2000 random points for statistical modeling

2000 random points across the three study sub-areas were selected for statistical modeling in binomial generalized linear mixed models. These points have digital elevation model (DEM) variables (elevation, slope, aspect, potential insolation in four seasons) and vegetation classifications for 1972 a...

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Bibliographic Details
Main Authors: Rinas, Christina L., Dial, Roman J., Sullivan, Patrick F., Smeltz, T. Scott, Tobin, S. Carl, Loso, Michael, Geck, Jason E.
Format: Dataset
Language:unknown
Published: Dryad Digital Repository 2017
Subjects:
Online Access:https://dx.doi.org/10.5061/dryad.dc863/2
http://datadryad.org/resource/doi:10.5061/dryad.dc863/2
id ftdatacite:10.5061/dryad.dc863/2
record_format openpolar
spelling ftdatacite:10.5061/dryad.dc863/2 2023-05-15T18:40:07+02:00 2000 random points for statistical modeling Rinas, Christina L. Dial, Roman J. Sullivan, Patrick F. Smeltz, T. Scott Tobin, S. Carl Loso, Michael Geck, Jason E. 2017 https://dx.doi.org/10.5061/dryad.dc863/2 http://datadryad.org/resource/doi:10.5061/dryad.dc863/2 unknown Dryad Digital Repository https://dx.doi.org/10.5061/dryad.dc863 http://creativecommons.org/publicdomain/zero/1.0 CC0 alpine climate change forecast modeling thermal niche modeling plant-climate interactions range expansion shrubs tundra Chugach Mountains Alaska North America Alnus Salix dataset Dataset DataFile 2017 ftdatacite https://doi.org/10.5061/dryad.dc863/2 https://doi.org/10.5061/dryad.dc863 2021-11-05T12:55:41Z 2000 random points across the three study sub-areas were selected for statistical modeling in binomial generalized linear mixed models. These points have digital elevation model (DEM) variables (elevation, slope, aspect, potential insolation in four seasons) and vegetation classifications for 1972 and 2012. Dataset Tundra Alaska DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic alpine
climate change
forecast modeling
thermal niche modeling
plant-climate interactions
range expansion
shrubs
tundra
Chugach Mountains
Alaska
North America
Alnus
Salix
spellingShingle alpine
climate change
forecast modeling
thermal niche modeling
plant-climate interactions
range expansion
shrubs
tundra
Chugach Mountains
Alaska
North America
Alnus
Salix
Rinas, Christina L.
Dial, Roman J.
Sullivan, Patrick F.
Smeltz, T. Scott
Tobin, S. Carl
Loso, Michael
Geck, Jason E.
2000 random points for statistical modeling
topic_facet alpine
climate change
forecast modeling
thermal niche modeling
plant-climate interactions
range expansion
shrubs
tundra
Chugach Mountains
Alaska
North America
Alnus
Salix
description 2000 random points across the three study sub-areas were selected for statistical modeling in binomial generalized linear mixed models. These points have digital elevation model (DEM) variables (elevation, slope, aspect, potential insolation in four seasons) and vegetation classifications for 1972 and 2012.
format Dataset
author Rinas, Christina L.
Dial, Roman J.
Sullivan, Patrick F.
Smeltz, T. Scott
Tobin, S. Carl
Loso, Michael
Geck, Jason E.
author_facet Rinas, Christina L.
Dial, Roman J.
Sullivan, Patrick F.
Smeltz, T. Scott
Tobin, S. Carl
Loso, Michael
Geck, Jason E.
author_sort Rinas, Christina L.
title 2000 random points for statistical modeling
title_short 2000 random points for statistical modeling
title_full 2000 random points for statistical modeling
title_fullStr 2000 random points for statistical modeling
title_full_unstemmed 2000 random points for statistical modeling
title_sort 2000 random points for statistical modeling
publisher Dryad Digital Repository
publishDate 2017
url https://dx.doi.org/10.5061/dryad.dc863/2
http://datadryad.org/resource/doi:10.5061/dryad.dc863/2
genre Tundra
Alaska
genre_facet Tundra
Alaska
op_relation https://dx.doi.org/10.5061/dryad.dc863
op_rights http://creativecommons.org/publicdomain/zero/1.0
op_rightsnorm CC0
op_doi https://doi.org/10.5061/dryad.dc863/2
https://doi.org/10.5061/dryad.dc863
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