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Peer-reviewedCC BY 4.0Royal Society Open Science

Terrestrial laser scanning-based aboveground biomass estimation across forest compartments in Patagonian forests: a workflow integrating freely available tools

  • Romina Gonzalez Musso1,2,3
  • Atticus Stovall4
  • Juan H. Gowda5
  • Alberto Rabino2
  • Thomas Kitzberger5,6
6 affiliations
  1. 1INIBIOMA, CONICET 1 , San Martín de los Andes, Neuquén, Argentina
  2. 2Universidad Nacional del Comahue, Centro Regional Universitario 2 San Martín de los Andes, Neuquén, Argentina
  3. 3Escuela para Graduados, Universidad de Buenos Aires, Facultad de Agronomía 3 , Buenos Aires, Argentina
  4. 4ESSIC, University of Maryland 4 , College Park, MD, USA
  5. 5INIBIOMA, CONICET 5 , San Carlos de Bariloche, Río Negro, Argentina
  6. 6Universidad Nacional del Comahue, Centro Regional Universitario Bariloche 6 , Río Negro, Argentina
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Abstract

Forests cover nearly 30% of Earth's land surface and store about 80% of plant biomass, playing a key role in the carbon cycle, yet documented and reproducible workflows for terrestrial laser scanning-based aboveground biomass (AGB) estimation in temperate forests of the Southern Hemisphere remain scarce. We documented and validated a reproducible workflow integrating existing freely available tools, combining voxel-based methods and quantitative structure modelling, for estimating AGB across forest compartments (stems, branches, foliage and understory) in Patagonian temperate forests dominated by Nothofagus. TLS data were collected at tree and stand levels across three post-fire successional stages, and six trees were destructively sampled for validation. TLS-derived estimates showed strong agreement with field data, with concordance correlation coefficients (CCCs) of 0.96 for diameter, 0.83 for height, 0.99 for stem volume and 0.94 for total volume, and relative root mean square error (RMSE) values of 7.3–17.0%. Total AGB showed a CCC of 0.93 and relative RMSE of 18.7%. Voxel-based estimates enabled biomass partitioning of fine vegetation components, and a sensitivity analysis of voxel size provides empirical guidance for future applications. The documented workflow and associated dataset provide a reproducible reference for TLS-based biomass estimation in structurally complex temperate forests of Patagonia.

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Cite

BibTeXRIS
BibTeX
@article{musso2026terrestrial,
  title = {{Terrestrial laser scanning-based aboveground biomass estimation across forest compartments in Patagonian forests: a workflow integrating freely available tools}},
  author = {Romina Gonzalez Musso and Atticus Stovall and Juan H. Gowda and Alberto Rabino and Thomas Kitzberger},
  journal = {Royal Society Open Science},
  year = {2026},
  month = sep,
  doi = {10.1098/rsos.261311},
  url = {https://royalsocietypublishing.org/rsos/article/13/9/261311/483415/Terrestrial-laser-scanning-based-aboveground},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Terrestrial laser scanning-based aboveground biomass estimation across forest compartments in Patagonian forests: a workflow integrating freely available tools
AU  - Romina Gonzalez Musso
AU  - Atticus Stovall
AU  - Juan H. Gowda
AU  - Alberto Rabino
AU  - Thomas Kitzberger
PY  - 2026
DA  - 2026/09/30
JO  - Royal Society Open Science
DO  - 10.1098/rsos.261311
UR  - https://royalsocietypublishing.org/rsos/article/13/9/261311/483415/Terrestrial-laser-scanning-based-aboveground
AB  - Forests cover nearly 30% of Earth's land surface and store about 80% of plant biomass, playing a key role in the carbon cycle, yet documented and reproducible workflows for terrestrial laser scanning-based aboveground biomass (AGB) estimation in temperate forests of the Southern Hemisphere remain scarce. We documented and validated a reproducible workflow integrating existing freely available tools, combining voxel-based methods and quantitative structure modelling, for estimating AGB across forest compartments (stems, branches, foliage and understory) in Patagonian temperate forests dominated by Nothofagus. TLS data were collected at tree and stand levels across three post-fire successional stages, and six trees were destructively sampled for validation. TLS-derived estimates showed strong agreement with field data, with concordance correlation coefficients (CCCs) of 0.96 for diameter, 0.83 for height, 0.99 for stem volume and 0.94 for total volume, and relative root mean square error (RMSE) values of 7.3–17.0%. Total AGB showed a CCC of 0.93 and relative RMSE of 18.7%. Voxel-based estimates enabled biomass partitioning of fine vegetation components, and a sensitivity analysis of voxel size provides empirical guidance for future applications. The documented workflow and associated dataset provide a reproducible reference for TLS-based biomass estimation in structurally complex temperate forests of Patagonia.
SN  - 2054-5703
ER  -