F-81-R-9, Michigan Study 230485 Revised: 2007-08 New Study: 1996-97 Name of Study: Assessment of salmonine populations and their prey in Michigan waters of Lake Michigan. A. Problem: Management of Lake Michigan salmonines, especially Chinook and coho salmon, requires an understanding of variation in stock dynamics between both predators and important prey fish (i.e., alewife, rainbow smelt, and bloaters). Collecting information through fisheryindependent sampling programs is an essential component of fisheries stock assessment and management. Specifically, there is a need to help minimize fluctuations in predator-prey levels by better understanding how variation in alewife recruitment will influence Chinook and coho salmon populations. An understanding of the status of Lake Michigan Chinook salmon, coho salmon, and prey fish stocks can be ascertained only through continuous monitoring. B. Objective: To assess the health and status of Chinook and coho salmon stocks in Lake Michigan, we will (1) evaluate the relative abundance, distribution, and biological characteristics (growth, mortality, diet composition, and clinical indicators of disease) for both hatchery and naturally reproduced Chinook and coho salmon using a fishery-independent gill net survey, (2) evaluate the abundance, biomass, and distribution of important prey fish from acoustic and midwater trawl surveys; (3) relate the variation in prey levels to Chinook and coho salmon growth, abundance, recruitment, and survival, and (4) assess the relative influence of bottom-up and top-down mechanisms on fluctuations in predator-prey interactions in Lake Michigan. C. Justification: Pacific salmon populations in Lake Michigan support an extremely popular and economically valuable recreational fishery. In 1986 and 1987, Lake Michigan anglers fished over 1 million days annually and had an economic impact on the region of from 40 to 50 million dollars (Jamsen 1990). Despite the value of the salmon fishery to the Great Lakes region, relatively little is still known about factors driving the sometimes extreme fluctuations in abundance of this valuable fishery. Given increasing demand for these species from recreational and tribal fisheries, gaps in our knowledge of salmon biology in the Great Lakes could seriously hinder our ability to develop appropriate management strategies. In the late 1980’s, unexpected events led to dramatic fluctuations in the abundance and catch of Chinook salmon in Lake Michigan. Lack of adequate forage fish and bacterial kidney disease (BKD) is believed to have caused the Chinook salmon population to crash. From this unfortunate experience, much has been added to our base of knowledge concerning Chinook and coho salmon, important prey fish, and predator-prey relations in the Lake Michigan environment. This information came as a direct result of research studies initiated to determine the cause of the population decline, to prevent further BKD/disease epidemics, and to better balance predator-prey levels. Unfortunately, a crisis was needed to precipitate what should have been routine assessment for Lake Michigan fish stocks. Only systematic monitoring of Chinook and coho salmon and their prey over a long-time period will allow managers to adjust management strategies and prevent further population crashes or wide fluctuations in predator and prey levels in Lake Michigan. Pacific salmon are not native to the Great Lakes, but their populations have become naturalized and successful management requires stock assessment information on the survival of hatchery stockings as well as contribution from natural reproduction to adjusting stocking rates, adjust regulations, and sustain fisheries. To adjust stocking rates accurately, we need information on salmon abundance relative to other species in the system, salmon mortality rates, and the amounts and composition of forage fish in F-81-R-9, Study 230485 - 2 Chinook and coho salmon diets. To have an accurate assessment of changes in salmon diets, we also need to know what types of forage are available and how abundant forage fish are (Strauss 1979; Bowen 1983). Stocking rates may also depend on the impact of disease outbreaks (other sources of natural mortality) on Lake Michigan salmon stocks. Unlike natural mortality, fishing mortality can be controlled to some degree by regulatory measures. In order to effectively implement meaningful regulations, we need to know a great deal more about salmon population dynamics in Lake Michigan. Ongoing, systematic assessments of Pacific salmon populations would provide us with an opportunity to be proactive rather than reactive in our management of these species. Long-term continuous monitoring is widely recognized as important in determining the