In order to develop Pmodel, proposed by Wang et al. (Wang, Prentice et al. 2017), from a diagnostic model to a prognostic model, we need to predict the FPAR value (An input parameter in the model). However, the understanding of what kind of climatic factors control vegetation greenness is still very limited (Iio, Hikosaka et al. 2014), which is also reflected in the huge uncertainty of existing vegetation models for simulation (Cui, Huang et al. 2019). Therefore, we need to use remote sensing data to analyze the impact of climate factors on FPAR.
The Tibetan Plateau, known as the “the third pole” of the earth, is the world’s highest and largest plateau. N deposition associated with human activities have little impact in this area. Therefore, by choosing Tibetan Plateau as our study area, we could study the impact of climate change on vegetation growth more efficiently.
We used a time series (1982 – 2016) data set of the Fraction of Absorbed Photosynthetically Active Radiation (FPAR) together with historical climate data to analyze interannual variations in rainfall and temperature sensitivity and to explore the impact of climate factors on vegetation sensitivity in Tibetan Plateau.
After sampling in the meteorological space, we obtained the coefficients that can characterize the climate sensitivity of vegetation by using the LOGSUMEXP model. We found that the Tibetan Plateau is overall getting warmer and wetter and both rainfall and temperature sensitivity have a declined trend.
Meanwhile, through the establishment of multiple regression equations, they found that both rainfall and temperature sensitivity have a negative response to the increase in carbon dioxide concentration, while they are positively related to radiation. By applying stepwise regression, we found that among the four variables (temperature, precipitation, radiation, and carbon dioxide concentration), both temperature and precipitation would affect the vegetation temperature sensitivity, but only precipitation had a significant impact on rainfall sensitivity.
Overall, this research is of great significance for understanding the adaptability of vegetation on the Tibetan Plateau to climate changes. However, further verification of the above conclusions will be still needed. And now they are working on these analyses.
References:
Cui, E., et al. (2019). “Vegetation functional properties determine uncertainty of simulated ecosystem productivity: A traceability analysis in the East Asian monsoon region.” Global Biogeochemical Cycles 33(6): 668-689.
Iio, A., et al. (2014). “Global dependence of field‐observed leaf area index in woody species on climate: a systematic review.” Global Ecology and Biogeography 23(3): 274-285.
Wang, H., et al. (2017). “Towards a universal model for carbon dioxide uptake by plants.” Nature Plants 3(9): 734-741.