Abstract
Leaf area index (LAI) is a key variable describing ecosystem structure and influencing the exchange of carbon, water, and energy. LAI is often evaluated with indirect methods. However, the accuracy of indirect measurements can vary with canopy structure and is not always generalizable across ecosystems. Previous research has characterized the accuracy of indirect methods for woody plants in forest ecosystems, but it is not well established for woody plants in open ecosystems—despite having large differences in canopy structure. In this study, we compared direct LAI measurements in clonal grassland shrub canopies to three indirect methods: a ceptometer, a handheld 3D scanner (processed using EXScanPro-3.6 software), and NEON's LAI product obtained from airborne hyperspectral imaging (derived from SAVI). To our knowledge, this is the first study to assess the accuracy of leaf area data in woody plants using a handheld 3D scanner and one of few studies assessing the accuracy of the National Ecological Observation Network's (NEON) Airborne Observation Platform—our source of airborne hyperspectral imaging. Data were collected in tallgrass prairie undergoing woody encroachment and three treatments: no herbivore disturbance, bison present, and simulated browsing. We found that direct LAI measurements of control and grazed C. drummondii canopies averaged ∼8.0. The ceptometer accurately estimated LAI in non-browsed canopies but overestimated LAI of browsed canopies by 38 %. One-sided leaf area of ramets measured with a handheld 3D scanner was strongly related to direct measurements (r2=0.86), but underestimated leaf area at greater values. LAI estimated from airborne spectral data underestimated LAI by 55 %. We conclude that a ceptometer was adequate for measuring LAI in dense shrub canopies when browsing was not present, the handheld 3D scanner was adequate for measuring leaf area of individual ramets, and the airborne spectral data was not suitable for estimating LAI of dense, grassland shrub canopies.
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