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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