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In 2009, Rhode Island implemented a pilot catch share program around summer flounder, or fluke, a state-managed species that is jointly harvested with the Northeast Multispecies groundfish complex. A sector was given a fluke allocation to land when they wished, while the rest of the fleet was managed through sub-seasonal total harvest caps and daily trip limits. Sector members avoided fluke landings during seasonal fluke derbies, instead shifting landings to post-derby closures in the general fishery, when the price was higher. However, they also affected prices of species they targeted instead. We combine predictions of counterfactual 2009 daily landings by sector vessels with a panel model of trip-level ex-vessel prices for 25 products targeted by the groundfish fleet to project what revenues would have been in the absence of the sector program. We find the pilot program increased fleetwide revenues by over $800,000, including benefits of over $250,000 to non-sector vessels.
In this study we assess the ability of the Marine Recreational Fishery Statistics Survey (MRFSS) to support single-species recreation demand models. We use the 2000 MRFSS southeast intercept data combined with the economic add-on. We determine that the MRFSS data will support only a few species-specific recreation demand models. Considering species of management interest in the Southeast, we focus on dolphinfish, king mackerel, red snapper, and red drum. We examine single-species recreational fishing behavior using random utility models of demand. We explore mixed logit (i.e., random parameter logit) and finite mixture (i.e., latent class logit) models for dealing with angler heterogeneity. We compare these to the commonly used conditional and nested logit models in terms of the value of catching (and keeping) one additional fish. Mixed logit models illustrate that the value of catch can be highly heterogeneous and, in some cases, can include both positive and negative values. The finite mixture model generates value estimates that were sometimes strikingly different than conditional, nested, and mixed logit models. Preference heterogeneity is significant within the MRFSS data. We find evidence that single-species models outperform multiple-species models and recreational values differ.
This article incorporates illegal fuel trading behavior to examine the effects of changes in the fishery subsidy rate, detection effort, and fish price on the level of fishing, illegal fuel trading, and fish biomass. The corresponding effects on the fisherman's profits and the profits of the oil company that supplies the raw fuel to the fishery are also examined. The findings are, first, that the subsidy policy benefits the oil company, but its effects on the fisherman are ambiguous. Second, an increase in detection effort leads to less illegal activity in relation to fuel trading and more legal fishing resulting in less fish biomass. The detection policy hurts the oil company, the fisherman who engages in fuel trading, and resource conservation. Finally, an increase in fish price leads to a similar result as an increase in detection effort, but the effects on the fisherman's profits are reversed. The oil company also benefits from increasing fish price.
In most coastal countries the fisheries sector satisfies multiple socioeconomic needs. This is especially the case in many coastal developing countries where fisheries represent a substantial source of food, jobs, and income. However, fisheries exert strong pressures on marine resources with threats to their sustainability. The context of overexploitation of marine resources is combined with a great diversity of stakeholders intervening in the governance of the fisheries. Thus, a better understanding of the challenges fisheries face is essential to enact management policies to ensure sustainability. Through a case study of the Senegalese fisheries, this article develops quantitative indicators of social, economic, and ecological states of the fisheries. Standardized principal components analysis combined with the Hodrick-Prescott filter is used to assess trends in the indicators. These indicators can contribute to an adaptive management framework in a context of multiple management objectives with diverse stakeholders and uncertainty.