Articles | Volume 17, issue 5
https://doi.org/10.5194/bg-17-1281-2020
https://doi.org/10.5194/bg-17-1281-2020
Research article
 | 
11 Mar 2020
Research article |  | 11 Mar 2020

Comparing stability in random forest models to map Northern Great Plains plant communities in pastures occupied by prairie dogs using Pleiades imagery

Jameson R. Brennan, Patricia S. Johnson, and Niall P. Hanan

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (16 Oct 2019) by Paul Stoy
AR by Jameson Brennan on behalf of the Authors (19 Nov 2019)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (25 Nov 2019) by Paul Stoy
RR by Anonymous Referee #1 (04 Dec 2019)
RR by Anonymous Referee #2 (11 Dec 2019)
ED: Reconsider after major revisions (12 Dec 2019) by Paul Stoy
AR by Jameson Brennan on behalf of the Authors (15 Jan 2020)  Manuscript 
ED: Referee Nomination & Report Request started (30 Jan 2020) by Paul Stoy
RR by Anonymous Referee #2 (10 Feb 2020)
ED: Publish as is (10 Feb 2020) by Paul Stoy
AR by Jameson Brennan on behalf of the Authors (13 Feb 2020)  Manuscript 
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Short summary
Prairie dogs have been described as a keystone species and are important for grassland conservation, yet concerns exist over the impact of prairie dogs on livestock production. The aim of this study was to classify plant communities on and off prairie dog towns in South Dakota and determine the utility of using remote sensing to identity prairie dog colony extent. The results show that remote sensing is effective at determining prairie dog colony boundaries.
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