Implication of community-level ecophysiological parameterization to modelling ecosystem productivity:a case study across nine contrasting forest sites in eastern China  

作　　者：Minzhe Fang Changjin Cheng Nianpeng He Guoxin Si Osbert Jianxin Sun 

机构地区：[1]School of Ecology and Nature Conservation,Beijing Forestry University,Beijing 100083,China [2]Research Institute of Energy Saving,Environmental Protection,Occupational Safety and Health,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China [3]Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China [4]College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049,China

出　　处：《Journal of Forestry Research》2024年第1期1-11,共11页林业研究（英文版）

基　　金：This research was funded by the National Natural Science Foundation of China(Grant Nos.31870426).

摘　　要：Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.

关 键 词：BIOME-BGC Community traits Forest Ecosystems Model parameterization 

分 类 号：S718.55[农业科学—林学]