Differences in growth pattern and response to climate warming between Larix olgensis and Pinus koraiensis in Northeast China are related to their distinctions in xylem hydraulics

2022 ◽  
Vol 312 ◽  
pp. 108724
Author(s):  
Qiu-Rui Ning ◽  
Xue-Wei Gong ◽  
Ming-Yong Li ◽  
Guang-You Hao
Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 36
Author(s):  
Qing Zhang ◽  
Wen Zhang ◽  
Yongqiang Yu ◽  
Tingting Li ◽  
Lijun Yu

Responses of crop growth to climate warming are fundamental to future food security. The response of crops to climate change may be subtly different at their growing stages. Close insights into the differentiated stage-dependent responses of crops are significantly important in making adaptive adjustments of crops’ phenological optimization and cultivar improvement in diverse cropping systems. Using the Agro-C model, we studied the influence of past climate warming on crops in typical cropping systems in China. The results showed that while the temperature had increased distinctly from the 1960s to 2000s, the temperature frequency distributions in the growth season of crops moved to the high-temperature direction. The low temperature days during the crop growth periods that suppress crop growth decreased in the winter wheat area in North and East China, rice and maize areas in Northeast China, and the optimum temperature days increased significantly. As a result, the above ground biomass (AGB) of rice and maize in Northeast China and winter wheat in North and East China increased distinctly, while that of rice in South China had no significant change. A comparison of the key growth periods before and after heading (silking) showed that the warming before heading (silking) made a great contribution to the increase in the AGB, especially for winter wheat.


2013 ◽  
Vol 14 (1) ◽  
pp. 39-48 ◽  
Author(s):  
Zhengguo Li ◽  
Peng Yang ◽  
Huajun Tang ◽  
Wenbin Wu ◽  
He Yin ◽  
...  

Author(s):  
Xiaoying Li ◽  
Huijun Jin ◽  
Long Sun ◽  
Hongwei Wang ◽  
Ruixia He ◽  
...  

2022 ◽  
Vol 268 ◽  
pp. 112769
Author(s):  
Yuanshuo Hao ◽  
Faris Rafi Almay Widagdo ◽  
Xin Liu ◽  
Ying Quan ◽  
Zhaogang Liu ◽  
...  

2019 ◽  
Vol 65 (No. 4) ◽  
pp. 134-143 ◽  
Author(s):  
Tuan Nguyen Thanh ◽  
Tai Dinh Tien ◽  
Hai Long Shen

Korean pine (Pinus koraiensis Sieb. et Zucc.) is one of the highly commercial woody species in Northeast China. In this study, six nonlinear equations and artificial neural network (ANN) models were employed to model and validate height-diameter (H-DBH) relationship in three different stand densities of one Korean pine plantation. Data were collected in 12 plots in a 43-year-old even-aged stand of P. koraiensis in Mengjiagang Forest Farm, China. The data were randomly split into two datasets for model development (9 plots) and for model validation (3 plots). All candidate models showed a good perfomance in explaining H-DBH relationship with error estimation of tree height ranging from 0.61 to 1.52 m. Especially, ANN models could reduce the root mean square error (RMSE) by the highest 40%, compared with Power function for the density level of 600 trees. In general, our results showed that ANN models were superior to other six nonlinear models. The H-DBH relationship appeared to differ between stand density levels, thus it is necessary to establish H-DBH models for specific stand densities to provide more accurate estimation of tree height.


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