Peat Carbon Vulnerability to Projected Climate Warming in the Hudson Bay Lowlands, Canada: A Decision Support Tool for Land Use Planning in Peatland Dominated Landscapes

Peatlands help regulate climate by sequestering (net removal) carbon from the atmosphere and storing it in plants and soils. However, as mean annual air temperature (MAAT) increases, peat carbon stocks may decrease. We conducted an in-depth synthesis of current knowledge about ecosystem controls on...

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Published in:Frontiers in Earth Science
Main Authors: James W. McLaughlin, Maara S. Packalen
Format: Article in Journal/Newspaper
Language:English
Published: Frontiers Media S.A. 2021
Subjects:
Q
Online Access:https://doi.org/10.3389/feart.2021.650662
https://doaj.org/article/17ac6c050970491b89d7ada65ce3764f
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spelling ftdoajarticles:oai:doaj.org/article:17ac6c050970491b89d7ada65ce3764f 2023-05-15T16:35:21+02:00 Peat Carbon Vulnerability to Projected Climate Warming in the Hudson Bay Lowlands, Canada: A Decision Support Tool for Land Use Planning in Peatland Dominated Landscapes James W. McLaughlin Maara S. Packalen 2021-07-01T00:00:00Z https://doi.org/10.3389/feart.2021.650662 https://doaj.org/article/17ac6c050970491b89d7ada65ce3764f EN eng Frontiers Media S.A. https://www.frontiersin.org/articles/10.3389/feart.2021.650662/full https://doaj.org/toc/2296-6463 2296-6463 doi:10.3389/feart.2021.650662 https://doaj.org/article/17ac6c050970491b89d7ada65ce3764f Frontiers in Earth Science, Vol 9 (2021) hudson bay lowlands moisture index climate warming peat carbon vulnerability probabilistic modelling land use planning Science Q article 2021 ftdoajarticles https://doi.org/10.3389/feart.2021.650662 2022-12-31T13:17:07Z Peatlands help regulate climate by sequestering (net removal) carbon from the atmosphere and storing it in plants and soils. However, as mean annual air temperature (MAAT) increases, peat carbon stocks may decrease. We conducted an in-depth synthesis of current knowledge about ecosystem controls on peatland carbon storage and fluxes to constrain the most influential parameters in probabilistic modelling of peat carbon sinks, such as Bayesian belief networks. Evaluated parameters included climate, carbon flux and mass, land cover, landscape position (defined here as elevation), fire records, and current and future climate scenarios for a 74,300 km2 landscape in the Hudson Bay Lowlands, Canada. The Bayesian belief network was constructed with four tiers: 1) exposure, expressed as MAAT, and the state variables of elevation and land cover; 2) sensitivity, expressed as ecosystem conditions relevant to peat carbon mass and its quality for decomposition, peat wetness, and fire; 3) carbon dioxide and methane fluxes and peat combustion; and 4) vulnerability of peat carbon sink strength under warmer MAAT. Simulations were conducted using current (−3.0 to 0.0°C), moderately warmer (0.1–4.0°C), and severely warmer (4.1–9.0°C) climate scenarios. Results from the severely warmer climate scenario projected an overall drying of peat, with approximately 20% reduction in the strong sink categories of net ecosystem exchange and peat carbon sink strength for the severely and, to a lesser degree, the moderately warmer climate scenarios relative to current MAAT. In the warmest temperature simulation, probability of methane emission decreased slightly and the probability of the strong peat carbon sink strength was 27% lower due to peat combustion. Our Bayesian belief network can assist land planners in decision-making for peatland-dominated landscapes, such as identifying high carbon storage areas and those projected to be at greatest risk of carbon loss due to climate change. Such areas may be designated, for example, as protected or ... Article in Journal/Newspaper Hudson Bay Directory of Open Access Journals: DOAJ Articles Canada Hudson Hudson Bay Frontiers in Earth Science 9
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic hudson bay lowlands
moisture index
climate warming
peat carbon vulnerability
probabilistic modelling
land use planning
Science
Q
spellingShingle hudson bay lowlands
moisture index
climate warming
peat carbon vulnerability
probabilistic modelling
land use planning
Science
Q
