期刊
BIODIVERSITY DATA JOURNAL
卷 9, 期 -, 页码 -出版社
PENSOFT PUBLISHERS
DOI: 10.3897/BDJ.9.e69560
关键词
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资金
- Consejo Nacional de Ciencia y Tecnologia (CONACyT) [239388]
- German Academic Exchange Service (DAAD) [91599355]
- Dorothea Schlozer Postdoctoral Programme of the Georg-August-Universitat
- Open Access Grant Program of the German Research Foundation (DFG)
- Open Access Publication Fund of the University of Gottingen
BIOVERA-Tree is a newly established database containing comprehensive data on tree diversity, community composition, forest structure, and functional traits collected in Veracruz State, Mexico. This database contributes to the understanding of how forest-use intensity and elevation interactively affect tree diversity, community composition, and functional traits in tropical forests.
Background Here, we describe BIOVERA-Tree, a database on tree diversity, community composition, forest structure and functional traits collected in 120 forest plots, distributed along an extensive elevational gradient in Veracruz State, Mexico. BIOVERA-Tree includes information on forest structure from three levels of forest-use intensity, namely old-growth, degraded and secondary forest, replicated across eight elevations from sea-level to near the tree line at 3500 m and on size and location of 4549 tree individuals with a diameter at breast height >= 5 cm belonging to 216 species, 154 genera and 80 families. We also report measurements of eight functional traits, namely wood density for 143 species, maximum height for 216 species and leaf traits including: specific leaf area, lamina density, leaf thickness, chlorophyll content and leaf area for 148 species and leaf dry matter content for 145 species. New information BIOVERA-Tree is a new database comprising data collected in a rigorous sampling design along forest-use intensity and elevational gradients, contributing to our understanding of how interactive effects of forest-use intensity and elevation affect tree diversity, community composition and functional traits in tropical forests.
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