Abstract
Plant traits are fundamental for understanding and predicting vegetation responses to global changes, and they provide a promising basis towards a more quantitative and predictive approach to ecology. As a consequence, information on plant traits is rapidly accumulating, and there is a growing need for efficient database tools that enable the assembly and synthesis of trait data. Plant traits are highly heterogeneous, exhibit a low degree of standardization and are linked and interdependent at various levels of biological organization: tissue, organ, plant and population. Therefore, they often require ancillary data for interpretation, including descriptors of the biotic and abiotic environment, methods and taxonomic relationships. We introduce a generic database structure that is tailored to accommodate plant trait complexity and is consistent with current theoretical approaches to characterize the structure of observational data. The over-arching utility of the proposed database structure is illustrated based on two independent plant trait database projects. The generic database structure proposed here is meant to serve as a flexible blueprint for future plant trait databases, improving data discovery, and ensuring compatibility among them.
Original language | English (US) |
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Pages (from-to) | 202-213 |
Number of pages | 12 |
Journal | Methods in Ecology and Evolution |
Volume | 2 |
Issue number | 2 |
DOIs | |
State | Published - Apr 2011 |
Externally published | Yes |
Keywords
- Ancillary data
- Bio-informatics
- Covariates
- Dimensional data model
- Eco-informatics
- Functional biodiversity
- Hierarchical data structure
- Relational database
- Star-scheme
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Ecological Modeling