Effects of foliage clumping on the estimation of global terrestrial gross primary productivity
Identifieur interne : 001528 ( Istex/Corpus ); précédent : 001527; suivant : 001529Effects of foliage clumping on the estimation of global terrestrial gross primary productivity
Auteurs : Jing M. Chen ; Gang Mo ; Jan Pisek ; Jane Liu ; Feng Deng ; Misa Ishizawa ; Douglas ChanSource :
- Global Biogeochemical Cycles [ 0886-6236 ] ; 2012-03.
Abstract
Sunlit and shaded leaf separation proposed by Norman (1982) is an effective way to upscale from leaf to canopy in modeling vegetation photosynthesis. The Boreal Ecosystem Productivity Simulator (BEPS) makes use of this methodology, and has been shown to be reliable in modeling the gross primary productivity (GPP) derived from CO2flux and tree ring measurements. In this study, we use BEPS to investigate the effect of canopy architecture on the global distribution of GPP. For this purpose, we use not only leaf area index (LAI) but also the first ever global map of the foliage clumping index derived from the multiangle satellite sensor POLDER at 6 km resolution. The clumping index, which characterizes the degree of the deviation of 3‐dimensional leaf spatial distributions from the random case, is used to separate sunlit and shaded LAI values for a given LAI. Our model results show that global GPP in 2003 was 132 ± 22 Pg C. Relative to this baseline case, our results also show: (1) global GPP is overestimated by 12% when accurate LAI is available but clumping is ignored, and (2) global GPP is underestimated by 9% when the effective LAI is available and clumping is ignored. The clumping effects in both cases are statistically significant (p < 0.001). The effective LAI is often derived from remote sensing by inverting the measured canopy gap fraction to LAI without considering the clumping. Global GPP would therefore be generally underestimated when remotely sensed LAI (actually effective LAI by our definition) is used. This is due to the underestimation of the shaded LAI and therefore the contribution of shaded leaves to GPP. We found that shaded leaves contribute 50%, 38%, 37%, 39%, 26%, 29% and 21% to the total GPP for broadleaf evergreen forest, broadleaf deciduous forest, evergreen conifer forest, deciduous conifer forest, shrub, C4 vegetation, and other vegetation, respectively. The global average of this ratio is 35%.
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DOI: 10.1029/2010GB003996
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Chen</name><affiliation><mods:affiliation>International Institute of Earth System Science, Nanjing University, Nanjing, China</mods:affiliation></affiliation><affiliation><mods:affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: chenj@geog.utoronto.ca</mods:affiliation></affiliation></author><author><name sortKey="Mo, Gang" sort="Mo, Gang" uniqKey="Mo G" first="Gang" last="Mo">Gang Mo</name><affiliation><mods:affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</mods:affiliation></affiliation></author><author><name sortKey="Pisek, Jan" sort="Pisek, Jan" uniqKey="Pisek J" first="Jan" last="Pisek">Jan Pisek</name><affiliation><mods:affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</mods:affiliation></affiliation><affiliation><mods:affiliation>Tartu Observatory 61602, Toravere, Estonia</mods:affiliation></affiliation></author><author><name sortKey="Liu, Jane" sort="Liu, Jane" uniqKey="Liu J" first="Jane" last="Liu">Jane Liu</name><affiliation><mods:affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</mods:affiliation></affiliation></author><author><name sortKey="Deng, Feng" sort="Deng, Feng" uniqKey="Deng F" first="Feng" last="Deng">Feng Deng</name><affiliation><mods:affiliation>International Institute of Earth System Science, Nanjing University, Nanjing, China</mods:affiliation></affiliation></author><author><name sortKey="Ishizawa, Misa" sort="Ishizawa, Misa" uniqKey="Ishizawa M" first="Misa" last="Ishizawa">Misa Ishizawa</name><affiliation><mods:affiliation>Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada</mods:affiliation></affiliation></author><author><name sortKey="Chan, Douglas" sort="Chan, Douglas" uniqKey="Chan D" first="Douglas" last="Chan">Douglas Chan</name><affiliation><mods:affiliation>Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:1BE91345AC1E39E7C900AB319CB7B6B9B953E9E6</idno><date when="2012" year="2012">2012</date><idno type="doi">10.1029/2010GB003996</idno><idno type="url">https://api.istex.fr/document/1BE91345AC1E39E7C900AB319CB7B6B9B953E9E6/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">001528</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">001528</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Effects of foliage clumping on the estimation of global terrestrial gross primary productivity</title><author><name sortKey="Chen, Jing M" sort="Chen, Jing M" uniqKey="Chen J" first="Jing M." last="Chen">Jing M. Chen</name><affiliation><mods:affiliation>International Institute of Earth System Science, Nanjing University, Nanjing, China</mods:affiliation></affiliation><affiliation><mods:affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: chenj@geog.utoronto.ca</mods:affiliation></affiliation></author><author><name sortKey="Mo, Gang" sort="Mo, Gang" uniqKey="Mo G" first="Gang" last="Mo">Gang Mo</name><affiliation><mods:affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</mods:affiliation></affiliation></author><author><name sortKey="Pisek, Jan" sort="Pisek, Jan" uniqKey="Pisek J" first="Jan" last="Pisek">Jan Pisek</name><affiliation><mods:affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</mods:affiliation></affiliation><affiliation><mods:affiliation>Tartu Observatory 61602, Toravere, Estonia</mods:affiliation></affiliation></author><author><name sortKey="Liu, Jane" sort="Liu, Jane" uniqKey="Liu J" first="Jane" last="Liu">Jane Liu</name><affiliation><mods:affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</mods:affiliation></affiliation></author><author><name sortKey="Deng, Feng" sort="Deng, Feng" uniqKey="Deng F" first="Feng" last="Deng">Feng Deng</name><affiliation><mods:affiliation>International Institute of Earth System Science, Nanjing University, Nanjing, China</mods:affiliation></affiliation></author><author><name sortKey="Ishizawa, Misa" sort="Ishizawa, Misa" uniqKey="Ishizawa M" first="Misa" last="Ishizawa">Misa Ishizawa</name><affiliation><mods:affiliation>Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada</mods:affiliation></affiliation></author><author><name sortKey="Chan, Douglas" sort="Chan, Douglas" uniqKey="Chan D" first="Douglas" last="Chan">Douglas Chan</name><affiliation><mods:affiliation>Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Global Biogeochemical Cycles</title><title level="j" type="abbrev">Global Biogeochem. Cycles</title><idno type="ISSN">0886-6236</idno><idno type="eISSN">1944-9224</idno><imprint><publisher>Blackwell Publishing Ltd</publisher><date type="published" when="2012-03">2012-03</date><biblScope unit="volume">26</biblScope><biblScope unit="issue">1</biblScope><biblScope unit="page" from="/">n/a</biblScope><biblScope unit="page" to="/">n/a</biblScope></imprint><idno type="ISSN">0886-6236</idno></series><idno type="istex">1BE91345AC1E39E7C900AB319CB7B6B9B953E9E6</idno><idno type="DOI">10.1029/2010GB003996</idno><idno type="ArticleID">2010GB003996</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0886-6236</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract">Sunlit and shaded leaf separation proposed by Norman (1982) is an effective way to upscale from leaf to canopy in modeling vegetation photosynthesis. The Boreal Ecosystem Productivity Simulator (BEPS) makes use of this methodology, and has been shown to be reliable in modeling the gross primary productivity (GPP) derived from CO2flux and tree ring measurements. In this study, we use BEPS to investigate the effect of canopy architecture on the global distribution of GPP. For this purpose, we use not only leaf area index (LAI) but also the first ever global map of the foliage clumping index derived from the multiangle satellite sensor POLDER at 6 km resolution. The clumping index, which characterizes the degree of the deviation of 3‐dimensional leaf spatial distributions from the random case, is used to separate sunlit and shaded LAI values for a given LAI. Our model results show that global GPP in 2003 was 132 ± 22 Pg C. Relative to this baseline case, our results also show: (1) global GPP is overestimated by 12% when accurate LAI is available but clumping is ignored, and (2) global GPP is underestimated by 9% when the effective LAI is available and clumping is ignored. The clumping effects in both cases are statistically significant (p < 0.001). The effective LAI is often derived from remote sensing by inverting the measured canopy gap fraction to LAI without considering the clumping. Global GPP would therefore be generally underestimated when remotely sensed LAI (actually effective LAI by our definition) is used. This is due to the underestimation of the shaded LAI and therefore the contribution of shaded leaves to GPP. We found that shaded leaves contribute 50%, 38%, 37%, 39%, 26%, 29% and 21% to the total GPP for broadleaf evergreen forest, broadleaf deciduous forest, evergreen conifer forest, deciduous conifer forest, shrub, C4 vegetation, and other vegetation, respectively. The global average of this ratio is 35%.