Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches

Foliar traits such as specific leaf area (SLA), leaf nitrogen (N), and phosphorus (P) concentrations play important roles in plant economic strategies and ecosystem functioning. Various global maps of these foliar traits have been generated using statistical upscaling approaches based on in-situ tra...

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Autores: Dechant, Benjamin|||0000-0001-5171-2364, Kattge, Jens|||0000-0002-1022-8469, Pavlick, Ryan, Schneider, Fabian D.|||0000-0003-1791-2041, Sabatini, Francesco M., Álvaro Moreno-Martínez, Álvaro, Butler, Ethan E.|||0000-0003-3482-1950, van Bodegom, Peter|||0000-0003-0771-4500, Vallicrosa Pou, Helena|||0000-0002-5860-3096, Kattenborn, Teja|||0000-0001-7381-3828, Boonman, Coline C. F.|||0000-0003-2417-1579, Madani, Nima, Wright, Ian J.|||0000-0001-8338-9143, Dong, Ning|||0000-0003-0793-8854, Feilhauer, Hannes, Peñuelas, Josep|||0000-0002-7215-0150, Sardans i Galobart, Jordi|||0000-0003-2478-0219, Aguirre-Gutiérrez, Jesús|||0000-0001-9190-3229, Reich, Peter|||0000-0003-4424-662X, J. Leitão, Pedro J., Townsend, Philip A.
Tipo de documento: artigo
Data de publicação:2024
País:España
Recursos:Universitat Autònoma de Barcelona
Repositório:Dipòsit Digital de Documents de la UAB
Idioma:inglês
OAI Identifier:oai:ddd.uab.cat:294941
Acesso em linha:https://ddd.uab.cat/record/294941
https://dx.doi.org/urn:doi:10.1016/j.rse.2024.114276
Access Level:Acceso aberto
Palavra-chave:Foliar trait
Specific leaf area
Leaf nitrogen
Leaf phosphorus
Global mapUpscaling
id ES_73e839ed3b9cefeb28417736ddff942e
oai_identifier_str oai:ddd.uab.cat:294941
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches
title Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches
spellingShingle Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches
Dechant, Benjamin|||0000-0001-5171-2364
Foliar trait
Specific leaf area
Leaf nitrogen
Leaf phosphorus
Global mapUpscaling
title_short Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches
title_full Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches
title_fullStr Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches
title_full_unstemmed Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches
title_sort Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approaches
dc.creator.none.fl_str_mv Dechant, Benjamin|||0000-0001-5171-2364
Kattge, Jens|||0000-0002-1022-8469
Pavlick, Ryan
Schneider, Fabian D.|||0000-0003-1791-2041
Sabatini, Francesco M.
Álvaro Moreno-Martínez, Álvaro
Butler, Ethan E.|||0000-0003-3482-1950
van Bodegom, Peter|||0000-0003-0771-4500
Vallicrosa Pou, Helena|||0000-0002-5860-3096
Kattenborn, Teja|||0000-0001-7381-3828
Boonman, Coline C. F.|||0000-0003-2417-1579
Madani, Nima
Wright, Ian J.|||0000-0001-8338-9143
Dong, Ning|||0000-0003-0793-8854
Feilhauer, Hannes
Peñuelas, Josep|||0000-0002-7215-0150
Sardans i Galobart, Jordi|||0000-0003-2478-0219
Aguirre-Gutiérrez, Jesús|||0000-0001-9190-3229
Reich, Peter|||0000-0003-4424-662X
J. Leitão, Pedro J.
Townsend, Philip A.
author Dechant, Benjamin|||0000-0001-5171-2364
author_facet Dechant, Benjamin|||0000-0001-5171-2364
Kattge, Jens|||0000-0002-1022-8469
Pavlick, Ryan
Schneider, Fabian D.|||0000-0003-1791-2041
Sabatini, Francesco M.
