Skip to main content

North America Bat Monitoring Program (NABat) Grid-Based Sampling Frame: Continental United States at a 10x10km resolution

Dates

Publication Date

Citation

Talbert, C., and Reichert, B., 2018, North American Bat Monitoring Program (NABat) Master Sample and Grid-Based Sampling Frame: U.S. Geological Survey data release, https://doi.org/10.5066/P9O75YDV.

Summary

The NABat sampling frame is a grid-based finite-area frame spanning Canada, the United States, and Mexico consisting of N total number of 10- by 10-km (100-km2) grid cell sample units. This grain size is biologically appropriate given the scale of movement of most bat species, which routinely travel many kilometers each night between roosts and foraging areas and along foraging routes. A draw of sample units from a finite sampling frame using the GRTS design produces an ordered list of units such that any ordered subset of that list is also randomized and spatially balanced. This vector dataset is the individual grid-based sampling grid for Continental United States at a 10x10km resolution.

Contacts

Point of Contact :
Brian E Reichert
Originator :
Colin Talbert, Brian E Reichert
Metadata Contact :
Colin Talbert
Publisher :
U.S. Geological Survey
Distributor :
U.S. Geological Survey - ScienceBase

Attached Files

Click on title to download individual files attached to this item.

Shapefile: conus_mastersample_10km_GRTS.zip
conus_mastersample_10km_GRTS.cpg 10 Bytes
conus_mastersample_10km_GRTS.dbf 8.55 MB
conus_mastersample_10km_GRTS.prj 423 Bytes
conus_mastersample_10km_GRTS.shp 17.35 MB
conus_mastersample_10km_GRTS.shx 1.02 MB

Purpose

The GRTS design provides solutions to several practical challenges faced by bat surveyors that are not provided by more familiar designs such as simple random, stratified, and systematic sampling. The GRTS design allows for sample site additions and deletions, supports unequal-probability selection of survey locations, and provides an approximately unbiased neighborhood-weighted variance estimator that takes advantage of the spatial structure present in the surveyed population.

Additional Information

Shapefile Extension

boundingBox
minY22.91699689501784
minX-127.94485205962674
maxY51.542647235860336
maxX-65.26264652581449
files
nameconus_mastersample_10km_GRTS.cpg
contentTypetext/plain
pathOnDisk__disk__6f/7a/7e/6f7a7ee4fa2ade28703eabfc383bc90646011e23
size10
dateUploadedFri Aug 17 17:01:17 MDT 2018
nameconus_mastersample_10km_GRTS.dbf
contentTypetext/plain
pathOnDisk__disk__71/6a/77/716a77d3199911b8fb85bc8342dde029011cb92d
size8965231
dateUploadedFri Aug 17 17:01:17 MDT 2018
nameconus_mastersample_10km_GRTS.prj
contentTypetext/plain
pathOnDisk__disk__70/fa/16/70fa1659123ad4a93739268db48ba091ac8081f2
size423
dateUploadedFri Aug 17 17:01:17 MDT 2018
nameconus_mastersample_10km_GRTS.shp
contentTypex-gis/x-shapefile
pathOnDisk__disk__c9/40/01/c94001f69b940856092160d3eb99ab7c8669433d
size18197852
dateUploadedFri Aug 17 17:01:17 MDT 2018
nameconus_mastersample_10km_GRTS.shp.xml
contentTypeapplication/fgdc+xml
pathOnDisk__disk__ec/15/44/ec154429aa03b39dc03fb8f84093babfbb3355bb
dateUploadedFri Sep 11 06:37:41 MDT 2020
originalMetadatatrue
nameconus_mastersample_10km_GRTS.shx
contentTypex-gis/x-shapefile
pathOnDisk__disk__81/69/fe/8169fe3064f1bf67891913c7407733b8c2becbb2
size1070556
dateUploadedFri Aug 17 17:01:17 MDT 2018
geometryTypeMultiPolygon
nameconus_mastersample_10km_GRTS
nativeCrsEPSG:5070

Item Actions

View Item as ...

Save Item as ...

View Item...