</div></front></TEI><istex><corpusName>wiley</corpusName><author><json:item><name>Jing M. Chen</name><affiliations><json:string>International Institute of Earth System Science, Nanjing University, Nanjing, China</json:string><json:string>Department of Geography, University of Toronto, Toronto, Ontario, Canada</json:string><json:string>E-mail: chenj@geog.utoronto.ca</json:string></affiliations></json:item><json:item><name>Gang Mo</name><affiliations><json:string>Department of Geography, University of Toronto, Toronto, Ontario, Canada</json:string></affiliations></json:item><json:item><name>Jan Pisek</name><affiliations><json:string>Department of Geography, University of Toronto, Toronto, Ontario, Canada</json:string><json:string>Tartu Observatory 61602, Toravere, Estonia</json:string></affiliations></json:item><json:item><name>Jane Liu</name><affiliations><json:string>Department of Geography, University of Toronto, Toronto, Ontario, Canada</json:string></affiliations></json:item><json:item><name>Feng Deng</name><affiliations><json:string>International Institute of Earth System Science, Nanjing University, Nanjing, China</json:string></affiliations></json:item><json:item><name>Misa Ishizawa</name><affiliations><json:string>Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada</json:string></affiliations></json:item><json:item><name>Douglas Chan</name><affiliations><json:string>Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>LAI</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>canopy radiation</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>clumping index</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>global GPP</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>photosynthesis model</value></json:item></subject><articleId><json:string>2010GB003996</json:string></articleId><language><json:string>eng</json:string></language><originalGenre><json:string>article</json:string></originalGenre><qualityIndicators><score>9.5</score><pdfVersion>1.6</pdfVersion><pdfPageSize>612 x 792 pts (letter)</pdfPageSize><refBibsNative>true</refBibsNative><abstractCharCount>1952</abstractCharCount><pdfWordCount>13637</pdfWordCount><pdfCharCount>81555</pdfCharCount><pdfPageCount>18</pdfPageCount><abstractWordCount>316</abstractWordCount></qualityIndicators><title>Effects of foliage clumping on the estimation of global terrestrial gross primary productivity</title><refBibs><json:item><author><json:item><name>P. B. Alton</name></json:item><json:item><name>R. Ellis</name></json:item><json:item><name>S. O. Los</name></json:item><json:item><name>P. R. North</name></json:item></author><host><volume>112</volume><author></author><title>J. Geophys. Res.</title></host><title>Improved global simulations of gross primary product based on a separate and explicit treatment of diffuse and direct sunlight</title></json:item><json:item><author><json:item><name>D. F. Baker</name></json:item></author><host><volume>20</volume><author></author><title>Global Biogeochem. Cycles</title></host><title>TransCom 3 inversion intercomparison: Impact of transport model errors on the interannual variability of regional CO2 fluxes, 1988–2003</title></json:item><json:item><author><json:item><name>D. Baldocchi</name></json:item></author><host><volume>14</volume><pages><last>1079</last><first>1069</first></pages><author></author><title>Tree Physiol.</title></host><title>An analytical solution for coupled leaf photosynthesis and stomatal conductance models</title></json:item><json:item><author><json:item><name>D. D. Baldocchi</name></json:item><json:item><name>P. C. Harley</name></json:item></author><host><volume>18</volume><pages><last>1173</last><first>1157</first></pages><author></author><title>Plant Cell Environ.</title></host><title>Scaling carbon dioxide and water vapor exchange from leaf to canopy in a deciduous forest: Model testing and application</title></json:item><json:item><author><json:item><name>D. D. Baldocchi</name></json:item><json:item><name>K. B. Wilson</name></json:item><json:item><name>L. H. Gu</name></json:item></author><host><volume>22</volume><pages><last>1077</last><first>1065</first></pages><author></author><title>Tree Physiol.</title></host><title>How the environment, canopy structure and canopy physiological functioning influence carbon, water and energy fluxes of a temperate broad‐leaved deciduous forest: An assessment with the biophysical model CANOAK</title></json:item><json:item><host><author></author><title>An analysis of stomatal conductance</title></host></json:item><json:item><author><json:item><name>F. Baret</name></json:item></author><host><volume>44</volume><pages><last>1803</last><first>1794</first></pages><author></author><title>IEEE Trans. Geosci. Remote Sens.</title></host><title>Evaluation of the representativeness of networks of sites for the global validation and inter‐comparison of land biophysical products: Proposition of the CEOS‐BELMANIP</title></json:item><json:item><author><json:item><name>F. Baret</name></json:item></author><host><volume>110</volume><pages><last>286</last><first>275</first></pages><author></author><title>Remote Sens. Environ.</title></host><title>LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithm</title></json:item><json:item><author><json:item><name>C. Beer</name></json:item></author><host><volume>329</volume><pages><last>838</last><first>834</first></pages><author></author><title>Science</title></host><title>Terrestrial gross carbon dioxide uptake: Global distribution and covariation with climate</title></json:item><json:item><author><json:item><name>T. A. Black</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>X. Lee</name></json:item><json:item><name>R. M. Sagar</name></json:item></author><host><volume>21</volume><pages><last>1028</last><first>1020</first></pages><author></author><title>Can. J. For. Res.</title></host><title>Characteristics of shortwave and longwave irradiances under a Douglas‐fir forest stand</title></json:item><json:item><author><json:item><name>G. B. Bonan</name></json:item></author><host><volume>27</volume><pages><last>781</last><first>767</first></pages><author></author><title>Water Resour. Res.</title></host><title>A biophysical surface‐energy budget analysis of soil‐temperature in the boreal forests of Interior Alaska</title></json:item><json:item><host><pages><last>145</last><first>129</first></pages><author></author><title>Campbell, G. S., and J. M. Norman (1998), An Introduction to Environmental Biophysics, pp. 129–145, Springer, New York, doi:10.1007/978‐1‐4612‐1626‐1_9.</title></host></json:item><json:item><author><json:item><name>J. G. Canadell</name></json:item><json:item><name>C. Le Quéré</name></json:item><json:item><name>M. R. Raupach</name></json:item><json:item><name>C. B. Field</name></json:item><json:item><name>E. T. Buitehuis</name></json:item><json:item><name>P. Ciais</name></json:item><json:item><name>T. J. Conway</name></json:item><json:item><name>N. P. Gillett</name></json:item><json:item><name>R. A. Houghton</name></json:item><json:item><name>G. Marland</name></json:item></author><host><volume>104</volume><pages><last>18,870</last><first>18,866</first></pages><author></author><title>Proc. Natl. Acad. Sci. U. S. A.</title></host><title>Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks</title></json:item><json:item><author><json:item><name>B. Chen</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>G. Mo</name></json:item><json:item><name>K. Yuan</name></json:item><json:item><name>K. Higuchi</name></json:item><json:item><name>D. Chan</name></json:item></author><host><volume>8</volume><pages><last>143</last><first>123</first></pages><author></author><title>J. Hydrometeorol.</title></host><title>Modeling and scaling coupled energy, water, and carbon fluxes based on remote sensing: An application to Canada's landmass</title></json:item><json:item><author><json:item><name>B. Chen</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>G. Mo</name></json:item><json:item><name>T. A. Black</name></json:item></author><host><volume>22</volume><author></author><title>Global Biogeochem. Cycles</title></host><title>Comparison of regional carbon flux estimates from CO2 concentration measurements and remote sensing based footprint integration</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item></author><host><volume>34</volume><pages><last>1368</last><first>1353</first></pages><author></author><title>IEEE Trans. Geosci. Remote Sens.</title></host><title>Canopy architecture and remote sensing of the fraction of photosynthetically active radiation in boreal conifer stands</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item></author><host><volume>80</volume><pages><last>163</last><first>135</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>Optically based methods for measuring seasonal variation in leaf area index of boreal conifer forests</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item><json:item><name>T. A. Black</name></json:item></author><host><volume>15</volume><pages><last>429</last><first>421</first></pages><author></author><title>Plant Cell Environ.</title></host><title>Defining leaf area index for non‐flat leaves</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item><json:item><name>J. Cihlar</name></json:item></author><host><volume>33</volume><pages><last>787</last><first>777</first></pages><author></author><title>IEEE Trans. Geosci. Remote Sens.</title></host><title>Quantifying the effect of canopy architecture on optical measurements of leaf area index using two gap size analysis methods</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item><json:item><name>S. Leblanc</name></json:item></author><host><volume>35</volume><pages><last>1337</last><first>1316</first></pages><author></author><title>IEEE Trans. Geosci. Remote Sens.</title></host><title>A 4‐scale bidirectional reflection model based on canopy architecture</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item><json:item><name>S. G. Leblanc</name></json:item></author><host><volume>39</volume><pages><last>1071</last><first>1061</first></pages><author></author><title>IEEE Trans. Geosci. Remote Sens.</title></host><title>Multiple‐scattering scheme useful for hyperspectral geometrical optical modelling</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item><json:item><name>T. A. Black</name></json:item><json:item><name>R. S. Adams</name></json:item></author><host><volume>56</volume><pages><last>143</last><first>129</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>Evaluation of hemispherical photography for determining plant area index and geometry of a forest stand</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item><json:item><name>P. M. Rich</name></json:item><json:item><name>T. S. Gower</name></json:item><json:item><name>J. M. Norman</name></json:item><json:item><name>S. Plummer</name></json:item></author><host><volume>102</volume><pages><last>29,443</last><first>29,429</first></pages><author></author><title>J. Geophys. Res.</title></host><title>Leaf area index of boreal forests: Theory, techniques and measurements</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item><json:item><name>J. Liu</name></json:item><json:item><name>J. Cihlar</name></json:item><json:item><name>M. L. Goulden</name></json:item></author><host><volume>124</volume><pages><last>119</last><first>99</first></pages><author></author><title>Ecol. Modell.</title></host><title>Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item><json:item><name>W. Ju</name></json:item><json:item><name>J. Cihlar</name></json:item><json:item><name>D. Price</name></json:item><json:item><name>J. Liu</name></json:item><json:item><name>W. Chen</name></json:item><json:item><name>J. Pan</name></json:item><json:item><name>T. A. Black</name></json:item><json:item><name>A. Barr</name></json:item></author><host><volume>55</volume><pages><last>641</last><first>622</first></pages><author></author><title>Tellus, Ser. B</title></host><title>Spatial distribution of carbon sources and sinks in Canada's forests based on remote sensing</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item><json:item><name>C. H. Menges</name></json:item><json:item><name>S. G. Leblanc</name></json:item></author><host><volume>97</volume><pages><last>457</last><first>447</first></pages><author></author><title>Remote Sens. Environ.