Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
292
datasets available to search
ShareScore release 0.9.0
Dataset results
292 results for “Livestock”
Supplementary Table 1. Raw data of egg quality parameters for 990 egg samples with ATOL (Animal Trait Ontology for Livestock) descriptors, as function of hen age, pen no. and genotype in 15 replicates.
<p>Data table of egg quality parameters</p>
Supplementary data to publication "Growth efficiency, intestinal biology, and nutrient utilization and requirements of black soldier fly (Hermetia illucens) larvae compared to monogastric livestock species: a review"
<p>The datasets provided in the excel file were used to generate Table 2 and Fig. 2 in the publication entitled "Growth efficiency, intestinal biology, and nutrient utilization and requirements of black soldier fly (Hermetia illucens) larvae compared to monogastric livestock species: a review" by Seyedalmoosavi et al., 2022 published in Journal of Animal Science and Biotechnology. https://doi.org/10.1186/s40104-022-00682-7</p>
The oropharyngeal microbiome of COPD patients and controls in a livestock dense area
<p>This ready to load <strong>phyloseq</strong> R S4 object contains the ASV table, taxonomy table and sample metadata. This dataset was build using the DaDa2 (version 1.6.0) and phyloseq (version 1.223) R packages using our raw MiSeq PE300 sequencing data deposited at NCBI-SRA under BioProject: PRJNA810336. Additional metadata is available upon request. </p> <p><strong>Study</strong></p> <p>Air pollution from livestock farms is a known respiratory health risk for patients with chronic obstructive pulmonary disease (COPD). We hypothesize that air pollutants could affect respiratory health through modulation of the airway microbiome. Therefore, we studied determinants of the oropharyngeal microbiota (OPM) composition of COPD patients and controls in a livestock-dense area.</p> <p>Oropharyngeal swabs were collected from 99 community-based (mostly mild) COPD cases and 184 controls (baseline), and after 6 and 12 weeks. Participants were non-smokers or former smokers, Annual average livestock-related outdoor air pollution at the home address was predicted using dispersion modeling. OPM composition was analyzed using 16S rRNA-based sequencing in all baseline samples and 6-week and 12-week repeated samples of 20 randomly selected subjects (n=323 samples).</p> <p>Case-control status was not associated with community structure while correcting for known confounders (multivariate PERMANOVA p>0.05). However, members of the genus <em>Streptococcus</em> were more abundant in the COPD group (Benjamini-Hochberg adjusted p<0.01). Both farm-emitted endotoxin and PM<sub>10 </sub>levels were associated with increased richness in COPD patients (p<0.05). Procrustes analysis showed a moderate correlation between ordinations (Principal coordinates analysis of Bray-Curtis dissimilarity) of 20 subjects analyzed at 0, 6, and 12 weeks (r=0.52 to 0.66; p<0.05) indicating that the OPM is relatively stable over a 12 week period and that a single sample sufficiently represents the OPM.</p> <p>Results show modest differences in OPM of community-based COPD patients compared to controls. Livestock-related air pollution was associated with OPM diversity of COPD patients. </p>
Quantifying the relationship between prey density, livestock and illegal killing of leopards
<p>Many large mammalian carnivores are facing population declines due to illegal killing (e.g., shooting) and habitat modification (e.g., livestock farming). Illegal killing occurs cryptically and hence is difficult to detect. However, reducing illegal killing requires a solid understanding of its magnitude and underlying drivers, while accounting for the imperfect detection of illegal killing events. Despite the importance of illegal killing of large carnivores in comparison with other causes of mortality, its relationship with <span>potential</span> drivers such as livestock density and wild prey abundance is rarely described.</p> <p>Using ranger-collected data (2007-2019) of leopard killing events and data on covariates (livestock density, wild prey abundance, road length, protected area size, elevation) across Iran, we applied a single-visit N-mixture model to jointly model variation in detection probability and expected annualized number of leopard killing events.</p> <p>Over the study period, we estimated 428 leopard mortalities (95% CI 184–1014), which was 45% larger than the observed number. Expected intensity of leopard killing was positively related to protected area size, livestock density and wild prey abundance. Detection of leopard killing was higher in areas with more developed road networks.