Cite this dataset as
Jackson, T.D. , Bittencourt, P., Coomes, D.A. (2023). Bending strains on the trunks of trees on Barro Colorado Island, Panama, 2022. NERC EDS Environmental Information Data Centre. (Dataset). https://doi.org/10.5285/f03806fa-3596-4119-90c5-70254f39cfc0
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This dataset is available under the terms of the Open Government Licence
Bending strains on the trunks of trees on Barro Colorado Island, Panama, 2022
This data was collected for the purpose of estimating the risk of wind damage to these trees. It could also be used to estimate the fundamental sway frequencies of the trees, and how they change over time, which varies with leaf phenology and tree water content. There are lots of short data gaps due to transmission issues in the forest.
Format
Comma-separated values (CSV)
Spatial information
- Study area
-
- Spatial representation type
- Tabular (text)
- Spatial reference system
- WGS 84 / Pseudo-Mercator
Temporal information
- Temporal extent
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2022-01-01 to 2022-12-31
Provenance & quality
The data was collected from the SD cards and converted from binary format to csv files. The mV measurements were converted to bending strain by multiplying by a fixed calibration coefficient. This 4 Hz bending strain data is provided here.
Related
Correspondence/contact details
Authors
Other contacts
- Rights holder
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University of Cambridge
- Custodian
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NERC EDS Environmental Information Data Centreinfo@eidc.ac.uk
- Publisher
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NERC EDS Environmental Information Data Centreinfo@eidc.ac.uk
Additional metadata
More information about these numbers
Get the data
By accessing or using this dataset, you agree to the terms of the relevant licence agreement(s). You will ensure that this dataset is cited in any publication that describes research in which the data have been used.
This dataset is available under the terms of the Open Government Licence
CITE AS: Jackson, T.D. ; Bittencourt, P.; Coomes, D.A. (2023). Bending strains on the trunks of trees on Barro Colorado Island, Panama, 2022. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/f03806fa-3596-4119-90c5-70254f39cfc0