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179 results for “buffalo”
Fig. 1 in Epidemiology of Anaplasma marginale and Anaplasma centrale infections in African buffalo (Syncerus caffer) from Kruger National Park, South Africa
Fig. 1. The proportion of animals infected with Anaplasma spp. from a managed African buffalo (Syncerus caffer) herd from Kruger National Park, South Africa. a) The mean prevalence of animals with A. marginale single infection, A. centrale single infection, or co-infections with each other over four age groups: calves (0–1 years old), sub-adults (1–5.5 years old), adults (5.5–15 years) and geriatrics (15 years plus); b) the mean prevalence of new infections with A. marginale or A. centrale for each capture event over the two-and-a-half-year study period. Numbers at the top of figure represent sample size.
Fig. 3 in Epidemiology of Anaplasma marginale and Anaplasma centrale infections in African buffalo (Syncerus caffer) from Kruger National Park, South Africa
Fig. 3. Patterns of infection with Anaplasma spp. based on age and sex for a managed African buffalo (Syncerus caffer) herd from Kruger National Park, South Africa. a) The infection intensity (log-transformed number of copies/reaction) of A. marginale and A. centrale based on age (years); b) overall proportion of animals infected with A. marginale or A. centrale based on sex; c) infection intensity (log-transformed number of copies/reaction) results for A. marginale or A. centrale based on sex. * indicates statistical significance (p <0.05). Error bars are standard error.
Linked collectors and determiners for: Buffalo Society of Natural Sciences Clinton Herbarium.
Natural history specimen data linked to collectors and determiners held within, "Buffalo Society of Natural Sciences Clinton Herbarium". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/17d312c2-9ab3-4aca-a383-6af5fb79dca0">https://bionomia.net/dataset/17d312c2-9ab3-4aca-a383-6af5fb79dca0</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/17d312c2-9ab3-4aca-a383-6af5fb79dca0">https://gbif.org/dataset/17d312c2-9ab3-4aca-a383-6af5fb79dca0</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Buffalo Society of Natural Sciences Ornithology.
Natural history specimen data linked to collectors and determiners held within, "Buffalo Society of Natural Sciences Ornithology". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/147e1b93-9e2d-43a2-a34d-18738edeaa24">https://bionomia.net/dataset/147e1b93-9e2d-43a2-a34d-18738edeaa24</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/147e1b93-9e2d-43a2-a34d-18738edeaa24">https://gbif.org/dataset/147e1b93-9e2d-43a2-a34d-18738edeaa24</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Buffalo Society of Natural Sciences Conchology.
Natural history specimen data linked to collectors and determiners held within, "Buffalo Society of Natural Sciences Conchology". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/d984cc71-7248-416a-8648-6aea17153b36">https://bionomia.net/dataset/d984cc71-7248-416a-8648-6aea17153b36</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/d984cc71-7248-416a-8648-6aea17153b36">https://gbif.org/dataset/d984cc71-7248-416a-8648-6aea17153b36</a>. Formatted as a Frictionless Data package.
