Articles | Volume 15, issue 12
https://doi.org/10.5194/gmd-15-4783-2022
© Author(s) 2022. 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-15-4783-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
21 Jun 2022
Development and technical paper |
| 21 Jun 2022
| 21 Jun 2022
Using terrestrial laser scanning to constrain forest ecosystem structure and functions in the Ecosystem Demography model (ED2.2)
Félicien Meunier
CORRESPONDING AUTHOR
CAVElab – Computational and Applied Vegetation Ecology, Department of
Environment, Ghent University, Ghent, Belgium
Sruthi M. Krishna Moorthy
CAVElab – Computational and Applied Vegetation Ecology, Department of
Environment, Ghent University, Ghent, Belgium
Marc Peaucelle
CAVElab – Computational and Applied Vegetation Ecology, Department of
Environment, Ghent University, Ghent, Belgium
now at: INRAE, Université de Bordeaux, UMR 1391 ISPA, 33140
Villenave-d'Ornon, France
Kim Calders
CAVElab – Computational and Applied Vegetation Ecology, Department of
Environment, Ghent University, Ghent, Belgium
Louise Terryn
CAVElab – Computational and Applied Vegetation Ecology, Department of
Environment, Ghent University, Ghent, Belgium
Wim Verbruggen
CAVElab – Computational and Applied Vegetation Ecology, Department of
Environment, Ghent University, Ghent, Belgium
Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, 1350, Denmark
Chang Liu
CAVElab – Computational and Applied Vegetation Ecology, Department of
Environment, Ghent University, Ghent, Belgium
Ninni Saarinen
Department of Forest Sciences, University of Helsinki, Helsinki, Finland
School of Forest Sciences, University of Eastern Finland, Joensuu, Finland
Niall Origo
NPL – Climate and Earth Observation (CEO) group, National Physical
Laboratory, Teddington, UK
Joanne Nightingale
NPL – Climate and Earth Observation (CEO) group, National Physical
Laboratory, Teddington, UK
Mathias Disney
UCL Department of Geography, Gower Street, London, WC1E 6BT, UK
NERC National Centre for Earth Observation (NCEO), UCL Geography,
Gower Street, London, WC1E 6BT, UK
Yadvinder Malhi
Environmental Change Institute, School of Geography and the
Environment, University of Oxford, Oxford, UK
Hans Verbeeck
CAVElab – Computational and Applied Vegetation Ecology, Department of
Environment, Ghent University, Ghent, Belgium
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Cited
6 citations as recorded by crossref.
- Simulating the Impacts of Drought and Warming in Summer and Autumn on the Productivity of Subtropical Coniferous Forests M. Xie et al. 10.3390/f13122147
- Remote Sensing‐Based Forest Modeling Reveals Positive Effects of Functional Diversity on Productivity at Local Spatial Scale F. Schneider et al. 10.1029/2023JG007421
- Tree parameter extraction method based on new remote sensing technology and terrestrial laser scanning technology A. Wang et al. 10.1016/j.bdr.2024.100460
- Low Cost Automatic Reconstruction of Tree Structure by AdQSM with Terrestrial Close-Range Photogrammetry Y. Dong et al. 10.3390/f12081020
- Using terrestrial laser scanning to constrain forest ecosystem structure and functions in the Ecosystem Demography model (ED2.2) F. Meunier et al. 10.5194/gmd-15-4783-2022
- Predicting mangrove forest dynamics across a soil salinity gradient using an individual-based vegetation model linked with plant hydraulics M. Yoshikai et al. 10.5194/bg-19-1813-2022
3 citations as recorded by crossref.
- Simulating the Impacts of Drought and Warming in Summer and Autumn on the Productivity of Subtropical Coniferous Forests M. Xie et al. 10.3390/f13122147
- Remote Sensing‐Based Forest Modeling Reveals Positive Effects of Functional Diversity on Productivity at Local Spatial Scale F. Schneider et al. 10.1029/2023JG007421
- Tree parameter extraction method based on new remote sensing technology and terrestrial laser scanning technology A. Wang et al. 10.1016/j.bdr.2024.100460
3 citations as recorded by crossref.
- Low Cost Automatic Reconstruction of Tree Structure by AdQSM with Terrestrial Close-Range Photogrammetry Y. Dong et al. 10.3390/f12081020
- Using terrestrial laser scanning to constrain forest ecosystem structure and functions in the Ecosystem Demography model (ED2.2) F. Meunier et al. 10.5194/gmd-15-4783-2022
- Predicting mangrove forest dynamics across a soil salinity gradient using an individual-based vegetation model linked with plant hydraulics M. Yoshikai et al. 10.5194/bg-19-1813-2022
Latest update: 23 Nov 2024
Short summary
We integrated state-of-the-art observations of the structure of the vegetation in a temperate forest to constrain a vegetation model that aims to reproduce such an ecosystem in silico. We showed that the use of this information helps to constrain the model structure, its critical parameters, as well as its initial state. This research confirms the critical importance of the representation of the vegetation structure in vegetation models and proposes a method to overcome this challenge.
We integrated state-of-the-art observations of the structure of the vegetation in a temperate...
