Seasonal Usage of Off-Channel Habitats in the Entiat River by Juvenile Chinook Salmon

Nicholas Albrecht and Tom Desgroseillier

PIT Tag WorkshopSkamania Lodge, WA

January 27th-29th, 2015

Integrated Status and Effectiveness Monitoring Program (ISEMP)

• Design monitoring programs to address multiple management objectives

• Assess the status of anadromous salmonid populations, their tributary habitat, restoration, and management actions– Status and Trend Monitoring– Intensively monitored watershed (IMW)

• Entiat River, WA• Bridge Creek, John Day River, OR • Lemhi River, ID

– Evaluating benefits of habitat restoration

The Entiat River Basin

• Originates from 11 glaciers and snowfields in the Cascade Mountains

• 69 km• Drains 1,085km2

• Supports 8 salmonid species– Chinook Salmon (Oncorhynchus.

tshawytscha)– Steelhead/Rainbow Trout (O. mykiss)– Sockeye (O. nerka)– Westslope cuttroat trout (O. clacki lewisi)– Coho Salmon (O. kisutch)– Mountain Whitefish (Prosopium

williamsoni)– Bull Trout (Salvelinus confluentus)– Eastern Brook Trout (S. fontinalis)

Goals/Objectives

• Investigate juvenile Chinook salmon usage of 5 off-channel habitats in the Entiat River utilizing Passive Integrated Transponders (PIT) tag technology and mark-recapture methods

• Size• Density• Survival• Movement/Occupation of side channels

Study Area

Study Area

Study Area

Study Area

Study Area

Methods• Sampling was done for 1 cohort of

age-0 Chinook salmon from August 2013-April 2014– Mainstem – Summer/Winter– Off-channel – Summer/Fall/Winter

• Population abundance was determined using mark-recapture methodoloy and estimated using Chapman-Petersen Method

• N = ((n1+1)(n2+1)/(m2+12))-1• Lengths and weights were taking on

all fish• All fish >50mm were PIT tagged

MethodsBarker Model

• 1 model with 5 groups (side channels)

• Model Selection • Selection using evidence

(weight) ratio that was derived from Quasi-likelihood Akaike Information Criterion adjusted for over-dispersion (QAIC)

• Goodness of fit was measured using bootstrapping

• Model was adjusted using c-hatModel K Delta QAICc AICc Weights Model Likelihood QDevianceS(g*t) p(g*t) r(g*t) R(g*t) R'(g*t) F(.) F'(.) 72 0 1.00000 1.00000 5347.2434S(g*t) p(g*t) r(g*t) R(g*t) R'(g*t) F(g*t) F'(g*t) 79 53.4736 0.00000 0.00000 5386.4605S(g*t) p(g*t) r(g) R(.) R'(g*t) F(.) F'(.) 57 97.0804 0.00000 0.00000 5474.7932S(g*t) p(g) r(.) R(g*t) R'(.) F(.) F'(.) 50 117.5564 0.00000 0.00000 5569.4507

Results

• Summer– 3D>SanRay>Wilson’s>Tyee=Harrison’s

• Fall– 3D=SanRay>Wilson’s=Harrison’s>Tyee

• Winter– Tyee=Wilson’s

Analysis of Variance Table Response: Fork.Length Df Sum Sq Mean Sq F value Pr(>F) Site 4 94241 23560.1 329.577 < 2.2e-16 *** Season 2 51923 25961.5 363.168 < 2.2e-16 *** Site:Season 5 5051 1010.2 14.131 1.12e-13 *** Residuals 2798 200018 71.5

Season

Summer Fall Winter

Fo

rk L

en

gth

(mm

)

0

20

40

60

80

100

VS3 3D Tyee Wilson's San Ray Harrison's VS1

• Summer– ANOVA: F-value=153.110 p=<.001– VS3 was significantly different

from 3D (p<0.001) and Tyee (p<0.001) in the summer

– 3D>VS3>Tyee

• Winter– ANOVA: F-value=26.338 p=<.001– Fork Length in VS3 was significant

greater than Tyee (p<0.001)

Season

Summer Fall Winter

Fo

rk L

en

gth

(mm

)

0

20

40

60

80

100

VS3 3D Tyee Wilson's San Ray Harrison's VS1

• Summer– ANOVA: F-value=153.110 p=<.001– VS1 was significantly different

from Wilson’s (p=0.009), San Ray (p=0.003), and Harrison’s (p<0.001)

– San Ray>VS1>Wilson’s>Harrison’s

• Winter– ANOVA: F-value=26.338 p=<.001– Fork Length in VS1 was significant

great than Wilson’s (p<0.001)

• Summer– 3D>SanRay>Wilson’s>Tyee=Harrison’s

• Fall– 3D>SanRay=Harrison’s=Wilson’s>Tyee

• Winter– Tyee=Wilson’s

Analysis of Variance Table Response: Weight Df Sum Sq Mean Sq F value Pr(>F) Site 4 2612.2 653.06 286.95 < 2.2e-16 *** Season 2 1067.0 533.51 234.42 < 2.2e-16 *** Site:Season 5 108.6 21.71 9.54 4.881e-09 *** Residuals 2798 6367.9 2.28

Season

Summer Fall Winter

We

igh

t (g) 0

2

4

6

8

10VS3 3D Tyee Wilson's San Ray Harrison's VS1

• Summer– ANOVA: F-value=119.660 p=<.001– VS3 was significantly different

from 3D (p<0.001) and Tyee(p<0.001)