health of animal populations. Collecting this type of long-term, consistent, fishery-independent data is an essential component of fisheries stock assessment and management (Kline 1996). The popularity and large economic value of the fishery justify this type of monitoring program for Lake Michigan Chinook and coho salmon. The field sampling for Chinook and coho salmon surveys, prey fish assessments, and evaluating ecosystem processes (bottom-up vs. top-down mechanisms) will involve a combined effort by the crew of the S/V Steelhead, use of the small vessel R/V Pimepheles, laboratory sample analysis shared among the project biologists and fishery technicians, as well as a partnership with the United States Geological Survey-Great Lakes Science Center for prey fish assessments, and multi-agency collaboration with the United States Fish and Wildlife Service, the 1836 Native American Tribes, and the states of Illinois, Indiana, and Wisconsin. D. Expected Results and Benefits: Lake Michigan fishery managers need to match stocking rates of salmonines with available forage fish production. Chinook stocking rates have been adjusted in the past in an attempt to better balance salmonine populations with their prey. Study 485 is the only open-water, fishery-independent survey designed for salmonines in the Great Lakes. The survey provides critical data to monitor changes in Chinook and coho salmon populations as well as changes in forage fish dynamics. Study 485 will help fishery managers evaluate current stocking rates and provide information on how Chinook and coho salmon populations respond to changes in our management strategies. Finally, this project will provide information on food webbased interactions (through the monitoring of forage fishes) that can be used in forecasting changes in predator-prey interactions that can impact not only the Lake Michigan food web, but ultimately, the salmonine recreational fishery. E. Background: Michigan DNR experimental sampling of Pacific salmon in Michigan’s waters of Lake Michigan began only in 1990. Objectives of Study 463 (a precursor to this study) were to monitor diet of Chinook salmon in a limited portion of the lake, and to experiment with the best methods for sampling Chinook salmon in offshore waters. In Study 485, sampling was extended in 1994 through 1997 to the entire eastern shoreline of Lake Michigan -- but still on an experimental basis. Spatial-temporal interactions in salmon abundance and abundance of important prey were not adequately addressed in previous study plans. With several years of experience in large-scale survey design and implementation for both salmonines and their prey, we are now ready to implement a comprehensive long-term monitoring program to assess predator-prey interactions for the Michigan waters of Lake Michigan. Moreover, the Lake Michigan Fish Community Objectives (FCOs) encourage locally adapted fish stocks that will benefit from natural selection, and over time will be able to adapt to the changing Lake Michigan environment (Eshenroder et al. 1995). In the FCOs, biological integrity is defined in terms of promoting the natural recruitment of native species as well as desirable, non-native anadromous species to promote self-sustaining stocks, which function through natural feedbacks of nutrient flow and predator-prey dynamics. Therefore, understanding the factors that regulate F-81-R-9, Study 230485 - 3 balance between prey production and predator demand in the Great Lakes is critical to making effective management decisions (Great Lakes Fishery Commission 1997). As a measure of progress toward meeting the Lake Michigan FCOs, there is a need to evaluate potential threats to predator-prey balance and self-sustainability (Eshenroder et al. 1995). The main criteria used to evaluate predator-prey balance are estimates of recruitment, abundance, and biomass of Chinook/coho salmon and their preferred forage fish (alewife; Claramunt et al. 2006). These measures have been identified as key uncertainties in the management of salmonines (Szalai 2003). While the populations of salmon and alewife are likely linked, the nature of this relationship is dynamic and shifts in predator-prey balance can potentially have substantial impacts on the Lake Michigan food web. Currently, stocking strategies are modified to manage for a stable fishery, but these decisions are often based on uncertain levels of predators and prey as well as a minimal understanding of mechanisms (bottom-up vs. top-down) within the Lake Michigan food web. Although Chinook salmon proved to be economically valuable and effective at maintaining reduced alewife levels, their dependence on alewives as an energy source, the necessity of continued stocking, and angler interest