Landscape-scale analysis of the relationship between juvenile Chinook size and growth and stream
temperature in western Alaska.
Principle investigator:
Dr. Suresh A. Sethi, R7 US Fish and Wildlife Service, Fisheries and Ecological Services, Biometrics
Co-investigator:
Dr. Brad Harris, Alaska Pacific University, Department of Environmental Sciences
Location:
Western Alaska freshwater systems harboring juvenile Chinook salmon
Summary:
This project seeks to understand the interaction between climate change and subsequent
responses by Chinook, Oncorhynchus tshawytscha, populations during their juvenile freshwater life
stages. Recently, Chinook salmon abundance has synchronously declined across many Alaskan
stocks, resulting in cultural and socioeconomic hardship for user groups. Water temperature plays a
critical role in the health of pre-smolt salmon life stages (hereafter "juvenile"), and changes in water
temperature may be a strong driving factor on growth and survival of juvenile Chinook salmon.
Furthermore, climate is expected to warm substantially in the coming decades in western Alaska,
potentially affecting juvenile salmon condition in freshwater habitats.
In this project, we undertake a landscape-scale meta analysis using statistical modeling to
infer juvenile Chinook size at age and annual growth from extant fork length data, which is available
with substantial spatial and temporal coverage. We investigate whether there is a discernible
relationship between climate and juvenile Chinook condition by examining the association between
juvenile Chinook size or growth and patterns in stream temperature. To accomplish this, project
objectives are to: 1) leverage ongoing data collection efforts in Alaska to synthesize extant fish
length and temperature data, 2) implement mixture models to estimate Chinook size at age and
annual growth from fork length data, and 3) analyze the association between stream temperature and
growth or size at age of Chinook salmon across the western Alaska landscape.
Expected output from this project includes development of statistical methodology to infer
size and growth from easy-to-collect fork length data, creation of a large spatially and temporally
explicit dataset on western Alaska juvenile Chinook size and growth, with associated temperature
data, and new insight into the interaction between climate and juvenile Chinook during freshwater
life stages. Results from this project will inform population management of Chinook stocks, as well
as contribute to landscape-level planning for salmon population responses to climate change. In light
of this, we will disseminate results from this work to both the scientific community, as well as
Federal, State, and international salmon management agencies tasked with Chinook management in
Alaska.
This analysis will require substantial data collation, statistical modeling, and results
communication efforts, and to achieve this, we will engage a Master’s student at an Alaskan
university to spearhead the work. In doing so, this project will contribute to the development of the
next generation of landscape ecologists in Alaska with emphasis on quantitative training necessary to
tackle complex ecological questions of relevance for natural resource management. This will also
strengthen collaboration between the US Fish and Wildlife Service and our Anchorage academic
partners in jointly mentoring a graduate student on this project. Such institutional collaboration and
the development of local scientific capacity as the next cohort of scientists will be an important
component to long-term workforce development at the Service, and for Alaskan natural resource
management more broadly.
Landscape-scale analysis of the relationship between juvenile Chinook size and growth and stream
temperature in western Alaska.
Dr. Suresh A. Sethi, R7 US Fish and Wildlife Service, Fisheries and Ecological Services, Biometrics
Dr. Brad Harris, Alaska Pacific University, Department of Environmental Sciences
A. Project Narrative
A.1 Statement of Need
Chinook salmon, Oncorhynchus tshawytscha, are a critical component of commercial, sport,
and subsistence fisheries in western Alaska. Recently, Chinook salmon abundance has
synchronously declined across many Alaskan stocks, resulting in cultural and socioeconomic
hardship for user groups. For example, Chinook salmon run declines resulted in extensive closures
of commercial and subsistence fisheries in the Yukon and Kuskokwim rivers in 2011 and 2012, as
well as extensive closures in commercial and sport fishing for the Kenai River and Upper Cook Inlet
streams in 2012, leading to fishery disaster declaration for areas of the State in 2012 (Blank 2012).
