BLM REA YKL 2011 Alaska GAP Modeled Habitat Distribution of American Beaver

Metadata Updated: November 12, 2020

Some of the YKL rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - Gap analysis uses the predicted distributions of native vertebrate species to evaluate their conservation status relative to existing land management, utilizing Geographic Information Systems (GIS) technology. Previous to this effort there were no maps available, digital or otherwise, showing the likely present-day distribution of species by habitat across their ranges in Alaska. Besides gap analysis, the maps of vertebrate species distributions and associated information may be used to answer a wide variety of management, planning, and research questions relating to individual species or groups of species. These species maps and information are also available in digital GIS databases (see How to obtain GAP data) which enables computerized query and analysis of the data. It is important to stress that the information on species’ habitat associations, elevation limits and statewide geographical distributions compiled in this atlas were collected for the purposes of statewide and regional analyses of biodiversity conservation. This information was not intended for the purpose of determining a measure of abundance, health or condition of populations of any species listed herein. Wherever possible we have tried to detail the circumstances where our mapping procedures were insufficient to accurately represent the geographic distribution of particular species. Deductive and inductive modeling techniques were used to produce GAP distribution models. Combined models were created as an intersection of where there was agreement between the two model types. Deductive distribution modeling followed the traditional, land cover-based procedures described by Csuti and Crist (1998), to produce models. Inductive models were derived using known points of occurrence and their intersection with a suite of environmental parameters. The inductive modeling process included occurrence data processing and filtering, ancillary data layer development or refinement, and the application of the Maximum Entropy algorithm (MaxEnt version 3.3.1) to produce models. See Gotthardt et al. 2012 for further details on modeling methods.

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License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Metadata Date December 20, 2017
Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020
Reference Date(s) January 1, 2012 (publication)
Frequency Of Update notPlanned

Metadata Source

Harvested from DOI Open Data

Additional Metadata

Resource Type Dataset
Metadata Date December 20, 2017
Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020
Reference Date(s) January 1, 2012 (publication)
Responsible Party Alaska Natural Heritage Program, University of Alaska Anchorage (Point of Contact)
Contact Email
Access Constraints Use Constraints: These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. The information contained in these data is dynamic and may change over time. The data are not better than the original sources from which they were derived, and both scale and accuracy may vary across the data set. These data may not have the accuracy, resolution, completeness, timeliness, or other characteristics appropriate for applications that potential users of the data may contemplate. The User is encouraged to carefully consider the content of the metadata file associated with these data. These data are neither legal documents nor land surveys, and must not be used as such. Official records may be referenced at most BLM offices. Please report any errors in the data to the BLM office for which it was obtained. The BLM should be cited as the data source in any products derived from these data. Any Users wishing to modify the data should describe the types of modifications they have performed. The User should not misrepresent the data, nor imply that changes made were approved or endorsed by BLM. This information may be updated without notification., Access Constraints: None, these data are considered public domain
Bbox East Long -134.04
Bbox North Lat 71.434014
Bbox South Lat 49.090610
Bbox West Long -180.000000
Coupled Resource
Frequency Of Update notPlanned
Licence The BLM assumes no responsibility for errors or omissions. No warranty is made by the BLM as to the accuracy, reliability, or completeness of these data for individual use or aggregate use with other data; nor shall the act of distribution to contractors, partners, or beyond, constitute any such warranty for individual or aggregate data use with other data. Although these data have been processed successfully on computers of BLM, no warranty, expressed or implied, is made by BLM regarding the use of these data on any other system, or for general or scientific purposes, nor does the fact of distribution constitute or imply any such warranty. In no event shall the BLM have any liability whatsoever for payment of any consequential, incidental, indirect, special, or tort damages of any kind, including, but not limited to, any loss of profits arising out of the use or reliance on the geographic data or arising out of the delivery, installation, operation, or support by BLM.
Metadata Language
Metadata Type geospatial
Progress completed
Spatial Data Service Type
Spatial Reference System
Spatial Harvester True

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