scholarly journals Sensitivity Analysis of Biome-BGCMuSo for Gross and Net Primary Productivity of Typical Forests in China

2021 ◽  
Author(s):  
Hongge Ren ◽  
Li Zhang ◽  
Min Yan ◽  
Xin Tian ◽  
Xingbo Zheng
Keyword(s):  
Sensitivity Analysis ◽  
Primary Productivity ◽  
Model Calibration ◽  
Field Experiments ◽  
Net Primary Productivity ◽  
Phase 1 ◽  
Light Extinction ◽  
Sensitivity Index ◽  
Sensitivity Testing ◽  
Climate Gradient

Abstract Background: Process-based models are widely used to simulate forest productivity, but complex parameterization and calibration challenge the application and development of these models. Sensitivity analysis of numerous parameters is an essential step in model calibration and carbon flux simulation. However, parameters are not dependent on each other, and the results of sensitivity analysis usually vary due to different forest types and regions. Hence, global and representative sensitivity analysis would provide reliable information for simple calibration. Methods: To determine the contributions of input parameters to gross primary productivity (GPP) and net primary productivity (NPP), regression analysis and extended Fourier amplitude sensitivity testing (EFAST) were conducted for Biome-BGCMuSo to calculate the sensitivity index of the parameters at four observation sites under climate gradient from ChinaFLUX. Results: Generally, GPP and NPP were highly sensitive to C:N leaf (C:N of leaves), W int (canopy water interception coefficient), k (canopy light extinction coefficient), FLNR (fraction of leaf N in Rubisco), MR pern (maintenance respiration in kg C/day per kg of tissue N), VPD f (vapor pressure deficit complete conductance reduction), and SLA1 (canopy average specific leaf area in phenological phase 1) at all observation sites. Various sensitive parameters occurred at four observation sites within different climate zones. GPP and NPP were particularly sensitive to FLNR, SLA1 and W int , and C:N leaf in temperate, alpine and subtropical zones, respectively. Conclusions: The results indicated that sensitivity parameters of China's forest ecosystems change with climate gradient. We found that parameter calibration should be performed according to plant functional type (PFT), and more attention needs to be paid to the differences in climate and environment. These findings contribute to determining the target parameters in field experiments and model calibration.

scholarly journals Impact of Weeds on Paddy Biomass in Upland Rainfed Areas of Terai Region of Nepal

2009 ◽  
Vol 13 ◽  
pp. 15-22
Author(s):  
M. D. Bhatt ◽  
S. P. Singh ◽  
A. Tewarir
Keyword(s):  
Primary Productivity ◽  
Field Experiments ◽  
Net Primary Productivity ◽  
Block Design ◽  
Weed Species ◽  
Randomized Block Design ◽  
Hand Weeding ◽  
Paddy Crop ◽  
Biomass Reduction ◽  
Better Than

Field experiments were conducted to analyze impacts of weeds on biomass of two varieties of rain fed upland paddy (cv. Radha-4 and Neemai) during the Kharif session of 2004-2005 in the Terai region of Nepal. Four experiments were conducted in randomized block design with three replications. A total of 55 weed species were identified with densities of 240 individual plants per sqm in Radha-4 and 236 individual plants per sqm in Neemai. The annual net primary productivity of paddy crop was maximum (2329.3 g m-2 yr-1 in Radha-4 and 2170.3 g m-2 yr-1 in Neemai) in weed-free plots and lowest (1659.8 g m-2 yr-1 in Radha-4 and 1659.4 g m-2 yr-1 in Neemai) in unweeded plots. Hand weeding was done twice at 25 and 50 days after broadcasting and proved to be better than herbicides in the paddy biomass. The mean maximum biomass of paddy in weed free plots was 2418.7 and 2270.3 g m-2 in Radha-4 and Neemai. This biomass was similar to twice hand weeded plots being 1% lower in both the varieties. Compared to weed-free plots the biomass reduction in Radha-4 and Neemai in herbicides treated plots was lower by 1.4% in both the varieties. Compared to weed-free plots the biomass reduction in unweeded plots was recorded 29% lower in Radha-4 and 23% in Neemai. The weed biomass was highest in unweed plots (516.4 and 436.6 g m-2) and lowest (169.3 and 192.3g m-2 in twice hand-weeded plots. The net annual primary productivity of weeds was highest (437.9 g m>-2 yr-1 in Radha-4 and 376.6 g m-2 yr-1 in Neemai) in unweeded plots and lowest (119.7 g m-2 yr-1 in Radha-4 and 145.5 g m-2 yr-1 in Neemai) in twice hand weeded plots. The trend of grain yield in both the varieties were; weed-free plots (TT) > twice hand-weeded plots (T1) > chemical fertilizer and butachlor plots (T2) > unweeded plots (To).Key words: Paddy; weeds; upland; biomass; Teraidoi: 10.3126/eco.v13i0.1623 Ecoprint (An International Journal of Ecology) Vol. 13, No. 1, 2006 Page 15-22

