Early-spring soil warming partially offsets the enhancement of alpine grassland aboveground productivity induced by warmer growing seasons on the Qinghai-Tibetan Plateau
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The response of vegetation productivity to global warming is becoming a worldwide concern. While most reports on responses to warming trends are based on measured increases in air temperature, few studies have evaluated long-term variation in soil temperature and its impacts on vegetation productivity. Such impacts are especially important for high-latitude or high-altitude regions, where low temperature is recognized as the most critical limitation for plant growth.
We used Partial Least Squares regression to correlate long-term aboveground net primary productivity (ANPP) data of an alpine grassland on the Qinghai-Tibetan Plateau with daily air and soil temperatures during 1997–2011. We also analyzed temporal trends for air temperature and soil temperature at different depths.
Soil temperatures have steadily increased at a rate of 0.4–0.9 °C per decade, whereas air temperatures showed no significant trend between 1997 and 2011. While temperature increases during the growing season (May–August) promoted aboveground productivity, warming before the growing season (March–April) had a negative effect on productivity. The negative effect was amplified in the soil layers, especially at 15 cm depth, where variation in aboveground productivity was dominated by early-spring soil warming, rather than by increasing temperature during the growing season.
Future warming, especially in winter and spring, may further reduce soil water availability in early spring, which may slow down or even reverse the increases in grassland aboveground productivity that have widely been reported on the Qinghai-Tibetan Plateau.
KeywordsAboveground net primary productivity (ANPP) Alpine grassland Climate warming Qinghai-Tibetan Plateau Soil temperature
We thank the staff at the Haibei Grassland Ecological Monitoring Station on the Qinghai-Tibetan Plateau for collecting grassland aboveground productivity, weather and soil temperature data since 1997. This research was supported by the National Natural Science Foundation of China (41701606 & 41701292), the National Key Research Program of China (2016YFC0500700), the China Postdoctoral Science Foundation (2016 M590974 & 2017M610647), the Natural Science Basic Research Plan in Shaanxi Province (2017JQ3015 & 2017JQ3041), the West Light Foundation of the Chinese Academy of Sciences (K318021507), and the program from Northwest A&F University (2452016108). Further support was supplied by the Key Cultivation Project of the Chinese Academy of Sciences and Fundamental Research Funds for the Central Universities (3102016QD078). We also thank the field editor from Plant and Soil and four anonymous reviewers who provided constructive and thoughtful comments on earlier drafts of this paper.
Compliance with ethical standards
Conflict of interest
The authors have no conflicts of interest or ethical issues to declare.
- Han G, Wang Y, Fang S (2011) Climate change over the Qinghai-Tibet Plateau and its impacts on local agriculture and animal husbandry in the last 50 years. Resour Sci 33:1969–1975Google Scholar
- IPCC (2013) Climate Change 2013: The Physical Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USAGoogle Scholar
- Luedeling E (2017) chillR: Statistical Methods for Phenology Analysis in Temperate Fruit Trees. R Package Version 0.66. http://cran.r-project.org/package=chillR
- Luo Y, Zhou X (2010) Soil Respiration and the Environment. Academic press, San DiegoGoogle Scholar
- Mevik BH, Wehrens R, Liland K (2016) PLS: Partial Least Squares and Principal Component Regression. R Package Version 2.6.0. http://cran.r-project.org/package=pls
- Nychka D, Furrer R, Paige J, Sain S (2017) Fields: Tools for Spatial Data. R Package Version 9.0. http://cran.r-project.org/package=fields
- Qian B, Gregorich EG, Gameda S, Hopkins DW, Wang XL (2011) Observed soil temperature trends associated with climate change in Canada. J Geophys Res Atmos 116:D02106Google Scholar
- Core Team R (2017) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
- Wold S (1995) PLS for multivariate linear modeling. In: van der Waterbeemd H (ed) Chemometric methods in molecular design: methods and principles in medicinal chemistry. Verlag-Chemie, Weinheim, pp 195–218Google Scholar
- Zhang Y, Chen W, Smith SL, Riseborough DW, Cihlar J (2005) Soil temperature in Canada during the twentieth century: Complex responses to atmospheric climate change. J Geophys Res Atmos 110:D03112Google Scholar