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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

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Authors

Steven D Mamet

Nathan Young

Profile image of Kwok Chun

Dr Kwok Chun Kwok.Chun@uwe.ac.uk
Lecturer in Environmental Managment

Jill F Johnstone



Abstract

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.

Journal Article Type Article
Acceptance Date Feb 21, 2016
Online Publication Date Mar 31, 2016
Publication Date 2016-09
Deposit Date Jan 25, 2022
Publicly Available Date Jan 25, 2022
Journal Arctic Science
Publisher NRC Research Press (Canadian Science Publishing)
Peer Reviewed Peer Reviewed
Volume 2
Issue 3
Pages 127-141
DOI https://doi.org/10.1139/as-2015-0020
Public URL https://uwe-repository.worktribe.com/output/8545337

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