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Trait Estimation in Herbaceous Plant Assemblages from in situ Canopy Spectra
AbstractEstimating plant traits in herbaceous plant assemblages from spectral reflectance data requires aggregation of small scale trait variations to a canopy mean value that is ecologically meaningful and corresponds to the trait content that affects the canopy spectral signal. We investigated estimation capacities of plant traits in a herbaceous setting and how different trait-aggregation methods influence estimation accuracies. Canopy reflectance of 40 herbaceous plant assemblages was measured in situ and biomass was analysed for N, P and C concentration, chlorophyll, lignin, phenol, tannin and specific water concentration, expressed on a mass basis (mg∙g−1). Using Specific Leaf Area (SLA) and Leaf Area Index (LAI), traits were aggregated to two additional expressions: mass per leaf surface (mg∙m−2) and mass per canopy surface (mg∙m−2). All traits were related to reflectance using partial least squares regression. Accuracy of trait estimation varied between traits but was mainly influenced by the trait expression. Chlorophyll and traits expressed on canopy surface were least accurately estimated. Results are attributed to damping or enhancement of the trait signal upon conversion from mass based trait values to leaf and canopy surface expressions. A priori determination of the most appropriate trait expression is viable by considering plant growing strategies.
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Roelofsen, H.D.; van Bodegom, P.M.; Kooistra, L.; Witte, J.-P.M. Trait Estimation in Herbaceous Plant Assemblages from in situ Canopy Spectra. Remote Sens. 2013, 5, 6323-6345.View more citation formats
Roelofsen HD, van Bodegom PM, Kooistra L, Witte J-PM. Trait Estimation in Herbaceous Plant Assemblages from in situ Canopy Spectra. Remote Sensing. 2013; 5(12):6323-6345.Chicago/Turabian Style
Roelofsen, Hans D.; van Bodegom, Peter M.; Kooistra, Lammert; Witte, Jan-Philip M. 2013. "Trait Estimation in Herbaceous Plant Assemblages from in situ Canopy Spectra." Remote Sens. 5, no. 12: 6323-6345.