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92 results for “Sus scrofa”
Feral pig (Sus scrofa) disturbance facilitates establishment of resource-acquisitive species in Hawaiian forest understories
<p>In this study, we quantify the effects of leaf traits and dispersal attributes on species responses to pig soil disturbance at two spatial scales – 0.5 m<sup>2</sup> patches embedded along 20 m transects within sites – across a gradient of pig density in a Hawaiian montane wet forest using Bayesian mixed models. </p> <p>Native and non-native species demonstrated divergent responses, with increasing presence and abundance of non-native species in the understory as soil disturbance within patches and sites increased. Dominant patterns in measured traits tracked the leaf economic spectrum (LES), with non-native species tending toward resource-acquisitive traits. Species with resource-acquisitive traits, regardless of identity, were favored with disturbance and responded positively to light availability in disturbed sites. Models showed species primarily dispersed by wind were more prevalent in disturbed patches and sites than those dispersed by endozoochory, while seed mass had no effect.</p>
Probabilistic genetic identification of wild boar hybridization to support control of invasive wild pigs (Sus scrofa)
<p>The rapid expansion of wild pigs (<em>Sus scrofa</em>) throughout the United States (US) has been fueled by unlawful introductions, with invasive populations causing extensive crop losses, damaging native ecosystems, and serving as a reservoir for disease. Multiple states have passed laws prohibiting the possession or transport of wild pigs. However, genetic and phenotypic similarities between domestic pigs and invasive wild pigs – which overwhelmingly represent domestic pig-wild boar hybrids – pose a challenge for the enforcement of such regulations. We sought to exploit wild boar ancestry as a common attribute among the vast majority of invasive wild pigs as a means of genetically differentiating wild pigs from breeds of domestic pigs found within the US. We organized reference high-density single nucleotide polymorphism genotypes (1,039 samples from 33 domestic breeds and 382 samples from 16 wild boar populations) into five genetically cohesive reference groups: mixed-commercial breeds, Durocs, heritage breeds, primitive breeds, and wild boar. Building upon well-established genetic clustering approaches, we structured the test statistic to describe the difference in the likelihood of a given genotype's ancestry vectors (<em>sensu</em> genetic clustering analysis) if derived strictly from the four described domestic pig reference groups versus allowing for admixture from the wild boar group. By fitting statistical distributions to test statistics of reference domestic pigs, we characterized the distribution of the null hypothesis – that a given genotype descends strictly from domestic pig reference groups. We tested the approach with simulated genotypes and empirical data from an additional 29 breeds of domestic pig represented by 435 unique genotypes; all associated test statistics for simulated and empirical domestic pig challenge sets fell within the distribution of reference domestic pigs. We then evaluated 6,566 invasive wild pigs sampled across the contiguous United States, of which 63% exceeded the maximum threshold for domestic pigs and could be statistically classified as possessing wild boar ancestry. This approach provides a scientific foundation to enforce regulations prohibiting the possession of this destructive invasive species. Further, this computationally efficient and generalizable approach could be readily adapted to quantify gene flow among ecological systems of conservation or management concern.</p>
An inbreeding perspective on the effectiveness of wildlife population defragmentation measures: A case study on wild boar (Sus scrofa) of Veluwe, The Netherlands
<p>Pervasive inbreeding is a major genetic threat of population fragmentation and can undermine the efficacy of population connectivity measures. Nevertheless, few studies have evaluated whether wildlife crossings can alleviate the frequency and length of genomic autozygous segments. Here, we provided a genomic inbreeding perspective on the potential effectiveness of mammal population defragmentation measures. We applied a SNP-genotyping case study on the ~2500 wild boar Sus scrofa population of Veluwe, The Netherlands, a 1000-km<sup>2 </sup>Natura 2000 protected area with many fences and roads but also, increasingly, fence openings and wildlife crossings. We combined a 20K genotyping assessment of genetic status and migration rate with a simulation that examined the potential for alleviation of isolation and inbreeding. We found that Veluwe wild boar subpopulations are significantly differentiated (FST-values of 0.02-0.07) and have low levels of gene flow. One noteworthy exception