The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Patrick A Hanchin - One of the best experts on this subject based on the ideXlab platform.
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estimating walleye sander vitreus movement and Fishing Mortality using state space models implications for management of spatially structured populations
Canadian Journal of Fisheries and Aquatic Sciences, 2016Co-Authors: Seth J Herbst, Bryan S Stevens, Daniel B Hayes, Patrick A HanchinAbstract:Fish often exhibit complex movement patterns, and quantification of these patterns is critical for understanding many facets of fisheries ecology and management. In this study, we estimated movement and Fishing Mortality rates for exploited walleye (Sander vitreus) populations in a lake-chain system in northern Michigan. We developed a state-space model to estimate lake-specific movement and fishery parameters and fit models to observed angler tag return data using Bayesian estimation and inference procedures. Informative prior distributions for lake-specific spawning-site fidelity, Fishing Mortality, and system-wide tag reporting rates were developed using auxiliary data to aid model-fitting. Our results indicated that postspawn movement among lakes was asymmetrical and ranged from approximately 1% to 42% per year, with the largest outmigration occurring from the Black River, which was primarily used by adult fish during the spawning season. Instantaneous Fishing Mortality rates differed among lakes and ...
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Estimating walleye (Sander vitreus) movement and Fishing Mortality using state-space models: implications for management of spatially structured populations
Canadian Journal of Fisheries and Aquatic Sciences, 2016Co-Authors: Seth J Herbst, Bryan S Stevens, Daniel B Hayes, Patrick A HanchinAbstract:Fish often exhibit complex movement patterns, and quantification of these patterns is critical for understanding many facets of fisheries ecology and management. In this study, we estimated movement and Fishing Mortality rates for exploited walleye (Sander vitreus) populations in a lake-chain system in northern Michigan. We developed a state-space model to estimate lake-specific movement and fishery parameters and fit models to observed angler tag return data using Bayesian estimation and inference procedures. Informative prior distributions for lake-specific spawning-site fidelity, Fishing Mortality, and system-wide tag reporting rates were developed using auxiliary data to aid model-fitting. Our results indicated that postspawn movement among lakes was asymmetrical and ranged from approximately 1% to 42% per year, with the largest outmigration occurring from the Black River, which was primarily used by adult fish during the spawning season. Instantaneous Fishing Mortality rates differed among lakes and ranged from 0.16 to 0.27, with the highest rate coming from one of the smaller and uppermost lakes in the system. The approach developed provides a flexible framework that incorporates seasonal behavioral ecology (i.e., spawning-site fidelity) in estimation of movement for a mobile fish species that will ultimately provide information to aid research and management for spatially structured fish populations.
Steven J D Martell - One of the best experts on this subject based on the ideXlab platform.
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a new likelihood for simultaneously estimating von bertalanffy growth parameters gear selectivity and natural and Fishing Mortality
Canadian Journal of Fisheries and Aquatic Sciences, 2005Co-Authors: Nathan Taylor, Carl J Walters, Steven J D MartellAbstract:Gear selectivity and the cumulative effects of size-selective Fishing produce bias in the length-at-age samples used to estimate the von Bertalanffy growth parameters. In fished populations, fast-growing young fish and slow-growing old fish are overrepresented in sizeage samples. To account for such effects, we treated size-at-age observations as multinomial samples, with expected catches in each sizeage category dependent on growth parameters, growth variation, size selectivity, abundance at age, and the history of exploitation. Using simulated data sets, estimated growth parameters using the multinomial likelihood were unbiased when Fishing Mortality was not too high and the shape of the vulnerability function was correct. In contrast, estimated growth parameters using a least squares approach overestimated the metabolic growth coefficient (K) and underestimated mean asymptotic length (L∞). Models that do not explicitly account for the effects of Fishing and size selectivity underestimated L∞ and over...
