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The Fire and Tree Mortality Database, for empirical modeling of individual tree mortality after fire.
- Source :
- Scientific Data; 6/22/2020, Vol. 7 Issue 1, p1-14, 14p
- Publication Year :
- 2020
-
Abstract
- Wildland fires have a multitude of ecological effects in forests, woodlands, and savannas across the globe. A major focus of past research has been on tree mortality from fire, as trees provide a vast range of biological services. We assembled a database of individual-tree records from prescribed fires and wildfires in the United States. The Fire and Tree Mortality (FTM) database includes records from 164,293 individual trees with records of fire injury (crown scorch, bole char, etc.), tree diameter, and either mortality or top-kill up to ten years post-fire. Data span 142 species and 62 genera, from 409 fires occurring from 1981-2016. Additional variables such as insect attack are included when available. The FTM database can be used to evaluate individual fire-caused mortality models for pre-fire planning and post-fire decision support, to develop improved models, and to explore general patterns of individual fire-induced tree death. The database can also be used to identify knowledge gaps that could be addressed in future research. Measurement(s) plant morphology trait • tree mortality • fire • tree fire injury • wildfire Technology Type(s) digital curation Factor Type(s) year of data collection • geographic location of fire • tree fire injury Sample Characteristic - Organism trees Sample Characteristic - Environment forest ecosystem Sample Characteristic - Location Cascades Region • Blue Mountains • Far Northern Rockies • Sierra Nevada • Piedmont Province • Region of Piedmont • Atlantic and Gulf Coastal Plain Floristic Province • Northern Rocky Mountains Provincial Park Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12369293 [ABSTRACT FROM AUTHOR]
- Subjects :
- TREE mortality
WILDFIRES
DATABASES
TREE injuries
PLANT morphology
Subjects
Details
- Language :
- English
- ISSN :
- 20524463
- Volume :
- 7
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Scientific Data
- Publication Type :
- Academic Journal
- Accession number :
- 143892321
- Full Text :
- https://doi.org/10.1038/s41597-020-0522-7