Methane emissions from high latitude peatlands: controls of their spatio-temporal dynamics across a mire complex

Koffi Dodji Noumonvi

doi:10.54612/a.7rle58mqf6

Methane emissions from high latitude peatlands: controls of their spatio-temporal dynamics across a mire complex

Bidragets översatta titel: Metanemissioner från nordliga myrar: Reglering av spatio-temporala dynamik över ett myrkomplex

Koffi Dodji Noumonvi

Institutionen för skogens ekologi och skötsel

Publikation: Avhandling › Doktorsavhandling

15 Nedladdningar

Sammanfattning

Nordliga myrar är viktiga naturliga källor till atmosfärisk metan (CH4), men det finns betydande osäkerheter kring hur stor denna källa är, vilket påverkar globala CH4- budgetskattningar. En viktig källa till denna osäkerhet är begränsad förståelse för rumsliga variationer inom myrkomplex på mesoskalan. Nuvarande skattningar förlitar sig ofta på empiriska mätningar från enstaka platser, som sedan antas vara representativa för ett större område. Denna avhandling använde Kulbäckslidens Forskningsinfrastruktur (KRI) i norra Sverige, som omfattar fyra eddy covariancestationer spridda över ett myrkomplex, för att undersöka variationer i CH4-flöden (FCH4) på mesoskala. Först dokumenterades infrastrukturens unika konfiguration med replikerade ekosystemmätningar och kartering av vegetationen (Artikel I). Sedan utvecklades HuHoLa modellen för klassificering av torvmarksmikrotopografi (Artikel II). Vidare undersöktes rumsliga mönster i FCH4 över myrkomplexet och faktorer som reglerar CH4-utbytet (Artikel III). Slutligen utvecklades datadrivna metoder för uppskalning av mätningar från enstaka platser till ett större geografiskt område (Artikel IV). Resultaten visade att replikerade ekosystem-skaliga mätningar är nödvändiga för att förstå rumslig variation och utveckla uppskalningsmetoder. HuHoLa förbättrade karakteriseringen av myrelement, bortom traditionella binära klassificeringar, genom att identifiera tre mikroformklasser och tillhandahålla indikatorer för kartläggning av grundvattennivå och marktemperatur (Ts). Rumslig variation i FCH4 inom myrkomplexet motsvarade den som vanligtvis observeras bland geografiskt avlägsna myrlokaler, där C:N-förhållandet sätter utgångspunkten för rumsliga variationer medan Ts och växtproduktivitet reglerade tidsvariationer. De utvecklade uppskalningsmetoderna minskade osäkerheten i uppskattningar av FCH4 från myrkomplex med upp till 50% jämfört med enklare extrapolering från enstaka lokaler. Resultaten bidrar till ny förståelse och verktyg för att minska osäkerheter i skattningen av den globala CH4-budgeten, vilket är avgörande för att förutsäga myrar-klimat återkopplingar under miljöförändringar

Bidragets översatta titel	Metanemissioner från nordliga myrar: Reglering av spatio-temporala dynamik över ett myrkomplex
Originalspråk	Engelska
Kvalifikation	Doktor i filosofi
Förlag	Swedish University of Agricultural Sciences
Tryckta ISBN	978-91-8046-448-2
Elektroniska ISBN	978-91-8046-498-7
DOI	https://doi.org/10.54612/a.7rle58mqf6
Status	Publicerad - 2025

Nyckelord

C:N ratio
eddy covariance
footprint analysis
machine learning
methane flux
microtopography
peatland
research infrastructure
upscaling

SLU-serie

Acta Universitatis Agriculturae Sueciae

Åtkomst av dokument

10.54612/a.7rle58mqf6

FulltextSlutlig publicerad version, 33,2 MBLicens: CC BY-NC

Andra filer och länkar

Permanent länk till denna sida

Citera det här

@phdthesis{5b7eb6a9f1544b84af1cafc99c2f7efc,

title = "Methane emissions from high latitude peatlands: controls of their spatio-temporal dynamics across a mire complex",

abstract = "Northern peatlands are significant natural sources of atmospheric methane (CH4), yet high uncertainties remain in estimates of global CH4 budgets. A key source of this uncertainty is a limited understanding of spatial variations at the mesoscale of peatland complexes. Current estimates typically rely on single-site measurements at the local scale. This thesis utilized the Kulb{\"a}cksliden Research Infrastructure (KRI) in northern Sweden, comprising four eddy covariance tower stations across a peatland complex, with the overall aim to investigate and predict mesoscale variations in CH4 fluxes (FCH4). The research first documented the infrastructure's unique configuration with replicated ecosystem-scale measurements and detailed mapping of vegetation (Paper I), then developed the Hummock-Hollow-Lawn (HuHoLa) model for peatland microtopography classification (Paper II). Using data from the KRI, spatial patterns in FCH4 across the mire complex and their environmental controls were investigated (Paper III), followed by the development of data-driven approaches for upscaling single-site measurements (Paper IV). Key findings demonstrated that replicated ecosystem-scale measurements are essential for understanding spatial heterogeneity in peatland processes and developing upscaling approaches. The HuHoLa model advanced peatland surface characterization beyond traditional binary classifications by identifying three distinct microform classes and providing proxies for mapping water table depth and soil temperature (Ts). Spatial variability in FCH4 within the mire complex matched that typically observed among geographically distant mire systems, with C:N ratio setting the baseline for spatial variations while Ts and plant productivity controlled temporal dynamics. The developed upscaling approaches reduced uncertainty in mire complex FCH4 estimates by up to 50\% compared to simple single-site extrapolation. These advances provide new understanding and tools for reducing uncertainties in global CH4 budget estimates, crucial for predicting peatland-climate feedbacks under changing environmental conditions.",