in large, abundant Chinook salmon created a difficult management situation that persists to this day (Madenjian et al. 2002; Jones et al. 1993). A major source of uncertainty in making effective management decisions is the variability in recruitment. In an effort to improve the understanding of alewife recruitment dynamics, Madenjian et al. (2005) modeled recruitment of age-3 alewife as a function of spawner abundance, summer water temperature, and alewife consumption by salmonines. Although this model could be used for predicting recruitment, it requires knowledge of Chinook salmon abundance during the first three years of the life of a given alewife year class. Compared to bottom trawl surveys (Madenjian et al. 2005; Brown 1972), acoustic sampling can provide a more reliable estimate of age-0 and age-1 alewife abundance. Chinook salmon management practices (stocking rate adjustments) could benefit from the ability to predict future alewife population levels from fall age-0 alewife biomass, which has been measured acoustically throughout the 1990s (Argyle et al. 1998) and 2001-present (Warner et al. 2006). Since their introduction into Lake Michigan in 1967, numbers of naturally produced Chinook salmon smolts have been estimated in five separate investigations (Carl 1982, 1984; Seelbach 1985, 1986; Zafft 1992; Hesse 1994; and Rutherford 1997). Natural reproduction has been quantified using both mark-recapture studies of hatchery-released fish and by counting outmigrating wild smolts in tributary streams (Rutherford et al. 2002). From these studies, natural production has been found to range from 0 – 7 million smolts per year (Jonas et al. 2007), and this extreme variability has led to the desire to provide more accurate estimates of natural production through a coordinated, lake-wide evaluation including the marking of all stocked Chinook salmon in Lake Michigan. Starting with the 2006 year-class, all Chinook salmon stocked in Lake Michigan will be marked. We will make the majority with oxytetracycline (OTC). Management agencies represented by Lake Michigan Committee (LMC) have initiated a baseline assessment program to evaluate the proportion of wild and stocked Chinook salmon from the OTC marking program started in 2006 using samples collected from the recreational fishery. However, these estimates will be derived from older (age 2 and 3) Chinook salmon, and these evaluations assume that stocked and wild fish grow, mature, and survive at the same rates. Because stocked and wild fish likely differ in biological characteristics, estimates of natural reproduction derived from age-2 and 3 year olds may include substantial bias in addition to detection errors (Szalai and Bence 2002). In contrast to using older age classes, estimates derived from sampling smolts or age-0 Chinook salmon can also be problematic since one assumption with mark-recapture methodology is that stocked (marked) and wild (unmarked) fish are well mixed. However, stocking is not equally distributed around the lake, and natural reproduction is F-81-R-9, Study 230485 - 4 highly concentrated on the eastern shoreline of Lake Michigan. Estimates derived using proportions from age-0 fish could be biased based on the proximity to streams with substantial natural reproduction, and it will be difficult to expand these estimates to lakewide smolt production. Therefore, we expect to minimize the aforementioned assumptions and provide a better estimate of natural reproduction by using a gill net survey of age-1 Chinook salmon. By implementing an ongoing acoustic assessment of forage fish in Lake Michigan to estimate prey fish levels along with implementing a fishery-independent survey to directly measure the abundance of Chinook and coho salmon, we will be addressing key uncertainties in predator-prey management in Lake Michigan. F. Procedures: Job 1. Survey design and coordination.–This study will establish an ongoing assessment project aimed at improving management of salmonines in Lake Michigan. For this project, we will design and implement three major survey components: (1) fishery-independent survey of pelagic salmonines, (2) lakewide acoustic-midwater trawl survey to estimate pelagic prey fishes, and (3) lakewide OTC marking program to evaluate Chinook salmon natural reproduction. These surveys provide the baseline monitoring, but additional research may be needed to fully understand mechanisms influencing fluctuations in the relationship between Chinook / coho salmon and their prey. This project will evaluate Lake Michigan predator-prey dynamics within the context that these two species have become naturalized to the Lake Michigan ecosystem and their populations appear to be fluctuating according to a “natural” predator-prey relationship. This project will complement other agency efforts by building strong partnerships, and by building a lasting collaborative framework that will allow us to gain a better understanding of specific mechanisms for regulation (bottom-up vs. top-down) of Chinook / coho salmon and their prey. Understanding predator-prey interactions will provide managers with a unique tool to make short-term predictions of predator survival and ultimately, predictions of stability in the Lake Michigan food web that support our invaluable fishery. Job 2. Conduct surveys and process samples.