Journal
METHODS IN ECOLOGY AND EVOLUTION
Volume 2, Issue 2, Pages 202-213Publisher
WILEY
DOI: 10.1111/j.2041-210X.2010.00067.x
Keywords
ancillary data; bio-informatics; covariates; dimensional data model; eco-informatics; functional biodiversity; hierarchical data structure; relational database; star-scheme
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Funding
- National Science Foundation (NSF) [0630119, EPS-0447681]
- Div Of Biological Infrastructure
- Direct For Biological Sciences [1133366] Funding Source: National Science Foundation
- Div Of Biological Infrastructure
- Direct For Biological Sciences [0630119] Funding Source: National Science Foundation
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P>1. 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. 2. 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. 3. 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. 4. 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.
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