keywords = "C:N ratio, eddy covariance, footprint analysis, machine learning, methane flux, microtopography, peatland, research infrastructure, upscaling, C:N ratio, eddy covariance, footprint analysis, machine learning, methane flux, microtopography, peatland, research infrastructure, upscaling",

author = "Noumonvi, \{Koffi Dodji\}",

year = "2025",

doi = "10.54612/a.7rle58mqf6",

language = "English",

isbn = "978-91-8046-448-2",

series = "Acta Universitatis Agriculturae Sueciae",

publisher = "Swedish University of Agricultural Sciences",

number = "2025:13",

address = "Sweden",

}

TY - BOOK

T1 - Methane emissions from high latitude peatlands

T2 - controls of their spatio-temporal dynamics across a mire complex

AU - Noumonvi, Koffi Dodji

PY - 2025

Y1 - 2025

N2 - Northern peatlands are significant natural sources of atmospheric methane (CH4), yet high uncertainties remain in estimates of global CH4 budgets. A key source of this uncertainty is a limited understanding of spatial variations at the mesoscale of peatland complexes. Current estimates typically rely on single-site measurements at the local scale. This thesis utilized the Kulbäcksliden Research Infrastructure (KRI) in northern Sweden, comprising four eddy covariance tower stations across a peatland complex, with the overall aim to investigate and predict mesoscale variations in CH4 fluxes (FCH4). The research first documented the infrastructure's unique configuration with replicated ecosystem-scale measurements and detailed mapping of vegetation (Paper I), then developed the Hummock-Hollow-Lawn (HuHoLa) model for peatland microtopography classification (Paper II). Using data from the KRI, spatial patterns in FCH4 across the mire complex and their environmental controls were investigated (Paper III), followed by the development of data-driven approaches for upscaling single-site measurements (Paper IV). Key findings demonstrated that replicated ecosystem-scale measurements are essential for understanding spatial heterogeneity in peatland processes and developing upscaling approaches. The HuHoLa model advanced peatland surface characterization beyond traditional binary classifications by identifying three distinct microform classes and providing proxies for mapping water table depth and soil temperature (Ts). Spatial variability in FCH4 within the mire complex matched that typically observed among geographically distant mire systems, with C:N ratio setting the baseline for spatial variations while Ts and plant productivity controlled temporal dynamics. The developed upscaling approaches reduced uncertainty in mire complex FCH4 estimates by up to 50% compared to simple single-site extrapolation. These advances provide new understanding and tools for reducing uncertainties in global CH4 budget estimates, crucial for predicting peatland-climate feedbacks under changing environmental conditions.

AB - Northern peatlands are significant natural sources of atmospheric methane (CH4), yet high uncertainties remain in estimates of global CH4 budgets. A key source of this uncertainty is a limited understanding of spatial variations at the mesoscale of peatland complexes. Current estimates typically rely on single-site measurements at the local scale. This thesis utilized the Kulbäcksliden Research Infrastructure (KRI) in northern Sweden, comprising four eddy covariance tower stations across a peatland complex, with the overall aim to investigate and predict mesoscale variations in CH4 fluxes (FCH4). The research first documented the infrastructure's unique configuration with replicated ecosystem-scale measurements and detailed mapping of vegetation (Paper I), then developed the Hummock-Hollow-Lawn (HuHoLa) model for peatland microtopography classification (Paper II). Using data from the KRI, spatial patterns in FCH4 across the mire complex and their environmental controls were investigated (Paper III), followed by the development of data-driven approaches for upscaling single-site measurements (Paper IV). Key findings demonstrated that replicated ecosystem-scale measurements are essential for understanding spatial heterogeneity in peatland processes and developing upscaling approaches. The HuHoLa model advanced peatland surface characterization beyond traditional binary classifications by identifying three distinct microform classes and providing proxies for mapping water table depth and soil temperature (Ts). Spatial variability in FCH4 within the mire complex matched that typically observed among geographically distant mire systems, with C:N ratio setting the baseline for spatial variations while Ts and plant productivity controlled temporal dynamics. The developed upscaling approaches reduced uncertainty in mire complex FCH4 estimates by up to 50% compared to simple single-site extrapolation. These advances provide new understanding and tools for reducing uncertainties in global CH4 budget estimates, crucial for predicting peatland-climate feedbacks under changing environmental conditions.

KW - C:N ratio

KW - eddy covariance

KW - footprint analysis

KW - machine learning

KW - methane flux

KW - microtopography

KW - peatland

KW - research infrastructure

KW - upscaling

KW - C:N ratio

KW - eddy covariance

KW - footprint analysis

KW - machine learning

KW - methane flux

KW - microtopography

KW - peatland

KW - research infrastructure

KW - upscaling

UR - https://res.slu.se/id/publ/132953

U2 - 10.54612/a.7rle58mqf6

DO - 10.54612/a.7rle58mqf6

M3 - Doctoral thesis

SN - 978-91-8046-448-2

T3 - Acta Universitatis Agriculturae Sueciae

PB - Swedish University of Agricultural Sciences

ER -