC: FC_Total~ Year + (1|ownership)+ (1|site)

Federal Private

Large Woody Debris• Best AIC: LWD ~ (1 | Strahler) + (1 | site) + (1 | ownership)

1 2 3

4 5

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

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

Geomorphic & climate based watershed classification

Human disturbance based watershed classification

CHaMP watersheds relative to ICRB steelhead and sp/su Chinook population

CHaMP Watershed?Resemblance: D1 Euclidean distance

CHAMPyesno

2D Stress: 0.03

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.