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

Tags: biota, data-analysis, data-treatment, forests, geospatial-analysis, holocene, macrofossils, niche-breadth, north-america, paleogeography, shrublands, spatial-sampling-bias, species-distribution-modeling, statistical-anaysis, usgs-5b7da9f0e4b045b1dc7beb81, western-usa
Organization: Department of the Interior