Handel\u27s Messiah and A Christmas Celebration

Program listing performers and works performe

The Value of Research Involved in Stock Assessment

Using stock assessments to inform management and decision makers about the impacts of fishing is increasing worldwide. Stock assessments are costly to conduct well, and there is often a data management lag in terms of when data used to inform stock assessment predictions are available for inclusion in the model. Therefore, increasing the frequency of conducting stock assessments and decreasing the data management lag need to be weighed against the benefits they may generate. In this paper, we use a management strategy evaluation approach that simulates the stock assessment process from a "true" population model that is sampled with error, thus generating a stock assessment with uncertainty. We apply our approach under the US National Standard 1 guidelines under which fishery management councils are required to implement a harvest control rule that determines an annual acceptable biological catch level that achieves an acceptable probability of overfishing. The simulation model is used to evaluate a range of data acquiring decisions to determine their performance in terms of economic welfare as measured by producer and consumer surplus while achieving the predefined management target of the probability of overfishing. In particular, we are interested in the impact of the data management lag on the stability of harvest over time and its impact on fleet dynamics. An empirical application is conducted for the Mid-Atlantic summer flounder for which the 2015 stock assessment update resulted in a considerable reduction in quotas. Such an instability in catch limits could have been mitigated by more frequent assessments.Proceedings of the Eighteenth Biennial Conference of the International Institute of Fisheries Economics and Trade, held July 11-15, 2016 at Aberdeen Exhibition and Conference Center (AECC), Aberdeen, Scotland, UK

Population model estimates for oysters (Crassostrea virginica) in the Choptank and Little Choptank Rivers

Dataset: Oyster Population Model EstimatesThis data set contains estimates derived from a population model of oysters in the Choptank and Little Choptank Rivers. The methods and data used in the model are described in Damiano et al. (2019). For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/808879NSF Division of Ocean Sciences (NSF OCE) OCE-142701

Historic and Modern Lake Trout Abundance, Effects of Fishing on Lake Trout, and Dynamics of the Commercial Lake Trout Fishery in Michigan Waters of Lake Superior

For more than one hundred years Lake Superior supported one of the largest lake trout (Salvelinus namaycush) fisheries in the world. Lake trout populations in Lake Superior collapsed in the late 1950s due to the combined effects of overfishing and sea lamprey (Petromyzon marinus) predation. A binational effort to restore lake trout began with chemical control of sea lamprey, stocking of hatchery-reared lake trout, and closure of the commercial fishery. The objectives of this thesis were to compare historic and modem lake trout abundance, to quantify the effect of large mesh (>/= 114-mm stretch-measure) gill net fishing on lake trout recruitment, and to determine how the behavior of commercial lake trout fishermen changed over time. I compared historic and modern lake trout density with t-tests and Welch's approximate t-tests, and determined whether yield was an accurate index of lake trout density with linear and nonlinear regression. Modern (1984-1998) lake trout CPE was equal to or significantly higher than historic (1929-1943) CPE off Ontonagen (MI-2), in waters west of the Keweenaw Peninsula (MI-3), in Keweenaw Bay (Ml-4), off Marquette (Ml-5), and off Munising (MI-6). Relative variation in CPE was similar between historic and modern periods. Modern CPE was higher than historic CPE, because lake trout density is now higher in most areas than during 1929-194 3. Gill net yield was maintained across a wide range of lake trout densities and was best described by a saturation curve. Historic lake trout yield should not be used as the lake trout restoration goal for Lake Superior, because it is not a good index of lake trout abundance. I fit Ricker stock-recruit models with terms for parental stock size and large mesh (>/= 114-mm stretch-measure) gill net effort to lake trout CPE data for Michigan waters of Lake Superior to determine if and when recruitment overfishing occurred. Large mesh gill net effort likely suppressed lake trout recruitment in five Michigan management areas of Lake Superior. Lake trout were overexploited before 1929 near Isle Royale (MI-1), in MI-3, and in Whitefish Bay (MI-8), during 1929-1959 in MI-4, MI-5, and Mi-6, and not overexploited in MI-2 and near Grand Marais (MI-7). Historic abundance indices should not be used as lake trout restoration goals in the areas that were overfished before 1943. I examined dynamics of the commercial lake trout fishery that occurred in Michigan waters of Lake Superior during 1929-1961. The number of full-time commercial fishermen increased during 1933-1943 and decreased during 1945-1957. Increases in the number of fishermen were related to past yield, market prices, and fishing opportunities on Lake Huron. Decreases in the number of fishermen corresponded with decreases in lake trout abundance. The amount of large mesh gill net fished increased during 1929-1951. Fishermen tended to fish more net near shore as lake trout density declined even though lake trout CPE was often higher in deeper waters. The most common gill net mesh size increased over time from 114-mm to 120-mm. Mean fishing location changed in MI-1, Ml-2, MI-4, MI-5, MI-6, and MI-8. More effort was fished near shore than offshore and near shore effort was more stable over time than offshore effort. Relatively stable yield was maintained by increasing gill net effort and by moving some effort to better grounds. Abundance estimates derived from CPE may be biased high, because of changes in fishing locations within management areas and increases in mesh size over time. The yield during 1929-1943 should not be used as the lake trout restoration goal for Lake Superior, because it is probably an overestimate of maximum sustainable yield

