Effects of foliage clumping on the estimation of global terrestrial gross primary productivity
Identifieur interne : 000368 ( Main/Exploration ); précédent : 000367; suivant : 000369Effects of foliage clumping on the estimation of global terrestrial gross primary productivity
Auteurs : Jing M. Chen [République populaire de Chine, Canada] ; Gang Mo [Canada] ; Jan Pisek [Canada, Estonie] ; Jane Liu [Canada] ; Feng Deng [République populaire de Chine] ; Misa Ishizawa [Canada] ; Douglas Chan [Canada]Source :
- 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%.
Url:
DOI: 10.1029/2010GB003996
Affiliations:
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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><affiliations><list><country><li>Canada</li><li>Estonie</li><li>République populaire de Chine</li></country><region><li>Ontario</li></region><settlement><li>Toronto</li></settlement><orgName><li>Université de Toronto</li></orgName></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Chen, Jing M" sort="Chen, Jing M" uniqKey="Chen J" first="Jing M." last="Chen">Jing M. Chen</name></noRegion><name sortKey="Deng, Feng" sort="Deng, Feng" uniqKey="Deng F" first="Feng" last="Deng">Feng Deng</name></country><country name="Canada"><region name="Ontario"><name sortKey="Chen, Jing M" sort="Chen, Jing M" uniqKey="Chen J" first="Jing M." last="Chen">Jing M. Chen</name></region><name sortKey="Chan, Douglas" sort="Chan, Douglas" uniqKey="Chan D" first="Douglas" last="Chan">Douglas Chan</name><name sortKey="Chen, Jing M" sort="Chen, Jing M" uniqKey="Chen J" first="Jing M." last="Chen">Jing M. Chen</name><name sortKey="Ishizawa, Misa" sort="Ishizawa, Misa" uniqKey="Ishizawa M" first="Misa" last="Ishizawa">Misa Ishizawa</name><name sortKey="Liu, Jane" sort="Liu, Jane" uniqKey="Liu J" first="Jane" last="Liu">Jane Liu</name><name sortKey="Mo, Gang" sort="Mo, Gang" uniqKey="Mo G" first="Gang" last="Mo">Gang Mo</name><name sortKey="Pisek, Jan" sort="Pisek, Jan" uniqKey="Pisek J" first="Jan" last="Pisek">Jan Pisek</name></country><country name="Estonie"><noRegion><name sortKey="Pisek, Jan" sort="Pisek, Jan" uniqKey="Pisek J" first="Jan" last="Pisek">Jan Pisek</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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