Title
Data and code for remote spectral detection of biodiversity effects on forest biomass
Published Date
2020-08-26
Authors
Author Contact
Williams, Laura J (will3972@umn.edu)
Type
Dataset
Field Study Data
Statistical Computing Software Code
Abstract
Quantifying how biodiversity affects ecosystem functions through time over large spatial extents is needed to meet global biodiversity goals yet is infeasible with field-based approaches alone. Imaging spectroscopy is a tool with potential to help address this challenge. In this study, we demonstrated a spectral approach to assess biodiversity effects in young forests that provides insight into its underlying drivers and could potentially be applied at large spatial scales. Using airborne imaging (NASA AVIRIS-NG) of a tree diversity experiment (IDENT-Cloquet in Cloquet, MN), spectral differences among plots enabled us to quantify net biodiversity effects on stem biomass and canopy nitrogen. In this repository, we present the spectral data and field data along with spectral model coefficients and example code for fitting and applying spectral models to calculate spectral biodiversity effects.
Funding information
Sponsorship:
The project was funded by a National Science Foundation and National Aeronautic and Space Administration grant awarded to Jeannine Cavender-Bares (DEB-1342872) and Philip A. Townsend (DEB-1342778) through the Dimensions of Biodiversity program.
Referenced by
Williams, L.J., Cavender-Bares, J., Townsend, P.A., Couture, J.J., Wang, Z., Stefanski, A., Messier, C., and Reich, P.B. Remote spectral detection of biodiversity effects on forest biomass. Nature Ecology & Evolution.
License
Attribution-NonCommercial-NoDerivs 3.0 United States
Suggested Citation
Williams, Laura J; Cavender-Bares, Jeannine; Townsend, Philip A; Couture, John J; Wang, Zhihui; Stefanski, Artur; Messier, Christian; Reich, Peter B.
(2020). Data and code for remote spectral detection of biodiversity effects on forest biomass.
Retrieved from the Data Repository for the University of Minnesota,
https://doi.org/10.13020/s7pf-am91.