An effective harvest strategy using improved catch-curves

Wayte, Sally E.; Klaer, Neil

doi:10.1016/j.fishres.2010.08.012

Cited by 37 publications

(32 citation statements)

References 16 publications

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“…A2 B) that seeks to achieve a catch target of MEY based on an observation model that estimated current fishing mortality (F c ur ) from the age-structure of recent catches. The population status was determined from the equilibrium spawning biomass associated with the estimated current fishing mortality (Cordue 2012), where current fishing mortality is based on a modified catch curve analysis applied to age-composition data captured from the underlying biological model (Wayte & Klaer 2010). (3) Management control 3 set harvest levels annually based on a decision rule (Fig.…”

Section: Forecast Resultsmentioning

confidence: 99%

“…This was followed in the second step by calculating the expected value of the pay-off ; (B) current estimated fishing mortality F cur where F limit is the fishing mortality that leads to B limit and F 0.4 is the fishing mortality that leads to B 0.40 ) for management control 2 (Wayte & Klaer 2010); and (C) current estimated catch-rate for management control 3 where CPUE limit is the catch-rate corresponding to B limit and CPUE target is the catch-rate corresponding to MEY (Little et al 2011). of annual TAC against the annual landings, both scaled to the estimate of maximum sustained yield (MSY), for ten species in the SESSF: jackass morwong, blue warehou, redfish, tiger flathead, blue grenadier, pink ling, ocean perch, eastern gemfish, western gemfish, silver warehou.…”

Section: Price Calculationmentioning

confidence: 99%

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Environmental Derivatives, Risk Analysis, and Conservation Management

Little

Parslow

Fay

et al. 2013

Conservation Letters

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Two key challenges in conservation management are: (1) how to quantify and manage the risk that natural populations will fall below critical thresholds and (2) how to fund recovery plans should a population do so. Statistically estimated, process-based simulation models of two distinct fish populations are used to forecast the species population levels, and capture the risk of crossing a management defined trigger point. We show how to calculate the environmental derivative price, which is the amount a risk-neutral investor would require for promising a pay-out should the species abundance fall below the trigger level. The approach provides the potential for environmental derivatives to support species recovery, and a method for measuring the underlying "health" of a managed population and calculating risk-cost tradeoffs among alternative management strategies.

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Section: Forecast Resultsmentioning

confidence: 99%

Section: Price Calculationmentioning

confidence: 99%

Environmental Derivatives, Risk Analysis, and Conservation Management

Little

Parslow

Fay

et al. 2013

Conservation Letters

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“…In recent years, research on developing assessment techniques for data-poor fisheries has 54 increased, and a suite of tools is evolving for scientists and managers to assess and manage 55 stocks with limited data (Kelly et Klaer, 2010). However, many of these methods still require considerable amounts of data 57 from the fishery or the biology of the target species, including a time-series of historical 58 catch, catch-per-unit-effort (CPUE) trends, or information on the age structure of the stock, 59…”

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confidence: 99%

An evaluation of an iterative harvest strategy for data-poor fisheries using the length-based spawning potential ratio assessment methodology

2015

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11 Data on the length structure of exploited stocks are one of the easiest sources of 12 information to obtain for data-poor fisheries, and have the potential to provide cost-effective 13 solutions to the management of data-poor fisheries. However, incorporating the results from 14 stock assessments into a harvest strategy usually requires information on the total catch or 15 catch-per-unit effort, data that are not available for many data-poor fisheries. This paper 16 describes and tests a harvest strategy where only length composition data of the catch and 17 knowledge of basic biological parameters are available. The harvest strategy uses a recently 18 developed methodology for stock assessment that estimates the spawning potential ratio 19 (SPR) for an exploited stock from the length structure of the catch (the length-based SPR 20 model; LB-SPR), and uses an effort-based harvest control rule to iteratively drive fishing 21 pressure towards a target level of SPR (40%). A management strategy evaluation framework 22 was used to explore the behaviour of various parameterizations of the harvest control rule for 23 three species with a diverse range of life-histories and M/k ratios ranging from 0.36 (unfished 24 population dominated by large fish) to the Beverton-Holt invariant M/k of 1.5 (unfished 25 population dominated by smaller fish). The harvest strategy performed well for all three 26 species but the time taken for the SPR to stabilize at the target SPR was greatest for the oldest 27 species with the lowest M/k.

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“…As such, catch curves are instrumental tools for assessing stock status (e.g. Thorson and Prager, 2011) and informing harvest strategies (Wayte and Klaer, 2010) from a limited amount of data. For a population that is sampled in a single year, each age corresponds to a different year-class (with earlier year-classes being sampled at older ages), and mortality estimates may be valid only under the assumption of constant year-class strength (Robson and Chapman, 1961).…”

Section: Introductionmentioning

confidence: 99%

“…In reality, most of the assumptions underlying the catch-curve approach are violated (Dunn et al, 2002;Catalano et al, 2009), thus requiring modifications of the simple approach outlined above (Xiao, 2005;Schnute and Haigh, 2007;Wayte and Klaer, 2010;Thorson and Prager, 2011). One core issue that is common to all approaches utilizing catch-at-age data is that sampled individuals are pooled into discrete (integer) age-classes.…”

Section: Introductionmentioning

confidence: 99%

An individual-based approach to year-class strength estimation

Thanassekos

Latour

Fabrizio

2016

ICES Journal of Marine Science

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Estimating year-class strength-the number of larvae hatched in a given year-from survey data is key to investigating fish population dynamics. Year-class strength can be estimated from catch-at-age data using catch curves. In practice, most catch-curve assumptions are violated, which can result in spurious estimates of year-class strength. Among the simplifying assumptions is that pooling individuals into annual age-classes provides a representation of the population age structure that is adequate for estimating mortality. This oversimplification is unnecessary when age data are available at finer scales, and can lead to biased results. We present a new method to estimate past year-class strength with a set of equations that apply to each sampled individual. Through the reconstruction of individual histories from hatch to capture, this approach takes full advantage of the individual resolution of survey data, enables the incorporation of the processes that violate catch-curve assumptions, and provides more accurate year-class strength estimates.

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An effective harvest strategy using improved catch-curves

Cited by 37 publications

References 16 publications

Environmental Derivatives, Risk Analysis, and Conservation Management

Environmental Derivatives, Risk Analysis, and Conservation Management

An evaluation of an iterative harvest strategy for data-poor fisheries using the length-based spawning potential ratio assessment methodology

An individual-based approach to year-class strength estimation

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