– a. Fishery-independent salmonine gill net survey. For the fishery-independent estimate of wild Chinook salmon, monofilament surface and suspended gill nets will be used on the S/V Steelhead because they are efficient at catching salmon in the open lake (Schneeberger et al. 2001; Claramunt et al. 2006). Chinook and coho salmon will be sampled from Statistical Districts MM-6 to MM-8 during May to August, as described in Schneeberger et al. (2001). Recent evaluations of coded-wire tag data indicate that Chinook and coho salmon tend to be distributed in the South Chippewa Basin of Lake Michigan in the late spring through mid-summer (Charlevoix Fisheries Research Station, unpublished data). It is likely that Chinook and coho salmon overwinter in the southern basin because of the warmer water temperatures and the distribution of young alewife (Warner et al. 2006). Therefore, gill nets will be set in the spring through mid-summer in southern Lake Michigan; stratification of net locations will follow the lakewide assessment plan for salmonines in Lake Michigan (Schneeberger et al. 2001). Assessment gill nets used to sample Chinook and coho salmon will be 9-m (30-ft) deep, 976-m (3,200-ft) long, graded mesh. A net will consist of four gill-net gangs that are 244-m (800-ft) sections of net composed of single, 30-m (100-ft) long panels of eight different mesh sizes (76, 89, 102, 114, 127, 140, 152, and 178-mm). Because F-81-R-9, Study 230485 - 5 the nets are bulky, the S/V Steelhead is equipped with a gill net drum similar to those used in commercial marine fisheries to lift the surface and suspended nets, and the vessel will tend the nets during sampling because they pose a potential navigational hazard. Within the southern basin of Lake Michigan, nets will be set at depths including preferred temperatures for Chinook and coho salmon (12-14 °C; Brett 1952), with the top of the suspended net set at a depth of at least 10 m (to avoid overlap with the surface net), and the bottom of the net set at the depth where water temperatures drop below 13°C to cover the range of habitat (temperature) available to Chinook and coho salmon. Target soak time for a net set is approximately four hours after sunset. b. Prey fish acoustic and midwater trawl survey. To estimate potential production of alewife, we will conduct an acoustic-midwater trawl survey following a modified design (stratified-systematic) from the initial Lake Michigan acoustic survey adopted by the Lake Michigan Committee (LMC). We will add two additional strata (north and south offshore regions) to improve estimates of age-0 production from the original three strata (north, south-central, and west) of the lakewide protocol. The locations of strata were determined from previous data using geographic distribution of alewife and the variability of fish abundance within the strata. Transects will be allocated optimally to the strata based on stratum area and variability of alewife density in each stratum. Acoustic surveys will be conducted at night during AugustSeptember on the S/V Steelhead and R/V Sturgeon. Midwater trawls will be used to identify species in fish aggregations observed with echosounders and to provide size composition data. Tows will target aggregations of fish observed in echograms while sampling and fishing locations will be chosen when there is uncertainty about the composition of fish aggregations observed acoustically. A trawl with a 5-m headrope and 6.35-mm bar mesh cod end will be fished on the S/V Steelhead, while the USGS vessel R/V Sturgeon uses a trawl with ~15-m headrope and 6.35-mm cod end. Trawl depth and net opening will be monitored using net sensors. Fish captured in midwater trawls will be measured (nearest mm) either in the field or frozen in water and measured upon return to the laboratory. Lengths of fish in large catches (>100 fish) will be taken from a random subsample. Fish will be weighed in groups (total catch weight per species, nearest 2-g) in the field or individually in the laboratory (nearest 0.1-g). Total catch weight is recorded as the sum of weights of individual species. Alewives caught in the trawls will be separated into age classes for