</title></host><title>Global derivation of the vegetation clumping index from multi‐angular satellite data</title></json:item><json:item><author><json:item><name>J. M. Chen</name></json:item><json:item><name>F. Deng</name></json:item><json:item><name>M. Chen</name></json:item></author><host><volume>44</volume><pages><last>2238</last><first>2230</first></pages><author></author><title>IEEE Trans. Geosci. Remote Sens.</title></host><title>Automated erratic cubic‐spline capping method for reconstructing seasonal trajectories of a surface parameter derived from remote sensing</title></json:item><json:item><author><json:item><name>X. Chen</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>S. An</name></json:item><json:item><name>W. Ju</name></json:item></author><host><volume>85</volume><pages><last>596</last><first>585</first></pages><author></author><title>J. Environ. Manage.</title></host><title>Effects of topography on simulated net primary productivity at landscape scale</title></json:item><json:item><author><json:item><name>S. Cohen</name></json:item><json:item><name>R. S. Rao</name></json:item><json:item><name>Y. Cohen</name></json:item></author><host><volume>86</volume><pages><last>234</last><first>225</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>Canopy transmittance inversion using a line quantum probe for a row crop</title></json:item><json:item><author><json:item><name>G. J. Collatz</name></json:item><json:item><name>J. T. Ball</name></json:item><json:item><name>C. Crivet</name></json:item><json:item><name>T. A. Berry</name></json:item></author><host><volume>54</volume><pages><last>136</last><first>107</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: A model that includes a laminar boundary layer</title></json:item><json:item><author><json:item><name>W. Cramer</name></json:item></author><host><volume>5</volume><pages><last>15</last><first>1</first></pages><author></author><title>Global Change Biol.</title></host><title>Comparing global models of terrestrial net primary productivity (NPP): Overview and key results</title></json:item><json:item><author><json:item><name>W. Cramer</name></json:item></author><host><volume>7</volume><pages><last>373</last><first>357</first></pages><author></author><title>Global Change Biol.</title></host><title>Global response of terrestrial ecosystem structure and function to CO2 and climate change: Results from six dynamic global vegetation models</title></json:item><json:item><author><json:item><name>V. Demarez</name></json:item><json:item><name>S. Duthoit</name></json:item><json:item><name>F. Baret</name></json:item><json:item><name>M. Weiss</name></json:item><json:item><name>G. Dedieu</name></json:item></author><host><volume>148</volume><pages><last>655</last><first>644</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>Estimation of leaf area and clumping indexes of crops with hemispherical photographs</title></json:item><json:item><author><json:item><name>J. Demarty</name></json:item><json:item><name>F. Chevallier</name></json:item><json:item><name>A. D. Friend</name></json:item><json:item><name>N. Viovy</name></json:item><json:item><name>S. Piao</name></json:item><json:item><name>P. Ciais</name></json:item></author><host><volume>34</volume><author></author><title>Geophys. Res. Lett.</title></host><title>Assimilation of global MODIS leaf area index retrievals within a terrestrial biosphere model</title></json:item><json:item><author><json:item><name>F. Deng</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>S. Plummer</name></json:item><json:item><name>M. Chen</name></json:item></author><host><volume>44</volume><pages><last>2229</last><first>2219</first></pages><author></author><title>IEEE Trans. Geosci. Remote Sens.</title></host><title>Global LAI algorithm integrating the bidirectional information</title></json:item><json:item><author><json:item><name>D. G. G. De Pury</name></json:item><json:item><name>G. D. Farquhar</name></json:item></author><host><volume>20</volume><pages><last>557</last><first>537</first></pages><author></author><title>Plant Cell Environ.</title></host><title>Simple scaling of photosynthesis from leaves to canopies without the errors of big‐leaf models</title></json:item><json:item><author><json:item><name>D. G. Erbs</name></json:item><json:item><name>S. A. Klein</name></json:item><json:item><name>J. A. Duffie</name></json:item></author><host><volume>28</volume><pages><last>304</last><first>293</first></pages><author></author><title>Sol. Energy</title></host><title>Estimation of diffuse radiation fraction for hourly, daily and monthly‐averaged global radiation</title></json:item><json:item><author><json:item><name>G. D. Farquhar</name></json:item><json:item><name>S. von Caemmerer</name></json:item><json:item><name>J. A. Berry</name></json:item></author><host><volume>149</volume><pages><last>90</last><first>78</first></pages><author></author><title>Planta</title></host><title>A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species</title></json:item><json:item><author><json:item><name>X. Feng</name></json:item><json:item><name>G. Liu</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>M. Chen</name></json:item><json:item><name>J. Liu</name></json:item><json:item><name>W. Ju</name></json:item><json:item><name>R. Sun</name></json:item><json:item><name>W. Zhou</name></json:item></author><host><volume>85</volume><pages><last>573</last><first>563</first></pages><author></author><title>J. Environ. Manage.</title></host><title>Simulating net primary productivity of terrestrial ecosystems in China using a process model driven by remote sensing</title></json:item><json:item><author><json:item><name>P. Friedlingstein</name></json:item></author><host><volume>19</volume><pages><last>3353</last><first>3337</first></pages><author></author><title>J. Clim.</title></host><title>Climate‐carbon cycle feedback analysis: Results from C4MIP model intercomparison</title></json:item><json:item><author><json:item><name>S. Garrigues</name></json:item></author><host><volume>113</volume><author></author><title>J. Geophys. Res.</title></host><title>Validation and intercomparison of global Leaf Area Index products derived from remote sensing data</title></json:item><json:item><author><json:item><name>S. J. Goetz</name></json:item><json:item><name>S. D. Prince</name></json:item><json:item><name>J. Small</name></json:item><json:item><name>A. C. R. Gleason</name></json:item></author><host><volume>105</volume><pages><last>20,091</last><first>20,077</first></pages><author></author><title>J. Geophys. Res.</title></host><title>Interannual variability of global terrestrial primary production: Results of a model driven with satellite observations</title></json:item><json:item><author><json:item><name>M. L. Goulden</name></json:item><json:item><name>B. C. Daube</name></json:item><json:item><name>S.‐M. Fan</name></json:item><json:item><name>D. J. Sutton</name></json:item><json:item><name>A. Bazzaz</name></json:item><json:item><name>J. W. Munger</name></json:item><json:item><name>S. C. Wofsy</name></json:item></author><host><volume>102</volume><pages><last>28,996</last><first>28,987</first></pages><author></author><title>J. Geophys. Res.</title></host><title>Physiological responses of a black spruce forest to weather</title></json:item><json:item><author><json:item><name>K. R. Gurney</name></json:item></author><host><volume>415</volume><pages><last>630</last><first>626</first></pages><author></author><title>Nature</title></host><title>Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models</title></json:item><json:item><author><json:item><name>N. P. Hanan</name></json:item><json:item><name>J. A. Berry</name></json:item><json:item><name>S. B. Verma</name></json:item><json:item><name>E. A. Walter‐Shea</name></json:item><json:item><name>A. E. Suyker</name></json:item><json:item><name>G. G. Burba</name></json:item><json:item><name>A. S. Denning</name></json:item></author><host><volume>131</volume><pages><last>179</last><first>162</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>Testing a model of CO2, water and energy exchange in Great Plains tallgrass prairie and wheat ecosystems</title></json:item><json:item><author><json:item><name>J. A. Hicke</name></json:item></author><host><volume>19</volume><author></author><title>Global Biogeochem. Cycles</title></host><title>NCEP and GISS solar radiation data sets available for ecosystem modeling: Description, differences, and impacts on net primary production</title></json:item><json:item><author><json:item><name>A. R. Huete</name></json:item><json:item><name>K. Didan</name></json:item><json:item><name>Y. E. Shimabukuro</name></json:item><json:item><name>P. Ratana</name></json:item><json:item><name>S. R. Saleska</name></json:item><json:item><name>L. R. Hutyra</name></json:item><json:item><name>W. Yang</name></json:item><json:item><name>R. R. Nemani</name></json:item><json:item><name>R. Myneni</name></json:item></author><host><volume>33</volume><author></author><title>Geophys. Res. Lett.</title></host><title>Amazon rainforests green‐up with sunlight in dry season</title></json:item><json:item><author><json:item><name>E. R. Hunt Jr.</name></json:item><json:item><name>S. W. Running</name></json:item></author><host><volume>18</volume><pages><last>133</last><first>126</first></pages><author></author><title>Can. J. Remote Sens.</title></host><title>Simulated dry matter yields for aspen and spruce stand in the North American boreal forest</title></json:item><json:item><author><json:item><name>P. G. Jarvis</name></json:item></author><host><volume>273</volume><pages><last>610</last><first>593</first></pages><author></author><title>Philos. Trans. R. Soc. London, Ser. B</title></host><title>The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the fields</title></json:item><json:item><author><json:item><name>W. Ju</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>T. A. Black</name></json:item><json:item><name>A. G. Barr</name></json:item><json:item><name>J. Liu</name></json:item><json:item><name>B. Chen</name></json:item></author><host><volume>140</volume><pages><last>151</last><first>136</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>Modeling coupled water and carbon fluxes in a boreal aspen forest</title></json:item><json:item><author><json:item><name>J. Kattge</name></json:item><json:item><name>W. Knorr</name></json:item><json:item><name>T. Raddatz</name></json:item><json:item><name>C. Wirth</name></json:item></author><host><volume>15</volume><pages><last>991</last><first>976</first></pages><author></author><title>Global Change Biol.