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Report of the ENETWILD workshop:

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Disclaimer: The present document has been produced and adopted by the bodies identified above as author(s). This task has been carried out exclusively by the author(s) in the context of a contract between the European Food Safety Authority and the author(s), awarded following a tender procedure. The present document is published complying with the transparency principle to which the Authority is subject. It may not be considered as an output adopted by the Authority. The European Food Safety Authority reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors.

Abstract

The ENETWILD consortium implementedtheEFSA‐funded project “Wildlife: collecting and sharing data on wildlife populations, transmitting animal diseases agents”,whose main objective is to collect wild boardensity, hunting and occurrence dataand model species geographical distribution and abundance throughout Europe.This subject is of particular concern due to the continued advance of African swine fever (ASF). In May 2019,the ENETWILD consortiumorganised aworkshop for 30game biologists, animal health professionals, and experts from national huntingand forest authorities from 14 countries form North East Europe.The overall objectives of the workshop were to present milestones and achievements of the ENETWILD project,review different country frameworks forwild boar data collection and harmonization (hunting, density and occurrence data), as well as to review scientificmethods for determiningwild boar abundance and density, and train oncamera trapping and the random encounter method (REM).It was agreed thatwild boar abundance and densityestimates available in NorthEastern Europe are unreliable because most of them are not based on scientific methods. Hence, there is a need to implement a novel method for determining wild boar abundance and densitythat uses hunting bag statistics including measures of hunting effort and efficiency during collective drive hunts, compared against density values calculated using camera trapping and the random encounter method (REM). Several collaboratorsfrom Poland, Finland, Belarus, Russia, Lithuania have declared their willingness to participate in such pilot studies, and all agreed in improving data collection, including by means of citizen science.