</p> <p><strong>Synthesis and applications</strong></p> <p>Ranger based monitoring data on poaching of carnivores are cost-effective, but traditional analysis does not take into account imperfect detection. We show that innovative statistics (single-visit N-mixture modeling) can reliably quantify poaching events and address their drivers, at large geographical scales. We used the example of the Persian leopard across Iran, but our approach is also applicable to understand killing dynamics of other species. Results suggest that a high frequency of leopard killing is likely to occur in areas with > 100 livestock per km<sup>2</sup> and > 450 individuals of wild prey per km<sup>2</sup>. This highlights the need for improved management of livestock grazing and effective measures around high-risk protected areas to mitigate human-leopard conflict and reduce killing of leopards.</p>
Data for 'Global trends in grassland carrying capacity and relative stocking density of livestock'
<p><strong>This collection contains all data needed to reproduce maps presented in the following publication (<em>please cite that when using the data</em>):</strong></p> <p>Piipponen, J., Jalava, M., de Leeuw, J., Rizayeva, A., Godde, C., Cramer, G., Herrero, M., & Kummu, M. (2022). Global trends in grassland carrying capacity and relative stocking density of livestock. <em>Global Change Biology</em>, <em>28</em>(12), 3902–3919. <a href="https://doi.org/10.1111/gcb.16174">https://doi.org/10.1111/gcb.16174</a></p> <p>A detailed description of files, as well as references and licences related to input/output/supplementary data, can be found in the file <em>List_of_provided_files.txt</em>.</p> <p>All relevant source codes are available in GitHub: <a href="https://github.com/jpiippon/cc_rsd_repo">https://github.com/jpiippon/cc_rsd_repo</a></p> <p>*Note that data for most of the output maps, such as AGB, CC and RSD can be found in simulation_results_n1000.csv inside Output.7z. See R script figures.Rmd in GitHub for converting this file to raster format and plotting.</p>
Ecological determinants of rabies virus dynamics in vampire bats and spillover to livestock
<p>Data and scripts for the publication</p>
Harmonized livestock number dataset for Europe
<p>This dataset comprises spatial and temporal data on ruminant livestock distributions on detailed spatial level. We collected statistics on cattle, sheep and goats distribution for 43 countries and territories in Europe: for 31 countries and territories we collected data on the level of local administrative units, for 8 countries on regional level (NUTS 3), and on national level (NUTS 0) for 4 countries. We provide data for over 73 thousand administrative units, making them more detailed than publicly provided by the European Statistical Office (which reports data for 325 adminstrative units). The data are available for the periods corresponding to 2000, 2010 and 2020.</p> <p><strong>Harmonizing to livestock units:</strong></p> <p>We harmonized the data to livestock units (LSU), making them easy to use and compare between different countries and regions. We used livestock coefficients provided by EUROSTAT (https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:Livestock_unit_(LSU) ) to harmonize numbers of different livestock types, with more detail on the processing provided in the accompanying data_sources.xlsx file.<br><br><strong>File description:</strong></p> <p>The data-set consists of the following files:</p> <ul> <li>a spreadsheet describing in detail the sources of data and how the data was processed (file <a href="../api/records/11058509/draft/files/data_sources.xlsx/content" target="_blank" rel="noopener noreferrer">data_sources.xlsx</a>)</li> <li>three geopackage files (archived as a zip file) for each year (2000, 2010, 2020) for harmonized ruminant livestock numbers for all 43 countries and territories (<a href="../api/records/11058509/draft/files/livestock2000.zip/content" target="_blank" rel="noopener noreferrer">livestock2000.zip</a>, <a href="../api/records/11058509/draft/files/livestock2010.zip/content" target="_blank" rel="noopener noreferrer">livestock2010.zip</a>, <a href="../api/records/11058509/draft/files/livestock2020.zip/content" target="_blank" rel="noopener noreferrer">livestock2020.zip</a> )</li> <li>three geopackage files (archived as a zip file) for each year (2000, 2010, 2020) for sheep and goats for Poland (as the