The Arctic Plant Aboveground Biomass Synthesis Dataset

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  • Logan T. Berner
  • Kathleen M. Orndahl
  • Melissa Rose
  • Mikkel Tamstorf
  • Marie F. Arndal
  • Heather D. Alexander
  • Elyn R. Humphreys
  • Michael M. Loranty
  • Sarah M. Ludwig
  • Johanna Nyman
  • Sari Juutinen
  • Mika Aurela
  • Konsta Happonen
  • Juha Mikola
  • Michelle C. Mack
  • Mathew R. Vankoughnett
  • Colleen M. Iversen
  • Verity G. Salmon
  • Dedi Yang
  • Jitendra Kumar
  • Paul Grogan
  • Ryan K. Danby
  • Neal A. Scott
  • Johan Olofsson
  • Matthias B. Siewert
  • Lucas Deschamps
  • Esther Lévesque
  • Vincent Maire
  • Amélie Morneault
  • Gilles Gauthier
  • Charles Gignac
  • Stéphane Boudreau
  • Anna Gaspard
  • Alexander Kholodov
  • M. Syndonia Bret-Harte
  • Heather E. Greaves
  • Donald Walker
  • Fiona M. Gregory
  • Timo Kumpula
  • Miguel Villoslada
  • Henni Ylänne
  • Miska Luoto
  • Tarmo Virtanen
  • Bruce C. Forbes
  • Norbert Hölzel
  • Howard Epstein
  • Ramona J. Heim
  • Andrew Bunn
  • Robert M. Holmes
  • Jacqueline K.Y. Hung
  • Susan M. Natali
  • Anna Maria Virkkala
  • Scott J. Goetz

Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m−2) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.

Original languageEnglish
Article number305
JournalScientific Data
Volume11
Issue number1
Number of pages13
ISSN2052-4463
DOIs
Publication statusPublished - 2024

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© The Author(s) 2024.

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