Hengchun Luo, Chao Zhang, Anchao Wei. The Effect of Climate on the Biomass of Pinus yunnanensis Standing Forest[J]. Journal of Southwest Forestry University, 2017, 37(6): 99-104. DOI: 10.11929/j.issn.2095-1914.2017.06.016
Citation: Hengchun Luo, Chao Zhang, Anchao Wei. The Effect of Climate on the Biomass of Pinus yunnanensis Standing Forest[J]. Journal of Southwest Forestry University, 2017, 37(6): 99-104. DOI: 10.11929/j.issn.2095-1914.2017.06.016

The Effect of Climate on the Biomass of Pinus yunnanensis Standing Forest

  • Under the background of global climate warming, climate change would affect the structure and function of forest ecosystem. Pinus yunnanensis was the main constructive species and the study of biomass of P.yunnanensis forest play an important role in the southwest region. The study analyzed the correlation between the biomass of P.yunnanensis forest and the meteorological factors that based on the data of the Continuous Forest Inventories (CFI) and combined with the data of meteorological stations in Yunnan. The 13 kinds of basic model were used to select the optimal model, and the meteorological factors were introduced into the optimal model to analyze the effect of climate on the biomass of P.yunnanensis. The result showed that: There was no significant correlation between mean annual precipitation (MAP) and mean annual sunshine duration (MASD) and biomass of P.yunnanensis. There was a significant negative correlation between themean annual temperature (MAT) and the biological temperature (BT) and biomass of P.yunnanensis. The optimal model was Gompertz model with the coefficient R2 and root mean square error (RMSE) as index. The coefficient R2 and RMSE were 0.461 and 23.184 t/hm2. The determination coefficient was reached 0.524, 0.532, 0.520, 0.521 and the precision inspection was reached 73.349%, 71.792%, 72.863%, 62.354% after introducing into the meteorological factors of MAT, WI, BT and HI. The minimum root mean square error and the absolute average relative error were both reduced. Therefore, introduction the meteorological factors would improve the fitting precision of the biomass growth model of P.yunnanensis.
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