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A new likelihood for simultaneously estimating von Bertalanffy growth parameters, gear selectivity, and natural and Fishing Mortality
Canadian Journal of Fisheries and Aquatic Sciences, 2005Co-Authors: Nathan Taylor, Carl J Walters, Steven J D MartellAbstract:Gear selectivity and the cumulative effects of size-selective Fishing produce bias in the length-at-age samples used to estimate the von Bertalanffy growth parameters. In fished populations, fast-growing young fish and slow-growing old fish are overrepresented in sizeage samples. To account for such effects, we treated size-at-age observations as multinomial samples, with expected catches in each sizeage category dependent on growth parameters, growth variation, size selectivity, abundance at age, and the history of exploitation. Using simulated data sets, estimated growth parameters using the multinomial likelihood were unbiased when Fishing Mortality was not too high and the shape of the vulnerability function was correct. In contrast, estimated growth parameters using a least squares approach overestimated the metabolic growth coefficient (K) and underestimated mean asymptotic length (L∞). Models that do not explicitly account for the effects of Fishing and size selectivity underestimated L∞ and overestimated K. We estimate growth parameters for northern pikeminnow (Ptychocheilus oregonensis) as an example of the method and document a stunted "pigmy" population with an L∞ of 175-mm fork length, attributing its small size to effects of high density and (or) a short growing season.
Simon Jennings - One of the best experts on this subject based on the ideXlab platform.
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A data-limited approach for estimating Fishing Mortality rates and exploitation status of diverse target and non-target fish species impacted by mixed multispecies fisheries
ICES Journal of Marine Science, 2019Co-Authors: Nicola D. Walker, Bernardo Garcia-carreras, Will J.f. Le Quesne, David Maxwell, Simon JenningsAbstract:Abstract Most towed-gear bottom-trawl fisheries catch several target and myriad non-target species with the same gears at the same time. Differences in species’ exposure and sensitivity to Fishing Mortality lead to diverse outcomes in terms of population status. We develop and apply a data-limited approach for estimating Fishing Mortality rates and exploitation status of all species impacted by a mixed fishery. The approach requires (i) estimates of Fishing Mortality F by species based on area swept by towed gears, gear efficiency, and modelled species’ distributions and (ii) estimation of spawning potential ratio (SPR), by species, from cross-species relationships between maximum body size and other life history parameters. Application in the North Sea reveals per cent SPR (%SPR) (reproductive output per recruit at estimated F/reproductive output at F=0) by species ranges from 2.4 to 99.3. For 10% of species, including 57% of elasmobranchs, %SPR < 20 (a limit reference point), while for 17% of species 20 < %SPR < 40, and for 72% %SPR > 40 (implying relatively high and sustainable yield and low risk of population collapse). Applications of the approach include community-wide stock status assessment, state of environment reporting, risk assessment, and evaluating effects of changes in Fishing distribution and intensity.
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Gauging the impact of Fishing Mortality on non-target species
ICES Journal of Marine Science, 2000Co-Authors: John G. Pope, Dave S. Macdonald, Niels Daan, Jd Reynolds, Simon JenningsAbstract:The most obvious effect of Fishing on non-target species is direct Mortality. To quantify this effect on the vulnerability of species requires measurement of the current Fishing Mortality rate and of the tolerance of the species to Fishing Mortality. These are difficult to estimate for the little-studied non-target species. We describe two potential methods for estimating current Fishing Mortality rate when data are limited. Their application is illustrated for dab (Limanda limanda) and grey gurnard (Eutrigula gurnardus), two common non-target species in the North Sea. We also develop approaches to define tolerance levels for Fishing Mortality for little-studied and rare species, based on the potential jeopardy level: the Fishing Mortality that causes a reduction in spawning stock biomass per recruit relative to the unexploited situation. We propose that for non-target species, models founded on basic knowledge of life history parameters, and on generally established relationships between these parameters, may offer the only practical approach
Seth J Herbst - One of the best experts on this subject based on the ideXlab platform.
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estimating walleye sander vitreus movement and Fishing Mortality using state space models implications for management of spatially structured populations
Canadian Journal of Fisheries and Aquatic Sciences, 2016Co-Authors: Seth J Herbst, Bryan S Stevens, Daniel B Hayes, Patrick A HanchinAbstract:Fish often exhibit complex movement patterns, and quantification of these patterns is critical for understanding many facets of fisheries ecology and management. In this study, we estimated movement and Fishing Mortality rates for exploited walleye (Sander vitreus) populations in a lake-chain system in northern Michigan. We developed a state-space model to estimate lake-specific movement and fishery parameters and fit models to observed angler tag return data using Bayesian estimation and inference procedures. Informative prior distributions for lake-specific spawning-site fidelity, Fishing Mortality, and system-wide tag reporting rates were developed using auxiliary data to aid model-fitting. Our results indicated that postspawn movement among lakes was asymmetrical and ranged from approximately 1% to 42% per year, with the largest outmigration occurring from the Black River, which was primarily used by adult fish during the spawning season. Instantaneous Fishing Mortality rates differed among lakes and ...
