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Environmentally-dependent wood density influences forest structure and dynamics in a demographic vegetation model

Voss, Anna Kristina LU orcid ; Olin, Stefan LU orcid ; Zhou, Hao LU orcid ; Fonti, Patrick and Eckes-Shephard, Annemarie Hildegard LU orcid (2026) In Quantitative Plant Biology 7.
Abstract
Wood density is a crucial anatomical trait influencing forest carbon storage. However, dynamic global vegetation models (DGVMs) typically assume a fixed species-level wood density, neglecting environment-driven variability. In this proof-of-concept study, we explore the potential impact of dynamic wood density on tree- and forest-level carbon storage by integrating a simple temperature-response function of wood density into the DGVM LPJ-GUESS.
Simulations along a temperature gradient show that incorporating environmentally-responsive wood density can substantially alter simulated stand structure and carbon stocks. Overall, our model experiments illustrated sites with higher wood density had more but smaller trees which stored less... (More)
Wood density is a crucial anatomical trait influencing forest carbon storage. However, dynamic global vegetation models (DGVMs) typically assume a fixed species-level wood density, neglecting environment-driven variability. In this proof-of-concept study, we explore the potential impact of dynamic wood density on tree- and forest-level carbon storage by integrating a simple temperature-response function of wood density into the DGVM LPJ-GUESS.
Simulations along a temperature gradient show that incorporating environmentally-responsive wood density can substantially alter simulated stand structure and carbon stocks. Overall, our model experiments illustrated sites with higher wood density had more but smaller trees which stored less carbon compared to the standard model. The strongest effects were predicted to appear before canopy closure, where per treecarbon deviated by up to 32%. This exploratory study suggests the need to represent a mechanism for dynamic wood density to better assess ecological feedbacks to forest carbon storage predictions, particularly in young and regenerating forests. (Less)
Please use this url to cite or link to this publication:
author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Quantitative Plant Biology
volume
7
publisher
Cambridge University Press
external identifiers
  • scopus:105030058568
  • pmid:41988098
ISSN
2632-8828
DOI
10.1017/qpb.2026.10038
project
Fundamental controls of wood formation processes on the size and resilience of the future forest carbon sink
language
English
LU publication?
yes
id
f437e9b2-f2a9-4e1a-9e43-60ad4be9a6a0
date added to LUP
2026-02-28 16:50:55
date last changed
2026-07-20 16:37:06
@article{f437e9b2-f2a9-4e1a-9e43-60ad4be9a6a0,
  abstract     = {{Wood density is a crucial anatomical trait influencing forest carbon storage. However, dynamic global vegetation models (DGVMs) typically assume a fixed species-level wood density, neglecting environment-driven variability. In this proof-of-concept study, we explore the potential impact of dynamic wood density on tree- and forest-level carbon storage by integrating a simple temperature-response function of wood density into the DGVM LPJ-GUESS.<br/>Simulations along a temperature gradient show that incorporating environmentally-responsive wood density can substantially alter simulated stand structure and carbon stocks. Overall, our model experiments illustrated sites with higher wood density had more but smaller trees which stored less carbon compared to the standard model. The strongest effects were predicted to appear before canopy closure, where per treecarbon deviated by up to 32%. This exploratory study suggests the need to represent a mechanism for dynamic wood density to better assess ecological feedbacks to forest carbon storage predictions, particularly in young and regenerating forests.}},
  author       = {{Voss, Anna Kristina and Olin, Stefan and Zhou, Hao and Fonti, Patrick and Eckes-Shephard, Annemarie Hildegard}},
  issn         = {{2632-8828}},
  language     = {{eng}},
  publisher    = {{Cambridge University Press}},
  series       = {{Quantitative Plant Biology}},
  title        = {{Environmentally-dependent wood density influences forest structure and dynamics in a demographic vegetation model}},
  url          = {{http://dx.doi.org/10.1017/qpb.2026.10038}},
  doi          = {{10.1017/qpb.2026.10038}},
  volume       = {{7}},
  year         = {{2026}},
}