was the Central and Southeastern subpopulation, which were nearly panmictic and appeared to be effectively connected through a highway wildlife overpass. Estimated effective population sizes were at least 85 for the meta-population and ranging from 31 to 52 for the subpopulations. All subpopulations, including the two connected subpopulations, experienced substantial inbreeding, as evidenced through the occurrence of many long homozygous segments. Simulation output indicated that whereas one or few migrants per generation could undo genetic differentiation and boost effective population sizes rapidly, genomic inbreeding was only marginally reduced. The implication is that ostensibly successful connectivity restoration projects may fail to alleviate genomic breeding of fragmented mammal populations. We put forward that defragmentation projects should allow for (i) monitoring of levels of differentiation, migration and genomic inbreeding, (ii) anticipation of the inbreeding status of the meta-population, and, if inbreeding levels are high and/or haplotypes have become fixed, (iii) consideration of enhancing migration and gene flow among meta-populations, possibly through translocation.</p>
T a b l e 4 in Changes In The Trophic Structure Of The Vertebrate Predator Community In The Cold Season In Belarussian Paazerje (Northern Belarus) With Emphasis On Depopulation Of The Wild Boar, Sus Scrofa (Artiodactyla, Suida)
T a b l e 4. Dietary overlaps (the Morisita's index) between vertebrate predators in the cold season in coniferous-small-leaved forests of Belarussian Paazerje, Northern Belarus, upper right corner — before a depopulation of the Wild Boar (1982–2011), bottom left corner — aft er a large-scale depopulation of the Wild Boar (2013–2019)
Fig. 2 in Changes In The Trophic Structure Of The Vertebrate Predator Community In The Cold Season In Belarussian Paazerje (Northern Belarus) With Emphasis On Depopulation Of The Wild Boar, Sus Scrofa (Artiodactyla, Suida)
Fig. 2. Th e Golden and White-tailed Eagles feed regularly on carrion and physical interference takes place quite often.
Fig. 1 in Changes In The Trophic Structure Of The Vertebrate Predator Community In The Cold Season In Belarussian Paazerje (Northern Belarus) With Emphasis On Depopulation Of The Wild Boar, Sus Scrofa (Artiodactyla, Suida)
Fig. 1. Dietary similarity of 17 vertebrate predators in the cold season in Belarussian Paazerje, 1972–2012.
Fig. 4 in Changes In The Trophic Structure Of The Vertebrate Predator Community In The Cold Season In Belarussian Paazerje (Northern Belarus) With Emphasis On Depopulation Of The Wild Boar, Sus Scrofa (Artiodactyla, Suida)
Fig. 4. Dietary similarity of 10 vertebrate predators in the cold season in Belarussian Paazerje, 2013–2019.
Fig. 1 in Short communication First documented observation of differential dorsoventral coat colouration in wild boar Sus scrofa (Artyodactyla: Suidae) in Italy
Fig. 1 - The juvenile wild boar object of this note showing the differential dorsoventral colouration pattern (right) next another wild-type individual (left). Additional footage available at: https://youtu.be/gTc0BFSE9kA. / Il giovane esemplare di cinghiale oggetto di questa nota in cui è visibile il pattern cromatico a demarcazione dorsoventrale (a destra) accanto a un altro individuo con la tipica colorazione marrone uniforme (a sinistra). È anche disponibile un filmato aggiuntivo: https://youtu.be/ gTc0BFSE9kA. (Photo and video: / Foto e video: Francesco Gallozzi).
Fig. 1 in Trichinella species circulating in wild boar (Sus scrofa) populations in Poland
Fig. 1. Example of electrophoretic patterns obtained from multiplex PCR on Trichinella larvae collected from wild boar. Lane 1 and 8 molecular weight marker (Fermentas 100 bp DNA Ladder); lanes 2 and 4, T. spiralis; lanes 3 and 5, T. britovi; lane 6, T. spiralis and T. britovi mixed infection; lane 7, negative control.
Fig. 2 in Seroprevalence of Toxoplasma gondii in wild boars (Sus scrofa) hunted in Ukraine
Fig. 2. Box plot of Toxoplasma gondii serology results from wild boars from Ukraine, obtained using a locally available enzyme-linked immunosorbent assay and majority criteria based on results of three tests (locally available enzyme-linked immunosorbent assay (ELISA), commercial ELISA (ID Screen Toxoplasmosis Indirect Multi-Species), and an indirect immunofluorescence test (IFAT)). ELISA proportion (OD sample/mean OD of positive controls *100) using the locally available ELISA is on the Y-axis and majority criteria is on the X-axis.
Fig. 1 in Seroprevalence of Toxoplasma gondii in wild boars (Sus scrofa) hunted in Ukraine
Fig. 1. Seroprevalence of Toxoplasma gondii infection among wild boars by region in Ukraine, based on results from a locally available enzyme-linked immunosorbent assay (ELISA). For regions with at least one seropositive wild boar, the number of seropositive wild boards out of number of tested wild boars is shown.
