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A CO2 Concentration Gradient Facility for Testing CO2 Enrichment and Soil Effects on Grassland Ecosystem Function
Published on: November 21, 2015
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Climatic change controls productivity variation in global grasslands.
Qingzhu Gao1,2, Wenquan Zhu3, Mark W Schwartz4
1Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Scientific Reports
|June 1, 2016
Summary
Climate change significantly impacts global grassland productivity, affecting nearly 40% of areas. This research analyzed vegetation index trends against climate models to understand these effects.
Area of Science:
- Ecology
- Climate Science
- Remote Sensing
Background:
- Climate change impacts on ecosystems are a critical research area.
- Understanding these impacts on grassland productivity is essential for global ecological stability.
Purpose of the Study:
- To determine the effect of historic climate change on global grassland productivity from 1982 to 2011.
- To compare actual vegetation productivity trends with climate-induced potential productivity.
Main Methods:
- Comparison of average annual Normalized Difference Vegetation Index (NDVI) values with theoretical Net Primary Productivity (NPP) based on temperature and precipitation.
- Analysis of trends in actual versus potential productivity across global grasslands over a 30-year period.
Main Results:
- Nearly 40% of global grassland areas showed significant climate change impacts on productivity trends.
- Climate change contributed 15.2-71.2% to grassland productivity variability between 1982 and 2011.
- Significant long-term impacts were observed in North America, central Eurasia, central Africa, and Oceania, indicating higher sensitivity in these regions.
Conclusions:
- Climate change has a substantial and regionally varied effect on global grassland productivity.
- The Western Hemisphere experienced greater climate change impacts on grassland productivity variability than the Eastern Hemisphere.
- Further long-term controlled experiments and multi-model ensembles are needed to confirm trends and elucidate underlying mechanisms.
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