Time-Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/142446 |
Resumo: | Much uncertainty remains in measuring the inter-annual and longer-term dynamics of vegetation gross and net primary productivity (GPP, NPP) and the connected land carbon sink. Potential for better GPP estimation lies in newer satellite products representing different processes or vegetation states, but how they capture interannual GPP dynamics remains to be explored. Here, we differentiate shorter- and longer-term vegetation dynamics and their drivers for several Earth-observation-based vegetation proxies and a GPP estimate using time series decomposition. We find that relations between proxies can significantly differ between time scales, along land cover and climate gradients. For GPP estimated at FLUXNET sites, seasonal and multiannual slopes differ by at least 25% for half of the cases investigated, indicating considerable mismatch if multiannual relations were derived from seasonal slopes. Considering time-scale-specific sensitivities between proxies of vegetation productivity may improve estimates of interannual variability in vegetation productivity. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Time-Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation ProductivityGeophysicsEarth and Planetary Sciences(all)SDG 13 - Climate ActionMuch uncertainty remains in measuring the inter-annual and longer-term dynamics of vegetation gross and net primary productivity (GPP, NPP) and the connected land carbon sink. Potential for better GPP estimation lies in newer satellite products representing different processes or vegetation states, but how they capture interannual GPP dynamics remains to be explored. Here, we differentiate shorter- and longer-term vegetation dynamics and their drivers for several Earth-observation-based vegetation proxies and a GPP estimate using time series decomposition. We find that relations between proxies can significantly differ between time scales, along land cover and climate gradients. For GPP estimated at FLUXNET sites, seasonal and multiannual slopes differ by at least 25% for half of the cases investigated, indicating considerable mismatch if multiannual relations were derived from seasonal slopes. Considering time-scale-specific sensitivities between proxies of vegetation productivity may improve estimates of interannual variability in vegetation productivity.DCEA - Departamento de Ciências e Engenharia do AmbienteRUNLinscheid, NoraMahecha, Miguel D.Rammig, AnjaCarvalhais, NunoGans, FabianNelson, Jacob A.Walther, SophiaWeber, UlrichReichstein, Markus2022-07-26T22:26:28Z2021-12-282021-12-28T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/142446eng0094-8276PURE: 45617192https://doi.org/10.1029/2021GL093285info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-05-22T18:03:54Zoai:run.unl.pt:10362/142446Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-22T18:03:54Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Time-Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity |
title |
Time-Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity |
spellingShingle |
Time-Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity Linscheid, Nora Geophysics Earth and Planetary Sciences(all) SDG 13 - Climate Action |
title_short |
Time-Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity |
title_full |
Time-Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity |
title_fullStr |
Time-Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity |
title_full_unstemmed |
Time-Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity |
title_sort |
Time-Scale Dependent Relations Between Earth Observation Based Proxies of Vegetation Productivity |
author |
Linscheid, Nora |
author_facet |
Linscheid, Nora Mahecha, Miguel D. Rammig, Anja Carvalhais, Nuno Gans, Fabian Nelson, Jacob A. Walther, Sophia Weber, Ulrich Reichstein, Markus |
author_role |
author |
author2 |
Mahecha, Miguel D. Rammig, Anja Carvalhais, Nuno Gans, Fabian Nelson, Jacob A. Walther, Sophia Weber, Ulrich Reichstein, Markus |
author2_role |
author author author author author author author author |
dc.contributor.none.fl_str_mv |
DCEA - Departamento de Ciências e Engenharia do Ambiente RUN |
dc.contributor.author.fl_str_mv |
Linscheid, Nora Mahecha, Miguel D. Rammig, Anja Carvalhais, Nuno Gans, Fabian Nelson, Jacob A. Walther, Sophia Weber, Ulrich Reichstein, Markus |
dc.subject.por.fl_str_mv |
Geophysics Earth and Planetary Sciences(all) SDG 13 - Climate Action |
topic |
Geophysics Earth and Planetary Sciences(all) SDG 13 - Climate Action |
description |
Much uncertainty remains in measuring the inter-annual and longer-term dynamics of vegetation gross and net primary productivity (GPP, NPP) and the connected land carbon sink. Potential for better GPP estimation lies in newer satellite products representing different processes or vegetation states, but how they capture interannual GPP dynamics remains to be explored. Here, we differentiate shorter- and longer-term vegetation dynamics and their drivers for several Earth-observation-based vegetation proxies and a GPP estimate using time series decomposition. We find that relations between proxies can significantly differ between time scales, along land cover and climate gradients. For GPP estimated at FLUXNET sites, seasonal and multiannual slopes differ by at least 25% for half of the cases investigated, indicating considerable mismatch if multiannual relations were derived from seasonal slopes. Considering time-scale-specific sensitivities between proxies of vegetation productivity may improve estimates of interannual variability in vegetation productivity. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-12-28 2021-12-28T00:00:00Z 2022-07-26T22:26:28Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/142446 |
url |
http://hdl.handle.net/10362/142446 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0094-8276 PURE: 45617192 https://doi.org/10.1029/2021GL093285 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
mluisa.alvim@gmail.com |
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1817545877637562368 |