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A | 189650 | 165 | Produce Environmental Compliance Documentation | Produce Environmental Compliance Documentation | Obtain Federal, Tribal, State, and Local permits necessary to complete the project work elements. Inform BPA environmental compliance officer of all permits. | $3,191 | 1.04% | 03/01/2019 | 02/29/2020 |
B | 189652 | 159 | Transfer/Consolidate Regionally Standardized Data | Acquire and format 2018 Fall Walleye Indexing Netting (FWIN) data from Co-managers | The Lake Roosevelt Co-Managers implemented a standardized index sampling of the Lake Roosevelt walleye population in 2002 - Fall Walleye Index Netting (FWIN) - to monitor population status and trends. The FWIN program has been implemented annually since its inception. Burbot are captured as by-catch in FWIN gill nets. In 2013, we conducted an analysis of the 10-year FWIN data set to determine if it can be used to monitor Lake Roosevelt burbot population status and trends with appropriate statistical power. The results indicated that FWIN is adequate for monitoring burbot population status and trends, with some uncertainty about size and age representation. In 2018, we will continue to monitor population status and trends by analyzing the FWIN data set with the addition of the 2018 data set.
In order to analyze the full data set, we will need to acquire the 2018 FWIN data from the other project partners - Washington Department of Fish and Wildlife (WDFW) and the Spokane Tribe of Indians (STOI) - and format it. Formatting will require extracting the burbot data, adding the age data (see WE F), conducting QA/QC, and arranging it for import in to statistical software programs. Colville Tribe's biological staff will acquire and format the 2017 FWIN data set. | $7,500 | 2.45% | 03/01/2019 | 05/31/2019 |
C | 189653 | 157 | Collect/Generate/Validate Field and Lab Data | Supplemental sampling to investigate age bias and burbot maturity | Age Bias
Despite the demonstrated utility of FWIN as a tool for Lake Roosevelt Burbot stock assessment, there is a need to evaluate the size and associated age selectivity of the gill net gear and maturity assessments. Size selectivity of fishing gear can bias estimates of size structure, growth and mortality and thus should be evaluated in any stock assessment program (McCombie and Fry 1960; Jensen 1982; Rudstam et al. 1984; Willis et al. 1985; Colombo et al. 2008; Gwinn et al. 2010). Gears with parabolic (bell-shaped) size selectivity curves, such as some gill nets, overestimate the proportion of faster growing young fish and slower growing adult fish in the population (Hovgård and Lassen 2000; Gwinn et al. 2010). The relative lack of small/young and large/old Burbot in the Lake Roosevelt FWIN catch (Bennett and Steinhorst 2014), and rapid growth of young (= age 4) Burbot and slow growth of older (> age 4) Burbot in the 2010 FWIN catch (Knudson et al. 2014), suggest that FWIN gill nets are size selective. Thus, length and age based indices calculated using FWIN data may be biased.
Age bias resulting from gill net selectivity can be corrected by applying the proportion of fish of each age within each length bin to the bias-corrected length data (see WE H regarding analysis of gill net size selectivity from the FWIN data). However, due to the lack of small (young) and large (old) fish in the FWIN catch, the proportions obtained would be based on small sample sizes. To increase sample sizes of small (young) and large (old) Burbot, supplemental sampling with alternative gears can be conducted. Multiple fishing gears are often employed in an attempt to represent the full range of sizes and ages within a population (Yeh 1977; Shoup et al. 2003; Colombo et al. 2008). To this end, we will conduct supplemental sampling using towed trawls and mid-water Bongo nets (to capture small fish) and modified cod traps (large fish) – both of which have been used to sample Burbot populations (Spence 2000; Prince 2007; Jackson et al. 2008; Stapanian et al. 2008). We do not intend to use the supplemental sampling to directly estimate FWIN gill net size selectivity, as we will not devote funds to evaluating the selectivity of the supplemental gears. The sole purpose of the supplemental sampling is to improve the estimated proportions of Burbot of each age within each length bin underrepresented in the FWIN gill net catch and apply them to the length bias-corrected catch to calculate unbiased age-based stock assessment indices.
