Title: A Review of Greenhouse Gas Emissions from Agricultural Soil

Journal: Sustainability 

DOI: https://doi.org/10.3390/su16114789

Abstract: Greenhouse gases (GHGs) like nitrous oxide (N₂O), carbon dioxide (CO₂), and methane (CH₄) are both emitted and removed by soils. Accurate worldwide allocations of carbon budget are essential for land use planning, global climate change, and climate-related research. Precise measurements, drivers, and mitigation strategies are necessary, given agricultural soil’s significant potential storage and emission capacities. Different agricultural management practices cause greenhouse gas (GHG) emissions into the atmosphere and contribute to anthropogenic emissions. Agricultural soils can generate 70% of the world’s manmade N₂O emissions and also behave as a CO₂ sink and a source of organic carbon and as producers and consumers of CH₄. When it comes to agronomic management, the source and sink of all these GHGs are distinct. Therefore, several approaches to measuring GHG emissions from agricultural soils are available and can be categorized into chamber systems and remote sensing approaches. Sustainable agriculture stands out as a viable and transformative approach to increase agricultural efficiency while addressing the challenge of GHG emissions. Incorporating advanced technologies, precise data analytics, and site-specific management practices can offer a pathway to mitigate GHG emissions, thereby reducing the global warming potential (GWP). Therefore, this review paper focuses solely on the drivers influencing and involving soil emissions and on quantification approaches for GHG emissions. In addition, mitigation practices aimed at optimizing GHG emissions from agricultural soils are highlighted.

Title: Future projections of temperature-related indices in Prince Edward Island using ensemble average of three CMIP6 models

Journal: Scientific Reports

DOI: https://doi.org/10.1038/s41598-024-63450-9

Abstract: Prince Edward Island (PEI) is an agricultural province heavily relying on rainfed agriculture. The island has already experienced significant impacts from climate change. Accurate projections of PEI temperature extreme indices are required to mitigate and adapt to the changing climate conditions. This study aims to develop ensemble projections using Coupled Model Intercomparison Project Phase 6 (CMIP6) global circulation models (GCMs) to analyze temperature extremes on PEI. In this study, the ECMWF ERA5 reanalysis dataset was chosen for stepwise cluster analysis (SCA) due to its high accuracy. Three CMIP6 (NorESM2-MM, MPI-ESM1.2-HR, and CanESM5) GCMs, along with their ensemble average, were utilized in the SCA model to project future changes in daily maximum temperature (Tmax) and minimum temperature (Tmin) at four meteorological stations on PEI (East Point, Charlottetown, Summerside, and North Cape) under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5). These GCMs were selected based on their low, medium, and high Equilibrium Climate Sensitivity. The bias-corrected results for the future period of Tmax and Tmin showed that the GCM-specific changes in the ECS also impact the regional scale. Additionally, several temperature extreme indices, including the daily temperature range (DTR), summer days (SU), growing degree days (GDD), growing season length (GSL), ice days (ID), and frost days (FD), were analyzed for two future periods: FP1(202–2050) and FP2 (2051–2075). The results indicate that DTR, SU, GDD, and GSL are expected to increase, while ID and FD are projected to decrease during FP1 and FP2 under both scenarios. The future projected mean monthly changes in Tmax, Tmin, and the selected temperature extreme indices highlight warmer future periods and an increase in agriculture-related indices such as GDD and GSL. Specifically, July, August, and September are expected to experience even higher temperatures in the future. As the climate becomes warmer, cold extreme events are projected to be shorter in duration but more intense in terms of their impact. The largest increments/decrements for Tmax, Tmin, and their relevant indices were observed during FP2 under SSP5-8.5. The outcomes of this study provide valuable insights for agricultural development, water resource management, and the formulation of effective mitigation strategies to address the impacts of climate change on PEI. 

The following review paper about the greenhouse gas emissions from agricultural soil has been recently accepted for publication by Sustainability.

Basheer, S., X. Wang, A. Farooque, R. A. Nawaz, T. Pang, and E. O. Neokye. A Review of Greenhouse Gas Emissions from Agricultural Soil. Sustainability, accepted on June 2, 2024.

More details will come soon once the paper is published.

The following paper about the spatiotemporal and weather effects on the reproductive success of piping plovers has been recently accepted for publication by Ecology and Evolution.

Guild, R., X. Wang, S. Hirtle, and S. Mader. Spatiotemporal and Weather Effects on the Reproductive Success of Piping Plovers on Prince Edward Island, Canada. Ecology and Evolution, accepted on May 31, 2024.

More details will come soon once the paper is published.

Title: Landcover-based detection of rapid impacts of extreme storm on coastal landscape

Journal: Science of The Total Environment

DOI: https://doi.org/10.1016/j.scitotenv.2024.173099

Abstract: On September 24, 2022, Post-Tropical Hurricane Fiona made landfall in Atlantic Canada and caused unprecedented damages to the coastal communities and ecosystems therein. The aftermath triggered local government and communities in Prince Edward Island (PEI), Canada to rethink current policies and practices for coastal protection in the context of climate change. This historic hazard represents the escalating frequency and intensity of extreme weather events that globally threaten coastal regions, accelerating coastal erosion and endangering communities. This study employs landcover-based detection to assess rapid storm impact of Fiona on coastline of PEI using Sentinel-2 satellite images, to gauge the efficacy of landcover-based detection and quantify storm-induced coastal environmental changes. Our results indicate that, following Fiona, over 51 km² coastal land loss due to the erosion at beach foreshore and inundation at tidal flat, and over 11 km² sand dune loss mainly on the PEI north shore. This constitutes a 3.5 % loss of coastal land resources within the 1798 km² PEI coastal zone. Fiona also caused over 194 km² area in coastal buffer zone showed temporal fluid-mud from the eroded sediments of sand dunes, cliffs, and tidal flats, suggesting the significant sediment loss from vertical structures in addition to the direct retreat. The landcover-based method can be regarded as a valuable tool for the storm impacts on coastal environments. Based on the coastal change pattern, more sustainable coastal protection and adaptation measures should be developed, focusing on reducing hydrodynamic intensity and improving erosion capacity, with consideration of the increasing likelihood of more intense and frequent storm events in a warming climate.