An operational framework for seeing and simulating feedbacks in land change science

Progress towards sustainability demands recognizing nonlinear, time delayed interactions that are at the heart of dynamic integrated socioeconomic and biophysical systems. Sustainability and land change science communities have recognized the need to go beyond static and vague depictions of nonlinear feedback processes in the study of these integrated systems. But to date, there have been few attempts to move beyond conceptualizations to develop operational frameworks that i) are spatially explicit and ii) incorporate feedbacks as endogenous structural sources of the observed behavior patterns iii) both within and across scales. Land use land cover change (LUCC) is a significant component of integrated socioeconomic and biophysical systems. We present an operational framework that takes its strength from its clear emphasis on nonlinear feedback interactions as drivers of LUCC. The framework addresses both local-and regional-level processes by employing the complementary use of systems modeling and spatially-explicit discrete-choice modeling. We demonstrate the potential of the approach on a rapidly urbanizing region, Pearl River Delta (PRD) in South China. Urbanization as a significant land change process puts pressure on landscapes in both direct and indirect ways through conversion of land to urban uses and increased demands for various natural resources, respectively. To this end, we employ our systemic framework and identify the most influential feedbacks and linkages impacting the urban land conversion over the course of urban and economic growth as experienced in PRD. The integrated framework allows tracking both local and regional level dynamics simultaneously. We also discuss the potential of systems approaches and use of complementary methods in advancing land change science both in theory and in practice. DRAFT 3 DRAFT 1. Introduction Advance in sustainability science requires uncovering those processes of integrated socioeconomic and biophysical systems that are relevant for the research questions at hand. These processes are a culmination of complex, and sometimes simply complicated interactions between the components of these systems and require the integration of knowledge from diverse natural and social science disciplines (Grimm, Morgan Grove et al. 2000; Alberti, Marzluff et al. 2003; Ostrom 2007). The challenge in dealing with integrated socioeconomic and biophysical systems stems from the fact that typically, in such complex systems, the cause and effect are not only simultaneously distant and interlocking in both time and space Lambin et al. 2007) but may also be separated across different spatio-temporal scales (Turner, Dale et al. 1989; Gibson, Ostrom et al. 2000). Nonlinear feedback interactions and …