</title></host><title>Quantifying photosynthetic capacity and its relationship to leaf nitrogen content for global‐scale terrestrial biosphere models</title></json:item><json:item><author><json:item><name>W. Knorr</name></json:item><json:item><name>M. Heimann</name></json:item></author><host><volume>15</volume><pages><last>225</last><first>207</first></pages><author></author><title>Global Biogeochem. Cycles</title></host><title>Uncertainties in global terrestrial biosphere modeling: 1. A comprehensive sensitivity analysis with a new photosynthesis and energy balance scheme</title></json:item><json:item><author><json:item><name>G. Krinner</name></json:item><json:item><name>N. Viovy</name></json:item><json:item><name>N. de Noblet‐Ducoudré</name></json:item><json:item><name>J. Ogée</name></json:item><json:item><name>J. Polcher</name></json:item><json:item><name>P. Friedlingstein</name></json:item><json:item><name>P. Ciais</name></json:item><json:item><name>S. Sitch</name></json:item><json:item><name>I. C. Prentice</name></json:item></author><host><volume>19</volume><author></author><title>Global Biogeochem. Cycles</title></host><title>A dynamic global vegetation model for studies of the coupled atmosphere‐biosphere system</title></json:item><json:item><author><json:item><name>R. Lacaze</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>J.‐L. Roujean</name></json:item><json:item><name>S. G. Leblanc</name></json:item></author><host><volume>79</volume><pages><last>95</last><first>84</first></pages><author></author><title>Remote Sens. Environ.</title></host><title>Retrieval of vegetation clumping index using hot spot signatures measured by multiangular POLDER instrument</title></json:item><json:item><author><json:item><name>S. G. Leblanc</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>H. P. White</name></json:item><json:item><name>R. Latifvic</name></json:item><json:item><name>J. R. Roujean</name></json:item><json:item><name>R. Lacaze</name></json:item></author><host><volume>31</volume><pages><last>376</last><first>364</first></pages><author></author><title>Can. J. Remote Sens.</title></host><title>Canada‐wide foliage clumping index mapping from multi‐angular POLDER measurements</title></json:item><json:item><author><json:item><name>S. G. Leblanc</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>R. Fernandes</name></json:item><json:item><name>D. W. Deering</name></json:item><json:item><name>A. Conley</name></json:item></author><host><volume>129</volume><pages><last>207</last><first>187</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>Methodology comparison for canopy structure parameters extraction from digital hemispherical photography in boreal forests</title></json:item><json:item><author><json:item><name>C. Le Quéré</name></json:item></author><host><volume>2</volume><pages><last>836</last><first>831</first></pages><author></author><title>Nat. Geosci.</title></host><title>Trends in the sources and sinks of carbon dioxide</title></json:item><json:item><author><json:item><name>R. Leuning</name></json:item></author><host><volume>17</volume><pages><last>175</last><first>159</first></pages><author></author><title>Aust. J. Plant Physiol.</title></host><title>Modelling stomatal behaviour and photosynthesis of eucalyptus grandis</title></json:item><json:item><author><json:item><name>R. Leuning</name></json:item></author><host><volume>18</volume><pages><last>355</last><first>339</first></pages><author></author><title>Plant Cell Environ.</title></host><title>A critical appraisal of a combined stomatal‐photosynthesis model for C3 plants</title></json:item><json:item><author><json:item><name>R. Leuning</name></json:item><json:item><name>F. M. Kelliher</name></json:item><json:item><name>D. G. G. De Pury</name></json:item><json:item><name>E.‐D. Schulze</name></json:item></author><host><volume>18</volume><pages><last>1200</last><first>1183</first></pages><author></author><title>Plant Cell Environ.</title></host><title>Leaf nitrogen, photosynthesis, conductance and transpiration: Scaling from leaves to canopies</title></json:item><json:item><author><json:item><name>K. Y. Li</name></json:item><json:item><name>R. De Jong</name></json:item><json:item><name>J. B. Boisvert</name></json:item></author><host><volume>252</volume><pages><last>204</last><first>189</first></pages><author></author><title>J. Hydrol.</title></host><title>An exponential root‐water‐uptake model with water stress compensation</title></json:item><json:item><author><json:item><name>J. Liu</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>J. Cihlar</name></json:item><json:item><name>W. M. Park</name></json:item></author><host><volume>62</volume><pages><last>175</last><first>158</first></pages><author></author><title>Remote Sens. Environ.</title></host><title>A process‐based boreal ecosystem productivity simulator using remote sensing inputs</title></json:item><json:item><author><json:item><name>B. Matsushita</name></json:item><json:item><name>M. Tamura</name></json:item></author><host><volume>81</volume><pages><last>66</last><first>58</first></pages><author></author><title>Remote Sens. Environ.</title></host><title>Integrating remotely sensed data with an ecosystem model to estimate net primary productivity in East Asia</title></json:item><json:item><author><json:item><name>B. Matsushita</name></json:item><json:item><name>M. Xu</name></json:item><json:item><name>J. Chen</name></json:item><json:item><name>S. Kameyama</name></json:item><json:item><name>M. Tamura</name></json:item></author><host><volume>178</volume><pages><last>388</last><first>371</first></pages><author></author><title>Ecol. Modell.</title></host><title>Estimation of regional net primary productivity (NPP) using a process‐based ecosystem model: How important is the accuracy of climate data?</title></json:item><json:item><author><json:item><name>B. E. Medlyn</name></json:item></author><host><volume>22</volume><pages><last>1495</last><first>1475</first></pages><author></author><title>Plant Cell Environ.</title></host><title>Effects of elevated [CO2] on photosynthesis in European forest species: A meta‐analysis of model parameters</title></json:item><json:item><host><author></author><title>Meta‐analysis of model parametersPredicted Impacts of Rising Carbon Dioxide and Temperature on Forests in Europe at Stand Scale</title></host></json:item><json:item><author><json:item><name>E. E. Miller</name></json:item><json:item><name>J. M. Norman</name></json:item></author><host><volume>63</volume><pages><last>738</last><first>735</first></pages><issue>5</issue><author></author><title>Agron. J.</title></host><title>Sunfleck theory for plant canopies 1. Lengths of sunlit segments along a transect</title></json:item><json:item><author><json:item><name>E. E. Miller</name></json:item><json:item><name>J. M. Norman</name></json:item></author><host><volume>63</volume><pages><last>743</last><first>739</first></pages><issue>5</issue><author></author><title>Agron. J.</title></host><title>Sunfleck theory for plant canopies 2. Penumbra effect: Intensity distributions along sunfleck segments</title></json:item><json:item><author><json:item><name>J. T. Morisette</name></json:item></author><host><volume>44</volume><pages><last>1817</last><first>1804</first></pages><author></author><title>IEEE Trans. Geosci. Remote Sens.</title></host><title>Validation of global Moderate‐Resolution LAI products: A framework proposed within the CEOS land product validation subgroup</title></json:item><json:item><author><json:item><name>R. B. Myneni</name></json:item></author><host><volume>83</volume><pages><last>231</last><first>214</first></pages><author></author><title>Remote Sens. Environ.</title></host><title>Global products of vegetation leaf area and fraction absorbed PAR from one year of MODIS data</title></json:item><json:item><author><json:item><name>T. Nilson</name></json:item></author><host><volume>8</volume><pages><last>38</last><first>25</first></pages><author></author><title>Agric. Meteorol.</title></host><title>A theoretical analysis of the frequency of gaps in plant stands</title></json:item><json:item><author><json:item><name>S. Niu</name></json:item><json:item><name>Z. Yuan</name></json:item><json:item><name>Y. Zhang</name></json:item><json:item><name>W. Liu</name></json:item><json:item><name>L. Zhang</name></json:item><json:item><name>J. Huang</name></json:item><json:item><name>S. Wan</name></json:item></author><host><volume>56</volume><pages><last>2876</last><first>2867</first></pages><author></author><title>J. Exp. Bot.</title></host><title>Photosynthetic responses of C3 and C4 species to seasonal water variability and competition</title></json:item><json:item><author><json:item><name>J. M. Norman</name></json:item></author><host><pages><last>99</last><first>65</first></pages><author></author><title>Biometeorology in Integrated Pest Management</title></host><title>Simulation of microclimates</title></json:item><json:item><author><json:item><name>J. M. Norman</name></json:item><json:item><name>P. G. Jarvis</name></json:item></author><host><volume>11</volume><pages><last>398</last><first>375</first></pages><author></author><title>J. Appl. Ecol.</title></host><title>Photosynthesis in sitka spruce (Picea‐sitchensis (Bong) carr) 3. Measurements of canopy structure and interception of radiation</title></json:item><json:item><author><json:item><name>J. M. Norman</name></json:item><json:item><name>J. M. Welles</name></json:item></author><host><volume>75</volume><pages><last>488</last><first>481</first></pages><author></author><title>Agron. J.</title></host><title>Radiative transfer in an array of canopies</title></json:item><json:item><author><json:item><name>S. Piao</name></json:item><json:item><name>P. Ciais</name></json:item><json:item><name>P. Friedlingstein</name></json:item><json:item><name>N. de Noblet‐Ducoudré</name></json:item><json:item><name>P. Cadule</name></json:item><json:item><name>N. Viovy</name></json:item><json:item><name>T. Wang</name></json:item></author><host><volume>23</volume><author></author><title>Global Biogeochem. Cycles</title></host><title>Spatiotemporal patterns of terrestrial carbon cycle during the 20th century</title></json:item><json:item><author><json:item><name>J. Pisek</name></json:item><json:item><name>J. M. Chen</name></json:item></author><host><volume>109</volume><pages><last>94</last><first>81</first></pages><author></author><title>Remote Sens. Environ.