Close Message
CBFish website will be offline between 5:00 PM and 6:00 PM today for regular maintenance. Thank you for your patience.
Columbia Basin Fish and Wildlife Program Columbia Basin Fish and Wildlife Program
SOW Report
Contract 76914 REL 4: 2003-054-00 EXP REPRO OF STEELHEAD IN HOOD RIVER
Project Number:
Title:
Evaluate the Relative Reproductive Success of Hatchery-Origin and Wild-Origin Steelhead Spawning Naturally in the Hood River
Stage:
Closed
Area:
Province Subbasin %
Basinwide - 100.00%
Contract Number:
76914 REL 4
Contract Title:
2003-054-00 EXP REPRO OF STEELHEAD IN HOOD RIVER
Contract Continuation:
Previous: Next:
76914 REL 2: 2003-054-00 EXP REPRO OF STEELHEAD IN HOOD RIV
  • 76914 REL 6: 2003-054-00 EXP REPRO OF STEELHEAD IN HOOD RIV
Contract Status:
Closed
Contract Description:
PROJECT COORDINATION AND PARTNERSHIPS
The genetics work has been, and continues to be, carried out by Michael Blouin at Oregon State University.  This project was originally coordinated with the Hood River steelhead hatchery and research program, funded by Bonneville Power Administration and administered and implemented by the Oregon Department of Fish and Wildlife and the Warm Springs Tribes (project numbers 198805307, 198805308, 198805304 and 198805303).  These projects included operation and maintenance of the Oak Springs and Parkdale hatchery facilities, and operation and maintenance of the fish collection and handling facility at Powerdale Dam, as well as database management and data analysis on the part of ODFW.   The work continues in cooperation with ODFW biologists, both in continued analysis of the samples that were originally collected at Powerdale Dam and in ongoing experiments conducted mainly at the Oregon...  Hatchery Research Center (OHRC), an ODFW facility run in partnership with Oregon State University

LOCATION OF PROJECT
Steelhead samples were collected at the former Powerdale Dam, Hood River, under supervision of Rod French, ODFW, who also coordinated aging of scale samples.  All laboratory work and genetics data analysis continues to be conducted in the laboratory of Michael Blouin at Oregon State University.  We continue to use those pedigreed samples from the Hood River in ongoing studies on the genetics of domestication.  We also conduct experimental work at the OHRC using coastal stocks of steelhead to test hypotheses about adaptation to captivity that were generated by the Hood River data.  

BACKGROUND AND RESULTS TO DATE FROM THE HOOD RIVER
The Hood River supports two populations of steelhead, a summer run and a winter run.  They spawned only above the Powerdale Dam, which is a complete barrier to all salmonids.  From 1991 to 2010 every adult passed above the dam was measured, cataloged and sampled for scales or fin snip.  Therefore, we have a DNA sample from every adult steelhead that went over the dam to potentially spawn in the Hood River from 1991 to 2010, when the dam was removed.  Similar numbers of hatchery and wild fish were passed above the dam during the last decade.  During the 1990's "old" domesticated hatchery stocks of each run (multiple generations in the hatchery, out-of-basin origin) were phased out, and conservation hatchery programs were started for the purpose of supplementing the two wild populations (using wild broodstock; hereafter F1 hatchery fish).  The winter-run F1s were started in 1991, and the summer-run F1s were started in 1997.  In a supplementation program such as this, wild-born broodstock are used as parents in the hatchery in an attempt to circumvent the low fitness induced by multiple generations of selection in the hatchery.  This 19 years of samples gave us the ability to estimate, via microsatellite-based pedigree analysis, the relative total reproductive success (adult to adult production) of hatchery (H) and wild (W) fish for two populations (summer and winter), over multiple brood years.  We now have an almost 4-generation pedigree that is complete for all anadromous fish (note, however, that we are missing samples from resident fish that apparently are the parents of many steelhead).  We compared the relative success of two "old" hatchery stocks vs. wild fish (the winter run “Big Creek” stock and the summer run “Skamania” stock), and showed they have much lower total fitness than wild fish when both breed in the wild (Araki et al., 2007a).  In that paper we also concluded that the winter-run F1 were not significantly different from wild fish, based on 3 run years of data.  But in a subsequent analysis based on six run years of data the difference was significant, with the F1 winter run fish averaging about 85% the fitness of wild fish (Araki et al., 2007d).  

One problem with interpreting an observed difference in fitness between fish raised in a hatchery and fish raised in the wild is that the difference can have a genetic and/or environmental basis (because the H fish experienced a very different environment during the juvenile phase).  However, in Araki et al. (2007d) we were able to compare the first generation fish with second-generation hatchery fish raised in the same hatchery.  These data suggest that the second generation fish have ~55% the reproductive fitness of the first generation fish (Araki et al., 2007d).  Because both types of fish experienced identical environments, the difference between them must be genetically based.  This result also suggests that the decline in fitness that results from additional generations of selection in the hatchery can occur very quickly.  

