Exploring the effect of the spatial scale of fishery management

TL;DR

This paper investigates how the spatial scale of fishery management impacts economic and ecological outcomes, emphasizing the importance of habitat distribution patterns in determining optimal management subdivision.

Contribution

It introduces a bioeconomic model to quantify effects of management scale on fishery profit, biomass, effort, and habitat protection, highlighting habitat distribution as a key factor.

Findings

Profit increases linearly with segments if habitats are random.

Profit increases with diminishing returns if habitats are autocorrelated.

Optimal management scale depends on habitat distribution and subdivision costs.

Abstract

For any spatially explicit management, determining the appropriate spatial scale of management decisions is critical to success at achieving a given management goal. Specifically, managers must decide how much to subdivide a given managed region: from implementing a uniform approach across the region to considering a unique approach in each of one hundred patches and everything in between. Spatially explicit approaches, such as the implementation of marine spatial planning and marine reserves, are increasingly used in fishery management. Using a spatially explicit bioeconomic model, we quantify how the management scale affects optimal fishery profit, biomass, fishery effort, and the fraction of habitat in marine reserves. We find that, if habitats are randomly distributed, the fishery profit increases almost linearly with the number of segments. However, if habitats are positively autocorrelated, then the fishery profit increases with diminishing returns. Therefore, the true optimum in management scale given cost to subdivision depends on the habitat distribution pattern.