Open AccessReport of the ENETWILD workshop:
Author(s) -
Petrovic Karolina,
BlancoAguiar José Antonio,
Vicente Joaquin,
Smith Graham,
Podgorski Tomasz
Publication year - 2019
Publication title -
efsa supporting publications
Language(s) - English
Resource type - Journals
ISSN - 2397-8325
DOI - 10.2903/sp.efsa.2019.en-1712
Subject(s) - wild boar , harmonization , wildlife , abundance (ecology) , geography , data collection , distribution (mathematics) , fishery , environmental resource management , ecology , archaeology , biology , sociology , environmental science , social science , mathematical analysis , physics , mathematics , acoustics
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.