Articles | Volume 18, issue 24
https://doi.org/10.5194/bg-18-6517-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-18-6517-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Dec 2021
Research article |
| 20 Dec 2021
| 20 Dec 2021
Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50 ha plot
Raquel Fernandes Araujo
CORRESPONDING AUTHOR
Forest Global Earth Observatory (Center for Tropical Forest Science),
Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Balboa, Ancón,
Panama
Samuel Grubinger
Department of Forest Resources Management, University of British
Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
Carlos Henrique Souza Celes
Forest Global Earth Observatory (Center for Tropical Forest Science),
Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Balboa, Ancón,
Panama
Robinson I. Negrón-Juárez
Climate Sciences Department, Lawrence Berkeley National Laboratory, 1
Cyclotron Road, Berkeley, CA 94720, USA
Milton Garcia
Forest Global Earth Observatory (Center for Tropical Forest Science),
Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Balboa, Ancón,
Panama
Jonathan P. Dandois
Facilities Information Technology, Johns Hopkins Facilities and Real Estate, Johns Hopkins University, 3910 Keswick Rd., Suite N3100, Baltimore, MD 21211, USA
Helene C. Muller-Landau
Forest Global Earth Observatory (Center for Tropical Forest Science),
Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Balboa, Ancón,
Panama
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Cited
16 citations as recorded by crossref.
- Recording Rainfall Intensity: Has an Optimum Method Been Found? D. Dunkerley 10.3390/w15193383
- Species-specific machine learning models for UAV-based forest health monitoring: Revealing the importance of the BNDVI S. Ecke et al. 10.1016/j.jag.2024.104257
- Major axes of variation in tree demography across global forests M. Leite et al. 10.1111/ecog.07187
- Damage to living trees contributes to almost half of the biomass losses in tropical forests D. Zuleta et al. 10.1111/gcb.16687
- Exploring forest changes in an Ips typographus L. outbreak area: insights from multi-temporal multispectral UAS remote sensing M. Östersund et al. 10.1007/s10342-024-01734-5
- Tree crown damage and its effects on forest carbon cycling in a tropical forest J. Needham et al. 10.1111/gcb.16318
- UAV-Based Forest Health Monitoring: A Systematic Review S. Ecke et al. 10.3390/rs14133205
- Tropical cyclones moving into boreal forests: Relationships between disturbance areas and environmental drivers K. Korznikov et al. 10.1016/j.scitotenv.2022.156931
- Towards the fully automated monitoring of ecological communities M. Besson et al. 10.1111/ele.14123
- Accurate delineation of individual tree crowns in tropical forests from aerial RGB imagery using Mask R‐CNN J. Ball et al. 10.1002/rse2.332
- Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50 ha plot R. Araujo et al. 10.5194/bg-18-6517-2021
- Cost-effective and accurate monitoring of flowering across multiple tropical tree species over two years with a time series of high-resolution drone imagery and deep learning C. Lee et al. 10.1016/j.isprsjprs.2023.05.022
- Soils and topography control natural disturbance rates and thereby forest structure in a lowland tropical landscape K. Cushman et al. 10.1111/ele.13978
- Canopy gaps and associated losses of biomass – combining UAV imagery and field data in a central Amazon forest A. Simonetti et al. 10.5194/bg-20-3651-2023
- Canopy gaps and associated losses of biomass – combining UAV imagery and field data in a central Amazon forest A. Simonetti et al. 10.5194/bg-20-3651-2023
- Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50 ha plot R. Araujo et al. 10.5194/bg-18-6517-2021
14 citations as recorded by crossref.
- Recording Rainfall Intensity: Has an Optimum Method Been Found? D. Dunkerley 10.3390/w15193383
- Species-specific machine learning models for UAV-based forest health monitoring: Revealing the importance of the BNDVI S. Ecke et al. 10.1016/j.jag.2024.104257
- Major axes of variation in tree demography across global forests M. Leite et al. 10.1111/ecog.07187
- Damage to living trees contributes to almost half of the biomass losses in tropical forests D. Zuleta et al. 10.1111/gcb.16687
- Exploring forest changes in an Ips typographus L. outbreak area: insights from multi-temporal multispectral UAS remote sensing M. Östersund et al. 10.1007/s10342-024-01734-5
- Tree crown damage and its effects on forest carbon cycling in a tropical forest J. Needham et al. 10.1111/gcb.16318
- UAV-Based Forest Health Monitoring: A Systematic Review S. Ecke et al. 10.3390/rs14133205
- Tropical cyclones moving into boreal forests: Relationships between disturbance areas and environmental drivers K. Korznikov et al. 10.1016/j.scitotenv.2022.156931
- Towards the fully automated monitoring of ecological communities M. Besson et al. 10.1111/ele.14123
- Accurate delineation of individual tree crowns in tropical forests from aerial RGB imagery using Mask R‐CNN J. Ball et al. 10.1002/rse2.332
- Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50 ha plot R. Araujo et al. 10.5194/bg-18-6517-2021
- Cost-effective and accurate monitoring of flowering across multiple tropical tree species over two years with a time series of high-resolution drone imagery and deep learning C. Lee et al. 10.1016/j.isprsjprs.2023.05.022
- Soils and topography control natural disturbance rates and thereby forest structure in a lowland tropical landscape K. Cushman et al. 10.1111/ele.13978
- Canopy gaps and associated losses of biomass – combining UAV imagery and field data in a central Amazon forest A. Simonetti et al. 10.5194/bg-20-3651-2023
2 citations as recorded by crossref.
- Canopy gaps and associated losses of biomass – combining UAV imagery and field data in a central Amazon forest A. Simonetti et al. 10.5194/bg-20-3651-2023
- Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50 ha plot R. Araujo et al. 10.5194/bg-18-6517-2021
Latest update: 13 Dec 2024
Short summary
Our study contributed to improving the understanding of temporal variation and climate correlates of canopy disturbances mainly caused by treefalls and branchfalls. We used a unique dataset of 5 years of approximately monthly drone-acquired RGB (red–green–blue) imagery for 50 ha of mature tropical forest on Barro Colorado Island, Panama. We found that canopy disturbance rates were highly temporally variable, were higher in the wet season, and were related to extreme rainfall events.
Our study contributed to improving the understanding of temporal variation and climate...
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