Shrub cover change in Noatak National Preserve (1951-2016)

More than four decades’ high-resolution (~1 meter (m)) remote sensing observation in upland and lowland tundra revealed divergent pathways of shrub-cover responses to fire disturbance and climate change during 1951 to 2016 in the Noatak National Preserve of northern Alaska. We set up 114 study sites...

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Main Authors: Chen, Yaping, Lara, Mark, Hu, Feng Sheng
Format: Dataset
Language:English
Published: NSF Arctic Data Center 2020
Subjects:
Online Access:https://dx.doi.org/10.18739/a25m6277j
https://arcticdata.io/catalog/view/doi:10.18739/A25M6277J
id ftdatacite:10.18739/a25m6277j
record_format openpolar
spelling ftdatacite:10.18739/a25m6277j 2023-05-15T17:58:02+02:00 Shrub cover change in Noatak National Preserve (1951-2016) Chen, Yaping Lara, Mark Hu, Feng Sheng 2020 text/xml https://dx.doi.org/10.18739/a25m6277j https://arcticdata.io/catalog/view/doi:10.18739/A25M6277J en eng NSF Arctic Data Center tundra fire disturbance permafrost climate change dataset Dataset 2020 ftdatacite https://doi.org/10.18739/a25m6277j 2021-11-05T12:55:41Z More than four decades’ high-resolution (~1 meter (m)) remote sensing observation in upland and lowland tundra revealed divergent pathways of shrub-cover responses to fire disturbance and climate change during 1951 to 2016 in the Noatak National Preserve of northern Alaska. We set up 114 study sites (250 m by 250 m) in burned and the adjacent unburned upland and lowland tundra using stratified random sampling. Specifically, all sites were placed with a minimum distance of 500 m apart from one another, and the unburned sites were located in areas greater than 500 m and less than 2,000 m radius surrounding the fire perimeters. To achieve an unbiased representation of tundra types (upland and lowland tundra) and fire severity levels (high, moderate, low, and unburned), a minumun of 12 study sites were randomly assigned to each tundra type × fire severity group. We then analyzed decadal-scale shrub cover change in each study site using supervised support vector machine classifier (ArcGIS 10.5). The data was presented as shrub cover (m2 ha (hectare)-1) at years before fire and after fire, where negative values of Year Since Fire (YSF) correspond to the number of years before fire, and positive values are the number of years after fire. Our results revealed that shrub expansion in the well-drained uplands was largely enhanced by fire disturbance, and it showed positive correlation with fire severity. In contrast, shrub cover decreased in lowland tundra after fire, which triggered thermokarst-associated water impounding and resulted in ~ 50% loss of shrub cover over three decades. Dataset permafrost Thermokarst 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 English
topic tundra
fire disturbance
permafrost
climate change
spellingShingle tundra
fire disturbance
permafrost
climate change
Chen, Yaping
Lara, Mark
Hu, Feng Sheng
Shrub cover change in Noatak National Preserve (1951-2016)
topic_facet tundra
fire disturbance
permafrost
climate change
description More than four decades’ high-resolution (~1 meter (m)) remote sensing observation in upland and lowland tundra revealed divergent pathways of shrub-cover responses to fire disturbance and climate change during 1951 to 2016 in the Noatak National Preserve of northern Alaska. We set up 114 study sites (250 m by 250 m) in burned and the adjacent unburned upland and lowland tundra using stratified random sampling. Specifically, all sites were placed with a minimum distance of 500 m apart from one another, and the unburned sites were located in areas greater than 500 m and less than 2,000 m radius surrounding the fire perimeters. To achieve an unbiased representation of tundra types (upland and lowland tundra) and fire severity levels (high, moderate, low, and unburned), a minumun of 12 study sites were randomly assigned to each tundra type × fire severity group. We then analyzed decadal-scale shrub cover change in each study site using supervised support vector machine classifier (ArcGIS 10.5). The data was presented as shrub cover (m2 ha (hectare)-1) at years before fire and after fire, where negative values of Year Since Fire (YSF) correspond to the number of years before fire, and positive values are the number of years after fire. Our results revealed that shrub expansion in the well-drained uplands was largely enhanced by fire disturbance, and it showed positive correlation with fire severity. In contrast, shrub cover decreased in lowland tundra after fire, which triggered thermokarst-associated water impounding and resulted in ~ 50% loss of shrub cover over three decades.
format Dataset
author Chen, Yaping
Lara, Mark
Hu, Feng Sheng
author_facet Chen, Yaping
Lara, Mark
Hu, Feng Sheng
author_sort Chen, Yaping
title Shrub cover change in Noatak National Preserve (1951-2016)
title_short Shrub cover change in Noatak National Preserve (1951-2016)
title_full Shrub cover change in Noatak National Preserve (1951-2016)
title_fullStr Shrub cover change in Noatak National Preserve (1951-2016)
title_full_unstemmed Shrub cover change in Noatak National Preserve (1951-2016)
title_sort shrub cover change in noatak national preserve (1951-2016)
publisher NSF Arctic Data Center
publishDate 2020
url https://dx.doi.org/10.18739/a25m6277j
https://arcticdata.io/catalog/view/doi:10.18739/A25M6277J
genre permafrost
Thermokarst
Tundra
Alaska
genre_facet permafrost
Thermokarst
Tundra
Alaska
op_doi https://doi.org/10.18739/a25m6277j
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