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description Publicationkeyboard_double_arrow_right Article , Other literature type 2023 France, France, Austria, France, United Kingdom, FinlandPublisher:Springer Science and Business Media LLC Publicly fundedFunded by:ARC | Discovery Projects - Gran...ARC| Discovery Projects - Grant ID: DP200102542Budiman Minasny; Diana Vigah Adetsu; Matt Aitkenhead; Rebekka Artz; Nikki Baggaley; Alexandra Barthelmes; Amélie Beucher; Jean Caron; Giulia Conchedda; John Connolly; Raphaël Deragon; Chris Evans; Kjetil Damsberg Fadnes; Dian Fiantis; Zisis Gagkas; Louis Gilet; Alessandro Gimona; Stephan Glatzel; Mogens H. Greve; Wahaj Habib; Kristell Hergoualc'h; Cecilie Hermansen; Darren Kidd; Triven Koganti; Dianna Kopansky; David J. Large; Tuula Larmola; A. Lilly; Haojie Liu; Matthew A. Marcus; Maarit Middleton; Keith Morrison; Rasmus Jes Petersen; Tristan Quaife; Line Rochefort; . Rudiyanto; Linda Toca; Francesco N. Tubiello; Peter Lystbæk Weber; Simon Weldon; Wirastuti Widyatmanti; Jenny Williamson; Dominik Zak;handle: 10568/135828
AbstractPeatlands cover only 3–4% of the Earth’s surface, but they store nearly 30% of global soil carbon stock. This significant carbon store is under threat as peatlands continue to be degraded at alarming rates around the world. It has prompted countries worldwide to establish regulations to conserve and reduce emissions from this carbon rich ecosystem. For example, the EU has implemented new rules that mandate sustainable management of peatlands, critical to reaching the goal of carbon neutrality by 2050. However, a lack of information on the extent and condition of peatlands has hindered the development of national policies and restoration efforts. This paper reviews the current state of knowledge on mapping and monitoring peatlands from field sites to the globe and identifies areas where further research is needed. It presents an overview of the different methodologies used to map peatlands in nine countries, which vary in definition of peat soil and peatland, mapping coverage, and mapping detail. Whereas mapping peatlands across the world with only one approach is hardly possible, the paper highlights the need for more consistent approaches within regions having comparable peatland types and climates to inform their protection and urgent restoration. The review further summarises various approaches used for monitoring peatland conditions and functions. These include monitoring at the plot scale for degree of humification and stoichiometric ratio, and proximal sensing such as gamma radiometrics and electromagnetic induction at the field to landscape scale for mapping peat thickness and identifying hotspots for greenhouse gas (GHG) emissions. Remote sensing techniques with passive and active sensors at regional to national scale can help in monitoring subsidence rate, water table, peat moisture, landslides, and GHG emissions. Although the use of water table depth as a proxy for interannual GHG emissions from peatlands has been well established, there is no single remote sensing method or data product yet that has been verified beyond local or regional scales. Broader land-use change and fire monitoring at a global scale may further assist national GHG inventory reporting. Monitoring of peatland conditions to evaluate the success of individual restoration schemes still requires field work to assess local proxies combined with remote sensing and modeling. Long-term monitoring is necessary to draw valid conclusions on revegetation outcomes and associated GHG emissions in rewetted peatlands, as their dynamics are not fully understood at the site level. Monitoring vegetation development and hydrology of restored peatlands is needed as a proxy to assess the return of water and changes in nutrient cycling and biodiversity.