Wood Buffalo Environmental Association (WBEA) Historical Monitoring Data used in "Passive Tracer Modelling at Super-Resolution with WRF-ARW to Assess Mass-Balance Schemes"
<p>Wood Buffalo Environmental Association (WBEA) Historical Monitoring Data from two monitoring stations Bertha Ganter – Fort McKay and Barge Landing for 20 August 2013 to 2 September 2013. This data was used in "Passive Tracer Modelling at Super-Resolution with WRF-ARW to Assess Mass-Balance Schemes" (Fathi et al., 2022 - egusphere-2022-1125) for model output and observational data comparisons. The same data can be accessed and downloaded from "<a href="https://wbea.org/historical-monitoring-data/">https://wbea.org/historical-monitoring-data/</a>".</p>
Campus Pond (Buffalo Creek Watershed) Data from 2022-07-08 to 2022-09-01
<p>General Metadata for Campus Pond Sampling Station</p> <p>Files</p> <p>Specific metadata for each deployment and sensor can be found as text files with the file format of:</p> <pre><code>BC_CampusPond_YYYY-MM-DD_YYYY-MM-DD_metadata.txt</code></pre> <p>Where YYYY-MM-DD_YYYY-MM-DD is the date range of the sampling period.</p> <p>NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab <a href="https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts">https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts</a>.</p> <p>File Created</p> <ul> <li>2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md</li> </ul> <p>File Modified</p> <p>Description</p> <p>These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702).</p> <p>All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a></p> <p>Station Specifics</p> <p>The specific sensors at the site are:</p> <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> <p>The sensors are sampled every 15 minutes</p> <p>Measurement Parameters, units, and Variable Names</p> <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT - the temperature (dC) from the DO or conductivity. * WaterTemp - the water temperature measured from the pressure transducer in the water (dC). * AirTemp - the air temperature measured from the pressure transducer (BP sensor) in the air (dC). * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
Campus Pond (Buffalo Creek Watershed) Data from 2022-06-13 to 2022-07-08
<p>General Metadata for Campus Pond Sampling Station</p> <p>Files</p> <p>Specific metadata for each deployment and sensor can be found as text files with the file format of:</p> <pre><code>BC_CampusPond_YYYY-MM-DD_YYYY-MM-DD_metadata.txt</code></pre> <p>Where YYYY-MM-DD_YYYY-MM-DD is the date range of the sampling period.</p> <p>NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab <a href="https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts">https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts</a>.</p> <p>File Created</p> <ul> <li>2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md</li> </ul> <p>File Modified</p> <p>Description</p> <p>These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702).</p> <p>All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a></p> <p>Station Specifics</p> <p>The specific sensors at the site are:</p> <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> <p>The sensors are sampled every 15 minutes</p> <p>Measurement Parameters, units, and Variable Names</p> <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT - the temperature (dC) from the DO or conductivity. * WaterTemp - the water temperature measured from the pressure transducer in the water (dC). * AirTemp - the air temperature measured from the pressure transducer (BP sensor) in the air (dC). * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
Chalgrove Lake (Buffalo Creek Watershed) Data from 2022-06-28 to 2022-08-05
