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Title: Explaining inter-annual variability of gross primary productivity from plant phenology and physiology

Authors:
; ; ; ; ; ; ;
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1397522
Resource Type:
Journal Article: Publisher's Accepted Manuscript
Journal Name:
Agricultural and Forest Meteorology
Additional Journal Information:
Journal Volume: 226-227; Journal Issue: C; Related Information: CHORUS Timestamp: 2017-10-04 21:34:09; Journal ID: ISSN 0168-1923
Publisher:
Elsevier
Country of Publication:
Netherlands
Language:
English

Citation Formats

Zhou, Sha, Zhang, Yao, Caylor, Kelly K., Luo, Yiqi, Xiao, Xiangming, Ciais, Philippe, Huang, Yuefei, and Wang, Guangqian. Explaining inter-annual variability of gross primary productivity from plant phenology and physiology. Netherlands: N. p., 2016. Web. doi:10.1016/j.agrformet.2016.06.010.
Zhou, Sha, Zhang, Yao, Caylor, Kelly K., Luo, Yiqi, Xiao, Xiangming, Ciais, Philippe, Huang, Yuefei, & Wang, Guangqian. Explaining inter-annual variability of gross primary productivity from plant phenology and physiology. Netherlands. doi:10.1016/j.agrformet.2016.06.010.
Zhou, Sha, Zhang, Yao, Caylor, Kelly K., Luo, Yiqi, Xiao, Xiangming, Ciais, Philippe, Huang, Yuefei, and Wang, Guangqian. 2016. "Explaining inter-annual variability of gross primary productivity from plant phenology and physiology". Netherlands. doi:10.1016/j.agrformet.2016.06.010.
@article{osti_1397522,
title = {Explaining inter-annual variability of gross primary productivity from plant phenology and physiology},
author = {Zhou, Sha and Zhang, Yao and Caylor, Kelly K. and Luo, Yiqi and Xiao, Xiangming and Ciais, Philippe and Huang, Yuefei and Wang, Guangqian},
abstractNote = {},
doi = {10.1016/j.agrformet.2016.06.010},
journal = {Agricultural and Forest Meteorology},
number = C,
volume = 226-227,
place = {Netherlands},
year = 2016,
month =
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1016/j.agrformet.2016.06.010

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  • Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000-2010 total global GPP estimated from the model ensemble to be 117±13 Pg C yr-1 (mean ± 1 standard deviation), whichmore » was higher than MODIS (112 Pg C yr-1), and close to the MTE (120 Pg C yr-1). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.« less
  • The largest global source of secondary organic aerosol (SOA) in the atmosphere is derived from the oxidation of biogenic emissions. Plant stressors associated with a changing environment can alter both the quantity and composition of the compounds that are emitted. Alterations to the biogenic volatile organic compound (BVOC) profile could impact the characteristics of the SOA formed from those emissions. This study investigated the impacts of one global change stressor, increased herbivory, on the composition of SOA derived from real plant emissions. Herbivory was simulated via application of methyl jasmonate (MeJA), a proxy compound. Experiments were repeated under pre- andmore » post-treatment conditions for six different coniferous plant types. Volatile organic compounds (VOCs) emitted from the plants were oxidized to form SOA via dark ozone-initiated chemistry. The SOA chemical composition was measured using a Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-AMS). The aerosol mass spectra of pre-treatment biogenic SOA from all plant types tended to be similar with correlations usually greater than or equal to 0.90. The presence of a stressor produced characteristic differences in the SOA mass spectra. Specifically, the following m/z were identified as a possible biogenic stress AMS marker with the corresponding HR ion(s) shown in parentheses: m/z 31 (CH 3O +), m/z 58 (C 2H 2O 2 +, C 3H 6O +), m/z 29 (C 2H 5 +), m/z 57 (C 3H 5O +), m/z 59 (C 2H 3O 2 +, C 3H 7O +), m/z 71 (C 3H 3O 2 +, C 4H 7O +), and m/z 83 (C 5H 7O +). The first aerosol mass spectrum of SOA generated from the oxidation of the plant stress hormone, MeJA, is also presented. Elemental analysis results demonstrated an O : C range of baseline biogenic SOA between 0.3 and 0.47. The O : C of standard MeJA SOA was 0.52. Furthermore the results presented here could be used to help identify a biogenic plant stress marker in ambient data sets collected in forest environments.« less
    Cited by 3
  • The largest global source of secondary organic aerosol (SOA) in the atmosphere is derived from the oxidation of biogenic emissions. Plant stressors associated with a changing environment can alter both the quantity and composition of the compounds that are emitted. Alterations to the biogenic volatile organic compound (BVOC) profile could impact the characteristics of the SOA formed from those emissions. This study investigated the impacts of one global change stressor, increased herbivory, on the composition of SOA derived from real plant emissions. Herbivory was simulated via application of methyl jasmonate (MeJA), a proxy compound. Experiments were repeated under pre- andmore » post-treatment conditions for six different coniferous plant types. Volatile organic compounds (VOCs) emitted from the plants were oxidized to form SOA via dark ozone-initiated chemistry. The SOA chemical composition was measured using a Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-AMS). The aerosol mass spectra of pre-treatment biogenic SOA from all plant types tended to be similar with correlations usually greater than or equal to 0.90. The presence of a stressor produced characteristic differences in the SOA mass spectra. Specifically, the following m/z were identified as a possible biogenic stress AMS marker with the corresponding HR ion(s) shown in parentheses: m/z 31 (CH 3O +), m/z 58 (C 2H 2O 2 +, C 3H 6O +), m/z 29 (C 2H 5 +), m/z 57 (C 3H 5O +), m/z 59 (C 2H 3O 2 +, C 3H 7O +), m/z 71 (C 3H 3O 2 +, C 4H 7O +), and m/z 83 (C 5H 7O +). The first aerosol mass spectrum of SOA generated from the oxidation of the plant stress hormone, MeJA, is also presented. Elemental analysis results demonstrated an O : C range of baseline biogenic SOA between 0.3 and 0.47. The O : C of standard MeJA SOA was 0.52. Furthermore the results presented here could be used to help identify a biogenic plant stress marker in ambient data sets collected in forest environments.« less