Literature DB >> 21442733

Toward a knowledge infrastructure for traits-based ecological risk assessment.

Donald J Baird1, Christopher J O Baker, Robert B Brua, Mehrdad Hajibabaei, Kearon McNicol, Timothy J Pascoe, Dick de Zwart.   

Abstract

The trait approach has already indicated significant potential as a tool in understanding natural variation among species in sensitivity to contaminants in the process of ecological risk assessment. However, to realize its full potential, a defined nomenclature for traits is urgently required, and significant effort is required to populate databases of species-trait relationships. Recently, there have been significant advances in the area of information management and discovery in the area of the semantic web. Combined with continuing progress in biological trait knowledge, these suggest that the time is right for a reevaluation of how trait information from divergent research traditions is collated and made available for end users in the field of environmental management. Although there has already been a great deal of work on traits, the information is scattered throughout databases, literature, and undiscovered sources. Further progress will require better leverage of this existing data and research to fill in the gaps. We review and discuss a number of technical and social challenges to bringing together existing information and moving toward a new, collaborative approach. Finally, we outline a path toward enhanced knowledge discovery within the traits domain space, showing that, by linking knowledge management infrastructure, semantic metadata (trait ontologies), and Web 2.0 and 3.0 technologies, we can begin to construct a dedicated platform for TERA science.
Copyright © 2010 SETAC.

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Year:  2010        PMID: 21442733     DOI: 10.1002/ieam.129

Source DB:  PubMed          Journal:  Integr Environ Assess Manag        ISSN: 1551-3777            Impact factor:   2.992


  5 in total

1.  Derivation of water quality criteria of phenanthrene using interspecies correlation estimation models for aquatic life in China.

Authors:  Jiangyue Wu; Zhengtao Liu; Zhenguang Yan; Xianliang Yi
Journal:  Environ Sci Pollut Res Int       Date:  2015-01-23       Impact factor: 4.223

2.  Sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants.

Authors:  Nadine V Gerner; Kevin Cailleaud; Anne Bassères; Matthias Liess; Mikhail A Beketov
Journal:  Ecotoxicology       Date:  2017-09-06       Impact factor: 2.823

3.  taxize: taxonomic search and retrieval in R.

Authors:  Scott A Chamberlain; Eduard Szöcs
Journal:  F1000Res       Date:  2013-09-18

4.  Species traits as predictors for intrinsic sensitivity of aquatic invertebrates to the insecticide chlorpyrifos.

Authors:  Mascha N Rubach; Donald J Baird; Marie-Claire Boerwinkel; Stephen J Maund; Ivo Roessink; Paul J Van den Brink
Journal:  Ecotoxicology       Date:  2012-06-19       Impact factor: 2.823

5.  Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits.

Authors:  Sanne J P Van den Berg; Hans Baveco; Emma Butler; Frederik De Laender; Andreas Focks; Antonio Franco; Cecilie Rendal; Paul J Van den Brink
Journal:  Environ Sci Technol       Date:  2019-04-30       Impact factor: 9.028

  5 in total

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