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Optimising harvest strategies over multiple objectives and stakeholder preferences

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Abstract Natural resource management has long recognised that the multi-objective nature of management is important, but has struggled to operationalise this into quantitative, measurable objectives for functional use in management.… Click to show full abstract

Abstract Natural resource management has long recognised that the multi-objective nature of management is important, but has struggled to operationalise this into quantitative, measurable objectives for functional use in management. Operationalising broader ecological and social objectives has been particularly problematic. In fisheries management, the focus has mainly been on target species sustainability and, in the past few decades, on profitability. However, multi-objective management is now essential as fisheries have become recognised as complex social-ecological-systems. Policy and legislation demand a move towards quantitative approaches for reconciling multiple objectives and operationalising these within harvest strategies. We present a quantitative, non-commensurable-unit approach, via a multi-indicator value function with explicit objective preference weights. We use a simulation to set Total Allowable Catches (TACs) for three main species groups in a reef line fishery in Australia's Great Barrier Reef. Our method enables stakeholders to consider a richer range of tradeoffs than is possible with bio-economic models. Moreover, it allows the formal evaluation of performance across alternative stakeholder group preferences, providing an impartial way to obtain an overall optimum TAC. The simulation requires extensive fishery data and requires the performance indicators associated with each objective to be quantitatively and defensibly defined. Thus, our approach provides a pathway forward that forces managers and stakeholders to confront the associated data requirements.

Keywords: optimising harvest; multiple objectives; management; strategies multiple; harvest strategies

Journal Title: Ecological Modelling
Year Published: 2020

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