Fig. 2 in Hepatozoon apri n. sp. (Adeleorina: Hepatozoidae) from the Japanese wild boar Sus scrofa leucomystax (Mammalia: Cetartiodactyla)
Fig. 2. Inflammatory lesion with released merozoites or gamonts in the femoral muscle of Japanese wild boar.
Fig. 1. a–b in Hepatozoon apri n. sp. (Adeleorina: Hepatozoidae) from the Japanese wild boar Sus scrofa leucomystax (Mammalia: Cetartiodactyla)
Fig. 1. a–b) Gamonts of Hepatozoon apri n. sp. in the cytoplasm of neutrophils detected in the blood smear of a boar (ID: 28-11), showing acentric and rounded nuclei (arrows) and a small protrusion containing eosinophilic granules (arrowheads).
Fig. 4 in Hepatozoon apri n. sp. (Adeleorina: Hepatozoidae) from the Japanese wild boar Sus scrofa leucomystax (Mammalia: Cetartiodactyla)
Fig. 4. Phylogenetic analysis of Hepatozoon apri n. sp. based on 18S rDNA sequences (522-bp). Adelina dimidiata (accession no. DQ096835) was chosen as the outgroup to root the phylogeny. Neighbor-joining (NJ) and maximum likelihood (ML) analysis showing the phylogenetic relationships among boar isolates and two Hepatozoon spp. (KF318170, KF318171) detected in Dermacentor ticks collected from wild boar in Thailand. Sequences included in the comparison were downloaded from the DDBJ/EMBL/GenBank databases. Filled circles indicate Hepatozoon species reported from Japan. Nodal support values based on 1000 bootstrap replicates (NJ/ML) are represented on the ML tree. Scale bar represents 0.01 nucleotide substitutions per site.
Fig. 3. a–d in Hepatozoon apri n. sp. (Adeleorina: Hepatozoidae) from the Japanese wild boar Sus scrofa leucomystax (Mammalia: Cetartiodactyla)
Fig. 3. a–d) Various developmental stages of Hepatozoon apri n. sp. detected in the muscles. a) A trophozoite (arrow) in the femoral muscles. The outer layer contains a fibroblast-like nucleus (arrowhead). b–c) Immature meronts found in the heart. d) Mature meront in the femoral muscles. H&E stain. Bar = 20 μm.
Fig. 4 in Cystic echinococcosis in wild boars (Sus scrofa) from southern Italy: Epidemiological survey and molecular characterization
Fig. 4. Distribution of the 93 positive wild boars in the study area and details of prevalence, provinces, regional and national parks.
Figure 7 in Mitochondrial DNA control region variability of wild boar Sus scrofa with various external phenotypes in Turkey
Figure 7. Median-joining network of 68 haplotypes from 485 wild boars from different regions of the world. Circle sizes are proportional to haplotype frequencies and numbers refer to haplotype codes in Table 2. Numbers on the branches indicate the number of nucleotide substitutions, if more than one. Major haplogroups are delimited by dashed lines. A, Asian; NE, Near Eastern; E1, European E1; E2, European E2. Haplotypes exclusive to Turkey are labeled in green.
Figure 3 in Mitochondrial DNA control region variability of wild boar Sus scrofa with various external phenotypes in Turkey
Figure 3. Maximum likelihood phylogenetic tree of haplotypes of the Turkish wild boars (Sus scrofa) obtained in the present study, based on the partial D-loop sequences of mtDNA. Numbers above or below branches indicate bootstrap values. TR numbers refer to current haplotype numbers in Table 1 and H numbers refer to the published haplotype labels downloaded from GenBank (Table 2). E1: European 1 haplogroup/clade in Figure 5, NE: Near East haplogroup/ clade in Figure 5.
Figure 2 in Mitochondrial DNA control region variability of wild boar Sus scrofa with various external phenotypes in Turkey
Figure 2. Various phenotypes of obtained Turkish wild boar individuals from different localities studied presently.
Figure 6 in Mitochondrial DNA control region variability of wild boar Sus scrofa with various external phenotypes in Turkey
Figure 6. Bayesian inference tree based on 68 partial D-loop haplotypes of 485 wild boars (both obtained in this study and downloaded from GenBank). Posterior probabilities are indicated at nodes. Haplogroups: A, Asian; NE, Near Eastern; E1, European E1; E2, European E2. Outgroup taxa are Sus barbatus and Phacochoerus aethiopicus.
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