Application of the space-for-time substitution method in validating long-term biomass predictions of a forest landscape model

被引：21

作者：

Ma, Jun ^{[1
]}

Xiao, Xiangming ^{[1
,2
]}

Bu, Rencang ^{[3
]}

Doughty, Russell ^{[2
]}

Hu, Yuanman ^{[3
]}

Chen, Bangqian ^{[1
,4
]}

Li, Xiangping ^{[1
]}

Zhao, Bin ^{[1
]}

机构：

[1] Fudan Univ, Inst Biodivers Sci, Key Lab Biodivers Sci & Ecol Engn, Minist Educ, Shanghai 200433, Peoples R China

[2] Univ Oklahoma, Dept Microbiol & Plant Biol, Ctr Spatial Anal, Norman, OK 73019 USA

[3] Chinese Acad Sci, Inst Appl Ecol, Shenyang 110016, Peoples R China

[4] CATAS, Rubber Res Inst, Minist Agr, Danzhou Invest & Expt Stn Trop Cops, Danzhou 571737, Peoples R China

来源：

ENVIRONMENTAL MODELLING & SOFTWARE | 2017年 / 94卷

基金：

美国国家科学基金会; 中国博士后科学基金;

关键词：

Forest landscape models; LANDIS-II model; Forest biomass; Forest age; Space-for-time; Northeastern China; JERSEY PINE-BARRENS; CARBON STOCKS; SIMULATION-MODEL; CLIMATE-CHANGE; SPATIALLY EXPLICIT; ECOSYSTEM MODEL; PRESCRIBED FIRE; UNITED-STATES; SCALE MODEL; OLD-GROWTH;

D O I：

10.1016/j.envsoft.2017.04.004

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Validation of the long-term biomass predictions of forest landscape models (FLMs) has always been a challenging task. Using the space-for-time substitution method, forest biomass curves over stand age were generated from a forest survey dataset (FSD) in the Lesser Khingan Mountains area (LKM), Northeastern China and compared with long-term biomass predictions of LANDIS-II model. The results showed that mean forest age and mean biomass of the LKM in 2000 were 51.6 years and 84.2 Mg ha(-1), respectively. Significant linear correlations were found between FSD derived biomass and simulated biomass in the aggradation phase for the entire LKM and most subregions. However, a considerable difference in the mean maximum biomass (53.45 Mg ha(-1)) existed between from FSD and simulation during the post-aggradation phase. The space-for-time substitution method has potential in validating time series biomass predictions of FLMs in aggradation phase when only limited forest inventory data is available. (c) 2017 Elsevier Ltd. All rights reserved.

引用

页码：127 / 139

页数：13

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