View in EDS

Improved global simulations of gross primary product based on a new definition of water stress factor and a separate treatment of C3 and C4 plants.

Saved in:
Bibliographic Details
Title: Improved global simulations of gross primary product based on a new definition of water stress factor and a separate treatment of C3 and C4 plants.
Authors: Yan, Hao1,2 yanhaon@hotmail.com, Wang, Shao-qiang3 sqwang@igsnrr.ac.cn, Billesbach, Dave4 dbillesbach1@unl.edu, Oechel, Walter5 oechel@sunstroke.sdsu.edu, Bohrer, Gil6 bohrer.17@osu.edu, Meyers, Tilden7 tilden.meyers@noaa.gov, Martin, Timothy A.8 tamartin@ufl.edu, Matamala, Roser9 matamala@anl.gov, Phillips, Richard P.10 rpp6@indiana.edu, Rahman, Faiz11 farahman@indiana.edu, Yu, Qin12 qy4a@virginia.edu, Shugart, Herman H.2 hhs@virginia.edu
Source: Ecological Modelling. Feb2015, Vol. 297, p42-59. 18p.
Subjects: Primary productivity (Biology) measurement, Ecology simulation methods, Carbon cycle, Spatio-temporal variation, Carbon 3 photosynthesis, Carbon 4 photosynthesis, Evapotranspiration, Evaporative power, Mathematical models
Abstract: Accurate simulation of terrestrial gross primary production (GPP), the largest global carbon flux, benefits our understanding of carbon cycle and its source of variation. This paper presents a novel light use efficiency-based GPP model called the terrestrial ecosystem carbon flux model (TEC) driven by MODIS FPAR and climate data coupled with a precipitation-driven evapotranspiration (E) model ( Yan et al., 2012 ). TEC incorporated a new water stress factor, defined as the ratio of actual E to Priestley and Taylor (1972) potential evaporation (EPT). A maximum light use efficiency (ϵ*) of 1.8 gC MJ−1 and 2.76 gC MJ−1 was applied to C3 and C4 ecosystems, respectively. An evaluation at 18 eddy covariance flux towers representing various ecosystem types under various climates indicates that the TEC model predicted monthly average GPP for all sites with overall statistics of r = 0.85, RMSE = 2.20 gC m−2 day−1, and bias = −0.05 gC m−2 day−1. For comparison the MODIS GPP products (MOD17A2) had overall statistics of r = 0.73, RMSE = 2.82 gC m−2 day−1, and bias = −0.31 gC m−2 day−1 for this same set of data. In this case, the TEC model performed better than MOD17A2 products, especially for C4 plants. We obtained an estimate of global mean annual GPP flux at 128.2 ± 1.5 Pg C yr −1 from monthly MODIS FPAR and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA reanalysis data at a 1.0° spatial resolution over 11 year period from 2000 to 2010. This falls in the range of published land GPP estimates that consider the effect of C4 and C3 species. The TEC model with its new definition of water stress factor and its parameterization of C4 and C3 plants should help better understand the coupled climate-carbon cycle processes. [ABSTRACT FROM AUTHOR]
Copyright of Ecological Modelling is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 100508731
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Improved global simulations of gross primary product based on a new definition of water stress factor and a separate treatment of C3 and C4 plants.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Yan%2C+Hao%22">Yan, Hao</searchLink><relatesTo>1,2</relatesTo><i> yanhaon@hotmail.com</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Shao-qiang%22">Wang, Shao-qiang</searchLink><relatesTo>3</relatesTo><i> sqwang@igsnrr.ac.cn</i><br /><searchLink fieldCode="AR" term="%22Billesbach%2C+Dave%22">Billesbach, Dave</searchLink><relatesTo>4</relatesTo><i> dbillesbach1@unl.edu</i><br /><searchLink fieldCode="AR" term="%22Oechel%2C+Walter%22">Oechel, Walter</searchLink><relatesTo>5</relatesTo><i> oechel@sunstroke.sdsu.edu</i><br /><searchLink fieldCode="AR" term="%22Bohrer%2C+Gil%22">Bohrer, Gil</searchLink><relatesTo>6</relatesTo><i> bohrer.17@osu.edu</i><br /><searchLink fieldCode="AR" term="%22Meyers%2C+Tilden%22">Meyers, Tilden</searchLink><relatesTo>7</relatesTo><i> tilden.meyers@noaa.gov</i><br /><searchLink fieldCode="AR" term="%22Martin%2C+Timothy+A%2E%22">Martin, Timothy A.</searchLink><relatesTo>8</relatesTo><i> tamartin@ufl.edu</i><br /><searchLink fieldCode="AR" term="%22Matamala%2C+Roser%22">Matamala, Roser</searchLink><relatesTo>9</relatesTo><i> matamala@anl.gov</i><br /><searchLink fieldCode="AR" term="%22Phillips%2C+Richard+P%2E%22">Phillips, Richard P.</searchLink><relatesTo>10</relatesTo><i> rpp6@indiana.edu</i><br /><searchLink fieldCode="AR" term="%22Rahman%2C+Faiz%22">Rahman, Faiz</searchLink><relatesTo>11</relatesTo><i> farahman@indiana.edu</i><br /><searchLink fieldCode="AR" term="%22Yu%2C+Qin%22">Yu, Qin</searchLink><relatesTo>12</relatesTo><i> qy4a@virginia.edu</i><br /><searchLink fieldCode="AR" term="%22Shugart%2C+Herman+H%2E%22">Shugart, Herman H.</searchLink><relatesTo>2</relatesTo><i> hhs@virginia.edu</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Ecological+Modelling%22">Ecological Modelling</searchLink>. Feb2015, Vol. 297, p42-59. 