Browsing by Subject "Camera trap"

Now showing 1 - 3 of 3
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    Harmonization of the use of hunting statistics for wild boar density estimation in different study areas: report based on comparison of case studies in different wild boar populations representative of the different management and habitat conditions across Europe.
    (Wiley, 2019-08-29) ENETWILD-consortium; Vicente, Joaquín; Palencia, Pablo; Plhal, Radim; Blanco Aguiar, José Antonio; Laguna, Eduardo; Soriguer, Ramón; Fernández López, Javier; Podgórski, Tomasz; Petrović, Karolina; Apollonio, Marco; Scandura, Massimo; Ferroglio, Ezio; Zanet, Stefania; Brivio, Fracesca; Keuling, Oliver; Smith, Graham C.; Guibert, Miguel; Villanua, Diego; Rosell, Carme; Colomer, Joana; Armenteros, Jose Ángel; González Quirós, Pablo; Hernández Palacios, Orencio; Ferreres, Javier; Torres, José Antonio; Pareja, Pablo; Martínez-Carrasco Pleite, Carlos; Fafián, José Antonio; Escribano, Fernando; Esteve, Carles; Acevedo Lavandera, Pelayo; Sanidad Animal; Facultades de la UMU::Facultad de Veterinaria
    Hunting statistics can be suitable to determine wild boar density estimates if a calibration with an accepted rigorous method is performed. Here, densities calculated from drive counts during collective drive hunting activities are compared against density values calculated by camera trapping using the random encounter method. For this purpose, we selected 10 study sites in Spain, from North to South representing a diversity of habitats, management and hunting traditions without artificial feeding, plus one study site in Czech Republic where artificial feeding was practiced. Density values estimated from both drive counts and camera trapping were strongly positively correlated (R2=0.84 and 0.87 for linear and non-linear models, respectively) and showed a good agreement. Drive counts data might be therefore used as a density estimate to calibrate models for estimating density in large areas and potentially, to compare densities among areas. For these purposes, there is still the need to harmonise hunting data collection across Europe to make them usable at a large scale. Our results need to be confirmed across a wider number of European populations to provide valid geographical wild boar density predictions across Europe.
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    Wild boar density data generated by camera trapping in nineteen European areas
    (Wiley, 2022-03-17) ENETWILD-consortium; Acevedo, P.; Aleksovski, V.; Apollonio, M.; Berdión, O.; Blanco-Aguiar, J.A.; Río Alonso, Laura del; Ertürk, A.; Fajdiga, L.; Escribano, F.; Ferroglio, E.; Gruychev, G.; Gutiérrez, I.; Häberlein, V.; Hoxha, B; Kavčić, K.; Keuling, O.; Martínez-Carrasco Pleite, Carlos; Palencia, P.; Pereira, P.; Plhal, R.; Plis, K.; Podgórski, T.; Ruiz, C.; Scandura, M.; Santos, J.; Sereno, J.; Sergeyev, A.; Shakun, V.; Soriguer, R.; Soyumert, A.; Sprem, N.; Stoyanov, S.; Smith, G.C.; Trajçe, A.; Urbani, N.; Zanet, S.; Vicente, J.; Sanidad Animal; Facultad de Veterinaria
    This report presents the results of field activities in relation to the generation of reliable wild boar density values by camera trapping (CT) in 19 areas in Europe, mainly in East Europe. Random Encounter Model (REM) densities ranged from 0.35±0.24 to 15.25±2.41 (SE) individuals/km2. No statistical differences in density among bioregions were found. The number of contacts was the component of the trapping rate that determined the coefficient of variation (CV) the most. The daily range (DR) significantly varied as a function of management; the higher values were detected in hunting grounds compared to protected areas, indicating that movement parameters are population specific, and confirming the potential role of hunting activities in increasing wild boar movement and contact rates among individual or groups. The results presented in this report illustrate that a harmonized approach to actual wildlife density estimation (namely for terrestrial mammals) is possible at a European scale, sharing the same protocols, collaboratively designing the study, processing, and analysing the data. This report adds reliable wild boar density values that have the potential to be used for wild boar abundance spatial modelling, both directly or to calibrate outputs of model based on abundance (such as hunting bags) or occurrence data. Future REM developments should focus on improving the precision of estimates (probably through increased survey effort). Next steps require an exhaustive and representative design of a monitoring network to estimate reliable trends of wild boar populations as a function of different factors in Europe. In this regard, the newly created European Observatory of Wildlife will be a network of observation points provided by collaborators from all European countries capable to monitor wildlife population at European level.
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    Wild ungulate density data generated by camera trapping in 37 European areas: first output of the European Observatory of Wildlife (EOW)
    (Wiley, 2023-03-27) Martínez-Carrasco Pleite, Carlos; ENETWILD-consortium, "et.al."; Sanidad Animal; Facultad de Veterinaria
    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.