Vulnerability of forest vegetation to anthropogenic climate change in China

Sci Total Environ. 2018 Apr 15;621:1633-1641. doi: 10.1016/j.scitotenv.2017.10.065. Epub 2017 Nov 6.

Abstract

China has large areas of forest vegetation that are critical to biodiversity and carbon storage. It is important to assess vulnerability of forest vegetation to anthropogenic climate change in China because it may change the distributions and species compositions of forest vegetation. Based on the equilibrium assumption of forest communities across different spatial and temporal scales, we used species distribution modelling coupled with endemics-area relationship to assess the vulnerability of 204 forest communities across 16 vegetation types under different climate change scenarios in China. By mapping the vulnerability of forest vegetation to climate change, we determined that 78.9% and 61.8% of forest vegetation should be relatively stable in the low and high concentration scenarios, respectively. There were large vulnerable areas of forest vegetation under anthropogenic climate change in northeastern and southwestern China. The vegetation of subtropical mixed broadleaf evergreen and deciduous forest, cold-temperate and temperate mountains needleleaf forest, and temperate mixed needleleaf and broadleaf deciduous forest types were the most vulnerable under climate change. Furthermore, the vulnerability of forest vegetation may increase due to high greenhouse gas concentrations. Given our estimates of forest vegetation vulnerability to anthropogenic climate change, it is critical that we ensure long-term monitoring of forest vegetation responses to future climate change to assess our projections against observations. We need to better integrate projected changes of temperature and precipitation into climate-adaptive conservation strategies for forest vegetation in China.

Keywords: Climatic change; Endemics–area relationship; Forest ecosystem; Species distribution modelling; Vulnerable forest vegetation.

MeSH terms

  • Biodiversity*
  • China
  • Climate Change*
  • Forests*
  • Plants*
  • Temperature