Policy shifts influence the functional changes of the CNH systems on the Mongolian plateau

Abstract

© 2015 IOP Publishing Ltd. By applying the concept of the coupled natural and human system (CNH), we compared spatiotemporal changes in livestock (LSK), land cover, and ecosystem production to understand the relative roles that natural and social driving forces have on CNH dynamics on the Mongolia plateau. We used socioeconomic and physical data at prefecture level for Inner Mongolia and Mongolia from 1981 through 2010 to represent changes in net primary productivity (NPP), enhanced vegetation index (EVI), precipitation, annual average temperature, LSK, livestock density (LSKD), land cover change (LCC), gross domestic production (GDP), and population (POP). The ratios such as LSK: NPP, LSKD: EVI, LSKD:albedo, LSK:POP, and LSK:GDP were examined and compared between Inner Mongolia and Mongolia, and structural equation modeling (SEM) was applied to quantify the complex interactions. Substantial differences in LSK, POP, and economic development were found among the biomes and between Inner Mongolia and Mongolia. When various indicators for policy shifts - such as the World Trade Organization (WTO) for China, the Third Campaign to Reclaim Abandoned Agriculture Lands (ATAR-3), and the Grain for Green Program for China (GFG) - were added into our SEM, the results showed significant change in the strength of the above relationships. After China joined the WTO, the relationships in Inner Mongolia between LSKD:LCC and LSKD: NPP were immensely strengthened, whereas relationships in NPP:LCC were weakened. In Mongolia, the ATAR-3 program first appeared to be an insignificant policy, but the Collapse of the Soviet Union enhanced the correlation between LSKD:LCC, weakened the connection of LCC:NPP, and did not affect LSKD:NPP. We conclude that human influences on the Mongolian CNH system exceeded those of the biophysical changes, but that the significance varies in time and per biome, as well as between Inner Mongolia and Mongolia.