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6 results for “cattle density”
Spatial distribution of cattle, sheep and goat density, and grazed areas for the European Union and the United Kingdom
<p>To improve the sustainability of the European livestock sector we need improved knowledge on livestock density, and also on the grazing patterns. Here we provide spatially explicit data on the distribution of cattle, sheep and goats, developed by combining agricultural and veterinary statistics, in-situ data, expert surveys and machine learning. The data allow for the differentiation between livestock that are grazing on semi-natural areas and managed grasslands, versus those that do not graze and are kept indoors. </p> <p>This dataset covers all European Union Member States and the United Kingdom, and presents the spatial distribution of cattle, sheep and goat density for approximately the year 2020. Livestock density was allocated on the Corine Land Cover data, resulting in a data-set with a 100 m resolution (EPSG: 3035 - ETRS89-extended / LAEA Europe).</p> <p>Together with the livestock density maps, we also provide spatial data on the probability for grazing, and allocated grazed and non grazed areas.</p> <p><strong>File description:</strong></p> <p>The data-set consists of the following files:</p> <p> </p> <ul> <li><strong>clc_forage_mask.tif</strong> , forage areas mask for EU, based on selected Corine Land Cover classes (not including seminatural land cover areas such as natural grasslands...). This was developed by surveying grazing, grassland and livestock experts from all EU Member States and the United Kingdom. More info in the upcoming paper and in the linked paper below (Malek et al. 2024). Values are the same as in the Corine Land Cover data.</li> <li><strong>grazing_probability.tif</strong> , grazing probability map, indicating how likely each location in the EU+UK is grazed</li> <li><strong>allocated_grazing.tif</strong> , allocated grazing map, indicating which areas are grazed and which are not</li> </ul> <p> </p> <ul> <li>cattle density maps: <ul> <li><strong>cattle_grazing.tif</strong> , cattle grazing on managed forage areas</li> <li><strong>cattle_other.tif</strong> , cattle kept indoors, receiving feed from managed forage areas</li> <li><strong>cattle_seminatural.tif</strong> , cattle grazing in semi-natural areas</li> <li><strong>cattle_mosaic_categorical.tif</strong> (with a legend file) , combined categorical map for all cattle types.</li> </ul> </li> </ul> <p> </p> <ul> <li>sheep and goat density maps: <ul> <li><strong>sheep_goat_other.tif</strong> , sheep and goat density</li> <li><strong>sheep_goat_seminatural.tif </strong>, sheep and goat grazing in seminatural areas</li> </ul> </li> </ul>
Spatio-temporal distribution of LSD outbreaks in the Balkan region since deecember 2016 until November 2017 and cattle density (animals/square km)
<p>The European Food Safety Authority (EFSA), under request of the European Commission, performed an epidemiological analysis of the lumpy skin disease (LSD) epidemics based on the data collected from the affected and at-risk Member States and non-EU countries in south-eastern Europe. Spatial and temporal (monthly) distribution of LSD outbreaks reported in the Balkan region between December 2016 and November 2017 and cattle density (animals/square km) shown as green shade (for Bosnia and Herzegovina data at regional level are not available). LSD outbreaks were reported in this time frame only in Albania, the former Yugoslav Republic of Macedonia and Greece. Red and grey dots indicate new and past outbreaks, respectively.</p> <p>*This designation is without prejudice to positions on status and is in line with UNSCR 1244 and the ICJ Opinion on the Kosovo Declaration of Independence</p>
The Genomic Reference Resource for African Cattle: genome sequences and high-density array variants.
<p><em>The diversity in genome resources is fundamental to designing genomic strategies for local breed improvement and utilisation. These resources also support gene discovery and enhance our understanding of the mechanisms of resilience with applications beyond local breeds. We report here the genome sequences of 573 samples (198 new genomes) and high-density (HD) array genotyping of 1,082 samples (537 new samples) from indigenous African cattle populations. The new sequences have an average genome coverage of ~30X, three times higher than the average (~10X) of the over 300 sequences already in the public domain. Following variant quality checks, we identified approximately 32.4 million sequence variants and 661,943 HD autosomal variants mapped to the Bos taurus reference genome (ARS-UCD1.2). The new datasets were generated as part of the Centre for Tropical Livestock Genetic and Health (CTLGH) Genomic Reference Resource for African Cattle (GRRFAC) initiative, which aspires to facilitate the generation of this livestock resource. We hope this resource will be utilised by the global scientific community and breeders for sustainable global livestock improvement.</em></p>
Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis
<p>Native cattle breeds can carry specific signatures of selection reflecting their adaptation to the local environmental conditions and response to the breeding strategy used. In this study, we comprehensively analysed high-density single nucleotide polymorphism (SNP) genotypes to characterise the population structure and detect the selection signatures in Russian native Yaroslavl and Kholmogor dairy cattle breeds, which have been little influenced by introgression with transboundary breeds. Fifty-six samples of pedigree-recorded purebred animals, originating from different breeding farms and representing different sire lines, of the two studied breeds were genotyped using a genome-wide bovine genotyping array (Bovine HD BeadChip). Three statistical analyses—calculation of fixation index (<i>F</i><sub>ST</sub>) for each SNP for the comparison of the pairs of breeds, hapFLK analysis, and estimation of the runs of homozygosity (ROH) islands shared in more than 50% of animals—were combined for detecting the selection signatures in the genome of the studied cattle breeds. We confirmed nine and six known regions under putative selection in the genomes of Yaroslavl and Kholmogor cattle, respectively; the flanking positions of most of these regions were elucidated. Only two of the selected regions (localised on BTA 14 at 24.4–25.1 Mbp and on BTA 16 at 42.5–43.5 Mb) overlapped in Yaroslavl, Kholmogor and Holstein breeds. In addition, we detected three novel selection sweeps in the genome of Yaroslavl (BTA 4 at 4.74–5.36 Mbp, BTA 15 at 17.80–18.77 Mbp, and BTA 17 at 45.59–45.61 Mbp) and Kholmogor breeds (BTA 12 at 82.40–81.69 Mbp, BTA 15 at 16.04–16.62 Mbp, and BTA 18 at 0.19–1.46 Mbp) by using at least two of the above-mentioned methods. We expanded the list of candidate genes associated with the selected genomic regions and performed their functional annotation. We discussed the possible involvement of the identified candidate genes in artificial selection in connection with the origin and development of the breeds. Our findings on the Yaroslavl and Kholmogor breeds obtained using high-density SNP genotyping and three different statistical methods allowed the detection of novel putative genomic regions and candidate genes that might be under selection. These results might be useful for the sustainable development and conservation of these two oldest Russian native cattle breeds.</p>
Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis
Open the record for dataset details and reuse information.
Genome-wide identification of copy number variations in Holstein cattle from Baja California, Mexico, using high-density SNP genotyping arrays
GEO Series GSE54813. Bos taurus. 12 samples. Type: Genome variation profiling by SNP array; SNP genotyping by SNP array.
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