numbers are provided on a different level for these two livestock type for Poland) (<a href="../api/records/11058509/draft/files/poland_sheep_goats2000.zip/content" target="_blank" rel="noopener noreferrer">poland_sheep_goats2000.zip</a> , <a href="../api/records/11058509/draft/files/poland_sheep_goats2010.zip/content" target="_blank" rel="noopener noreferrer">poland_sheep_goats2010.zip</a> , <a href="../api/records/11058509/draft/files/poland_sheep_goats2020.zip/content" target="_blank" rel="noopener noreferrer">poland_sheep_goats2020.zip</a> )</li> <li>a geopackage file (archived as a zip file) with (estimated) shares of cattle grazing for each country, in many cases for subnational units (<a href="../api/records/11058509/draft/files/grazing_share.zip/content" target="_blank" rel="noopener noreferrer">grazing_share.zip</a> )</li> </ul> <p><strong>Source information:</strong></p> <p>The raw data on livestock numbers are available from each country individually, and we provide the sources in the data_sources.xlsx file , to enable future updates.</p> <p> </p> <div> <p>This dataset has been created as part of LAMASUS Project under the scope of Deliverable 2.1 titled "The LUM Geodatabase and Area Estimates of Land Use Change to 2018 ". The full text of the deliverable can be accessed via: <a href="https://www.lamasus.eu/wp-content/uploads/LAMASUS_D2.1_LUMGeodatabase.pdf">https://www.lamasus.eu/wp-content/uploads/LAMASUS_D2.1_LUMGeodatabase.pdf.</a></p> </div>
Supplementary File 8; The full data set derived from formal quantitative surveys of land cover types and activities of humans, livestock and wildlife (Section 2.3) that were used for the analyses described in sections 2.4, 2.5 and 2.7
Open the record for dataset details and reuse information.
Figure 3 in Distribution of tick species parasitizing livestock in Sirumalai, The Eastern Ghats of Tamil Nadu, South India and its implications for public health
Figure 3. Images of ticks collected from Sirumalai foot hill villages.
Figure 2 in Distribution of tick species parasitizing livestock in Sirumalai, The Eastern Ghats of Tamil Nadu, South India and its implications for public health
Figure 2. Tick infestation rate in cattle, dogs and sheep.
Figure 1. A in Distribution of tick species parasitizing livestock in Sirumalai, The Eastern Ghats of Tamil Nadu, South India and its implications for public health
Figure 1. A map of the Sirumalai ticks collected areas.
Fig. 3 in Value of forest remnants for montane amphibians on the livestock grazed Mount Mbam, Cameroon
Fig. 3. Species accumulation curves of Mount Mbam by land use based on contemporary records.
Shrub influence on soil carbon and nitrogen in a semi-arid grassland is mediated by precipitation and largely insensitive to livestock grazing
<p>Dryland (arid and semi-arid) ecosystems globally provide more than half of livestock production and store roughly one-third of soil organic carbon (SOC). Biogeochemical pools are changing due toshrub encroachment, livestock grazing, and climate change. We assessed how vegetation microsite, grazing, and precipitation interacted to affect SOC and total nitrogen (TN) at a site with long-term grazing manipulations and well-described patterns of shrub encroachment across elevation and mean annual precipitation (MAP) gradients. We analyzed SOC and TN in the context of vegetation cover at ungrazed locations within livestock exclosures, high-inten- sity grazing locations near water sources, and moderate-intensity grazing locations away from water. SOC was enhanced by MAP (p<0.0001), but grazing intensity had little effect regardless of MAP (p = 0.12). Shrubs enhanced SOC (300–1279 g C m2) and TN (27–122 g N m2), except at high MAP where the contribution or stabilization of shrub inputs relative to grassland inputs was likely diminished. Cover of perennial herbaceous plants and litter were significant predictors of SOC (r2 = 0.63 and 0.34, respectively) and TN (r2 = 0.64 and 0.30, respectively). Our results suggest that continued shrub encroachment in drylands can increase SOC storage when grass production remains high, although this response may saturate with higher MAP. In contrast, grazing – at least at the intensities of our sites – has a lesser effect. These effects underscore the need to understand how future climate and grazing may interact to influence dryland biogeochemical cycling.</p>
FIG. 4 in Rodents in grassland habitats: does livestock grazing matter? A comparison of two Alpine sites with different grazing histories
FIG. 4. — Apodemus Spp. caught during the study.
