Carbon balance assessment at regional scale
The mechanisms involved in carbon exchange between terrestrial ecosystems and the atmosphee are mostly well known. Reliable estimates of CO exchange can be done using biological simulation models at plant, plot and, with lower accuracy, at ecosystem scale. Direct measurement of such exchange is of o...
Main Authors: | , |
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Format: | Article |
Language: | Italian |
Published: |
Italian Society of Silviculture and Forest Ecology (SISEF)
2007-12-01
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Series: | Forest@ |
Subjects: | |
Online Access: | http://www.sisef.it/forest@/showPaper.php?action=html(14,486)&lang=en |
Summary: | The mechanisms involved in carbon exchange between terrestrial ecosystems and the atmosphee are mostly well known. Reliable estimates of CO exchange can be done using biological simulation models at plant, plot and, with lower accuracy, at ecosystem scale. Direct measurement of such exchange is of outmost importance to verify models and the hypothesis on which they rare based, and also to investigate, verify and model new and poorly known processes. Until today scientific research has been provided with reliable tecniques to measure carbon exchange at leaf and plant level (chambers), and ecosystem level (eddy covariance), while difficulties exist into up scaling these figures to the regional and the global scales. The advent of compact instruments and data systems has recently allowed small research aircraft to measure mass, momentum, and energy fluxes at the regional scale with the eddy covariance tecnique. This paper describes the aerial platform and the application of micrometeorological methods from moving platforms. A methodology, applied within international research projects, aimed at quantifying the regional annual carbon balance is described, based on the computation of mean daily fluxes for ecosystem type. The advanteges and the limitations of using such approach to derive regional fluxes are discussed, while potential improvements based on the integration of direct flux measurements with multispectral remote sensing are highlighted. |
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ISSN: | 1824-0119 1824-0119 |