Thus, we have demonstrated a genetically-based effect of hatchery culture that reduces fitness in the wild and that accumulates with each generation of hatchery culture.  Nevertheless, even if captive-bred individuals are genetically different and produce fewer offspring than wild individuals, adding them to a wild population can still give a demographic boost without substantial harm to a wild population that is below carrying capacity if (1) the genetic effects do not persist into the next generation (i.e., natural selection purges the offspring generation of their deleterious alleles before they reproduce), and (2) enough captive-bred individuals are added each generation to make up for their lower productivity.   If the first condition is not true, however, genetic effects will accumulate over time, potentially leading to a downward spiral in the absolute fitness of the supplemented wild population.  Thus, one key question is whether the wild-born descendents of captive-bred fish are less reproductively successful than the descendents of wild fish. In Araki et al. (2009) we analyzed the fitness of wild-born fish as a function of their parentage.  We found that wild-born offspring of two first-generation hatchery fish averaged 37% the fitness of the offspring of wild fish, while offspring of hatchery-by-wild crosses averaged 87% (Araki et al., 2009).  These results suggest that the hatchery genetic load is not purged from the wild-born population after a full generation of natural selection in the wild.  

We subsequently showed that F1 winter-run  hatchery fish make better broodstock than do wild fish (in terms of number of returning adult hatchery offspring produced)(Christie et al., 2012a), while at the same time performing worse in the wild.  We also showed an interesting tradeoff in which wild broodstock that successfully produced many returning adult hatchery offspring, produced offspring that performed poorly in the wild and vice versa (Christie et al., 2012a).  These two pieces of information strongly suggest that strong domestication selection was acting in the hatchery to make fish rapidly adapt to hatchery conditions. Interestingly, a similar pattern has now been observed in Chinook, so the result does not appear to be limited to steelhead (Ford et al., 2012).  

To summarize the pedigree-based work to date on the Hood River, we have shown: (1) the older, multi-generation, summer and winter hatchery stocks from the Hood River had very low fitness relative to wild fish (10-30%).  This result is consistent with results of many other studies on old stocks (Berejikian and Ford, 2004; Araki et al., 2008). (2) first generation winter run fish have significantly lower fitness than wild fish (about 85%), second generation fish do even worse, and the effect is genetically based. (3) The genetic effects of hatchery culture identified for the winter-run stock persist into the first wild-born generation, with the fitness of wild-born fish depending on whether their parents were both wild, both hatchery or one of each.  Again, the common environment experienced by these three types of wild fish suggests a genetic effect.  Finally, the data in Christie et al. (2012a) strongly suggest that the above effects (loss of fitness in the wild) result from rapid adaptation to the hatchery, rather than some generalized genomic deterioration.

In addition to the three foci of our research, we have addressed related questions that are relevant to hatchery uncertainties research.  These topics include the effects of hatchery and resident fish on the effective size of the Hood River steelhead population (Araki et al., 2007b; Christie et al., 2012b) and methodological work on methods for fitness estimation (Araki and Blouin, 2005; Christie et al., 2011) and for estimation of effective size (Araki et al., 2007c).  We also tested whether residualized hatchery fish are a significant route of gene flow from the hatchery into the wild steelhead population – they aren’t (Christie et al., 2011).   However, that work did illustrate how important the resident, wild fish are to the genetic integrity of the anadromous, steelhead population. In other work, we developed new pedigree analysis methods (e.g. SOLOMON software; Christie et al., 2013a), and extended our analyses of the consequences of small effective population size in the hatchery broodstock (Christie et al., 2013b).  In that last publication we show that inbreeding between related hatchery fish on the spawning grounds cannot explain their low fitness relative to wild fish.   Other, recent work includes:  a review paper on the fitness of early-generation hatchery fish from published studies available to date for which data on the reproductive success of F1 or integrated stock hatchery fish has been evaluated in their stream of origin (Christie et al., 2014); a study on why Hood River wild steelhead have a female-biased sex ratio while hatchery steelhead have a 50:50 sex ratio (Thompson et al., 2014); a transcriptome for steelhead that others can use for RNAseq (gene expression) studies on O. mykiss (Fox et al., 2014); and an analysis of environmental factors that may influence body size at release in hatchery Hood River steelhead (Thompson et al., 2016).  In that paper we showed that spawn date can have a significant effect, presumably owing to the fact that the earliest clutches are cooled to slow their development until all the families can be ponded at the same time.  Most recently, we used our steelhead pedigree to study the fitness consequences of variation in life history traits, including single vs. repeat-spawners (itero- vs. semelparity), and age at return (Christie et al., 2018).  We showed that repeat spawners have double the lifetime reproductive success of single spawners, but that they invest less in their first spawning than do single spawners.  Thus, the life history polymorphism is likely maintained by differential allocation of energy to initial spawning vs. ocean survival as kelts (spawned fish that return to sea).   More remarkably, we found evidence that variation in age at return among females is maintained by negative frequency dependent selection.  We plan to continue to use the Hood River pedigree and associated DNA samples to continue to study the genetics of adaptation to hatcheries, and the basic biology of steelhead.
  A full bibliography of our work resulting from BPA funding through 2016 can be found in Project Attachments (file: “Bibliography to 2016”).   Most of those plus subsequent papers are available as pdfs in Project Documents on cbfish.org.

