Welcome to visit Scientia Silvae Sinicae,Today is

Scientia Silvae Sinicae ›› 2024, Vol. 60 ›› Issue (7): 28-39.doi: 10.11707/j.1001-7488.LYKX20230296

Previous Articles     Next Articles

Response and Prediction of Productivity and Water Use Efficiency of Pinus sylvestris var. mongolica Plantations in Western Liaoning Province to Climate Change

Chongfan Guan1,2,3,Xiang Gao1,2,3,Zhipeng Li1,2,3,Xiaochuang Hu1,2,3,Meijun Hu1,2,3,Jinsong Zhang1,2,3,Ping Meng1,2,3,Jinfeng Cai2,Shoujia Sun1,2,3,*()   

  1. 1. Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration Research Institute of Forestry, Chinese Academy of Forestry Beijing 100091
    2. Collaborative Innovation Center of Sustainable Forestry in Southern China Nanjing Forest University Nanjing 210037
    3. Henan Xiaolangdi Earth Critical Zone National Research Station on the Middle Yellow River Jiyuan 454650
  • Received:2023-07-06 Online:2024-07-25 Published:2024-08-19
  • Contact: Shoujia Sun E-mail:.ssj1011@163.com

Abstract:

Objective: This study aims to predict the changes in gross primary productivity (GPP) and inherent water use efficiency (iWUE) of Pinus sylvestris var. mongolica plantations in Heishui forest station in western Liaoning Province under future different climatic conditions. Method: A sensitivity analysis was conducted on the parameters affecting GPP and evapotranspiration (ET) in the BIOME-BGC model. Parameter estimation (PEST) combined with eddy covariance data of GPP was used to adjust the model parameters, to obtain the simulated gross primary productivity (GPPm) and simulated inherent water use efficiency (iWUEm). The result of stable isotope measurement was compared with remote sensing data. The responses of GPPm and iWUEm of P. sylvestris var. mongolica in the Heishui forest station to climate change and increasing CO2 concentration by the end of this century were also predicted. Result: The carbon allocation ratio between fine roots and leaves was a highly sensitive parameter affecting both GPP and ET in the BIOME-BGC model, while the turnover rates of leaves and fine roots were moderately sensitive parameters. After calibration of the sensitive parameters, the simulated values of GPP were closer to the observed values. The simulated iWUEm was significantly correlated with the inherent water use efficiency (iWUEy) obtained by remote sensing and the individual inherent water use efficiency (iWUEd) with isotopic measurement (P<0.05). Under warming, GPPm increased, but under reduced precipitation and increased CO2, GPPm did not change significantly. The iWUEm showed similar trends in different scenarios, but with larger variations. Under the RCP2.6, RCP4.5, and RCP8.5 scenarios, GPPm of P. sylvestris var. mongolica significantly increased compared to the baseline, with significant differences among scenarios. However, iWUEm did not differ significantly from the baseline under RCP2.6 and RCP4.5, but increased significantly under RCP8.5 (P<0.01). Conclusion: The BIOME-BGC model, after calibration, can accurately simulate GPPm and iWUEm of P. sylvestris var. mongolica in the Heishui forest station. The differences in the future trends of GPPm and iWUEm suggest that the response mechanism of iWUE to climate change is more complex than that of GPP, and iWUE is not only influenced by climate change, but also by local site conditions.

Key words: BIOME-BGC model, gross primary productivity (GPP), inherent water use efficiency (iWUE), climate response, scene mode

CLC Number: