Sensitivity analysis for primary factors of the forest net primary productivity in Changbaishan Natural Reserve based on process model

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.