CURRENT AND FUTURE WORK
As described above, there now exists substantial evidence that even early-generation hatchery salmonids have lower  fitness than wild fish in the wild, and strong evidence from steelhead that the effect is genetic and owing to adaptation to captivity.  So we believe that now the most important research question is to figure out how to modify hatchery culture conditions to reduce the rate of adaptation to captivity.  

Because size at release is positively correlated with survival at sea, one plausible hypothesis to explain rapid domestication in hatcheries is that hatcheries select for physiological or behavioral traits that promote fast growth in captivity (this might be especially true for steelhead, which are raised to smolting in one year versus the normal two years that they take in the wild).   If those favored traits are maladaptive in the wild, then that could explain why hatchery fish quickly evolve to have lower reproductive success than natural-origin fish in the wild environment.  Support for this hypothesis comes from scale-aging and pedigree data that show the average size at smolting of steelhead that survived to return as adults to the Hood River was much larger than the average size of all smolts from the same cohort at release (Thompson et al., 2018).  Therefore, in our experimental work we have been using growth rate as our measure of performance in the hatchery.

The two main questions we aim to answer are: (1) what traits are under selection in the hatchery? And (2) what hatchery conditions cause strong selection on those traits?  Answering these questions would then tell us how one might modify hatchery culture conditions to reduce the selection pressures that cause such rapid domestication.  This would allow managers to produce hatchery fish that are more like wild fish and thus pose less genetic risk to wild populations.  We are taking three main approaches to answer these questions.

(1) The first approach has been to vary environmental conditions in the hatchery that we suspect might exacerbate selection.  Then we test whether the modified conditions produce fish that show less variation among families in performance in the hatchery than do the standard conditions.  Under standard conditions we see large variance among families in size at release, which means large opportunity for selection.  If we can find environmental conditions that reduce that variance, then there would be less selection among families, and a slower rate of adaptation to the hatchery.  This experimental work has been going on at the Oregon Hatchery Research Center (originally funded by BPA, but now with matching funding from the ODFW), and now at OSU’s Aquatic Animal Health Lab.  Environmental conditions we have been studying include crowding levels (density), feed type and feeding methods, and environmental complexity (including flowing water in circular tanks).  To date we have rejected the hypothesis that increased crowding in the hatchery increases the opportunity for domestication selection (Thompson and Blouin, 2015).  Tests of the other environmental conditions are ongoing.  

(2) The second approach has been to test candidate behavioral and physiological traits that might be under selection.  To date we have shown that fast growing families tend to be more dominant than slow growing families (Thompson and Blouin, 2016), and are currently testing whether other measures of boldness and activity correlate with family growth rate.  This is the focus of our FY 2020 SOW.

(3) In a third approach to figure out what traits are under selection, we have used genome-scan methods to try to identify genes that have responded to selection in hatcheries.  In Christie et al., (2016) we compared the genome-wide patterns of gene expression offspring of HxH, HxW, WxH and WxW crosses raised in a common environment.  We found many differentially-expressed genes between HxH and WxW fish, and showed that the difference was not a maternal effect.   Genes involved in wound healing, immunity and metabolism were over-represented in the set of differentially expressed genes, suggesting that selection in hatcheries may favor fish with enhanced scope for growth and/or ability to repair damage from aggressive interactions.  We recently did a genome-wide association analysis (GWAS) on H and W steelhead from the Hood River, the Wenatchee River (Ford et al., 2016) and Little Sheep Creek (Berntson et al., 2011).  We found no genomic regions that were significantly associated with having been through a hatchery in any dataset, although the Omy5 chromosomal inversion was a weak outlier in the Hood River (unpub. data).  The Omy5 inversion is interesting, as the polymorphism is associated with variation in growth rate and residency/anadromy (Miller et al., 2012; Pearse et al., 2014).  So this result warrants further exploration.  Nevertheless, the lack of obvious, major-effect loci suggests that whatever genetic variation is under selection is probably polygenic in origin, owing to many genes of small effect rather than one or a few of large effect.  This is not a surprising result, but it was important to ask the question.  Finally, we have done gene expression analysis (RNAseq) on siblings of the families whose growth rate we quantified in the lab.  We found no individual genes that significantly predict growth, but the power of such tests is low.  We are now attempting to determine if any gene expression networks (correlated expression patterns among many genes) show any obvious trends, and if those networks mirror what is observed in comparisons between offspring of HxH versus WxW parents.  