There is a lack of basic ecological knowledge about factors driving Chinook mortality in
Alaskan systems (Schindler et al. 2013), and consequently the causes of Chinook decline in western
Alaska are unknown. The Artic-Yukon-Kuskokwim (AYK) Sustainable Salmon Initiative convened
a panel of experts to compile a set of hypotheses on the causes of Chinook salmon declines
throughout western Alaska, condensing the universe of plausible causes into seven key hypotheses.
In some systems, mortality during freshwater salmon life stages may account for half of total
mortality (Bradford 1995), and one of the key hypotheses advanced by the expert panel is that:
“Change in the suitability or productivity of freshwater habitats used for spawning, rearing and
migration has contributed to declines in AYK Chinook salmon stocks (Schindler et al. 2013, pg.
37)”.
Water temperature plays a critical role in the health of pre-smolt salmon life stages (hereafter
"juvenile"), and changes in water temperature may be a strong driving factor of growth and survival
of juvenile Chinook salmon (Margolis et al. 1995; Quinn 2004). Furthermore, climate is expected to
warm substantially in the coming decades in western Alaska, potentially affecting juvenile salmon
condition in freshwater habitats (Griffiths and Schindler 2012). To provide insight into the
hypothesis that changes in freshwater rearing habitat suitability may be a significant driver of
juvenile Chinook dynamics in western Alaska systems put forth by the AYK Sustainable Salmon
Initiative expert panel, we proposed to conduct a landscape-scale meta analysis using a combination
of fork length data available through the extant Alaska Department of Fish and Game Freshwater
Fish Inventory database (available at http://www.adfg.alaska.gov) and extant stream temperature data
such as those available from data consolidation efforts funded by the WALCC (Trammel et al. 2013
funding cycle; WALCC 2013) to relate juvenile Chinook size and growth to spatial and temporal
water temperature gradients.
This proposed work moves beyond description of changes in landscape-level climate, and
seeks to understand the interaction between climate changes and subsequent responses by Chinook
populations. To achieve this, we propose a landscape-scale meta analysis involving: 1) synthesis and
integration of diffusely available extant fish length and relevant temperature data, 2) implementation
of mixture models to estimate Chinook size at age and inter-annual growth, and 3) analysis of the
association between temperature and size or growth of Chinook salmon across the western Alaska
landscape (Figure 1). While data are not available to directly test for a relationship between water
temperature and freshwater mortality for juvenile Chinook, using extant data on fork lengths, which
are available with good temporal and spatial coverage across the state, we can examine growth and
size which are related to survival through the freshwater life stage and contribute to the
understanding about the interaction between habitat suitability and juvenile Chinook condition in
freshwater rearing environments.
The research questions to be addressed by this work are:
1. What is the variability in size at age and annual growth for juvenile Chinook salmon across the
western Alaska landscape?
2. Is there a discernible association between juvenile Chinook size at age or annual growth with
spatial or temporal stream temperature gradients?
3. Will future water temperature changes in western Alaska expected to result from climate change
affect juvenile Chinook salmon habitat suitability and ultimately juvenile salmon condition?
The proposed work contributes directly to Chinook salmon life history knowledge in western
Alaska by examining the role water temperature may play in the condition of juvenile salmon. Such
information could ultimately be integrated into stock assessment and pre-season forecasting for
harvest management of western Alaska Chinook stocks. In addition to contributing to the
understanding of Chinook ecology in Alaska, the work will directly inform landscape-level climate
change response planning for Chinook salmon by providing insight into the association between
water temperatures and juvenile Chinook salmon size or growth. Furthermore, this work will
generate new data products including spatially and temporally explicit estimates of size and growth
for western Alaska juvenile Chinook salmon, and summary of local data support highlighting
regional data gaps. These will be useful for further investigations and will help guide site selection
for future field sampling to address juvenile Chinook dynamics in the freshwater rearing habitat.