scholarly journals Parameters sensitivity analysis for a~crop growth model applied to winter wheat in the Huanghuaihai Plain in China

2014 ◽  
Vol 7 (3) ◽  
pp. 3867-3888 ◽  
Author(s):  
M. Liu ◽  
B. He ◽  
A. Lü ◽  
L. Zhou ◽  
J. Wu
Keyword(s):  
Sensitivity Analysis ◽  
Model Calibration ◽  
Regional Scale ◽  
Model Parameters ◽  
Sensitivity Index ◽  
Root Weight ◽  
Sensitivity Indices ◽  
Nutrition Supplement ◽  
Sources Of Variation ◽  
Crop Parameters

Abstract. Parameters sensitivity analysis is a crucial step in effective model calibration. It quantitatively apportions the variation of model output to different sources of variation, and identifies how "sensitive" a model is to changes in the values of model parameters. Through calibration of parameters that are sensitive to model outputs, parameter estimation becomes more efficient. Due to uncertainties associated with yield estimates in a regional assessment, field-based models that perform well at field scale are not accurate enough to model at regional scale. Conducting parameters sensitivity analysis at the regional scale and analyzing the differences of parameter sensitivity between stations would make model calibration and validation in different sub-regions more efficient. Further, it would benefit the model applied to the regional scale. Through simulating 2000 × 22 samples for 10 stations in the Huanghuaihai Plain, this study discovered that TB (Optimal temperature), HI (Normal harvest index), WA (Potential radiation use efficiency), BN2 (Normal fraction of N in crop biomass at mid-season) and RWPC1 (Fraction of root weight at emergency) are more sensitive than other parameters. Parameters that determine nutrition supplement and LAI development have higher global sensitivity indices than first-order indices. For spatial application, soil diversity is crucial because soil is responsible for crop parameters sensitivity index differences between sites.

Satellite-based estimation of net primary productivity for southern China’s grasslands from 1982 to 2012

2017 ◽  
Vol 71 (3) ◽  
pp. 187-201 ◽  
Author(s):  
W Yang ◽  
T Lu ◽  
S Liu ◽  
J Jian ◽  
F Shi ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity

scholarly journals Incentive Function of Audit Opinion for the Increase of Regional Operational Expenditure and Own-Source Revenues Through Sensitivity Analysis in Indonesia

2020 ◽  
Vol 11 (1) ◽  
pp. 20
Author(s):  
Muhammad Ikbal Abdullah ◽  
Andi Chairil Furqan ◽  
Nina Yusnita Yamin ◽  
Fahri Eka Oktora
Keyword(s):  
Sensitivity Analysis ◽  
Significant Influence ◽  
Provincial Government ◽  
Sensitivity Testing ◽  
Audit Opinion ◽  
Absolute Value ◽  
Operating Expenditure ◽  
The Absolute ◽  
Operational Expenditure

This study aims to analyze the sensitivity testing using measurements of realization of regional own-source revenues and operating expenditure and to analyze the extent of the effect of sample differences between Java and non-Java provinces by using samples outside of Java. By using sensitivity analysis, the results found the influence of audit opinion on the performance of the provincial government mediated by the realization of regional operating expenditure. More specifically, when using the measurement of the absolute value of the realization of regional operating expenditure it was found that there was a direct positive and significant influence of audit opinion on the performance of the Provincial Government. However, no significant effect of audit opinion was found on the realization value of regional operating expenditure and the effect of the realization value of regional operating expenditure on the performance of the Provincial Government. This result implies that an increase in audit opinion will be more likely to be used as an incentive for the Provincial Government to increase the realization of regional operating expenditure.

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