Challenges in integrating short-term behaviour in a mixed-fishery Management Strategies Evaluation frame: a case study of the North Sea flatfish fishery

This study presents a fleet-based bioeconomic simulation model to the international mixed flatfish fishery in the North Sea. The model uses a Management Strategies Evaluation framework including a discrete choice model accounting for short-term temporal changes in effort allocation across fisheries. A simplified random utility model was used based on the expected revenue (or economic attractiveness) and two tradition parameters related to short and long term historical fishing patterns. All three parameters were significant. Even though reactions and adaptations vary between fleets, the estimated conservative behaviour of the main fleets led to only marginal effect at the stock level. The importance of accounting for fleet behaviour was then evaluated using an elasticity analysis to explore how increased weight of economic attractiveness contributes to changes in the biological output and positive increase in the economic performance of the individual fleets. This showed the existence of a window of sensitivity of the model to the behaviour assumptions. The study highlights the challenge of implementing an effort allocation model in a general framework of Management Strategies Evaluation for mixed-fisheries, and illustrates the necessary trade-offs between very detailed numerical relationships and the representation of aggregated processes

What is the value of a good map ? An example using high spatial resolution imagery to aid riparian restoration

Riparian areas contain structurally diverse habitats that are challenging to monitor routinely and accurately over broad areas. As the structural variability within riparian areas is often indiscernible using moderate-scale satellite imagery, new mapping techniques are needed. We used high spatial resolution satellite imagery from the QuickBird satellite to map harvested and intact forests in coastal British Columbia, Canada. We distinguished forest structural classes used in riparian restoration planning, each with different restoration costs. To assess the accuracy of high spatial resolution imagery relative to coarser imagery, we coarsened the pixel resolution of the image, repeated the classifications, and compared results. Accuracy assessments produced individual class accuracies ranging from 70 to 90% for most classes; whilst accuracies obtained using coarser scale imagery were lower. We also examined the implications of map error on riparian restoration budgets derived from our classified maps. To do so, we modified the confusion matrix to create a cost error matrix quantifying costs associated with misclassification. High spatial resolution satellite imagery can be useful for riparian mapping; however, errors in restoration budgets attributable to misclassification error can be significant, even when using highly accurate maps. As the spatial resolution of imagery increases, it will be used more routinely in ecosystem ecology. Thus, our ability to evaluate map accuracy in practical, meaningful ways must develop further. The cost error matrix is one method that can be adapted for conservation and planning decisions in many ecosystems