A revealed preference approach to valuing non-market recreational fishing losses from the Deepwater Horizon oil spill.

At an estimated 206 million gallons, the Deepwater Horizon (DWH) is the largest marine oil spill in the history of the United States. In this paper we develop a series of random utility models of site choice by saltwater anglers in the Southeast US and estimate monetary compensation for recreational losses due to the DWH oil spill. Heterogeneity in angler preferences is accounted for by using mixed logit models, and different compensation measures for shore-based, private boat, and for-hire anglers are estimated. Results indicate that willingness to pay for oil spill prevention varies by fishing mode and anglers fishing from shore and private boats exhibit heterogeneous preferences for oil spill avoidance. In addition, the total monetary compensation due to anglers is estimated at USD 585 million.

The fishery performance indicators: a management tool for triple bottom line outcomes.

Pursuit of the triple bottom line of economic, community and ecological sustainability has increased the complexity of fishery management; fisheries assessments require new types of data and analysis to guide science-based policy in addition to traditional biological information and modeling. We introduce the Fishery Performance Indicators (FPIs), a broadly applicable and flexible tool for assessing performance in individual fisheries, and for establishing cross-sectional links between enabling conditions, management strategies and triple bottom line outcomes. Conceptually separating measures of performance, the FPIs use 68 individual outcome metrics--coded on a 1 to 5 scale based on expert assessment to facilitate application to data poor fisheries and sectors--that can be partitioned into sector-based or triple-bottom-line sustainability-based interpretative indicators. Variation among outcomes is explained with 54 similarly structured metrics of inputs, management approaches and enabling conditions. Using 61 initial fishery case studies drawn from industrial and developing countries around the world, we demonstrate the inferential importance of tracking economic and community outcomes, in addition to resource status.