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?