7 datasets found
  1. d

    Polioptila californica genotype data from California, USA and Baja...

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). Polioptila californica genotype data from California, USA and Baja California, Mexico [Dataset]. https://catalog.data.gov/dataset/polioptila-californica-genotype-data-from-california-usa-and-baja-california-mexico
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    U.S. Geological Survey
    Area covered
    United States, Mexico, California, Baja California
    Description

    This dataset contains genomic records from 184 California Gnatcatchers (Polioptila californica) collected at 18 sites in southern California (USA), 13 sites in Baja California (Mexico), and 17 sites in Baja California Sur (Mexico). Genomic markers were generated from ddRAD loci (Peterson and others, 2012) and analyzed using the Stacks v2.53 (Catchen and others, 2013) pipeline. The genotypes for all samples are provided in a VCF file with 84,125 independent loci and 7 percent missing data. A companion file is provided with sample names and occurrence designations. These files may be opened and edited in a text editor program, such as Notepad (PC) or BBEdit (Mac). The .vcf file can be loaded into the Stacks population program (Catchen and others, 2013) to calculate genetic diversity statistics, or loaded into R, using vcfR (Knaus and Grunwald, 2017), for further analysis. References: Catchen J., Hohenlohe P.A., Bassham S., Amores A., Cresko W.A. Stacks-an analysis tool set for population genomics. Molecular Ecology. 2013; 22:3124-3140. Knaus, B.J, Grunwald N.J. vcfr: a package to manipulate and visualize variant call format data in R. Molecular Ecology Resources. 2016; 17:44-53. Peterson B.K., Weber J.N., Kay E.H., Fisher H.S., Hoekstra H.E. Double Digest RADseq-an inexpensive method for de novo SNP discovery and genotyping in model and non-model species: PLoS ONE. 2012; 7:e37135.

  2. d

    The North American Breeding Bird Survey in Mexico, 2008-2018 — unprocessed...

    • catalog.data.gov
    • data.usgs.gov
    Updated Jul 6, 2024
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    U.S. Geological Survey (2024). The North American Breeding Bird Survey in Mexico, 2008-2018 — unprocessed data [Dataset]. https://catalog.data.gov/dataset/the-north-american-breeding-bird-survey-in-mexico-2008-2018-unprocessed-data
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Mexico
    Description

    This dataset includes all North American Breeding Bird Survey data collected in Mexico between 2008-2018. These data were used as the basis for all analyses discussed in an associated publication: The North American Breeding Bird Survey in Mexico, 2008-2018 — A Status Report; https:doi.org/10.3133/cir1479. The records include avian point count data for all reported taxa (species, races, and unidentified species groupings). In addition to avian count data, this dataset also contains survey date, survey start and end times, start and end weather conditions, a unique observer identification number, route identification information, and route location information including country, state, and BCR, as well as geographic coordinates of each route's start location. These data were collected annually during the breeding season, primarily in May, June and July, along randomly established roadside survey routes in seven states in northern Mexico (Baja California Sur, Baja California, Sonora, Chihuahua, Coahuila, Nuevo León and Tamaulipas). Routes are roughly 24.5 miles (39.2 km) long with counting locations placed at approximately half-mile (800-m) intervals, for a total of 50 stops. A brief summary of the methodology is as follows: At each stop a person highly skilled in avian identification conducts a 3-minute point count, recording every bird seen within a quarter-mile (400-m) radius, or heard at any distance (excluding birds believed to have been recorded at a previous stop). Surveys begin 30 minutes before local sunrise and take approximately 5 hours to complete. Routes are sampled once per year. NOTE: The data in this release include all records reported. They have not been subjected to the rigorous quality control screening that BBS data from the U.S. and Canada receive. Therefore, these data are NOT intended to be lumped with U.S. and Canada data for pooled population analyses.

  3. b

    Kelletia kelletii size-frequency population survey data collected by...

