Evidence of vegetation greening at alpine treeline ecotones

Three decades of Landsat spectral trends informed by lidar-derived vertical structure

Bibliographic Data

ID15544992
AuthorsDouglas K Bolton (0000-0002-4365-2039, University of British Columbia, corresponding author), Nicholas C Coops (0000-0002-0151-9037, University of British Columbia), Txomin Hermosilla (0000-0002-5445-0360, University of British Columbia), Michael A Wulder (0000-0002-6942-1896, Natural Resources Canada), Joanne C White (0000-0003-4674-0373, Canadian Forest Service)
Year2018
Volume13
Issue8
Pages084022-084022
Publication date2018-07-25
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironmental Research Letters (JOURNAL)
Journal identifiersISSN: 1748-9326 • E-ISSN: 1748-9326
PublisherIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/aad5d2
OpenAlexW2883057959
LanguageEN
Citations received2
References cited47

Monitoring changes in vegetation at high-latitude and alpine treeline ecotones is critical for characterizing changes to carbon and energy budgets, plant species richness, and habitat suitability and is often considered a bellwether of a changing climate. Herein, we used transects of airborne laser scanning (ALS) data to identify alpine treeline ecotones in the Yukon Territory of Canada, and assessed changes in vegetation greenness using a time-series of Landsat imagery over a 30 year period from 1985 to 2015. Specifically, we calculated the enhanced vegetation index (EVI) from annual Landsat composites and assessed temporal trends within 500 m of detected forest-lines (i.e., transition point from continuous forest into treeline ecotones) using Theil–Sen’s nonparametric regression. Across 74 detected treeline ecotones, 27.5% of Landsat pixels displayed a significant positive trend in EVI and 5.6% of pixels displayed a significant negative trend ( p < 0.05). By using ALS data to determine vegetation structural class, we found that non-treed pixels had the highest percentage of significant positive trends in vegetation greenness (40.8%), followed by shrubs (30.5%), with lower percentages in sparse forests (18.9%) and open/dense forests (13.3%). These results suggest herbaceous and shrub vegetation types are undergoing the most significant changes in greenness, likely due to increases in shrub cover and herbaceous biomass in areas associated with these alpine treeline ecotones. The limited increases in EVI in forests likely indicates that vegetation cover is changing less rapidly in forests than in shrub and herbaceous vegetation types. Moreover, EVI may not be capturing increased height growth in forests near the treeline. Combining ALS data and Landsat time-series data provides a useful approach to locate and characterize alpine treeline ecotones, and enables the direct assessment of which vegetation structural classes are experiencing the greatest greening trends, thereby providing new insights to ecosystem change

Biology · Climate change · Ecotone · Enhanced vegetation index · Geography · Normalized Difference Vegetation Index · Physical geography · Remote sensing · Shrub · Transect · Vegetation (pathology · Vegetation Index · Environmental Science · Remote Sensing and LiDAR Applications · Remote Sensing in Agriculture · Tree-ring climate responses · Ecology

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