Sampling Strategy
CCT biologists and technicians will complete a pilot effort of up to 10 trawl tows, 10 Bongo net tows, and 80 overnight modified cod trap sets in the spring and fall in an attempt to capture age classes not represented in the FWIN data set. The set locations for cod traps will be selected using a spatially balanced general random tesselation stratified (GRTS) design (Stevens and Olsen 2004). The sample area fished with the pots will be limited to those areas of the reservoir that have a depth <30 m and a bottom slope <45 degrees (100%). Cod traps will be baited with fresh fish (likely walleye).
CCT biologists and technicians will collect biological data from the catch in both gear types in a manner that is consistent with that collected from burbot during the FWIN survey. Data will include total length (mm), weight (g), sex, and gonad weight. Otoliths will be collected for aging, All fish will be examined by ultrasound to determine sex and the size of the gonads will be measured. Additional (i.e., not sampled during the standard FWIN survey) biological samples to be collected from a sub-sample (approximately 50 males and 50 females) will include blood plasma and gonad tissue to confirm sex and maturity assessments generated by ultrasound. Otoliths will be aged by CCT Biologists and technicians - see WE F. Blood plasma will be analyzed for endocrine markers (estrogen and testosterone) and gonad tissue will be examined histologically to confirm state of maturity by a qualified subcontractor - see WE G.
CCT biologists and technicians will enter all of the data into an electronic database and prepare it for analysis. The entered data will be reviewed for quality assurance and quality control (QA/QC).
REFERENCES
Abrahamse, M.S. 2009. Abundance and structure of burbot Lota lota populations in lakes and reservoirs of the Wind River Drainage, Wyoming. M.S. Thesis. University of Wyoming, Laramie.
Askey, P.J., J.R. Post, E.A. Parkinson, E.e Rivot, A.J. Paul, and P.A. Biro. 2007. Estimation of gillnet efficiency and selectivity across multiple sampling units: a hierarchical Bayesian analysis using mark-recapture data. Fisheries Research 83:162-174.
Bennett, D.H., and R.K. Steinhorst. 2014. An assessment of the utility of fwin sampling for burbot in Lake Roosevelt, Washington: does FWIN sampling work for burbot? Annual Progress Report (2013) to Bonneville Power Administration, Portland, Oregon. Project No. 2008-115-00.
Colombo, R.E., Q.E. Phelps , J.E. Garvey , R.C. Heidinger, and T. Stefanavage. 2008. Gear-specific population demographics of channel catfish in a large Midwestern river. North American Journal of Fisheries Management 28:241-246.
Gardunio, E.I., C.A. Myrick, R.A. Ridenour, R.M. Keith, and C.J. Amadio. 2011. Invasion of illegally introduced burbot in the upper Colorado River Basin, USA. Journal of Applied Ichthyology 27:36-42.
Gwinn, D.C., M.S. Allen, and M.W. Rogers. 2010. Evaluation of procedures to reduce bias in fish growth parameter estimates resulting from size-selective sampling. Fisheries Research 105:75-79.
Hovgård, H., and H. Lassen. 2000. Manual on estimation of selectivity for gillnet and longline gears in abundance surveys. FAO Fisheries Technical Paper. No. 397. Rome, FAO. 2000.
Jackson, J.R., A.J. VanDeValk, J.L. Forney, B.F. Lantry, T.E. Brooking, and L.G. Rudstam. 2008. Long-term trends in burbot abundance in Oneida Lake, New York: life at the southern edge of the range in an era of climate change. Pages 131-152 in V.L. Paragamian and D.H. Bennett, editors. Burbot: ecology, management, and culture. American Fisheries Society, Fisheries Management Section, Symposium 59, Bethesda, MD.
Jensen, A.L. 1982. Adjusting catch curves for gill net selection with the logistic distribution. Fisheries Research 1:155-162.
Knudson, T., E. Kittel, A. Blake, J. Seibert, and P.B. Nichols. 2014. Lake Roosevelt Fisheries Evaluation Program. Annual Progress Report (2010) to Bonneville Power Administration, Portland, OR. Project No. 1994-043-00.
McCombie, A.M., and F.E J. Fry. 1960. Selectivity of gill nets for lake whitefish, Coregonus clupeaformis. Transactions of the American Fisheries Society, 89:176-184.
Millar, R.B., and R. Holst. 1997. Estimation of gillnet and hook selectivity using log-linear models. ICES Journal of Marine Science 54:471-477.
Pierce, R.B., C.M. Tomcko, and T.D. Kolander. 1994. Indirect and direct estimates of gill-net size selectivity for northern pike. North American Journal of Fisheries Management 14:170-177.
