scholarly journals Global and Regional Variability and Change in Terrestrial Ecosystems Net Primary Production and NDVI: A Model-Data Comparison

2016 ◽  
Vol 8 (3) ◽  
pp. 177 ◽  
Author(s):  
Rashid Rafique ◽  
Fang Zhao ◽  
Rogier de Jong ◽  
Ning Zeng ◽  
Ghassem Asrar
Keyword(s):  
Primary Production ◽  
Net Primary Production ◽  
Terrestrial Ecosystems ◽  
Model Data ◽  
Regional Variability ◽  
Data Comparison

scholarly journals Quantifying and mapping the human appropriation of net primary production in earth's terrestrial ecosystems

2007 ◽  
Vol 104 (31) ◽  
pp. 12942-12947 ◽  
Author(s):  
H. Haberl ◽  
K. H. Erb ◽  
F. Krausmann ◽  
V. Gaube ◽  
A. Bondeau ◽  
...  
Keyword(s):  
Primary Production ◽  
Net Primary Production ◽  
Terrestrial Ecosystems

scholarly journals Reduction of Global Plant Production due to Droughts from 2001 to 2010: An Analysis with a Process-Based Global Terrestrial Ecosystem Model

2015 ◽  
Vol 19 (16) ◽  
pp. 1-21 ◽  
Author(s):  
Chang Liao ◽  
Qianlai Zhuang
Keyword(s):  
Primary Production ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Ecosystem Model ◽  
Plant Production ◽  
Model Parameters ◽  
Drought Impact ◽  
Terrestrial Ecosystem Model

Abstract Droughts dramatically affect plant production of global terrestrial ecosystems. To date, quantification of this impact remains a challenge because of the complex plant physiological and biochemical processes associated with drought. Here, this study incorporates a drought index into an existing process-based terrestrial ecosystem model to estimate the drought impact on global plant production for the period 2001–10. Global Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data products are used to constrain model parameters and verify the model algorithms. The verified model is then applied to evaluate the drought impact. The study indicates that droughts will reduce GPP by 9.8 g C m−2 month−1 during the study period. On average, drought reduces GPP by 10% globally. As a result, the global GPP decreased from 106.4 to 95.9 Pg C yr−1 while the global net primary production (NPP) decreased from 54.9 to 49.9 Pg C yr−1. This study revises the estimation of the global NPP and suggests that the future quantification of the global carbon budget of terrestrial ecosystems should take the drought impact into account.

scholarly journals Net primary production of terrestrial ecosystems from 2000 to 2009

2012 ◽  
Vol 115 (2) ◽  
pp. 365-378 ◽  
Author(s):  
Christopher Potter ◽  
Steven Klooster ◽  
Vanessa Genovese
Keyword(s):  
Primary Production ◽  
Net Primary Production ◽  
Terrestrial Ecosystems

scholarly journals Effects of carbon turnover time on terrestrial ecosystem carbon storage

2017 ◽  
Vol 14 (23) ◽  
pp. 5441-5454 ◽  
Author(s):  
Yaner Yan ◽  
Xuhui Zhou ◽  
Lifeng Jiang ◽  
Yiqi Luo
Keyword(s):  
Primary Production ◽  
Spatial Variation ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Turnover Time ◽  
Soil C ◽  
C Storage ◽  
Key Factor

Abstract. Carbon (C) turnover time is a key factor in determining C storage capacity in various plant and soil pools as well as terrestrial C sink in a changing climate. However, the effects of C turnover time on ecosystem C storage have not been well explored. In this study, we compared mean C turnover times (MTTs) of ecosystem and soil, examined their variability to climate, and then quantified the spatial variation in ecosystem C storage over time from changes in C turnover time and/or net primary production (NPP). Our results showed that mean ecosystem MTT based on gross primary production (GPP; MTTEC_GPP =  Cpool/GPP, 25.0 ± 2.7 years) was shorter than soil MTT (MTTsoil =  Csoil/NPP, 35.5 ± 1.2 years) and NPP-based ecosystem MTT (MTTEC_NPP =  Cpool/NPP, 50.8 ± 3 years; Cpool and Csoil referred to ecosystem or soil C storage, respectively). On the biome scale, temperature is the best predictor for MTTEC (R2 =  0.77, p < 0.001) and MTTsoil (R2 =  0.68, p < 0.001), while the inclusion of precipitation in the model did not improve the performance of MTTEC (R2 =  0.76, p < 0.001). Ecosystem MTT decreased by approximately 4 years from 1901 to 2011 when only temperature was considered, resulting in a large C release from terrestrial ecosystems. The resultant terrestrial C release caused by the decrease in MTT only accounted for about 13.5 % of that due to the change in NPP uptake (159.3 ± 1.45 vs. 1215.4 ± 11.0 Pg C). However, the larger uncertainties in the spatial variation of MTT than temporal changes could lead to a greater impact on ecosystem C storage, which deserves further study in the future.

scholarly journals Water use efficiency of net primary production in global terrestrial ecosystems

2015 ◽  
Vol 124 (5) ◽  
pp. 921-931 ◽  
Author(s):  
Lei Xia ◽  
Fei Wang ◽  
Xingmin Mu ◽  
Kai Jin ◽  
Wenyi Sun ◽  
...  
Keyword(s):  
Primary Production ◽  
Water Use Efficiency ◽  
Water Use ◽  
Net Primary Production ◽  
Terrestrial Ecosystems ◽  
Use Efficiency

scholarly journals Generation of High Resolution Vegetation Productivity from a Downscaling Method

2018 ◽  
Vol 10 (11) ◽  
pp. 1748 ◽  
Author(s):  
Tao Yu ◽  
Rui Sun ◽  
Zhiqiang Xiao ◽  
Qiang Zhang ◽  
Juanmin Wang ◽  
...  
Keyword(s):  
High Resolution ◽  
Primary Production ◽  
Land Surface ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Terrestrial Ecosystems ◽  
Vegetation Productivity ◽  
Area Index ◽  
Multi Scale ◽  
Downscaling Method

Accurately estimating vegetation productivity is important in the research of terrestrial ecosystems, carbon cycles and climate change. Although several gross primary production (GPP) and net primary production (NPP) products have been generated and many algorithms developed, advances are still needed to exploit multi-scale data streams for producing GPP and NPP with higher spatial and temporal resolution. In this paper, a method to generate high spatial resolution (30 m) GPP and NPP products was developed based on multi-scale remote sensing data and a downscaling method. First, high resolution fraction photosynthetically active radiation (FPAR) and leaf area index (LAI) were obtained by using a regression tree approach and the spatial and temporal adaptive reflectance fusion model (STARFM). Second, the GPP and NPP were estimated from a multi-source data synergized quantitative algorithm. Finally, the vegetation productivity estimates were validated with the ground-based field data, and were compared with MODerate Resolution Imaging Spectroradiometer (MODIS) and estimated Global LAnd Surface Satellite (GLASS) products. Results of this paper indicated that downscaling methods have great potential in generating high resolution GPP and NPP.

Sign in / Sign up

Export Citation Format

Share Document