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133 results for “wild boar”

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dryad32/100

Data from: Comparative landscape genetic analyses show a Belgian motorway to be a gene flow barrier for red deer (Cervus elaphus), but not wild boars (Sus scrofa)

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publicMay 2012View details →
dryad32/100

Ecological drivers of African swine fever virus persistence in wild boar populations: insight for control

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publicJan 2021View details →
dryad32/100

Data from: Genomic diversity and differentiation of a managed island wild boar population

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publicMay 2015View details →
dryad32/100

Data from: Fluctuating food resources influence developmental plasticity in wild boar

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publicJul 2013View details →
dryad32/100

Data from: Unexpected but welcome. Artificially selected traits may increase fitness in wild boar

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publicMar 2016View details →
dryad32/100

Data from: Do cities represent sources, sinks or isolated islands for urban wild boar population structure?

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publicJul 2017View details →
dryad32/100

Data from: Demographic history, current expansion and future management challenges of wild boar populations in the Balkans and Europe

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publicJun 2016View details →
dryad32/100

Early life growth and telomere length in wild boar piglets 2018

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publicNov 2021View details →
dryad32/100

Data from: Distinguishing migration events of different timing for wild boar in the Balkans

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publicJul 2017View details →
dryad32/100

Data from: Genome-wide single nucleotide polymorphism analysis reveals recent genetic introgression from domestic pigs into Northwest European wild boar populations

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publicMay 2012View details →
dryad32/100

Data from: Risk factors associated to a high Mycobacterium tuberculosis complex seroprevalence in wild boar (Sus scrofa) from a low bovine tuberculosis prevalence area

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publicMar 2020View details →
dryad28/100

Data from: Does multiple paternity explain phenotypic variation among offspring in wild boar?

During pregnancy, littermates compete to extract maternal resources from the placenta. Unequal extraction of resources leads to developmental differences among offspring and thus within-litter variation in offspring mass. Because competition among littermates can be stronger among half-sibs, multiple paternity may represent an adaptive strategy allowing females to increase within-litter phenotypic variation among offspring when facing variable environments. Wild boar (Sus scrofa) females produce large litters with diversified offspring in terms of body mass. Additionally, multiple paternity within a litter has been observed in this promiscuous species. One can hypothesize that multiple paternity represents the mechanism by which females increase within-litter phenotypic variation. Combining long-term monitoring data with paternity analyses in a wild boar population, we tested whether the increase in the number of fathers within a litter explained the increase in within-litter variation in offspring mass observed in large litters. We showed that heavy females mated earlier during the rut, produced larger litters with a higher number of fathers and more variable fetus mass than lighter females. Within-litter variation of offspring mass increased with gestation stage and litter size, suggesting differential allocation of maternal resource among offspring in utero. However, we found only a weak paternal effect on offspring mass and no direct effect of the number of fathers on the within-litter variation in offspring mass. These results indicate that differential maternal allocation to offspring during pregnancy is unlikely related to paternal identity in this species.

opencc-zeroDec 2017View details →
dryad28/100

Ecological relationships among habitat type, food nutrients, parasites and hormones in wild boar during winter

