Abstract:The management strategy evaluation (MSE) approach was used to evaluate management strategies based on the current method of stock assessment for rock lobster (Jasus edwardsii) off Victoria, Australia, and decision rules inferred from the management plan for Victorian rock lobster and past practice when selecting total allowable catches, TACs. The results are expressed in terms of whether it is possible to keep stocks above limit reference points with high probability and recover overexploited stocks to the tar… Show more
“…There are a number of empirical studies specifically designed to examine the implications of stock structure uncertainty (IWC 1994;Dichmont et al 2006;Kell et al 2009;Punt & Hobday 2009), and while none have considered explicit economic implications, the work contained in this paper adds to the research that ignoring spatial structureboth demographic and fishery relatedcan have a profound impact. We found that the assumptions made about stock structure not only resulted in different bioeconomic TRPs (generally, smaller steady-state effort from the multistock models) but also different economic outcomes, although little evidence of differences in conservation-related outcomes was found.…”
Summary1. Bioeconomic models are increasingly used to provide benchmarks for harvest levels in wildlife and natural resource management, yet uncertainties related to model structure are underexplored. We investigate the importance of a range of uncertainties with a focus on model structure and life histories when estimating bioeconomic target reference point (TRPs) and assess the policy implications of ignoring these uncertainties. 2. We use three contrasting case studies to investigate the interactions between model, observational and process errors related to life-history parameters: the short-lived Japanese common squid Todarodes pacificus and Pacific saury Cololabis saira, and the slow-growing Patagonian toothfish Dissostichus eleginoides. We developed a simulation framework to test the harvest strategies resulting from bioeconomic TRPs under various assumptions about model structures and parameters. 3. We found the relative importance of different types of uncertainties affecting precision and accuracy of the model outputs varied according to the life-history traits. Little difference in TRP estimates was found between simple vs. complex population models for saury, while large differences were found for toothfish. The assumptions made about stock structure for squid not only resulted in different TRP estimates (generally, smaller for the multistock models), but also different economic outcomes depending on the balance of effort allocation between stocks. 4. Synthesis and applications. We use models similar to those used in the actual management of three case study species to explore the effects of interacting uncertainties on the management advice. We show that the interactions between structural elements of the models lead to very different management advice, depending on the life history of the species concerned. For the long-lived toothfish, life-history and gear selectivity parameters interacted strongly. For the short-lived squid which is managed as two stocks, spatial fishing effort allocation, correlation of environmental drivers between stocks and differential stock productivity interacted, producing very poor economic performance if assumptions about stock structure are incorrect. The key message for model-based natural resource management is that it is vital to investigate the major uncertainties related to model structure, process and estimation errors simultaneously, because they interact to produce non-intuitive results.
“…There are a number of empirical studies specifically designed to examine the implications of stock structure uncertainty (IWC 1994;Dichmont et al 2006;Kell et al 2009;Punt & Hobday 2009), and while none have considered explicit economic implications, the work contained in this paper adds to the research that ignoring spatial structureboth demographic and fishery relatedcan have a profound impact. We found that the assumptions made about stock structure not only resulted in different bioeconomic TRPs (generally, smaller steady-state effort from the multistock models) but also different economic outcomes, although little evidence of differences in conservation-related outcomes was found.…”
Summary1. Bioeconomic models are increasingly used to provide benchmarks for harvest levels in wildlife and natural resource management, yet uncertainties related to model structure are underexplored. We investigate the importance of a range of uncertainties with a focus on model structure and life histories when estimating bioeconomic target reference point (TRPs) and assess the policy implications of ignoring these uncertainties. 2. We use three contrasting case studies to investigate the interactions between model, observational and process errors related to life-history parameters: the short-lived Japanese common squid Todarodes pacificus and Pacific saury Cololabis saira, and the slow-growing Patagonian toothfish Dissostichus eleginoides. We developed a simulation framework to test the harvest strategies resulting from bioeconomic TRPs under various assumptions about model structures and parameters. 3. We found the relative importance of different types of uncertainties affecting precision and accuracy of the model outputs varied according to the life-history traits. Little difference in TRP estimates was found between simple vs. complex population models for saury, while large differences were found for toothfish. The assumptions made about stock structure for squid not only resulted in different TRP estimates (generally, smaller for the multistock models), but also different economic outcomes depending on the balance of effort allocation between stocks. 4. Synthesis and applications. We use models similar to those used in the actual management of three case study species to explore the effects of interacting uncertainties on the management advice. We show that the interactions between structural elements of the models lead to very different management advice, depending on the life history of the species concerned. For the long-lived toothfish, life-history and gear selectivity parameters interacted strongly. For the short-lived squid which is managed as two stocks, spatial fishing effort allocation, correlation of environmental drivers between stocks and differential stock productivity interacted, producing very poor economic performance if assumptions about stock structure are incorrect. The key message for model-based natural resource management is that it is vital to investigate the major uncertainties related to model structure, process and estimation errors simultaneously, because they interact to produce non-intuitive results.
“…For example, although Butterworth and Punt () commented that there were very few operating models which accounted for spatial structure when they conducted their review in 1998, subsequently Punt et al . (), IWC (,b, , ), Punt and Hobday () and Carruthers et al . () have all developed operating models which can, to some extent, account for spatial structure.…”
Management strategy evaluation (MSE) involves using simulation to compare the relative effectiveness for achieving management objectives of different combinations of data collection schemes, methods of analysis and subsequent processes leading to management actions. MSE can be used to identify a 'best' management strategy among a set of candidate strategies, or to determine how well an existing strategy performs. The ability of MSE to facilitate fisheries management achieving its aims depends on how well uncertainty is represented, and how effectively the results of simulations are summarized and presented to the decision-makers. Key challenges for effective use of MSE therefore include characterizing objectives and uncertainty, assigning plausibility ranks to the trials considered, and working with decisionmakers to interpret and implement the results of the MSE. This paper explores how MSEs are conducted and characterizes current 'best practice' guidelines, while also indicating whether and how these best practices were applied to two casestudies: the Bering-Chukchi-Beaufort Seas bowhead whales (Balaena mysticetus; Balaenidae) and the northern subpopulation of Pacific sardine (Sardinops sagax caerulea; Clupeidae).
“…In the development of management strategies, management strategy evaluation (MSE) is often used to evaluate the potential different strategies that can influence the states of fish resources and their corresponding fisheries (Punt and Hobday, 2009). The MSE simulates the behaviour of fish stocks and fishing fleets and provides the ability to forecast, with estimates of the associated uncertainty, changes in the states of the fish stock and its fishery as a consequence of management scenarios.…”
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