Trypanosoma cruzi in Mexican Neotropical vectors and mammals: Wildlife, livestock, pets, and human population
<p><span>The aim of the present study has been to provide primary evidence of <em>Trypanosoma cruzi</em> landscape genetics in the Mexican Neotropics.</span><span> <em>T. cruzi</em> and DTU prevalence were analyzed in landscape communities of vectors, wildlife, livestock, pets, and sympatric human populations using endpoint PCR and sequencing of all relevant amplicons from mitochondrial (kDNA) and nuclear (ME, 18S, 24Sα) gene markers. Although 98% of the infected sample set (N=2963) contained single or mixed infections of DTUI (TcI, 96.2%) and TcVI (22.6%), TcIV and TcII were identified. The sensitivity of individual markers varied and was dependent on the host taxon; kDNA, ME, and 18S combined identified 95% of infections. ME genotyped 90% of vector infections, but 60% of mammals (36% wildlife), while neither 18S nor 24Sα typed more than 20% of mammal infections. Available gene fragments to identify or genotype <em>T. cruzi</em> are not universally sensitive for all landscape parasite populations, highlighting important <em>T. cruzi</em> heterogeneity among mammal reservoir taxa and triatomine species.</span></p>
Evaluating livestock farmers' knowledge, beliefs, and management of arboviral diseases in Kenya
<p>Globally, arthropod-borne virus (arbovirus) infections continue to pose substantial threats to public health and economic development, especially in developing countries. In Kenya, although arboviral diseases (ADs) are largely endemic, little is known about the factors influencing livestock farmers' knowledge, beliefs, and management (KBM) of the three major ADs: Rift Valley fever (RVF), dengue fever and chikungunya fever. This study evaluates the drivers of livestock farmers' KBM of ADs from a sample of 629 respondents selected using a three-stage sampling procedure in Kenya's three hotspot counties of Baringo, Kwale, and Kilifi. </p>
Intensified livestock farming increases antibiotic resistance genotypes and phenotypes in animal feces
<p class="MsoNormal"><span>Animal feces from livestock farming can be a major source of antibiotic resistance to the environment, but a clear gap exists on how the resistance reservoir in feces alters as farming activities intensify. Here, we sampled feces from eight Chinese farms, where yak, sheep, pig, and horse were reared under free-range to intensive conditions, and determined fecal resistance using both genotype and phenotype approaches. </span><span>A</span><span>nimals reared </span><span><span>intensively</span></span><span> exhibited increased </span><span><span>diversity</span></span><span> of antibiotic resistance genes (ARGs) and greater resistance phenotypes in feces, which were cross-correlated. Furthermore, a</span><span>t the metagenome contig level, ARGs</span><span> </span><span>were </span><span><span>co-located</span></span><span> with </span><span>mobile genetic elements </span><span>at a higher frequency (27.38%) </span><span>as farming intensified, </span><span>with</span><span> associated resistance phenotyp</span><span><span>e</span></span><span>s </span><span>being less coupled with bacterial phylogeny. </span><span>I</span><span>ntensified farming also expanded the multidrug resistance preferentially carried on pathogens in fecal microbi</span><span>omes</span><span><span>.</span></span><span> Overall, </span><span><span>farming intensification </span></span><span>can </span><span><span>increase </span></span><span>antibiotic resistance</span><span> <span>genotypes and phenotypes in </span></span><span>domestic animal </span><span><span>feces</span></span><span>, with implications for environmental health.</span></p> <p> </p>
Fencing farm dams to exclude livestock halves methane emissions and improves water quality
