Seasonal variation of vegetation productivity over an alpine meadow in the Qinghai–Tibet Plateau in China: modeling the interactions of vegetation productivity, phenology, and the soil freeze–thaw process
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Phenology controls the seasonal activities of vegetation on land surfaces and thus plays a fundamental role in regulating photosynthesis and other ecosystem processes. Therefore, accurately simulating phenology and soil processes is critical to ecosystem and climate modeling. In this study, we present an integrated ecosystem model of plant productivity, plant phenology, and the soil freeze–thaw process to (1) improve the quality of simulations of soil thermal regimes and (2) estimate the seasonal variability of plant phenology and its effects on plant productivity in high-altitude seasonal frozen regions. We tested different model configurations and parameterizations, including a refined soil stratification scheme that included unfrozen water in frozen soil, a remotely sensed diagnostic phenology scheme, and a modified prognostic phenology scheme, to describe the seasonal variation in vegetation. After refined soil layering resolution and the inclusion of unfrozen water in frozen soil, the results show that the model adequately reproduced the soil thermal regimes and their interactions observed at the site. The inclusion of unfrozen water in frozen soil was found to have a significant effect on soil moisture simulation during the spring but only a small effect on soil temperature simulation at this site. Moreover, the performance of improved phenology schemes was good. The phenology model accurately predicted the start and end of phenology, and its precise prediction of phenology variation allows an improved simulation of vegetation production.
KeywordsAlpine meadow Qinghai–Tibet Plateau (QTP) Unfrozen water Primary production Phenology Freezing–thawing process
This work is funded by the Chinese State Key Basic Research Project (grant number: 2009CB421305), the Knowledge Innovation Program of the Chinese Academy of Sciences (grant number: KZCX2-EW-312), and the national high-tech program (863) of China (grant number: 2009AA122104). We would like to thank Dr. David T. Price for his kind help in IBIS modeling, Xujun Han for his help of soil parameters survey, and Yanlin Zhang, Qiuan Zhu, Qingxi Guo for their useful discussions about this work. We also thank two anonymous reviewers and editors for helpful comments on earlier versions of this manuscript.
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