Sarah Keenan Jacobi
A Framework for Optimal Spatial and Temporal Resource Allocation for Large Scale Conservation Problems
Abstract
Optimal resource allocation over large spatial scales is a challenging component of many biological conservation management plans. To address this challenge, I propose an innovative multi-stage decision framework that allocates resources spatially and temporally while explicitly incorporating various sources of uncertainty. The framework combines a genetic algorithm that optimally allocates funds, with a simulation model describing species dynamics (migration or invasion). For each site receiving funds, a stochastic programming model will be used to select the optimal set of management actions to apply locally. Additionally, a Bayesian approach will update model predictions with monitoring data to adaptively manage resource allocation over time. The framework will be applied to two case studies: allocating monetary resources to develop and maintain habitat for North American waterfowl migration, and allocating resources to protect against reed canary grass (Phalaris arundinacea) invasion.
Mentors
Dr. Jeffrey Camm, University of Cincinnati School of Business; Dr. Eric Lonsdorf, Lincoln Park Zoo
Undergraduate Education
B.S. Civil and Environmental Engineering,University of Illinois at Urbana-Champaign, 1999
Graduate Education
M.S. Geography and Environmental Engineering, Johns Hopkins University, 2004
M.S. Applied Mathematics and Statistics, Johns Hopkins University, 2006
Ph.D. Geography and Environmental Engineering, Johns Hopkins University
Current Title and Affiliation
PCI Certified Parent Coach and Paraprofessional, Are We There Yet Coaching LLC and Denver Public Schools
