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Management strategy evaluation: a powerful tool for conservation?

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The poor management of natural resources has led in many cases to the decline and extirpation of populations. Recent advances in fisheries science could revolutionize management of harvested stocks by evaluating management scenarios in a virtual world by including stakeholders and by assessing its robustness to uncertainty. These advances have been synthesized into a framework, management strategy evaluation (MSE), which has hitherto not been used in terrestrial conservation. We review the potential of MSE to transform terrestrial conservation, emphasizing that the behavior of individual harvesters must be included because harvester compliance with management rules has been a major challenge in conservation. Incorporating resource user decision-making required to make MSEs relevant to terrestrial conservation will also advance fisheries science.

Section snippets

Management of natural resources

The management of natural resources is a complex process driven by interactions between the dynamics of the natural system, the decision-making and behavior of stakeholders, and uncertainty at various levels of the management process and the natural system. Traditional forms of natural resource management (e.g. fixed harvest quotas) do not respond to system dynamics and uncertainty, and so are prone to failure 1, 2. Realization of the importance of learning about the dynamics of the system led

How MSE works

The MSE approach is based upon a set of models of the ‘true’ population dynamics of the species (called ‘operating model’; Figure 1, Glossary). The operating model aims at capturing the key processes in the dynamics of the fish population given the best ecological knowledge available, and can be thought of as a minimum realistic model [12].

The next step in the MSE is to simulate the process of monitoring the stock. This results in simulated measurements such as biomass or number of individuals.

Uncertainty in the management of natural resources

One of the main strengths of MSE is that it brings uncertainty center stage in the modeling process. Uncertainty plays a fundamental part in the dynamics of ecological and economic systems, in our measurement and understanding of these systems, and in the devising and implementation of rules to control harvesting. Various classifications exist, and we use those of Milner-Gulland and Rowcliffe [17]: process uncertainty comes from the variation in the system itself (e.g. weather affecting

Including the wider ecosystem

Most applications of the MSE approach have focused on harvest strategies for target species. The indirect effects of harvesting on the ecosystem are rarely incorporated into MSEs. However, this is changing as fisheries science increasingly takes an ecosystems approach (e.g. Atlantis model for south-eastern Australia 20, 21). Multi-species population models and effects on the wider ecosystem have recently been included in an MSE for a prawn fishery in Australia 22, 23. Similarly, MSEs are now

Conclusions

The only application of a comparable approach to MSE outside fisheries has been by Chee and Wintle [52], which was for management of over-abundant species. However, the MSE approach has enormous potential for exploited resources that face competing objectives and where harvester decision-making is an important consideration. The MSE approach is no longer limited to top–down management of a single species by an all-powerful manager. Work has already started to extend the MSE approach to more

Acknowledgements

NB and EJMG were supported by the European Commission under the HUNT project of the 7th Framework Program for Research and Technological Development. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use made of the information. The views expressed in this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. EJMG also acknowledges the support of a Royal Society Wolfson

Glossary

Assessment model
a mathematical model coupled to a statistical estimation process that integrates data from various sources to provide estimates of reference points and past and present abundance, mortality, and productivity of a resource.
Harvest control rule (HCR)
a set of well-defined rules used for determining management actions in the form of a total allowable catch (TAC) or allowable effort.
Harvest strategy
intended meaning may be synonymous with MP.
Implementation model
process of application

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