Simulating soil carbon sequestration from long term fertilizer and manure additions under continuous wheat using the DailyDayCent model

Bangabandhu Fellowship on Science and ICT project, Ministry of Science and Technology, People’s Republic of Bangladesh. Open Access via Springer Compact AgreementPeer reviewedPublisher PD

Crossing the chasm: a 'tube-map' for agent-based social simulation of policy scenarios in spatially-distributed systems

Agent based models (ABMs) simulate actions and interactions of autonomous agents/groups and their effect on systems as a whole, accounting for learning without assuming perfect rationality or complete knowledge. ABMs are an increasingly popular approach to studying complex, spatially distributed socio-environmental systems, but have still to become an established approach in the sense of being one that is expected by those wanting to explore scenarios in such systems. Partly, this is an issue of awareness – ABM is still new enough that many people have not heard of it; partly, it is an issue of confidence – ABM has more to do to prove itself if it is to become a preferred method. This paper will identify advances in the craft and deployment of ABM needed if ABM is to become an accepted part of mainstream science for policy or stakeholders. The conduct of ABM has, over the last decade, seen a transition from using abstracted representations of systems (supporting theory-led thought experiments) to more accessible representations derived empirically (to deliver more applied analysis). This has enhanced the perception of potential users of ABM outputs that the latter are salient and credible. Empirical ABM is not, however, a panacea, as it demands more computing and data resources, limiting applications to domains where data exist along with suitable environmental models where these are required. Further, empirical ABM is still facing serious questions of validation and the ontology used to describe the system in the first place. Using Geoffrey A. Moore’s Crossing the Chasm as a lens, we argue that the way ahead for ABM lies in identifying the niches in which it can best demonstrate its advantages, working with collaborators to demonstrate that it can deliver on its promises. This leads us to identify several areas where work is needed

Modelling greenhouse gas emissions and mitigation potentials in fertilized paddy rice fields in Bangladesh

The work was supported by Bangabandhu Fellowship on Science and ICT project, Ministry of Science and Technology, People’s Republic of Bangladesh. We are grateful to the model developers at the Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado, United States of America, for sending us the new methane version of the DayCent model.Peer reviewedPostprin

Understanding carbon sequestration in upland habitats

This project set out to review the current state of knowledge on the potential for carbon sequestration in key Scottish upland open habitats. Upland soils play a vital role in regulating greenhouse gas (GHG) emissions in our environment. Scotland’s soils contain 2500-3500 Mt of carbon, much of which is located in upland soil environments. This quantity of carbon is the equivalent of more than 200 years of annual emissions of greenhouse gases from the whole Scottish economy. To achieve Scotland’s ambitious net-zero emissions targets, sound management of uplands and their soils will thus be critical. Despite the potential of soils to store carbon, however, there is uncertainty as to the long-term stability of this carbon pool. Increasing temperatures, altered patterns of rainfall distribution and changes in land use threaten to reduce soil carbon stocks. This review identifies the key drivers of change such as: climate change; nitrogen deposition; changes in atmospheric carbon dioxide concentrations; and local land management factors such as grazing by sheep and deer, and burning to maintain habitat and vegetation quality for grazing animals and grouse. It covers three upland habitats: upland dry heath, upland wet heath and upland grasslands, defined by vegetation communities. It assesses potential greenhouse gas (GHG) fluxes and the impact on biodiversity within these habitats

Measuring the vulnerability of Scottish soils to a changing climate

The second Scottish Climate Change Adaptation Programme (SCCAP) identifies soil health as a priority research area to support sustainable soil management and ecosystem services. This follows concerns over a perceived lack of data or gaps in understanding that have been raised in both independent assessments of the first SCCAP by the Committee on Climate Change. The aim of this study is to summarise previous work on Scottish soils, explore existing datasets, and identify those metrics which could support the monitoring of Scotland’s soil health and measure the vulnerability of Scottish soils to climate change in future

Capturing cropland and grassland management impacts on soil carbon in the UK LULUCF inventory