<p>Habitat quality and parasite assembly influence wildlife health, and they are key indicators of health and survivability of wildlife populations. To investigate the potential ecological relationships among habitat type, food nutrients, parasites and hormones in wild boar (<i><span>Sus scrofa</span></i>), we collected samples of wild boar feces and available plants in their habitat <span>by line transects during winter</span><span>. </span><span>Along transects, we identified the composition of plants foraged by wild boar and measured the content of nutrients in available plants to estimate nutrient intake. We also quantified parasites and hormones in wild boar fecal samples. We compared food nutrients among different forest types and explored possible relationships among estimated nutrient intake, parasites and hormones.</span><span> We found coniferous forest</span><span> had positive effects on estimated fat intake and negative effects on estimated protein and fiber intake by wild boar</span><span>. Furthermore, we revealed that </span><span>estimated fat intake was negatively correlated with </span><i><span><span>Metastrongylus elongatus </span></span></i><span>parasites and positively correlated with triiodothyronine (T3). In contrast, estimated protein intake was positively correlated with </span><i><span><span>M. elongatus</span></span></i><span> and negatively correlated with T3. </span><span>Finally, we found </span><span>negative relationship</span><span>s</span><span> between T3 concentrations and loads of </span><i><span><span>Ascaris suum</span></span></i><span> parasites and between cortisol (COR) and loads of </span><i><span><span>Trichuris suis</span></span></i><span> parasites.</span><i> </i><span>T</span><span>hese insights on ecological relationships help identify potential dietary parameters in winter that could help predict and manage parasite and hormone responses for wild boar population recovery.</span>Habitat quality and parasite assembly influence wildlife health, and they are key indicators of health and survivability of wildlife populations. To investigate the potential ecological relationships among habitat type, food nutrients, parasites and hormones in wild boar (<i><span>Sus scrofa</span></i>), we collected samples of wild boar feces and available plants in their habitat <span>by line transects during winter</span><span>. </span><span>Along transects, we identified the composition of plants foraged by wild boar and measured the content of nutrients in available plants to estimate nutrient intake. We also quantified parasites and hormones in wild boar fecal samples. We compared food nutrients among different forest types and explored possible relationships among estimated nutrient intake, parasites and hormones.</span><span> We found coniferous forest</span><span> had positive effects on estimated fat intake and negative effects on estimated protein and fiber intake by wild boar</span><span>. Furthermore, we revealed that </span><span>estimated fat intake was negatively correlated with </span><i><span><span>Metastrongylus elongatus </span></span></i><span>parasites and positively correlated with triiodothyronine (T3). In contrast, estimated protein intake was positively correlated with </span><i><span><span>M. elongatus</span></span></i><span> and negatively correlated with T3. </span><span>Finally, we found </span><span>negative relationship</span><span>s</span><span> between T3 concentrations and loads of </span><i><span><span>Ascaris suum</span></span></i><span> parasites and between cortisol (COR) and loads of </span><i><span><span>Trichuris suis</span></span></i><span> parasites.</span><i> </i><span>T</span><span>hese insights on ecological relationships </span><span>help identify potential dietary parameters in winter that could help predict and manage parasite and hormone responses for wild boar population recovery.</span></p>

opencc-zeroJan 2022View details →
dryad28/100

SNPs genotypes of Italian wild boar (Sus scrofa) populations

<p>Human activities can globally modify natural ecosystems determining ecological, demographic and range perturbations for several animal species. These changes can jeopardize native gene pools in different ways, leading either to genetic homogenization or, conversely, to the split into genetically divergent demes.</p> <p> </p> <p>In the past decades, most European wild boar (<i>Sus scrofa</i>) populations were heavily managed by humans. Anthropic manipulations have strongly affected also Italian populations through heavy hunting, translocations and reintroductions that might have deeply modified their original gene pools.</p> <p> </p> <p>In this study, exploiting the availability of the well-mapped porcine genome, we applied genomic tools to explore genome-wide variability in Italian wild boar populations, investigate their genetic structure and detect signatures of possible introgression from domestic pigs and non-native wild boar. Genomic data from 134 wild boar sampled in six areas of peninsular Italy and in Sardinia were gathered using the Illumina Porcine SNP60 Beadchip (60k Single Nucleotide Polymorphisms – SNPs) and compared with reference genotypes from European specimens and from domestic pigs (both commercial and Italian local breeds), using multivariate and maximum-likelihood approaches.</p> <p> </p> <p>Pairwise F<sub>ST</sub> values, multivariate analysis and assignment procedures indicated that Italian populations were highly differentiated from all the other analyzed European wild boar populations.</p> <p> </p> <p>Overall, a lower heterozygosity was found in the Italian population than in the other European regions. The most diverging populations in Castelporziano Presidential Estate and Maremma Regional Park can be the result of long-lasting isolation, reduced population size and genetic drift. Conversely, an unexpected similarity was found among Apennine populations, even at high distances. Signatures of introgression from both non-Italian wild boar and domestic breeds were very limited.</p> <p> </p> <p>To summarize, we successfully applied genome-wide procedures to explore, for the first time, the genomic diversity of Italian wild boar, demonstrating that they represent a strongly heterogeneous assemblage of demes with different demographic and manipulation histories. Nonetheless, our results suggest that a native component of genomic variation is predominant over exogenous ones in most populations.</p>

opencc-zeroFeb 2022View details →
zenodo28/100

The Effects of Wild Boar Rooting on Epigeic Arthropods in Oak Forests

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opencc-by-4.0Jun 2024View details →
zenodo28/100

