A generic structure for plant trait databases

Jens Kattge, Kiona Ogle, Gerhard Bönisch, Sandra Díaz, Sandra Lavorel, Joshua Madin, Karin Nadrowski, Stephanie Nöllert, Karla Sartor, Christian Wirth

Research output: Contribution to journalArticle

68 Scopus citations

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 languageEnglish (US)
Pages (from-to)202-213
Number of pages12
JournalMethods in Ecology and Evolution
Volume2
Issue number2
DOIs
StatePublished - Apr 2011

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

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