全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
地理研究  2008 

Sensitivity analysis for primary factors of the forest net primary productivity in Changbaishan Natural Reserve based on process model
长白山森林植被NPP主要影响因子的敏感性分析

Keywords: BEPS,NPP,sensitivity analysis,Changbaishan Natural Reserve
北部生态系统生产力模拟模型(BEPS)
,净第一性生产力,敏感性分析,长白山

Full-Text   Cite this paper   Add to My Lib

Abstract:

The sensitivity analysis of primary factors affecting the forest Net Primary Productivity(NPP) is important to estimate NPP accurately.In this paper,the sensitivity of NPP to primary parameters of BEPS(boreal ecosystem productivity simulator) was explored using uncertainty and sensitivity matrix(USM) at Changbaishan Natural Reserve in southeast Jilin province,China.Three input parameters for BEPS(leaf area index,temperature and precipitation) were selected for single factor analysis.The analysis was based on an uncertainty and sensitivity matrix with two fixed parameters and the third one was given with a change of /-5%(or 0.5 degree), /-10%(or 1 degree) and /-20%(or 2 degree) respectively.The result shows that in Changbaishan Natural Reserve,forest net primary productivity increases with the increase of LAI,drops with the rise of temperature,and has no obvious relationship with precipitation.The sensitivity analysis of different vegetation classes,including coniferous forest,broadleaf forest and mixed forest,was also done.We find the coniferous forest has a strong adaptability to environment and less effect on the environmental changes. This study was just performed at one of the parameters with pre-setting changes,while the other two parameters are fixed at true values.Definitely,any parameter will respond to the change of other parameter.Hence the net forest primary productivity will change with them.Therefore,in the future,we need to strengthen the research of changing more parameters than one simultaneously to study the sensitivity of NPP to input parameters.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133