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Invasive Species Management: FY 2004 PREISM Competitive Awards

Title: Developing and Integrating Tools for Assessing the Impacts of Invasive Plants for Prioritization of Management on Federal Lands
Principal Investigator: Bruce D. Maxwell
Affiliation: Montana State University, Bozeman, MT
Award: $238,300

The objective of this research project is to develop a Geographic Information Systems (GIS)-based decision support tool to help land managers assess tradeoffs among ecosystem indicators and control costs and prioritize invasive plant populations for management. U.S. Forest Service land managers will be actively engaged in the project as providers of expert opinion and prospective users of the tools. Specifically, the research plan includes: 1) development of an understanding of the relationship between the probability of invasive plant species occurrences and ecosystem impacts; 2) integration of the plant invasion and ecosystem impacts into a plant community change model that employs GIS technology to analyze spatial and temporal aspects of disturbance processes; 3) modification and linkage of decision support system models for economic analysis of production systems (Tradeoff Analysis) with the ecosystem models; and 4) creation of an example economic assessment of alternative invasive plant species management plans for Bozeman District of Gallatin National Forest to reflect the spread and impact of a representative set of common invasive plant species currently found in the District.

Title: A Risk-Based Approach to Manage Intentional Introduction of Non-Native Species
Principal Investigator: James J. Opaluch
Affiliation: University of Rhode Island, Kingston, RI
Award: $219,880

This study's investigators will develop a risk-based framework to balance potential benefits of non-native species intentionally introduced for commercial purposes against the risks that the species become invasive and cause harm. It will examine the proposed introduction of Asian oysters in the Chesapeake Bay. The spatially explicit framework is based on a principal agent model, where the regulatory agency plays the role of principal by designing policies that provide incentives and constraints for agents, which are firms proposing to introduce non-native species. The analysis will consider multiple tiers of risk in addition to the risk of the intentional introduction becoming invasive, including invasions from hitchhiker species, "rogue" introductions in clear violation of government policy, and financial risks leading to incomplete control of production operations. This project also considers a number of policy measures for controlling risk, including technological input controls, best management practices, assignment of property rights, phased introduction of commercially introduced species with "intervention points" where the initial decision to introduce a species might be reversible at feasible cost, and the creation of a source of funds to finance early detection of and rapid response to an invasion.

Title: Spatial Management of Invasive Alien Species: An Application to Cheatgrass Management in the Great Basin
Principal Investigator: James N. Sanchirico
Affiliation: Resources for the Future, Washington, DC
Award: $190,860

For this project, the researchers will develop a stochastic, spatial, and inter-temporal bioeconomic model for comparing the costs and benefits of targeting invasive-species management actions, such as exclusion, surveillance, control, and mitigation, at various times and locations. Using the model, the researchers will examine three research questions: What are the crucial spatial and inter-temporal feedbacks that influence the effectiveness of invasive species policies? What are the potential efficiency losses when the scope of invasive species policies does not match the ecosystem and economic scale of the problem? How do economic and ecologic uncertainties affect the portfolio of optimal invasive species policies both across time and space? Uncertainty, dynamics, and a social planner will be explicitly modeled along with a two-region trade model. Imports can flow into each region from elsewhere, the regions trade with each other, and have different production potentials and habitat qualities. The level of commodity production and habitat quality influence the probability that an invasion will occur. Conversely, the level of infestation influences habitat quality, possibly irreversibly. The researchers will simulate control policies to examine the questions posed, using cheatgrass in the Great Basin as an example.

