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1. Identity statement
Reference TypeJournal Article
Siteplutao.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
IdentifierJ8LNKAN8RW/36KNMEH
Repositorydpi.inpe.br/plutao@80/2009/12.22.14.54.24
Last Update2010:09.15.13.47.32 (UTC) marciana
Metadata Repositorydpi.inpe.br/plutao@80/2009/12.22.14.54.25
Metadata Last Update2018:06.05.00.12.55 (UTC) administrator
Secondary KeyINPE--PRE/
DOI10.5194/bg-6-1883-2009
Labellattes: 7834780583735756 1 AndersonMLASPBCEHLLMNPQAV:2009:InLaHe
Citation KeyAndersonMLASPBCEHLLMNPQA:2009:InLaHe
TitleInfluence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in Amazonia
Year2009
Access Date2024, May 18
Number of Files1
Size3676 KiB
2. Context
Author 1 Anderson, Liana Oighenstein
 2 Malhi, Yadvinder
 3 Ladle, Richard J.
 4 Aragão, Luiz Eduardo O. C.
 5 Shimabukuro, Yosio Edemir
 6 Phillips, Oliver
 7 Baker, Tim
 8 Costa, Antonio Lola da
 9 Espejo, Javier
10 Higuchi, Niro
11 Laurance, William F.
12 López-González, Gabi
13 Monteagudo, Abel
14 Núñez-Vargas, Percy
15 Peacock, July
16 Quesada, Carlos A.
17 Almeida, Samuel
Resume Identifier 1
 2
 3
 4
 5 8JMKD3MGP5W/3C9JJCQ
Group 1
 2
 3
 4
 5 DSR-OBT-INPE-MCT-BR
Affiliation 1 Univ Oxford, Sch Geog & Environm, Oxford, England
 2 Univ Oxford, Sch Geog & Environm, Oxford, England
 3 Univ Oxford, Sch Geog & Environm, Oxford, England
 4 Univ Oxford, Sch Geog & Environm, Oxford, England
 5 Instituto Nacional de Pesquisas Espaciais (INPE)
 6 Univ Leeds, Sch Geog, Earth & Biosphere Inst, Leeds LS2 9JT, W Yorkshire England
 7 Univ Leeds, Sch Geog, Earth & Biosphere Inst, Leeds LS2 9JT, W Yorkshire England
 8 Fed Univ Para, BR-66059 Belem, Para Brazil
 9 Inst Natl Pesquisas Amazonia, Manaus, Amazonas Brazil
10 Inst Natl Pesquisas Amazonia, Manaus, Amazonas Brazil
11 Smithsonian Trop Res Inst, Balboa, Panama
12
13 Univ Nacl San Antonia Abad Cusco, Herbario Vargas, Cuzco, Peru
14 Univ Nacl San Antonia Abad Cusco, Herbario Vargas, Cuzco, Peru
15 Univ Leeds, Sch Geog, Earth & Biosphere Inst, Leeds LS2 9JT, W Yorkshire England
16 Univ Leeds, Sch Geog, Earth & Biosphere Inst, Leeds LS2 9JT, W Yorkshire England
17 Museu Paraense Emilio Goeldi, Belem, Para Brazil
Author e-Mail Address 1 liana.anderson@ouce.ox.ac.uk
e-Mail Addressliana.anderson@ouce.ox.ac.uk
JournalBiogeosciences
Volume6
Number9
Pages1883-1902
History (UTC)2009-12-23 14:00:46 :: lattes -> marciana ::
2010-01-04 17:51:35 :: marciana -> administrator ::
2010-01-26 15:36:55 :: administrator -> marciana ::
2010-05-11 14:45:40 :: marciana -> administrator ::
2010-05-12 02:06:39 :: administrator -> marciana ::
2011-12-07 11:31:33 :: marciana -> administrator :: 2009
2016-06-04 01:08:39 :: administrator -> marciana :: 2009
2016-10-04 14:18:26 :: marciana -> administrator :: 2009
2018-06-05 00:12:55 :: administrator -> marciana :: 2009
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
Keywords: aboveground biomass
carbon cycle
forestry production
geomorphology
Landsat thematic mapper
landscape structure
remote sensing
wood
Amazonia
Heliconia
AbstractLong-term studies using the RAINFOR network of forest plots have generated significant insights into the spatial and temporal dynamics of forest carbon cycling in Amazonia. In this work, we map and explore the landscape context of several major RAINFOR plot clusters using Landsat ETM+ satellite data. In particular, we explore how representative the plots are of their landscape context, and test whether bias in plot location within landscapes may be influencing the regional mean values obtained for important forest biophysical parameters. Specifically, we evaluate whether the regional variations in wood productivity, wood specific density and above ground biomass derived from the RAINFOR network could be driven by systematic and unintentional biases in plot location. Remote sensing data covering 45 field plots were aggregated to generate landscape maps to identify the specific physiognomy of the plots. In the Landsat ETM+ data, it was possible to spectrally differentiate three types of terra firme forest, three types of forests over Paleovarzea geomorphologycal formation, two types of bamboo-dominated forest, palm forest, Heliconia monodominant vegetation, swamp forest, disturbed forests and land use areas. Overall, the plots were generally representative of the forest physiognomies in the landscape in which they are located. Furthermore, the analysis supports the observed regional trends in those important forest parameters. This study demonstrates the utility of landscape scale analysis of forest physiognomies for validating and supporting the finds of plot based studies. Moreover, the more precise geolocation of many key RAINFOR plot clusters achieved during this research provides important contextual information for studies employing the RAINFOR database.
AreaSRE
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Influence of landscape...
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data URLhttp://urlib.net/ibi/J8LNKAN8RW/36KNMEH
zipped data URLhttp://urlib.net/zip/J8LNKAN8RW/36KNMEH
Languageen
Target Filebg-6-1883-2009.pdf
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Visibilityshown
Archiving Policyallowpublisher allowfinaldraft
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Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ER446E
URL (untrusted data)http://www.cosis.net/members/journals/df/recent.php?j_id=8
Host Collectiondpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notes
NotesDOAJ Directory of Open Access Journals Free
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