This analysis will require substantial data collation, statistical modeling, and results
communication efforts, and to achieve this, we will engage a Master’s student at an Alaskan
university to spearhead the work. In doing so, this project will contribute to the development of the
next generation of landscape ecologists in Alaska with emphasis on quantitative training necessary to
tackle complex ecological questions of relevance for natural resource management. This will also
strengthen collaboration between the US Fish and Wildlife Service (FWS) and our Anchorage
academic partners in jointly mentoring a graduate student on this project. Such institutional
collaboration and the development of local scientific capacity as the next cohort of scientists will be
an important component to long-term workforce development at the Service, and for Alaskan natural
resource management more broadly.
A.2 Project Goals and Objectives
The longterm goals and associated objectives for this project are:
Goal 1: Develop and apply methodology to generate size at age and annual growth information as
inferred from juvenile salmon fork length data.
Objective 1.1: Collate extant data on juvenile Chinook salmon fork lengths in western Alaska
systems, and pending data availability and time, in other Lanscape Conservation Cooperative
(LCC) regions throughout the range of Chinook in Alaska.
Objective 1.2: Collate extant freshwater temperature data which overlap spatially and
temporally with juvenile Chinook length data from Objective 1.1
Objective 1.3: Develop R code (RDCT 2013) to estimate size at age and annual growth from
samples of fork lengths from juvenile Chinook populations using K-finite mixture models
(Fraley and Raftery 2002, 2006).
Goal 2: Provide insight into the effects of stream temperature on juvenile Chinook salmon size and
annual growth in western Alaska freshwater rearing systems.
Objective 2: Use regression techniques to test for association between freshwater
temperatures and juvenile Chinook size at age, and annual growth.
Goal 3: Contribute to the development of next generation of landscape ecologists in Alaska with
emphasis on quantitative training necessary to tackle complex ecological questions of relevance for
natural resource management in Alaska.
Objective 3: Provide funding and mentorship for a graduate student at Alaska Pacific
University to complete a Master’s degree using this project for their thesis research.
A.3 Project Activities, Methods, and Timetables
Project Activities
The primary activities necessary to achieve project objectives include collation of extant fish
and water temperature data, data management, statistical modeling, and communication of results at
scientific and public speaking venues, in peer-reviewed publication, and to Federal and State
resource managers.
Methods
Fish fork length data will be taken from the Alaska Freshwater Fish Inventory public
database managed by the Alaska Department of Fish and Game
(http://www.adfg.alaska.gov/index.cfm?adfg=ffinventory.main; Objective 1.1). A primary use of
these data are for inventorying salmon-bearing freshwater streams for inclusion in the State of Alaska
Anadromous Waters Catalog (Johnson and Blanche 2011), which warrants them for protection
against development that may threaten salmon freshwater habitat. Our work will extend the use of
this large database by generating novel information about Chinook salmon freshwater life history,
leveraging resources from ADFG and partners who contributed fish data to the Alaska Freshwater
Fish Inventory database. As of August, 2013, some 40,000 fork lengths were available in the
database for juvenile Chinook salmon across the state and over 1998-2012 combined. The Alaska
Freshwater Fish Inventory contains some water temperature data concurrent with fish fork lengths
(Objective 1.2). Additional water temperature collection of extant data will utilize publicly available
water temperature data portals, such as the AK-OATS 2013 project funded by WALCC (Trammel et
al. 2013 funding cycle; WALCC 2013) and portals maintained by the Alaska Ocean Observing
System, such as “Skin Temperature” surfaces (available at http://www.aoos.org/aoos-dataresources/). The Trammel et al. AK-OATS water temperature clearinghouse is expected to be
available by September 2014, coinciding with the commencement of data collection for this project
(personal communication w/ J. Trammel and M. Geist, October 2013; see the ‘Timeline’ below).
Samples of juvenile Chinook in freshwater rearing environments can contain a mix of
animals that are young of year, and those that have remained in freshwater for more than a year.
