Poster – The MYR Project (2018-21): Climate smart management practices on Norwegian organic soils
Xiao Huang, Höglind Mats, Knut Bjørkelo, ...
Cultivated organic soils account for ∼7% of Norway’s agricultural land area, and they are estimated to be a significant source of greenhouse gas (GHG) emissions. The project ‘Climate smart management practices on Norwegian organic soils’ (MYR), commissioned by the Research Council of Norway (decision no. 281109), aims to evaluate GHG (e.g. carbon dioxide, methane and nitrous oxide) emissions and impacts on biomass productivity from three land use types (cultivated, abandoned and restored) on organic soils. At the cultivated sites, impacts of drainage depth and management intensity will be measured. We established experimental sites in Norway covering a broad range of climate and management regimes, which will produce observational data in high spatiotemporal resolution during 2019-2021. Using state-of-the-art modelling techniques, MYR aims to predict the potential GHG mitigation under different scenarios. Four models (BASGRA, DNDC, Coup and ECOSSE) will be further developed according to the soil properties, and then used independently in simulating biogeochemical processes and biomass dynamics in the different land uses. Robust parameterization schemes for each model will be based in the observational data from the project for both soil and crop combinations. Eventually, a multi-model ensemble prediction will be carried out to provide scenario analyses by 2030 and 2050. By integrating experimental results and modelling, the project aims at generating useful information for recommendations on environment-friendly use of Norwegian peatlands.
Poster – The MYR project (2018-21): GHG emissions and biomass production at cultivated organic soils in Norway
Xiao Huang, Mats Höglind, Knut Bjørkelo, ...
Cultivated organic soils (7-8% of Norway’s agricultural land area) are economically important sources for forage production in some regions in Norway, but they are also ‘hot spots’ for greenhouse gas (GHG) emissions. The project ‘Climate smart management practices on Norwegian organic soils’ (MYR; funded by the Research Council of Norway, decision no. 281109) will evaluate how water table management and the intensity of other management practices (i.e. tillage and fertilization intensity) affects both GHG emissions and forage’s quality & production. The overall aim of MYR is to generate useful information for recommendations on climate-friendly management of Norwegian peatlands for both policy makers and farmers. For this project, we established two experimental sites on Norwegian peatlands for grass cultivation, of which one in Northern (subarctic, continental climate) and another in Southern (temperate, coastal climate) Norway. Both sites have a water table level (WTL) gradient ranging from low to high. In order to explore the effects of management practices, controlled trials with different fertilization strategies and tillage intensity will be conducted at these sites with WTL gradients considered. Meanwhile, GHG emissions (including carbon dioxide, methane and nitrous oxide), crop-related observations (e.g. phenology, production), and hydrological conditions (e.g. soil moisture, WTL dynamics) will be monitored with high spatiotemporal resolution along the WTL gradients during 2019-2021. Besides, MYR aims at predicting potential GHG mitigation under different scenarios by using state-of-the-art modelling techniques. Four models (BASGRA, Coup, DNDC and ECOSSE), with strengths in predicting grass growth, hydrological processes, soil nitrification-denitrification and carbon decomposition, respectively, will be further developed according to the soil properties. Then these models will be used independently to simulate biogeochemical and agroecological processes in our experimental fields. Robust parameterization schemes will be based on the observational data for both soil and crop combinations. Eventually, a multi-model ensemble prediction will be carried out to provide scenario analyses by 2030 and 2050. We will couple these process-based models with optimization algorithm to explore the potential reduction in GHG emissions with consideration of production sustenance, and upscale our assessment to regional level.