Temporal and spatial evolution and obstacle diagnosis of resource and environment carrying capacity in the Loess Plateau

PLoS One. 2021 Aug 18;16(8):e0256334. doi: 10.1371/journal.pone.0256334. eCollection 2021.

Abstract

Natural resources are scarce in the Loess Plateau, and the ecological environment is fragile. Sustainable development requires special attention to resource and environmental carrying capacity (RECC). This study selected 24 representative cities in five natural areas of the Loess Plateau; used the entropy-weight-based TOPSIS method to evaluate and analyze the RECC of each city and region from 2013 to 2018; established a diagnosis model to identify the obstacle factors restricting the improvement of RECC; and constructed the theoretical framework of the RECC system mechanism. The results show that the RECC of the Loess Plateau is increasing in general but is relatively small. The environmental and social subsystems have the highest and lowest carrying capacities, respectively. There is an evident contradiction between economic development and the environment. Population density, investment in technological innovation, per capita sown area, and per capita water resources are the main obstacles affecting the improvement of RECC in the Loess Plateau. Such evaluations and diagnoses can support ecological civilization and sustainable development.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Cities / economics
  • Conservation of Water Resources / trends*
  • Economic Development / trends*
  • Ecosystem
  • Entropy
  • Humans
  • Sustainable Development / economics*

Grants and funding

This paper is supported by the National Natural Science Foundation of China (41790445, 42042019), National Social Science Foundation of China (19FJYB028), Independent Project Foundation of the State Key Laboratory of Geohazard Prevention and Geo-environment Protection (SKLGP2015Z004), the Social Science Foundation of Chengdu University of Technology (YJ2019-JX004), and the Project of Social Science Key Research Bases in Sichuan Province (TYZX2020-01).