    • bco-dmo.org
    • datacart.bco-dmo.org
    Updated Mar 12, 2025
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    Crow White (2025). Kelletia kelletii size-frequency population survey data collected by scientific SCUBA divers at 36 kelp forest habitat sites across the species’ biogeographic range in 2015, 2016 and 2017 [Dataset]. http://doi.org/10.26008/1912/bco-dmo.955710.1
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    Dataset updated
    Mar 12, 2025
    Dataset provided by
    Biological and Chemical Data Management Office
    Authors
    Crow White
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 16, 2015 - Aug 17, 2017
    Area covered
    Variables measured
    H_E, lat, lon, Size_mm, Mex0_US1, SiteCode, SiteName, IslandCode, IslandName, SiteNumber, and 5 more
    Description

    Sizes of Kellet’s whelk (Kelletia kelletii) individuals in populations in the wild were obtained from subtidal benthic surveys conducted by scientific SCUBA divers at kelp forest habitat sites across the species’ biogeographic range and over multiple years. The survey data was collected in 2015, 2016 and 2017 during summer months from 36 benthic kelp forest sites, from Monterey Bay, California, USA to Isla Asuncion, Baja California Sur, Mexico.

  4. f

    Description of tagging data utilized in this study with total deployment...

    • plos.figshare.com
    xls
    Updated Jun 5, 2023
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    Sofia Ortega-Garcia; Christopher R. Perle; Nicholas M. Whitney; Ruben Rodriguez-Sanchez; John O’Sullivan; Stephanie Snyder Koch (2023). Description of tagging data utilized in this study with total deployment duration reflected in the dates at liberty. [Dataset]. http://doi.org/10.1371/journal.pone.0276873.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Sofia Ortega-Garcia; Christopher R. Perle; Nicholas M. Whitney; Ruben Rodriguez-Sanchez; John O’Sullivan; Stephanie Snyder Koch
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Sample sizes for diurnal and 24-hr periods reflect the number of periods with sufficient data to classify behavior.

  5. d

    Size-based, spatially explicit, stochastic demographic model for green...

    • search.dataone.org
    • bco-dmo.org
    Updated Dec 5, 2021
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    Giulio Alessandro De Leo; James P. Barry; Stephen G. Monismith; Clifton Brock Woodson; Steven Y. Litvin (2021). Size-based, spatially explicit, stochastic demographic model for green abalone [Dataset]. https://search.dataone.org/view/sha256%3Af4cbd48cd89e3d199a397c0a044115c7fafdcdcf1cbe26f093695bd1c4570d98
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    Dataset updated
    Dec 5, 2021
    Dataset provided by
    Biological and Chemical Oceanography Data Management Office (BCO-DMO)
    Authors
    Giulio Alessandro De Leo; James P. Barry; Stephen G. Monismith; Clifton Brock Woodson; Steven Y. Litvin
    Description

    [2017-08-28]: The metadata for this dataset page is in progress.

    R code and associated data for a size-based, spatially explicit, stochastic demographic model to explore how different spatial configurations of marine reserve (MR) networks can affect the abundance and commercial yield of the green abalone (Haliotis fulgens), taking as a reference case the abalone fishery of Isla Natividad in Baja California Sur (Mexico).

    The model code is available in as .zip file: Rossetto_etal_2015_CJFAS-1.0.zip containing R-files. These files are also available in the following GitHub repository: Rossetto_etal_2015_CJFAS (release 1.0).

    The model and results were described in the following publication:

    Rossetto, M., Micheli, F., Saenz-Arroyo, A., Montes, J. A. E., & De Leo, G. A. (2015). No-take marine reserves can enhance population persistence and support the fishery of abalone. Canadian Journal of Fisheries and Aquatic Sciences, 72(10), 1503-1517. https://doi.org/10.1139/cjfas-2013-0623

  6. b

    Abalone recruitment data from Baja California and Baja California Sur,...