18p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Primary+productivity+%28Biology%29+measurement%22">Primary productivity (Biology) measurement</searchLink><br /><searchLink fieldCode="DE" term="%22Ecology+simulation+methods%22">Ecology simulation methods</searchLink><br /><searchLink fieldCode="DE" term="%22Carbon+cycle%22">Carbon cycle</searchLink><br /><searchLink fieldCode="DE" term="%22Spatio-temporal+variation%22">Spatio-temporal variation</searchLink><br /><searchLink fieldCode="DE" term="%22Carbon+3+photosynthesis%22">Carbon 3 photosynthesis</searchLink><br /><searchLink fieldCode="DE" term="%22Carbon+4+photosynthesis%22">Carbon 4 photosynthesis</searchLink><br /><searchLink fieldCode="DE" term="%22Evapotranspiration%22">Evapotranspiration</searchLink><br /><searchLink fieldCode="DE" term="%22Evaporative+power%22">Evaporative power</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Accurate simulation of terrestrial gross primary production (GPP), the largest global carbon flux, benefits our understanding of carbon cycle and its source of variation. This paper presents a novel light use efficiency-based GPP model called the terrestrial ecosystem carbon flux model (TEC) driven by MODIS FPAR and climate data coupled with a precipitation-driven evapotranspiration (E) model ( Yan et al., 2012 ). TEC incorporated a new water stress factor, defined as the ratio of actual E to Priestley and Taylor (1972) potential evaporation (EPT). A maximum light use efficiency (ϵ*) of 1.8 gC MJ−1 and 2.76 gC MJ−1 was applied to C3 and C4 ecosystems, respectively. An evaluation at 18 eddy covariance flux towers representing various ecosystem types under various climates indicates that the TEC model predicted monthly average GPP for all sites with overall statistics of r = 0.85, RMSE = 2.20 gC m−2 day−1, and bias = −0.05 gC m−2 day−1. For comparison the MODIS GPP products (MOD17A2) had overall statistics of r = 0.73, RMSE = 2.82 gC m−2 day−1, and bias = −0.31 gC m−2 day−1 for this same set of data. In this case, the TEC model performed better than MOD17A2 products, especially for C4 plants. We obtained an estimate of global mean annual GPP flux at 128.2 ± 1.5 Pg C yr −1 from monthly MODIS FPAR and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA reanalysis data at a 1.0° spatial resolution over 11 year period from 2000 to 2010. This falls in the range of published land GPP estimates that consider the effect of C4 and C3 species. The TEC model with its new definition of water stress factor and its parameterization of C4 and C3 plants should help better understand the coupled climate-carbon cycle processes. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Ecological Modelling is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=100508731
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.ecolmodel.2014.11.002
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 18
        StartPage: 42
    Subjects:
      – SubjectFull: Primary productivity (Biology) measurement
        Type: general
      – SubjectFull: Ecology simulation methods
        Type: general
      – SubjectFull: Carbon cycle
        Type: general
      – SubjectFull: Spatio-temporal variation
        Type: general
      – SubjectFull: Carbon 3 photosynthesis
        Type: general
      – SubjectFull: Carbon 4 photosynthesis
        Type: general
      – SubjectFull: Evapotranspiration
        Type: general
      – SubjectFull: Evaporative power
        Type: general
      – SubjectFull: Mathematical models
        Type: general
    Titles:
      – TitleFull: Improved global simulations of gross primary product based on a new definition of water stress factor and a separate treatment of C3 and C4 plants.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Yan, Hao
      – PersonEntity:
          Name:
            NameFull: Wang, Shao-qiang
      – PersonEntity:
          Name:
            NameFull: Billesbach, Dave
      – PersonEntity:
          Name:
            NameFull: Oechel, Walter
      – PersonEntity:
          Name:
            NameFull: Bohrer, Gil
      – PersonEntity:
          Name:
            NameFull: Meyers, Tilden
      – PersonEntity:
          Name:
            NameFull: Martin, Timothy A.
      – PersonEntity:
          Name:
            NameFull: Matamala, Roser
      – PersonEntity:
          Name:
            NameFull: Phillips, Richard P.
      – PersonEntity:
          Name:
            NameFull: Rahman, Faiz
      – PersonEntity:
          Name:
            NameFull: Yu, Qin
      – PersonEntity:
          Name:
            NameFull: Shugart, Herman H.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 10
              M: 02
              Text: Feb2015
              Type: published
              Y: 2015
          Identifiers:
            – Type: issn-print
              Value: 03043800
          Numbering:
            – Type: volume
              Value: 297
          Titles:
            – TitleFull: Ecological Modelling
              Type: main
ResultId 1