An Empirical Decision Tree–Based Harvest Strategy for in-Country Management of a Shared Pelagic Resource

An Empirical Decision Tree–Based Harvest Strategy for in-Country Management of a Shared Pelagic Resource

Robert A. Campbell, Jeremy D. Prince, Campbell R. Davies, Natalie A. Dowling, and Dale S. Kolody

An Empirical Decision Tree–Based Harvest Strategy for in-Country Management of a Shared Pelagic ResourceThis is part of Assessing and Managing Data-Limited Fish Stocks
PDF    
To download the free PDF [1.4 MB], please enter:
-or-

Description

Quota management systems often increase the burden for reliable stock assessments that are beyond the capacity of most fisheries. There is therefore a need to re-assess the utility to fishery assessment of simpler procedures that make greater use of indicators collected directly from the fishery. This is especially the case for data-poor fisheries. This study describes the rationale behind the development of an empirical indicator based harvest strategy for management of the Eastern Tuna and Billfish Fishery off eastern Australia. While Australian legislation requires management of this fishery against given reference points, in practice management is hampered by the distribution of the fished resources beyond the Australian jurisdiction and the shared nature of the total catch with other fishing nations. The harvest strategy is based on the use of empirical indicators (size-based catch rates and catch proportions) and the use of a multilayered decision-tree process. Implementation of the harvest strategy to one of the principal target species, broadbill swordfish, is described. The main strengths of the strategy are that it is broadly applicable to data-poor fisheries where only catch rate and size information are available, is readily understood and acceptable to stakeholder groups, and relatively easy to implement.

You might also like...

Item details