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Potential impacts of climate change on vegetation dynamics and ecosystem function in a mountain watershed on the Qinghai-Tibet Plateau

  • Decheng Zhou
  • Lu HaoEmail author
  • John B. Kim
  • Peilong Liu
  • Cen Pan
  • Yongqiang Liu
  • Ge Sun
Article

Abstract

The Qinghai-Tibet Plateau constitutes unique mountain ecosystems that can be used for early detection of the impacts of climate change on ecosystem functions. We use the MAPSS-CENTURY 2 (MC2), a dynamic global vegetation model, to examine the potential responses of terrestrial ecosystems to climate change in the past (1961–2010) and future (2011–2080) under one medium-low warming scenario (RCP4.5) at a 1-km spatial resolution in the Upper Heihe River Basin (UHRB), northwestern China. Results showed that 21.4% of the watershed area has experienced changes in potential natural vegetation types in the past and that 42.6% of the land would undergo changes by the 2070s, characterized by a sharp increase in alpine tundra at the cost of cold barren land. Net primary productivity (NPP) and heterotrophic respiration (RH) have increased sharply since the mid-1980s and are projected to remain at reduced rates in the future. Overall, UHRB switched from carbon neutral to a carbon sink in 1961–2010, and the sink strength is projected to decline after 2040. Additionally, future climate change is projected to drive a decrease in water yield due to a slight decrease in precipitation and an increase in evapotranspiration (ET). Furthermore, we find large spatial variations in simulated ecosystem dynamics, including an upward trend of NPP, RH, and ET in the alpine zone, but a downward trend in the mid-elevation forest zone. These results underscore the complexity of potential impacts of climate change on mountain watersheds that represent the headwaters of inland river systems in an arid environment.

Notes

Acknowledgments

We thank the Cold and Arid Regions Science Data Center for sharing the climate and vegetation data. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Fig. 1 of this paper) for producing and making available their model output.

Funding information

This research was funded by the Natural Science Foundation of China (Grant No. 91425301, 41571026, and 41601196) and the Qinglan Project of Jiangsu Province of China. Partial support was provided by the Southern Research Station of the US Department of Agriculture Forest Service.

Supplementary material

10584_2019_2524_MOESM1_ESM.docx (623 kb)
ESM 1 (DOCX 623 kb)

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Jiangsu Key Laboratory of Agricultural MeteorologyNanjing University of Information Science and TechnologyNanjingChina
  2. 2.Pacific Northwest Research Station, USDA Forest ServiceCorvallisUSA
  3. 3.Centers for Forest Disturbance Science, Southern Research Station, USDA Forest ServiceAthensUSA
  4. 4.Eastern Forest Environmental Threat Assessment Center, Southern Research Station, USDA Forest ServiceResearch Triangle ParkUSA

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