Designing Wetland Conservation Strategies under Climate Change Jiayi Li, Elizabeth Marshall, James Shortle, Richard Ready, Carl Hershner Department of Agricultural Economics and Rural Sociology Virginia Institute of Marine Sciences Introduction Wetland conservation is a major environmental concern in the Chesapeake Bay region. Substantial losses due to land development and other factors have had profound impacts on the Bay’s aquatic resources. Major wetland functions include: habitat provision, water quality improvement, flood protection, bank stabilization, and sediment control. Current conservation efforts fail to account for the impacts of climate change on sea level, which can affect the success of conservation efforts. Methods  Cost-effective analysis is used to compare two wetland conservations strategies: - Strategy 1: Preserve high-elevation undeveloped land adjacent to existing wetland. Objective This study develops a methodology for evaluating public wetlands conservation investments that takes climate change into account. We demonstrate the methodology for the Elizabeth River watershed in Virginia under plausible sea-level rise and land use scenarios. We consider a 30-year time period Fig 3: Elizabeth River Watershed, Virginia Cellular Automaton (CA) Model  CA examines changes taking place purely as a function of what happens in the immediate vicinity of any particular cell. The land use data is mapped into cells, as shown in Figure 5.  We identify four major drivers that influence the development possibility for each undeveloped land cell.  We assign different weight sets to the four major drivers to reflect three different future land use scenarios: compact development, dispersed development, and nodal development. Discrete Stochastic Sequential Programming (DSSP)  We consider two types of uncertain events that may affect decisions in our DSSP model. - Acquisition of new information about high or low sea-level rise (SLR). - Knowing the likelihood that an undeveloped land parcel would become developed.  Figure 6 shows how these uncertain events are included in a 2-stage decision process. Immediate vicinity land use type Distance to shoreline Distance to primary roads Distance to population centers Fig 5: CA Model Illustration Decision Not Buy Buy High SLR (P 0 ) Low SLR (1- P 0 ) Sell Keep Sell Keep Low SLR/Undeveloped (P 2 ) High SLR/Developed (P 3 ) Low SLR/Developed (1-P 1 -P 2 -P 3 ) High SLR/Undeveloped (P 1 ) Not Buy Buy Not Buy Buy T = 1T = 2 Fig 6: Two stage decision process Acknowledgement: 1. Support is provided by the Global Change Research Program, Office of Research and Development, U.S. Environmental Protection Agency (Cooperative Agreement R ). 2. Steve Graham, Penn State and Tamia Rudnicky, Virginia Institute of Marine Science (VIMS) provided GIS data and analysis assistance. 3. Marcia Bermen, Walter Priest and Dan Schatt, VIMS gave valuable suggestions. Fig 1: Function: Water Quality Source: National Image Library Fig 2: Function: Wildlife Habitat Source: National Image Library - Strategy 2: Relocate wetland to suitable areas where land prices are low.  The cellular automaton (CA) model is used to construct a development vulnerability index and to project land use changes for the study area.  The discrete stochastic sequential programming (DSSP) technique is used to minimize the costs of implementing each wetland conservation strategy. Fig 4: Wetland Migration (Titus, 1990)