Changes in vegetation phenology on the Mongolian Plateau and their climatic determinants

PLoS One. 2017 Dec 21;12(12):e0190313. doi: 10.1371/journal.pone.0190313. eCollection 2017.

Abstract

Climate change affects the timing of phenological events, such as the start, end, and length of the growing season of vegetation. A better understanding of how the phenology responded to climatic determinants is important in order to better anticipate future climate-ecosystem interactions. We examined the changes of three phenological events for the Mongolian Plateau and their climatic determinants. To do so, we derived three phenological metrics from remotely sensed vegetation indices and associated these with climate data for the period of 1982 to 2011. The results suggested that the start of the growing season advanced by 0.10 days yr-1, the end was delayed by 0.11 days yr-1, and the length of the growing season expanded by 6.3 days during the period from 1982 to 2011. The delayed end and extended length of the growing season were observed consistently in grassland, forest, and shrubland, while the earlier start was only observed in grassland. Partial correlation analysis between the phenological events and the climate variables revealed that higher temperature was associated with an earlier start of the growing season, and both temperature and precipitation contributed to the later ending. Overall, our findings suggest that climate change will substantially alter the vegetation phenology in the grasslands of the Mongolian Plateau, and likely also in biomes with similar environmental conditions, such as other semi-arid steppe regions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biodiversity
  • Climate Change*
  • Ecosystem*
  • Mongolia
  • Plants*

Grants and funding

The work was financially supported by National Key Research and Development Program of China (Grant no. 2017YFC0504301), the Key Project of National Social and Scientific Fund Program (Grant no. 16ZDA047), Alexander von Humboldt Foundation, Startup Foundation for Introducing Talents of Nanjing University of Information Science and Technology (Grant no. 2243141601048), National Basic Research Development Program of China (Grant no. 2015CB953602, 2016YFA0602500), and the National Science Foundation of China (Grant no. 41271542). The publication of this article was funded by the Open Access Fund of the Leibniz Association. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.