Search

Leaf traits and physiological performance govern the amount of light reflected from leaves at visible and infrared wavebands. Information on leaf optical properties of tropical trees is scarce. Here, we examine leaf reflectance of Mesoamerican trees for three applications: (1) to compare the magnitude of within- and between-species variability in leaf reflectance, (2) to determine the potential for species identification based on leaf reflectance, and (3) to test the strength of relationships between leaf traits (chlorophyll content, mesophyll attributes, thickness) and leaf spectral reflectance. Within species, shape and amplitude differences between spectra were compared within single leaves, between leaves of a single tree, and between trees. We also investigated the variation in a species' leaf reflectance across sites and seasons. Using forward feature selection and pattern recognition tools, species classification within a single site and season was successful, while classification between sites or seasons was not. The implications of variability in leaf spectral reflectance were considered in light of potential tree crown classifications from remote airborne or satellite-borne sensors. Species classification is an emerging field with broad applications to tropical biologists and ecologists, including tree demographic studies and habitat diversity assessments. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: A number of recent studies have focused on estimating gross primary production (GPP) using vegetation indices (VIs). In this paper, GPP is retrieved as a product of incident light use efficiency (LUE), defined as GPP/PAR, and the photosynthetically active radiation (PAR). As a good correlation is found between canopy chlorophyll content and incident LUE for six types of wheat canopy (R 2 =0.87, n =24), indices aimed for chlorophyll assessment can be used as an indicator of incident LUE and the product of chlorophyll indices and PAR will be a proxy of GPP. In a field experiment, we investigated four canopy chlorophyll content related indices (Red edge Normalized Difference Vegetation Index [Red Edge NDVI], modified Chlorophyll Absorption Ratio Index [MCARI710], Red Edge Chlorophyll Index [CIred edge] and the MERIS Terrestrial Chlorophyll Index [MTCI]) for GPP estimation during the growth cycle of wheat. These indices are validated for leaf and canopy chlorophyll estimation with ground truth data of canopy chlorophyll content. With ground truth data, a strong correlation is observed for canopy chlorophyll estimation with correlation coefficients R 2 of 0.79, 0.84, 0.85 and 0.87 for Red Edge NDVI, MCARI710, CIred edge and MTCI, respectively (n =24). As evidence of the existence of a relationship between canopy chlorophyll and GPP/PAR, these indices are shown to be a good proxy of GPP/PAR with R 2 ranging from 0.70 for Red Edge NDVI and 0.75 for MTCI (n =240). Remote estimation of GPP from canopy chlorophyll content×PAR is proved to be relatively successful (R 2 of 0.47, 0.53, 0.65 and 0.66 for Red edge NDVI, MCARI710, CIred edge and MTCI respectively, n =240). These results open up a new possibility to estimate GPP and should inspire new models for remote sensing of GPP. [Copyright &y& Elsevier]