Thus a set of fork lengths from a population contain a mix of age 0 and age 1 juveniles (and
potentially older age classes, depending on the salmon species; Figure 2). We will utilize univariate
K-component Gaussian finite mixture models implemented using the mclust package (Fraley and
Raftery 2002, 2006) in the R statistical programming environment (RDCT 2013) to separate out
animals into distributions of age 0 and age 1 based upon fork length data. Mixture models attempt to
decompose sample data based on a mixture of probability distributions by estimating the parameters
of the underlying component distributions. In the context of this study, this amounts to separating
out the probability distributions representing the length frequencies of different age classes present in
a sample of fork lengths taken from a population made up of mixed age classes. mclust implements
maximum likelihood methods to fit mixture distributions where the likelihood is expressed as:
(eq. 1)
𝐿(𝝉, 𝝁, 𝝈|𝒚, 𝐾) = ∏𝑛𝑖=1 ∑𝐾
𝑘=1 𝜏𝑘 𝑓(𝑦𝑖 |𝜇𝑘 , 𝜎𝑘 )
where 𝒚 = 𝑦1 , … , 𝑦𝑛 is the data vector of fork lengths, 𝝉 = 𝜏1 , … , 𝜏𝑘 represents the probabilities that a
randomly drawn data point comes from a particular component distribution (i.e., a juvenile salmon
age class) with the constraints that 𝜏𝑘 ∈ [0,1] and ∑𝐾
𝑘=1 𝜏𝑘 = 1 for k = 1,2,…,K , and 𝑓(𝑦𝑖 |𝜇𝑘 , 𝜎𝑘 )
represents the probability of the observed data point given the parameters specifying a Normal
distribution for the kth component with mean, 𝜇𝑘 , and standard deviation, 𝜎𝑘 :
(eq. 2)
𝑓(𝑦𝑖 |𝜇𝑘 , 𝜎𝑘 ) =
1
√2𝜋𝜎𝑘2
exp (−
(𝑦𝑖 −𝜇𝑘 )2
2𝜎𝑘2
).
The 𝜏 parameters are interpreted as the proportion with which the kth component is present in the
population (e.g. the proportion of age 1’s in the population for which a sample is in hand). The
likelihood in equation 1 is maximized in choice of the proportions with which the underlying
component distributions are present in the population, and their means and variances, given K and
given a specification for the covariance structure across the component distributions. In cases where
more than one age class is present in a sample of juvenile Chinook (i.e. age 0 and age 1 fish), we can
use the difference in mean size at age 0 and mean size at age 1 as an estimate of annual growth
(Figure 2). At the end of the modeling analyses, we will have estimates of (mean) size (fork length)
by age cohort and estimates of annual growth, by month, year, and location, across populations of
juvenile Chinook salmon in western Alaska and across a range of years that can be used to examine
spatiotemporal variability in juvenile size and growth (Objective 1.3).
Finally, using mixture model output, we will regress juvenile Chinook size at age, and if data
are available for enough populations for which both age 0 and age 1 cohorts are present in fork
length samples, inter-annual growth against water temperature data to examine the strength of
association between juvenile size or growth and temperature (Objective 2). In examining size at age
for population i against water temperature, we will examine regressions of the form:
size_at_agei = f(year effect, month effect, temperature, location) + error .
We will explore a range of parametric forms for regression analyses, including random effects
models to control for within year or within location correlation if necessary. Regression modeling
will be conducted in the R statistical programming environment.
While extreme water temperatures may cause acute mortality effects on juvenile Chinook
salmon, our proposed methodology examines size at age and annual growth which are the results of a
history of temperature exposure throughout an animal’s life. For example, consider a sample of
juvenile Chinook fork lengths from a stream location in western Alaska in July 2012 which contain a
mix of both age 0 and age 1 fish such that both size at age and inter-annual growth estimates are
possible. Assuming in this hypothetical scenario juvenile Chinook emerge in May, then the two
cohorts experience the following freshwater rearing habitat histories up to the time of the survey:
Age 1 fish experience the previous year’s temperature environment, whereas age 0 fish
experience only two months of the temperature regime at the time of sampling. To accommodate
this discrepancy, we will explore different types of temperature data relevant to the two age cohorts,
using information theoretic-based model selection (Burnham and Anderson 2002) to let the data to
provide evidence about which are the most informative types of temperature data to explain
variability in size at age or inter-annual growth for juvenile Chinook in the study.