Prince, A. 2007. East Kootenay burbot population assessment. Report to British Columbia Ministry of Environment, Nelson, British Columbia. Westslope Fisheries Ltd., Cranbrook, British Columbia.
Rudstam, L.G, J.J. Magnuson, and W.M. Tonn. 1984. Size selectivity of passive fishing gear: a correction for encounter probability applied to gill nets. Canadian Journal of Fisheries and Aquatic Sciences. 41:1252-1255.
Shoup, D.E., R.E. Carlson, R.T. Heath, and M.W. Kershner. 2003. Comparison of the species composition, catch rate, and length distribution of the catch from trap nets with three different mesh and throat size combinations. North American Journal of Fisheries Management 23:462-469.
Spence, C.R. 2000. A comparison of catch success between two styles of burbot traps in lakes. Pages 165-170 in V.L. Paragamian and D.W. Willis, editors. Burbot: biology, management, and ecology. American Fisheries Society, Fisheries Management Section, Publication Number 1, Bethesda, MD.
Stapanian, M.A., C.P. Madenjian, C.R. Bronte. M.P. Ebener, B.F. Lantry, and J.D. Stockwell. 2008. Status of burbot populations in the Laurentian Great Lakes. Pages 111-130 in V.L. Paragamian and D.H. Bennett, editors. Burbot: ecology, management, and culture. American Fisheries Society, Fisheries Management Section, Symposium 59, Bethesda, MD.
Stevens, D.L., Jr., and A.R. Olsen. 2004. Spatially balanced sampling of natural resources. Journal of the American Statistical Association 99:262-278.
Yeh, C.F. 1977. Relative selectivity of fishing gear used in a large reservoir in Texas. Transactions of the American Fisheries Society 106:309-313. | $135,700 | 44.33% | 03/01/2019 | 02/29/2020 |
D | 189654 | 157 | Collect/Generate/Validate Field and Lab Data | Age Lake Roosevelt burbot captured | CCT Biologists and technicians will age Burbot by counting annuli on otoliths acquired from the FWIN and supplemental catch. Otoliths from Burbot captured during FWIN will be provided by the participating agencies - WDFW, CCT, and STOI. Otoliths will be extracted from each individual fish, cleaned, and stored in individually labeled 0.5 mL cryogenic vials. Ototliths will be prepared for aging using the thin-section technique (Edwards et al. 2011). Otoliths will be removed from the vials, placed in a mold, cast in epoxy resin, and thin-sectioned (0.5 mm) through the center (focus) of the otolith with an IsoMet saw. Each otolith section will be lightly polished, mounted on a microscope slide, and polished again until the annuli are visible. Each section will be viewed under a dissecting microscope and a digital image will be captured. Two agers will examine each image. Per Edwards et al. (2011) ages will be "estimated by counting the alternating bands of growth. Light (hyaline) bands represent periods of fast growth and are generally wider than the dark (opaque) bands which represent periods of slow growth and together represent 1 year of growth (DeVries and Frie, 1996). The dark (opaque) bands are considered annuli and are counted to estimate the age." ANALYSIS NOTE: Age data will be included in the final 2017 FWIN data set to be analyzed in 2018. Lit Cited DeVries, D.R. and R.V. Frie. 1996. Determination of age and growth. In: Fisheries techniques, 2nd edn. B.R. Murphy and D.W. Willis (Eds). American Fisheries Society, Bethesda, Maryland, pp. 483–512. Edwards, W.H., M.A. Stapanian, and A.T. Stoneman. 2011. Precision of two methods for estimating age from burbot otoliths. J. Appl. Ichthyol. 27 (Suppl. 1):43–48. | $53,367 | 17.43% | 03/01/2019 | 02/29/2020 |
E | 189656 | 157 | Collect/Generate/Validate Field and Lab Data | Recruitment variability - investigate burbot spawning tributaries to Lake Roosevelt | In 2015 and 2016, we investigated factors responsible for the apparent recruitment variability in the Lake Roosevelt Burbot population. Multivariate statistical techniques were used to explore relationships between mean age 2 catch rate in FWIN gill nets and the abiotic and biotic conditions in the year of birth for each year class. Since the recruitment of most fish species, including Burbot, is suspected to occur during the early life stages (Cowan et al. 2000; Hardy et al. 2008), we focused our evaluation of abiotic and biotic conditions during corresponding seasons (winter-spring). Abiotic variables included hydrologic conditions (reservoir inflow, reservoir outflow, and elevation), water temperature, and turbidity. Biotic variables included primary (chlorophyll a) and secondary (zooplankton) productivity. Data for each variable examined was acquired from existing Lake Roosevelt data sets. Results indicated that recruitment was weakly related to range of reservoir elevation between the egg and pelagic larvae stages and minimum and mean temperature during incubation (Golder 2017). A shortcoming of the analysis was our lack of knowledge regarding conditions at spawning and nursery locations because these locations are unknown. As such, conditions at these areas during critical times may not have been represented in the recruitment variability analysis.
