Articles | Volume 12, issue 10
https://doi.org/10.5194/gmd-12-4347-2019
© Author(s) 2019. 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-12-4347-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| Highlight paper
| 
14 Oct 2019
Model evaluation paper | Highlight paper |
| 14 Oct 2019
| 14 Oct 2019
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America
Harvard University, Cambridge, MA, USA
Embrapa Agricultural Informatics, Campinas, SP, Brazil
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Ryan G. Knox
Massachusetts Institute of Technology, Cambridge, MA, USA
Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Naomi M. Levine
University of Southern California, Los Angeles, CA, USA
Abigail L. S. Swann
University of Washington, Seattle, WA, USA
David M. Medvigy
University of Notre Dame, Notre Dame, IN, USA
Michael C. Dietze
Boston University, Boston, MA, USA
Yeonjoo Kim
Department of Civil and Environmental Engineering, Yonsei University, Seoul, Republic of Korea
Hohai University, Nanjing, Jiangsu, China
Damien Bonal
INRA, UMR 1137 EEF, Champenoux, France
Benoit Burban
INRA, UMR 0745 EcoFoG, Campus Agronomique, Kourou, France
Plínio B. Camargo
University of São Paulo, Piracicaba, SP, Brazil
Matthew N. Hayek
Harvard University, Cambridge, MA, USA
New York University, New York, NY, USA
Scott R. Saleska
University of Arizona, Tucson, AZ, USA
Rodrigo da Silva
Federal University of Western Pará, Santarém, PA, Brazil
Rafael L. Bras
Georgia Institute of Technology, Atlanta, GA, USA
Steven C. Wofsy
Harvard University, Cambridge, MA, USA
Paul R. Moorcroft
Harvard University, Cambridge, MA, USA
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- Mapping tropical forest functional variation at satellite remote sensing resolutions depends on key traits E. Ordway et al. 10.1038/s43247-022-00564-w
- Unraveling the relative role of light and water competition between lianas and trees in tropical forests: A vegetation model analysis F. Meunier et al. 10.1111/1365-2745.13540
- Overlooked branch turnover creates a widespread bias in forest carbon accounting H. Lim et al. 10.1073/pnas.2401035121
- The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0 J. Zhang et al. 10.5194/gmd-15-5107-2022
- Tropical dry forest response to nutrient fertilization: a model validation and sensitivity analysis S. Li et al. 10.5194/bg-21-455-2024
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- Lianas Significantly Reduce Aboveground and Belowground Carbon Storage: A Virtual Removal Experiment F. Meunier et al. 10.3389/ffgc.2021.663291
- Patterns and mechanisms of spatial variation in tropical forest productivity, woody residence time, and biomass H. Muller‐Landau et al. 10.1111/nph.17084
- Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests M. Longo et al. 10.1029/2020JG005677
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- Intra-annual variation in microclimatic conditions in relation to vegetation type and structure in two tropical dry forests undergoing secondary succession N. Schwartz et al. 10.1016/j.foreco.2022.120132
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- Preserving isohydricity: vertical environmental variability explains Amazon forest water-use strategies D. Penha et al. 10.1093/treephys/tpae088
- Understanding Tree Mortality Patterns: A Comprehensive Review of Remote Sensing and Meteorological Ground-Based Studies F. Eliades et al. 10.3390/f15081357
- Allometric constraints and competition enable the simulation of size structure and carbon fluxes in a dynamic vegetation model of tropical forests (LM3PPA‐TV) I. Martínez Cano et al. 10.1111/gcb.15188
- Understanding water and energy fluxes in the Amazonia: Lessons from an observation‐model intercomparison N. Restrepo‐Coupe et al. 10.1111/gcb.15555
- 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
- Quantitative evaluation method of species diversity index in beach area of coastal tourism characteristic town Z. Liu et al. 10.1007/s42965-022-00261-x
- Future Hurricanes Will Increase Palm Abundance and Decrease Aboveground Biomass in a Tropical Forest J. Zhang et al. 10.1029/2022GL100090
- Drivers of forest productivity in two regions of the United States: Relative impacts of management and environmental variables H. Karimi et al. 10.1016/j.jenvman.2025.124040
- Remote Sensing‐Based Forest Modeling Reveals Positive Effects of Functional Diversity on Productivity at Local Spatial Scale F. Schneider et al. 10.1029/2023JG007421
- Understanding the effect of fire on vegetation composition and gross primary production in a semi-arid shrubland ecosystem using the Ecosystem Demography (EDv2.2) model K. Pandit et al. 10.5194/bg-18-2027-2021
- A transiting temperate-subtropical mixed forest: carbon cycle projection and uncertainty J. Kim et al. 10.1088/1748-9326/ac87c0
- Robust Ecosystem Demography (RED version 1.0): a parsimonious approach to modelling vegetation dynamics in Earth system models A. Argles et al. 10.5194/gmd-13-4067-2020
29 citations as recorded by crossref.