<p>General Metadata for Chalgrove Lake YSI Data</p> <p>Files</p> <p>Specific metadata for each deployment can be found as text files with the file format of:</p> <pre><code>BC_chalgrove_lake_YYYY-MM-DD_YYYY-MM-DD_metadata.txt</code></pre> <p>Where YYYY-MM-DD_YYYY-MM-DD is the date range of the deployment.</p> <p>File Created</p> <ul> <li>2019-04-12 by KF</li> </ul> <p>File Modified</p> <ul> <li>2019-10-31 by KF - added the descriptions of the total algae variables</li> <li>2022-05-04 by KF - updated to match LEO standards and current deployment specs</li> <li>2022-05-23 by KF - updated to include Total Algae Sensor information</li> </ul> <p>Description</p> <p>These data are from a YSI EXO2 multiparameter sonde deployed at approximatly 0.7 m in Chalgrove Lake (37.242983 N, -78.464116 W) in approximately 4 m of water.</p> <p>Sonde Specifics</p> <p>The specific sensors and SNs deployed are on the metadata specific to each deployment but generally the sonde has:</p> <ul> <li>Temperature</li> <li>Conductivity</li> <li>pH</li> <li>ODO</li> <li>Turbidity</li> <li>Total Algae</li> </ul> <p>Measurement Parameters, units, and Variable Names</p> <ul> <li>date.time = the combined date and time of the measurement (YYYY-MM-DD HH:MM:SS)</li> <li>date = the sampling date reported by the YSI (M/D/YYYY)</li> <li>time = the sampling time reported by the YSI (HH:MM:SS)</li> <li>frac_sec = the sampling fractions of a second reported by the YSI</li> <li>site_name = the site name on the YSI deployment (left blank)</li> <li>Cond = the conductivity (uS/cm)</li> <li>Chl_RFU = the raw fluorescence of the chlorophyll sensor (RFU)</li> <li>nLF_Cond = the nLF conductivity (uS/cm)</li> <li>DO_perc = the percent oxygen saturation</li> <li>DO_percL = the percent local oxygen saturation</li> <li>DO_mgL = the dissolved oxygen concentration (mg/L)</li> <li>SAL = the salinity (psu)</li> <li>SPC = the specific conductivity (uS/cm)</li> <li>TAL_PC_RFU = the raw fluorescence of the phycocyanin (blue green algae) sensor (RFU)</li> <li>TDS = the total dissolved solids (mg/L)</li> <li>Turbidity = the turbidity of the water (FNU)</li> <li>TSS = the total suspended solids</li> <li>pH = the pH</li> <li>pH_mV = the millivolts of the pH sensor</li> <li>Temp = the temperature (dC)</li> <li>Batt_V = the battery voltage</li> <li>Cable_V = the cable power</li> </ul>
Chalgrove Lake (Buffalo Creek Watershed) Date from 2022-05-20 to 2022-06-28
<p>General Metadata for Chalgrove Lake YSI Data</p> <p>Files</p> <p>Specific metadata for each deployment can be found as text files with the file format of:</p> <pre><code>BC_chalgrove_lake_YYYY-MM-DD_YYYY-MM-DD_metadata.txt</code></pre> <p>Where YYYY-MM-DD_YYYY-MM-DD is the date range of the deployment.</p> <p>File Created</p> <ul> <li>2019-04-12 by KF</li> </ul> <p>File Modified</p> <ul> <li>2019-10-31 by KF - added the descriptions of the total algae variables</li> <li>2022-05-04 by KF - updated to match LEO standards and current deployment specs</li> <li>2022-05-23 by KF - updated to include Total Algae Sensor information</li> </ul> <p>Description</p> <p>These data are from a YSI EXO2 multiparameter sonde deployed at approximatly 0.7 m in Chalgrove Lake (37.242983 N, -78.464116 W) in approximately 4 m of water.</p> <p>Sonde Specifics</p> <p>The specific sensors and SNs deployed are on the metadata specific to each deployment but generally the sonde has:</p> <ul> <li>Temperature</li> <li>Conductivity</li> <li>pH</li> <li>ODO</li> <li>Turbidity</li> <li>Total Algae</li> </ul> <p>Measurement Parameters, units, and Variable Names</p> <ul> <li>date.time = the combined date and time of the measurement (YYYY-MM-DD HH:MM:SS)</li> <li>date = the sampling date reported by the YSI (M/D/YYYY)</li> <li>time = the sampling time reported by the YSI (HH:MM:SS)</li> <li>frac_sec = the sampling fractions of a second reported by the YSI</li> <li>site_name = the site name on the YSI deployment (left blank)</li> <li>Cond = the conductivity (uS/cm)</li> <li>Chl_RFU = the raw fluorescence of the chlorophyll sensor (RFU)</li> <li>nLF_Cond = the nLF conductivity (uS/cm)</li> <li>DO_perc = the percent oxygen saturation</li> <li>DO_percL = the percent local oxygen saturation</li> <li>DO_mgL = the dissolved oxygen concentration (mg/L)</li> <li>SAL = the salinity (psu)</li> <li>SPC = the specific conductivity (uS/cm)</li> <li>TAL_PC_RFU = the raw fluorescence of the phycocyanin (blue green algae) sensor (RFU)</li> <li>TDS = the total dissolved solids (mg/L)</li> <li>Turbidity = the turbidity of the water (FNU)</li> <li>TSS = the total suspended solids</li> <li>pH = the pH</li> <li>pH_mV = the millivolts of the pH sensor</li> <li>Temp = the temperature (dC)</li> <li>Batt_V = the battery voltage</li> <li>Cable_V = the cable power</li> </ul>