Title: Economic Impacts of Foreign Animal Disease
Principal Investigator: Philip L. Paarlberg
Affiliation: Purdue University, West Lafayette, IN
Award: $169,000

This project will result in the evaluation of the economic impacts of alternative livestock and poultry disease control strategies. The goal of this project is to better quantify the economic impacts of selected diseases that pose a threat to U.S. livestock and poultry industries' competitiveness. The project will focus on the economic impact of consumer and international trade responses to the presence of such diseases and of alternative disease control strategies. Foreign Animal Diseases (FAD) such as Foot and Mouth Disease (FMD), Classical Swine Fever (CSF), and Highly Pathogenic Avian Influenza (HPAI) will be examined. This analysis will use animal epidemiological disease spread models and prevalence estimates found in the literature to generate supply shifts. The results for each disease under alternative simulations of control strategies such as quarantine and surveillance will be introduced into a U.S. agricultural sector model along with information about trade impacts, regulatory costs, and potential consumer reactions to determine the impacts on market prices, quantities, and the welfare of economic agents. The objective is to determine optimal control strategies in terms of quarantine and surveillance zone size by balancing the economic interests of those affected on and off the farm.

Title: Robust Inspection for Invasive Species with a Limited Budget
Principal Investigator: L. Joe Moffitt
Affiliation: University of Massachusetts, Amherst, MA
Award: $125,400

This project's investigators will construct a decision tool to develop efficient border protection protocols for potentially damaging species under conditions of extreme uncertainty and limited budgets. The goal is to construct the decision support tool under information-gap uncertainty integrating only available information to structure events and show its applicability for quantitative decision support of border protection problems. The project will suggest revisions to the inspections processes laid out in the USDA/APHIS Agricultural Quarantine Inspection Monitoring Handbook for detection of invasive species, focusing on agricultural inspection at a northeastern U.S. port-of entry. The investigators will develop a hybrid info-gap model, which is a novel, non-probabilistic approach used in engineering to avoid worst-case outcomes. The model will incorporate an expected utility performance requirement and achieve it for all risk-averse decision makers by use of a stochastic dominance constraint in the process of maximization of robustness.

Title: Determinants and Welfare Implications of Federal and State Noxious Weed Regulations
Principal Investigator: Munisamy Gopinath
Affiliation: Oregon State University, Corvallis, OR
Award: $85,000

This project focuses on the ecological and economic factors determining what species appear on Federal and State noxious weed lists, which vary substantially across jurisdictions. A main objective is to evaluate the impact of the weed lists on interstate trade. Models will be constructed to analyze at the Federal, State and regional level such questions as: What are the key determinants of the size and composition of noxious weed lists? Do the noxious weed lists provide economic protection to producer groups in addition to ecological and agronomic protection? What are the effects on welfare and trade flows? Who are the winners and losers? The researchers also plan to address the question of why there is little overlap between State weed lists. Central to the research will be a political economy and ecological model of invasive species regulation. In the model, Federal and State governments choose noxious weed lists in response to pressure from environmental, agronomic, and trade-protection interests. Overlaps among State lists, and associated interstate seed and commodity trade flows, will be estimated as functions of agronomic and ecosystem characteristics, rent- seeking efforts, and other factors. Indexes of ecosystem and agronomic vulnerability, seed and commodity producer lobbying power, and interstate trade flows will be constructed to carry out the empirical analysis.

Title: The Regulation of Invasive Species Introduced Unintentionally Via Maritime Trade
Principal Investigator: Amitrajeet A. Batabyal
Affiliation: Rochester Institute of Technology, Rochester, NY
Award: $74,000

This project's investigator will analyze economic issues associated with the design and operation of two pest exclusion policy options, port of entry inspections and pre-export certifications, used by USDA. Specific research objectives include examination of the following questions: 1) Given benefits from free trade in agricultural products and the expected losses from the introduction of invasive species, under what circumstances can a trade ban be an effective regulatory policy? 2) Given asymmetric information between exporting and importing nations, what are the properties of credible pre-export certification schemes? 3) What would be the optimal number of inspectors in a stochastic context in which arriving ships may or may not be able to queue in a particular port?; 4) What would be the optimal number of inspectors and the intensity of inspection at ports of entry for an exclusion policy?; and, 5) How can information about the value of the products being transported by ships and the expected time to inspect ships be used to inform the design of inspection protocols? Queuing theory and the theory of stochastic optimal control will be used to account for the stochastic nature of the problem and to construct and analyze models of border measures to mitigate pest risks. When appropriate, the conceptual work will be augmented with numerical and empirical analyses.

 

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Updated date: October 12, 2005