James W. McLaughlin
Maara S. Packalen
Peat Carbon Vulnerability to Projected Climate Warming in the Hudson Bay Lowlands, Canada: A Decision Support Tool for Land Use Planning in Peatland Dominated Landscapes
topic_facet hudson bay lowlands
moisture index
climate warming
peat carbon vulnerability
probabilistic modelling
land use planning
Science
Q
description Peatlands help regulate climate by sequestering (net removal) carbon from the atmosphere and storing it in plants and soils. However, as mean annual air temperature (MAAT) increases, peat carbon stocks may decrease. We conducted an in-depth synthesis of current knowledge about ecosystem controls on peatland carbon storage and fluxes to constrain the most influential parameters in probabilistic modelling of peat carbon sinks, such as Bayesian belief networks. Evaluated parameters included climate, carbon flux and mass, land cover, landscape position (defined here as elevation), fire records, and current and future climate scenarios for a 74,300 km2 landscape in the Hudson Bay Lowlands, Canada. The Bayesian belief network was constructed with four tiers: 1) exposure, expressed as MAAT, and the state variables of elevation and land cover; 2) sensitivity, expressed as ecosystem conditions relevant to peat carbon mass and its quality for decomposition, peat wetness, and fire; 3) carbon dioxide and methane fluxes and peat combustion; and 4) vulnerability of peat carbon sink strength under warmer MAAT. Simulations were conducted using current (−3.0 to 0.0°C), moderately warmer (0.1–4.0°C), and severely warmer (4.1–9.0°C) climate scenarios. Results from the severely warmer climate scenario projected an overall drying of peat, with approximately 20% reduction in the strong sink categories of net ecosystem exchange and peat carbon sink strength for the severely and, to a lesser degree, the moderately warmer climate scenarios relative to current MAAT. In the warmest temperature simulation, probability of methane emission decreased slightly and the probability of the strong peat carbon sink strength was 27% lower due to peat combustion. Our Bayesian belief network can assist land planners in decision-making for peatland-dominated landscapes, such as identifying high carbon storage areas and those projected to be at greatest risk of carbon loss due to climate change. Such areas may be designated, for example, as protected or ...
format Article in Journal/Newspaper
author James W. McLaughlin
Maara S. Packalen
author_facet James W. McLaughlin
Maara S. Packalen
author_sort James W. McLaughlin
title Peat Carbon Vulnerability to Projected Climate Warming in the Hudson Bay Lowlands, Canada: A Decision Support Tool for Land Use Planning in Peatland Dominated Landscapes
title_short Peat Carbon Vulnerability to Projected Climate Warming in the Hudson Bay Lowlands, Canada: A Decision Support Tool for Land Use Planning in Peatland Dominated Landscapes
title_full Peat Carbon Vulnerability to Projected Climate Warming in the Hudson Bay Lowlands, Canada: A Decision Support Tool for Land Use Planning in Peatland Dominated Landscapes
title_fullStr Peat Carbon Vulnerability to Projected Climate Warming in the Hudson Bay Lowlands, Canada: A Decision Support Tool for Land Use Planning in Peatland Dominated Landscapes
title_full_unstemmed Peat Carbon Vulnerability to Projected Climate Warming in the Hudson Bay Lowlands, Canada: A Decision Support Tool for Land Use Planning in Peatland Dominated Landscapes
title_sort peat carbon vulnerability to projected climate warming in the hudson bay lowlands, canada: a decision support tool for land use planning in peatland dominated landscapes
publisher Frontiers Media S.A.
publishDate 2021
url https://doi.org/10.3389/feart.2021.650662
https://doaj.org/article/17ac6c050970491b89d7ada65ce3764f
geographic Canada
Hudson
Hudson Bay
geographic_facet Canada
Hudson
Hudson Bay
genre Hudson Bay
genre_facet Hudson Bay
op_source Frontiers in Earth Science, Vol 9 (2021)
op_relation https://www.frontiersin.org/articles/10.3389/feart.2021.650662/full
https://doaj.org/toc/2296-6463
2296-6463
doi:10.3389/feart.2021.650662
https://doaj.org/article/17ac6c050970491b89d7ada65ce3764f
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container_title Frontiers in Earth Science
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