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Event

Marine opportunity costs: a method for calculating opportunity costs to multiple stakeholder groups

When

Wednesday 17 June 2009, 12.00pm-1:00 pm

location
ARC Centre of Excellence Conference Room, JCU (DB44). Video-link to Centre for Marine Studies, UQ
Presenter
Vanessa Adams , James Cook University, ARC Centre of Excellence for Coral Reef Studies

Vanessa was raised in New Mexico (USA) and completed dual degrees in mathematics and a degree in biology at Washington and Lee University. She spent a year as a Fulbright scholar doing research with Prof. Hugh Possingham at University of Queensland. She is currently undertaking her PhD at James Cook University with Prof. Bob Pressey and Assoc. Prof. Natalie Stoeckl. The primary focus of her PhD is how to incorporate cost considerations in systematic conservation planning so that conservation targets can be achieved at a minimal cost (both social and economic considerations). She is interested in efficiency gains of including costs as well as uncertainties associated with the decision making process.

ABSTRACT:

A general goal of systematic conservation planning is to maximize conservation benefits while minimizing socio-economic costs.  When designing marine protected areas, most studies have assumed homogenous costs. Methods of creating heterogeneous cost layers for marine planning have included several approaches to mapping current fishing activities. These methods have typically been biased to a single fishing sector and might not give sufficient information on the tensions and tradeoffs between different stakeholder groups (e.g. trawling versus net fishery).  We expand upon current approaches by presenting a novel method for calculating the opportunity costs of conservation actions to multiple stakeholder groups, defined by catch of key species for consumption and revenue.  The first step of the method is to model species abundance of key coral reef fish species based on abundance surveys.  We compare four types of models: Poisson, Negative Binomial, Zero-inflated Poisson (ZIP), and Zero-inflated Negative Binomial (ZINB).  We provide an example of results from these four models for a species found in our study region and compare the results of each of the models.  Lastly, we discuss the next steps required to complete the opportunity cost model and outline its applications in the study region of Kubulau, Fiji.  The methods presented give an unbiased estimate of opportunity costs to multiple stakeholders in a marine environment that can be applied to any region using existing species data.  While we apply the method to species abundance data, the method can be modified for presence/absence data.  Additionally, we discuss the current status of the marine protected areas (MPAs) in Kubulau, the potential re-design of areas in this region, and the use of our opportunity cost models to ensure that future MPAs in the region are equitable to all stakeholder groups.

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