Sherry L. Larkin

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.

Adoption of Site-Specific Information and Variable-Rate Technologies in Cotton Precision Farming

Probit analysis identified factors that influence the adoption of precision farming technologies by Southeastern cotton farmers. Younger, more educated farmer who operated larger farms and were optimistic about the future of precision farming were most likely to adopt site-specific information technology. The probability of adopting variable-rate input application technology was higher for younger farmers who operated larger farms, owned more of the land they farmed, were more informed about the costs and benefits of precision farming, and were optimistic about the future of precision farming. Computer use was not important, possibly because custom hiring shifts the burden of computer use to agribusiness firms.

Intrinsic Fish Characteristics and Intraseason Production Efficiency: A Management-Level Bioeconomic Analysis of a Commercial Fishery

Biological changes in Pacific whiting (Merluccius productus) and corresponding production yields were used to model a vertically integrated fishery from harvest through processing. The seasonal bioeconomic programming model incorporated stock dynamics with the interactive economic effects of intrinsic fish quality, the harvest schedule, and quota allocation between heterogeneous user groups. The optimal management plan would maximize discounted net industry revenues (NPV) given a minimum spawning biomass. NPV was maximized when the intraseason timing of harvest coincided with the seasonal improvement in fish quality (e.g., following spawning and/or migration). NPV was only marginally affected, however, by the quota allocation between groups. Copyright 1999, Oxford University Press.

A Binary Logit Estimation of Factors Affecting Adoption of GPS Guidance Systems by Cotton Producers

Binary logit analysis was used to identify the factors influencing adoption of Global Positioning System (GPS) guidance systems by cotton farmers in 11 Mid-south and Southeastern states. Results indicate that adoption was more likely by those who had already adopted other precision-farming practices and had used computers for farm management. In addition, younger and more affluent farmers were more likely to adopt. Farmers with larger farms and with relatively high yields were also more likely to adopt. Education was not a significant factor in a farmer’s decision to adopt GPS guidance systems.

Harmful algal blooms and coastal business: economic consequences in Florida.

The impacts of harmful algal blooms (HABs) on coastal businesses in the Ft. Walton Beach and Destin areas of northwest Florida were estimated for 1995–1999. Separate time-series models for the restaurant and lodging sectors revealed that HABs reduced restaurant and lodging revenues in the localized study area by

Factors affecting farmer adoption of remotely sensed imagery for precision management in cotton production

2.8 million and

Intensity of Precision Agriculture Technology Adoption by Cotton Producers

3.7 million per month, respectively, which represents a 29% to 35% decline in average monthly revenues for each sector during months of red tide incidence. By comparison, a tropical storm was found to reduce monthly restaurant revenues by

Factors Affecting Perceived Improvements in Environmental Quality from Precision Farming

0.5 million, and each inch of rainfall reduced revenues an additional

Predicting Optimal Targeting Strategies in Multispecies Fisheries: A Portfolio Approach

41,000. Adverse weather was not found to affect the lodging sector. While the estimates are conservative given the resolution of data, the magnitude of effects indicate that coastal communities have suffered significant revenue losses due to HABs and that these losses are larger than caused by other environmental events.

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

This research evaluated the factors that influenced cotton (Gossypium hirsutum L.) producers to adopt remote sensing for variable-rate application of inputs. A logit model estimated with data from a 2005 mail survey of cotton producers in 11 southern USA states was used to evaluate the adoption of remote sensing. The most frequently made management decisions using remote sensing were the application of plant growth regulators, the identification of drainage problems and the management of harvest aids. A producer who was younger, more highly educated and had a larger farm with irrigated cotton was more likely to adopt remote sensing. In addition, farmers who used portable computers in fields and produced their own map-based prescriptions had a greater probability of using remote sensing. The results suggest that value-added map-making services from imagery providers greatly increased the likelihood of a farmer being a user of remote sensing.