For the initial analysis we assumed that the bulk of burbot spawning and early rearing occurs within Lake Roosevelt and the reservoir data we had was representative of the conditions at those locations at those times. However, burbot can also spawn in tributary streams and rivers (Scholz and McLellan 2010). If burbot are spawning in tributaries to Lake Roosevelt, then the conditions in these locations should be included in the recruitment variability analysis.
We will determine if burbot are spawning in select tributaries to Lake Roosevelt using eDNA techniques. CCT will subcontract a qualified laboratory to develop the eDNA marker for burbot and analyze samples. The marker development costs will be split with Idaho Fish and Game. CCT biologists and technicians will collect samples (n=125) by filtering water at select tributaries (n=7; 15 sites) to Lake Roosevelt during the spawning period (Jan-Mar). We will subcontract a lab to analyze the filter samples for burbot eDNA.
If Burbot presence is detected in these locations during the spawning period, surveys will be implemented in subsequent years to collect early life stages. Ultimately, if spawning is confirmed, future evaluations of recruitment variability will include data (abiotic and biotic factors) from these specific spawning areas. | $21,143 | 6.91% | 03/01/2019 | 02/29/2020 |
F | 189657 | 162 | Analyze/Interpret Data | Analyze 2018 FWIN burbot data | We will subcontract a research scientist and biometrician to analyze the Burbot by-catch data from the Lake Roosevelt Fall Walleye Index Netting (FWIN) survey (with the 2018 data set included) to continue to monitor status and trends in relative abundance, mortality, size and age structure, condition growth, and recruitment. In addition, CCT biologists will estimate Burbot harvest potential. The objectives of the analysis are to: 1) assess trends in relative and indexed abundance of Burbot based on comparison of catch rates and proportion of positive catch; 2) estimate annual mortality of Burbot; 3) examine size and age structure of Burbot; 4) estimate body condition based on length and weight information; 5) examine growth; 6) evaluate factors influencing recruitment; 7) estimate harvest potential; and, 8) estimate the power of all statistical tests.
Index of Relative Abundance
Relative abundance of Burbot will be calculated as the proportion of the fish community sampled in each year. These proportions will be compared between years and 95% confidence intervals calculated. Next, the index of burbot abundance will be calculated by each of two methods: catch rates (number of burbot/ 24 hour net set) and the proportion of positive catch (proportion of gill nets with burbot captures). To assess trends in indexed abundance of burbot, analysis of variance (ANOVA) will be conducted. Because of the potential for high variability in catch rates and the proportion of positive catch, the assumptions of normality and homogeneity of variances will be tested. If data are determined to invalidate these assumptions, catch rates and the proportion of positive catch will be ranked and the rank values used in the analysis (Dr. Kirk Steinhorst, Personal Communication, Professor Emeritus, University of Idaho). Descriptive statistics of mean and standard deviation of catch rates and the proportion of positive catch will be presented for direct comparisons among years.
Annual Mortality
Age determinations made by CCT biologists and technicians from burbot bony structures from the Lake Roosevelt FWIN and supplemental sampling will be used to assess the age distribution and mortality of the burbot population. Annual mortality of burbot will be assessed by catch curves using both numbers of individuals and length of individuals as a function of age. Regression analysis will be conducted and the slope of these regressions would be interpreted as the instantaneous rate of total mortality and then converted to an annual rate of mortality (Everhart and Youngs 1981). Age frequency distributions will be graphically presented to show the age composition of the burbot population in Lake Roosevelt. Age composition data will be used to interpret the success of recruitment and mortality to the population.
