What is the most efficient and effective method for long-term monitoring of alpine tundra vegetation?
Nondestructive estimations of plant community characteristics are essential to vegetation monitoring programs. However, there is no universally accepted method for this purpose in the Arctic, partly because not all programs share the same logistical constraints and monitoring goals. Our aim was to d...
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crcansciencepubl:10.1139/as-2015-0020 2024-06-23T07:48:17+00:00 What is the most efficient and effective method for long-term monitoring of alpine tundra vegetation? Mamet, Steven D. Young, Nathan Chun, Kwok P. Johnstone, Jill F. 2016 http://dx.doi.org/10.1139/as-2015-0020 https://cdnsciencepub.com/doi/full-xml/10.1139/as-2015-0020 https://cdnsciencepub.com/doi/pdf/10.1139/as-2015-0020 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Arctic Science volume 2, issue 3, page 127-141 ISSN 2368-7460 2368-7460 journal-article 2016 crcansciencepubl https://doi.org/10.1139/as-2015-0020 2024-06-13T04:10:52Z Nondestructive estimations of plant community characteristics are essential to vegetation monitoring programs. However, there is no universally accepted method for this purpose in the Arctic, partly because not all programs share the same logistical constraints and monitoring goals. Our aim was to determine the most efficient and effective method for long-term monitoring of alpine tundra vegetation. To achieve this, we established 12 vegetation-monitoring plots on a south-facing slope in the alpine tundra of southern Yukon Territory, Canada. Four observers assessed these plots for vascular plant species abundance employing three methods: visual cover (VC) and subplot frequency (SF) estimation and modified point-intercept (PI) (includes rare species present but not intersected by a pin). SF performed best in terms of time required per plot and sensitivity to variations in species richness. All methods were similarly poor at estimating relative abundance for rare species, but PI and VC were substantially better at high abundances. Differences among methods were larger than among observers. Our results suggest that SF is best when the monitoring focus is on rare species or species richness across extensive areas. However, when the focus is on monitoring changes in relative abundance of common species, VC or PI should be preferred. Article in Journal/Newspaper Arctic Arctic Tundra Yukon Canadian Science Publishing Arctic Canada Yukon Arctic Science 2 3 127 141 |
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Open Polar |
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Canadian Science Publishing |
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crcansciencepubl |
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English |
description |
Nondestructive estimations of plant community characteristics are essential to vegetation monitoring programs. However, there is no universally accepted method for this purpose in the Arctic, partly because not all programs share the same logistical constraints and monitoring goals. Our aim was to determine the most efficient and effective method for long-term monitoring of alpine tundra vegetation. To achieve this, we established 12 vegetation-monitoring plots on a south-facing slope in the alpine tundra of southern Yukon Territory, Canada. Four observers assessed these plots for vascular plant species abundance employing three methods: visual cover (VC) and subplot frequency (SF) estimation and modified point-intercept (PI) (includes rare species present but not intersected by a pin). SF performed best in terms of time required per plot and sensitivity to variations in species richness. All methods were similarly poor at estimating relative abundance for rare species, but PI and VC were substantially better at high abundances. Differences among methods were larger than among observers. Our results suggest that SF is best when the monitoring focus is on rare species or species richness across extensive areas. However, when the focus is on monitoring changes in relative abundance of common species, VC or PI should be preferred. |
format |
Article in Journal/Newspaper |
author |
Mamet, Steven D. Young, Nathan Chun, Kwok P. Johnstone, Jill F. |
spellingShingle |
Mamet, Steven D. Young, Nathan Chun, Kwok P. Johnstone, Jill F. What is the most efficient and effective method for long-term monitoring of alpine tundra vegetation? |
author_facet |
Mamet, Steven D. Young, Nathan Chun, Kwok P. Johnstone, Jill F. |
author_sort |
Mamet, Steven D. |
title |
What is the most efficient and effective method for long-term monitoring of alpine tundra vegetation? |
title_short |
What is the most efficient and effective method for long-term monitoring of alpine tundra vegetation? |
title_full |
What is the most efficient and effective method for long-term monitoring of alpine tundra vegetation? |
title_fullStr |
What is the most efficient and effective method for long-term monitoring of alpine tundra vegetation? |
title_full_unstemmed |
What is the most efficient and effective method for long-term monitoring of alpine tundra vegetation? |
title_sort |
what is the most efficient and effective method for long-term monitoring of alpine tundra vegetation? |
publisher |
Canadian Science Publishing |
publishDate |
2016 |
url |
http://dx.doi.org/10.1139/as-2015-0020 https://cdnsciencepub.com/doi/full-xml/10.1139/as-2015-0020 https://cdnsciencepub.com/doi/pdf/10.1139/as-2015-0020 |
geographic |
Arctic Canada Yukon |
geographic_facet |
Arctic Canada Yukon |
genre |
Arctic Arctic Tundra Yukon |
genre_facet |
Arctic Arctic Tundra Yukon |
op_source |
Arctic Science volume 2, issue 3, page 127-141 ISSN 2368-7460 2368-7460 |
op_rights |
http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining |
op_doi |
https://doi.org/10.1139/as-2015-0020 |
container_title |
Arctic Science |
container_volume |
2 |
container_issue |
3 |
container_start_page |
127 |
op_container_end_page |
141 |
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1802638700017876992 |