Summary
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.
Description
A generic structure for plant trait databases - Kattge - 2010 - Methods in Ecology and Evolution - Wiley Online Library
%0 Journal Article
%1 MEE3:MEE367
%A Kattge, Jens
%A Ogle, Kiona
%A Bönisch, Gerhard
%A Díaz, Sandra
%A Lavorel, Sandra
%A Madin, Joshua
%A Nadrowski, Karin
%A Nöllert, Stephanie
%A Sartor, Karla
%A Wirth, Christian
%D 2011
%I Blackwell Publishing Ltd
%J Methods in Ecology and Evolution
%K imported plant trait dbms
%N 2
%P 202--213
%R 10.1111/j.2041-210X.2010.00067.x
%T A generic structure for plant trait databases
%U http://dx.doi.org/10.1111/j.2041-210X.2010.00067.x
%V 2
%X Summary
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.
@article{MEE3:MEE367,
abstract = {Summary
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.},
added-at = {2011-05-31T11:12:23.000+0200},
author = {Kattge, Jens and Ogle, Kiona and Bönisch, Gerhard and Díaz, Sandra and Lavorel, Sandra and Madin, Joshua and Nadrowski, Karin and Nöllert, Stephanie and Sartor, Karla and Wirth, Christian},
biburl = {https://www.bibsonomy.org/bibtex/23b4bef54eb019167f50615c6aaf054d6/schmidt2},
description = {A generic structure for plant trait databases - Kattge - 2010 - Methods in Ecology and Evolution - Wiley Online Library},
doi = {10.1111/j.2041-210X.2010.00067.x},
interhash = {31ac8641a54f591d65f497ee7f922c1b},
intrahash = {3b4bef54eb019167f50615c6aaf054d6},
issn = {2041-210X},
journal = {Methods in Ecology and Evolution},
keywords = {imported plant trait dbms},
number = 2,
pages = {202--213},
publisher = {Blackwell Publishing Ltd},
timestamp = {2011-07-19T09:59:46.000+0200},
title = {A generic structure for plant trait databases},
url = {http://dx.doi.org/10.1111/j.2041-210X.2010.00067.x},
volume = 2,
year = 2011
}