production estimates. Rainbow smelt are assigned to two categories (<90-mm, ≥90-mm), while bloater are assigned to categories of <120-mm and ≥120-mm. Alewife will be assigned to age classes using an age-length key based on sagittal otolith age estimates. Age-length keys will be estimated for each year. c. Lakewide OTC marking program. A target sample size of 100 fish per statistical district from the gillnet survey will be used to assess biological characteristics. All fish will be measured for total length and wet body weight, and a muscle plug will be taken to evaluate body condition. Hard structures will be removed from each fish including scales for age determination and vertebrae for OTC mark detection (see below). A digital image of each bony structure will be taken to evaluate age and origin. For OTC sample processing, we will use a single calcified structure (a vertebrae), viewed with a specialized microscope that will allow for mark detection, quantification of mark fluorescence, and archival storage of an image of the mark for verification by other readers. The specialized system to detect OTC marks from vertebrae will include a microscope with a mercury vapor light (UV) of at least F-81-R-9, Study 230485 - 6 100W intensity equipped with a filter assembly that will limit wavelengths to 450490 nm. The system will include a software package capable of acquiring and saving images of the vertebrae and will be set up in a room that is dark during sample processing. Additional samples for evaluation of OTC marks / natural reproduction will be collected from the recreational fishery. These samples will be collected by Management Unit personnel (Plainwell), in coordination with “headhunters” employed through the MDNR statewide coded-wire tag recovery program (Study 230464). Study design for this phase of the assessment will follow Claramunt et al. (2007b). Samples will be processed, as described above, by Management Unit personnel (Plainwell, Bay City). Job 3. Manage data, maintain databases.–Survey and laboratory data will be entered into the MDNR Salmon - Microsoft Access database with the exception of the acoustic and midwater trawl data. Because of the size of raw acoustic data files (>30GB per year) and specialized software needed to process acoustic data, the GLSC-USGS will serve as the primary host for the acoustic data within their Oracle Database. Acoustic data will be backed up on the Charlevoix Fisheries Research Station server. Job 4. Analyze data, modeling.– a. We will evaluate the abundance, distribution, contribution of wild fish, and biological characteristics of Chinook and coho salmon (i.e., Claramunt et al. 2006, 2007a). We will compare the trends in salmon population characteristics from the long-term survey data with changes in prey fish to evaluate predator-prey interactions. b. Analyses of acoustic data will be conducted with Echoview software. Each transect will be subdivided in ~1,000 m horizontal segments that are 10 m deep. The decision to use the 1,000 m segments as the elementary sampling unit (ESU) is based on the need to balance the number of pings and targets in each cell with efforts to capture spatial variability. Trawl and acoustic data at water column depths <40 m will be linked in steps ranging from fine-scale to coarse-scale. First, acoustic data will be categorized by transect, depth layer (10-m bins), and bottom depth (10-m bins). Second, trawl data will be matched to acoustic data cells by transect, depth layer, and bottom depth category. This will provide essentially a one-to-one match by location. Subsequent steps will involve aggregation of trawl data by averaging over: 1) stratum, depth layer, and bottom depth, 2) depth layer and bottom depth, 3) depth layer, and 4) coarse depth layers corresponding to epilimnion (0-20 m depths), metalimnion (20-50 m depths), and hypolimnion (depth ≥50-m). For depths ≥40-m, we will assume that acoustic targets >-45 decibels (dB) are large bloater (TeWinkel and Fleischer 1999) and those smaller are large rainbow smelt (Parker-Stetter et al. 2006). Mean mass of fish in these cells will be estimated using the equations of Fleischer et al. (1997) and Rudstam et al. (2003). Acoustic density estimates for each transect will be made for two groups: all targets and those that corresponded to fish targets. An estimate of absolute density (including all targets) is made using the formula (1) Total density (#ha 1 ) 10 4 ABC F-81-R-9, Study 230485 - 7 where 104 = conversion factor (m2·ha-1), ABC = area backscattering coefficient (m2·m2) and = the mean backscattering cross section (m2) of all targets between -60 and -30 dB (a range including all fish catchable with the midwater trawls). The estimate from equation 1 will provide