Coupling Human and Natural Systems for Sustainability: Experiences from China’s Loess Plateau

Abstract

Abstract. Addressing the sustainability challenges facing humanity in the Anthropocene requires the coupling of human and natural systems, rather than their separate treatment. To understand the dynamics of a coupled human and natural system (CHANS) and promote its sustainability, we proposed a conceptual cascade framework of “Pattern-Process-Service-Sustainability”. The use of this framework was systematically illustrated by a review of CHANS research experiences in China’s Loess Plateau (LP) in terms of coupling landscape patterns and ecological processes, linking ecological processes to services, and promoting social-ecological sustainability. The LP is well-known for its historically notorious soil erosion and successful vegetation restoration achieved in recent decades. Vegetation coverage in the LP has increased since 2000 due to ecological restoration. Soil erosion has been well controlled and the sediment deriving from the LP, and flowing into the Yellow River, has greatly decreased; however, overplanting, the introduction of exotic plant species, and the mismanagement of planted vegetation have also led to soil drying in some areas. Ecosystem services, especially for soil conservation and carbon sequestration, have significantly improved, although a trade-off between carbon sequestration and water supply has been identified at multiple scales. Based on the comprehensive understanding of CHANS dynamics, targeted policy and management suggestions are here proposed to support the social-ecological sustainability of the LP. The research experience accumulated on the LP offers examples of the application of the “Pattern-Process-Service-Sustainability” framework. Future research using this framework should especially examine the integrated research of multiple processes, the cascades of ecosystem structure, function, services, and human-wellbeing, the feedback mechanisms of human and natural systems, and the data and models for sustainability.