Wild ungulate density data generated by camera trapping in 37 European areas: first output of the European Observatory of Wildlife (EOW)
Yazarlar (85)
Tancredi Guerrasio
Pelayo Acevedo
Marco Apollonio
Amir Arnon
Carlos Barroqueiro
Olgirda Belova
Oskar Berdión
José Antonio Blanco-Aguiar
Hanna Bijl
Norbert Bleier
Josef Bučko
Elena Bužan E
Davide Carniato
Francisco Carro
Jim Casaer
João Carvalho
Sándor Csányi
Lucía Del Rio L
Héctor Del Val Aliaga
Dr. Öğr. Üyesi Alper ERTÜRK Kastamonu Üniversitesi, Türkiye
Fernando Escribano Kastamonu Üniversitesi
Luka Duniš
Javier Fernández-Lopez
Ezio Ferroglio
Carlos Fonseca
Dragan Gačić
Aleksandre Gavashelishvili
Alexios Giannakopoulos
Azahara Gómez-Molina
Carmen Gómez-Peris
Gradimir Gruychev
Iván Gutiérrez
Veith Häberlein V
Siti Mastura Hasan
Lars Hillström
Bledi Hoxha
María Iranzo
Mihael Janječić M
Patrick Jansen
Sonia Illanas
Bhraaz Kashyap
Oliver Keuling
Eduardo Laguna
Hugues Lefranc
Alain Licoppe
Yorick Liefting
Carlos Martínez-Carrasco
Damir Mrđenović
Melitjan Nezaj
Xosé Pardavila X
Pablo Palencia
Guilherme Pereira
Patricia Pereira
Nuno Pinto
Radim Plhal
Kamila Plis
Tomasz Podgórski
Bostjan Pokorny
Ludovica Preite
Marina Radonjic
Marcus Rowcliffe M
Carmen Ruiz-Rodríguez
João Santos
Oscar Rodríguez
Massimo Scandura
Mario Sebastián
Jorge Sereno
Belma Šestovic
Ilir Shyti
Eder Somoza
Ramon Soriguer
Jordi Solàde La Torre
Doç. Dr. Anıl SOYUMERT ERTÜRK Kastamonu Üniversitesi, Türkiye
Nikica Šprem
Stojan Stoyanov
Graham C. Smith
Majlind Sulce
Rita Tinoco Torres
Aleksandër Trajçe
Gintautas Urbaitis
Nicolás Urbani
Tamar Uguzashvili
Rachele Vada
Stefania Zanet
Joaquín Vicente
| Makale Türü |
Diğer (Teknik, not, yorum, vaka takdimi, editöre mektup, özet, kitap krıtiği,
araştırma notu, bilirkişi raporu ve benzeri)
(Uluslararası alan indekslerindeki dergilerde yayınlanan teknik not,
editöre mektup, tartışma, vaka takdimi ve özet türünden makale)
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| Dergi Adı | Efsa Supporting Publications | ||
| Dergi ISSN | 2397-8325 | ||
| Dergi Tarandığı Indeksler | GLOBALHEALTH, CROSSREF, CABABSTRACTS, ROAD, THE KEEPERS | ||
| Makale Dili | Türkçe | Basım Tarihi | 03-2023 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 01-03-2023 |
| Cilt / Sayı / Sayfa | 20 / 3 / – | DOI | 10.2903/sp.efsa.2023.EN-7892 |
| Makale Linki | http://dx.doi.org/10.2903/sp.efsa.2023.en-7892 | ||
| Özet |
| Abstract The European Observatory of Wildlife (EOW) as part of the ENETWILD project, aims to improve the European capacity for monitoring wildlife populations, implementing international standards for data collection, providing guidance on wildlife density estimation, and finally, to promote collaborative, open data networks to develop wildlife monitoring, initially focusing on terrestrial wild mammals. This report presents density estimates for species that are widely distributed (wild boar (Sus scrofa), European roe deer (Capreolus capreolus), red deer (Cervus elaphus)) by following a standardised camera trapping (CT) protocol, in 48 areas from 28 different countries in Europe, during 2022. Density values are provided for 37 areas from 20 countries, while an additional 9 locations from 8 countries are currently completing the data analysis. The EOW involved different stakeholders over most European countries, which resulted for the first time in a number of reliable (known precision) wild ungulate density estimates, from areas representing different European bioregions. These estimates are the result of a collaborative effort from the network to apply practical systematic and rigorous protocols. The results presented from the first pilot campaign of the EOW cannot be used to accurately describe wildlife population gradients and trends at European level but can be used as first baseline data for future trend analyses. Our results show data gaps, but also provide relevant insights into some of the main drivers of demographic evolution of wild ungulate populations in Europe. We will expand and improve the EOW in the future to include more representative sites. The Agouti app, including photogrammetry methods to estimate CT detection zone size and animal speed of movement using a computer vision process proved useful to reduce the workload and to improve objectivity of measurements for REM method. We discuss the results obtained by the 2022 campaign in relation to the specific objectives of the EOW and propose the next steps. |
| Anahtar Kelimeler |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 22 |