REFERENCES CITED
Araki, H. and M.S. Blouin. 2005. Unbiased estimation of relative reproductive success of different groups: evaluation and correction of bias caused by parentage assignment errors. Molecular Ecology, 13:4907-4110.

Araki, H., W.R. Ardren, E. Olsen, B. Cooper and M.S. Blouin. 2007a. Reproductive success of captive-bred steelhead trout in the wild: evaluation of three hatchery programs in the Hood River. Conservation Biology 21:181-190.

Araki, H., R.S. Waples, W.R. Ardren, B. Cooper and M.S. Blouin. 2007b. Effective population size of steelhead trout: influence of variance in reproductive success, hatchery programs, and genetic compensation between life-history forms. Molecular Ecology 16:953-966

Araki, H., R.S. Waples and M.S. Blouin. 2007c. A potential bias in the temporal method for estimating Ne in admixed populations under natural selection. Molecular Ecology 16: 2261–2271

Araki, H., B. Cooper and M.S. Blouin. 2007d. Genetic effects of captive breeding cause a rapid, cumulative fitness decline in the wild. Science 318: 100-103.

Araki, H., B. Berejikian, M. Ford, and M.S. Blouin. 2008 Fitness of hatchery-reared salmonids in the wild. Evolutionary Applications 1:342-355.

Araki, H., B. Cooper and M.S. Blouin. 2009. Carry-over effect of captive breeding reduces reproductive fitness of wild-born descendents n the wild. Biology Letters doi: 10.1098/rsbl.2009.0315

Berejikian, B. A., and M. J. Ford. 2004. Review of the Relative Fitness of Hatchery and Natural Salmon. U.S. Dept. Commer., NOAA Tech. Memo. NMFS-NWFSC-61. 28 p. Northwest Fisheries Science Center, Seattle, WA.

Berntson, E. A., R.W. Carmichael, M. W. Flesher, E. J. Ward, and P. Moran. 2011. Diminished reproductive success of steelhead from a hatchery supplementation program (Little Sheep Creek, Imnaha Basin, Oregon). Transactions of the American Fisheries Society 140: 685–698.

Blouin, M.S. V. Thuillier, B. Cooper, V. Amarasinghe, L. Cluzel, H. Araki and C. Grunau. 2010. No evidence for large differences in genomic methylation between wild and hatchery steelhead trout (Oncorhynchus mykiss). Canadian Journal of Fisheries and Aquatic Sciences. 67: 217-224.

Christie, M., M. Ford and M.S. Blouin. 2014.  On the reproductive success of early-generation hatchery fish in the wild.  Evolutionary Applications, 7:883-896.

Christie, M. R., M. L. Marine, R. A. French, and M. S. Blouin. 2012a. Genetic adaptation to captivity can occur in a single generation. Proc Natl Acad Sci U S A 109:238-242.

Christie MR, RA French, ML Marine and MS. Blouin. 2012b Effective size of a wild salmonid population is greatly reduced by hatchery supplementation.  Heredity, 109, 254–260

Christie MR, RA French, ML Marine and MS. Blouin. 2012c Effective size of a wild salmonid population is greatly reduced by hatchery supplementation.  Heredity, 109, 254–260

Christie MR, RA French, ML Marine and MS. Blouin. 2013a. Does inbreeding cause the reduced fitness of captive-born individuals in the wild? J. Heredity, doi: 10.1093/jhered/est076

Christie MR, Tennessen JA, Blouin MS 2013b. Bayesian parentage analysis with systematic accountability of genotyping error, missing data, and false matching. Bioinformatics 10.1093/bioinformatics/btt039

Christie, M.R., M.L. Marine and M.S. Blouin. 2011. Who are the missing parents? Grandparentage analysis identifies multiple sources of gene flow into a wild population. Molecular Ecology, 20, 1263–1276

Christie, MR, ML Marine, SE Fox, RA French and MS Blouin. 2015. A single generation of domestication heritably alters expression at hundreds of genes.  Nature Communications doi:10.1038/ncomms10676

Christie MR, McNickle GG, French RA, and Blouin MS. 2018. Life history variation is maintained by fitness trade-offs and negative frequency-dependent selection. Proceedings of the National Academy of Sciences.  https://doi.org/10.1073/pnas.1801779115

Ford,  M., A. Murdoch, and S. Howard. 2012. Early male maturity explains a negative correlation in reproductive success between hatchery spawned
salmon and their naturally spawning progeny. Conservation Letters. DOI: 10.1111/j.1755-263X.2012.00261.x

Ford MJ, Murdoch AR, Hughes MS, Seamons TR, and LaHood ES. 2016. Broodstock History Strongly Influences Natural Spawning Success in Hatchery Steelhead (Oncorhynchus mykiss). PLoS ONE 11(10).