<p>Agricultural practices have created tens of millions of small artificial water bodies ("farm dams" or "agricultural ponds") to provide water for domestic livestock worldwide. Among freshwater ecosystems, farm dams have some of the highest greenhouse gas (GHG) emissions per m<sup>2</sup> due to fertilizer and manure run-off boosting methane production – an extremely potent GHG. However, management strategies to mitigate the substantial emissions from millions of farm dams remain unexplored. We tested the hypothesis that installing fences to exclude livestock could reduce nutrients, improve water quality, and lower aquatic GHG emissions. We established a large-scale experiment spanning 400 km across south-eastern Australia where we compared unfenced (N = 33) and fenced farm dams (N = 31) within 17 livestock farms. Fenced farm dams recorded 32% less dissolved nitrogen, 39% less dissolved phosphorus, 22% more dissolved oxygen, and produced 56% less diffusive methane emissions than unfenced dams. We found no effect of farm dam management on diffusive carbon dioxide emissions and on the organic carbon in the soil. Dissolved oxygen was the most important variable explaining changes in carbon fluxes across dams, whereby doubling dissolved oxygen from 5 to 10 mg L<sup>-1</sup> led to a 74% decrease in methane fluxes, a 124% decrease in carbon dioxide fluxes, and a 96% decrease in CO<sub>2</sub>-eq (CH<sub>4</sub> + CO<sub>2</sub>) fluxes. Dams with very high dissolved oxygen (>10 mg L<sup>-1</sup>) showed a switch from positive to negative CO<sub>2</sub>-eq. (CO<sub>2</sub> + CH<sub>4</sub>) fluxes (i.e., negative radiative balance), indicating a positive contribution to reducing atmospheric warming. Our results demonstrate that simple management actions can dramatically improve water quality and decrease methane emissions while contributing to more productive and sustainable farming.</p>
Complete bacterial assemblies for 'Enterobacterales plasmid sharing amongst human bloodstream infections, livestock, wastewater, and waterway niches in Oxfordshire, UK'
<p>Complete bacterial assemblies from the journal article 'Matlock, William, et al. "<em>Enterobacterales</em> plasmid sharing amongst human bloodstream infections, livestock, wastewater, and waterway niches in Oxfordshire, UK." <em>Elife</em> 12 (2023): e85302.'</p> <p>'assemblies.zip' contains assemblies for <em>n</em>=1,458 isolates with circularised chromosomes and <em>n</em>=3,697 circularised plasmids.</p> <p><strong>If you use this data please cite the journal article <em>and</em> the Zenodo DOI. </strong></p>
Long-term livestock exclusion increases plant richness and reproductive capacity in arid woodlands
<p><strong>Aim</strong></p> <p>Herbivore exclusion is implemented globally to recover ecosystems from grazing by introduced and native herbivores, but evidence for large-scale biodiversity benefits is inconsistent in arid ecosystems. We examined the effects of livestock exclusion on dryland plant richness and reproductive capacity.</p> <p><strong>Location</strong></p> <p>Central Australia.</p> <p><strong>Methods</strong></p> <p>We collected data on plant species richness and seeding (reproductive capacity), rainfall, vegetation productivity and cover, soil health, and herbivore grazing intensity from 68 sites across 6500 km<sup>2</sup> of arid Georgina gidgee (<em>Acacia</em> <em>georginae</em>) woodlands between 2017 and 2020. Sites were on an actively grazed cattle station and two destocked conservation reserves. We used structural equation modelling to examine indirect (via soil or vegetation modification) versus direct (herbivory) effects of grazing intensity by two introduced herbivores (cattle, camels) and a native herbivore (red kangaroo), on seasonal plant species richness and seeding.</p> <p><strong>Results</strong></p> <p>Soil health and rainfall were the strongest drivers of variation in richness and seeding. Cattle and camel grazing indirectly led to lower seasonal richness and seeding by reducing soil health. Kangaroos had a small but negative direct impact on richness, but no impact on soil health. Both introduced and native herbivores reduced annual chenopod shrub richness and seeding, whereas only cattle directly reduced perennial shrub richness and seeding. Camels indirectly reduced perennial shrub richness by impacting shrub abundance. Introduced herbivores reduced native grass richness and seeding indirectly via impacts on soil health, whereas forbs responded positively to cattle and camel activity.</p> <p><strong>Main conclusion</strong></p> <p>Considering indirect impacts improves evaluations of the effects of disturbances on biodiversity, as focusing only on direct effects can mask critical mechanisms of change. Our results indicate substantial biodiversity benefits from excluding livestock and controlling camels in drylands. Reducing introduced herbivore impacts will improve soil and vegetation condition, ensure reproduction and seasonal persistence of species, and protect native plant diversity.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.