Size, Age, Condition, and Growth
Annual growth increments will be determined from the age determinations and length measured at the time of capture. Annual growth will be determined as the difference of mean length at age from the prior year to the succeeding year.
Weight–length data provide important biological information to describe various characteristics of the population as well as providing an index of habitat quality. Length-frequency distributions will be used to examine the size composition of the burbot population within each of the geographical strata. We will use 1 cm length increments and compare the cumulative size distributions by the Kolmogorov-Smirnov test among years. Mean lengths of burbot will be compared by ANOVA among years. Similar to the catch data, tests of equality of variances and normality will determine whether transformation of lengths would be required. If significance are found (P=0.05), orthogonal contrasts will be used to identify differences among years. To compare body condition, both length and weight data will be used. We will calculate the length-weight relationship as: weight=a * (length) b where the coefficients of a and b will be determined from the regression of the log transformed weights and length. The slope of this regression will demonstrate the response of weight to increases in length and it will be compared statistically among years and to those regionally available. Also, body condition (K) will be calculated as K=weight x 105/(length)3 and also compared regionally. Additionally, relative weight will be calculated. The index of relative weight would be calculated as: relative weight = weight of individual/standard weight (Murphy and Willis 1991). For the standard weight, we will use the median weights of burbot across their range (Ws_50) which is considered the best for comparison with other populations (Abrahamse 2009). Mean relative weight will be calculated for each of the proportional stock size categories for comparison with other burbot populations within its range. Proportional stock density (PSD) provides an index of the proportion of fish in five length categories: stock, quality preferred, memorable, and trophy (Anderson and Gutreuter 1983). Minimum standardized length categories will follow those of McLellan and Hayes (2011) as proposed by Fisher et al. (1996): 20, 38, 53, 67, and 82 cm for stock, quality, preferred, memorable, and trophy length burbot. We will calculate 95% confidence intervals for each of these length categories. The length categories will be compared among years and geographical strata.
Statistical Power
The ability to detect significant differences in abundance and biological characteristics of burbot will be based on two aspects of the FWIN sampling: variability of the data and sample size. To assess the potential to detect significant differences, power analysis (Dowdy and Wearden 1991) will be used on all statistical tests. One of the important aspects of power analysis is its sensitivity to sample size. This analysis will provide information on the adequacy of the current sampling and, if inadequate, provide an estimate of the amount of effort required to detect differences between years.
Recruitment
We will investigate the factors that are responsible for the apparent recruitment variability in the Lake Roosevelt Burbot population. Multivariate statistical techniques will be utilized to explore relationships between mean age 2 C/f in FWIN gill nets and abiotic and biotic conditions in the year of birth for each year class. Since the recruitment of most fish species, including Burbot, is suspected to occur during the early life stages (Cowan et al. 2000; Hardy et al. 2008), we will focus our evaluation of the abiotic and biotic conditions during that time period (winter-spring). Abiotic variables that will be considered will include, at a minimum, hydrologic conditions (reservoir inflow, reservoir outflow, and elevation), water temperature, and turbidity. Biotic variables that will be considered will include, at a minimum, zooplankton (Cladocera, Copepoda, and Rotifera depending on availability) density and biomass. Data for each variable will be acquired from existing data sets for Lake Roosevelt and potentially the Arrow Lakes, British Columbia, Canada, which has a robust population of Burbot that may be contributing to the population in Lake Roosevelt.
Gill Net Size Selectivity
Gill net size selectivity can be estimated indirectly by fishing multiple mesh gill nets with equal effort and comparing catch frequencies within each of the mesh sizes (Millar and Holst 1997). Millar and Holst (1997) presented a maximum-likelihood approach to estimate parameters of log-linear selectivity models (Normal location, Normal scale, Gamma, Lognormal, and Bi-normal), also known as the SELECT method (Share Each Length’s Catch Total). A requirement of the SELECT method is that the catch is recorded by mesh size, which initiated in FWIN in 2014. Recording catch by mesh size is much less expensive than employing the direct estimation techniques (i.e. mark-recapture or gear comparisons). Thus, the most reasonable approach for estimating Burbot size selectivity of FWIN gill nets is through the use of the SELECT method. We will use the SELECT method to estimate size selectivity of Burbot in Lake Roosevelt FWIN gill nets and correct the length data prior to the calculation of length-based stock assessment indices.
