Balancing Ecological and Economic Objectives in Land Use and Management: Modeling to Identify Sustainable Spatial Patterns.

Abstract

Human-driven land-use/cover (LULC) changes threaten the integrity of ecosystems in many ways. To evaluate possible impacts of future changes in LULC on ecosystem services and support more sustainable environmental management, it is essential to understand how land-use patterns affect both ecological and economic outcomes, and how alternative spatial land-use and -management strategies may improve sustainability in land-use systems.

I developed and tested a spatial simulation approach that can help improve our understanding of how human-driven landscape conditions at the watershed scale might reshape impacts on both water quality and economic performance in a Lake Erie watershed under a changing climate. The dissertation is organized into three chapters. The first chapter describes a study in which I evaluated sensitivity of a stochastic land-change model (LCM) to pixel versus polygonal land unit derived from parcel maps. Performance of pixel- and polygon-based simulations suggest that using polygonal unit is helpful with generating more realistic landscape patterns, but at the cost of spatial allocation accuracy.

For the second chapter, I developed the first integrated modeling approach that compares the relative economic efficiency of alternative spatial land-use and -management strategies for addressing non-point source (NPS) nutrient pollution. Using the Soil Water Assessment Tool (SWAT) and data on crop costs and prices, I evaluated joint impacts on nutrient reduction and economic returns for optimized patterns of land-use changes (LUCs) versus conservation practices (CPs) at the field scale. Simulated results showed relying on CPs alone might not be sufficient to restore water quality in Lake Erie, and a combination strategy including both LUCs and CPs would be necessary and more efficient.

Finally, I examined sensitivity of optimized spatial patterns of land-use and -management (CPs) approaches to climate change. I found optimal land-use and -management placement can be quite sensitive to change in climatic conditions. CP targeting was found to be more robust to climate change than land-use change, but integration of both strategies would be necessary to achieve high DRP reduction (>65%) targets. Results from this study highlight the need for future spatial optimization studies to consider adaptive capacity of conservation actions under a changing climate.