The economics of fuel management: wildfire, invasive plants, and the dynamics of sagebrush rangelands in the western United States.

In this article we develop a simulation model to evaluate the economic efficiency of fuel treatments and apply it to two sagebrush ecosystems in the Great Basin of the western United States: the Wyoming Sagebrush Steppe and Mountain Big Sagebrush ecosystems. These ecosystems face the two most prominent concerns in sagebrush ecosystems relative to wildfire: annual grass invasion and native conifer expansion. Our model simulates long-run wildfire suppression costs with and without fuel treatments explicitly incorporating ecological dynamics, stochastic wildfire, uncertain fuel treatment success, and ecological thresholds. Our results indicate that, on the basis of wildfire suppression costs savings, fuel treatment is economically efficient only when the two ecosystems are in relatively good ecological health. We also investigate how shorter wildfire-return intervals, improved treatment success rates, and uncertainty about the location of thresholds between ecological states influence the economic efficiency of fuel treatments.

A dynamic, optimal disease control model for foot-and-mouth disease: I. Model description.

A dynamic optimization model was developed and used to evaluate alternative foot-and-mouth disease (FMD) control strategies. The model chose daily control strategies of depopulation and vaccination that minimized total regional cost for the entire epidemic duration, given disease dynamics and resource constraints. The disease dynamics and the impacts of control strategies on these dynamics were characterized in a set of difference equations; effects of movement restrictions on the disease dynamics were also considered. The model was applied to a three-county region in the Central Valley of California; the epidemic relationships were parameterized and validated using the information obtained from an FMD simulation model developed for the same region. The optimization model enables more efficient searches for desirable control strategies by considering all strategies simultaneously, providing the simulation model with optimization results to direct it in generating detailed predictions of potential FMD outbreaks.

A dynamic, optimal disease control model for foot-and-mouth-disease: II. Model results and policy implications.

A dynamic optimization model was used to search for optimal strategies to control foot-and-mouth disease (FMD) in the three-county region in the Central Valley of California. The model minimized total regional epidemic cost by choosing the levels of depopulation of diagnosed herds, preemptive depopulation, and vaccination. Impacts of limited carcass disposal capacity and vaccination were also examined, and the shadow value, the implicit value of each capacity, was estimated. The model found that to control FMD in the region, (1) preemptive depopulation was not optimal, (2) vaccination, if allowed, was optimal, reducing total cost by 3-7%, (3) increased vaccination capacity reduced total cost up to US$119 per dose, (4) increased carcass disposal capacity reduced total cost by US$9000-59,400 per head with and without vaccination, respectively, and (5) dairy operations should be given preferential attention in allocating limited control resources.

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.