Spatial predictions of habitat suitability for present-day (1950 – 2000 yr) and mid-Holocene (8.3 ka – 4.2 ka) time intervals

This dataset provides spatial predictions of habitat suitability for current (1950 – 2000 yr) and mid-Holocene (8.3 ka – 4.2 ka) intervals using hindcasting, and three separate paleo-distributions calibrated on the packrat midden archive: those without bias correction (naïve), those created with a standard method (standard), and those created with a novel alternative (modeled) incorporating a three-stage model of bias. The raster layers contained here accompany the manuscript Inman et al. 2018 and were used to evaluate utility of a novel bias correction method (modeled) over classic methods. Spatial predictions of habitat suitability were created using MaxEnt version 3.4.0 (Phillips et al., 2006), a widely-used software for SDM in presence-background frameworks. Detailed methods are provided in Inman et al. 2018. The files within the zipped folder are as listed below: Abies_concolor_midHolocene_hindcast_mean.asc, Abies_concolor_midHolocene_hindcast_stderr.asc, Abies_concolor_midHolocene_modeled_mean.asc, Abies_concolor_midHolocene_modeled_stderr.asc, Abies_concolor_midHolocene_naive_mean.asc, Abies_concolor_midHolocene_naive_stderr.asc, Abies_concolor_midHolocene_standard_mean.asc, Abies_concolor_midHolocene_standard_stderr.asc, Abies_concolor_PresentDay_mean.asc, Abies_concolor_PresentDay_stderr.asc, Artemisia_tridentata_midHolocene_hindcast_mean.asc, Artemisia_tridentata_midHolocene_hindcast_stderr.asc, Artemisia_tridentata_midHolocene_modeled_mean.asc, Artemisia_tridentata_midHolocene_modeled_stderr.asc, Artemisia_tridentata_midHolocene_naive_mean.asc, Artemisia_tridentata_midHolocene_naive_stderr.asc, Artemisia_tridentata_midHolocene_standard_mean.asc, Artemisia_tridentata_midHolocene_standard_stderr.asc, Artemisia_tridentata_PresentDay_mean.asc, Artemisia_tridentata_PresentDay_stderr.asc, Coleogyne_ramosissima_midHolocene_hindcast_mean.asc, Coleogyne_ramosissima_midHolocene_hindcast_stderr.asc, Coleogyne_ramosissima_midHolocene_modeled_mean.asc, Coleogyne_ramosissima_midHolocene_modeled_stderr.asc, Coleogyne_ramosissima_midHolocene_naive_mean.asc, Coleogyne_ramosissima_midHolocene_naive_stderr.asc, Coleogyne_ramosissima_midHolocene_standard_mean.asc, Coleogyne_ramosissima_midHolocene_standard_stderr.asc, Coleogyne_ramosissima_PresentDay_mean.asc, Coleogyne_ramosissima_PresentDay_stderr.asc, Juniperus_communis_midHolocene_hindcast_mean.asc, Juniperus_communis_midHolocene_hindcast_stderr.asc, Juniperus_communis_midHolocene_modeled_mean.asc, Juniperus_communis_midHolocene_modeled_stderr.asc, Juniperus_communis_midHolocene_naive_mean.asc, Juniperus_communis_midHolocene_naive_stderr.asc, Juniperus_communis_midHolocene_standard_mean.asc, Juniperus_communis_midHolocene_standard_stderr.asc, Juniperus_communis_PresentDay_mean.asc, Juniperus_communis_PresentDay_stderr.asc, Pinus_ponderosa_midHolocene_hindcast_mean.asc, Pinus_ponderosa_midHolocene_hindcast_stderr.asc, Pinus_ponderosa_midHolocene_modeled_mean.asc, Pinus_ponderosa_midHolocene_modeled_stderr.asc, Pinus_ponderosa_midHolocene_naive_mean.asc, Pinus_ponderosa_midHolocene_naive_stderr.asc, Pinus_ponderosa_midHolocene_standard_mean.asc, Pinus_ponderosa_midHolocene_standard_stderr.asc, Pinus_ponderosa_PresentDay_mean.asc, Pinus_ponderosa_PresentDay_stderr.asc, Quercus_gambelii_midHolocene_hindcast_mean.asc, Quercus_gambelii_midHolocene_hindcast_stderr.asc, Quercus_gambelii_midHolocene_modeled_mean.asc, Quercus_gambelii_midHolocene_modeled_stderr.asc, Quercus_gambelii_midHolocene_naive_mean.asc, Quercus_gambelii_midHolocene_naive_stderr.asc, Quercus_gambelii_midHolocene_standard_mean.asc, Quercus_gambelii_midHolocene_standard_stderr.asc, Quercus_gambelii_PresentDay_mean.asc, Quercus_gambelii_PresentDay_stderr.asc These data support the following publication: Inman et al., 2018, Spatial sampling bias in the Neotoma paleoecological archives affects species paleo-distribution models. Quaternary Science Reviews. xxx.xxx. References: Phillips, S.J., Anderson, R.P., Schapire, R.E., 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling 190, 231–259. doi:10.1016/j.ecolmodel.2005.03.026

                                            [
  "010:12"
]
                                        

                                            {
  "fn": "Richard Inman",
  "@type": "vcard:Contact",
  "hasEmail": "mailto:rdinman@usgs.gov"
}
                                        

                                            [
  {
    "@type": "dcat:Distribution",
    "title": "Digital Data",
    "format": "XML",
    "accessURL": "https://doi.org/10.5066/P9843JFT",
    "mediaType": "application/http",
    "description": "Landing page for access to the data"
  },
  {
    "@type": "dcat:Distribution",
    "title": "Original Metadata",
    "format": "XML",
    "mediaType": "text/xml",
    "description": "The metadata original format",
    "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.5b7da9f0e4b045b1dc7beb81.xml"
  }
]
                                        

                                            [
  "Data analysis",
  "Data treatment",
  "Holocene",
  "Macrofossils",
  "Niche Breadth",
  "North America",
  "Paleogeography",
  "Spatial Sampling Bias",
  "Species Distribution Modeling",
  "USGS:5b7da9f0e4b045b1dc7beb81",
  "Western USA",
  "biota",
  "forests",
  "geospatial analysis",
  "shrublands",
  "statistical anaysis"
]
                                        

                                            {
  "name": "U.S. Geological Survey",
  "@type": "org:Organization"
}
                                        

                                            [
  "Geospatial"
]