A Comparative Analysis on Assessment of Land Carrying Capacity with Ecological Footprint Analysis and Index System Method

PLoS One. 2015 Jun 29;10(6):e0130315. doi: 10.1371/journal.pone.0130315. eCollection 2015.

Abstract

Land carrying capacity (LCC) explains whether the local land resources are effectively used to support economic activities and/or human population. LCC can be evaluated commonly with two approaches, namely ecological footprint analysis (EFA) and the index system method (ISM). EFA is helpful to investigate the effects of different land categories whereas ISM can be used to evaluate the contributions of social, environmental, and economic factors. Here we compared the two LCC-evaluation approaches with data collected from Xiamen City, a typical region where rapid economic growth and urbanization are found in China. The results show that LCC assessments with EFA and ISM not only complement each other but also are mutually supportive. Both assessments suggest that decreases in arable land and increasingly high energy consumption have major negative effects on LCC and threaten sustainable development for Xiamen City. It is important for the local policy makers, planners and designers to reduce ecological deficits by controlling fossil energy consumption, protecting arable land and forest land from converting into other land types, and slowing down the speed of urbanization, and to promote sustainability by controlling rural-to-urban immigration, increasing hazard-free treatment rate of household garbage, and raising energy consumption per unit industrial added value. Although EFA seems more appropriate for estimating LCC for a resource-output or self-sufficient region and ISM is more suitable for a resource-input region, both approaches should be employed when perform LCC assessment in any places around the world.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agriculture
  • China
  • Cities
  • Conservation of Natural Resources*
  • Demography
  • Ecology / methods*
  • Ecosystem*
  • Environmental Monitoring
  • Environmental Pollutants
  • Geography
  • Humans
  • Industry
  • Models, Theoretical
  • Rural Population
  • Urban Population
  • Urbanization

Substances

  • Environmental Pollutants

Grants and funding

This work was supported by the National Natural Science Foundation of China (41101143).