Miller MR, Brunelli JP, Wheeler PA, Liu S, Rexroad CE, Palti Y, Doe CQ, and Thorgaard GH. 2012. A conserved haplotype controls parallel adaptation in geographically distant salmonid populations. Molecular Ecology 21(2):237-249.

Pearse DE, Miller MR, Abadía-Cardoso A, and Garza JC. 2014. Rapid parallel evolution of standing variation in a single, complex, genomic region is associated with life history in steelhead/rainbow trout. Proceedings of the Royal Society B: Biological Sciences 281(1783).

Thompson, NF and MS Blouin 2015. The effects of high rearing density on the potential for domestication selection in hatchery culture of steelhead (Oncorhynchus mykiss).  Canadian Journal of Fisheries and Aquatic Sciences.  72:1-6.

Thompson NF, Blouin MS. 2016. Family dominance level measured during the fry stage weakly influences family length at smolting in hatchery reared steelhead (Oncorhynchus mykiss). Transactions of the American Fisheries Society 145: 1282-1289.

Thompson, NF, M Christie, M. Marine, L. Curtis and M.S. Blouin.  2016 Spawn date explains variation in growth rate among families of hatchery reared Hood River steelhead (Oncorhynchus mykiss). Environmental Biology of fishes 99:581-591.  

Thompson NF, Clemens BJ, Ketchum LL, Simpson PC, Reagan RE, and Blouin MS. 2018. Family influence on length at release and size-biased survival post release in hatchery-reared steelhead: A mechanism to explain how genetic adaptation to captivity occurs. Aquaculture 491:135-146.


  
Account Type(s):
Expense
Contract Start Date:
11/01/2019
Contract End Date:
10/31/2020
Current Contract Value:
$175,000
Expenditures:
$175,000

* Expenditures data includes accruals and are based on data through 28-Feb-2025.

BPA CO:
BPA COR:
Env. Compliance Lead:
Contract Contractor:
Work Order Task(s):
Contract Type:
Release
Pricing Method:
Cost Reimbursement (CNF)
MarkerMarkerMarkerMarkerMarkerMarker
30 km
20 mi
Click the map to see this Contract's location details.

No photos have been uploaded yet for this Contract.

Full Name Organization Write Permission Contact Role Email Work Phone
Michael Blouin Oregon State University Yes Contract Manager blouinm@science.oregonstate.edu (541) 737-2362
Sandy Cobb Oregon State University No Administrative Contact sandy.cobb@oregonstate.edu (541) 737-9585
Lisa Dexter Bonneville Power Administration Yes Contracting Officer lldexter@bpa.gov (503) 230-3893
Edward Gresh Bonneville Power Administration Yes Env. Compliance Lead esgresh@bpa.gov (503) 230-5756
Kristen Jule Bonneville Power Administration Yes F&W Approver krjule@bpa.gov (503) 230-3588
Maureen Kavanagh Bonneville Power Administration Yes COR makavanagh@bpa.gov (503) 230-4272
Virginia Weis Oregon State University No Supervisor weisv@science.oregonstate.edu (541) 737-3705


