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A Multi-Model Gap-Filling Strategy Increases the Accuracy of GPP Estimation from Periodic Chamber-Based Flux Measurements on Sphagnum-Dominated Peatland

cris.lastimport.scopus2025-10-23T06:56:32Z
cris.virtual.author-orcid0000-0003-0901-9894
cris.virtual.author-orcid0000-0002-0953-7045
cris.virtual.author-orcid0000-0002-5212-7383
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcidfaa187d8-53df-4536-8acf-ac523f3e8a05
cris.virtualsource.author-orcid0af80967-45b1-40e8-a0bf-9989e4e639c2
cris.virtualsource.author-orcid039c5639-27fb-49d1-97b9-e20f4c473688
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
dc.abstract.enGross primary productivity (GPP), the primary driver of carbon accumulation, governs the sequestration of atmospheric CO2 into biomass. However, GPP cannot be measured directly, as photosynthesis and respiration are simultaneous. At canopy level in plot-scale studies, GPP can be estimated through the closed chamber-based measurements of net ecosystem exchange (NEE) and ecosystem respiration (Reco). This technique is cost-effective and widely used in small-scale studies with short vegetation, but measurements are periodic-based and require temporal interpolations. The rectangular hyperbolic model (RH) was the basis of this study, developing two temperature-dependent factors following a linear and exponential shift in GPP when the temperature oscillates from the optimum for vegetation performance. Additionally, a water table depth (WTD)-dependent model and an exponential model were tested. In the peak season, modified RH models showed the best performance, while for the rest of the year, the best model varied for each subplot. The statistical results demonstrate the limitations of assuming the light-use efficiency as a fixed shape mechanism (using only one model). Therefore, a multi-model approach with the best performance model selected for each period is proposed to improve GPP estimations for peatlands.
dc.affiliationWydział Inżynierii Środowiska i Inżynierii Mechanicznej
dc.affiliation.instituteKatedra Ekologii i Ochrony Środowiska
dc.contributor.authorAlbert-Saiz, Mar
dc.contributor.authorStróżecki, Marcin Grzegorz
dc.contributor.authorRastogi, Anshu
dc.contributor.authorJuszczak, Radosław
dc.date.access2025-03-31
dc.date.accessioned2025-03-31T10:41:04Z
dc.date.available2025-03-31T10:41:04Z
dc.date.copyright2025-01-07
dc.date.issued2025
dc.description.abstract<jats:p>Gross primary productivity (GPP), the primary driver of carbon accumulation, governs the sequestration of atmospheric CO2 into biomass. However, GPP cannot be measured directly, as photosynthesis and respiration are simultaneous. At canopy level in plot-scale studies, GPP can be estimated through the closed chamber-based measurements of net ecosystem exchange (NEE) and ecosystem respiration (Reco). This technique is cost-effective and widely used in small-scale studies with short vegetation, but measurements are periodic-based and require temporal interpolations. The rectangular hyperbolic model (RH) was the basis of this study, developing two temperature-dependent factors following a linear and exponential shift in GPP when the temperature oscillates from the optimum for vegetation performance. Additionally, a water table depth (WTD)-dependent model and an exponential model were tested. In the peak season, modified RH models showed the best performance, while for the rest of the year, the best model varied for each subplot. The statistical results demonstrate the limitations of assuming the light-use efficiency as a fixed shape mechanism (using only one model). Therefore, a multi-model approach with the best performance model selected for each period is proposed to improve GPP estimations for peatlands.</jats:p>
dc.description.accesstimeat_publication
dc.description.bibliographyil., bibliogr.
dc.description.financepublication_nocost
dc.description.financecost0,00
dc.description.if3,3
dc.description.number2
dc.description.points100
dc.description.versionfinal_published
dc.description.volume17
dc.identifier.doi10.3390/su17020393
dc.identifier.issn2071-1050
dc.identifier.urihttps://sciencerep.up.poznan.pl/handle/item/2657
dc.identifier.weblinkhttps://www.researchgate.net/publication/387819661_A_Multi-Model_Gap-Filling_Strategy_Increases_the_Accuracy_of_GPP_Estimation_from_Periodic_Chamber-Based_Flux_Measurements_on_Sphagnum-Dominated_Peatland
dc.languageen
dc.pbn.affiliationenvironmental engineering, mining and energy
dc.relation.ispartofSustainability
dc.relation.pagesart. 393
dc.rightsCC-BY
dc.sciencecloudsend
dc.share.typeOPEN_JOURNAL
dc.subject.enpeatland
dc.subject.engross primary productivity
dc.subject.enphotosynthesis
dc.subject.enwater table depth
dc.subject.enmodelling
dc.subject.encarbon cycle
dc.subject.plTorfowisko
dc.subject.plproduktywność pierowotna brutto
dc.subject.plfotosynteza
dc.subject.plpoziom wód gruntowych
dc.subject.plmodelowanie
dc.subject.plcykl węgla
dc.titleA Multi-Model Gap-Filling Strategy Increases the Accuracy of GPP Estimation from Periodic Chamber-Based Flux Measurements on Sphagnum-Dominated Peatland
dc.typeJournalArticle
dspace.entity.typePublication
oaire.citation.issue2
oaire.citation.volume17