Date
3-8-2019
Abstract
These data were simulated using the LANDIS-II model (v.6.0.) with the PnET-Succession extension (v.2.1.1.). We used climate data from the New Mexico Elevation Gradient of eddy-covariance flux towers and the CO2 data from the Mauna Loa Observatory. The sites are labeled as piñon-juniper (PJ), ponderosa pine (PP) and mixed-conifer (MC). The objective of the study was to quantify the differences between a model parametrization that includes species-specific values (SSP) and a generalized functional type parametrization (GFP) on projected carbon dynamics and future vegetation trajectories.
The data are organized as follows: The directory includes folders for carbon dynamics and above-ground biomass under Current climate conditions and under different climate Scenarios. The file naming convention is Site (PJ, PP, MC) and Model parametrization (SSP, GFP). Within each directory is the R code for processing the data and generating the figures in the manuscript Remy et al.
Current: In the Current folder are folders that include all of the output files generated by the PnET-extension for each of the simulations using climate data from the flux towers. The Current folder contains also a folder that includes the flux tower inventory data (biomass data), and files corresponding to the climate data and the eddy-covariance observations for the three sites.
Scenarios: In the Scenarios folder are folder that include all of the output files generated by the PnET-extension for each of the simulations using climate scenarios.
Document Type
Dataset
Recommended Citation
Remy, Cecile; Dan Krofcheck; Alisa Keyser; Marcy Litvak; Scott Collins; and Matthew Hurteau. "Supporting data for Integrating species-specific information in models improves regional projections under climate change." (2019). https://digitalrepository.unm.edu/bio_data/2
