Exposure to cold temperature affects the spring phenology of Alaskan deciduous vegetation types
Abstract Temperature is a dominant factor driving arctic and boreal ecosystem phenology, including leaf budburst and gross primary production (GPP) onset in Alaskan spring. Previous studies hypothesized that both accumulated growing degree day (GDD) and cold temperature (chilling) exposure are impor...
Published in: | Environmental Research Letters |
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Online Access: | http://dx.doi.org/10.1088/1748-9326/ab6502 https://iopscience.iop.org/article/10.1088/1748-9326/ab6502 https://iopscience.iop.org/article/10.1088/1748-9326/ab6502/pdf |
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crioppubl:10.1088/1748-9326/ab6502 2024-09-15T18:39:50+00:00 Exposure to cold temperature affects the spring phenology of Alaskan deciduous vegetation types Shi, Mingjie Parazoo, Nicholas C Jeong, Su-Jong Birch, Leah Lawrence, Peter Euskirchen, Eugenie S Miller, Charles E NASA Earth Science Division Interdisciplinary Science program 2020 http://dx.doi.org/10.1088/1748-9326/ab6502 https://iopscience.iop.org/article/10.1088/1748-9326/ab6502 https://iopscience.iop.org/article/10.1088/1748-9326/ab6502/pdf unknown IOP Publishing http://creativecommons.org/licenses/by/4.0/ https://iopscience.iop.org/info/page/text-and-data-mining Environmental Research Letters volume 15, issue 2, page 025006 ISSN 1748-9326 journal-article 2020 crioppubl https://doi.org/10.1088/1748-9326/ab6502 2024-07-29T04:16:08Z Abstract Temperature is a dominant factor driving arctic and boreal ecosystem phenology, including leaf budburst and gross primary production (GPP) onset in Alaskan spring. Previous studies hypothesized that both accumulated growing degree day (GDD) and cold temperature (chilling) exposure are important to leaf budburst. We test this hypothesis by combining both satellite and aircraft vegetation measurements with the Community Land Model Version 4.5 (CLM), in which the end of plant dormancy depends on thermal conditions (i.e. GDD). We study the sensitivity of GPP onset of different Alaskan deciduous vegetation types to a GDD model with chilling requirement (GC model) included. The default CLM simulations have a 1–12 d earlier day of year GPP onset over Alaska vegetated regions compared to satellite constrained estimates from the Polar Vegetation Photosynthesis and Respiration Model. Integrating a GC model into CLM shifts the phase and amplitude of GPP. During 2007–2016, mean GPP onset is postponed by 5 ± 7, 4 ± 8, and 1 ± 6 d over Alaskan northern tundra, shrub, and forest, respectively. The GC model has the greatest impact during warm springs, which is critical for predicting phenology response to future warming. Overall, spring GPP high bias is reduced by 10%. Thus, including chilling requirement in thermal forcing models improves northern high-latitude phenology, but leads to other impacts during the growing season which require further investigation. Article in Journal/Newspaper Tundra Alaska IOP Publishing Environmental Research Letters 15 2 025006 |
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Abstract Temperature is a dominant factor driving arctic and boreal ecosystem phenology, including leaf budburst and gross primary production (GPP) onset in Alaskan spring. Previous studies hypothesized that both accumulated growing degree day (GDD) and cold temperature (chilling) exposure are important to leaf budburst. We test this hypothesis by combining both satellite and aircraft vegetation measurements with the Community Land Model Version 4.5 (CLM), in which the end of plant dormancy depends on thermal conditions (i.e. GDD). We study the sensitivity of GPP onset of different Alaskan deciduous vegetation types to a GDD model with chilling requirement (GC model) included. The default CLM simulations have a 1–12 d earlier day of year GPP onset over Alaska vegetated regions compared to satellite constrained estimates from the Polar Vegetation Photosynthesis and Respiration Model. Integrating a GC model into CLM shifts the phase and amplitude of GPP. During 2007–2016, mean GPP onset is postponed by 5 ± 7, 4 ± 8, and 1 ± 6 d over Alaskan northern tundra, shrub, and forest, respectively. The GC model has the greatest impact during warm springs, which is critical for predicting phenology response to future warming. Overall, spring GPP high bias is reduced by 10%. Thus, including chilling requirement in thermal forcing models improves northern high-latitude phenology, but leads to other impacts during the growing season which require further investigation. |
author2 |
NASA Earth Science Division Interdisciplinary Science program |
format |
Article in Journal/Newspaper |
author |
Shi, Mingjie Parazoo, Nicholas C Jeong, Su-Jong Birch, Leah Lawrence, Peter Euskirchen, Eugenie S Miller, Charles E |
spellingShingle |
Shi, Mingjie Parazoo, Nicholas C Jeong, Su-Jong Birch, Leah Lawrence, Peter Euskirchen, Eugenie S Miller, Charles E Exposure to cold temperature affects the spring phenology of Alaskan deciduous vegetation types |
author_facet |
Shi, Mingjie Parazoo, Nicholas C Jeong, Su-Jong Birch, Leah Lawrence, Peter Euskirchen, Eugenie S Miller, Charles E |
author_sort |
Shi, Mingjie |
title |
Exposure to cold temperature affects the spring phenology of Alaskan deciduous vegetation types |
title_short |
Exposure to cold temperature affects the spring phenology of Alaskan deciduous vegetation types |
title_full |
Exposure to cold temperature affects the spring phenology of Alaskan deciduous vegetation types |
title_fullStr |
Exposure to cold temperature affects the spring phenology of Alaskan deciduous vegetation types |
title_full_unstemmed |
Exposure to cold temperature affects the spring phenology of Alaskan deciduous vegetation types |
title_sort |
exposure to cold temperature affects the spring phenology of alaskan deciduous vegetation types |
publisher |
IOP Publishing |
publishDate |
2020 |
url |
http://dx.doi.org/10.1088/1748-9326/ab6502 https://iopscience.iop.org/article/10.1088/1748-9326/ab6502 https://iopscience.iop.org/article/10.1088/1748-9326/ab6502/pdf |
genre |
Tundra Alaska |
genre_facet |
Tundra Alaska |
op_source |
Environmental Research Letters volume 15, issue 2, page 025006 ISSN 1748-9326 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ https://iopscience.iop.org/info/page/text-and-data-mining |
op_doi |
https://doi.org/10.1088/1748-9326/ab6502 |
container_title |
Environmental Research Letters |
container_volume |
15 |
container_issue |
2 |
container_start_page |
025006 |
_version_ |
1810484174459502592 |