Experience in implementing harvest strategies in Australia's south-eastern fisheries

Smith, Anthony D. M.; Smith, David C.; Tuck, Geoffrey N.; Klaer, Neil; Punt, André E.; Knuckey, Ian; Prince, J.D.; Morison, A. K.; Kloser, Rudy; Haddon, Malcolm; Wayte, Sally E.; Day, Jemery; Fay, Gavin; Pribac, Fred; Fuller, Mike; Taylor, Bruce L.; Little, L. Richard

doi:10.1016/j.fishres.2008.06.006

Cited by 118 publications

(80 citation statements)

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“…A2 A) that seeks to achieve a catch target of Maximum Economic Yield (MEY; Grafton et al 2007;Smith et al 2008). The annual harvest prescribed by the decision rule is based on the estimated spawning biomass determined from Stock Synthesis (Methot & Wetzel 2013) as an embedded observation model.…”

Section: Forecast Resultsmentioning

confidence: 99%

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%

Environmental Derivatives, Risk Analysis, and Conservation Management

Little

Parslow

Fay

et al. 2013

Conservation Letters

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“…Harvest control rules define the functional response of removals to the current state of the resource as reflected by indicators or RPs (Restrepo and Powers 1999;Smith et al 2008). The decision tree ( Figure 10) and risk assessment (Tables 4, 5) suggest ways in which catch-based length proportions can be used to provide advice regarding harvest regulation within the context of existing management RPs.…”

Section: Length-based Reference Points and Harvest Control Rulesmentioning

confidence: 99%

Length‐Based Reference Points for Data‐Limited Situations: Applications and Restrictions

2009

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Current fisheries management policies generally require an assessment of stock status, which is a difficult task when population and fisheries data are limited. Three simple metrics based on catch length compositions (i.e., that reflect exclusive take of mature individuals, P mat; that consist primarily of fish of optimal size, the size at which the highest yield from a cohort occurs, P opt; and that demonstrate the conservation of large, mature individuals, P mega) can be used to monitor population status relative to exploitation. The metrics (collectively referred to as Px) were intended to avoid growth and recruitment overfishing, but there was no quantitative linkage to stock status and calculation of future sustainable catches. We attempt to make this connection by exploring the relationship of Px measures to fishing mortality and spawning biomass (SB). The relationships are compared specifically to the current target reference point (0.4 times the virgin, or unfished, SB [SB0]) and limit reference point (0.25SB0) used for the U.S. West Coast groundfish fishery by using simulations based on a deterministic age‐structured population dynamics model. Sensitivity to fishery selectivity, life history traits, and recruitment compensation (steepness) is explored. Each Px measure showed a wide range of possible values depending on fishery selectivity, steepness, and the ratio of the length at maturity (L mat) to the optimal fishing length (L opt). Although the values of Px may be compatible with sustainable fishing, these values are not always sufficient to ensure stock protection from overfishing. Moreover, values for Px cannot be interpreted adequately without knowledge of the selectivity pattern. A new measure, P obj (the sum of P mat, P opt, and P mega), is introduced to distinguish selectivity patterns and construct a decision tree for development of stock status indicators. Heuristic indicator values are presented to demonstrate the utility of this approach. Although several caveats remain, this approach builds on the recommendations of previous literature by giving further guidance related to interpreting catch length composition data under variable fishery conditions without collecting additional information. It also provides a link to developing harvest control rules that inform proactive fisheries management under data‐limited conditions.

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“…Management Strategy Evaluation is a flexible framework for modeling the entire natural resource management system, rather than just the resource stock, which has shown its potential to improve fisheries management (16,17). Even in commercial fisheries, where user motivations are more clearly profit-driven, explicit modeling of their behavior within an MSE framework can improve understanding and prediction of their responses to policy interventions.…”

Section: Discussionmentioning

confidence: 99%

“…The extension of the MSE framework so as routinely to include a harvester OM would encourage the development of these aspects and ensure that MSE has a less top-down flavor; at the moment it is seen as providing advice to help managers in their decision making, which undersells the value of the approach. By modeling the system as a whole, it is just as possible to use the MSE approach from the perspective of the resource user; taking this perspective may further enhance stakeholder engagement, which has been an important feature of real-world implementation of MSEs to date (16,17). The one major study that has included a detailed, empirically based socioeconomic component in an MSE highlighted the sensitivity of model results to harvester behavior and called for further work in this area (7).…”

Section: Discussionmentioning

confidence: 99%

Integrating fisheries approaches and household utility models for improved resource management

Milner‐Gulland

2011

Proc. Natl. Acad. Sci. U.S.A.

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Natural resource management is littered with cases of overexploitation and ineffectual management, leading to loss of both biodiversity and human welfare. Disciplinary boundaries stifle the search for solutions to these issues. Here, I combine the approach of management strategy evaluation, widely applied in fisheries, with household utility models from the conservation and development literature, to produce an integrated framework for evaluating the effectiveness of competing management strategies for harvested resources against a range of performance metrics. I demonstrate the strengths of this approach with a simple model, and use it to examine the effect of manager ignorance of household decisions on resource management effectiveness, and an allocation tradeoff between monitoring resource stocks to reduce observation uncertainty and monitoring users to improve compliance. I show that this integrated framework enables management assessments to consider household utility as a direct metric for system performance, and that although utility and resource stock conservation metrics are well aligned, harvest yield is a poor proxy for both, because it is a product of household allocation decisions between alternate livelihood options, rather than an end in itself. This approach has potential far beyond single-species harvesting in situations where managers are in full control; I show that the integrated approach enables a range of management intervention options to be evaluated within the same framework.hunting | bushmeat M anagement Strategy Evaluation (MSE) is fast becoming the dominant framework for the development and assessment of management procedures for commercial fisheries (1, 2). This powerful approach uses simulation in a virtual environment to test the robustness of potential management strategies to a range of uncertainties. Unlike traditional approaches, MSE explicitly models the whole management system; not just the resource stock and its reaction to different harvest rules, but the gathering of data, the conversion of those data into a harvest rule, and the implementation of that rule (3). This approach then allows fisheries scientists to evaluate the effects of a lack of knowledge or understanding on the performance of a range of harvest rules. The management advice that comes from MSEs is nonprescriptive and probabilistic, enabling stakeholders to evaluate the tradeoffs inherent in choosing one or other management procedure. Indeed, one of the strengths of MSE is that it can encourage the participation of stakeholders, both in defining the metrics against which the performance of harvest rules can be evaluated, and in the generation of scenarios for testing

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Experience in implementing harvest strategies in Australia's south-eastern fisheries

Cited by 118 publications

References 10 publications

Environmental Derivatives, Risk Analysis, and Conservation Management

Environmental Derivatives, Risk Analysis, and Conservation Management

Length‐Based Reference Points for Data‐Limited Situations: Applications and Restrictions

Integrating fisheries approaches and household utility models for improved resource management

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