Publisher
University of Tennessee at Chattanooga
Place of Publication
Chattanooga (Tenn.)
Abstract
Effective control of invasive species requires strategies that are both ecologically sound and resource-efficient. Building on our previous modeling efforts, we present an extended framework for the spatiotemporal management of Chinese privet (Ligustrum spp.), emphasizing ongoing and future management strategies. The approach combines discrete-time invasion modeling with optimization-based planning to evaluate adaptive interventions across heterogeneous landscapes, incorporating seed- and root-mediated dispersal, treatment thresholds, and spatial prioritization. In this presentation, we will discuss extensions to the original framework, including multi-period planning scenarios, integration of real-time monitoring data, and projections of long-term ecological outcomes under various management strategies. By highlighting ongoing research and planned improvements, this work provides actionable insights for designing scalable, cost-effective, and ecologically responsible invasive species management programs.
Document Type
presentations
Language
English
Rights
http://rightsstatements.org/vocab/InC/1.0/
License
http://creativecommons.org/licenses/by/4.0/
Recommended Citation
WALAWWE, Maheshi GALAHITIYAWE; Weerasena, Lakmali; and Wang, Jin, "Multi-Objective Strategies for Controlling Chinese Privet: Balancing Ecological Impact and Operational Efficiency". ReSEARCH Dialogues Conference proceedings. https://scholar.utc.edu/research-dialogues/2026/presentations/1.
Multi-Objective Strategies for Controlling Chinese Privet: Balancing Ecological Impact and Operational Efficiency
Effective control of invasive species requires strategies that are both ecologically sound and resource-efficient. Building on our previous modeling efforts, we present an extended framework for the spatiotemporal management of Chinese privet (Ligustrum spp.), emphasizing ongoing and future management strategies. The approach combines discrete-time invasion modeling with optimization-based planning to evaluate adaptive interventions across heterogeneous landscapes, incorporating seed- and root-mediated dispersal, treatment thresholds, and spatial prioritization. In this presentation, we will discuss extensions to the original framework, including multi-period planning scenarios, integration of real-time monitoring data, and projections of long-term ecological outcomes under various management strategies. By highlighting ongoing research and planned improvements, this work provides actionable insights for designing scalable, cost-effective, and ecologically responsible invasive species management programs.