Socio-econ-ecosystem multipurpose simulator (SEEMS): An easy-to-apply agent-based model for simulating small-scale coupled human and nature systems in biological conservation hotspots

Abstract

The tension between economic development and ecological conservation has always been a hotly debated topic, especially in critical ecologically sensitive areas such as nature reserves in the developing world. Complexity modeling methods, such as Agent-based Models (ABM), are a feasible way to study such Coupled Human and Nature Systems (CHANS). This paper presents an ABM named Socio-Econ-Ecosystem Multipurpose Simulator (SEEMS) for small-scale CHANS, with particular focus on biological conservation hotspots areas under developmental pressures. The model highlights a microeconomic basis tailored for research objects of the kind featuring heterogeneous agents with partial rationality, and integration of various mechanisms of two-way human-nature interaction such as ecological succession, and farmland fallowing. These features, together with merits in low data and computational requirements and convenient extendibility, make SEEMS an easy-to-apply approach in CHANS modeling. A case study in China's Wolong National Reserve for Giant Pandas not only validates the model's capacity of accurately simulate the real-world demographic, social, economic, and ecological situations, but also demonstrates nonlinear outcomes that might not otherwise emerge in statistical models. Subsequent studies may benefit from these features of SEEMS to investigate theoretical problems in the human-nature relationship in biological conservation hotspots, or practical ones regarding conservative policy-making in such areas.