density for all targets. To maintain consistency with acoustic surveys of Lake Michigan in the 1990s (Argyle et al. 1998), targets <60 dB will be excluded. To accomplish this, density of fish targets will be estimated by multiplying total density (equation 1) by the proportion of the total number of targets that are between -60 and -20 dB. This threshold should include targets corresponding to the smallest YOY alewives (2-3 cm) at most orientations based on in situ TS-length relations (-60 to -52 dB) published by Warner et al. (2002). This threshold likely results in underestimation of rainbow smelt density given expected target strengths published by Rudstam et al. (2003). Numeric densities (fish/ha) of the different species will also be estimated as the product of fish density and the proportion by number in the catch at that location. Total alewife, smelt, and bloater density will be subdivided into size or age classspecific density by multiplying total density for these species by the numeric proportions in each age group. Biomass density (kg/ha) for the different groups will then be estimated as the product of density and species or age-specific mean mass as determined from trawling (except as described for depths ≥40-m). Mean and relative standard error (RSE = (SE/mean) x 100) for density and biomass in the survey area will be estimated using stratified cluster analysis methods featured in the statistical routine SAS PROC SURVEYMEANS (SAS Institute Inc. 2004). Cluster sampling techniques are appropriate for acoustic data, which represent a continuous stream of autocorrelated data (Williamson 1982; Connors and Schwager 2002). Density and biomass values for each ESU in each stratum will be weighted by dividing the stratum area (measured using GIS) by the number of ESUs in the stratum. c. Analysis of OTC marking data will follow procedures described in detail in Szalai and Bence (2002), Claramunt et al. (2007b), and in the MDNR internal procedure document “Common Elements of Lake Michigan and Lake Huron evaluation of Chinook salmon natural reproduction, using OTC marking”. Analyses will be completed and reported on through a collaboration between MDNR Research and Management Sections (Charlevoix, Plainwell), in coordination with the Lake Michigan Salmonid Working Group (LMC). Job 5. Write annual performance report.–Annual progress reports will be prepared according to the established Federal Aid timeline and format. Job 6. Write other reports.–Data and results from this study will also be used in reports to the Lake Michigan Committee (e.g., annual lake committee reports, state-of-the-lake five year assessments), MDNR Fisheries Research Reports, and manuscripts for publication in scientific journals. Job 7. Evaluate surveys.–Survey designs and data management procedures will be evaluated to insure that study objectives are met and data are collected efficiently and are reliable. Procedures will be evaluated periodically in terms of adequacy, necessity, reliability, and improved efficiency. F-81-R-9, Study 230485 - 8 G. Schedule/Budget1: Proposed work Job 1 Job 2 Job 3 Job 4 Job 5 Job 6 Job 7 Survey design and coordination Conduct surveys and process samples Manage data and maintain database Analyze data, modeling Write annual performance report Write other reports Evaluate surveys Associated travel and other expenses Totals 1 2007-08 2008-09 2009-10 2010-11 2011-12 10,398 84,345 17,207 7,161 11,298 5,251 NA 7,089 10,918 88,562 18,067 7,519 11,863 5,514 NA 7,443 11,464 92,990 18,970 7,895 12,456 5,790 NA 7,815 12,037 12,639 97,640 102,522 19,919 20,915 8,290 8,705 13,079 13,733 6,080 6,384 NA 2,897 8,206 8,616 142,749 149,886 157,380 165,251 176,411 NA = not scheduled H. Geographical Location: Data will be collected from Michigan waters of Lake Michigan and analyzed at the Charlevoix Great Lakes Fisheries Research Station, Charlevoix, Michigan, with the exception of work completed by partners (e.g., GLSC-USGS acoustic survey) as indicated above. I. Personnel: Randall M. Claramunt (principal investigator), Fisheries Research Biologist; David F. Clapp, Charlevoix Fisheries Research Station manager; Charlevoix Fisheries Research Station technicians and crew of the S/V Steelhead; Fisheries Division Management Unit personnel (Plainwell, Bay City). Literature Cited: Argyle, R. L., G. W. Fleischer, G. L. Curtis, J. V. Adams, and R. G. Stickel. 