Agent-based modeling of complex social-ecological feedback loops to assess multi-dimensional trade-offs in dryland ecosystem services

Authored by Takafumi Miyasaka, Quang Bao Le, Toshiya Okuro, Xueyong Zhao, Kazuhiko Takeuchi

Date Published: 2017

DOI: 10.1007/s10980-017-0495-x

Sponsors: Japanese Society for the Promotion of Science (JSPS)

Platforms: NetLogo

Model Documentation: ODD Flow charts

Model Code URLs: Model code not found

Abstract

Context Recent conceptual developments in ecosystem services research have revealed the need to elucidate the complex and unintended relationships between humans and the environment if we are to better understand and manage ecosystem services in practice. Objectives This study aimed to develop a model that spatially represents a complex human-environment (H-E) system consisting of heterogeneous social-ecological components and feedback mechanisms at multiple scales, in order to assess multi-dimensional (spatial, temporal, and social) trade-offs in ecosystem services. Methods We constructed an agent-based model and empirically calibrated it for a semi-arid region in Northeast China, and examined ecosystem service trade-offs derived from the Sloping Land Conversion Program (SLCP), which is based on payment for ecosystem services. This paper describes our model, named Inner Mongolia Land Use Dynamic Simulator (IM-LUDAS), using the overview, design concepts, and details + decision (ODD + D) protocol and demonstrates the capabilities of IM-LUDAS through simulations. Results IM-LUDAS represented typical characteristics of complex H-E systems, such as secondary and cross-scale feedback loops, time lags, and threshold change, revealing the following results: tree plantations expanded by the SLCP facilitated vegetation and soil restoration and household change toward off-farm livelihoods, as expected by the government; conversely, the program caused further land degradation outside the implementation plots; moreover, the livelihood changes were not large enough to compensate for income deterioration by policy-induced reduction in cropland. Conclusions IM-LUDAS proved itself to be an advanced empirical model that can recreate essential features of complex H-E systems and assess multi-dimensional trade-offs in ecosystem services.

Tags

multiagent systems Adaptive systems Multi-agent system Heterogeneity China Hierarchy land-cover change Payments Challenges Coupled human Natural systems Desertification Cost-effective targeting Economic structural shift Grain for green Horqin sandy land Inner mongolia Spatio temporal externality Sand-dune topography Sustainability science