Agri-Environmental Systems for the Future: Meeting the 2050 Emissions Targets

A special issue of Agronomy (ISSN 2073-4395).

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 8132

Special Issue Editors

School of Applied Sciences and Technology, Prudence College Dublin GSustain and University College Dublin, Belfield, Dublin 4, Ireland
Interests: soil biogeochemistry; carbon sequestration; nutrient management; greenhouse gases; modelling; carbon footprint; environmental sustainability; climate change
Special Issues, Collections and Topics in MDPI journals
UCD School of Biology and Environmental Science and UCD Earth Institute, University College Dublin, Belfield, Dublin 4, Ireland
Interests: ecosystem greenhouse gas emissions and their mitigation; carbon sequestration; climate change; invasive plants; underutilized crop species; crop productivity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In line with COP26, the EU Green Deal and UN-SDG targets, agricultural systems have a key role to play in averting catastrophic climate change through reductions in greenhouse gas (GHG) emissions and water, air and soil pollution without compromising their traditional role in the production of food and raw materials. To perform this dual role, the development and adoption of technologies with a low carbon/GHG footprint throughout the lifecycle/supply chain will be required. The range, uncertainty and complexity associated with GHG accounting across different land uses and their scaling from parcel to global levels remain key constraints to the development of effective mitigation and adaptation options. This Special Issue, based on contributions to ISCRAES 2022 (www.iscraes.org), seeks high-quality articles (original research, review articles, case studies, methodologies and modeling) to improve the knowledge base, identify research gaps and elucidate systems-based management practices/technologies that could be used to mitigate/offset/tradeoff GHGs and reduce environmental pollution whilst also recarbonizing agricultural soils and associated land uses. Importantly, we will also address how the 2050 emissions targets might be achieved without compromising the productivity, sustainability or economic viability of agroecosystems.

Dr. Mohammad Ibrahim Khalil
Prof. Dr. Bruce Osborne
Guest Editors

Manuscript Submission Information

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Keywords

  • climate change
  • greenhouse gases
  • soil and water pollution
  • mitigation
  • tradeoffs/offsets
  • management practices
  • agricultural systems

Published Papers (3 papers)