Harvest Potential
Having determined that FWIN is generally adequate for Burbot stock assessment in Lake Roosevelt, we would like to proceed toward our goal of achieving a Burbot population that has stable abundance and is managed to provide some harvest. The desired level of Burbot harvest has not been established, but will be developed by the Lake Roosevelt Co-Managers – CCT, WDFW, and Spokane Tribe of Indians per the Lake Roosevelt Guiding Document (Lake Roosevelt Management Team 2009) – taking into consideration biological, social, and economic factors.
The primary objective of this project is to provide technical advice to the Co-Managers regarding management alternatives so that they can develop realistic fishery targets and appropriate implementation strategies. Our approach will be to estimate the harvest potential of Lake Roosevelt Burbot under current management and population characteristics using the Fishery Analysis and Modeling Simulator (FAMS) software (Slipke and Maceina 2010). Model inputs are recruitment, mortality (natural and fishing), and growth, which can all be derived from the FWIN data with some supplemental field sampling to evaluate biases - see WE E.
REFERENCES
Abrahamse, M.S. 2009. Abundance and structure of burbot Lota lota populations in lakes and reservoirs of the Wind River drainage, Wyoming. Masters Thesis. University of Wyoming, Laramie in J.G. McLellan and S.G. Hayes. 2011. Burbot stock assessment in Bead and Sullivan lakes, Pend Oreille County, Washington. Annual Progress Report to U.S. Department of Energy. Bonneville Power Administration. Portland, Oregon. Project 1997-004-00. Document No. 121540.
Anderson, R. and S.J. Gutreuter. 1983. Length, weight, and associated structural indices. Pages 282-300 in L.A. Nielsen and D.L. Johnson, editors. 1983. Fisheries techniques. American Fisheries Society, Bethesda, Maryland.
Dowdy, S. and S. Wearden. 1991. Statistics for research. 2nd Edition. John Wiley & Sons. New York.
Everhart, W.H. and W.D. Youngs. 1981. Principles of fishery science. 2nd Edition. Cornell University Press. Ithaca, New York.
Fisher, S.J., D.W. Willis, and K.L. Pope. 1996. An assessment of burbot (Lota lota) weight-length data from North American populations. Canadian Journal of Zoology 74:570 – 575.
Horton, T.B., and A.C. Strainer. 2008. Distribution and population characteristics of burbot in the Missouri River, Montana: Based on hoop net, cod trap, and slat trap captures. Pages 201-212 in V.L. Paragamian, and D.H. Bennett, editors. 2008. Burbot: Ecology, management, and culture. American Fisheries Society, Symposium 59. Bethesda, Maryland.
Hubert, W.A. 1983. Passive capture techniques. Pages 95-122 in L.A. Nielsen and D.L. Johnson, editors. 1983. Fisheries techniques. American Fisheries Society, Bethesda, Maryland.
Hubert, W.A., D. Dufek, J. Deromedri, K. Johnson, S. Roth, and. D. Skates. 2008. Burbot in the Wind River drainage of Wyoming: Knowledge of stocks and management issues. Pages 187-200 in V.L. Paragamian and D.H. Bennett, editors. 2008. Burbot: Ecology, management, and culture. American Fisheries Society, Symposium 59. Bethesda, Maryland.
Jackson, J.R. A.J. VanDeValk, J.L. Forney, B.F. Lantry, T.E. Brooking, and L.G. Rudstam. 2008. Long-term trends in burbot abundance in Oneida Lake, New York: Life at the Southern edge of the range in an era of climate change. Pages 131-154 in V.L. Paragamian and D.H. Bennett, editors. 2008. Burbot: Ecology, management, and culture. American Fisheries Society, Symposium 59. Bethesda, Maryland.
Katzman, L.M. and A. Zale. 2000. Age and growth of an unexploited burbot population in Upper Red Rock Lake, Montana. Pages 139-146 in V.L. Paragamian and D.W. Willis, editors. 2000. Burbot: Biology , ecology, and management. Number 1. Fisheries Management Section of the American Fisheries Society. Spokane, Washington.
Lake Roosevelt Management Team. 2009. Lake Roosevelt fisheries guiding document. Unpublished document submitted to the Northwest Power and Conservation Council, Portland, OR.
