MRAG Americas. Funded by the Gordon and Betty Moore Foundation
MRAG Americas were asked to explore whether fisheries managed using catch shares score measurably differently under the Marine Stewardship Council (MSC) certification standard than those not managed using catch shares. Catch share management is where a specific proportion of the catch is allocated to individuals, groups or communities.
For MSC certification, fisheries are assessed against a setof indicators (30 Performance Indicators organised within a number of Components nested under three Principles) that evaluate different aspects of the sustainability of a fishery. The challenge is to construct a single coherent and consistent framework to assess the impact of catch share management across the whole suite of indicators.
Available data came from two different databases: MSC database of fishery scores for MSC certified fisheries and the Environmental Defence Fund’s database of fisheries under catch share programs. These are data that have had been collected for other purposes rather than with the intention of measuring the effects of the intervention of interest. Thus differences in Performance Indicators might be because of fishery characteristics such as gear type and target species rather than because of the effect of catch share management.
A two stage approach was taken:
Stage 1: The effect of catch share management was assessed for each Performance Indicator by fitting statistical models that also accounted for the challenges in the available data. In particular, the models investigated the effect of other fishery characteristics on Performance Indicator scores.
Stage 2: A Bayesian Belief Network (BBN) was constructed using the results of Stage 1 and knowledge of the overall structure of the MSC scoring system.
A BBN that can address a wide range of questions about the effect of catch share management on fisheries performance. For example, the probability of scoring highly across all three Principles, or on subsets of indicators, for fisheries with different characteristics and catch share management strategies.
The methodology is described in:
Underwood, F.M., et al., Building Bayesian Belief Networks to investigate how fishery performance responds to management interventions. Fisheries Research. (2015), http://dx.doi.org/10.1016/j.fishres.2015.12.005
The results are described in:
Parkes, G., et al., The effects of catch share management on MSC certification scores. Fisheries Research. (2015), http://dx.doi.org/10.1016/j.fishres.2015.10.003