3 research outputs found
The Influence of Stock Assessment Frequency on the Achievement of Fishery Management Objectives
<p>Because of resource limitations with respect to both funding and staff expertise, there is growing interest among fishery management agencies in moving from annual to less-frequent assessments of fish stocks. We conducted simulations based on Lake Whitefish <i>Coregonus clupeaformis</i> populations in the Laurentian Great Lakes to evaluate (1) how statistical catch-at-age assessment frequency, the time lag between data collection and assessment, and approaches to setting target harvests in the years between assessments affected the achievement of management objectives; and (2) how the outcomes were influenced by the quality of assessment data, features of the populations, and characteristics of the fisheries exploiting the populations. We found that as assessments became less frequent, relative yields were reduced and the risk of stock depletion and interannual variation in yield increased. The effects of less-frequent assessments were ameliorated in populations with greater levels of productivity and when target mortality was lower. Conversely, the effects of assessment frequency were largely insensitive to changes in recruitment variation or the quality of assessment data. A 1-year lag between data collection and assessment when assessments were conducted annually primarily affected the risk of stock depletion and the interannual variation in yield. As recruitment variation increased, relative yield also became sensitive to the 1-year lag. Approaches to setting harvest targets in years between full assessments were less important than assessment frequency, and no single approach consistently outperformed other rules. Although populations with low productivity were the most sensitive to changes in assessment frequency and the lag between data collection and assessment, the management of those populations benefited to a greater extent from implementation of an appropriate target mortality rate than from more-frequent assessments or removal of the 1-year lag.</p> <p>Received November 18, 2015; accepted March 9, 2016 Published online July 7, 2016
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Bayesian variable selection of factors explaining fish movement distance
Open-source code for MATLAB programing describing a variable
selection procedure under a Bayesian framework to explore the plausibility of
alternative linear regression models that include different explanatory variables, and
assess the associated uncertainty.
Bayesian variable selection treats the regression model itself as random
among all possible models with different sets of variables. The implementation of Bayesian
variable selection is via the reversible jump Markov chain Monte Carlo (rjMCMC) procedure.<div><div><br></div><div>Open-source code for R programing describing the use of boosted regression tree and random forest approaches are also provided to check if there are any nonlinear effects missed by Bayesian variable selections. </div></div
Contributions of Lake Erie and Lake St. Clair Walleye Populations to the Saginaw Bay, Lake Huron, Recreational Fishery: Evidence from Genetic Stock Identification
<div><p></p><p>Genetic stock identification analyses were conducted to determine spawning population contributions to the recreational fishery for Walleyes <i>Sander vitreus</i> in Saginaw Bay, Lake Huron. Two spawning population groups were considered: (1) the Tittabawassee River, which has been identified as the largest source of spawning Walleyes for Saginaw Bay; and (2) an aggregate of six spawning populations from Lake Erie and Lake St. Clair that were found to be genetically similar. Overall, the Lake Erie and Lake St. Clair spawning populations were estimated to comprise approximately 26% of the Walleye recreational harvest in Saginaw Bay during 2008–2009. Contribution levels were similar for the 2 years in which genetic samples were collected. Contributions from the Lake Erie and Lake St. Clair spawning populations to the harvest of age-5 and older Walleyes were greater during summer (31.8%; SE = 6.2%) than during late winter and spring (6.0%; SE = 3.7%). Conversely, contributions from the Lake Erie and Lake St. Clair spawning populations to the harvest of age-3 and age-4 fish were fairly similar between seasons (late winter and spring: 31.2%, SE = 6.7%; summer: 41.7%, SE = 5.6%), suggesting that younger Walleyes migrate earlier or reside in Saginaw Bay for extended periods. Our finding that one-quarter of the Saginaw Bay recreational harvest of Walleyes comprises fish from Lake Erie and Lake St. Clair has important management implications, as policies for one lake may have bearing on the other lake—one of the challenges associated with managing migratory fish species. Fisheries management in the Laurentian Great Lakes has a history of being highly coordinated and cooperative among the states and province bordering the individual lakes. Results from this study suggest that cooperation may need to be expanded to account for fish movement between lakes.</p><p>Received October 28, 2014; accepted February 11, 2015</p></div