Abstract
Arctic warming is altering vegetation and carbon dynamics with global implications, yet Earth System Model (ESM) predictions in the Arctic remain highly uncertain, in part due to historically limited data for model parameterization and validation. As such, ESMs typically represent Arctic ecosystems in an oversimplified manner. Recently, nine plant functional types (PFTs) designed to realistically represent tundra vegetation were integrated into the Energy Exascale Earth System Model (E3SM) Land Model (ELM) and parameterized using plot-scale observations from a single site. Additional evaluation was needed to determine their transferability across the Arctic. Here, we evaluated whether refined representation of tundra vegetation improved model accuracy by conducting spatially explicit 100 × 100 m resolution ELM simulations on Alaska's Seward Peninsula. Simulations with the default two-PFT configuration and with the nine Arctic-specific PFTs were benchmarked against observations of net ecosystem exchange, gross primary production, and aboveground biomass from multiple data streams including an eddy covariance flux tower, flux chambers, and aircraft and unoccupied aerial system hyperspectral remote sensing. Evaluation revealed that Arctic-specific PFT simulations produced more realistic landscape-level carbon exchanges, and better captured observed heterogeneity in biomass and productivity, explaining 60%–70% of spatial variance (R2 = 0.6–0.7) compared to just 12%–18% (R2 = 0.12–0.18) with the default configuration. However, the refined model failed to reproduce observed aboveground biomass for highly productive alder-willow communities, requiring further evaluation of carbon allocation parameterizations for tall shrubs that are increasingly expanding across tundra landscapes. Our results demonstrate that enhanced representation of vegetation heterogeneity boosts predictive understanding of tundra carbon dynamics, facilitating regional to pan-Arctic model and remote-sensing scaling.
| Original language | English |
|---|---|
| Article number | e2025JG009039 |
| Journal | Journal of Geophysical Research: Biogeosciences |
| Volume | 130 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 2025 |
Funding
We gratefully acknowledge the Council Native Corporation for their permission to conduct research on their lands, allowing us to deepen scientific understanding of Arctic ecosystems. We'd like to acknowledge Bob Busey and Jessica Cherry for their work maintaining the Council weather station and sharing the data they've collected, Terri Velliquette for data archival assistance, Amy Breen for collection of field data and translation of vegetation species into ELM PFTs, and Michele Thornton, Shih-Chieh Kao, and others at Oak Ridge National Laboratory for their work compiling and maintaining model forcing data. This work was supported by the Next Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project, funded by the Office of Biological and Environmental Research in the US Department of Energy's Office of Science. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. Notice: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). We gratefully acknowledge the Council Native Corporation for their permission to conduct research on their lands, allowing us to deepen scientific understanding of Arctic ecosystems. We'd like to acknowledge Bob Busey and Jessica Cherry for their work maintaining the Council weather station and sharing the data they've collected, Terri Velliquette for data archival assistance, Amy Breen for collection of field data and translation of vegetation species into ELM PFTs, and Michele Thornton, Shih‐Chieh Kao, and others at Oak Ridge National Laboratory for their work compiling and maintaining model forcing data. This work was supported by the Next Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project, funded by the Office of Biological and Environmental Research in the US Department of Energy's Office of Science. Oak Ridge National Laboratory is managed by UT‐Battelle, LLC, for the US Department of Energy under contract DE‐AC05‐00OR22725. This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE‐AC05‐00OR22725. This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE‐AC05‐00OR22725. Notice: This manuscript has been authored by UT‐Battelle, LLC, under contract DE‐AC05‐00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid‐up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe‐public‐access‐plan ).
Keywords
- Arctic carbon dynamics
- Arctic tundra vegetation
- land surface modeling
- model evaluation
- vegetation heterogeneity
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