– 3D>VS3>Tyee

• Winter– ANOVA: F-value=16.1978 p=<.001– Weight in VS3 was significant

greater than Tyee (p<0.001)

Season

Summer Fall Winter

Weig

ht (g

) 0

2

4

6

8

10VS3 3D Tyee Wilson's San Ray Harrison's VS1

• Summer– ANOVA: F-value=119.660 p=<.001– VS1 was significantly different from

Wilson’s (p<0.001), and Harrison’s (p<0.001), but not San Ray (p=1.000)

– San Ray=VS1>Wilson’s>Harrison’s

• Winter– ANOVA:F-value=16.197.338 p=<.001– Weight in VS1 was significant

greater than Wilson’s (p<0.001)

Summer

Log10(FL)

1.5 1.6 1.7 1.8 1.9 2.0 2.1

Lo

g1

0

(W)

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4Harrison'sSan Ray3DTyeeWilson's

Site Slope Intercept R2 Weight of 50mm

Weight of 100mm

3D 3.21 -5.33 .94 1.3 12.3

Tyee 3.34 -5.59 .94 1.2 12.2

Wilson’s 3.13 -5.22 .97 1.3 11.3

SanRay 3.10 -5.14 .88 1.3 11.4

Harrison’s 3.22 -5.38 .86 1.2 11.6

Df Sum Sq Mean Sq F value Pr(>F) LogFL 1 106.95 106.95 75158.570 < 0.001 *** Site 4 0.17 0.04 29.160 < 0.001 *** LogFL:Site 4 0.03 0.01 6.007 < 0.001 *** Residuals 1947 2.77 0.00

Fall

Log10(FL)

1.6 1.7 1.8 1.9 2.0 2.1 2.2

Lo

g1

0

(W)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6San RayHarrison's3DTyeeWilson's

Site Slope Intercept R2 Weight of 50mm

Weight of 100mm

3D 2.68 -4.33 .85 1.69 10.82

Tyee 3.11 -5.18 .95 1.28 11.10

Wilson’s 3.09 -5.17 .94 1.24 10.67

SanRay 3.28 -5.51 .92 1.17 11.37

Harrison’s 3.01 -5.00 .98 1.35 11.00

Df Sum Sq Mean Sq F value Pr(>F) LogFL 1 31.76 31.76 18069.688 <0.001 *** Site 4 0.16 0.04 22.737 <0.001 *** LogFL:Site 4 0.02 0.00 2.281 0.059 . Residuals 776 1.36 0.00

Density

Season

Summer Fall Winter

De

nsity (fish

/m^

2)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.63D Tyee Wilson's San Ray Harrison's

Survival

Period

August-October 2013 October 2013-March 2014Ap

paren

t Su

rvival Pro

ba

bility

0.0

0.1

0.2

0.3

0.4

0.5

0.63D Tyee Wilson's San Ray Harrison's

Movement/Occupation3D

Summer Fall

Days after Marking

0 1-10 11-30 31-60 61-90 91-120 121-150151-180181-210211-240 More

Pro

po

rtion

of L

ast Detectio

n

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Days after Marking

0 1-10 11-30 31-60 61-90 91-120 121-150151-180181-210211-240 More

Pro

po

rtion

of L

ast Detectio

n

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Movement/OccupationTyee

Summer Fall

Days after Marking

0 1-10 11-30 31-60 61-90 91-120 121-150151-180181-210211-240 More

Pro

po

rtion

of L

ast Detectio

n

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Days after Marking

0 1-10 11-30 31-60 61-90 91-120 121-150151-180181-210211-240 More

Pro

po

rtion

of L

ast Detectio

n

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Movement/OccupationWilson’s

Summer Fall

Days after Marking

0 1-10 11-30 31-60 61-90 91-120 121-150151-180181-210211-240 More

Pro

po

rtion

of L

ast Detectio

n

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Days after Marking

0 1-10 11-30 31-60 61-90 91-120 121-150151-180181-210211-240 More

Pro

po

rtion

of L

ast Detectio

n

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Movement/OccupationSan Ray

Summer Fall

Days after Marking

0 1-10 11-30 31-60 61-90 91-120 121-150151-180181-210211-240 More

Pro

po

rtion

of L

ast Detectio

n

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Days after Marking

0 1-10 11-30 31-60 61-90 91-120 121-150151-180181-210211-240 More

Pro

po

rtion

of L

ast Detectio

n

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Movement/OccupationHarrison’s

Summer Fall

Days after Marking

0 1-10 11-30 31-60 61-90 91-120 121-150151-180181-210211-240 More

Pro

po

rtion

of L

ast Detectio

n

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Days after Marking

0 1-10 11-30 31-60 61-90 91-120 121-150151-180181-210211-240 More

Pro

po

rtion

of L

ast Detectio

n

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Conclusions

• Length/Weight differences between side channels

• Difference in overwinter survival between side channels in VS3 and VS1

• Fish densities varying by site and season• Movement/Occupation of side channels varies

between side channels in VS3 and VS1

Future Directions

• Continue monitoring the current side channels• Add additional side channels• Conduct genetic analysis to determine the

run-type of juvenile chinook utilizing the off-channel habitats

• Examine the effects of habitat

Questions?