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Research

18 pages, 6267 KiB  
Article
Historical Changes in Agricultural Systems and the Current Greenhouse Gas Emissions in Southern Chile
by Francisca Meneses, Nicole Montenegro, Constanza Schapheer and Jorge F. Perez-Quezada
Agronomy 2023, 13(1), 240; https://doi.org/10.3390/agronomy13010240 - 13 Jan 2023
Cited by 2 | Viewed by 2106
Abstract
Agricultural activities are important contributors to greenhouse gas (GHG) emissions in southern Chile. Three types of agricultural systems coexist within this region: traditional, conventional and agroecological. Historical changes in agricultural practices were identified from bibliographic sources and field surveys of 10 farms of [...] Read more.
Agricultural activities are important contributors to greenhouse gas (GHG) emissions in southern Chile. Three types of agricultural systems coexist within this region: traditional, conventional and agroecological. Historical changes in agricultural practices were identified from bibliographic sources and field surveys of 10 farms of each system type. A similarity analysis between systems was carried out using the survey data, which were also input to the Cool Farm Tool software to estimate GHG emissions of carbon dioxide, methane and nitrous oxide. The main historical changes identified were: (i) replacement of organic inputs by chemical products, (ii) replacement of workforce by agricultural machinery, (iii) decrease in crop diversity and (iv) decrease in total agricultural area. A multivariate analysis showed that agroecological systems are different from the traditional and conventional systems mainly because of the land use and the amount of organic fertiliser applied. However, no significant differences were found in the GHG emissions, which on average were 2999 ± 1521, 3443 ± 2376 and 3746 ± 1837 kg CO2-eq ha−1 year−1 (traditional, conventional and agroecological, respectively). Enteric fermentation was the main source of emissions in all agricultural systems, therefore methane was the most important GHG. Identifying the sources and practices that produce more emissions should help to improve management to reduce GHG emissions. Full article
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21 pages, 3438 KiB  
Article
Validating the Contribution of Nature-Based Farming Solutions (NBFS) to Agrobiodiversity Values through a Multi-Scale Landscape Approach
by Ilda Vagge and Gemma Chiaffarelli
Agronomy 2023, 13(1), 233; https://doi.org/10.3390/agronomy13010233 - 12 Jan 2023
Cited by 4 | Viewed by 1404
Abstract
Nature-Based Farming Solutions (NBFS) are envisaged practices that still strongly demand further context-specific scientific validation for their viable deployment at the local scale. In this context, our study deals with the test of a multi-scale system of landscape ecology indicators, interpreted as surrogates [...] Read more.
Nature-Based Farming Solutions (NBFS) are envisaged practices that still strongly demand further context-specific scientific validation for their viable deployment at the local scale. In this context, our study deals with the test of a multi-scale system of landscape ecology indicators, interpreted as surrogates for the accounting of the contributions of NBFS to agrobiodiversity values and to the consequent environmental stability and resilience capacities of agroecosystems, recognized as pivotal for facing the ongoing climate change challenges. We here present the preliminary results obtained in a first pilot case study (Po Plain context). Landscape ecology analyses were undertaken at extra-local, local, and farm scales (with different levels of analytical detail), comparing the pilot farm to the surrounding conventionally managed context. A set of structural and functional indicators were tested, allowing a preliminary screening of the most suitable ones (good sensitivity to treatment changes, informative potential). Results suggested a multi-faceted positive contribution given by NBFS implementation and were the basis for orienting further NBFS implementation strategies based on vulnerability and resilience properties analysis. Further investigations are envisaged on wider datasets coming from other pilot case studies belonging to similar pedo-climatic conditions, in order to improve the informative potential of the here presented methodology. Full article
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19 pages, 3489 KiB  
Article
Application and Evaluation of a Simple Crop Modelling Framework: A Case Study for Spring Barley, Winter Wheat and Winter Oilseed Rape over Ireland
by Deepak Upreti, Tim McCarthy, Macdara O’Neill, Kazeem Ishola and Rowan Fealy
Agronomy 2022, 12(11), 2900; https://doi.org/10.3390/agronomy12112900 - 20 Nov 2022
Viewed by 2930
Abstract
Globally, croplands represent a significant contributor to climate change, through both greenhouse gas emissions and land use changes associated with cropland expansion. They also represent locations with significant potential to contribute to mitigating climate change through alternative land use management practices that lead [...] Read more.
Globally, croplands represent a significant contributor to climate change, through both greenhouse gas emissions and land use changes associated with cropland expansion. They also represent locations with significant potential to contribute to mitigating climate change through alternative land use management practices that lead to increased soil carbon sequestration. In spite of their global importance, there is a relative paucity of tools available to support field- or farm-level crop land decision making that could inform more effective climate mitigation practices. In recognition of this shortcoming, the Simple Algorithm for Yield Estimate (SAFY) model was developed to estimate crop growth, biomass, and yield at a range of scales from field to region. While the original SAFY model was developed and evaluated for winter wheat in Morocco, a key advantage to utilizing SAFY is that it presents a modular architecture which can be readily adapted. This has led to numerous modifications and alterations of specific modules which enable the model to be refined for new crops and locations. Here, we adapted the SAFY model for use with spring barley, winter wheat and winter oilseed rape at selected sites in Ireland. These crops were chosen as they represent the dominant crop types grown in Ireland. We modified the soil–water balance and carbon modules in SAFY to simulate components of water and carbon budgets in addition to crop growth and production. Results from the modified model were evaluated against available in situ data collected from previous studies. Spring barley biomass was estimated with high accuracy (R2 = 0.97, RMSE = 95.8 g·m−2, RRMSE = 11.7%) in comparison to GAI (R2 = 0.73, RMSE = 0.44 m2·m−2, RRMSE = 10.6%), across the three years for which the in situ data was available (2011–2013). The winter wheat module was evaluated against measured biomass and yield data obtained for the period 2013–2015 and from three sites located across Ireland. While the model was found to be capable of simulating winter wheat biomass (R2 = 0.71, RMSE = 1.81 t·ha−1, RRMSE = 8.0%), the model was found to be less capable of reproducing the associated yields (R2 = 0.09, RMSE = 2.3 t·ha−1, RRMSE = 18.6%). In spite of the low R2 obtained for yield, the simulated crop growth stage 61 (GS61) closely matched those observed in field data. Finally, winter oilseed rape (WOSR) was evaluated against a single growing season for which in situ data was available. WOSR biomass was also simulated with high accuracy (R2 = 0.99 and RMSE = 0.52 t·ha−1) in comparison to GAI (R2 = 0.3 and RMSE = 0.98 m2·m−2). In terms of the carbon fluxes, the model was found to be capable of estimating heterotrophic respiration (R2 = 0.52 and RMSE = 0.28 g·C·m−2·day−1), but less so the ecosystem respiration (R2 = 0.18 and RMSE = 1.01 g·C·m−2·day−1). Overall, the results indicate that the modified model can simulate GAI and biomass, for the chosen crops for which data were available, and yield, for winter wheat. However, the simulations of the carbon budgets and water budgets need to be further evaluated—a key limitation here was the lack of available in situ data. Another challenge is how to address the issue of parameter specification; in spite of the fact that the model has only six variable crop-related parameters, these need to be calibrated prior to application (e.g., date of emergence, effective light use efficiency etc.). While existing published values can be readily employed in the model, the availability of regionally derived values would likely lead to model improvements. This limitation could be overcome through the integration of available remote sensing data using a data assimilation procedure within the model to update the initial parameter values and adjust model estimates during the simulation. Full article
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