Chalgrove Lake (Buffalo Creek Watershed) Data from 2022-08-05 to 2022-09-19
<p>General Metadata for Chalgrove Lake YSI Data</p> <p>Files</p> <p>Specific metadata for each deployment can be found as text files with the file format of:</p> <pre><code>BC_chalgrove_lake_YYYY-MM-DD_YYYY-MM-DD_metadata.txt</code></pre> <p>Where YYYY-MM-DD_YYYY-MM-DD is the date range of the deployment.</p> <p>File Created</p> <ul> <li>2019-04-12 by KF</li> </ul> <p>File Modified</p> <ul> <li>2019-10-31 by KF - added the descriptions of the total algae variables</li> <li>2022-05-04 by KF - updated to match LEO standards and current deployment specs</li> <li>2022-05-23 by KF - updated to include Total Algae Sensor information</li> </ul> <p>Description</p> <p>These data are from a YSI EXO2 multiparameter sonde deployed at approximatly 0.7 m in Chalgrove Lake (37.242983 N, -78.464116 W) in approximately 4 m of water.</p> <p>Sonde Specifics</p> <p>The specific sensors and SNs deployed are on the metadata specific to each deployment but generally the sonde has:</p> <ul> <li>Temperature</li> <li>Conductivity</li> <li>pH</li> <li>ODO</li> <li>Turbidity</li> <li>Total Algae</li> </ul> <p>Measurement Parameters, units, and Variable Names</p> <ul> <li>date.time = the combined date and time of the measurement (YYYY-MM-DD HH:MM:SS)</li> <li>date = the sampling date reported by the YSI (M/D/YYYY)</li> <li>time = the sampling time reported by the YSI (HH:MM:SS)</li> <li>frac_sec = the sampling fractions of a second reported by the YSI</li> <li>site_name = the site name on the YSI deployment (left blank)</li> <li>Cond = the conductivity (uS/cm)</li> <li>Chl_RFU = the raw fluorescence of the chlorophyll sensor (RFU)</li> <li>nLF_Cond = the nLF conductivity (uS/cm)</li> <li>DO_perc = the percent oxygen saturation</li> <li>DO_percL = the percent local oxygen saturation</li> <li>DO_mgL = the dissolved oxygen concentration (mg/L)</li> <li>SAL = the salinity (psu)</li> <li>SPC = the specific conductivity (uS/cm)</li> <li>TAL_PC_RFU = the raw fluorescence of the phycocyanin (blue green algae) sensor (RFU)</li> <li>TDS = the total dissolved solids (mg/L)</li> <li>Turbidity = the turbidity of the water (FNU)</li> <li>TSS = the total suspended solids</li> <li>pH = the pH</li> <li>pH_mV = the millivolts of the pH sensor</li> <li>Temp = the temperature (dC)</li> <li>Batt_V = the battery voltage</li> <li>Cable_V = the cable power</li> </ul>
Campus Pond (Buffalo Creek Watershed) Data from 2022-05-11 to 2022-06-13
<p>General Metadata for Campus Pond Sampling Station</p> <p>Files</p> <p>Specific metadata for each deployment and sensor can be found as text files with the file format of:</p> <pre><code>BC_CampusPond_YYYY-MM-DD_YYYY-MM-DD_metadata.txt</code></pre> <p>Where YYYY-MM-DD_YYYY-MM-DD is the date range of the sampling period.</p> <p>NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab <a href="https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts">https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts</a>.</p> <p>File Created</p> <ul> <li>2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md</li> </ul> <p>File Modified</p> <p>Description</p> <p>These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702).</p> <p>All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a></p> <p>Station Specifics</p> <p>The specific sensors at the site are:</p> <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> <p>The sensors are sampled every 15 minutes</p> <p>Measurement Parameters, units, and Variable Names</p> <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT - the temperature (dC) from the DO or conductivity. * WaterTemp - the water temperature measured from the pressure transducer in the water (dC). * AirTemp - the air temperature measured from the pressure transducer (BP sensor) in the air (dC). * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
Fig. 1 in Seroprevalence of Toxoplasma gondii infection from water buffaloes (Bubalus bubalis) in northeastern and southern Thailand
Fig. 1. Epidemiological seroprevalence of Toxoplasma gondii (Nicolle et Manceaux, 1908) in water buffaloes from northeastern and southern Thailand. Figures in parentheses are seroprevalence/number of farms/number of samples/population size.