- Modeling Global Carbon Costs of Plant Nitrogen and Phosphorus Acquisition R. Braghiere et al. 10.1029/2022MS003204
- Mapping tropical forest functional variation at satellite remote sensing resolutions depends on key traits E. Ordway et al. 10.1038/s43247-022-00564-w
- Unraveling the relative role of light and water competition between lianas and trees in tropical forests: A vegetation model analysis F. Meunier et al. 10.1111/1365-2745.13540
- Overlooked branch turnover creates a widespread bias in forest carbon accounting H. Lim et al. 10.1073/pnas.2401035121
- The impact of hurricane disturbances on a tropical forest: implementing a palm plant functional type and hurricane disturbance module in ED2-HuDi V1.0 J. Zhang et al. 10.5194/gmd-15-5107-2022
- Tropical dry forest response to nutrient fertilization: a model validation and sensitivity analysis S. Li et al. 10.5194/bg-21-455-2024
- Landsat near-infrared (NIR) band and ELM-FATES sensitivity to forest disturbances and regrowth in the Central Amazon R. Negrón-Juárez et al. 10.5194/bg-17-6185-2020
- Lianas Significantly Reduce Aboveground and Belowground Carbon Storage: A Virtual Removal Experiment F. Meunier et al. 10.3389/ffgc.2021.663291
- Patterns and mechanisms of spatial variation in tropical forest productivity, woody residence time, and biomass H. Muller‐Landau et al. 10.1111/nph.17084
- Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests M. Longo et al. 10.1029/2020JG005677
- Assessing impacts of selective logging on water, energy, and carbon budgets and ecosystem dynamics in Amazon forests using the Functionally Assembled Terrestrial Ecosystem Simulator M. Huang et al. 10.5194/bg-17-4999-2020
- ForestGEO: Understanding forest diversity and dynamics through a global observatory network S. Davies et al. 10.1016/j.biocon.2020.108907
- The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description M. Longo et al. 10.5194/gmd-12-4309-2019
- Impacts of climate change and deforestation on hydropower planning in the Brazilian Amazon M. Arias et al. 10.1038/s41893-020-0492-y
- Degradation and deforestation increase the sensitivity of the Amazon Forest to climate extremes M. Longo et al. 10.1088/1748-9326/adc58c
- Intra-annual variation in microclimatic conditions in relation to vegetation type and structure in two tropical dry forests undergoing secondary succession N. Schwartz et al. 10.1016/j.foreco.2022.120132
- Application of Big Data Analysis in Cost Control of Marine Fishery Breeding Y. Gu & W. Pan 10.1155/2022/6827469
- Preserving isohydricity: vertical environmental variability explains Amazon forest water-use strategies D. Penha et al. 10.1093/treephys/tpae088
- Understanding Tree Mortality Patterns: A Comprehensive Review of Remote Sensing and Meteorological Ground-Based Studies F. Eliades et al. 10.3390/f15081357
- Allometric constraints and competition enable the simulation of size structure and carbon fluxes in a dynamic vegetation model of tropical forests (LM3PPA‐TV) I. Martínez Cano et al. 10.1111/gcb.15188
- Understanding water and energy fluxes in the Amazonia: Lessons from an observation‐model intercomparison N. Restrepo‐Coupe et al. 10.1111/gcb.15555
- 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
- Quantitative evaluation method of species diversity index in beach area of coastal tourism characteristic town Z. Liu et al. 10.1007/s42965-022-00261-x
- Future Hurricanes Will Increase Palm Abundance and Decrease Aboveground Biomass in a Tropical Forest J. Zhang et al. 10.1029/2022GL100090
- Drivers of forest productivity in two regions of the United States: Relative impacts of management and environmental variables H. Karimi et al. 10.1016/j.jenvman.2025.124040
- Remote Sensing‐Based Forest Modeling Reveals Positive Effects of Functional Diversity on Productivity at Local Spatial Scale F. Schneider et al. 10.1029/2023JG007421
- Understanding the effect of fire on vegetation composition and gross primary production in a semi-arid shrubland ecosystem using the Ecosystem Demography (EDv2.2) model K. Pandit et al. 10.5194/bg-18-2027-2021
- A transiting temperate-subtropical mixed forest: carbon cycle projection and uncertainty J. Kim et al. 10.1088/1748-9326/ac87c0
- Robust Ecosystem Demography (RED version 1.0): a parsimonious approach to modelling vegetation dynamics in Earth system models A. Argles et al. 10.5194/gmd-13-4067-2020
Latest update: 11 Jul 2025
Short summary
The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants and ground and the air, and the life cycle of plants in different climates. To test if our calculations were reasonable, we compared our results with field and satellite measurements. Our model predicts well the extent of the Amazon forest, how much light forests absorb, and how much water forests release to the air. However, it must improve the tree growth rates and how fast dead plants decompose.
The Ecosystem Demography model calculates the fluxes of heat, water, and carbon between plants...
