Influence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in Amazonia

Long-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...

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Asıl Yazarlar: Anderson, L, Malhi, Y, Ladle, R, Aragão, L, Shimabukuro, Y, Phillips, O, Baker, T, Costa, A, Espejo, J, Higuchi, N, Laurance, W, López-González, G, Monteagudo, A, Núñez-Vargas, P, Peacock, J, Quesada, C, Almeida, S
Diğer Yazarlar: European Geosciences Union
Materyal Türü: Journal article
Dil:English
Baskı/Yayın Bilgisi: Copernicus Publications 2009
Konular:
_version_ 1826281373725360128
author Anderson, L
Malhi, Y
Ladle, R
Aragão, L
Shimabukuro, Y
Phillips, O
Baker, T
Costa, A
Espejo, J
Higuchi, N
Laurance, W
López-González, G
Monteagudo, A
Núñez-Vargas, P
Peacock, J
Quesada, C
Almeida, S
author2 European Geosciences Union
author_facet European Geosciences Union
Anderson, L
Malhi, Y
Ladle, R
Aragão, L
Shimabukuro, Y
Phillips, O
Baker, T
Costa, A
Espejo, J
Higuchi, N
Laurance, W
López-González, G
Monteagudo, A
Núñez-Vargas, P
Peacock, J
Quesada, C
Almeida, S
author_sort Anderson, L
collection OXFORD
description Long-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 <em>terra firme</em> forest, three types of forests over Paleovarzea geomorphologycal formation, two types of bamboo-dominated forest, palm forest, <em>Heliconia</em> monodominant vegetation, swamp forest, disturbed forests and land use areas. Overall, the plots were generally representative of the forst 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 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.
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spelling oxford-uuid:7ebd98d2-c938-4ba7-9593-30eb29c7e5d42022-03-26T21:12:06ZInfluence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in AmazoniaJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:7ebd98d2-c938-4ba7-9593-30eb29c7e5d4Climate systems and policyEnvironmentEnglishOxford University Research Archive - ValetCopernicus Publications2009Anderson, LMalhi, YLadle, RAragão, LShimabukuro, YPhillips, OBaker, TCosta, AEspejo, JHiguchi, NLaurance, WLópez-González, GMonteagudo, ANúñez-Vargas, PPeacock, JQuesada, CAlmeida, SEuropean Geosciences UnionLong-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 <em>terra firme</em> forest, three types of forests over Paleovarzea geomorphologycal formation, two types of bamboo-dominated forest, palm forest, <em>Heliconia</em> monodominant vegetation, swamp forest, disturbed forests and land use areas. Overall, the plots were generally representative of the forst 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 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.
spellingShingle Climate systems and policy
Environment
Anderson, L
Malhi, Y
Ladle, R
Aragão, L
Shimabukuro, Y
Phillips, O
Baker, T
Costa, A
Espejo, J
Higuchi, N
Laurance, W
López-González, G
Monteagudo, A
Núñez-Vargas, P
Peacock, J
Quesada, C
Almeida, S
Influence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in Amazonia
title Influence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in Amazonia
title_full Influence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in Amazonia
title_fullStr Influence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in Amazonia
title_full_unstemmed Influence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in Amazonia
title_short Influence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in Amazonia
title_sort influence of landscape heterogeneity on spatial patterns of wood productivity wood specific density and above ground biomass in amazonia
topic Climate systems and policy
Environment
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