This project aimed to identify the extent to which emissions due to changes in Soil Organic Carbon (SOC) stocks arising from Cropland and Grassland/Grazing Land management can be incorporated into the UK’s Land Use, Land Use Change and Forestry (LULUCF) inventory. Key management activities were identified which might affect SOC stocks. A literature review carried out as part of the project concluded that tillage reduction cannot be considered a reliable management option to increase the SOC content of UK soils. However increasing crop residue returns and increasing inputs of manure and fertiliser could increase SOC stock although the SOC stock increases resulting from manure and fertiliser inputs could be outweighed by increases nitrous oxide emissions and the risk of nitrate run-off. The review found that increasing crop yields through increased fertilisation and improved crop rotation could increase the annual input of crop residues and root exudate to soils and hence increase SOC on low fertility soils. Manure additions resulted in greater C sequestration than the addition of equivalent amounts of N as mineral fertiliser and the effect lasted longer. However, increasing inputs of nitrogen from fertiliser or manure risk increasing N2O emissions which could negate any increases in SOC stock. IPCC default stock change factors were judged to be inappropriate to the UK, based on expert opinion and the literature review findings. Therefore the project used the Daily DayCent and Landscape DNDC models to attempt to estimate stock change factors for Cropland management activities under UK conditions. Although based on a very limited dataset this suggested that the effect of Cropland management activities under UK conditions might be less than implied by the IPCC stock change factors. Tillage reduction was found to have little effect on SOC stocks. Increasing manure and crop residue inputs increased SOC stocks, with manure inputs being particularly effective. A framework for reporting SOC stock changes resulting from Cropland management was developed, and used to assess mitigation options. Overall the impact of Cropland Management on SOC is likely to be very small compared to other activities in the LULUCF inventory such as land use change. The most effective mitigation option was using Cropland from annual tillage crops to perennial crops, fallow and set aside. However given the need for food production there is limited scope for such change. Increasing manure, fertiliser and crop residue inputs gave smaller increases in SOC stocks, but practical considerations limit the scope of these actions. Lack of field data on the effect of Grassland improvement on SOC stocks was identified as a knowledge gap. The literature review suggested that intensification could increase SOC stocks under pasture on mineral soils. However, expert opinion suggested that this might not be the case for rough grazing on organo-mineral soils, where intensification might lead to SOC loss. This lack of data meant that it was not possible to calibrate or validate models to estimate UK specific stock change factors for Grassland. As the IPCC stock change factors were judged to be inappropriate to UK conditions assessment of the mitigation potential of Grassland management using these factors was not carried out to avoid presenting potentially misleading results. Suggested strategies for filling these knowledge gaps are outlined in the report. Attempts to assess grass/crop rotation patterns across the UK using data from the Integrated Administration and Control System (IACS) used to handle Common Agricultural Policy (CAP) payments were hampered by difficulties in obtaining access to the data. However land use change matrices were generated for England and Wales, and used to map areas of change. Subject to data availability, this approach could be used in future inventories to give a better representation the effect of rotation patterns on SOC stocks

Modeling Denitrification : Can We Report What We Don't Know?

Funding Information: This study is the products of a workshop funded by the Deutsche Forschungsgemeinschaft through the research unit DFG‐FOR 2337: Denitrification in Agricultural Soils: Integrated Control and Modelling at Various Scales (DASIM), and by the German Federal Ministry of Education and Research (BMBF) under the “Make our Planet Great Again—German Research Initiative”, Grant 306060, implemented by the German Academic Exchange Service (DAAD). This work was supported by the European Union's Horizon 2020 research and innovation programme project VERIFY (grant agreement no. 776810). We would like to thank the contribution of all workshop participants of the II. DASIM Modeler Workshop. Publisher Copyright: © 2023. The Authors.Peer reviewedPublisher PD

Global Research Alliance N2O chamber methodology guidelines : Summary of modeling approaches

Acknowledgements Funding for this publication was provided by the New Zealand Government to support the objectives of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases. Individual authors work contribute to the following projects for which support has been received: Climate smart use of Norwegian organic soils (MYR, 2017-2022) project funded by the Research Council of Norway (decision no. 281109); Scottish Government's Strategic Research Programme, SuperG (under EU Horizon 2020 programme); DEVIL (NE/M021327/1), Soils-R-GRREAT (NE/P019455/1) and the EU H2020 project under Grant Agreement 774378—Coordination of International Research Cooperation on Soil Carbon Sequestration in Agriculture (CIRCASA); to project J-001793, Science and Technology Branch, Agriculture and Agri-Food Canada; and New Zealand Ministry of Business, Innovation and Employment (MBIE) core funding. Thanks to Alasdair Noble and the anonymous reviewers for helpful comments on a draft of this paper and to Anne Austin for editing services.Peer reviewedPublisher PD

MAGGnet: an international network to foster mitigation of agricultural greenhouse gases.

Research networks provide a framework for review, synthesis and systematic testing of theories by multiple scientists across international borders critical for addressing global-scale issues. In 2012, a GHG research network referred to as MAGGnet (Managing Agricultural Greenhouse Gases Network) was established within the Croplands Research Group of the Global Research Alliance on Agricultural Greenhouse Gases (GRA). With involvement from 46 alliance member countries, MAGGnet seeks to provide a platform for the inventory and analysis of agricultural GHG mitigation research throughout the world. To date, metadata from 315 experimental studies in 20 countries have been compiled using a standardized spreadsheet. Most studies were completed (74%) and conducted within a 1-3-year duration (68%). Soil carbon and nitrous oxide emissions were measured in over 80% of the studies. Among plant variables, grain yield was assessed across studies most frequently (56%), followed by stover (35%) and root (9%) biomass. MAGGnet has contributed to modeling efforts and has spurred other research groups in the GRA to collect experimental site metadata using an adapted spreadsheet. With continued growth and investment, MAGGnet will leverage limited-resource investments by any one country to produce an inclusive, globally shared meta-database focused on the science of GHG mitigation