Depending on data availability and data resolution of extant freshwater temperature in
western Alaskan systems for which we have fork length data, we will consider both mean
temperature data and variability in temperature for subsequent regression analyses. While we would
also like to examine water temperature over winter months for juveniles that spend a year in
freshwater, we anticipate a lack of winter water temperature data in the study system. As an
alternative, we will consider using more widely available air temperature or land surface “Skin
Temperature” data (available at www.aoos.org) as proxies and explore possibilities of modeling
water temperatures based on these data (e.g. Mohseni and Stefan 1999).
Regression analyses to examine the association between inter-annual growth estimates and
water temperature data will use analogous methodology as outlined above for size at age (Objective
2).
This project will require substantial time in data collection, statistical methodology
refinement, statistical analysis and coding, writing up results, and communicating results.
Furthermore, this project has all the workings of an excellent Master’s thesis (Objective 3):




The project is of the right scope for a Master’s thesis and methodology could be extended to
other salmon species and LCC’s pending data availability.
The impact of the project is expected to be high as little information exists at the landscape
level on juvenile Chinook size and growth, and understanding of the realized impacts that
temperature and climate change have had on Pacific salmon is limited.
The project will involve mentorship and collaboration across academic institutions and
management agencies.
The project will allow for substantial training in applied statistics, fisheries ecology, and
programming--key skills for the next generation of effective natural resource management
scientists.
Therefore, we propose to fund a graduate student at Alaska Pacific University to spearhead
the work on this project as a focus of their Master’s thesis. We feel the development of quantitative
ecology training capacity in south central Alaska, and Anchorage in particular, has substantial growth
potential, and we seek to strengthen the collaboration between the US Fish and Wildlife Service and
our Anchorage academic partners in jointly advising and mentoring a graduate student on this
project. Such institutional collaboration and the development of local scientific capacity in next
generation scientists will be an important component to long-term workforce development at the
Service.
Dr. Suresh Sethi (principle investigator, FWS Biometrician) is currently Scholar in Residence
at Alaska Pacific University and will co-advise a Master’s student on this project with Dr. Brad
Harris, a professor at Alaska Pacific University, and director of the Fisheries, Aquatic Science &
Technology Laboratory. As a result, we will work closely on this project and with the student to
accomplish the project goals.
Our approach to disseminate this work to other fisheries scientists, fisheries managers, and
the public will utilize different tools to reach different audiences. First, a focus of this project will be
the student’s Master’s thesis and publication of results in a peer-reviewed journal, communicating
results to the broader scientific community. Per requirements of most peer-review journals, any data
not already publicly available will be archived and made publicly available, and R code will also be
published with the accepting journal. The student will also be required to present these results at a
State or national scientific conference (e.g. the Alaska Chapter or national meeting of the American
Fisheries Society). Second, to reach fisheries managers, the student will be requested to present on
these methodology and results to FWS fisheries managers and to other management bodies relevant
to western Alaska Chinook stocks (e.g. Yukon Science Panel or ADFG presentation). Finally, with
the assistance of FWS and Fisheries, Aquatic Science & Technology Laboratory Lab outreach staff,
we will use social media to highlight the project, provide a non-technical write up of research results,
and use the research and data products in numerous outreach and education venues including the
Campbell Creek Science Center's Mid Summer's Night Science Series (Anchorage, AK), and direct
in-classroom activities with Anchorage area schools (e.g. Tudor Elementary School's Mad Scientist
Fair, Anchorage, AK).
Data management and accessibility
This project will synthesize extant juvenile Chinook information and relevant temperature
data, as well as generate spatially and temporally explicit “derived” information on size at age and
growth. We will maintain a database (e.g. Access) and appropriate metadata for the project, and
make the final database publicly available at a digital data repository such as Dryad
(www.datadryad.org). Detailed methodology for “derived” information on juvenile Chinook size at
age and annual growth will be publicly available in peer-reviewed reports (see Anticipated
Products/Outputs below).
Timetable
This project will take approximately 32 months to completion, with project results and
anticipated communication of results beginning in March 2016.
