SHORT-RUN WELFARE LOSSES FROM ESSENTIAL FISH HABITAT DESIGNATIONS FOR THE SURFCLAM AND OCEAN QUAHOG FISHERIES

In this paper, we present a spatial model of fishing that can be used to assess some of the economic welfare losses to producers from setting aside essential fish habitat (EFH) areas. The paper demonstrates how spatially explicit behavioral models of fishing are estimated, how these models can be used to measure welfare losses to fishermen, and how these models can then, in turn, be used to simulate fishing behavior. In developing the spatial model of fishing behavior, the work incorporates ideas of congestion and information effects, and we show a modification of standard welfare measures that accounts for these spillover effects. Using this methodology, these effects are traced through to the policy simulations, where we demonstrate how these welfare and predicted shares need to be modified to account for spillover effects from fleet activity.Resource /Energy Economics and Policy,

Short-run Welfare Losses from Essential Fish Habitat Designations for the Surfclam and Ocean Quahog Fisheries

In this paper, we present a spatial model of fishing that can be used to assess some of the economic welfare losses to producers from setting aside essential fish habitat (EFH) areas. The paper demonstrates how spatially explicit behavioral models of fishing are estimated, how these models can be used to measure welfare losses to fishermen, and how these models can then, in turn, be used to simulate fishing behavior. In developing the spatial model of fishing behavior, the work incorporates ideas of congestion and information effects, and we show a modification of standard welfare measures that accounts for these spillover effects. Using this methodology, these effects are traced through to the policy simulations, where we demonstrate how these welfare and predicted shares need to be modified to account for spillover effects from fleet activity

AN INTRODUCTION TO SPATIAL MODELING IN FISHERIES ECONOMICS

Resource /Energy Economics and Policy,

The Gulf of Mexico Grouper Fisheries: Heterogeneous Fleet and Expectations in Fishermen's Decision

This study focuses on Gulf of Mexico Fishermen's expectations about their revenues and risks when participating in the grouper fishery using handlines or longlines. Results indicated that expected revenues follow a seasonnal and a spatial pattern. Fishermen using longline are risk averse while handliners are risk takers.Resource /Energy Economics and Policy,

Spatial Econometric Issues for Bio-Economic and Land-Use Modeling

We survey the literature on spatial bio-economic and land-use modelling and review thematic developments. Unobserved site-specific heterogeneity is common in almost all of the surveyed works. Heterogeneity appears also to be a significant catalyst engendering significant methodological innovation. To better equip prototypes to adequately incorporate heterogeneity, we consider a smorgasbord of extensions. We highlight some problems arising with their application; provide Bayesian solutions to some; and conjecture solutions for others.spatial econometrics, bio-economic and land-use modelling, Bayesian solution, Land Economics/Use,

A Spatial Model of Dolphin Avoidance in the Eastern Tropical Pacific Ocean

This paper examines the impact of dolphin-safe eco-labeling and how it fundamentally altered the spatial distribution of fishing effort and fishermen's willingness to pay to avoid dolphins. To do this, a dynamic discrete choice econometric model is applied to the Eastern Tropical Pacific tuna fishery. This econometric approach combines a dynamic programming component with the static discrete site choice model. This estimator couples the current period projected profits associated with fishing a specific site with the value of all future location choices on the cruise, assuming choices are made optimally. The key feature of this model is that it recovers behavioral parameters and solves the dynamic programming problem recursively. The dynamic site choice model reveals a markedly higher impact on producers as compared to the commonly used static model following the labeling regime. Further, in all but a few cases the common practice in dynamic choice models of setting discount factors equal to one is rejected.Environmental Economics and Policy,

The Atlantic Surfclam Fishery and Offshore Wind Energy Development: 2. Assessing Economic Impacts

The Atlantic surfclam (Spisula solidissima) fishery generates approximately USD 30 million in landings revenues annually, distributed across ports throughout the US Mid-Atlantic and Northeast. Overlap between areas of Atlantic surfclam harvests and offshore wind energy leasing make the fishery vulnerable to exclusion and effort displacement as development expands in the region. An existing integrated bioeconomic agent-based model, including spatial dynamics in Atlantic surfclam stock biology, heterogeneous captain behaviour, and federal management processes, was extended to incorporate costs and revenues for fishing vessels and processors and used to evaluate the potential economic effects of offshore wind development on the Atlantic surfclam fishery. Fishing activity and economic outcomes were simulated under different offshore wind energy development scenarios that impose spatial restrictions on Atlantic surfclam vessel fishing and transiting behaviour. Decreases in the number of trips and shifts in the spatial distribution of fishing effort reduced revenues for Atlantic surfclam fishing vessels and processors by ∼3–15% and increased average fishing costs by \u3c 1–5%, with impacts varying across development scenarios and fishing ports. The modelling approach used in this analysis has potential for addressing additional questions surrounding sustainable ocean multi-use and further quantifying interactions between offshore wind energy development and commercial fisheries

The Atlantic surfclam fishery and offshore wind energy development: 2. Assessing economic impacts

The Atlantic surfclam (Spisula solidissima) fishery generates approximately USD 30 million in landings revenues annually, distributed across ports throughout the US Mid-Atlantic and Northeast. Overlap between areas of Atlantic surfclam harvests and offshore wind energy leasing make the fishery vulnerable to exclusion and effort displacement as development expands in the region. An existing integrated bioeconomic agent-based model, including spatial dynamics in Atlantic surfclam stock biology, heterogeneous captain behaviour, and federal management processes, was extended to incorporate costs and revenues for fishing vessels and processors and used to evaluate the potential economic effects of offshore wind development on the Atlantic surfclam fishery. Fishing activity and economic outcomes were simulated under different offshore wind energy development scenarios that impose spatial restrictions on Atlantic surfclam vessel fishing and transiting behaviour. Decreases in the number of trips and shifts in the spatial distribution of fishing effort reduced revenues for Atlantic surfclam fishing vessels and processors by ∼3–15% and increased average fishing costs by \u3c 1–5%, with impacts varying across development scenarios and fishing ports. The modelling approach used in this analysis has potential for addressing additional questions surrounding sustainable ocean multi-use and further quantifying interactions between offshore wind energy development and commercial fisheries

Rethinking Fisheries Management: Why Fisheries Management Fails

Fisheries management as we know it today is in a perpetual state of crisis because it is fatally flawed. Fisheries management will increasingly fail to prevent species decline, and even exacerbate those declines, unless it adopts new institutional priorities and methodologies based not on the prevalent “Industrial Model,” which is driven primarily by economic utility, but instead based on the “Biological Model,” which is primarily driven by the whole range of species’ biological needs, including limits placed by interactions with other species and by the ecosystem’s carrying capacity at each stage of a species’s lifecycle. In other words, fisheries managers – including fisheries economists – must stop just managing fishermen and learn to manage fish ecosystems by thinking more like biologists than economists. To do this, concepts such as “efficient use” and “optimization” of the resource must now be legally redefined primarily in biological and ecosystem conservation terms, and fisheries management agencies must adopt the tools of conservation biology, including investing far more heavily in the basic biological monitoring that makes such management possible. Failure to make these changes will simply lead to more stock crashes, unnecessary and probably fatal stresses on fishing-dependent communities, and ultimately extinction of whole species.Keywords: sustainable, fisheries, management, ecosystem, overfishin