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Understanding the spring phenology of Arctic tundra using multiple satellite data products and ground observations 被引量:1

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摘要 The Arctic is highly sensitive to climate change,and the rise in its near-surface air temperatures has been almost twice the global average.The increased growth of the Arctic tundra and its changing seasonality have been observed,largely in response to the impacts of climate change.In this study,we investigated the temporal and spatial variations of the start of the growing season(SOS)using various remote sensing indices,including Normalized Difference Vegetation Index,Normalized Difference Water Index,and Normalized Difference Snow Index from 2000 to 2018 in Arctic tundra regions.The SOS was derived at 29 sites from ground observations,including CO2 flux data,phenological images,and field records that were used to validate the SOS from remote sensing indices.Our results revealed that the SOS was delayed by approximately 3.86 days per degree of latitude along the northward latitudinal gradient.From 2000 to 2018,the start of the growing season and the interannual variability differed greatly among tundra types.Although the overall trends were not significant from 2000 to 2018,the start of the growing season in different plant communities was consistently delayed after 2016.High Arctic vegetation,including(1)low wetland complexes(5–10 cm)dominated by sedges,grasses,and mosses,and(2)slightly higher prostrate and hemi-prostrate shrubs(<15 cm),experienced a delayed start of the growing season.The start of the growing season of Low Arctic vegetation,comprising(1)wetland complexes(10–40 cm)dominated by sedges,grasses,mosses,and dwarf shrubs,(2)moist tundra(20–50 cm)dominated by tussock cottongrass and dwarf shrubs,and(3)transition zones containing tundra and taiga,displayed no obvious trend.
出处 《Science China Earth Sciences》 SCIE EI CAS CSCD 2020年第10期1599-1612,共14页 中国科学(地球科学英文版)
基金 supported by the National Natural Science Foundation of China(Grant No.41875107) the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA19070203)。
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