Table 1. Project timetable.
Abbreviations: Suresh Andrew Sethi (SAS), Brad Harris (BH), Master’s Student (MS)
A.4 Anticipated Products/Outputs
This proposed work will provide information useful for management of both the landscape in
which juvenile salmon rear, and harvest management of western Alaska Chinook stocks. Managers
who stand to benefit from improved understanding of juvenile salmon size and growth dynamics and
interactions with water temperature include Fish and Wildlife Service Refuge management staff (e.g.
Yukon Delta and Togiak refuges), Alaska Department of Fish and Game stock assessors and area
managers who prosecute Chinook fisheries, and international scientific and management panels, such
as the Yukon Panel or Yukon Science Panel, amongst others.
Anticipated output from the project include:
 Development of statistical methodology and R code for novel use of regularly-available fork
length data to study freshwater life history of salmon and to examine the association between
water temperature and Chinook size and growth in western Alaska. We anticipate this
methodology would be directly applicable in other LCC’s (Figure 1).





Peer-reviewed publication on the association between juvenile Chinook and water
temperature in western Alaska.
3+ oral presentations (one to FWS and LCC partners) of results to fisheries scientists and
fisheries managers
Public outreach regarding collaborative Service and local University research on Chinook
salmon--currently a State-wide natural resource management priority.
Strengthened ties between academic and federal resource management agencies in
developing quantitative ecological training and student mentorship capacity
Graduation of a Master’s student with a quantitative thesis focused on a State-wide
management priority.
A.5 Project Monitoring and Evaluation
We will set deadlines for project milestones and use these to monitor the project’s
progression. In addition, our intended plan of communication results and student graduation present
hard deadlines which bound the project. For example, we intend to present initial research results by
the 2016 American Fisheries Society meeting circuit (either Alaska, regional, or national meeting),
and M.S. student tuition and stipend funding will expire at the end of 2016FY. Finally, we will
measure success of the project by provision of the aforementioned anticipated outputs: production of
R code and statistical methodology, peer-reviewed publication, oral presentations of results, outreach
postings on social media, and successful graduation of a Master’s student.
A.6 Descriptions of Organizations Undertaking the Project
Dr. Suresh Andrew Sethi is the principle investigator of this project and is the Regional
Biometrician for the Fish and Wildlife Service, Fisheries and Ecological Services Division in Alaska.
The U.S. Fish and Wildlife Service is a Federal management agency tasked with the conservation of
Pacific salmon stocks on Federal refuge system lands in Alaska, and administers the LCC’s. At
present, Dr. Sethi is also Scholar in Residence at Alaska Pacific University and has a cooperative
agreement in place with the University to take on student mentorship duties. He will serve as the
FWS project officer on the project.
Dr. Brad Harris is a professor in the Department of Environmental Science at Alaska Pacific
University in Anchorage. Alaska Pacific University is a member of the NW Alaska Cooperative
Ecological Studies Unit and has a newly developing fisheries science program with which the FWS
Biometrics division is seeking to strengthen ties and increase cooperative scientific capacity available
to address Service management issues. Alaska Pacific University offers a Masters in Science degree
in Environmental Studies. Dr. Harris will serve as the project officer from Alaska Pacific University.
Both Drs. Sethi and Harris will take on substantial involvement in designing, advising, and
carrying-out this project; project responsibilities are indicated in Table 1, above. Vitae for Drs. Sethi
and Harris are attached at the end of this proposal.
A.7 Sustainability
We anticipate that this project will develop methodology useful for generating size and
growth information from routinely available fork length data for juvenile salmon species in other
regions of Alaska, and throughout the range of Pacific salmon. Follow up projects for which we will
seek additional competitive funding will examine landscape-level patterns in juvenile Chinook and
other salmon species in other regions of Alaska and in the lower 48 states.
A.8 Literature Cited
Blank RM (Acting Sectretary of Commerce) 2012. Letter of determination of fishery resource disaster to Alaska
Governor SR Parnell, dated September 12, 2012.
