Thursday 8 September 2022

11:30-13:00
SESSION E - Methods to estimate abundance­
Moderator: Stefano Focardi
The European Observatory of Wildlife (EOW): a collaborative network of observation points triggered by the need of monitoring wild boar at European scale

Tancredi Guerrasio 1, Pelayo Acevedo 2, Marco Apollonio 1, José Antonio Blanco-Aguiar 3, Guillaume Body 4, Jim Casaer 5, Ezio Ferroglio 6, Azahara Gomez Molina 3, Sonia Illanas 3, Patrick Jansen 7, Francesca Jaroszynska 8, Oliver Keuling 9, Yorick Liefting 7, Pablo Palencia 3, Kamila Pils 10, Tomasz Podgórski 10, Carmen Ruiz Rodriguez 3, Massimo Scandura 1, Graham Smith 11, Ramon Soriguer 3, Rachele Vada 6, Stefania Zanet 6, V Aleksowski, Oskar Berdión , Sandor Csányi 12, Alper Ertürk 13, Lidija Fajdiga 14, Fenand Escribano 3, Gradimir Valentinov Gruychev 15, I Gutiérrez , Veith Häberlein 16, Bledi Hoxha 16, Kresimir Kavčić 17, Carlos Martínez-Carrasco 18, P Pereira, Radim Plhal 19, João Santos 20, Jorge Sereno 3, Anil Soyumert 13, Nikica Sprem 21, Stoyan Stoyanov 22, Aleksander Trajce 16, Nicolas Urbani , Joaquín Vicente 3
1UNISS, Italy
2UCLMy, Spain
3UCLM, Spain
4ONCFS, France
5INBO, Belgium
6UNITO, Italy
7WUR, Netherlands
8OFB, France
9TiHo, Germany
10CZU, Czech Republic
11APHA, UK
12SZIU, Hungary
13Kastamonu University, Turkey
14HFM, Macedonia
15HECS, Bulgaria
16PPNEA, Germany
17UNIZG, Croatia
18UM, Spain
19MENDELU, Czech Republic
20PALOMBAR, Portugal
21University of Zagreb, Croatia
22LTU, Bulgaria

Automatic wild boar detection on camera trap images using machine learning

Beatriz Vidondo 1, Stefan Glüge 2, Laurent Huber 3, Claude Fischer 4, Luc Legrand 5
1University of Bern, Switzerland
2ZHAW Wädenswil, Switzerland
3Lepus, Switzerland
4HEPIA, Geneva, Switzerland
5KORA, Bern, Switzerland

Random Encouter and Staying Time model applied in Mediterranean environment: strengths and weaknesses

Pietro Pontiggia 1, Barbara Franzetti 1, Valentina Bellini 1, Alessandro Calabrese 1, Valerio Nicolucci 1, Stefano Focardi 2
1ISPRA, Italy
2CNR, Italy

Semi-automated density estimation of wild boars based on camera trap data

Maik Henrich 1, Christian Fiderer 1, Hjalmar Kühl 2, Timm Haucke 3, Volker Steinhage 3, Marco Heurich 4
1Bavarian Forest National Park/ University of Freiburg, Germany
2German Centre for Integrative Biodiversity Research, Germany
3University of Bonn, Germany
4Bavarian Forest National Park/ University of Freiburg/ Inland Norway University of Applied Sciences, Germany

Cameras or camus? Comparing camera traps and snow tracks surveys to estimate densities of large ungulate prey

Scott Waller 1, Dale Miquelle 1, Mark Hebblewhite 2, Jedediah Brodie 2, Hugh Robinson 3, Svetlana Soutyrina 4
1Wildlife Conservation Society, USA
2University of Montana, USA
3Panthera, Wildlife Conservation Society
4Sikhote-Alin Biosphere Zapovednik, Russia

Integrating hunting yield data at different resolution for wild boar abundance modeling

Javier Fernández-López 1, Sonia Illanas 2, David Ferrer 2, Jose A. Blanco-Aguiar 2, Joaquín Vicente 2, Pelayo Acevedo 2
1Centre d'Ecologie Fonctionelle et Evolutive (CEFE-CNRS), France
2Institute for Game and Wildlife Research (IREC-CSIC-UCLM), Spain