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Developing a European network of analytical laboratories and government institutions to prevent poisoning of raptors.

Irene ValverdeSilvia EspínPilar Gómez-RamírezPablo Sánchez-VirostaAntonio Juan García-FernándezPhilippe Berny
Published in: Environmental monitoring and assessment (2022)
Many cases of wildlife poisoning in Europe have been reported causing population declines, especially in raptors. Toxicovigilance and risk assessment studies are essential to reinforce the knowledge of the number of illegal poisoning cases and the substances involved in these crimes. Many researchers and projects in different institutions have suggested the creation of a network to improve communication and share information between European countries. This article presents the results of the Short-Term Scientific Mission titled "Developing a Network of Analytical Labs and Government Institutions" supported by the COST Action European Raptor Biomonitoring Facility (CA16224), which aims to initiate a network of veterinary forensic toxicology laboratories, in order to improve communication among laboratories to prevent wildlife poisoning, especially in raptors. For this purpose, a questionnaire was designed and sent by email to 119 laboratories in Europe. It contained 39 questions on different topics (e.g. laboratory activities, analytical information). A total of 29 responses were received. Most participant laboratories work on veterinary forensic toxicology research and external cases at the same time, which provides a robust overview of the actual situation in the field. Analytical techniques and data collection methods should be harmonised, and communication between laboratories is encouraged to create a more effective network. The present study established contact between laboratories as an initial step to create a European network and compiled basic data to identify strengths and weaknesses that will help harmonise methodologies across Europe and increase pan-European capacities.
Keyphrases
  • risk assessment
  • liquid chromatography
  • drinking water
  • big data
  • machine learning
  • heavy metals
  • mass spectrometry
  • artificial intelligence
  • human health
  • protein kinase