Bradford MJ 1995. Comparative review of Pacific salmon survival rates. Canadian Journal of Fisheries and Aquatic
Sciences 52:1327-1338.
Burnham KP, Anderson DR 2002. Model Selection and Multimodel Inference: a Practical Information-Theoretic
Approach. 2nd edition, Springer, New York.
Fraley C, Raftery AE 2002. Model-based clustering, discriminant analysis and density estimation. Journal of the
American Statistical Association 97:611-631.
Fraley C, Raftery AE 2006. MCLUST Version 3 for R: Normal mixture modeling and model-based clustering.
Technical Report No. 504 UW Department of Statistics, Seattle.
Griffiths JR, Schindler DE 2012. Consequences of changing climate and geomorphology for bioenergetics of
juvenile sockeye salmon in a shallow Alaskan lake. Ecology of Freshwater Fish 21:349-362.
Johnson J, Blanche P 2011. Catalog of waters important for spawning, rearing, or migration of anadromous fishes –
Southcentral Region, Effective June 1, 2010. Alaska Department of Fish and Game Special Publication No. 10-06,
Anchorage.
Margolis L, Groot C, Clark WC (Eds.) 1995. Physiological Ecology of Pacific Salmon. UBC Press, Vancouver, CA.
Mohseni O, Stefan HG 1999. Stream temperature/air temperature relationship: a physical interpretation. Journal of
Hydrology 218:128-141.
Quinn TP 2004. Behavior and Ecology of Pacific Salmon and Trout. UW Press, Seattle.
R Development Core Team (RDCT) 2013. R: A language and environment for statistical computing. R Foundation
for Statistical Computing, Vienna.
Schindler D, Krueger C, Bisson P, Bradford M, Clark B, et al. 2013. Arctic-Yukon-Kuskokwim Chinook Salmon
Research Action Plan: Evidence of Decline of Chinook Salmon Populations and Recommendations for Future
Research. Final draft, prepared for the AYK Sustainable Salmon Initiative, Anchorage, AK. [available at:
http://www.aykssi.org]
Western Alaska Landscape Conservation Cooperative (WALCC) 2013. 2013 Projects: Coastal Systems. Online
document, US Fish and Wildlife Service Anchorage, AK. [available at: https://westernalaskalcc.org]
Blank, RM. (Acting Sectretary of Commerce). 2012. Letter of determination of fishery resource disaster to Alaska
Governor Sean R. Parnell, dated September 12, 2012.
B. Figures
Figure 1. Proposed study region. Landscape-scale data for juvenile Chinook lengths will target populations in the
Western Alaska Landscape Conservation Cooperative (Green shaded area), however, methodology outlined in this
proposal will be applicable to Chinook populations throughout their Alaska range, pending data availability.
Figure 2. Example mixture model output. Juvenile Coho, O. kisutch, fork length data (histogram; gray bars) from
the Big Lake Drainage, Big Lake, Alaska, June-August 2011 (n= 1682). Data were taken using minnow traps
(courtesy J. Ashiline and J. Gerken, FWS). The black line indicates the fit of a 2-component Gaussian mixture
model (equal variance structure, chosen by BIC model selection). Mean size age 0 = 63.8mm, mean size age 1+ =
98.6 mm, inter-annual growth estimate = 34.8mm.
C. Budget
C.1 Itemized proposed budget
US Fish & Wildlife Service
Personnel Service Cost
Principle Investigator, Dr. Suresh Sethi
Monthly Salary =
$9,736 (includes fringe)
FY
2014
2015
Months
1
2
2016
2
Total Salary
Alaska Pacific University
Personnel Service Cost
Co-Investigator, Dr. Brad Harris
Monthly Salary = $11,550
(includes fringe)
WALCC
Match
Total
$4,868
$9,736
$4,868
$9,736
$9,736
$19,472
FY
2014
2015
Months
1.5
2
$9,736
$9,736
$19,472
2016
2
$24,340
$24,340
$48,680
Total
Trip
present res.
present res.