NERC Open Research A... arrow_drop_down CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2023License: CC BYFull-Text: https://hdl.handle.net/10568/135828Data sources: Bielefeld Academic Search Engine (BASE)Natural Environment Research Council: NERC Open Research ArchiveArticle . 2023License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 39 citations 39 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!
more_vert NERC Open Research A... arrow_drop_down CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2023License: CC BYFull-Text: https://hdl.handle.net/10568/135828Data sources: Bielefeld Academic Search Engine (BASE)Natural Environment Research Council: NERC Open Research ArchiveArticle . 2023License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:Zenodo Castellazzi, Marie; Gimona, Alessandro; Wardell-Johnson, Douglas; Miller, Dave; Rivington, Mike; Matthews, Keith;This dataset contains a land use change scenario (2050) for Scotland within the scope of a SSP1 - Low emissions scenario (Shared Socio-Economic Pathways). For achieving a low-emissions scenario, simulated land use change targeted woodland expansion (including silvo-arable and silvo-pastoral) and decreased grazing intensity, both land use changes also aimed at benefitting four aspects of ecosystem services: carbon storage through tree planting, emission reduction through deintensification, biodiversity enhancement through tree planting, and pollination to support food production. The 2019 baseline land use map at 100m resolution, was created by combining the Land Cover Map 2019 (Morton et al, 2020), estimations of stocking rates from IACS (Wardell-Johnson, 2022), and grazing conservation thresholds (Chapman, 2007; FAS, 2021). The land use scenario map was created using the SLM-OptionsTool, a land use change tool for Ecosystem Services based on the LandSFACTS model (Castellazzi et al, 2010). The attached land use scenario map for 2050 is not an optimised result, but it is only one possibility among others that meets all the constraints stipulated for the scenario. For a detailed description of the scenario refer to the following web storymap : https://storymaps.arcgis.com/stories/c3d3feff85f14460b6c973127089d6f9 This analysis was conducted as part of the Land use Transformations (https://landusetransformations.hutton.ac.uk/) project (JHI-C3-1) in the Scottish Government funded Strategic Research Programme 2022-27. The exact licence for this dataset is currently being finalised. When ready, the dataset will be uploaded as a new version.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
visibility 2visibility views 2 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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description Publicationkeyboard_double_arrow_right Article , Other literature type 2023 France, France, Austria, France, United Kingdom, FinlandPublisher:Springer Science and Business Media LLC Publicly fundedFunded by:ARC | Discovery Projects - Gran...ARC| Discovery Projects - Grant ID: DP200102542Budiman Minasny; Diana Vigah Adetsu; Matt Aitkenhead; Rebekka Artz; Nikki Baggaley; Alexandra Barthelmes; Amélie Beucher; Jean Caron; Giulia Conchedda; John Connolly; Raphaël Deragon; Chris Evans; Kjetil Damsberg Fadnes; Dian Fiantis; Zisis Gagkas; Louis Gilet; Alessandro Gimona; Stephan Glatzel; Mogens H. Greve; Wahaj Habib; Kristell Hergoualc'h; Cecilie Hermansen; Darren Kidd; Triven Koganti; Dianna Kopansky; David J. Large; Tuula Larmola; A. Lilly; Haojie Liu; Matthew A. Marcus; Maarit Middleton; Keith Morrison; Rasmus Jes Petersen; Tristan Quaife; Line Rochefort; . Rudiyanto; Linda Toca; Francesco N. Tubiello; Peter Lystbæk Weber; Simon Weldon; Wirastuti Widyatmanti; Jenny Williamson; Dominik Zak;handle: 10568/135828
AbstractPeatlands cover only 3–4% of the Earth’s surface, but they store nearly 30% of global soil carbon stock. This significant carbon store is under threat as peatlands continue to be degraded at alarming rates around the world. It has prompted countries worldwide to establish regulations to conserve and reduce emissions from this carbon rich ecosystem. For example, the EU has implemented new rules that mandate sustainable management of peatlands, critical to reaching the goal of carbon neutrality by 2050. However, a lack of information on the extent and condition of peatlands has hindered the development of national policies and restoration efforts. This paper reviews the current state of knowledge on mapping and monitoring peatlands from field sites to the globe and identifies areas where further research is needed. It presents an overview of the different methodologies used to map peatlands in nine countries, which vary in definition of peat soil and peatland, mapping coverage, and mapping