U.S. Department of EnergyOffice of Scientific and Technical Information
FATES size- and age-dependent mortality simulation outputs, 2019
Abstract
This dataset contains outputs from the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) and accompanies the paper “Needham, J.F., Chambers, J., Fisher, R., Knox, R., and Koven, C. D., Forest responses to simulated elevated CO2 under alternate hypotheses of size- and age-dependent mortality, 2020, Global Change Biology”. Data are unprocessed FATES outputs from size- and age-dependent mortality simulations which were run to test the effect of different mechanisms of mortality on forest response to elevated CO2 (eCO2). Specifically, this data package contains single plant functional type (PFT) simulations in which mortality is either a constant background rate, size-dependent or age-dependent. In each case, a simulation with constant woody NPP is compared to a simulation in which woody NPP increases by 25% to simulate the growth response of forests to eCO2. Ensemble simulations with size- and age-dependent mortality and two PFTs test the impact of different demographic rates on coexistence and the forest response to eCO2. Finally, the dataset includes simulations testing the sensitivity of results to allometry and to the recruitment scheme.
- Authors:
-
- Lawrence Berkeley National Laboratory; Lawrence Berkeley National Lab
- National Ctr for Atmospheric Res
- LBNL
- Lawrence Berkeley National Lab
- Publication Date:
- Other Number(s):
- NGT0150
- DOE Contract Number:
- AC02-05CH11231
- Research Org.:
- Next-Generation Ecosystem Experiments Tropics; Lawrence Berkeley National Laboratory
- Sponsoring Org.:
- U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, National Center for Atmospheric Research, University of California
- Subject:
- 54 ENVIRONMENTAL SCIENCES
- OSTI Identifier:
- 1633773
- DOI:
- https://doi.org/10.15486/ngt/1633773
Citation Formats
Needham, Jessica, Fisher, Rosie, Chambers, Jeff, Knox, Ryan, and Koven, Charlie. FATES size- and age-dependent mortality simulation outputs, 2019. United States: N. p., 2020.
Web. doi:10.15486/ngt/1633773.
Needham, Jessica, Fisher, Rosie, Chambers, Jeff, Knox, Ryan, & Koven, Charlie. FATES size- and age-dependent mortality simulation outputs, 2019. United States. doi:https://doi.org/10.15486/ngt/1633773
Needham, Jessica, Fisher, Rosie, Chambers, Jeff, Knox, Ryan, and Koven, Charlie. 2020.
"FATES size- and age-dependent mortality simulation outputs, 2019". United States. doi:https://doi.org/10.15486/ngt/1633773. https://www.osti.gov/servlets/purl/1633773. Pub date:Wed Jan 01 04:00:00 UTC 2020
@article{osti_1633773,
title = {FATES size- and age-dependent mortality simulation outputs, 2019},
author = {Needham, Jessica and Fisher, Rosie and Chambers, Jeff and Knox, Ryan and Koven, Charlie},
abstractNote = {This dataset contains outputs from the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) and accompanies the paper “Needham, J.F., Chambers, J., Fisher, R., Knox, R., and Koven, C. D., Forest responses to simulated elevated CO2 under alternate hypotheses of size- and age-dependent mortality, 2020, Global Change Biology”. Data are unprocessed FATES outputs from size- and age-dependent mortality simulations which were run to test the effect of different mechanisms of mortality on forest response to elevated CO2 (eCO2). Specifically, this data package contains single plant functional type (PFT) simulations in which mortality is either a constant background rate, size-dependent or age-dependent. In each case, a simulation with constant woody NPP is compared to a simulation in which woody NPP increases by 25% to simulate the growth response of forests to eCO2. Ensemble simulations with size- and age-dependent mortality and two PFTs test the impact of different demographic rates on coexistence and the forest response to eCO2. Finally, the dataset includes simulations testing the sensitivity of results to allometry and to the recruitment scheme.},
doi = {10.15486/ngt/1633773},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Jan 01 04:00:00 UTC 2020},
month = {Wed Jan 01 04:00:00 UTC 2020}
}