Álvaro Moreno-Martínez, Álvaro
Butler, Ethan E.|||0000-0003-3482-1950
van Bodegom, Peter|||0000-0003-0771-4500
Vallicrosa Pou, Helena|||0000-0002-5860-3096
Kattenborn, Teja|||0000-0001-7381-3828
Boonman, Coline C. F.|||0000-0003-2417-1579
Madani, Nima
Wright, Ian J.|||0000-0001-8338-9143
Dong, Ning|||0000-0003-0793-8854
Feilhauer, Hannes
Peñuelas, Josep|||0000-0002-7215-0150
Sardans i Galobart, Jordi|||0000-0003-2478-0219
Aguirre-Gutiérrez, Jesús|||0000-0001-9190-3229
Reich, Peter|||0000-0003-4424-662X
J. Leitão, Pedro J.
Townsend, Philip A.
author_role author
author2 Kattge, Jens|||0000-0002-1022-8469
Pavlick, Ryan
Schneider, Fabian D.|||0000-0003-1791-2041
Sabatini, Francesco M.
Álvaro Moreno-Martínez, Álvaro
Butler, Ethan E.|||0000-0003-3482-1950
van Bodegom, Peter|||0000-0003-0771-4500
Vallicrosa Pou, Helena|||0000-0002-5860-3096
Kattenborn, Teja|||0000-0001-7381-3828
Boonman, Coline C. F.|||0000-0003-2417-1579
Madani, Nima
Wright, Ian J.|||0000-0001-8338-9143
Dong, Ning|||0000-0003-0793-8854
Feilhauer, Hannes
Peñuelas, Josep|||0000-0002-7215-0150
Sardans i Galobart, Jordi|||0000-0003-2478-0219
Aguirre-Gutiérrez, Jesús|||0000-0001-9190-3229
Reich, Peter|||0000-0003-4424-662X
J. Leitão, Pedro J.
Townsend, Philip A.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Foliar trait
Specific leaf area
Leaf nitrogen
Leaf phosphorus
Global mapUpscaling
topic Foliar trait
Specific leaf area
Leaf nitrogen
Leaf phosphorus
Global mapUpscaling
description Foliar traits such as specific leaf area (SLA), leaf nitrogen (N), and phosphorus (P) concentrations play important roles in plant economic strategies and ecosystem functioning. Various global maps of these foliar traits have been generated using statistical upscaling approaches based on in-situ trait observations. Here, we intercompare such global upscaled foliar trait maps at 0.5° spatial resolution (six maps for SLA, five for N, three for P), categorize the upscaling approaches used to generate them, and evaluate the maps with trait estimates from a global database of vegetation plots (sPlotOpen). We disentangled the contributions from different plant functional types (PFTs) to the upscaled maps and quantified the impacts of using different plot-level trait metrics on the evaluation with sPlotOpen: community weighted mean (CWM) and top-of-canopy weighted mean (TWM). We found that the global foliar trait maps of SLA and N differ drastically and fall into two groups that are almost uncorrelated (for P only maps from one group were available). The primary factor explaining the differences between these groups is the use of PFT information combined with remote sensing-derived land cover products in one group while the other group mostly relied on environmental predictors alone. The maps that used PFT and corresponding land cover information exhibit considerable similarities in spatial patterns that are strongly driven by land cover. The maps not using PFTs show a lower level of similarity and tend to be strongly driven by individual environmental variables. Upscaled maps of both groups were moderately correlated to sPlotOpen data aggregated to the grid-cell level (R = 0.2-0.6) when processing sPlotOpen in a way that is consistent with the respective trait upscaling approaches, including the plot-level trait metric (CWM or TWM) and the scaling to the grid cells with or without accounting for fractional land cover. The impact of using TWM or CWM was relevant, but considerably smaller than that of the PFT and land cover information. The maps using PFT and land cover information better reproduce the between-PFT trait differences of sPlotOpen data, while the two groups performed similarly in capturing within-PFT trait variation. Our findings highlight the importance of explicitly accounting for within-grid-cell trait variation, which has important implications for applications using existing maps and future upscaling efforts. Remote sensing information has great potential to reduce uncertainties related to scaling from in-situ observations to grid cells and the regression-based mapping steps involved in the upscaling.
