Optical instruments for measuring leaf area index in low vegetation : application in Arctic ecosystems

Author Posting. © Ecological Society of America, 2005. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecological Applications 15 (2005): 1462–1470, doi:10.1890/03-5354. Leaf area index (LAI)...

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Bibliographic Details
Published in:Ecological Applications
Main Authors: van Wijk, Mark T., Williams, Mathew
Format: Article in Journal/Newspaper
Language:English
Published: Ecological Society of America 2005
Subjects:
LAI
Online Access:https://hdl.handle.net/1912/4710
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Summary:Author Posting. © Ecological Society of America, 2005. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecological Applications 15 (2005): 1462–1470, doi:10.1890/03-5354. Leaf area index (LAI) is a powerful diagnostic of plant productivity. Despite the fact that many methods have been developed to quantify LAI, both directly and indirectly, leaf area index remains difficult to quantify accurately, owing to large spatial and temporal variability. The gap-fraction technique is widely used to estimate the LAI indirectly. However, for low-stature vegetation, the gap-fraction sensor either cannot get totally underneath the plant canopy, thereby missing part of the leaf area present, or is too close to the individual leaves of the canopy, which leads to a large distortion of the LAI estimate. We set out to develop a methodology for easy and accurate nondestructive assessment of the variability of LAI in low-stature vegetation. We developed and tested the methodology in an arctic landscape close to Abisko, Sweden. The LAI of arctic vegetation could be estimated accurately and rapidly by combining field measurements of canopy reflectance (NDVI) and light penetration through the canopy (gap-fraction analysis using a LI-COR LAI-2000). By combining the two methodologies, the limitations of each could be circumvented, and a significantly increased accuracy of the LAI estimates was obtained. The combination of an NDVI sensor for sparser vegetation and a LAI-2000 for denser vegetation could explain 81% of the variance of LAI measured by destructive harvest. We used the method to quantify the spatial variability and the associated uncertainty of leaf area index in a small catchment area. This research was funded by U.S. National Science Foundation grant DEB0087046.