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Estimation of deciduous forest leaf area index using direct and indirect methods

✍ Scribed by Eric Dufrêne; Nathalie Bréda


Book ID
104724084
Publisher
Springer-Verlag
Year
1995
Tongue
English
Weight
828 KB
Volume
104
Category
Article
ISSN
0029-8549

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✦ Synopsis


This study evaluated one semi-direct and three indirect methods for estimating leaf area index (LAI) by comparing these estimates with direct estimates derived from litter collection. The semi-direct method uses a thin metallic needle to count a number of contacts across fresh litter layers. One indirect method is based on the penetration of diffuse global radiation measured over the course of a day. The second indirect method uses the LAI-2000 plant canopy analyser (PCA) which measures diffuse light penetration from five different sky sectors simultaneously. The third indirect method uses the "Demon" portable light sensor to measure the penetration of direct beam sunlight at different zenith angles over the course of half a day. The Poisson model of gap frequency was applied to estimate plant area index (PAI) from observed transmittances using the second and third methods. Litter collection from 11 temperate decidous forests gave values of LAI ranging from 1.7 to 7.5. Estimates based on the needle method showed a significant linear relationship with LAI values obtained from litter collections but were systematically lower (by 6-37%). PAI estimates using all three indirect techniques (fixed light sensor system, LAI-2000 and Demon) showed a strong linear relationship with LAI derived from litter collection. Differences, averaged over all forest stands, between PAI estimates from each of the three indirect methods and LAI from litter collections were below 2%. If we consider that LAI=PAI-WAI (wood area index) then, all three indirect methods underestimated LAI by an additional factor close to the value of WAI. One reason could be a local clumping of architectural canopy components: in particular, the spatial dispositions of branchlets and leaves are not independent, leading to a non-random relationship between the distributions of these two canopy components.


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