Abstract

Fisheries researchers have focused on the value of information (VOI) in fisheries management and trade-offs since scientists and managers realized that information from different resources has different contribution in the management process. We picked seven indicators, which are log-normal annual catch observation error (Cobs), annual catch observation bias (Cbias), log-normal annual index observation error (Iobs), maximum length observation bias (Linfbias), observed natural mortality rate bias (Mbias), observed von Bertalanffy growth parameter K bias (Kbias), and catch-at-age sample size (CAA_nsamp), and built operating models (OMs) to simulate fisheries dynamics, and then applied management strategy evaluation (MSE). Relative yield is chosen as the result to evaluate the contribution of the seven indicators. Within the parameter range, there was not much information value reflected from fisheries-dependent parameters including Cobs, Cbias, and Iobs. On the other hand, for fisheries-independent parameters such as Kbias, Mbias, and Linfbias, similar tendency of the information value was showed in the results, in which the relative yield goes down from the upper bound to the lower bound of the interval. CAA_nsamp had no impact on the yield after over 134 individuals. The VOI analysis contributes to the trade-offs in the decision-making process. Information with more value is more worthy to collect in case of waste of time and money so that we could make the best use of scientific effort. But we still need to improve the simulation process such as enhancing the diversity and predictability in an OM. More parameters are on the way to be tested in order to collect optimum information for management and decision-making.

Highlights

  • Uncertainty is pervasive in natural systems and manifests itself in many forms (Morgan and Henrion, 1990; Regan et al, 2002)

  • Simulation of fishery dynamics was carried out using statespace age-structured operating models (OMs) included in DLMtool (Carruthers and Hordyk, 2018) and MSEtool (Carruthers et al, 2018), an opensource package developed within the R environment for efficient closed-loop evaluation of fishery management procedures

  • Simulation tests of catch observation error (Cobs) and index observation error (Iobs) converged well, and the patterns showed that not much information value was necessary

Read more

Summary

Introduction

Uncertainty is pervasive in natural systems and manifests itself in many forms (Morgan and Henrion, 1990; Regan et al, 2002). The role of science in conservation and management of natural resources is generally to reduce uncertainty (Halpern et al, 2006). Fisheries management falls into the category of decisionmaking under uncertainty due to the growth of adapted management. Inherent in such a task is the problem of investing in new information (Mantyniemi et al, 2009). Information comes with a cost, basically; as a result, we should find an optimum amount of valuable information in the decision-making process. The cost savings from reduced information collecting may outweigh the small potential loss in the decision accuracy of the results (Walters and Pearse, 1996; de Bruin and Hunter, 2003; Ling et al, 2006)

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call