yakima o. mykiss modeling workshop ian courter casey justice steve cramer
TRANSCRIPT
Yakima O. mykiss Modeling Workshop
Ian Courter Casey Justice Steve Cramer
Introductions
• What interests you most about the topic of anadromy and residency in O. mykiss?
• What would it take to make this a successful meeting for you?
Project Objective
Quantify the influence of life-history diversity and environment on steelhead sustainability in the Yakima Basin.
Deliverables
• Excel-based O.mykiss life-cycle model
• Peer reviewed publication
• Updated BA Steelhead Effects Analysis
Roles and Responsibilities
“Clarifying roles up front is like writing a job description – without it, you have no idea who can do what to whom.”
Steve CramerProject Advisor
Yakima Joint Board / Bureau of ReclamationProject Sponsor
Ian CourterProject Lead
Casey JusticeLead Analyst
Advisors
Choosing the Right Approach
Advisor Comments and Contributions
• Comments will be addressed on an individual basis.
• Participants who to make substantive contributions will be given coauthorship on publications.
Proposed Modeling Approach to Evaluating Drivers of Anadromous and Resident O. mykiss Abundance in the
Yakima Basin
Project Background and Purpose
ICTRT Extinction Risk Analysis
Atlas of Pacific Salmon (2005)
“…abandon the typological thinking (‘steelhead’ and ‘rainbow trout’ as biologically independent units) that has pervaded the biology and management of this species...”
McPhee et al. 2007
Ecotype Abundance Drivers
• Carrying Capacity– Size-dependent, flow-dependent
• Growth– Temperature dependent
• Survival– Smolt to adult
• Fecundity– Size and life-history dependent
Habitat Characteristics Favoring Residency or Anadromy
• High summer rearing temperatures
• Low summer flows• Variable growth
conditions• Reduced capacity for
adult fish• High migration survival
• Low summer rearing temperatures
• High summer flows• Consistent growth
conditions• Year-round capacity for
adult fish• Low migration survival
Anadromy Residency
Resident Recruits
ResidentSpawners
Genetics
Environment
Mature Adults
NRAnadromous
Spawners
AnadromousRecruits
NA
Mature Adults
Genetics
Environment
Juvenile Life-history Response
genotype + environment =
Anadromy Non-anadromy
phenotype
Life-History Response
“The capability to balance life-history options fits understandings of anadromy as ‘…a suite of life history traits… expressed as points along continua for each species and population.’ (Quinn & Myers 2005) as ‘…a function of variation in costs and benefits…’ (Hendry et al. 2004)…”
McPhee et al. 2007
Key Concepts
• Resident trout produce anadromous offspring
• Anadromous O. mykiss produce resident offspring
• Resident trout and anadromous steelhead in the upper Yakima, though phenotypically different, are genetically indistinguishable
• Phenotypic state is determined by a combination of environment and genotype
• Phenotypic state determines juvenile life-history response (anadromy or non-anadromy)
• “State-dependent” or “conditional” strategies allow individuals within a population to maximize their fitness
Key Concepts
To appropriately model Yakima steelhead abundance drivers, exchange between life-history forms in the population needs to be accounted for.
Quantitative O. mykiss Population Assessment
Abundance
(1) Stochastic Population ModelProductivity
DiversitySpatial Structure
(2) Mechanistic Model
Genetic & Env ControlsSurvival
FecundityJuvenile Capacity
Modeling Phase
-Viability analysis tool
-Restoration planning tool
Resident Contribution
Conceptual Modeling Approach
Carrying Capacity
Growth(bioenergetics)
Juvenile Life-History Response
Survival and Fecundity
Genetics
Key Model Components
Flow Temperature
Territory Size(competition)
Growth(bioenergetics)
Food supply
Capacity
Abundance Body Size
Conditions: Habitat
Fish Metrics:
(survival)
WUA(PHabSim)
* Influenced by body size
Reproductive Success
Fecundity*
Marine Survival*
ResidentAnadromous
Life-history decision*
Juvenile Abundance
Freshwater Survival*
Reproductive Success
Fecundity
Population
Metolius Upper Yakima Naches Satus Toppenish
Flo
w v
aria
bili
ty i
nd
ex
(CV
flo
w M
ar-S
ep (
%))
0
20
40
60
80
100
120
140
Mar Apr May Jun Jul Aug Sep Oct
Flo
w (
cfs)
at
Up
per
Yak
ima
0
1000
2000
3000
4000
Flo
w (
cfs)
at
To
pp
enis
h C
r.
