Articles | Volume 18, issue 12
https://doi.org/10.5194/gmd-18-3857-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-3857-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Estimation of above- and below-ground ecosystem parameters for DVM-DOS-TEM v0.7.0 using MADS v1.7.3
Elchin E. Jafarov
CORRESPONDING AUTHOR
Woodwell Climate Research Center, Falmouth, MA, USA
Hélène Genet
Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK, USA
Velimir V. Vesselinov
EnviTrace LLC, Santa Fe, NM, USA
Valeria Briones
Woodwell Climate Research Center, Falmouth, MA, USA
Aiza Kabeer
Program in Applied Mathematics, University of Arizona, Tucson, AZ, USA
Andrew L. Mullen
Woodwell Climate Research Center, Falmouth, MA, USA
Benjamin Maglio
Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK, USA
Tobey Carman
Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK, USA
Ruth Rutter
Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK, USA
Joy Clein
Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK, USA
Chu-Chun Chang
Woodwell Climate Research Center, Falmouth, MA, USA
Dogukan Teber
Woodwell Climate Research Center, Falmouth, MA, USA
Trevor Smith
Woodwell Climate Research Center, Falmouth, MA, USA
Joshua M. Rady
Woodwell Climate Research Center, Falmouth, MA, USA
Christina Schädel
Woodwell Climate Research Center, Falmouth, MA, USA
Jennifer D. Watts
Woodwell Climate Research Center, Falmouth, MA, USA
Brendan M. Rogers
Woodwell Climate Research Center, Falmouth, MA, USA
Susan M. Natali
Woodwell Climate Research Center, Falmouth, MA, USA
Data sets
Estimation of above- and below-ground ecosystem parameters for the DVM-DOS-TEM v0.7.0 model using MADS v1.7.3 (model archive) Elchin E. Jafarov et al. https://doi.org/10.5281/zenodo.14940535
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Short summary
This study improves how we tune ecosystem models to reflect carbon and nitrogen storage in Arctic soils. By comparing model outputs with data from a black spruce forest in Alaska, we developed a clearer, more efficient method of matching observations. This is a key step towards understanding how Arctic ecosystems may respond to warming and release carbon, helping make future climate predictions more reliable.
This study improves how we tune ecosystem models to reflect carbon and nitrogen storage in...