Non-growing Season Plant Nutrient Uptake Controls Arctic Tundra Vegetation Composition: Modeling Archive

DOI: https://doi.org/10.5440/1785957
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NGEE Arctic Record ID: NGA263
Data Version: 1.0
Abstract

This Modeling Archive is in support of a NGEE-Arctic publication: Riley et al. (2021) “Non-growing season plant nutrient uptake controls Arctic tundra vegetation composition under future climate”. DOI.

The dataset contains “ecosys” model outputs reported in Riley et al. (2021) that examines the role of non-growing season (NGS) nutrient dynamics on 21st century vegetation composition. The study highlighted the importance of these nutrient dynamics on the emergent plant functional type distributions, focusing on their role in shrub expansion. The study showed that ignoring NGS nutrient dynamics led to a dramatic under-prediction of shrub expansion by year 2100, motivating the need to include these processes in Earth System Models.

Included are modeled net primary production (NPP) and nitrogen (N) uptake for two scenarios: (1) baseline and (2) no NGS N uptake. The output is provided (1) at 25 km resolution across the North American tundra; (2) for years 2012 through 2100; and (3) PFT-specific.

The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.

The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.

Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Authors
William Riley (wjriley@lbl.gov) 0000-0002-4615-2304
Zelalem Mekonnen (zmekonnen@lbl.gov) 0000-0002-2647-0671
Jinyun Tang ()
Qing Zhu ()
Nicholas Bouskill (njbouskill@lbl.gov) 0000-0002-6577-8724
Robert Grant (rgrant@lbl.gov)
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Dataset Citation
William Riley, Zelalem Mekonnen, Jinyun Tang, Qing Zhu, Nicholas Bouskill, Robert Grant. 2022. Non-growing Season Plant Nutrient Uptake Controls Arctic Tundra Vegetation Composition: Modeling Archive. Next Generation Ecosystem Experiments Arctic Data Collection, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, USA. Dataset accessed on [INSERT_DATE] at https://doi.org/10.5440/1785957.
Dates
2012-01-01 - 2100-12-31
Geographic Location
Alaska
North71.4
South50.9
East-129.3
West-180.0
Place Keywords:
Utqiagvik, Alaska | Seward Peninsula, Alaska | Barrow Environmental Observatory (BEO) | North Slope, Alaska
Subject Keywords:
ecosys model predictions |
GCMD Keywords
EARTH SCIENCE > LAND SURFACE > SOILS
EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > PLANTS
EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS
Methodology
Model Ecosys is an hourly time step model with multiple canopy and soil layers. The model represents fully coupled transformations of soil carbon, nitrogen, and phosphorus through microbially driven processes. A detailed description of inputs, parameters, and algorithms used in ecosys can be found in Grant (2001). The ecosys model source code can be requested at https://ecosys.ualberta.ca/ or contact Robert Grant: rgrant@ualberta.ca. Grant, R.F., 2001. A review of the Canadian ecosystem model ecosys. in Modeling Carbon and Nitrogen Dynamics for Soil Management: pp. 173-264, CRC Press, Boca Raton, FL. The model source code can be requested at https://ecosys.ualberta.ca/. A brief model description most relevant to these data is included in Riley et al. (2021) and Supplementary Information. Input Data Files • Soil: Unified North America Soil Map (Liu et al., 2013) and Circumpolar Soil Carbon Database (NCSCD) (Hugelius et al., 2013) • Atmospheric CO2: RCP8.5 greenhouse gas concentrations (Meinshausen et al., 2011) • Climate: NARR (Wei et al., 2014) and average of 15 CMIP5 models (Wei et al., 2014) Parameters Model algorithms and parameters used are documented in the Supplementary Information of Riley et al. (2021). Initializations Details of model initialization and simulation protocol are documented in the Methods section of the related publication (Riley et al., 2021). Output Details of the model outputs are documented in the Methods and Results Sections of the related publication (Riley et al., 2021). The provided .nc files are direct model outputs of Net Primary Production (NPP) and plant Nitrogen (N) uptake at 25 km resolution across the North American tundra for years 2012 through 2100 and are PFT-specific (P1 = evergreen shrub; p2 = graminoid; p3 = deciduous shrub; p4 = lichen; p5 = moss) Configurations A model configuration description relevant to the data provided here is given in Riley et al. (2021) and Supplementary Information. The model source code can be requested at https://ecosys.ualberta.ca/ or contact Robert Grant: rgrant@ualberta.ca. Post-processing/Distillation and Analysis Details of the model analysis are given in the Methods section of Riley et al. (2021). There was no special processing of the model output for publication. Plots of NPP and N uptake are spatial averages across the modeled domain.
Related References
Riley, W. J., Z. A. Mekonnen, J. Y. Tang, Q. Zhu, N. J. Bouskill, and R. F. Grant. 2021. Non-growing season plant nutrient uptake controls Arctic tundra vegetation composition under future climate. Environmental Research Letters. http://dx.doi.org/10.1088/1748-9326/ac0e63
Related Identifiers
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Metadata Contact
Contact information for the individual or organization that is knowledgeable about the data.
Person: William Riley
Organization: Lawrence Berkeley National Laboratory
Email: wjriley@lbl.gov
Point of Contact
Contact information for the individual or organization that is knowledgeable about the data.
Person: William Riley
Organization: Lawrence Berkeley National Laboratory
Email: wjriley@lbl.gov
Dataset Usage Rights
Public Datasets

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Distribution Point of Contact
Contact: Data Center Support
Organization: Next-Generation Ecosystem Experiments (NGEE) Arctic Project, Oak Ridge National Laboratory
Email: support@ngee-arctic.ornl.gov