DOI: 10.5061/dryad.k6djh9w4x
title: VTFT_Demography: global ageclass simulation data from the LPJ-wsl v2.0 Dynamic Global Vegetation Model

description: Forest ecosystem processes follow classic responses with age, peaking
 production around canopy closure and declining thereafter. Although age
 dynamics might be more dominant in certain regions over others,
 demographic effects on net primary production (NPP) and heterotrophic
 respiration (Rh) are bound to exist. Yet, explicit representation of
 ecosystem demography is notably absent in most global ecosystem models.
 This is concerning because the global community relies on these models to
 regularly update our collective understanding of the global carbon cycle.
 This paper aims to fill this gap in understanding by presenting the
 technical developments of a computationally-efficient approach for
 representing age-class dynamics within a global ecosystem model, the
 LPJ-wsl v2.0 Dynamic Global Vegetation Model. The modeled age-classes are
 initially created by fire feedbacks, wood harvesting, and abandonment of
 managed land, otherwise aging naturally until a stand-clearing disturbance
 is simulated or prescribed. In this paper, we show that the age-module can
 capture classic demographic patterns in stem density and tree height
 compared to inventory data, and that patterns of ecosystem function follow
 classic responses with age. We also present a few scientific applications
 of the model to assess the modeled age-class distribution over time and to
 determine the demographic effect on ecosystem fluxes relative to climate.
 Simulations show that, between 1860 and 2016, zonal age distribution on
 Earth was driven predominately by fire, causing a ~45-year difference in
 ages between boreal (50N-90N) and tropical (23S-23N) latitudes. Land use
 change and land management was responsible for an additional decrease in
 zonal age by -6 years in boreal and by -21 years in temperate (23N-50N)
 and tropical latitudes, with the anthropogenic effect on zonal age
 distribution increasing over time. A statistical model helped reduced
 LPJ-wsl complexity by predicting per-grid-cell annual NPP and Rh fluxes by
 three terms: precipitation, temperature and age-class; at global scales,
 R2 was between 0.95 and 0.98. As determined by the statistical model, the
 demographic effect on ecosystem function was often less than 0.10 kg C m-2
 yr-1 but as high as 0.60 kg C m-2 yr-1 where the effect was greatest. In
 eastern forests of North America, the demographic effect was of similar
 magnitude, or greater than, the effects of climate; demographic effects
 were similarly important in large regions of every vegetated continent.
 Spatial datasets are provided for global ecosystem ages and the estimated
 coefficients for effects of precipitation, temperature and demography on
 ecosystem function. The discussion focuses on our finding of an increasing
 role of demography in the global carbon cycle, the effect of demography on
 relaxation times (resilience) following a disturbance event and its
 implications at global scales, and a finding of a 40-Pg C increase in
 turnover from age dynamics at global scales. Whereas time is the only
 mechanism that increases ecosystem age, any additional disturbance not
 explicitly modeled will decrease age. This LPJ-based age-module therefore
 simulates the upper limit of age-class distributions on Earth and
 represents another step forward towards understanding the role of
 demography in global ecosystems.
description: These datasets contain raw data that were simulated by the
 LPJ-wsl v2.0 model
 &lt;https://github.com/benpoulter/LPJ-wsl_v2.0&gt; and R scripts
 to reproduce analyses and figures in the associated publication 
description: There is a general README text file in main folder of
 the archive. It provides detail description of the folder/file structure
 and of every file in the archive. For NetCDF files (*.nc), the
 pre-processing history is self-contained in the metadata and can be
 accessed via the command-line utility "ncdump -h {file.nc}", to
 print the history to screen. The R scripts are heavily annotated and a
 main header describes the contents and objectives of each script. The R
 scripts have been tested and can be run from within the scripts folder.
 All R scripts reference datasets in the data folder. The following R
 package libraries are required to succesfully run the scripts: ggplot2,
 gridExtra, ncdf4, plyr, raster, vioplot.