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  3. Aquatic Gap Analysis Project (Aquatic GAP) Aquatic Species Distribution Modeling on the National Hydrography Dataset Plus Version 2.1
  4. Fluvial Fish Native Distributions for the Conterminous United States using the NHDPlusV2.1 and Boosted Regression Tree (BRT) Models

Fluvial Fish Native Distributions for the Conterminous United States using the NHDPlusV2.1 and Boosted Regression Tree (BRT) Models

Dates

Publication Date

Citation

Yu, H., Cooper, A.R., Infante, D.M., and Ross, J.A., 2022, Fluvial Fish Native Distributions for the Conterminous United States using the NHDPlusV2.1 and Boosted Regression Tree (BRT) Models: U.S. Geological Survey data release, https://doi.org/10.5066/P9YX3EX6.

Summary

This USGS data release documents species distribution models for 271 fluvial fish species in their native ranges of the conterminous United States. Source data, supporting code and model results are documented in this data package. Boosted Regression Tree (BRT) models were used to develop presence/absence predictions for each of the National Hydrography Dataset Plus Version 2.1 stream segments within a species' native range. The predictions provided can be linked to the NHDPlusV2.1 geospatial dataset through the COMID to create a spatial depiction of the models. The primary results are stored in the file "BRT Predictions" and are provided in comma separated value (CSV) and Parquet file formats. Parquet file format is provided to [...]

Contacts

Point of Contact :
Dana M Infante, Michigan State University, Department of Fisheries and Wildlife
Originator :
Hao Yu, Arthur R Cooper, Dana M Infante, Jared A Ross
Metadata Contact :
Daniel J Wieferich
Publisher :
U.S. Geological Survey
Data Owner :
Science Analytics and Synthesis
Distributor :
U.S. Geological Survey - ScienceBase
USGS Mission Area :
Core Science Systems
SDC Data Owner :
Science Analytics and Synthesis

Attached Files

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

fluvial_fish_brt_model_data.xml
“Metadata”
Original FGDC Metadata
View 		28.73 KB application/fgdc+xml
fluvial_fish_brt_predictions.parquet.gzip
“BRT Predictions In Alternative Data Format (Parquet) For R And Python Users” 		889.28 MB application/unknown

“BRT Predictions - In Zipped Comma Separated Value (CSV) Format” 		1.17 GB application/zip
fish_list.csv
“List Of Modeled Fish Species In Comma Separated Value (CSV) Format” 		23.5 KB text/csv
fluvial_fish_brt_model_artifacts.zip
“BRT Artifacts” 		3.46 MB application/zip
readme.pdf
“Readme Document - Structure And Explanation Of Data Release” 		247.93 KB application/pdf

Purpose

These models were developed to provide resource managers information on the distribution of fluvial fishes throughout the conterminous United States, to identify the landscape level drivers of those distributions, and to support a national protected areas assessment of the protection status for these fishes. These species distribution models support the U.S. Geological Surveys Aquatic Gap Analysis Project (AGAP). The mission of AGAP is to provide data and analyses to support the conservation of aquatic species and their habitats. Modeling aquatic species distributions across the nation on a consistent spatial framework allows us to 1) highlight aquatic systems needing protection; 2) identify the natural ecological potential of high quality habitats too support aquatic diversity; 3) identify systems under threat; and 4) inform species- or habitat-specific management strategies.

Rights

Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty.

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DOI https://www.sciencebase.gov/vocab/category/item/identifier doi:10.5066/P9YX3EX6

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