1998. An integrated acoustic and trawl based prey fish assessment strategy for Lake Michigan. A report to the Illinois Department of Natural Resources, Indiana Department of Natural Resources, Michigan Department of Natural Resources, and Wisconsin Department of Natural Resources. U.S. Geological Survey, Biological Resource Division, Great Lakes Science Center, 1451 Green Road, Ann Arbor, MI USA. Brett, J. R. 1952. Temperature tolerance in young Pacific salmon, genus Oncorhynchus. Journal of the Fisheries Research Board of Canada 9: 265-323. Brown, E. H., Jr. 1972. Population biology of alewives, Alosa pseudoharengus, in Lake Michigan, 1949–70. Journal of the Fisheries Research Board of Canada 29:477–500. Bowen, S. H. 1983. Quantitative description of the diet. Pages 325-336 in L. A. Nielsen and D. L. Johnson, editors. Fisheries Techniques. American Fisheries Society, Bethesda, Maryland. Carl, L. M. 1982. Natural reproduction of coho salmon and chinook salmon in some Michigan streams. North American Journal of Fisheries Management 4:375-380. Carl, L. M. 1984. Chinook salmon density, growth, mortality, and movement in two Lake Michigan tributaries. Canadian Journal of Zoology 62: 65-71. F-81-R-9, Study 230485 - 9 Claramunt, R.M., D.F. Clapp, and J.R. Bence. 2007a. in press. Using a fishery-independent gill net survey to evaluate relative abundance and biological characteristics of Chinook salmon in Lake Michigan, 1990-2002. North American Journal of Fisheries Management. Claramunt, R.M., and eight co-authors. 2007b. Annual work plan for estimating wild production of Chinook salmon Oncorhynchus tshawytscha from oxytetracycline marking. Lake Michigan Technical Committee, Salmonid Working Group, internal report. Claramunt, R. M., B. Breidert, D. F. Clapp, R. F. Elliott, C. P. Madenjian, P. Peeters, S. R. Robillard, D. M. Warner, G. Wright. 2006. Status of Chinook salmon in Lake Michigan, 1985-2005. Annual report to the Great Lakes Fishery Commission, Ann Arbor, MI. Connors, M.E., and S.J. Schwager. 2002. The use of adaptive cluster sampling for hydroacoustic surveys ICES Journal of Marine Science 59: 1314-1325. Eshenroder, R.L., M.E. Holey, T.K. Gorenflo, and R.D., Clark, Jr. 1995. Fish community objectives for Lake Michigan. Great Lakes Fishery Commission Special Publication 95-3. 56pp. Available: www.glfc.org/pubs/SpecialPubs/Sp95_3.pdf. Fleischer, G.W., R.L. Argyle, and G.L. Curtis. 1997. In situ relations of target strength to fish size for Great Lakes pelagic planktivores. Transactions of the American Fisheries Society 126: 786-794. Great Lakes Fishery Commission (GLFC). 1997. A Joint Strategic Plan for Management of Great Lakes Fisheries (Supersedes 1994 version). Ann Arbor, Michigan. Available: www.glfc.org/fishmgmt/jsp97.htm. Hesse, J. A. 1994. Contribution of hatchery and natural chinook salmon to the eastern Lake Michigan sport fishery, 1992-1993. Master’s Thesis, Michigan State University, East Lansing, Michigan. Jamsen, G. 1990. Economics. Pages 195-209 in M. Keller, K. D. Smith, and R. Rybicki, editors. Review of salmon and trout management in Lake Michigan. Michigan Department of Natural Resources, Fisheries Special Report 14, Ann Arbor. Jonas, J. L., R. M. Claramunt, and E. S. Rutherford. 2007. Salmonine reproduction and recruitment. In The state of Lake Michigan in 2005. Edited by D. F. Clapp and W. Horns. Great Lakes Fishery Commission Special Publication In press. Jones, M. L., J. F. Koonce, and R. O'Gorman. 1993. Sustainability of hatchery-dependent salmonine fisheries in Lake Ontario: the conflict between predator demand and prey supply. Transactions of the American Fisheries Society 122: 1002–1018. Kline, L. 1996. Fisheries research under fire: more than just a money issue. Fisheries 21(6):4. Madenjian, C. P., G. L. Fahnenstiel, T. H. Johengen, T. F. Nalepa, H. A. Vanderploeg, G. W. Fleischer, P. J. Schneeberger, D. M. Benjamin, E. B. Smith, J. R. Bence, E. S. Rutherford, D. S. Lavis, D. M. Robertson, D. J. Jude, and M. P. Ebener. 2002. Dynamics of the Lake Michigan food web, 1970–2000. Canadian Journal of Fisheries and Aquatic Sciences 59: 736–753. Madenjian, C. P., T. O. Hook, E. S. Rutherford, D. M. Mason, T. E. Croley II, E. B. Szalai, and J. R. Bence. 2005. Recruitment variability of alewives in Lake Michigan. Transactions of the American Fisheries Society 134: 218-230. F-81-R-9, Study 230485 - 10 Parker-Stetter, S.L., L.G Rudstam, J.L. Stritzel Thomson and D.L. Parrish. 2006. Hydroacoustic separation of rainbow smelt (Osmerus mordax) age groups in Lake Champlain. Fisheries Research 82:176-185. Rudstam, L.G., S.L. Parker, D.W. Einhouse, L. Witzel, D.M. Warner, J. Stritzel, D.L. Parrish, and P. Sullivan. 2003. Application of in situ target strength to abundance estimations in lakes- examples from rainbow smelt surveys in Lakes Erie and Champlain. ICES Journal of Marine Science 60: 500-507. Rutherford, E. S. 1997. Evaluation of natural reproduction, stocking rates, and fishing regulations for steelhead Oncorhynchus mykiss, chinook salmon O. tshawytscha, and coho salmon in Lake Michigan. 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