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...

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Bibliographic Details
Published in:Environmental Research Letters
Main Authors: Shi, Mingjie, Parazoo, Nicholas C, Jeong, Su-Jong, Birch, Leah, Lawrence, Peter, Euskirchen, Eugenie S, Miller, Charles E
Other Authors: NASA Earth Science Division Interdisciplinary Science program
Format: Article in Journal/Newspaper
Language:unknown
Published: IOP Publishing 2020
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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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Summary: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.