</title></host><title>Comparison and validation of MODIS and VEGETATION global LAI products over four BigFoot sites in North America</title></json:item><json:item><author><json:item><name>J. Pisek</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>F. Deng</name></json:item></author><host><volume>33</volume><pages><last>16</last><first>1</first></pages><author></author><title>Can. J. Remote Sens.</title></host><title>Canada‐wide validation of a new global leaf area index dataset from SPOT‐4 VEGETATION data</title></json:item><json:item><author><json:item><name>J. Pisek</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>R. Lacaze</name></json:item><json:item><name>O. Sonnentag</name></json:item><json:item><name>K. Alikas</name></json:item></author><host><volume>65</volume><pages><last>346</last><first>341</first></pages><author></author><title>ISPRS J. Photogramm. Remote Sens.</title></host><title>Expanding global mapping of foliage clumping index with multi‐angular POLDER 3 measurements: Evaluation and topographic compensation</title></json:item><json:item><author><json:item><name>C. S. Potter</name></json:item><json:item><name>J. T. Randerson</name></json:item><json:item><name>C. B. Field</name></json:item><json:item><name>P. A. Matson</name></json:item><json:item><name>P. M. Vitousek</name></json:item><json:item><name>H. A. Mooney</name></json:item><json:item><name>S. A. Klooster</name></json:item></author><host><volume>7</volume><pages><last>841</last><first>811</first></pages><author></author><title>Global Biogeochem. Cycles</title></host><title>Terrestrial ecosystem production: A process model based on global satellite and surface data</title></json:item><json:item><host><author></author><title>Modelling drought tolerance in Amazonia with SiB3</title></host></json:item><json:item><author><json:item><name>D. Radcliffe</name></json:item><json:item><name>T. Hayden</name></json:item><json:item><name>K. Watson</name></json:item><json:item><name>P. Crowley</name></json:item><json:item><name>R. E. Phillips</name></json:item></author><host><volume>72</volume><pages><last>24</last><first>19</first></pages><author></author><title>Agron. J.</title></host><title>Simulation of soil‐water within the root zone of a corn crop</title></json:item><json:item><author><json:item><name>P. J. Rayner</name></json:item><json:item><name>R. M. Law</name></json:item><json:item><name>C. E. Allison</name></json:item><json:item><name>R. J. Francey</name></json:item><json:item><name>C. M. Trudinger</name></json:item><json:item><name>C. Pickett‐Heaps</name></json:item></author><host><volume>22</volume><author></author><title>Global Biogeochem. Cycles</title></host><title>Interannual variability of the global carbon cycle (1992–2005) inferred by inversion of atmospheric CO2 and δ13CO2 measurements</title></json:item><json:item><author><json:item><name>J.‐L. Roujean</name></json:item><json:item><name>R. Lacaze</name></json:item></author><host><volume>170</volume><issue>D12</issue><author></author><title>J. Geophys. Res.</title></host><title>Global mapping of vegetation parameters from POLDER multiangular measurements for studies of surface‐atmosphere interactions: A pragmatic method and its validation</title></json:item><json:item><author><json:item><name>A. Ruimy</name></json:item><json:item><name>G. Dedieu</name></json:item><json:item><name>B. Saugier</name></json:item></author><host><volume>10</volume><pages><last>285</last><first>269</first></pages><author></author><title>Global Biogeochem. Cycles</title></host><title>TURC: A diagnostic model of continental gross primary productivity and net primary productivity</title></json:item><json:item><author><json:item><name>S. W. Running</name></json:item><json:item><name>R. R. Nemani</name></json:item><json:item><name>F. A. Heinsch</name></json:item><json:item><name>M. Zhao</name></json:item><json:item><name>M. Reeves</name></json:item><json:item><name>H. Hashimoto</name></json:item></author><host><volume>54</volume><pages><last>560</last><first>547</first></pages><author></author><title>BioScience</title></host><title>A continuous satellite‐derived measure of global terrestrial primary production</title></json:item><json:item><author><json:item><name>Y. Ryu</name></json:item><json:item><name>T. Nilson</name></json:item><json:item><name>H. Kobayashi</name></json:item><json:item><name>O. Sonnentag</name></json:item><json:item><name>B. E. Law</name></json:item><json:item><name>D. D. Baldocchi</name></json:item></author><host><volume>150</volume><pages><last>472</last><first>463</first></pages><issue>3</issue><author></author><title>Agric. For. Meteorol.</title></host><title>On the correct estimation of effective leaf area index: Does it reveal information on clumping effects?</title></json:item><json:item><author><json:item><name>Y. Ryu</name></json:item><json:item><name>O. Sonnentag</name></json:item><json:item><name>T. Nilson</name></json:item><json:item><name>R. Vargas</name></json:item><json:item><name>H. Kobayashi</name></json:item><json:item><name>R. Wenk</name></json:item><json:item><name>D. D. Baldochi</name></json:item></author><host><volume>150</volume><pages><last>76</last><first>63</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>How to quantify tree leaf area index in an open savanna ecosystem: A multi‐instrument and multi‐model approach</title></json:item><json:item><author><json:item><name>N. Saigusa</name></json:item></author><host><volume>148</volume><pages><last>713</last><first>700</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>Temporal and spatial variations in the seasonal patterns of CO2 flux in boreal, temperate, and tropical forests in East Asia</title></json:item><json:item><author><json:item><name>K. E. Saxton</name></json:item><json:item><name>W. J. Rawls</name></json:item><json:item><name>J. S. Romberger</name></json:item><json:item><name>R. I. Papendick</name></json:item></author><host><volume>50</volume><pages><last>1036</last><first>1031</first></pages><author></author><title>Soil Sci. Soc. Am. J.</title></host><title>Estimating generalized soil‐water characteristics from texture</title></json:item><json:item><host><author></author><title>Schieving, F. (1998), Plato's Plant: On the Mathematical Structure of Simple Plants and Canopies, 360 pp. Backhuys, Leiden, Netherlands.</title></host></json:item><json:item><author><json:item><name>E.‐D. Schulze</name></json:item><json:item><name>D. S. S. Schimel</name></json:item></author><host><pages><last>14</last><first>1</first></pages><author></author><title>Global Biogeochemical Cycles in the Climate System</title></host><title>Uncertainties of global biogeochemical predictions</title></json:item><json:item><author><json:item><name>C. R. Schwalm</name></json:item></author><host><volume>115</volume><author></author><title>J. Geophys. Res.</title></host><title>A model‐data intercomparison of CO2 exchange across North America: Results from the North America Carbon Program site synthesis</title></json:item><json:item><author><json:item><name>O. Sonnentag</name></json:item><json:item><name>J. Talbot</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>T. N. Roulet</name></json:item></author><host><volume>144</volume><pages><last>212</last><first>200</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>Using direct and indirect measurements of leaf area index to characterize the shrub canopy of an ombrotrophic peatland</title></json:item><json:item><author><json:item><name>C. J. T. Spitters</name></json:item><json:item><name>H. A. J. M. Toussaint</name></json:item><json:item><name>J. Goudriaan</name></json:item></author><host><volume>38</volume><pages><last>229</last><first>217</first></pages><issue>1–3)</issue><author></author><title>Agric. For. Meteorol.</title></host><title>Separating the diffuse and direct component of global radiation and its implications for modeling canopy photosynthesis. Part I. Components of incoming radiation</title></json:item><json:item><author><json:item><name>M. Sprintsin</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>A. R. Desai</name></json:item><json:item><name>C. M. Gough</name></json:item></author><host><author></author><title>J. Geophys. Res.</title></host><title>Evaluation of leaf‐to‐canopy upscaling methodologies against carbon flux data in North America</title></json:item><json:item><author><json:item><name>F. J. Sterck</name></json:item><json:item><name>F. Schieving</name></json:item></author><host><volume>77</volume><pages><last>420</last><first>405</first></pages><author></author><title>Ecol. Monogr.</title></host><title>3‐D growth patterns of trees: Effects of carbon economy, meristem activity, and selection</title></json:item><json:item><author><json:item><name>C. J. Still</name></json:item><json:item><name>J. A. Berry</name></json:item><json:item><name>G. J. Collatz</name></json:item><json:item><name>R. S. DeFries</name></json:item></author><host><volume>17</volume><issue>1</issue><author></author><title>Global Biogeochem. Cycles</title></host><title>Global distribution of C3 and C4 vegetation: Carbon cycle implications</title></json:item><json:item><author><json:item><name>Q. Wang</name></json:item><json:item><name>J. Tenhunen</name></json:item><json:item><name>E. Falge</name></json:item><json:item><name>C. Bernhofer</name></json:item><json:item><name>A. Granier</name></json:item><json:item><name>T. Vesalas</name></json:item></author><host><volume>10</volume><pages><last>51</last><first>37</first></pages><author></author><title>Global Change Biol.</title></host><title>Simulation and scaling of temporal variation in gross primary production for coniferous and deciduous temperate forests</title></json:item><json:item><author><json:item><name>S. Wang</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>W. Ju</name></json:item><json:item><name>X. Feng</name></json:item><json:item><name>M. Chen</name></json:item><json:item><name>P. Chen</name></json:item><json:item><name>G. Yu</name></json:item></author><host><volume>85</volume><pages><last>537</last><first>524</first></pages><author></author><title>J. Environ. Manage.</title></host><title>Carbon sinks and sources in China's forests during 1901–2001</title></json:item><json:item><author><json:item><name>Y.‐P. Wang</name></json:item><json:item><name>R. Leuning</name></json:item></author><host><volume>91</volume><pages><last>111</last><first>89</first></pages><author></author><title>Agric. For. Meteorol.