Selected large model output files and Buffalo sounding data from: Lake Huron enhances snowfall downwind of Lake Erie: a modeling study of the 2010 near year’s Lake-effect snowfall event
Open the record for dataset details and reuse information.
Simulated trajectories of city population: Levy walks along Buffalo, NY, street network
<p>Simulated trajectories of the full 2000 census population of Buffalo, New York. Each simulated person was placed randomly along a road within his or her census tract of residence and then independently performed road-network-constrained, truncated Lévy walks for 8 hours of simulated time, moving at 4 km per hour. The trajectories were then sampled at 30 minute intervals. The original dataset was created for studying indexes of activity-space segregation. It is archived at <a href="https://zenodo.org/record/2865830#.XpYviKsza00">https://zenodo.org/record/2865830#.XpYviKsza00</a> and described more fully in Palmer (2013), Activity-Space Segregation: Understanding Social Divisions in Space and Time (http://arks.princeton.edu/ark:/88435/dsp01k643b130h).</p> <p>This version has been created to aid in testing contact-tracing apps and mobility analysis tools. The fields are:</p> <p>latitude: latitude</p> <p>longitude: longitude</p> <p>time: UNIX time in milliseconds</p> <p>ID: random ID assigned to each individual</p>
Data from: A natural gene drive system influences bovine tuberculosis susceptibility in African buffalo: possible implications for disease management
Bovine tuberculosis (BTB) is endemic to the African buffalo (Syncerus caffer) of Hluhluwe-iMfolozi Park (HiP) and Kruger National Park, South Africa. In HiP, the disease has been actively managed since 1999 through a test-and-cull procedure targeting BTB-positive buffalo. Prior studies in Kruger showed associations between microsatellite alleles, BTB and body condition. A sex chromosomal meiotic drive, a form of natural gene drive, was hypothesized to be ultimately responsible. These associations indicate high-frequency occurrence of two types of male-deleterious alleles (or multiple-allele haplotypes). One type negatively affects body condition and BTB resistance in both sexes. The other type has sexually antagonistic effects: negative in males but positive in females. Here, we investigate whether a similar gene drive system is present in HiP buffalo, using 17 autosomal microsatellites and microsatellite-derived Y-chromosomal haplotypes from 401 individuals, culled in 2002-2004. We show that the association between autosomal microsatellite alleles and BTB susceptibility detected in Kruger, is also present in HiP. Further, Y-haplotype frequency dynamics indicated that a sex chromosomal meiotic drive also occurred in HiP. BTB was associated with negative selection of male-deleterious alleles in HiP, unlike positive selection in Kruger. Birth sex ratios were female-biased. We attribute negative selection and female-biased sex ratios in HiP to the absence of a Y-chromosomal sex-ratio distorter. This distorter has been hypothesized to contribute to positive selection of male-deleterious alleles and male-biased birth sex ratios in Kruger. As previously shown in Kruger, microsatellite alleles were only associated with male-deleterious effects in individuals born after wet pre-birth years; a phenomenon attributed to epigenetic modification. We identified two additional allele types: male-specific deleterious and beneficial alleles, with no discernible effect on females. Finally, we discuss how our findings may be used for breeding disease-free buffalo and implementing BTB test-and-cull programs.
Data from: Genetic responsiveness of African buffalo to environmental stressors: a role for epigenetics in balancing autosomal and sex chromosome interactions?
