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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
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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
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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)
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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
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Study Area
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Study Area
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Study Area
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Study Area
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Study Area
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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
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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
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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
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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)
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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)
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• 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
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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)
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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)
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Questions?