publishDate 2024
dc.date.none.fl_str_mv 2
2024-01-01
2024
2024-01-01
dc.type.none.fl_str_mv Article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://ddd.uab.cat/record/294941
https://dx.doi.org/urn:doi:10.1016/j.rse.2024.114276
url https://ddd.uab.cat/record/294941
https://dx.doi.org/urn:doi:10.1016/j.rse.2024.114276
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission https://doi.org/10.13039/501100000780 855187
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
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dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
reponame_str Dipòsit Digital de Documents de la UAB
collection Dipòsit Digital de Documents de la UAB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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spelling Intercomparison of global foliar trait maps reveals fundamental differences and limitations of upscaling approachesDechant, Benjamin|||0000-0001-5171-2364Kattge, Jens|||0000-0002-1022-8469Pavlick, RyanSchneider, Fabian D.|||0000-0003-1791-2041Sabatini, Francesco M.Álvaro Moreno-Martínez, ÁlvaroButler, Ethan E.|||0000-0003-3482-1950van Bodegom, Peter|||0000-0003-0771-4500Vallicrosa Pou, Helena|||0000-0002-5860-3096Kattenborn, Teja|||0000-0001-7381-3828Boonman, Coline C. F.|||0000-0003-2417-1579Madani, NimaWright, Ian J.|||0000-0001-8338-9143Dong, Ning|||0000-0003-0793-8854Feilhauer, HannesPeñuelas, Josep|||0000-0002-7215-0150Sardans i Galobart, Jordi|||0000-0003-2478-0219Aguirre-Gutiérrez, Jesús|||0000-0001-9190-3229Reich, Peter|||0000-0003-4424-662XJ. Leitão, Pedro J.Townsend, Philip A.Foliar traitSpecific leaf areaLeaf nitrogenLeaf phosphorusGlobal mapUpscalingFoliar traits such as specific leaf area (SLA), leaf nitrogen (N), and phosphorus (P) concentrations play important roles in plant economic strategies and ecosystem functioning. Various global maps of these foliar traits have been generated using statistical upscaling approaches based on in-situ trait observations. Here, we intercompare such global upscaled foliar trait maps at 0.5° spatial resolution (six maps for SLA, five for N, three for P), categorize the upscaling approaches used to generate them, and evaluate the maps with trait estimates from a global database of vegetation plots (sPlotOpen). We disentangled the contributions from different plant functional types (PFTs) to the upscaled maps and quantified the impacts of using different plot-level trait metrics on the evaluation with sPlotOpen: community weighted mean (CWM) and top-of-canopy weighted mean (TWM). We found that the global foliar trait maps of SLA and N differ drastically and fall into two groups that are almost uncorrelated (for P only maps from one group were available). The primary factor explaining the differences between these groups is the use of PFT information combined with remote sensing-derived land cover products in one group while the other group mostly relied on environmental predictors alone. The maps that used PFT and corresponding land cover information exhibit considerable similarities in spatial patterns that are strongly driven by land cover. The maps not using PFTs show a lower level of similarity and tend to be strongly driven by individual environmental variables. Upscaled maps of both groups were moderately correlated to sPlotOpen data aggregated to the grid-cell level (R = 0.2-0.6) when processing sPlotOpen in a way that is consistent with the respective trait upscaling approaches, including the plot-level trait metric (CWM or TWM) and the scaling to the grid cells with or without accounting for fractional land cover. The impact of using TWM or CWM was relevant, but considerably smaller than that of the PFT and land cover information. The maps using PFT and land cover information better reproduce the between-PFT trait differences of sPlotOpen data, while the two groups performed similarly in capturing within-PFT trait variation. Our findings highlight the importance of explicitly accounting for within-grid-cell trait variation, which has important implications for applications using existing maps and future upscaling efforts. Remote sensing information has great potential to reduce uncertainties related to scaling from in-situ observations to grid cells and the regression-based mapping steps involved in the upscaling. 22024-01-0120242024-01-01Articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://ddd.uab.cat/record/294941https://dx.doi.org/urn:doi:10.1016/j.rse.2024.114276reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengEuropean Commission https://doi.org/10.13039/501100000780 855187open accesshttp://purl.org/coar/access_right/c_abf2Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:2949412026-06-06T12:50:31Z
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