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| Titel |
Influence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in Amazonia |
| VerfasserIn |
L. O. Anderson, Y. Malhi, R. J. Ladle, L. E. O. C. Aragão, Y. Shimabukuro, O. L. Phillips, T. Baker, A. C. L. Costa, J. S. Espejo, N. Higuchi, W. F. Laurance, G. López-González, A. Monteagudo, P. Núñez-Vargas, J. Peacock, C. A. Quesada, S. Almeida |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 6, no. 9 ; Nr. 6, no. 9 (2009-09-08), S.1883-1902 |
| Datensatznummer |
250003992
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| Publikation (Nr.) |
 copernicus.org/bg-6-1883-2009.pdf |
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| Zusammenfassung |
| 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 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. |
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