Viewing 10 of 10 Work Statement Elements
Sort Order
WSEV ID
WE ID
Work Element Name
Title
Description
WSE Effective Budget
% of Total WSE Effective Budget
WSE Start
WSE End
A211147185Produce CBFish Status ReportPeriodic Status Reports for BPAThe Contractor shall report on the status of milestones and deliverables in Pisces. Reports shall be completed either monthly or quarterly as determined by the BPA COTR. Additionally, when indicating a deliverable milestone as COMPLETE, the contractor shall provide metrics and the final location (latitude and longitude) prior to submitting the report to the BPA COTR.$3,0001.71%01/01/202010/31/2020
B211148165Produce Environmental Compliance DocumentationCategorical ExclusionCategorical Exclusion Applied (from Subpart D, 10 C.F.R. Part 1021): B3.3: Field and laboratory research, inventory, and information collection activities that are directly related to the conservation of fish or wildlife resources and that involve only negligible habitat destruction or population reduction.$3,0001.71%11/01/201910/31/2020
C211149119Manage and Administer ProjectsProject/Contract AdministrationAdministrative work in support of on the ground efforts and in support of BPA's programmatic requirements such as metric reporting, financial reporting (e.g. accruals), and development of SOW package (includes draft and final SOW, budget and property inventory).$28,00016.00%11/01/201910/31/2020
D211150157Collect/Generate/Validate Field and Lab DataGenetics lab work - prep for microsatellite genotyping of steelheadMICROSATELLITE GENOTYPING We expect to have approximately 2000 fish to sort back into families during this granting period. These are from an experiment using 15 families of Siletz River fish that we set up at OSU’s Aquatic Animal Health Lab (AAHL) in Spring of 2019 to test the correlation between family growth rate and the behavior of each family. Once the growth rate fish have achieved a sufficient size, we will genotype all the fish to sort them back into families.$15,0008.57%11/01/201910/31/2020
E211151162Analyze/Interpret DataMicrosatellite genotyping of steelheadStandard parentage analysis on the microstatellite data in order to sort fish from the growth rate tanks back into their families of origin.$00.00%11/01/201910/31/2020
F211152157Collect/Generate/Validate Field and Lab DataBehavior assaysBEHAVIOR TRIALS One way to learn what traits might be under selection in hatcheries is to raise families to measure their growth, and then measure various physiological and behavioral traits on their siblings. Then one can determine if among-family variation in any of those traits correlates with performance in the hatchery. Any traits that show such a correlation are likely under selection because larger smolts at release have a higher probability of survival at sea. We also predict that offspring of HxH crosses would differ from offspring of WxW crosses in the same traits, and in the predicted direction (e.g. if within a fish type (HxH vs. WxW), bolder families perform best in the hatchery, then we expect HxH families to be bolder, on average, than WxW families). To date we have shown via behavior trials that steelhead families scored as more dominant also grew slightly faster in the main tanks (Thompson and Blouin, 2016). We also observed that preference for being high or low in the water column, and quickness to feed at the surface, showed strong family effects in preliminary experiments (unpub. data). We will test whether variation in these traits predicts variation among families in growth rate. Traits such as quickness to feed, and propensity to be near the surface can all be manifestations of variation in general fearfulness/anxiety, which has been well characterized in fish as the shyness/boldness behavioral syndrome (Conrad et al., 2011). Reduced anxiety/fearfulness is an almost universal outcome of domestication in vertebrates (Price, 2002), and it has been suggested that the high-food, high-density, predator-free environment of a hatchery selects for generalized boldness (Huntingford, 2004; Sundström et al., 2004; Huntingford & Adams, 2005; Salonen & Peuhkuri, 2006). Such selection could then explain the reduced reproductive success of hatchery fish in the wild, as the boldness that served them well in captivity becomes a liability for their offspring in the low-food, predator-filled wild environment (Biro et al., 2004, 2007). For example, several studies showed domesticated salmon stocks feed more readily, and are more susceptible to, or less fearful of, predators than wild stocks (e.g. Johnsson and Abrahams, 1991; Biro et al., 2004; Huntingford, 2004; Houde et al., 2010; Jackson and Brown, 2011). Hatchery masu salmon also showed greater propensity to feed near the surface (Reinhardt, 2001), in addition to reduced fear of predators and greater feeding rates (Yamamoto and Reinhardt, 2003) than wild stocks. Such behavioral change is not limited to salmonids. Domesticated zebrafish showed a higher degree of surface orientation, a reduced startle response, and higher growth rate in the lab than wild zebrafish (Robison and Rowland, 2011). It was also shown that zebrafish selected for swimming at the front of the tank (nearest to the observer) also swam higher in the water column, and fed more quickly as a correlated response to selection (Oswald et al., 2013). So there appears to be a suite of genetically correlated traits in fish, including surface orientation, that all change together in response to selection for any one of them. Other vertebrates deliberately selected for reduced fear of humans also show correlated responses in a variety of other behavioral and physiological traits, similar to what is observed in fish (e.g. foxes: Trut et al., 2009; wild jungle fowl: Agnvall et al., 2015). So what we are observing in steelhead may be a very general phenomenon in vertebrates. Studying the extent to which steelhead hatcheries select for particular behaviors (especially along the boldness/shyness axis), and how that might affect the survival of their offspring in the wild, is now the main focus of our work. For this year (summer 2020) we plan to follow up on preliminary studies we did in the summers of 2018 and 2019. We plan to set up 10-20 full-sib families of steehead in replicate tanks to measure their growth, as done previously for other experiment s (e.g Thompson and Blouin 2016; Thompson and Blouin, 2015). The number of families we can use, and their source, will depend on availability of broodstock from our collaborating hatcheries (Trask hatchery for the Wilson River stock, Alsea hatchery for the Siletz stock). If they have enough eggs for their production goals and can spare extra, we will include wild broodstock (WxW). If not, we will use F1 fish (we assume there will still be genetic variation for the traits of interest, even if the fish have been through one generation of selection. There is certainly plenty of variation among families in growth rate). Ideally, we would be able to use 10 WxW pairs and 10 HxH pairs and also compare the two types of fish, but the final availability of W and H fish is hard to predict. If we can get enough eggs from the hatchery, we will also put siblings of the experimental fish into the artificial streams at the OHRC to see if family boldness is negatively correlated with growth and/or survival in a “wild” environment. This experiment depends on the streams being available in 2020, which may not be the case if proposed modifications to the dam upstream of the facility come to pass. For each family, we will conduct a series of behavioral tests to measure various correlates of generalized boldness. The first is propensity to feed at the surface in the days after yolk absorption. Here we set up groups of 15 fry per family, in triplicate, and each time they are fed we count the number of nose-pokes to the surface in a 2 minute