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Models for Predicting leaf traits across functional groups using reflectance spectroscopy

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Title:
Models for Predicting leaf traits across functional groups using reflectance spectroscopy
Author: Kothari, Shan ; Beauchamp-Rioux, Rosalie ; Blanchard, Florence ; Crofts, Anna L ; Girard, Alizée ; Guilbeault-Mayers, Xavier ; Hacker, Paul ; Pardo, Juliana ; Schweiger, Anna K ; Demers-Thibeault, Sabrina ; Bruneau, Anne ; Coops, Nicholas C ; Kalacska, Margaret ; Vellend, Mark ; Laliberté, Etienne
Subjects: Earth and Environmental Sciences ; ecology ; functional traits ; partial least-squares regression ; reflectance spectroscopy
Description: (2022-11-12) This repository contains the partial least-squares regression (PLSR) model coefficients to accompany the paper "Predicting leaf traits across functional groups using reflectance spectroscopy" by Kothari et al. (2023) New Phytologist (DOI: 10.1111/nph.18713). The repository includes the models in various sets of .csv files along with a README that contains detailed instructions about what the models mean and how to use them. 2023-04-06 Update: We have added models to predict EWT for fresh leaves under field conditions rather than rehydrated leaves. These models are found in the folder EWTCorrectedModels. It is recommended to use these rather than the other EWT models for most purposes.
Publisher: Université de Montréal Dataverse
Creation Date: 2022
Language: English
Identifier: DOI: 10.5683/SP3/NYABAG
Source: Lunaris – Canada’s National Data Discovery Service

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