detail. Whereas mapping peatlands across the world with only one approach is hardly possible, the paper highlights the need for more consistent approaches within regions having comparable peatland types and climates to inform their protection and urgent restoration. The review further summarises various approaches used for monitoring peatland conditions and functions. These include monitoring at the plot scale for degree of humification and stoichiometric ratio, and proximal sensing such as gamma radiometrics and electromagnetic induction at the field to landscape scale for mapping peat thickness and identifying hotspots for greenhouse gas (GHG) emissions. Remote sensing techniques with passive and active sensors at regional to national scale can help in monitoring subsidence rate, water table, peat moisture, landslides, and GHG emissions. Although the use of water table depth as a proxy for interannual GHG emissions from peatlands has been well established, there is no single remote sensing method or data product yet that has been verified beyond local or regional scales. Broader land-use change and fire monitoring at a global scale may further assist national GHG inventory reporting. Monitoring of peatland conditions to evaluate the success of individual restoration schemes still requires field work to assess local proxies combined with remote sensing and modeling. Long-term monitoring is necessary to draw valid conclusions on revegetation outcomes and associated GHG emissions in rewetted peatlands, as their dynamics are not fully understood at the site level. Monitoring vegetation development and hydrology of restored peatlands is needed as a proxy to assess the return of water and changes in nutrient cycling and biodiversity.
NERC Open Research A... arrow_drop_down CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2023License: CC BYFull-Text: https://hdl.handle.net/10568/135828Data sources: Bielefeld Academic Search Engine (BASE)Natural Environment Research Council: NERC Open Research ArchiveArticle . 2023License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10533-023-01084-1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 39 citations 39 popularity Top 10% influence Top 10% impulse Top 1% Powered by BIP!
more_vert NERC Open Research A... arrow_drop_down CGIAR CGSpace (Consultative Group on International Agricultural Research)Article . 2023License: CC BYFull-Text: https://hdl.handle.net/10568/135828Data sources: Bielefeld Academic Search Engine (BASE)Natural Environment Research Council: NERC Open Research ArchiveArticle . 2023License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10533-023-01084-1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:Zenodo Castellazzi, Marie; Gimona, Alessandro; Wardell-Johnson, Douglas; Miller, Dave; Rivington, Mike; Matthews, Keith;This dataset contains a land use change scenario (2050) for Scotland within the scope of a SSP1 - Low emissions scenario (Shared Socio-Economic Pathways). For achieving a low-emissions scenario, simulated land use change targeted woodland expansion (including silvo-arable and silvo-pastoral) and decreased grazing intensity, both land use changes also aimed at benefitting four aspects of ecosystem services: carbon storage through tree planting, emission reduction through deintensification, biodiversity enhancement through tree planting, and pollination to support food production. The 2019 baseline land use map at 100m resolution, was created by combining the Land Cover Map 2019 (Morton et al, 2020), estimations of stocking rates from IACS (Wardell-Johnson, 2022), and grazing conservation thresholds (Chapman, 2007; FAS, 2021). The land use scenario map was created using the SLM-OptionsTool, a land use change tool for Ecosystem Services based on the LandSFACTS model (Castellazzi et al, 2010). The attached land use scenario map for 2050 is not an optimised result, but it is only one possibility among others that meets all the constraints stipulated for the scenario. For a detailed description of the scenario refer to the following web storymap : https://storymaps.arcgis.com/stories/c3d3feff85f14460b6c973127089d6f9 This analysis was conducted as part of the Land use Transformations (https://landusetransformations.hutton.ac.uk/) project (JHI-C3-1) in the Scottish Government funded Strategic Research Programme 2022-27. The exact licence for this dataset is currently being finalised. When ready, the dataset will be uploaded as a new version.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.7675268&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
visibility 2visibility views 2 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.7675268&type=result"></script>'); --> </script>
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