Fig. 3 in Cystic echinococcosis in wild boars (Sus scrofa) from southern Italy: Epidemiological survey and molecular characterization

Fig. 3. Pseudo multilocular hydatid cyst, by Echinococcus granulosus sensu stricto, l spleen localization.

opencc-by-4.0Aug 2019View details →
zenodo28/100

Model outputs of ENETWILD density model for wild boar based on hunting yield data. August 2021

<p>These maps are models obtained from density hunting yield data of the ENETWILD project based on available raw data. These are frequently updated&nbsp;in order to improve results.</p> <p>Objectives:<br> -&nbsp; To evaluate whether an approach based on density data is capable to correct overpredictions of previous reports for high-resolution predicted patterns when raw data are collected at different spatial resolution.<br> - Downscaling to 10x10 km grid &gt;&gt;&gt; file&nbsp; &quot; sp_DensityModel_10km_20210621_MESS_crs3035.tif&quot;<br> - Downscaling to 2x2 km grid &nbsp; &gt;&gt;&gt; file &quot;sp_DensityModel_2km_20210621_MESS_MaxPred50_crs3035.tif&rdquo;<br> <br> Model settings and predictors:&nbsp; &nbsp;&nbsp;<br> - Assuming cells as municipality in 10x10 km grid downscaling.<br> - Assuming cells as hunting grounds in 2x2 km grid downscaling.</p> <p>Conclusions guiding future methodological steps:<br> - To explore approaches to manage spatial autocorrelation at European scale to improve the predictive performance of the results<br> - To compile complete data for each country for modeling temporal dimension of wild boar patterns.</p> <p>For further details and methodological approach see the report:</p> <p>ENETWILD-consortium, S. Illanas, S. Croft, G. C. Smith, J. Fern&aacute;ndez-L&oacute;pez, J. Vicente, J. A. Blanco-Aguiar, R. Pascual-Rico, M. Scandura, M. Apollonio, E. Ferroglio, O. Keuling, S. Zanet, F. Brivio, T. Podgorski, K. Plis, R. C. Soriguer, P.&nbsp; Acevedo. Update of model for wild boar abundance based on hunting yield and first models based on occurrence for wild ruminants at European scale. EFSA supporting publication 2021: EN-6825. 30 pp. <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.2903%2Fsp.efsa.2021.EN-6825&amp;data=04%7C01%7C%7C371a629e88d2444ab27f08d966f4158f%7C406a174be31548bdaa0acdaddc44250b%7C1%7C0%7C637654020801719420%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&amp;sdata=4XGKExGdoJYsJ%2B8xvdTrVxVzQHPRN8Aem%2BMX7zSd8f4%3D&amp;reserved=0">https://doi.org/10.2903/sp.efsa.2021.EN-6825</a></p>

opencc-by-4.0Aug 2021View details →
dryad28/100

Body mass measurements of wild boar from two French populations

<p>Despite the importance of body growth in shaping life history tactics and population dynamics, exploring individual growth trajectories in the wild remains challenging. Here, we quantified wild boar growth trajectories at both the population and the individual levels using standard growth models (i.e. Gompertz, logistic, and monomolecular models) that encompass the expected range of growth shapes. According to current theories of life history evolution, we expect wild boar to display a sex-specific Gompertz type growth trajectory and lower size dimorphism in the poorer environment. While wild boar displayed the expected Gompertz type trajectory in the rich site at the population level, we found differences in growth shapes between the two populations and among individuals within each population. Asymptotic body mass, growth rate and timing of maximum growth rate differed as well, indicating a high flexibility of growth trajectories in wild boar. In addition, we found a cohort effect on asymptotic body mass suggesting that environmental conditions early in life shape body mass at adulthood. Our findings demonstrate that body growth trajectories in wild boar are context-, sex- and cohort-specific, differing between populations and among individuals within a population.</p>

opencc-zeroOct 2022View details →
dryad28/100

Data from: Does multiple paternity explain phenotypic variation among offspring in wild boar?

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publicMar 2018View details →
dryad28/100

SNPs genotypes of Italian wild boar (Sus scrofa) populations

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publicFeb 2022View details →

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Allen Brain Atlas

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dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
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International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

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behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
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OpenNeuro

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Last verified 2026-04-29Open record