Using censored regression when estimating abundance with CPUE data to account for daily catch limits

In fisheries where there is a limit on total catch in a given period, catch-per-unit-effort (CPUE) data may not be proportional to abundance because catches may be censored at the limit. Commonly used depletion estimators (e.g., Leslie method) could be biased when ordinary least squares (OLS) regression is used to estimate abundance with censored CPUE data. We used simulations to examine the performance of OLS regression and a censored regression approach when estimating abundance and exploitation using censored CPUE data over a range of known exploitation rates. We also applied the censored regression approach to data from a commercial fishery for the eastern oyster (Crassostrea virginica). The censored regression approach always performed better than the OLS regression when estimating abundance and exploitation in our simulations. Harvest and abundance of oysters in Fishing Bay, Maryland, increased during 2009 to 2013 and then decreased through 2016, while exploitation rates had no substantial trend over time. The censored regression approach is useful for estimating abundance and exploitation when the distribution of CPUE is affected by daily catch limits.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

A performance evaluation of surplus production models with time-varying intrinsic growth in dynamic ecosystems

We conducted a simulation study to evaluate performance of surplus production models (SPMs) with a time-varying intrinsic growth rate (SPMTVr) for stocks with predation-driven changes in productivity. Data sets were simulated using an age-structured, linked, predator-prey model of Atlantic menhaden (Brevoortia tyrannus), a forage fish native to the Northwest Atlantic, and Atlantic striped bass (Morone saxatilis), its primary predator, with differing time series of fishing mortality on both predator and prey. Simulations generated test data sets for Atlantic menhaden SPMs that included either a static or time-varying intrinsic growth rate parameter. The SPMTVr largely produced more accurate, less variable estimates of exploitation rate and biomass than models with static intrinsic growth. We also applied SPMTVr to empirical Atlantic menhaden catch and survey data for 1964-2016. The SPMTVr fit the survey data well, estimated an intrinsic growth rate time series that mirrored long-term juvenile survey trends, and produced biomass and exploitation rate trends that mirrored a statistical catch-at-age model. The SPMTVr estimated dynamic, MSY-based reference points that reflected changing stock productivity.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Business english : an individualised learning programme/ Wilberg

159 hal, : ill.; 29 cm

Valuing Changes in Frequency of Fish Stock Assessments

Updating stock assessments frequently and ensuring that the most recent fishery dependent and independent data is included is a costly endeavor. We use a management strategy evaluation for the mid-Atlantic summer flounder fishery to determine the economic returns to increasing update frequencies and decreasing the data management lag. We simulate the annual acceptable biological catch for the period 2015-2040 under a range of update frequencies and data lags. We calculate present value net economic benefits for the commercial and recreational fisheries for each scenario. Discounting, the timing of harvest quotas, species specific price flexibilities and fishing cost response to biomass and quota differences suggest that the benefits gained from frequent updating and reduction in data lags will vary by fishery. For summer flounder, we find the cost of more frequent updating (1 year versus 5 years), and reducing the data management lag (1 year versus 2 years), are more than compensated for by societal benefits generated by the fishery.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Management Evaluation for the Chesapeake Bay Blue Crab Fishery: An Integrated Bioeconomic Approach

An integrated bioeconomic model is built based on an individual-based simulation model and a stock assessment model for the Chesapeake Bay blue crab fishery. The resulting model is able to not only compare alternative management scenarios being considered by policy makers in terms of both sustainable yield (SY) and sustainable revenue (SR), but also provide insights into impacts of relevant policy factors that together form management scenarios. The preliminary regression results based on simulated management scenarios show variations in effects of different policy factors, suggesting that the fishery policies should be made accordingly

International Review Panel Presentation for the 2023 International Fisheries Stock Assessment workshop

Presentation to the International Stock Assessment Workshop, University of Cape Town, 27 November - 1 December 2023: 17pp, titled: 'International Review Panel Presentation for the 2023 International Fisheries Stock Assessment workshop'</p