period. In 2018 we set up a preliminary test of this trait, and found striking variation among families – some readily feed at the surface en masse, while some families linger at the bottom and wait for food to fall. We are currently replicating that experiment. We are also assaying several aspects of boldness (e.g. aggression towards other fish, position in water column, quickness to feed) on individually-marked fish in mixed-family groups. Here we are using twelve glass tanks in which we have mixed-family groups consisting of one fish per family. All fish in each tank are individually marked with fluorescent tags, and we are quantifying the behavior of each individual fish during feeding in order to get family averages across the 12 tanks. We will repeat this experiment in summer of 2020. From these data we will determine if surface feeding by each family as assayed in single-family groups predicts what one sees in mixed-family groups. We will also see if any combination of behaviors we can quantify on each family in the mixed-family behavior tanks predicts the performance (growth) of their siblings in the large grow-out tanks. REFERENCES Agnvall B, Katajamaa R, Altimiras J, and Jensen P. 2015. Is domestication driven by reduced fear of humans? Boldness, metabolism and serotonin levels in divergently selected red junglefowl (Gallus gallus). Biol Letters 11(9):20150509. Biro PA, Abrahams MV, and Post JR. 2007. Direct manipulation of behaviour reveals a mechanism for variation in growth and mortality among prey populations. Animal Behaviour 73(5):891-896. Biro, PA, MV Abrahams, JR Post and EA Parkinson. 2004. Predators select against high growth rates and risk-taking behaviour in domestic trout populations. Proceedings: Biological Sciences 271:1554-2233 Conrad JL, Weinersmith KL, Brodin T, Saltz JB, and Sih A. 2011. Behavioural syndromes in fishes: a review with implications for ecology and fisheries management. Journal of Fish Biology 78(2):395-435. Houde ALS, Fraser DJ, and Hutchings JA. 2010. Reduced anti-predator responses in multi-generational hybrids of farmed and wild Atlantic salmon (Salmo salar L.). Conserv Genet 11(3):785-794. Huntingford FA. 2004. Implications of domestication and rearing conditions for the behaviour of cultivated fishes. Journal of Fish Biology 65(s1):122-142. Huntingford F, and Adams C. 2005. Behavioural syndromes in farmed fish: implications for production and welfare. Behaviour 142(9-10):1207-1221. Jackson CD, and Brown GE. 2011. Differences in antipredator behaviour between wild and hatchery-reared juvenile Atlantic salmon (Salmo salar) under seminatural conditions. Can J Fish Aquat Sci 68(12):2157-2166. Johnsson JI, and Abrahams MV. 1991. Interbreeding with Domestic Strain Increases Foraging under Threat of Predation in Juvenile Steelhead Trout (Oncorhynchus mykiss): An Experimental Study. Can J Fish Aquat Sci 48(2):243-247. Oswald ME, Singer M, and Robison BD. 2013. The Quantitative Genetic Architecture of the Bold-Shy Continuum in Zebrafish, Danio rerio. PLoS ONE 8(7):e68828. Price EO. 2002. Animal Domestication and Behavior. New York: CABI Publishing. 297 p. Reinhardt UG. 2001. Selection for Surface Feeding in Farmed and Sea-Ranched Masu Salmon Juveniles. Transactions of the American Fisheries Society 130(1):155-158. Robison BD, and Rowland W. 2005. A potential model system for studying the genetics of domestication: behavioral variation among wild and domesticated strains of zebra danio (Danio rerio). Can J Fish Aquat Sci 62(9):2046-2054. Salonen A, and Peuhkuri N. 2006. The effect of captive breeding on aggressive behaviour of European grayling, Thymallus thymallus, in different contexts. Animal Behaviour 72(4):819-825. Sundström LF, Petersson E, Höjesjö J, Johnsson JI, and Järvi T. 2004. Hatchery selection promotes boldness in newly hatched brown trout (Salmo trutta): implications for dominance. Behavioral Ecology 15(2):192-198. Thompson, NF and MS Blouin 2015 The effects of high rearing density on the potential for domestication selection in hatchery culture of steelhead (Oncorhynchus mykiss). Canadian Journal of Fisheries and Aquatic Sciences. 72:1-6. Thompson NF, Blouin MS. 2016. Family dominance level measured during the fry stage weakly influences family length at smolting in hatchery reared steelhead (Oncorhynchus mykiss). Transactions of the American Fisheries Society 145: 1282-1289. Trut L, Oskina I, and Kharlamova A. 2009. Animal evolution during domestication: the domesticated fox as a model. Bioessays 31(3):349-360. Yamamoto T, and Reinhardt UG. 2003. Dominance and predator avoidance in domestic and wild masu salmon Oncorhynchus masou. Fisheries Science 69:88-94.$80,00045.71%11/01/201910/31/2020
G211153162Analyze/Interpret DataBehavior assays analysisAnalysis of the family-level correlation between quantified behavior of each family and family growth rate will occur in FY 2021 when we have the family growth rate data. In the meantime, we will quantify each measure of behavior for each family, and describe variation as the percentage of total variation among individuals (or replicates for behaviors assayed in groups of sibs) that is distributed among families in order to identify traits having the strongest family component.$10,0005.71%11/01/201910/31/2020
H211154157Collect/Generate/Validate Field and Lab DataSet up growth rate experimentWe plan is to estimate the growth rate of each family in replicate 3-foot circular tanks raised under two conditions at the AAHL (four replicate tanks per treatment). The two conditions are standard broadcast feeding on the surface versus automated feeders. The automated feeder treatment reduces interaction with humans. We hypothesize that bolder families will have an advantage in standard broadcast feeding because they will feed more readily in the presence of a human, but that their advantage will diminish in the automated feeder treatment. We anticipate ~15 families, and around 20 fish per family per tank. Of course, how many families we can get, and from what river, tends to vary yearly depending on the returns each of the hatcheries we work with get that year, so experimental design changes may occur. Any major changes to this design will be coordinated with the BPA COR. At the end of the grow-out period the fish will be microsatellite genotyped and sorted back into full-sibling families. Note that these fish will be set up to grow as part of this year’s (Fy20) experiments, but will need to be genotyped as part of the subsequent (FY21) year’s work.$30,00017.14%11/01/201910/31/2020
I211155162Analyze/Interpret DataAnalysis of growth rate dataFry from this year's growth experiment will be put in mixed-family groups, and reared together in replicate tanks for up to 9 months, well into FY 2021. So there will be no data to analyze in FY 2021. In FY 2021 we will take down the tanks, measure the size of each fish and sort them back into families via microsatellite genotyping (as in work elements D and E of this year, which involve analysis of experiments started last year). For the fish started in Spring of 2019, we will sort them back into families and estimate average family size and percentage of variation distributed among families.$2,0001.14%11/01/201910/31/2020
J211156132Produce Progress (Annual) ReportSubmit Progress Report for the period January 1, 2019 to December 31, 2019The progress report summarizes the project goal, objectives, hypotheses (for research), completed and uncompleted deliverables, problems encountered, lessons learned, and long-term planning. Examples of long-term planning include future improvements, new directions, or any ramping up or ramping down of contract components or of the project as a whole. RM&E Technical Progress reports must conform to BPA guidelines. See the "RME Technical Reporting" link at: http://www.cbfish.org/Help.mvc/GuidanceDocuments.$4,0002.29%11/01/201906/15/2020
      
