Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data
Abstract While numerous studies report shifts in vegetation phenology, in this regard eddy covariance (EC) data, despite its continuous high-frequency observations, still requires further exploration. Furthermore, there is no general consensus on optimal methodologies for data smoothing and extracti...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-41048-x |
| _version_ | 1827711401381068800 |
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| author | Annu Panwar Mirco Migliavacca Jacob A. Nelson José Cortés Ana Bastos Matthias Forkel Alexander J. Winkler |
| author_facet | Annu Panwar Mirco Migliavacca Jacob A. Nelson José Cortés Ana Bastos Matthias Forkel Alexander J. Winkler |
| author_sort | Annu Panwar |
| collection | DOAJ |
| description | Abstract While numerous studies report shifts in vegetation phenology, in this regard eddy covariance (EC) data, despite its continuous high-frequency observations, still requires further exploration. Furthermore, there is no general consensus on optimal methodologies for data smoothing and extracting phenological transition dates (PTDs). Here, we revisit existing methodologies and present new prospects to investigate phenological changes in gross primary productivity (GPP) from EC measurements. First, we present a smoothing technique of GPP time series through the derivative of its smoothed annual cumulative sum. Second, we calculate PTDs and their trends from a commonly used threshold method that identifies days with a fixed percentage of the annual maximum GPP. A systematic analysis is performed for various thresholds ranging from 0.1 to 0.7. Lastly, we examine the relation of PTDs trends to trends in GPP across the years on a weekly basis. Results from 47 EC sites with long time series (> 10 years) show that advancing trends in start of season (SOS) are strongest at lower thresholds but for the end of season (EOS) at higher thresholds. Moreover, the trends are variable at different thresholds for individual vegetation types and individual sites, outlining reasonable concerns on using a single threshold value. Relationship of trends in PTDs and weekly GPP reveal association of advanced SOS and delayed EOS to increase in immediate primary productivity, but not to the trends in overall seasonal productivity. Drawing on these analyses, we emphasise on abstaining from subjective choices and investigating relationship of PTDs trend to finer temporal trends of GPP. Our study examines existing methodological challenges and presents approaches that optimize the use of EC data in identifying vegetation phenological changes and their relation to carbon uptake. |
| first_indexed | 2024-03-10T17:54:05Z |
| format | Article |
| id | doaj.art-ac55d3be2e52478ca4f2f052828d3ac3 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-10T17:54:05Z |
| publishDate | 2023-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-ac55d3be2e52478ca4f2f052828d3ac32023-11-20T09:14:47ZengNature PortfolioScientific Reports2045-23222023-08-0113111410.1038/s41598-023-41048-xMethodological challenges and new perspectives of shifting vegetation phenology in eddy covariance dataAnnu Panwar0Mirco Migliavacca1Jacob A. Nelson2José Cortés3Ana Bastos4Matthias Forkel5Alexander J. Winkler6Department of Biogeochemical Integration, Max Planck Institute for BiogeochemistryEuropean Commission, Joint Research Centre (JRC)Department of Biogeochemical Integration, Max Planck Institute for BiogeochemistryDepartment of Biogeochemical Integration, Max Planck Institute for BiogeochemistryDepartment of Biogeochemical Integration, Max Planck Institute for BiogeochemistryTUD Dresden University of Technology, Faculty of Environmental SciencesDepartment of Biogeochemical Integration, Max Planck Institute for BiogeochemistryAbstract While numerous studies report shifts in vegetation phenology, in this regard eddy covariance (EC) data, despite its continuous high-frequency observations, still requires further exploration. Furthermore, there is no general consensus on optimal methodologies for data smoothing and extracting phenological transition dates (PTDs). Here, we revisit existing methodologies and present new prospects to investigate phenological changes in gross primary productivity (GPP) from EC measurements. First, we present a smoothing technique of GPP time series through the derivative of its smoothed annual cumulative sum. Second, we calculate PTDs and their trends from a commonly used threshold method that identifies days with a fixed percentage of the annual maximum GPP. A systematic analysis is performed for various thresholds ranging from 0.1 to 0.7. Lastly, we examine the relation of PTDs trends to trends in GPP across the years on a weekly basis. Results from 47 EC sites with long time series (> 10 years) show that advancing trends in start of season (SOS) are strongest at lower thresholds but for the end of season (EOS) at higher thresholds. Moreover, the trends are variable at different thresholds for individual vegetation types and individual sites, outlining reasonable concerns on using a single threshold value. Relationship of trends in PTDs and weekly GPP reveal association of advanced SOS and delayed EOS to increase in immediate primary productivity, but not to the trends in overall seasonal productivity. Drawing on these analyses, we emphasise on abstaining from subjective choices and investigating relationship of PTDs trend to finer temporal trends of GPP. Our study examines existing methodological challenges and presents approaches that optimize the use of EC data in identifying vegetation phenological changes and their relation to carbon uptake.https://doi.org/10.1038/s41598-023-41048-x |
| spellingShingle | Annu Panwar Mirco Migliavacca Jacob A. Nelson José Cortés Ana Bastos Matthias Forkel Alexander J. Winkler Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data Scientific Reports |
| title | Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data |
| title_full | Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data |
| title_fullStr | Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data |
| title_full_unstemmed | Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data |
| title_short | Methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data |
| title_sort | methodological challenges and new perspectives of shifting vegetation phenology in eddy covariance data |
| url | https://doi.org/10.1038/s41598-023-41048-x |
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