| Title: Efficient Management of White Pine
Blister Rust in High Elevation Ecosystems: A Dynamic
Modeling Approach |
| Principal Investigator: Craig Bond |
| Affiliation: Colorado State University |
| Award: $178,000 |
| Description: The research team will analyze economic
tradeoffs of managing white pine blister rust in high-altitude,
non-timber pine forests and use a bio-economic and
dynamic programming model to evaluate efficient management
strategies. They will examine proactive intervention
and reactive strategies, which involve cutting or burning
overstory trees and planting resistant varieties, under
different infestation levels. The team will estimate
non-market values and consider the attitudes of recreational
users when evaluating management options for affected
and threatened areas. |
| Title: Institutional Design for Resource Allocation
and Risk Sharing Among Private and Public Sector Agents
to Manage Invasive Grasses and Wildfire in the Great
Basin |
|
Principal Investigator: Kimberly Rollins |
| Affiliation: University of Nevada, Reno |
| Award: $178,000 |
| Description: The project will examine contractual
arrangements to encourage ranchers to preemptively
manage wildfire-inducing weeds, primarily cheatgrass,
in the Great Basin, and efficiency gains from coordinating
the allocation of invasive weed and wildfire risk
management resources across multiple agencies and
private entities. The researchers will incorporate
a spatial component into a dynamic optimization model and
investigate tradeoffs among grazing pressure, fire control
costs, preemptive weed management, and post-fire restoration.
They will also address rancher risks and incentives for
grazing and vegetation management and the effects of USDA
conservation programs. |
| Title: Cost-Sensitive Machine Learning Algorithms
for Invasive Species Decision Support, Risk Analysis,
and Policy |
| Principal Investigator: John Drake |
| Affiliation: University of Georgia |
| Award: $174,000 |
| Description: The researchers will develop
cost-sensitive decision support tools to aid risk analysis
for potentially-invasive, imported ornamental plant
species, considering the characteristics and economic
effects of successful plant invaders and using information
about taxonomy, ecology, and biological features gained
prior to importation. They will use a database of the
characteristics of introduced plant species, develop
cost and benefit models for introduced species, classify
species by biological features and potential impact,
and develop parameterized algorithms and visual decision
trees to aid risk classification. The classification
algorithms will focus on minimizing expected damages
rather than total errors in risk classification. |
| Title: Risk Factors for Invasive Pest Introductions
in Commodity Imports |
|
Principal Investigators: Erik Lichtenberg and Lars Olson |
|
Affiliation: University of Maryland |
| Award: $172,000 |
| Description: The study will investigate the effects
of alternative phytosanitary policies, such as pre-clearance,
pre-treatment requirements, and World Trade Organization
(WTO) notifications, on invasive pest risks in imports
and the implications for allocating surveillance resources
under current budgets. The researchers will examine
theoretically how economic factors and different phytosanitary
policies affect equilibrium risk of pest introductions
in imports, and empirically analyze risk factors for
pest introductions in imports of fruits, vegetables,
cut flowers, and propagative plant materials, using
APHIS inspections data and information on phytosanitary
policy from the U.S. Code of Federal Regulations and
the WTO notification database. |
| Title: Economics of Discovery Alternatives for
Emerging Animal Diseases |
| Principal Investigator: L. Joe Moffitt |
| Affiliation: University of Massachusetts |
| Award: $147,000 |
| Description: The researchers will investigate the
structural characteristics of a robust, economically
efficient surveillance network for emerging animal
diseases. They will characterize an animal population
as a network of uncertain structure through which diseases
spread, and determine the characteristics of a surveillance
network for early discovery of unknown or undetected
diseases that is most robust in transmitting information
under uncertainty, adhering to performance and cost
criteria. Methods will address network structure, speed
of information flow, and effects of severe uncertainty
concerning disease spread and the animal population
and surveillance networks. |
| Title: Market-Based Instruments for the Optimal
Control of Invasive Insect Species: B. Tabaci in
Arizona |
| Principal Investigator: Timothy J. Richards |
| Affiliation: Arizona State University |
| Award: $125,000 |
| Description: The project will compare mechanisms, such as Pigouvian
taxes, marketable invasion permits, and performance
bonds, to encourage integrated pest management in the
event of an invasion of pesticide-resistant whitefly
on Arizona cotton. The researchers will use an optimal
control framework to compare spatio-temporal pest dispersion
paths under each mechanism to a socially optimal path.
They will estimate relationships between infestations,
crop yield and quality, and control costs to achieve
a population level below acceptable injury levels,
using data collected by University of Arizona entomologists. |
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