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An integrated pan-tropical biomass map using multiple reference datasets.

Identifieur interne : 002378 ( Main/Exploration ); précédent : 002377; suivant : 002379

An integrated pan-tropical biomass map using multiple reference datasets.

Auteurs : Valerio Avitabile [Pays-Bas] ; Martin Herold [Pays-Bas] ; Gerard B M. Heuvelink [Pays-Bas] ; Simon L. Lewis [Royaume-Uni] ; Oliver L. Phillips [Royaume-Uni] ; Gregory P. Asner [États-Unis] ; John Armston [Australie] ; Peter S. Ashton [États-Unis] ; Lindsay Banin [Royaume-Uni] ; Nicolas Bayol [France] ; Nicholas J. Berry [Royaume-Uni] ; Pascal Boeckx [Belgique] ; Bernardus H J. De Jong [Mexique] ; Ben Devries [Pays-Bas] ; Cecile A J. Girardin [Royaume-Uni] ; Elizabeth Kearsley [Belgique] ; Jeremy A. Lindsell [Royaume-Uni] ; Gabriela Lopez-Gonzalez [Royaume-Uni] ; Richard Lucas [Australie] ; Yadvinder Malhi [Royaume-Uni] ; Alexandra Morel [Royaume-Uni] ; Edward T A. Mitchard [Royaume-Uni] ; Laszlo Nagy [Brésil] ; Lan Qie [Royaume-Uni] ; Marcela J. Quinones [Pays-Bas] ; Casey M. Ryan [Royaume-Uni] ; Slik J W. Ferry [Brunei] ; Terry Sunderland [Indonésie] ; Gaia Vaglio Laurin [Italie] ; Roberto Cazzolla Gatti [Italie] ; Riccardo Valentini [Italie] ; Hans Verbeeck [Belgique] ; Arief Wijaya [Indonésie] ; Simon Willcock [Royaume-Uni]

Source :

RBID : pubmed:26499288

Descripteurs français

English descriptors

Abstract

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.

DOI: 10.1111/gcb.13139
PubMed: 26499288


Affiliations:


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<name sortKey="Sunderland, Terry" sort="Sunderland, Terry" uniqKey="Sunderland T" first="Terry" last="Sunderland">Terry Sunderland</name>
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<nlm:affiliation>Centro Euro-Mediterraneo sui Cambiamenti Climatici, Iafes Division, via Pacinotti 5, Viterbo, Italy.</nlm:affiliation>
<country xml:lang="fr">Italie</country>
<wicri:regionArea>Centro Euro-Mediterraneo sui Cambiamenti Climatici, Iafes Division, via Pacinotti 5, Viterbo</wicri:regionArea>
<wicri:noRegion>Viterbo</wicri:noRegion>
</affiliation>
</author>
<author>
<name sortKey="Valentini, Riccardo" sort="Valentini, Riccardo" uniqKey="Valentini R" first="Riccardo" last="Valentini">Riccardo Valentini</name>
<affiliation wicri:level="1">
<nlm:affiliation>Department of Innovation of Biological Systems, Tuscia University, Via S. Camillo de Lellis, Viterbo, Italy.</nlm:affiliation>
<country xml:lang="fr">Italie</country>
<wicri:regionArea>Department of Innovation of Biological Systems, Tuscia University, Via S. Camillo de Lellis, Viterbo</wicri:regionArea>
<wicri:noRegion>Viterbo</wicri:noRegion>
</affiliation>
</author>
<author>
<name sortKey="Verbeeck, Hans" sort="Verbeeck, Hans" uniqKey="Verbeeck H" first="Hans" last="Verbeeck">Hans Verbeeck</name>
<affiliation wicri:level="4">
<nlm:affiliation>Isotope Bioscience Laboratory, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000, Gent, Belgium.</nlm:affiliation>
<country xml:lang="fr">Belgique</country>
<wicri:regionArea>Isotope Bioscience Laboratory, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000, Gent</wicri:regionArea>
<orgName type="university">Université de Gand</orgName>
<placeName>
<settlement type="city">Gand</settlement>
<region>Région flamande</region>
<region type="district" nuts="2">Province de Flandre-Orientale</region>
</placeName>
</affiliation>
</author>
<author>
<name sortKey="Wijaya, Arief" sort="Wijaya, Arief" uniqKey="Wijaya A" first="Arief" last="Wijaya">Arief Wijaya</name>
<affiliation wicri:level="1">
<nlm:affiliation>Center for International Forestry Research, PO Box 0113 BOCBD, Bogor, 16000, Indonesia.</nlm:affiliation>
<country xml:lang="fr">Indonésie</country>
<wicri:regionArea>Center for International Forestry Research, PO Box 0113 BOCBD, Bogor, 16000</wicri:regionArea>
<wicri:noRegion>16000</wicri:noRegion>
</affiliation>
</author>
<author>
<name sortKey="Willcock, Simon" sort="Willcock, Simon" uniqKey="Willcock S" first="Simon" last="Willcock">Simon Willcock</name>
<affiliation wicri:level="1">
<nlm:affiliation>Centre for Biological Sciences, the University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK.</nlm:affiliation>
<country xml:lang="fr">Royaume-Uni</country>
<wicri:regionArea>Centre for Biological Sciences, the University of Southampton, Highfield Campus, Southampton, SO17 1BJ</wicri:regionArea>
<wicri:noRegion>SO17 1BJ</wicri:noRegion>
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</author>
</analytic>
<series>
<title level="j">Global change biology</title>
<idno type="eISSN">1365-2486</idno>
<imprint>
<date when="2016" type="published">2016</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc>
<textClass>
<keywords scheme="KwdEn" xml:lang="en">
<term>Biomass</term>
<term>Datasets as Topic</term>
<term>Maps as Topic</term>
<term>Models, Theoretical</term>
<term>Trees</term>
<term>Tropical Climate</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr">
<term>Arbres</term>
<term>Biomasse</term>
<term>Cartes comme sujet</term>
<term>Climat tropical</term>
<term>Données de la recherche comme sujet</term>
<term>Modèles théoriques</term>
</keywords>
<keywords scheme="MESH" xml:lang="en">
<term>Biomass</term>
<term>Datasets as Topic</term>
<term>Maps as Topic</term>
<term>Models, Theoretical</term>
<term>Trees</term>
<term>Tropical Climate</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr">
<term>Arbres</term>
<term>Biomasse</term>
<term>Cartes comme sujet</term>
<term>Climat tropical</term>
<term>Données de la recherche comme sujet</term>
<term>Modèles théoriques</term>
</keywords>
</textClass>
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</teiHeader>
<front>
<div type="abstract" xml:lang="en">We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.</div>
</front>
</TEI>
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<list>
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<li>Australie</li>
<li>Belgique</li>
<li>Brunei</li>
<li>Brésil</li>
<li>France</li>
<li>Indonésie</li>
<li>Italie</li>
<li>Mexique</li>
<li>Pays-Bas</li>
<li>Royaume-Uni</li>
<li>États-Unis</li>
</country>
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<li>Angleterre</li>
<li>Gueldre (province)</li>
<li>Massachusetts</li>
<li>Oxfordshire</li>
<li>Province de Flandre-Orientale</li>
<li>Région flamande</li>
<li>Yorkshire-et-Humber</li>
<li>Écosse</li>
<li>État de São Paulo</li>
</region>
<settlement>
<li>Cambridge (Massachusetts)</li>
<li>Campinas</li>
<li>Gand</li>
<li>Leeds</li>
<li>Oxford</li>
<li>Wageningue</li>
<li>Édimbourg</li>
</settlement>
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<li>Université Harvard</li>
<li>Université d'Oxford</li>
<li>Université d'Édimbourg</li>
<li>Université d'État de Campinas</li>
<li>Université de Gand</li>
<li>Université de Leeds</li>
<li>Université de Wageningue</li>
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<name sortKey="Heuvelink, Gerard B M" sort="Heuvelink, Gerard B M" uniqKey="Heuvelink G" first="Gerard B M" last="Heuvelink">Gerard B M. Heuvelink</name>
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<name sortKey="Lindsell, Jeremy A" sort="Lindsell, Jeremy A" uniqKey="Lindsell J" first="Jeremy A" last="Lindsell">Jeremy A. Lindsell</name>
<name sortKey="Lopez Gonzalez, Gabriela" sort="Lopez Gonzalez, Gabriela" uniqKey="Lopez Gonzalez G" first="Gabriela" last="Lopez-Gonzalez">Gabriela Lopez-Gonzalez</name>
<name sortKey="Malhi, Yadvinder" sort="Malhi, Yadvinder" uniqKey="Malhi Y" first="Yadvinder" last="Malhi">Yadvinder Malhi</name>
<name sortKey="Mitchard, Edward T A" sort="Mitchard, Edward T A" uniqKey="Mitchard E" first="Edward T A" last="Mitchard">Edward T A. Mitchard</name>
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<name sortKey="Bayol, Nicolas" sort="Bayol, Nicolas" uniqKey="Bayol N" first="Nicolas" last="Bayol">Nicolas Bayol</name>
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<name sortKey="Boeckx, Pascal" sort="Boeckx, Pascal" uniqKey="Boeckx P" first="Pascal" last="Boeckx">Pascal Boeckx</name>
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<name sortKey="Kearsley, Elizabeth" sort="Kearsley, Elizabeth" uniqKey="Kearsley E" first="Elizabeth" last="Kearsley">Elizabeth Kearsley</name>
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<noRegion>
<name sortKey="De Jong, Bernardus H J" sort="De Jong, Bernardus H J" uniqKey="De Jong B" first="Bernardus H J" last="De Jong">Bernardus H J. De Jong</name>
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<region name="État de São Paulo">
<name sortKey="Nagy, Laszlo" sort="Nagy, Laszlo" uniqKey="Nagy L" first="Laszlo" last="Nagy">Laszlo Nagy</name>
</region>
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