McLellan, J.G. and S.G. Hayes. 2011. Burbot stock assessment in Bead and Sullivan lakes, Pend Oreille County, Washington. Annual Progress Report to U.S. Department of Energy. Bonneville Power Administration. Portland, Oregon. Project 1997-004-00. Document No. 121540.
Morgan, G.E. 2002. Manual of instructions – Fall Walleye Index Netting (FWIN). Percid Community Synthesis. Diagnostics and Sampling Standards Working Group. Ontario Ministry of Natural Resources, Fish and /Wildife Branch, Peterborough, Ontario, Canada.
Mullan, J.W. 1984. Overview of artifical and natural propagation of coho salmon (Oncorhynchus kisutch) 1983. U.S. fish and Wildlife Service. Report FRI/FAO-84-4. Portland, Oregon.
Murphy, B.R. and D.W. Willis. 1991. Application of relative weight (Wr) to western warmwater fisheries. Pages 243 -248 in Proceedings of the Warmwater Fisheries Symposium I, June 4-8, 1991. Scottsdale, Arizona. USDA Forest Service, General Technical Report RM-207.
NWPPC (Northwest Power Planning Council). 1987. Columbia River Basin Fish and Wildlife evaluation program. Section 900. Resident fish. Northwest Power Planning Council. Portland, Oregon.
Paragamian, V.L. and D.H. Bennett, editors. 2008. Burbot: Ecology, management, and culture. American Fisheries Society, Symposium 59. Bethesda, Maryland.
Paragamian, V.L. and D.W. Willis, editors. 2000. Burbot: Biology , ecology, and management. Number 1. Fisheries Management Section of the American Fisheries Society. Spokane, Washington.
Slipke, J.W., and M.J. Maceina. 2010. Fishery Analysis and Modeling Simulator (FAMS 1.0) software. American Fisheries Society, Bethesda, MD. | $33,300 | 10.88% | 03/01/2019 | 02/29/2020 |
G | 189651 | 119 | Manage and Administer Projects | Manage & Administer the Lake Roosevelt Burbot Population Asessment Project | Manage the Lake Roosevelt Burbot Population Assessment project work for the Colville Confederated Tribes to ensure project work elements and milestones are completed. Prepare scope of work, equipment inventories, and budget for fiscal year 2019 Lake Roosevelt Burbot Population Assessment Project work. Prepare September accrual estimates as requested by Bonneville Power Administration. | $39,904 | 13.04% | 03/01/2019 | 02/29/2020 |
H | 189659 | 132 | Produce Progress (Annual) Report | Submit Progress Report for the period (Jan 2018) to (Dec 2018) | Examples of long-term planning include future improvements, new directions, or level of effort for contract implementation, including any ramping up or ramping down of contract components or of the project as a whole. Date range Jan to Dec 2018 will be agreed upon by the COTR and the contractor. This may or may not coincide with the contract period. For an ongoing project, a progress report covering a contract period may be submitted under the subsequent contract, if approved by the COTR.
Progress reports must conform to BPA guidelines. See the ''formatting guidelines'' link at the Technical Reports and Publications page: https://www.cbfish.org/Help.mvc/GuidanceDocuments.
If producing a technical report for this contract, a discrete experiment, or a peer-reviewed publication, use work element 183: Produce Journal Article. | $1,724 | 0.56% | 03/01/2019 | 08/31/2019 |
I | 189660 | 132 | Produce Progress (Annual) Report | Draft Progress Report for the period (Jan 2019) to (Dec 2019) | Examples of long-term planning include future improvements, new directions, or level of effort for contract implementation, including any ramping up or ramping down of contract components or of the project as a whole. Date range Jan to Dec 2019 will be agreed upon by the COTR and the contractor. This may or may not coincide with the contract period. For an ongoing project, a progress report covering a contract period may be submitted under the subsequent contract, if approved by the COTR.
Progress reports must conform to BPA guidelines. See the ''formatting guidelines'' link at the Technical Reports and Publications page: https://www.cbfish.org/Help.mvc/GuidanceDocuments.
If producing a technical report for this contract, a discrete experiment, or a peer-reviewed publication, use work element 183: Produce Journal Article. | $9,050 | 2.96% | 11/01/2019 | 02/28/2020 |
J | 189649 | 185 | Produce CBFish Status Report | Periodic Status Reports for BPA | The 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. | $1,250 | 0.41% | 07/01/2019 | 02/29/2020 |