</title></host><title>A two‐leaf model for canopy conductance, photosynthesis and partitioning of available energy I: Model description and comparison with a multi‐layered model</title></json:item><json:item><author><json:item><name>R. S. Webb</name></json:item><json:item><name>C. E. Rosenzweig</name></json:item><json:item><name>E. R. Levine</name></json:item></author><host><volume>TM‐4286</volume><author></author><title>NASA Tech. Memo.</title></host><title>A global data set of soil particle size properties</title></json:item><json:item><author><json:item><name>M. Williams</name></json:item></author><host><volume>19</volume><pages><last>927</last><first>911</first></pages><author></author><title>Plant Cell Environ.</title></host><title>Modeling the soil‐plant‐atmosphere continuum in a Quercus‐Acer stand at Harvard forest: The regulation of stomatal conductance by light, nitrogen and soil/plant hydraulic properties</title></json:item><json:item><author><json:item><name>S. D. Wullschleger</name></json:item></author><host><volume>44</volume><pages><last>920</last><first>907</first></pages><author></author><title>J. Exp. Bot.</title></host><title>Biochemical limitations to carbon assimilation in C3 plants: A retrospective analysis of the A/Ci curves from 109 species</title></json:item><json:item><author><json:item><name>M. Zhao</name></json:item><json:item><name>S. W. Running</name></json:item></author><host><volume>329</volume><pages><last>943</last><first>940</first></pages><author></author><title>Science</title></host><title>Drought‐induced reduction in global terrestrial net primary production from 2000 through 2009</title></json:item><json:item><author><json:item><name>M. Zhao</name></json:item><json:item><name>S. W. Running</name></json:item><json:item><name>R. R. Nemani</name></json:item></author><host><volume>111</volume><author></author><title>J. Geophys. Res.</title></host><title>Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses</title></json:item><json:item><author><json:item><name>G. Zheng</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>Q. Tian</name></json:item><json:item><name>W. M. Ju</name></json:item><json:item><name>X. Xia</name></json:item></author><host><volume>85</volume><pages><last>623</last><first>616</first></pages><author></author><title>J. Environ. Manage.</title></host><title>Combining remote sensing imagery and forest age inventory for biomass mapping</title></json:item><json:item><author><json:item><name>Y. Zhou</name></json:item><json:item><name>Q. Zhu</name></json:item><json:item><name>J. M. Chen</name></json:item><json:item><name>Y. Q. Wang</name></json:item><json:item><name>J. Liu</name></json:item><json:item><name>R. Sun</name></json:item><json:item><name>S. Tang</name></json:item></author><host><volume>85</volume><pages><last>584</last><first>574</first></pages><author></author><title>J. Environ. Manage.</title></host><title>Observation and simulation of net primary productivity in Qilian mountain, Western China</title></json:item><json:item><author><json:item><name>B. Zierl</name></json:item></author><host><volume>242</volume><pages><last>136</last><first>115</first></pages><author></author><title>J. Hydrol.</title></host><title>A water balance model to simulate drought in forested ecosystems and its application to the entire forested area in Switzerland</title></json:item></refBibs><genre><json:string>article</json:string></genre><host><volume>26</volume><publisherId><json:string>GBC</json:string></publisherId><pages><total>18</total><last>n/a</last><first>n/a</first></pages><issn><json:string>0886-6236</json:string></issn><issue>1</issue><subject><json:item><value>BIOGEOSCIENCES</value></json:item><json:item><value>Biogeochemical kinetics and reaction modeling</value></json:item><json:item><value>Biogeochemical cycles, processes, and modeling</value></json:item><json:item><value>Carbon cycling</value></json:item><json:item><value>CRYOSPHERE</value></json:item><json:item><value>Biogeochemistry</value></json:item><json:item><value>GLOBAL CHANGE</value></json:item><json:item><value>Biogeochemical cycles, processes, and modeling</value></json:item><json:item><value>Remote sensing</value></json:item><json:item><value>HYDROLOGY</value></json:item><json:item><value>Remote sensing</value></json:item><json:item><value>NATURAL HAZARDS</value></json:item><json:item><value>Remote sensing and disasters</value></json:item><json:item><value>OCEANOGRAPHY: BIOLOGICAL AND CHEMICAL</value></json:item><json:item><value>Carbon cycling</value></json:item><json:item><value>Biogeochemical cycles, processes, and modeling</value></json:item><json:item><value>PALEOCEANOGRAPHY</value></json:item><json:item><value>Biogeochemical cycles, processes, and modeling</value></json:item></subject><genre><json:string>journal</json:string></genre><language><json:string>unknown</json:string></language><eissn><json:string>1944-9224</json:string></eissn><title>Global Biogeochemical Cycles</title><doi><json:string>10.1002/(ISSN)1944-9224</json:string></doi></host><categories><wos><json:string>science</json:string><json:string>meteorology & atmospheric sciences</json:string><json:string>geosciences, multidisciplinary</json:string><json:string>environmental sciences</json:string></wos><scienceMetrix><json:string>natural sciences</json:string><json:string>earth & environmental sciences</json:string><json:string>meteorology & atmospheric sciences</json:string></scienceMetrix></categories><publicationDate>2012</publicationDate><copyrightDate>2012</copyrightDate><doi><json:string>10.1029/2010GB003996</json:string></doi><id>1BE91345AC1E39E7C900AB319CB7B6B9B953E9E6</id><score>1</score><fulltext><json:item><extension>pdf</extension><original>true</original><mimetype>application/pdf</mimetype><uri>https://api.istex.fr/document/1BE91345AC1E39E7C900AB319CB7B6B9B953E9E6/fulltext/pdf</uri></json:item><json:item><extension>zip</extension><original>false</original><mimetype>application/zip</mimetype><uri>https://api.istex.fr/document/1BE91345AC1E39E7C900AB319CB7B6B9B953E9E6/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/1BE91345AC1E39E7C900AB319CB7B6B9B953E9E6/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a" type="main" xml:lang="en">Effects of foliage clumping on the estimation of global terrestrial gross primary productivity</title></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>Blackwell Publishing Ltd</publisher><availability><p>Copyright 2012 by the American Geophysical Union</p></availability><date>2012</date></publicationStmt><notesStmt><note>Tab‐delimited Table 1.Tab‐delimited Table 2.Tab‐delimited Table 3.</note></notesStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a" type="main" xml:lang="en">Effects of foliage clumping on the estimation of global terrestrial gross primary productivity</title><author xml:id="author-1"><persName><forename type="first">Jing M.</forename><surname>Chen</surname></persName><email>chenj@geog.utoronto.ca</email><affiliation>International Institute of Earth System Science, Nanjing University, Nanjing, China</affiliation><affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</affiliation></author><author xml:id="author-2"><persName><forename type="first">Gang</forename><surname>Mo</surname></persName><affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</affiliation></author><author xml:id="author-3"><persName><forename type="first">Jan</forename><surname>Pisek</surname></persName><affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</affiliation><affiliation>Tartu Observatory 61602, Toravere, Estonia</affiliation></author><author xml:id="author-4"><persName><forename type="first">Jane</forename><surname>Liu</surname></persName><affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</affiliation></author><author xml:id="author-5"><persName><forename type="first">Feng</forename><surname>Deng</surname></persName><affiliation>International Institute of Earth System Science, Nanjing University, Nanjing, China</affiliation></author><author xml:id="author-6"><persName><forename type="first">Misa</forename><surname>Ishizawa</surname></persName><affiliation>Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada</affiliation></author><author xml:id="author-7"><persName><forename type="first">Douglas</forename><surname>Chan</surname></persName><affiliation>Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada</affiliation></author></analytic><monogr><title level="j">Global Biogeochemical Cycles</title><title level="j" type="abbrev">Global Biogeochem. Cycles</title><idno type="pISSN">0886-6236</idno><idno type="eISSN">1944-9224</idno><idno type="DOI">10.1002/(ISSN)1944-9224</idno><imprint><publisher>Blackwell Publishing Ltd</publisher><date type="published" when="2012-03"></date><biblScope unit="volume">26</biblScope><biblScope unit="issue">1</biblScope><biblScope unit="page" from="/">n/a</biblScope><biblScope unit="page" to="/">n/a</biblScope></imprint></monogr><idno type="istex">1BE91345AC1E39E7C900AB319CB7B6B9B953E9E6</idno><idno type="DOI">10.1029/2010GB003996</idno><idno type="ArticleID">2010GB003996</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>2012</date></creation><langUsage><language ident="en">en</language></langUsage><abstract><p>Sunlit and shaded leaf separation proposed by Norman (1982) is an effective way to upscale from leaf to canopy in modeling vegetation photosynthesis. The Boreal Ecosystem Productivity Simulator (BEPS) makes use of this methodology, and has been shown to be reliable in modeling the gross primary productivity (GPP) derived from CO2flux and tree ring measurements. In this study, we use BEPS to investigate the effect of canopy architecture on the global distribution of GPP. For this purpose, we use not only leaf area index (LAI) but also the first ever global map of the foliage clumping index derived from the multiangle satellite sensor POLDER at 6 km resolution. The clumping index, which characterizes the degree of the deviation of 3‐dimensional leaf spatial distributions from the random case, is used to separate sunlit and shaded LAI values for a given LAI. Our model results show that global GPP in 2003 was 132 ± 22 Pg C. Relative to this baseline case, our results also show: (1) global GPP is overestimated by 12% when accurate LAI is available but clumping is ignored, and (2) global GPP is underestimated by 9% when the effective LAI is available and clumping is ignored. The clumping effects in both cases are statistically significant (p < 0.001). The effective LAI is often derived from remote sensing by inverting the measured canopy gap fraction to LAI without considering the clumping. Global GPP would therefore be generally underestimated when remotely sensed LAI (actually effective LAI by our definition) is used. This is due to the underestimation of the shaded LAI and therefore the contribution of shaded leaves to GPP. We found that shaded leaves contribute 50%, 38%, 37%, 39%, 26%, 29% and 21% to the total GPP for broadleaf evergreen forest, broadleaf deciduous forest, evergreen conifer forest, deciduous conifer forest, shrub, C4 vegetation, and other vegetation, respectively. The global average of this ratio is 35%.