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Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016
Warming climate and its impact on vegetation phenological trends have been widely investigated. However, interannual variability in temperature is considerably large in recent decades, which is expected to trigger an increasing trend of variation in vegetation phenology. To explore the interannual p...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578661/ https://www.ncbi.nlm.nih.gov/pubmed/33087789 http://dx.doi.org/10.1038/s41598-020-74804-4 |
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author | Liu, Lingling Zhang, Xiaoyang |
author_facet | Liu, Lingling Zhang, Xiaoyang |
author_sort | Liu, Lingling |
collection | PubMed |
description | Warming climate and its impact on vegetation phenological trends have been widely investigated. However, interannual variability in temperature is considerably large in recent decades, which is expected to trigger an increasing trend of variation in vegetation phenology. To explore the interannual phenological variation across the contiguous United States (CONUS), we first detected the onset of vegetation greenup using the time series of the daily two-band Enhanced Vegetation Index (EVI2) observed from the AVHRR Long-Term Data Record (1982–1999) and the MODIS Climate Modeling Grid (2000–2016). We then calculated the interannual variation in greenup onset during four decadal periods: 1982–1989, 1990–1999, 2000–2009 and 2010–2016. Further, the trend of interannual variation in greenup onset from 1982 to 2016 was analyzed at pixel and state levels. Extreme phenological events were also determined using a greenup onset anomaly for each pixel. Similar approaches were applied to spring temperatures to detect extreme years and to the temporal trend of interannual variation to explain the phenological variation. The results revealed that 62% of pixels show an increasing interannual variation in greenup onset, and in 44% of pixels, this variation could be explained by the temperature. Although extreme phenology occurred locally in different years, three nationwide extreme phenological years were distinguished. The extreme warm spring that occurred in 2012 resulted in the occurrence of greenup onset as much as 20 days earlier than normal in large parts of the CONUS. In contrast, greenup onset was much later (up to 30 days) in 1983 and 1996 due to cool spring temperatures. These findings suggest that interannual variation in spring phenology could be much stronger in the future in response to climate variation, which could have more significant impacts on terrestrial ecosystems than the regular long-term phenological trend. |
format | Online Article Text |
id | pubmed-7578661 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75786612020-10-23 Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016 Liu, Lingling Zhang, Xiaoyang Sci Rep Article Warming climate and its impact on vegetation phenological trends have been widely investigated. However, interannual variability in temperature is considerably large in recent decades, which is expected to trigger an increasing trend of variation in vegetation phenology. To explore the interannual phenological variation across the contiguous United States (CONUS), we first detected the onset of vegetation greenup using the time series of the daily two-band Enhanced Vegetation Index (EVI2) observed from the AVHRR Long-Term Data Record (1982–1999) and the MODIS Climate Modeling Grid (2000–2016). We then calculated the interannual variation in greenup onset during four decadal periods: 1982–1989, 1990–1999, 2000–2009 and 2010–2016. Further, the trend of interannual variation in greenup onset from 1982 to 2016 was analyzed at pixel and state levels. Extreme phenological events were also determined using a greenup onset anomaly for each pixel. Similar approaches were applied to spring temperatures to detect extreme years and to the temporal trend of interannual variation to explain the phenological variation. The results revealed that 62% of pixels show an increasing interannual variation in greenup onset, and in 44% of pixels, this variation could be explained by the temperature. Although extreme phenology occurred locally in different years, three nationwide extreme phenological years were distinguished. The extreme warm spring that occurred in 2012 resulted in the occurrence of greenup onset as much as 20 days earlier than normal in large parts of the CONUS. In contrast, greenup onset was much later (up to 30 days) in 1983 and 1996 due to cool spring temperatures. These findings suggest that interannual variation in spring phenology could be much stronger in the future in response to climate variation, which could have more significant impacts on terrestrial ecosystems than the regular long-term phenological trend. Nature Publishing Group UK 2020-10-21 /pmc/articles/PMC7578661/ /pubmed/33087789 http://dx.doi.org/10.1038/s41598-020-74804-4 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Liu, Lingling Zhang, Xiaoyang Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016 |
title | Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016 |
title_full | Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016 |
title_fullStr | Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016 |
title_full_unstemmed | Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016 |
title_short | Effects of temperature variability and extremes on spring phenology across the contiguous United States from 1982 to 2016 |
title_sort | effects of temperature variability and extremes on spring phenology across the contiguous united states from 1982 to 2016 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578661/ https://www.ncbi.nlm.nih.gov/pubmed/33087789 http://dx.doi.org/10.1038/s41598-020-74804-4 |
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