TY - JOUR

T1 - Drivers of contemporary and future changes in Arctic seasonal transition dates for a tundra site in coastal Greenland

AU - Liu, Yijing

AU - Wang, Peiyan

AU - Elberling, Bo

AU - Westergaard-Nielsen, Andreas

N1 - CENPERMOA[2024] Publisher Copyright: © 2023 The Authors. Global Change Biology published by John Wiley & Sons Ltd.

PY - 2024

Y1 - 2024

N2 - Climate change has had a significant impact on the seasonal transition dates of Arctic tundra ecosystems, causing diverse variations between distinct land surface classes. However, the combined effect of multiple controls as well as their individual effects on these dates remains unclear at various scales and across diverse land surface classes. Here we quantified spatiotemporal variations of three seasonal transition dates (start of spring, maximum normalized difference vegetation index (NDVImax) day, end of fall) for five dominating land surface classes in the ice-free Greenland. Using a distributed snow model, structural equation modeling, and a random forest model, based on ground observations and remote sensing data, we assessed the indirect and direct effects of climate, snow, and terrain on seasonal transition dates. We then presented new projections of likely changes in seasonal transition dates under six future climate scenarios. The coupled climate, snow cover, and terrain conditions explained up to 61% of seasonal transition dates across different land surface classes. Snow ending day played a crucial role in the start of spring and timing of NDVImax. A warmer June and a decline in wind could advance the NDVImax day. Increased precipitation and temperature during July–August are the most important for delaying the end of fall. We projected that a 1–4.5°C increase in temperature and a 5%–20% increase in precipitation would lengthen the spring-to-fall period for all five land surface classes by 2050, thus the current order of spring-to-fall lengths for the five land surface classes could undergo notable changes. Tall shrubs and fens would have a longer spring-to-fall period under the warmest and wettest scenario, suggesting a competitive advantage for these vegetation communities. This study's results illustrate controls on seasonal transition dates and portend potential changes in vegetation composition in the Arctic under climate change.

AB - Climate change has had a significant impact on the seasonal transition dates of Arctic tundra ecosystems, causing diverse variations between distinct land surface classes. However, the combined effect of multiple controls as well as their individual effects on these dates remains unclear at various scales and across diverse land surface classes. Here we quantified spatiotemporal variations of three seasonal transition dates (start of spring, maximum normalized difference vegetation index (NDVImax) day, end of fall) for five dominating land surface classes in the ice-free Greenland. Using a distributed snow model, structural equation modeling, and a random forest model, based on ground observations and remote sensing data, we assessed the indirect and direct effects of climate, snow, and terrain on seasonal transition dates. We then presented new projections of likely changes in seasonal transition dates under six future climate scenarios. The coupled climate, snow cover, and terrain conditions explained up to 61% of seasonal transition dates across different land surface classes. Snow ending day played a crucial role in the start of spring and timing of NDVImax. A warmer June and a decline in wind could advance the NDVImax day. Increased precipitation and temperature during July–August are the most important for delaying the end of fall. We projected that a 1–4.5°C increase in temperature and a 5%–20% increase in precipitation would lengthen the spring-to-fall period for all five land surface classes by 2050, thus the current order of spring-to-fall lengths for the five land surface classes could undergo notable changes. Tall shrubs and fens would have a longer spring-to-fall period under the warmest and wettest scenario, suggesting a competitive advantage for these vegetation communities. This study's results illustrate controls on seasonal transition dates and portend potential changes in vegetation composition in the Arctic under climate change.

KW - Arctic tundra ecosystem

KW - climate change

KW - projection

KW - seasonal transition dates

KW - snow cover

U2 - 10.1111/gcb.17118

DO - 10.1111/gcb.17118

M3 - Journal article

C2 - 38273573

AN - SCOPUS:85181220208

VL - 30

JO - Global Change Biology

JF - Global Change Biology

SN - 1354-1013

IS - 1

M1 - e17118

ER -