In the African buffalo (Syncerus caffer) population of the Kruger National Park (South Africa) a primary sex-ratio distorter and a primary sex-ratio suppressor have been shown to occur on the Y chromosome. A subsequent autosomal microsatellite study indicated that two types of deleterious alleles with a negative effect on male body condition, but a positive effect on relative fitness when averaged across sexes and generations, occur genome-wide and at high frequencies in the same population. One type negatively affects body condition of both sexes, while the other acts antagonistically: it negatively affects male but positively affects female body condition. Here we show that high frequencies of male-deleterious alleles are attributable to Y-chromosomal distorter-suppressor pair activity and that these alleles are suppressed in individuals born after three dry pre-birth years, likely through epigenetic modification. Epigenetic suppression was indicated by statistical interactions between pre-birth rainfall, a proxy for parental body condition, and the phenotypic effect of homozygosity/heterozygosity status of microsatellites linked to male-deleterious alleles, while a role for the Y-chromosomal distorter-suppressor pair was indicated by between-sex genetic differences among pre-dispersal calves. We argue that suppression of male-deleterious alleles results in negative frequency-dependent selection of the Y distorter and suppressor; a prerequisite for a stable polymorphism of the Y distorter-suppressor pair. The Y distorter seems to be responsible for positive selection of male-deleterious alleles during resource-rich periods and the Y suppressor for positive selection of these alleles during resource-poor periods. Male-deleterious alleles were also associated with susceptibility to bovine tuberculosis, indicating that Kruger buffalo are sensitive to stressors such as diseases and droughts. We anticipate that future genetic studies on African buffalo will provide important new insights into gene fitness and epigenetic modification in the context of sex-ratio distortion and infectious disease dynamics.
Thai water buffalo vessel, c. 1000 BCE
Thai ceremonial vessel, c. 1000 BCE, now in the collection of the Minneapolis Institute of Art. From its description on artsmia.org: *'This extraordinary ceremonial vessel, one of a group, was discovered in the Lopburi–Pa Sak basin in central Thailand. The oldest settlements in this region date back over three thousand years and have yielded several important Neolithic objects. While a few ceramic depictions of animals in Neolithic and Bronze Age Thailand are known, this water buffalo, which stands as the centerpiece of the group, exhibits an originality, creativity, and superb workmanship that has no comparison in early Thai ceramic art. It is also the largest pottery buffalo known from this period.'* More information: https://collections.artsmia.org/art/12963/ceremonial-vessel-thailand Source: Objaverse 1.0 / Sketchfab
Pathogen group-specific risk factors for intra-mammary infection in water buffalo
<p>A cross-sectional study was conducted to estimate the prevalence of intra-mammary infection (IMI) associated bacteria and to identify risk factors for pathogen group-specific IMI in water buffalo in Bangladesh. A California Mastitis Test (CMT) and bacteriological cultures were performed on 1,374 quarter milk samples collected from 763 water buffalo from 244 buffalo farms in nine districts in Bangladesh. Quarter, buffalo, and farm-related data were obtained through questionnaires and visual observations. A total of 618 quarter samples were found to be culture-positive. Non-<em>aureus</em> staphylococci were the predominant IMI-associated bacterial species, and <em>Staphylococcus </em>(<em>S.</em>)<em> chromogenes</em>, <em>S. hyicus</em>, and <em>S. epidermidis </em>were the most common bacteria found. The proportion of non-aureus staphylococci or <em>Mammaliicoccus sciuri</em> (NASM), <em>S. aureus</em>, and other bacterial species identified in the buffalo quarter samples varied between buffalo farms. Therefore, different management practices, buffalo breeding factors, and nutrition were considered and further analyzed when estimating the IMI odds ratio (OR). The odds of IMI by any pathogen (OR: 1.8) or by NASM (OR: 2.2) were high in buffalo herds with poor milking hygiene. Poor cleanliness of the hind quarters had a high odds of IMI caused by any pathogen (OR: 2.0) or NASM (OR: 1.9). Twice daily milking (OR: 3.1) and farms with buffalo purchased from another herd (OR: 2.0) were associated with IMI by any pathogen. Asymmetrical udders were associated with IMI-caused by any bacteria (OR: 1.7). A poor body condition score showed higher odds of IMI by any pathogen (OR: 1.4) or by NASM (OR: 1.7). This study shows that the prevalence of IMI in water buffalo was high and varied between farms. In accordance with the literature, our data highlight that IMI can be partly controlled through better farm management, primarily by improving hygiene, milking management, breeding, and nutrition.</p>
Microsatellite data from various African buffalo (Syncerus caffer) populations throughout Africa
<p>1280 African buffalo (<em>Syncerus caffer</em>) samples genotyped with up to 19 microsatellites. 1275 samples are from East (12 populations) and southern Africa (4 populations). 5 samples are from central Africa (2 populations).</p>
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