$175,000
   

Deliverable Title WSE Sort Letter, Number, Title Start End Concluded
Complies with NEPA B: 165. Categorical Exclusion 10/31/2020 12/01/2019
All administrative tasks shall be fulfilled on time and with quality products. C: 119. Project/Contract Administration 10/31/2020 10/31/2020
microsatellite genotyping D: 157. Genetics lab work - prep for microsatellite genotyping of steelhead 10/31/2020
sort growth rate fish into families E: 162. Microsatellite genotyping of steelhead 10/31/2020
Quantify behavior of each family G: 162. Behavior assays analysis 10/31/2020 10/31/2020
Successfully set up growth rate experiments I: 162. Analysis of growth rate data 10/31/2020 10/31/2020
Completed Annual Report J: 132. Submit Progress Report for the period January 1, 2019 to December 31, 2019 06/15/2020 06/23/2020

Viewing of Implementation Metrics
Loading...
Sort Order
WE ID
Work Element Name
Title
Description
Metric ID
Metric
End Fiscal Year
Planned
Actual
Contractor Comments
All Measures
Annual Progress Report Measures
Populations
Viewing of Environmental Metrics Customize
Loading...
WSE ID
WSE Start
WSE End
WE ID
Title
WSE Progress
Study Plan
Protocol
Category
Subcategory
Focus 1
Focus 2
Specific Metric Title

Primary Focal Species Work Statement Elements
Steelhead (Oncorhynchus mykiss) - All Populations
  • 3 instances of WE 157 Collect/Generate/Validate Field and Lab Data
  • 2 instances of WE 162 Analyze/Interpret Data
Steelhead (O. mykiss) - Lower Columbia River DPS (Threatened)
  • 1 instance of WE 162 Analyze/Interpret Data

Sort WE ID WE Title NEPA NOAA USFWS NHPA Has Provisions Inadvertent Discovery Completed
A 185 Periodic Status Reports for BPA
B 165 Categorical Exclusion
C 119 Project/Contract Administration
D 157 Genetics lab work - prep for microsatellite genotyping of steelhead 09/04/2019
E 162 Microsatellite genotyping of steelhead
F 157 Behavior assays 09/04/2019
G 162 Behavior assays analysis
H 157 Set up growth rate experiment 09/04/2019
I 162 Analysis of growth rate data
J 132 Submit Progress Report for the period January 1, 2019 to December 31, 2019