ENETWILD Camera trap Course

ENETWILD Camera trap Course

Camera trapping for monitoring wildlife and density estimation ​course

2020 September Training Course

The ENETWILD Project (www.enetwild.com) initiated its way about 3 years ago. By then, the harmonized use of comparable (standardized) data on the distribution and abundance of wildlife in Europe, particularly mammals, was hardly possible. ENETWILD approach, as a pioneer pilot initiative, has been able to build the foundations to address the harmonized monitoring of any wildlife over the continent thanks to a large network of collaborators, for which we transmit our gratitude to you, your team and Institution.  


African swine fever in Europe, and the case of wild boar as wild host, has kept the main focus of the project since its start. Only a few density data are available for wild boar and can be validated. This data is essential to calibrate other predictions and to define a range of values across large areas that are relevant for policy. In a long term, even density values can be directly and spatially modeled. Therefore, supporting teams to generate density values over different European contexts (habitats, landscapes, management, spatial distribution, epidemiology) has become an objective of the project, for which we are providing training to collaborators. For this purpose, ENETWILD is organized an online course addressed to a reduced number of participants who are part of our network of collaborators on days 2nd-3rd September 2020.  

Title of the Training School

Online course on the use of camera trapping for monitoring wildlife and density estimation


Pelayo Acevedo (IREC)
Marco Apollonio (UNISS)

J Antonio Blanco-Aguiar (IREC)

Jim Casaer (Research Institute for Nature and Forest)

Patrick Jansen (WUR)

Oliver Keuling (ITAW)

Pablo Palencia (IREC )
Javier Fernández-López (IREC)

Tomasz Podgorski (MRI)

Massimo Scandura (UNISS)

Graham Smith (APHA)

Joaquin Vicente Baños (IREC)

Learning objectives and expected outcomes

Introduce the participants to the use of camera traps as tools to monitor wildlife ecology, assess densities, management and interaction at the
interface, use of population data in risk assessment, collaborative science, open science, citizen science. Participants must be able to design the field study and prepare a datasheet for analysis and estimation of density by the end of the course. ​

Content and structure

2th Sep (9:30-13:00)

Presentation of ENETWILD and the training course (JV)
Wildlife population monitoring (I): abundance and density methods for wild boar (OK)
Wildlife population monitoring (II): abundance and density methods for wild ungulates and carnivores (MS, MA)
Principles of camera trapping (PP/JF)
Camera trap methods for density estimation. General (I) (TP)


Camera trap methods for density estimation. REM and REST (II) (PA-JF)
Field protocol for CT density estimation (JV)
Data processing for REM (I) (PP)
Data processing for REST (II) (PP)

3th Sep

Automated identification (JC)

MammalNet: Camera trapping and Citizen Science (JB)

iMammalia and MammalWeb (GS)

Agouti Platform (PJ)

Agouti: Case example (JC-PJ)

Materials provided by the teachers

Presentations (pdf)

Format of the presentation

15-20 minutes for presentation

Assumed knowledge of participants

Basic ecology and management of wildlife

Supporting information

Guidance on estimation of wild boar population abundance and density: methods, challenges, possibilities

Guidance on estimation of abundance and density data of wild ruminant population: methods, challenges, possibilities

Harmonization of the use of hunting statistics for wild boar density estimation in different study areas

Basic instructions to estimate the density of wild boar through the use of camera traps

Slides repository

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