Total Travel
Indirect
Internal FWS-none
WALCC
Match
Total
$8,663
$7,700
$8,663
$15,400
$17,325
$23,100
$7,700
$15,400
$23,100
$24,063
$39,463
$63,525
2015FY
USFWS
APU
2016FY
USFWS
APU
Graduate Student, TBD
Non-personnel Service Cost
Travel
FY
2014
2015
2016
Annual Project Totals (with indirect for WALCC funds)
WALCC
Match
Year
Organization
2014FY
USFWS
$4,868
$4,868
APU
$10,178
$8,663
WALCC
$0
$2,000
$2,000
Match
$0
$0
$0
Total
$0
$2,000
$2,000
FY
2014
2015
2016
Annual Tuition = $16,680
WALCC
$41,680
$31,680
$41,680
$31,680
$4,000
$0
$4,000
Total
$63,360
$20,000
$83,360
WALCC
$0
$2,000
$2,000
Match
$0
$0
$0
Total
$0
$2,000
$2,000
$4,000
$0
$4,000
$0
Annual Stipend = $25,000
Match
Total
$0
$10,000
$41,680
$10,000
$41,680
Non-personnel Service Cost
Graduate Student, TBD
Travel
FY
2014
2015
2016
Trip
present res.
present res.
Total
Indirect
CESU Rate = 17.5%
$15,999
$15,046
$11,736
$48,622
$13,531
$9,736
$25,400
$28,577
$21,472
$74,022
$60,358
$35,136
$95,494
$11,736
$48,622
$9,736
$25,400
$21,472
$74,022
$60,358
$35,136
$95,494
Summary: Project Total (with indirect for WALCC funds)
WALCC
Match
USFWS
APU
Total
Total
$9,736
$18,841
$28,340
$107,421
$135,761
Total
$24,340
$52,680
$59,463
$150,885
$83,803
$203,565
Match percent:
62%
C.2 Budget explanations
FWS
Limited funding is requested for part of Dr. Sethi’s time on this project not covered by
Fish and Widlife Service base funds. As Biometrician for the Fisheries and Ecological Services
Division, Dr. Sethi’s base salary is made up of contributions from Fisheries and Ecological
Services directorate funds, FWS Fisheries program funds, field office funds, conservation
genetics lab funds, and Subsistence Management Funds, based upon allocation of time between
programs and contribution by Dr. Sethi’s work to those programs. This project will entail a shift
of an amount of time for Dr. Sethi over the project life and is supported by his direct supervisor
(Dr. John Wenburg), however, general Fisheries and Ecological Services funds are not sufficient
to cover all his time on the project. The amount requested fills in the gaps; the Service is
matching funds for Dr. Sethi’s time out of base funds equal to the amount requested by WALCC
salary funds.
APU
APU is a member of the North and West Alaska Cooperative Ecosystem Studies Unit and
signatory to the Cooperative and Joint Venture Agreement for this unit. Therefore, APU has a
negotiated 17.5% indirect rate for this work.
Salary-- Dr. Harris will dedicate between 1.5 and 2 months per year to this work. His salary
match funds will be provided by the Fisheries, Aquatic Science & Technology Laboratory.
Student Stipend and Tuition--As part of Objective 3, we seek to fund a M.S. graduate throughout
the completion of this project which would serve as the focus of their thesis. Associated costs
include tuition for enrollment in the Masters of Science in Environmental Sciences Program and
a living stipend over the calendar year to offset food and housing expenses, allowing the student
to focus on scholarship and research, and attracting the best graduate candidates for the project.
Student support match funds will be provide by the Fisheries, Aquatic Science & Technology
Laboratory.
Travel
As part of the outreach strategy for this project, we intend to communicate results at a
scientific conference, such as the Alaska Chapter American Fisheries Society annual meeting, to
a relevant management body, such as the Yukon Scientific Panel, and to FWS scientists and
managers. Travel funds are requested for these presentations by the student and/or investigators.
Federally Funded Equipment
Dr. Sethi will utilize a desktop computer which has been paid for and is the property of
the U.S. Fish and Wildlife Service. This equipment is not included as matching funds in the
requested budget for this project.