EFSA updated database to support GM crops assessment

A database on arthropods inhabiting European arable crops has been established in 2012 to support the environmental risk assessment of genetically modified (GM) crops. In the current project, the database was updated and extended to include the small grain cereals wheat, barley, oats, triticale, rye, sorghum, and buckwheat. 
 

Systematic literature searches were conducted to identify publications on small grain cereals and to identify additional publications on the crops covered by the previous database (maize, beet, potato, oilseed rape, rice, cotton, soy). 
 

The final database contains information on more than 4000 arthropod species, > 27700 records, and > 2000 references. Overall, small grain cereals in Europe were reported to harbour more than 2000 arthropod species, with most information being available for wheat and barley. For the other crops, the updated database contains more than 3200 species. Most of the records are available for maize, followed by beet, potato, and oilseed rape. 
 

The majority of the collected arthropods belong to the functional groups of predators and herbivores, while relatively few records are available for decomposers, parasitoids, and pollinators. The taxonomic composition among the different small grain cereals and also between small grain cereals and the other crops in the database was comparable, in particular for generalists, such as predators and decomposers. 

 

The update resulted in only minor changes in the taxonomic composition of the different functional groups compared to the previous database version, and the species selection for risk assessment proposed previously remains fully valid. 
 

In addition, information on arthropods inhabiting field margins of arable crops in European agricultural landscapes was reviewed. In systematic literature searches, more than 300 studies were identified that contain species-level data suitable for the database. Sampled field margin elements comprised natural herbaceous vegetation, sown margin strips, hedgerows or shelterbelts, and naturally regenerating margins. A data model is proposed that allows the compilation of multiple field margin elements for each studied margin.

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