Getting more for less: benchmarking the cost-effectiveness of fishery-dependent and -independent monitoring programs

Abstract

The cost-effectiveness of fisheries monitoring programs is seldom assessed, especially when fishery-dependent and -independent data are simultaneously used. We developed a framework that explores the trade-offs between a set of estimated abundance performance metrics, sampling size and costs of both monitoring programs while considering risk and statistical robustness. The approach was applied on the Danish Baltic fisheries sampling program and focused on three commercially important species with different life-history traits. Irrespective of data source, species and year, our results indicated that increasing the sampling size does not result in a proportional increase in the abundance accuracy. Moreover, combining both data sources can provide abundance estimates as accurate as those informed solely by fishery-independent data. If only the abundance performance metrics should be minimized, fishery-independent data were amongst the most cost-effective. However, the most risk-averse sampling strategies occurred when fishery-dependent data were additionally considered. Similar results occurred when the abundance performance metrics were minimized together with the sampling costs. Overall, our results revealed that we could reduce the sampling costs when more fishery-dependent data are used.