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Estimating walleye (Sander vitreus) movement and Fishing Mortality using state-space models: implications for management of spatially structured populations
Canadian Journal of Fisheries and Aquatic Sciences, 2016Co-Authors: Seth J Herbst, Bryan S Stevens, Daniel B Hayes, Patrick A HanchinAbstract:Fish often exhibit complex movement patterns, and quantification of these patterns is critical for understanding many facets of fisheries ecology and management. In this study, we estimated movement and Fishing Mortality rates for exploited walleye (Sander vitreus) populations in a lake-chain system in northern Michigan. We developed a state-space model to estimate lake-specific movement and fishery parameters and fit models to observed angler tag return data using Bayesian estimation and inference procedures. Informative prior distributions for lake-specific spawning-site fidelity, Fishing Mortality, and system-wide tag reporting rates were developed using auxiliary data to aid model-fitting. Our results indicated that postspawn movement among lakes was asymmetrical and ranged from approximately 1% to 42% per year, with the largest outmigration occurring from the Black River, which was primarily used by adult fish during the spawning season. Instantaneous Fishing Mortality rates differed among lakes and ranged from 0.16 to 0.27, with the highest rate coming from one of the smaller and uppermost lakes in the system. The approach developed provides a flexible framework that incorporates seasonal behavioral ecology (i.e., spawning-site fidelity) in estimation of movement for a mobile fish species that will ultimately provide information to aid research and management for spatially structured fish populations.
Nathan Taylor - One of the best experts on this subject based on the ideXlab platform.
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a new likelihood for simultaneously estimating von bertalanffy growth parameters gear selectivity and natural and Fishing Mortality
Canadian Journal of Fisheries and Aquatic Sciences, 2005Co-Authors: Nathan Taylor, Carl J Walters, Steven J D MartellAbstract:Gear selectivity and the cumulative effects of size-selective Fishing produce bias in the length-at-age samples used to estimate the von Bertalanffy growth parameters. In fished populations, fast-growing young fish and slow-growing old fish are overrepresented in sizeage samples. To account for such effects, we treated size-at-age observations as multinomial samples, with expected catches in each sizeage category dependent on growth parameters, growth variation, size selectivity, abundance at age, and the history of exploitation. Using simulated data sets, estimated growth parameters using the multinomial likelihood were unbiased when Fishing Mortality was not too high and the shape of the vulnerability function was correct. In contrast, estimated growth parameters using a least squares approach overestimated the metabolic growth coefficient (K) and underestimated mean asymptotic length (L∞). Models that do not explicitly account for the effects of Fishing and size selectivity underestimated L∞ and over...
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A new likelihood for simultaneously estimating von Bertalanffy growth parameters, gear selectivity, and natural and Fishing Mortality
Canadian Journal of Fisheries and Aquatic Sciences, 2005Co-Authors: Nathan Taylor, Carl J Walters, Steven J D MartellAbstract:Gear selectivity and the cumulative effects of size-selective Fishing produce bias in the length-at-age samples used to estimate the von Bertalanffy growth parameters. In fished populations, fast-growing young fish and slow-growing old fish are overrepresented in sizeage samples. To account for such effects, we treated size-at-age observations as multinomial samples, with expected catches in each sizeage category dependent on growth parameters, growth variation, size selectivity, abundance at age, and the history of exploitation. Using simulated data sets, estimated growth parameters using the multinomial likelihood were unbiased when Fishing Mortality was not too high and the shape of the vulnerability function was correct. In contrast, estimated growth parameters using a least squares approach overestimated the metabolic growth coefficient (K) and underestimated mean asymptotic length (L∞). Models that do not explicitly account for the effects of Fishing and size selectivity underestimated L∞ and overestimated K. We estimate growth parameters for northern pikeminnow (Ptychocheilus oregonensis) as an example of the method and document a stunted "pigmy" population with an L∞ of 175-mm fork length, attributing its small size to effects of high density and (or) a short growing season.