    • bco-dmo.org
    csv
    Updated Oct 18, 2023
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    Fiorenza Micheli; Arturo Hernández-Velasco; Laura Rogers-Bennett; Alexandra Smith (2023). Abalone recruitment data from Baja California and Baja California Sur, Mexico in 2019 [Dataset]. http://doi.org/10.26008/1912/bco-dmo.907383.1
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    csv(188.95 KB)Available download formats
    Dataset updated
    Oct 18, 2023
    Dataset provided by
    Biological and Chemical Data Management Office
    Authors
    Fiorenza Micheli; Arturo Hernández-Velasco; Laura Rogers-Bennett; Alexandra Smith
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 18, 2019 - Jun 25, 2019
    Area covered
    Variables measured
    lat, Bouy, Site, date, long, depth, camera, divers, number, size_mm, and 6 more
    Measurement technique
    Camera, Self-Contained Underwater Breathing Apparatus
    Description

    Abalone support commercial and recreational fishery, however their population have decline dramatically since 1950's. To understand the recruitment of abalone populations, standarized abalone recruitment modules made of half cinder blocks inside cages were deployed in Baja California and Baja California Sur, Mexico. 12 cages were deployed at three sites (i.e., El Rosario, Isla Natividad and La Bocana) in Mexico. The abundances of abalone and invertebrates found in the cages were checked after 12months. This dataset presents all the information collected from the cages deployed at three sites (El Rosario, Isla Natividad and La Bocana) in Baja California and Baja California Sur, Mexico.

  7. W

    Mexico - Datos de Población y Vivienda 2010

    • cloud.csiss.gmu.edu
    • data.amerigeoss.org
    zip
    Updated Jun 18, 2019
    + more versions
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    UN Humanitarian Data Exchange (2019). Mexico - Datos de Población y Vivienda 2010 [Dataset]. https://cloud.csiss.gmu.edu/uddi/mn_MN/dataset/mexico-datos-de-poblacion-y-vivienda-2010
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    zipAvailable download formats
    Dataset updated
    Jun 18, 2019
    Dataset provided by
    UN Humanitarian Data Exchange
    Area covered
    Мексик
    Description

    Contiene información de la población y las viviendas captada en el Censo del 2010, sobre los siguientes entidades federativas: Oaxaca, Baja California Sur, Sinaloa, Jalisco, Guerrero, Nayarit, Michoacán de Ocampo, Colima

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U.S. Geological Survey (2024). Polioptila californica genotype data from California, USA and Baja California, Mexico [Dataset]. https://catalog.data.gov/dataset/polioptila-californica-genotype-data-from-california-usa-and-baja-california-mexico

Polioptila californica genotype data from California, USA and Baja California, Mexico

Explore at:
Dataset updated
Jul 6, 2024
Dataset provided by
U.S. Geological Survey
Area covered
United States, Mexico, California, Baja California
Description

This dataset contains genomic records from 184 California Gnatcatchers (Polioptila californica) collected at 18 sites in southern California (USA), 13 sites in Baja California (Mexico), and 17 sites in Baja California Sur (Mexico). Genomic markers were generated from ddRAD loci (Peterson and others, 2012) and analyzed using the Stacks v2.53 (Catchen and others, 2013) pipeline. The genotypes for all samples are provided in a VCF file with 84,125 independent loci and 7 percent missing data. A companion file is provided with sample names and occurrence designations. These files may be opened and edited in a text editor program, such as Notepad (PC) or BBEdit (Mac). The .vcf file can be loaded into the Stacks population program (Catchen and others, 2013) to calculate genetic diversity statistics, or loaded into R, using vcfR (Knaus and Grunwald, 2017), for further analysis. References: Catchen J., Hohenlohe P.A., Bassham S., Amores A., Cresko W.A. Stacks-an analysis tool set for population genomics. Molecular Ecology. 2013; 22:3124-3140. Knaus, B.J, Grunwald N.J. vcfr: a package to manipulate and visualize variant call format data in R. Molecular Ecology Resources. 2016; 17:44-53. Peterson B.K., Weber J.N., Kay E.H., Fisher H.S., Hoekstra H.E. Double Digest RADseq-an inexpensive method for de novo SNP discovery and genotyping in model and non-model species: PLoS ONE. 2012; 7:e37135.

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