辽西地区樟子松人工林生产力和水分利用效率对气候变化的响应及预测  

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

作　　者：管崇帆 高翔 李志鹏[1,2,3] 胡晓创 胡美均 张劲松 孟平[1,2,3] 蔡金峰 孙守家[1,2,3] Guan Chongfan;Gao Xiang;Li Zhipeng;Hu Xiaochuang;Hu Meijun;Zhang Jinsong;Meng Ping;Cai Jinfeng;Sun Shoujia(Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration Research Institute of Forestry,Chinese Academy of Forestry,Beijing 100091;Collaborative Innovation Center of Sustainable Forestry in Southern China Nanjing Forest University,Nanjing 210037;Henan Xiaolangdi Earth Critical Zone National Research Station on the Middle Yellow River,Jiyuan 454650)

机构地区：[1]中国林业科学研究院林业研究所国家林草局林木培育重点实验室,北京100091 [2]南京林业大学南方现代林业协同创新中心,南京210037 [3]河南黄河小浪底关键带国家野外科学观测研究站,济源454650

出　　处：《林业科学》2024年第7期28-39,共12页Scientia Silvae Sinicae

基　　金：国家重点研发计划项目(2020YFA0608101);中央级公益性科研院所基本科研业务费专项资金(CAFYBB2022ZA00102)。

摘　　要：[目的]预测未来气候背景下辽宁西部黑水林场樟子松人工林总初级生产力(GPP)和生态系统内禀水分利用效率(iWUE)的变化趋势及差异,为樟子松人工林的可持续管理与科学经营提供科学参考。[方法]对BIOME-BGC模型中影响GPP和蒸散(ET)的参数进行敏感性分析,利用参数估计(PEST)结合涡度数据对模型进行参数调整,获得模拟生态系统总初级生产力(GPP_(m))和模拟生态系统内禀水分利用效率(iWUEh_(m)),以稳定同位素和遥感数据进行比对,预测本世纪末黑水林场樟子松GPP_(m)和iWUE_(m)对气候变化和CO_(2)浓度增加的响应。[结果]细根与叶片碳分配比是同时影响BIOME-BGC模型中GPP和ET的高敏感性参数,叶片和细根年周转率是中敏感性参数。对敏感性参数进行校正后,模型输出的GPP模拟值更趋近于实测值。iWUE_(m)与遥感生态系统内禀水分利用效率(iWUE_(y))、单株内禀水分利用效率(iWUE_(d))均呈显著相关(P<0.05)。在增温情景下,樟子松GPP_(m)升高,但在降水和CO_(2)增加情景下GPP_(m)变化不显著,不同情景下的iWUE_(m)与GPP_(m)变化相似但变幅更大。在RCP2.6、RCP4.5和RCP8.5情景下,樟子松GPP_(m)与基线相比呈上升趋势且差异显著,但在RCP2.6和RCP4.5情景下iWUE_(m)与基线差异不显著,仅在RCP8.5情景下极显著升高(P<0.01)。[结论]参数校正后的BIOME-BGC模型能够准确模拟黑水林场樟子松GPP_(m)和iWUE_(m),未来GPP_(m)与iWUE_(m)变化趋势的差异暗示iWUE的气候变化响应机制比GPP更复杂,其不仅受气候变化影响,还可能与当地立地条件有关。[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(GPP_(m))and simulated inherent water use efficiency(iWUE_(m)).The result of stable isotope measurement was compared with remote sensing data.The responses of GPP_(m)and iWUE_(m)of P.sylvestris var.mongolica in the Heishui forest station to climate change and increasing CO_(2)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 iWUE_(m) was significantly correlated with the inherent water use efficiency(iWUE_(y))obtained by remote sensing and the individual inherent water use efficiency(iWUE_(d))with isotopic measurement(P<0.05).Under warming,GPP_(m) increased,but under reduced precipitation and increased CO_(2),GPP_(m) did not change significantly.The iWUE_(m) showed similar trends in different scenarios,but with larger variations.Under the RCP2.6,RCP4.5,and RCP8.5 scenarios,GPP_(m) of P.sylvestris var.mongolica significantly increased compared to the baseline,with significant differences among scenarios.However,iWUE_(m) 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 G

关 键 词：BIOME-BGC模型 总初级生产力 内禀水分利用效率 气候响应 情景模式 

分 类 号：S718.45[农业科学—林学]