</p></abstract><abstract style="short"><p>Plant canopy structure is quantified by both LAI and clumping index A global clumping map is for the first time used for global GPP estimation The impact of clumping is highly significant for global GPP modeling</p></abstract><textClass><keywords scheme="keyword"><list><head>keywords</head><item><term>LAI</term></item><item><term>canopy radiation</term></item><item><term>clumping index</term></item><item><term>global GPP</term></item><item><term>photosynthesis model</term></item></list></keywords></textClass><textClass><keywords scheme="Journal Subject"><list><head>index-terms</head><item><term>BIOGEOSCIENCES</term></item><item><term>Biogeochemical kinetics and reaction modeling</term></item><item><term>Biogeochemical cycles, processes, and modeling</term></item><item><term>Carbon cycling</term></item><item><term>CRYOSPHERE</term></item><item><term>Biogeochemistry</term></item><item><term>GLOBAL CHANGE</term></item><item><term>Biogeochemical cycles, processes, and modeling</term></item><item><term>Remote sensing</term></item><item><term>HYDROLOGY</term></item><item><term>Remote sensing</term></item><item><term>NATURAL HAZARDS</term></item><item><term>Remote sensing and disasters</term></item><item><term>OCEANOGRAPHY: BIOLOGICAL AND CHEMICAL</term></item><item><term>Carbon cycling</term></item><item><term>Biogeochemical cycles, processes, and modeling</term></item><item><term>PALEOCEANOGRAPHY</term></item><item><term>Biogeochemical cycles, processes, and modeling</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="2010-11-16">Received</change><change when="2012-01-03">Registration</change><change when="2012-03">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/1BE91345AC1E39E7C900AB319CB7B6B9B953E9E6/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Wiley, elements deleted: body"><istex:xmlDeclaration>version="1.0" encoding="UTF-8" standalone="yes"</istex:xmlDeclaration><istex:document><component type="serialArticle" version="2.0" xml:lang="en" xml:id="gbc1842"><header><publicationMeta level="product"><doi>10.1002/(ISSN)1944-9224</doi><issn type="print">0886-6236</issn><issn type="electronic">1944-9224</issn><idGroup><id type="product" value="GBC"></id><id type="coden" value="GBCYEP"></id></idGroup><titleGroup><title type="main" xml:lang="en" sort="GLOBAL BIOGEOCHEMICAL CYCLES">Global Biogeochemical Cycles</title><title type="short">Global Biogeochem. Cycles</title></titleGroup></publicationMeta><publicationMeta level="part" position="10"><doi>10.1002/gbc.v26.1</doi><numberingGroup><numbering type="journalVolume" number="26">26</numbering><numbering type="journalIssue">1</numbering></numberingGroup><coverDate startDate="2012-03">March 2012</coverDate></publicationMeta><publicationMeta level="unit" type="article" position="140" status="forIssue"><doi>10.1029/2010GB003996</doi><idGroup><id type="editorialOffice" value="2010GB003996"></id><id type="society" value="GB1019"></id><id type="unit" value="GBC1842"></id></idGroup><countGroup><count type="pageTotal" number="18"></count></countGroup><copyright ownership="thirdParty">Copyright 2012 by the American Geophysical Union</copyright><eventGroup><event type="manuscriptReceived" date="2010-11-16"></event><event type="manuscriptRevised" date="2011-11-22"></event><event type="manuscriptAccepted" date="2012-01-03"></event><event type="firstOnline" date="2012-03-01"></event><event type="publishedOnlineFinalForm" date="2012-03-01"></event><event type="xmlConverted" agent="SPi Global Converter:AGUv5.2_TO_WileyML3Gv1.0.3 version:1.3; WileyML 3G Packaging Tool v1.0; AGU2WileyML3G Final Clean Up v1.0" date="2012-12-12"></event><event type="xmlConverted" agent="Converter:WILEY_ML3G_TO_WILEY_ML3GV2 version:3.8.8" date="2014-01-25"></event><event type="xmlConverted" agent="Converter:WML3G_To_WML3G version:4.3.4 mode:FullText" date="2015-02-24"></event></eventGroup><numberingGroup><numbering type="pageFirst">n/a</numbering><numbering type="pageLast">n/a</numbering></numberingGroup><subjectInfo><subject href="http://psi.agu.org/taxonomy5/0400">BIOGEOSCIENCES</subject><subjectInfo><subject href="http://psi.agu.org/taxonomy5/0412">Biogeochemical kinetics and reaction modeling</subject><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/0414">Biogeochemical cycles, processes, and modeling</subject><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/0428">Carbon cycling</subject></subjectInfo><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/0700">CRYOSPHERE</subject><subjectInfo><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/0793">Biogeochemistry</subject></subjectInfo><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/1600">GLOBAL CHANGE</subject><subjectInfo><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/1615">Biogeochemical cycles, processes, and modeling</subject><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/1640">Remote sensing</subject></subjectInfo><subject href="http://psi.agu.org/taxonomy5/1800">HYDROLOGY</subject><subjectInfo><subject href="http://psi.agu.org/taxonomy5/1855">Remote sensing</subject></subjectInfo><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/4300">NATURAL HAZARDS</subject><subjectInfo><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/4337">Remote sensing and disasters</subject></subjectInfo><subject href="http://psi.agu.org/taxonomy5/4800">OCEANOGRAPHY: BIOLOGICAL AND CHEMICAL</subject><subjectInfo><subject href="http://psi.agu.org/taxonomy5/4806">Carbon cycling</subject><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/4805">Biogeochemical cycles, processes, and modeling</subject></subjectInfo><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/4900">PALEOCEANOGRAPHY</subject><subjectInfo><subject role="crossTerm" href="http://psi.agu.org/taxonomy5/4912">Biogeochemical cycles, processes, and modeling</subject></subjectInfo></subjectInfo><selfCitationGroup><citation xml:id="gbc1842-cit-0000" type="self"><author><familyName>Chen</familyName>, <givenNames>J. M.</givenNames></author>, <author><givenNames>G.</givenNames> <familyName>Mo</familyName></author>, <author><givenNames>J.</givenNames> <familyName>Pisek</familyName></author>, <author><givenNames>J.</givenNames> <familyName>Liu</familyName></author>, <author><givenNames>F.</givenNames> <familyName>Deng</familyName></author>, <author><givenNames>M.</givenNames> <familyName>Ishizawa</familyName></author>, and <author><givenNames>D.</givenNames> <familyName>Chan</familyName></author> (<pubYear year="2012">2012</pubYear>), <articleTitle>Effects of foliage clumping on the estimation of global terrestrial gross primary productivity</articleTitle>, <journalTitle>Global Biogeochem. Cycles</journalTitle>, <vol>26</vol>, GB1019, doi:<accessionId ref="info:doi/10.1029/2010GB003996">10.1029/2010GB003996</accessionId>.</citation></selfCitationGroup><objectNameGroup><objectName elementName="appendix">Appendix</objectName></objectNameGroup><linkGroup><link type="toTypesetVersion" href="file:GBC.GBC1842.pdf"></link></linkGroup></publicationMeta><contentMeta><countGroup><count type="wordTotal" number="15000"></count><count type="figureTotal" number="6"></count><count type="tableTotal" number="3"></count></countGroup><titleGroup><title type="main">Effects of foliage clumping on the estimation of global terrestrial gross primary productivity</title><title type="shortAuthors">CHEN ET AL.</title><title type="short">FOLIAGE CLUMPING EFFECT ON GLOBAL GPP</title></titleGroup><creators><creator xml:id="gbc1842-cr-0001" creatorRole="author" affiliationRef="#gbc1842-aff-0001 #gbc1842-aff-0002"><personName><givenNames>Jing M.</givenNames><familyName>Chen</familyName></personName><contactDetails><email>chenj@geog.utoronto.ca</email></contactDetails></creator><creator xml:id="gbc1842-cr-0002" creatorRole="author" affiliationRef="#gbc1842-aff-0002"><personName><givenNames>Gang</givenNames><familyName>Mo</familyName></personName></creator><creator xml:id="gbc1842-cr-0003" creatorRole="author" affiliationRef="#gbc1842-aff-0002 #gbc1842-aff-0003"><personName><givenNames>Jan</givenNames><familyName>Pisek</familyName></personName></creator><creator xml:id="gbc1842-cr-0004" creatorRole="author" affiliationRef="#gbc1842-aff-0002"><personName><givenNames>Jane</givenNames><familyName>Liu</familyName></personName></creator><creator xml:id="gbc1842-cr-0005" creatorRole="author" affiliationRef="#gbc1842-aff-0001"><personName><givenNames>Feng</givenNames><familyName>Deng</familyName></personName></creator><creator xml:id="gbc1842-cr-0006" creatorRole="author" affiliationRef="#gbc1842-aff-0004"><personName><givenNames>Misa</givenNames><familyName>Ishizawa</familyName></personName></creator><creator xml:id="gbc1842-cr-0007" creatorRole="author" affiliationRef="#gbc1842-aff-0004"><personName><givenNames>Douglas</givenNames><familyName>Chan</familyName></personName></creator></creators><affiliationGroup><affiliation xml:id="gbc1842-aff-0001" countryCode="CN" type="organization"><unparsedAffiliation>International Institute of Earth System Science, Nanjing University, Nanjing, China</unparsedAffiliation></affiliation><affiliation xml:id="gbc1842-aff-0002" countryCode="CA" type="organization"><unparsedAffiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</unparsedAffiliation></affiliation><affiliation xml:id="gbc1842-aff-0003" countryCode="EE" type="organization"><unparsedAffiliation>Tartu Observatory 61602, Toravere, Estonia</unparsedAffiliation></affiliation><affiliation xml:id="gbc1842-aff-0004" countryCode="CA" type="organization"><unparsedAffiliation>Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada</unparsedAffiliation></affiliation></affiliationGroup><keywordGroup type="author"><keyword xml:id="gbc1842-kwd-0001">LAI</keyword><keyword xml:id="gbc1842-kwd-0002">canopy radiation</keyword><keyword xml:id="gbc1842-kwd-0003">clumping index</keyword><keyword xml:id="gbc1842-kwd-0004">global GPP</keyword><keyword xml:id="gbc1842-kwd-0005">photosynthesis model</keyword></keywordGroup><supportingInformation><supportingInfoItem><mediaResource alt="supplementary data" mimeType="text/plain" href="urn-x:wiley:08866236:media:gbc1842:gbc1842-sup-0001-t01"></mediaResource><caption>Tab‐delimited Table 1.</caption></supportingInfoItem><supportingInfoItem><mediaResource alt="supplementary data" mimeType="text/plain" href="urn-x:wiley:08866236:media:gbc1842:gbc1842-sup-0002-t02"></mediaResource><caption>Tab‐delimited Table 2.