Many, large and early: Hunting pressure on wild boar relates to simple metrics of hunting effort

Vajas, Pablo; Clément, Christophe; Richard, Emmanuelle; Fattebert, Julien; Rousset, Cyril; Saı̈d, Sonia; Baubet, Éric

doi:10.1016/j.scitotenv.2019.134251

Cited by 42 publications

(19 citation statements)

References 51 publications

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“…African swine fever has already been detected in Belgium (Linden et al 2019, Pikalo et al 2020) and some eastern states in Germany (Sauter‐Louis et al 2021), and spread to countries in central and western Europe is a distinct possibility (Sanchez‐Vizcaino et al 2015; Śmietanka et al 2016; World Organisation for Animal Health 2017 a , b ). This continued expansion leads to social and administrative demands for countermeasures to prevent and limit the spread of ASF (Keuling et al 2016, Liordos et al 2017, Podgórski and Śmietanka 2018, Vajas et al 2019). The management of ASF in free‐roaming animals is of primary importance to reduce the risk of introduction and continued spread of ASF in a given region (Chenais et al 2018, Saegerman 2018, Petit et al 2020).…”

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confidence: 99%

Genetic Differentiation of Wild Boar Populations in a Region Endangered by African Swine Fever

et al. 2021

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For areas at risk for African swine fever (ASF) introduction from neighboring regions, it is important for epidemic control to know how wild boar (Sus scrofa) dispersion dynamics could be used to combat the spread of ASF. In this regard, long‐term information based on population genetic data makes an important contribution. We selected our study area as Rhineland‐Palatinate, Germany, because it had a high density of wild boars and was threatened by ASF via infected wild boars from neighboring Belgium. On an area of around 20,000 km2, we collected almost 1,200 blood samples from 22 wild boar hunting grounds. The study area included a network of potential barriers to movement, including roads and rivers. We assessed genetic differentiation based on microsatellite data. We used 2 spatial (Bayesian Analysis of Population Structure [BAPS] and TESS) and 1 non‐spatial (STRUCTURE) Bayesian model‐based approaches to analyze the data. Each of the algorithms detected 4 clusters with different cluster compositions in different areas and identified the highest degrees of differentiation between hunting grounds east and west of the Rhine River, between Pfalz and Eifel‐Hunsrück, and to a lesser degree between Westerwald and Taunus and between Eifel and Hunsrück. Thus, genetic evidence suggests barriers of different strength that might be helpful in a setup of complex and expensive measures against the spread of animal diseases such as ASF. The described approach could also provide valuable information for other threatened regions to contain ASF. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.

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confidence: 99%

Genetic Differentiation of Wild Boar Populations in a Region Endangered by African Swine Fever

et al. 2021

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“…Wild boars ( Sus scrofa ), also known as wild pigs or feral pigs in the USA, have strongly expanded their range in northern Europe during the last decade (von Essen 2019 ). They are also very intensively hunted in Europe (Vajas et al 2020 ) and the most important hunting species in the world (Massei et al 2015). In Finland, the wild boar population has increased drastically during the past years with large regional differences in the population densities.…”

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confidence: 99%

Foodborne Zoonoses Common in Hunted Wild Boars

et al. 2020

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The northern European wild boar population has increased during the last decade. Highest wild boar numbers in Finland have been reported in the southeastern part near the Russian border. Wild boars may be infected with several human and animal pathogens. In this study, we investigated the presence of important foodborne pathogens in wild boars hunted in 2016 in Finland using serology, PCR and culturing. Seroprevalence of Salmonella (38%) and Yersinia (56%) infections was high in wild boars. Antibodies to hepatitis E virus, Toxoplasma gondii and Brucella were found in 18%, 9% and 9% of the wild boars, respectively. Trichinella antibodies were detected in 1% of the animals. We recorded no differences in the seroprevalence between males and females. However, Yersinia and T. gondii antibodies were detected significantly more often in adults than in young individuals. Listeria monocytogenes (48%) and stx-positive Escherichia coli (33%) determinants were frequently detected in the visceral organs (spleen and kidneys) by PCR. Yersinia pseudotuberculosis O:1 and L. monocytogenes 2a and 4b were identified by culturing from the PCR-positive samples. Brucella suis biovar 2 was isolated from visceral organs. No African swine fever, classical swine fever or Aujeszky’s disease were detected in the wild boars. Our study shows that wild boars are important reservoirs of foodborne pathogens.

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“…A less significant seasonal effect (p < 0.05) was also recorded on wild boar ADR. The food exploitation hypothesis [16,17] climate-limiting factors [18] and hunting disturbance [19][20][21][22] are all possible drivers of wild ungulates home range shifting, and temporal abundance variation at the local scale. According to the ecology of fear [23] animals try to avoid predation risk shifting their home range toward refuge areas limiting, temporary, their movements outside the sphere of influence of the refuge [24].…”

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confidence: 99%

Seasonal Variation in Wild Ungulate Abundance in a Hunting-Ban Beech Forest: A Case Study of Amiata Mountain, Central Italy

Viola

Girotti

Serafini

et al. 2020

The 1st International Electronic Conference on Forests—Forests for a Better Future: Sustainability, Innovation, Inter

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Several studies have focused on the impact of ungulates on agricultural systems, but the magnitude of their antagonistic role in forest renovation dynamics has long been underestimated and is rarely considered. The abundance of ungulate species is susceptible to seasonal variations according to their autecology, human management choices, and territorial planning. Therefore, the appropriate choice of counting period is crucial. In this case study, we used camera traps to assess the seasonal abundance variations of wild boar and roe deer in a 560-hectares hunting-ban beech forest (95.48%) in southern Tuscany managed for timber production. Camera-trapping sessions were performed in both early summer and autumn. The roe deer abundance index is higher in early summer, although statistically not significant, potentially affecting seedling survival. Inversely, wild boars significantly (F = 79.125; p = 0.001) increase their abundance at the local scale in autumn when probably, according to the ecology of fear, they shift their home range toward refuge areas temporary. In autumn, the high density of wild boars can reduce seed availability at the local scale. Further analyses assessing the correlation between seasonal wild ungulate abundance and forest regeneration rates are in progress, based on data recorded within and around three fenced sample plots.

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Many, large and early: Hunting pressure on wild boar relates to simple metrics of hunting effort

Cited by 42 publications

References 51 publications

Genetic Differentiation of Wild Boar Populations in a Region Endangered by African Swine Fever

Genetic Differentiation of Wild Boar Populations in a Region Endangered by African Swine Fever

Foodborne Zoonoses Common in Hunted Wild Boars

Seasonal Variation in Wild Ungulate Abundance in a Hunting-Ban Beech Forest: A Case Study of Amiata Mountain, Central Italy

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