Using trout producer survey data and the contingent valuation method, we estimate willingness to pay for a potential insurance policy. The survey was conducted in 2005 across the United States; 268 producers completed the survey instrument, resulting in a response rate of 81 percent. Design of the contingent valuation method takes into account two coverage levels and four premium rates. Using standard willingness-to-pay techniques, we assess the premium rate that producers with varying practices and regions are willing to pay for two different coverage levels of insurance. In general, trout producers appear willing to pay premium rates of 2 to 11 percent for these coverage levels.

Emerging diseases (ED) can have devastating effects on agriculture. Consequently, agricultural insurance for ED can develop if basic insurability criteria are met, including the capability to estimate the severity of ED outbreaks with associated uncertainty. The U.S. farm-raised channel catfish (Ictalurus punctatus) industry was used to evaluate the feasibility of using a disease spread simulation modeling framework to estimate the potential losses from new ED for agricultural insurance purposes. Two stochastic models were used to simulate the spread of ED between and within channel catfish ponds in Mississippi (MS) under high, medium, and low disease impact scenarios. The mean (95% prediction interval (PI)) proportion of ponds infected within disease-impacted farms was 7.6% (3.8%, 22.8%), 24.5% (3.8%, 72.0%), and 45.6% (4.0%, 92.3%), and the mean (95% PI) proportion of fish mortalities in ponds affected by the disease was 9.8% (1.4%, 26.7%), 49.2% (4.7%, 60.7%), and 88.3% (85.9%, 90.5%) for the low, medium, and high impact scenarios, respectively. The farm-level mortality losses from an ED were up to 40.3% of the total farm inventory and can be used for insurance premium rate development. Disease spread modeling provides a systematic way to organize the current knowledge on the ED perils and, ultimately, use this information to help develop actuarially sound agricultural insurance policies and premiums. However, the estimates obtained will include a large amount of uncertainty driven by the stochastic nature of disease outbreaks, by the uncertainty in the frequency of future ED occurrences, and by the often sparse data available from past outbreaks.

This chapter discusses a large-scale study about the feasibility of developing and implementing risk management programmes for US aquaculture species (catfish, salmon, trout and baitfish) with the greatest economic value. Using aquaculture as an example, an approach is described for developing an animal disease insurance product. The steps involve determining risks, evaluating the nature of the risks, developing draft underwriting language to define coverage, collecting actuarial data, and assessing producer willingness to pay. It is determined that every situation in aquaculture is sufficiently unique that insurability conditions need to be examined on a case-by-case basis. An insurability condition matrix is used, and the way to elicit risk for these unique settings is discussed. Risks are then classified and the implications and potential for aquaculture insurance are discussed. It is concluded that guidelines can be established to enable the development of insurance programmes for aquaculture.

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The Deepwater Horizon (DWH) oil spill was the first spill that occurred in the deep ocean, nearly one mile below the ocean’s surface. The large-scale applications of dispersants used at the surface and wellhead during the Deepwater Horizon oil spill raised many questions and highlighted the importance of understanding their effects on the marine environment.  This 9-page fact sheet concerns the use of dispersants in response to the Deepwater Horizon (DWH) oil spill, the first spill that occurred in the deep ocean, nearly a mile below the surface. Written by Monica Wilson, Larissa Graham, Christine Hale, Emily Maung-Douglass, Stephen Sempier, and LaDon Swann and published by the Florida Sea Grant College Program, the fact sheet was selected for publication on EDIS by Monica Wilson. Originally published at the National Sea Grant Library: https://eos.ucs.uri.edu/EOS_Linked_Documents/gomsg/EX-GOMRI-1%20-%20Wilson_M_2015.pdfhttp://edis.ifas.ufl.edu/sg150