</caption></supportingInfoItem><supportingInfoItem><mediaResource alt="supplementary data" mimeType="text/plain" href="urn-x:wiley:08866236:media:gbc1842:gbc1842-sup-0003-t03"></mediaResource><caption>Tab‐delimited Table 3.</caption></supportingInfoItem></supportingInformation><abstractGroup><abstract type="main"><p xml:id="gbc1842-para-0001" label="1">Sunlit and shaded leaf separation proposed by Norman (1982) is an effective way to upscale from leaf to canopy in modeling vegetation photosynthesis. The Boreal Ecosystem Productivity Simulator (BEPS) makes use of this methodology, and has been shown to be reliable in modeling the gross primary productivity (GPP) derived from CO<sub>2</sub>flux and tree ring measurements. In this study, we use BEPS to investigate the effect of canopy architecture on the global distribution of GPP. For this purpose, we use not only leaf area index (LAI) but also the first ever global map of the foliage clumping index derived from the multiangle satellite sensor POLDER at 6 km resolution. The clumping index, which characterizes the degree of the deviation of 3‐dimensional leaf spatial distributions from the random case, is used to separate sunlit and shaded LAI values for a given LAI. Our model results show that global GPP in 2003 was 132 ± 22 Pg C. Relative to this baseline case, our results also show: (1) global GPP is overestimated by 12% when accurate LAI is available but clumping is ignored, and (2) global GPP is underestimated by 9% when the effective LAI is available and clumping is ignored. The clumping effects in both cases are statistically significant (p < 0.001). The effective LAI is often derived from remote sensing by inverting the measured canopy gap fraction to LAI without considering the clumping. Global GPP would therefore be generally underestimated when remotely sensed LAI (actually effective LAI by our definition) is used. This is due to the underestimation of the shaded LAI and therefore the contribution of shaded leaves to GPP. We found that shaded leaves contribute 50%, 38%, 37%, 39%, 26%, 29% and 21% to the total GPP for broadleaf evergreen forest, broadleaf deciduous forest, evergreen conifer forest, deciduous conifer forest, shrub, C4 vegetation, and other vegetation, respectively. The global average of this ratio is 35%.</p></abstract><abstract type="short"><title type="main">Key Points</title><p xml:id="gbc1842-para-0002"><list style="bulleted"><listItem>Plant canopy structure is quantified by both LAI and clumping index</listItem><listItem>A global clumping map is for the first time used for global GPP estimation</listItem><listItem>The impact of clumping is highly significant for global GPP modeling</listItem></list></p></abstract></abstractGroup></contentMeta></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Effects of foliage clumping on the estimation of global terrestrial gross primary productivity</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>FOLIAGE CLUMPING EFFECT ON GLOBAL GPP</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Effects of foliage clumping on the estimation of global terrestrial gross primary productivity</title></titleInfo><name type="personal"><namePart type="given">Jing M.</namePart><namePart type="family">Chen</namePart><affiliation>International Institute of Earth System Science, Nanjing University, Nanjing, China</affiliation><affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</affiliation><affiliation>E-mail: chenj@geog.utoronto.ca</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Gang</namePart><namePart type="family">Mo</namePart><affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Jan</namePart><namePart type="family">Pisek</namePart><affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</affiliation><affiliation>Tartu Observatory 61602, Toravere, Estonia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Jane</namePart><namePart type="family">Liu</namePart><affiliation>Department of Geography, University of Toronto, Toronto, Ontario, Canada</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Feng</namePart><namePart type="family">Deng</namePart><affiliation>International Institute of Earth System Science, Nanjing University, Nanjing, China</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Misa</namePart><namePart type="family">Ishizawa</namePart><affiliation>Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Douglas</namePart><namePart type="family">Chan</namePart><affiliation>Meteorological Service of Canada, Environment Canada, Toronto, Ontario, Canada</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="article" displayLabel="article"></genre><originInfo><publisher>Blackwell Publishing Ltd</publisher><dateIssued encoding="w3cdtf">2012-03</dateIssued><dateCaptured encoding="w3cdtf">2010-11-16</dateCaptured><dateValid encoding="w3cdtf">2012-01-03</dateValid><edition>Chen, J. M., G. Mo, J. Pisek, J. Liu, F. Deng, M. Ishizawa, and D. Chan (2012), Effects of foliage clumping on the estimation of global terrestrial gross primary productivity, Global Biogeochem. Cycles, 26, GB1019, doi:10.1029/2010GB003996.</edition><copyrightDate encoding="w3cdtf">2012</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType><extent unit="figures">6</extent><extent unit="tables">3</extent><extent unit="words">15000</extent></physicalDescription><abstract>Sunlit and shaded leaf separation proposed by Norman (1982) is an effective way to upscale from leaf to canopy in modeling vegetation photosynthesis. The Boreal Ecosystem Productivity Simulator (BEPS) makes use of this methodology, and has been shown to be reliable in modeling the gross primary productivity (GPP) derived from CO2flux and tree ring measurements. In this study, we use BEPS to investigate the effect of canopy architecture on the global distribution of GPP. For this purpose, we use not only leaf area index (LAI) but also the first ever global map of the foliage clumping index derived from the multiangle satellite sensor POLDER at 6 km resolution. The clumping index, which characterizes the degree of the deviation of 3‐dimensional leaf spatial distributions from the random case, is used to separate sunlit and shaded LAI values for a given LAI. Our model results show that global GPP in 2003 was 132 ± 22 Pg C. Relative to this baseline case, our results also show: (1) global GPP is overestimated by 12% when accurate LAI is available but clumping is ignored, and (2) global GPP is underestimated by 9% when the effective LAI is available and clumping is ignored. The clumping effects in both cases are statistically significant (p < 0.001). The effective LAI is often derived from remote sensing by inverting the measured canopy gap fraction to LAI without considering the clumping. Global GPP would therefore be generally underestimated when remotely sensed LAI (actually effective LAI by our definition) is used. This is due to the underestimation of the shaded LAI and therefore the contribution of shaded leaves to GPP. We found that shaded leaves contribute 50%, 38%, 37%, 39%, 26%, 29% and 21% to the total GPP for broadleaf evergreen forest, broadleaf deciduous forest, evergreen conifer forest, deciduous conifer forest, shrub, C4 vegetation, and other vegetation, respectively. The global average of this ratio is 35%.</abstract><abstract type="short">Plant canopy structure is quantified by both LAI and clumping index A global clumping map is for the first time used for global GPP estimation The impact of clumping is highly significant for global GPP modeling</abstract><note type="additional physical form">Tab‐delimited Table 1.Tab‐delimited Table 2.Tab‐delimited Table 3.</note><subject><genre>keywords</genre><topic>LAI</topic><topic>canopy radiation</topic><topic>clumping index</topic><topic>global GPP</topic><topic>photosynthesis model</topic></subject><relatedItem type="host"><titleInfo><title>Global Biogeochemical Cycles</title></titleInfo><titleInfo type="abbreviated"><title>Global Biogeochem. Cycles</title></titleInfo><genre type="journal">journal</genre><subject><genre>index-terms</genre><topic authorityURI="http://psi.agu.org/taxonomy5/0400">BIOGEOSCIENCES</topic><topic authorityURI="http://psi.agu.org/taxonomy5/0412">Biogeochemical kinetics and reaction modeling</topic><topic authorityURI="http://psi.agu.org/taxonomy5/0414">Biogeochemical cycles, processes, and modeling</topic><topic authorityURI="http://psi.agu.org/taxonomy5/0428">Carbon cycling</topic><topic authorityURI="http://psi.agu.org/taxonomy5/0700">CRYOSPHERE</topic><topic authorityURI="http://psi.agu.org/taxonomy5/0793">Biogeochemistry</topic><topic authorityURI="http://psi.agu.org/taxonomy5/1600">GLOBAL CHANGE</topic><topic authorityURI="http://psi.agu.org/taxonomy5/1615">Biogeochemical cycles, processes, and modeling</topic><topic authorityURI="http://psi.agu.org/taxonomy5/1640">Remote sensing</topic><topic authorityURI="http://psi.agu.org/taxonomy5/1800">HYDROLOGY</topic><topic authorityURI="http://psi.agu.org/taxonomy5/1855">Remote sensing</topic><topic authorityURI="http://psi.agu.org/taxonomy5/4300">NATURAL HAZARDS</topic><topic authorityURI="http://psi.agu.org/taxonomy5/4337">Remote sensing and disasters</topic><topic authorityURI="http://psi.agu.org/taxonomy5/4800">OCEANOGRAPHY: BIOLOGICAL AND CHEMICAL</topic><topic authorityURI="http://psi.agu.org/taxonomy5/4806">Carbon cycling</topic><topic authorityURI="http://psi.agu.org/taxonomy5/4805">Biogeochemical cycles, processes, and modeling</topic><topic authorityURI="http://psi.agu.org/taxonomy5/4900">PALEOCEANOGRAPHY</topic><topic authorityURI="http://psi.agu.org/taxonomy5/4912">Biogeochemical cycles, processes, and modeling</topic></subject><identifier type="ISSN">0886-6236</identifier><identifier type="eISSN">1944-9224</identifier><identifier type="DOI">10.1002/(ISSN)1944-9224</identifier><identifier type="CODEN">GBCYEP</identifier><identifier type="PublisherID">GBC</identifier><part><date>2012</date><detail type="volume"><caption>vol.</caption><number>26</number></detail><detail type="issue"><caption>no.</caption><number>1</number></detail><extent unit="pages"><start>n/a</start><end>n/a</end><total>18</total></extent></part></relatedItem><identifier type="istex">1BE91345AC1E39E7C900AB319CB7B6B9B953E9E6</identifier><identifier type="DOI">10.1029/2010GB003996</identifier><identifier type="ArticleID">2010GB003996</identifier><accessCondition type="use and reproduction" contentType="copyright">Copyright 2012 by the American Geophysical Union</accessCondition><recordInfo><recordContentSource>WILEY</recordContentSource></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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