0
100
200
300
400
500
600
Upper Yakima Toppenish
Toppenish Creek above Olney
Flow (cfs)
0 20 40 60 80 100 120 140 160
Juve
nile
ste
elh
ead
WU
A (
ft²/
1000
ft)
500
1000
1500
2000
2500
3000
Recalibrated data from Hardin and Davis (1990)
How do we model effects of flow on capacity?
Flow (cfs)
0 500 1000 1500 2000
WU
A (
ft²/
1000
ft)
0
1000
2000
3000
4000
5000
6000
FryJuvenileAdult
From Grant and Kramer (1990)
Fish length (mm)
0 50 100 150 200 250 300 350 400
Ter
rito
ry s
ize
(m²)
0
2
4
6
8
10
12
14
16Fry Juvenile Adult
Rearing capacity = WUA (m2) / Territory size (m2)
Flow (cfs)
0 500 1000 1500 2000
Fry
cap
acit
y
0
10000
20000
30000
40000
50000
60000
Juve
nil
e an
d a
du
lt c
apac
ity
0
1000
2000
3000
4000
FryJuvenileAdult
Flow (cfs)
0 200 400 600 800 1000
Ad
ult
cap
acit
y /
juve
nile
cap
acit
y
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
Stream temperature (°C)
0 5 10 15 20 25
Gro
wth
(g
/day
)
-0.01
0.00
0.01
0.02
0.03
0.04
0.05
From Rand et al. (1993) and Mangel and Sattherthwaite (2008).
Modeling Growth in FreshwaterGrowth = anabolic gains – catabolic losses
Factors influencing growth:
1) Temperature
2) Food availability
3) Fish density (competition)
4) Fish size
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Dai
ly a
vg.
tem
per
atu
re (
°C)
0
5
10
15
20
Upper YakimaNaches
Data from Hydromet 2000-2007:
Satus and Toppenish temperature data?
Jun Dec Jun Dec Jun Dec Jun
Fo
rk l
eng
th (
mm
)
0
100
200
300
400
Age-0 Age-1 Age-2
Predicted growth in the Upper Yakima
May Jun Jul Aug Sep Oct
Fo
rk le
ng
th (
mm
)
120
140
160
180
200
220
240
Expected(Optimal)
Observed(Constrained
Jun-Sep)
DecisionPoint
Δ Length (Observed – Expected)
= -28.6 mm
Age-1 Juvenile Growth
How does fish growth influence life-history variability?
May Jun Jul Aug Sep Oct
Fo
rk le
ng
th (
mm
)
120
140
160
180
200
220
240
Expected(Optimal)
Observed(Constrained September)
DecisionPoint
Δ Length (Observed – Expected)
= -7.8 mm
Age-1 Juvenile Growth
Survival Tradeoffs
Marine(smolt to adult survival)
Fre
shw
ater
(juve
nile
to
adul
t su
rviv
al)
Resident
Anadromous
Both?
Both?Neither?
Reproductive Success(population status)
Length at emergence (mm)
100 125 150 175 200 225 250 275 300
Mar
ine
surv
ival
sca
lar
(% o
f m
ax)
0
20
40
60
80
100
120
Data from Ward and Slaney (1989)
Fecundity vs Body Size
Fecundity of Steelhead and Rainbow Trout Stocks
Length (inches)
0 5 10 15 20 25 30
Eg
gs
0
1000
2000
3000
4000
5000
6000
7000
8000
Rainbow Trout
Steelhead
Genetics Modeling
• Thrower et al. 2004
– Heritabilities: probability of smolting and maturing
• Falconer 1989
– Response to selection
Communication Platforms
• Project website: http://www.fishsciences.net/projects/yakima
• Webinar meetings and conference calls
• Personal email and phone correspondence
End of Show
Sashin Creek Rearing Studies 1996 Brood
Weight (g)
Age-2 life-history Jun-97 Oct-97 Jun-98
Resident 4 30 67
Mature 5 43 71
Smolt 5 41 89
Frank Thrower, pers. comm.