Comparison of Multi-Frequency and Multi-Coil Electromagnetic Induction (EMI) for Mapping Properties in Shallow Podsolic Soils.

Electromagnetic induction (EMI) technique is an established method to measure the apparent electrical conductivity (ECa) of soil as a proxy for its physicochemical properties. Multi-frequency (MF) and multi-coil (MC) are the two types of commercially available EMI sensors. Although the working principles are similar, their theoretical and effective depth of investigation and their resolution capacity can vary. Given the recent emphasis on non-invasive mapping of soil properties, the selection of the most appropriate instrument is critical to support robust relationships between ECa and the targeted properties. In this study, we compared the performance of MC and MF sensors by their ability to define relationships between ECa (i.e., MF-ECa and MC-ECa) and shallow soil properties. Field experiments were conducted under wet and dry conditions on a silage-corn field in western Newfoundland, Canada. Relationships between temporally stable properties, such as texture and bulk density, and temporally variable properties, such as soil water content (SWC), cation exchange capacity (CEC) and pore water electrical conductivity (ECw) were investigated. Results revealed significant (p < 0.05) positive correlations of ECa to silt content, SWC and CEC for both sensors under dry conditions, higher correlated for MC-ECa. Under wet conditions, correlation of MF-ECa to temporally variable properties decreased, particularly to SWC, while the correlations to sand and silt increased. We concluded that the MF sensor is more sensitive to changes in SWC which influenced its ability to map temporally variable properties. The performance of the MC sensor was less affected by variable weather conditions, providing overall stronger correlations to both, temporally stable or variable soil properties for the tested Podzol and hence the more suitable sensor toward various precision agricultural practices.

Nitrous oxide fluxes of a boreal abandoned pasture do not significantly differ from an adjacent natural bog despite distinct environmental conditions.

Land-use conversion of pristine boreal peatlands for agricultural purposes is an ongoing process and projected to become more intensive with rising population growth and increased demands for food production. However, agricultural use of peatlands affects the production and emission of nitrous oxide (N2O), a very potent greenhouse gas currently gaining more attention in the global assessment of greenhouse gases. While the intensity of N2O emissions depends on a range of environmental factors, including hydrological parameters, temperature and the availability of nitrogen in soils, key driving processes remain poorly understood. In order to understand the effects of land-use change on the peatland ecosystem, we quantified N2O fluxes under different land-use in a comparative study between a natural bog and an adjacent abandoned pasture in Newfoundland, Canada. We conducted in situ gas flux measurements using the static chamber method over five growing seasons. In addition, we measured photosynthetic rates and environmental parameters, namely soil temperature and moisture, water table and concentrations of total nitrogen and dissolved organic carbon in pore waters. According to previous studies, we hypothesized higher N2O emissions from the abandoned pasture due to drainage compared to the natural bog. However, despite significant differences of environmental parameters and photosynthetic rates, we found no significant difference of N2O fluxes between the two sites. We argue that N2O production at the abandoned pasture was inhibited due to exhaustion of plant-available nitrogen as a result of increased gross primary production compared to the natural bog. We conclude that the effect of drainage and fertilization on N2O fluxes during the growing season was superposed by vegetation composition change effects at the abandoned pasture, leading to similar N2O fluxes at both sites.

Calibration, Conversion, and Quantitative Multi-Layer Inversion of Multi-Coil Rigid-Boom Electromagnetic Induction Data.

Multi-coil electromagnetic induction (EMI) systems induce magnetic fields below and above the subsurface. The resulting magnetic field is measured at multiple coils increasingly separated from the transmitter in a rigid boom. This field relates to the subsurface apparent electrical conductivity (σa), and σa represents an average value for the depth range investigated with a specific coil separation and orientation. Multi-coil EMI data can be inverted to obtain layered bulk electrical conductivity models. However, above-ground stationary influences alter the signal and the inversion results can be unreliable. This study proposes an improved data processing chain, including EMI data calibration, conversion, and inversion. For the calibration of σa, three direct current resistivity techniques are compared: Electrical resistivity tomography with Dipole-Dipole and Schlumberger electrode arrays and vertical electrical soundings. All three methods obtained robust calibration results. The Dipole-Dipole-based calibration proved stable upon testing on different soil types. To further improve accuracy, we propose a non-linear exact EMI conversion to convert the magnetic field to σa. The complete processing workflow provides accurate and quantitative EMI data and the inversions reliable estimates of the intrinsic electrical conductivities. This improves the ability to combine EMI with, e.g., remote sensing, and the use of EMI for monitoring purposes.

Northward shift of the agricultural climate zone under 21st-century global climate change.

As agricultural regions are threatened by climate change, warming of high latitude regions and increasing food demands may lead to northward expansion of global agriculture. While socio-economic demands and edaphic conditions may govern the expansion, climate is a key limiting factor. Extant literature on future crop projections considers established agricultural regions and is mainly temperature based. We employed growing degree days (GDD), as the physiological link between temperature and crop growth, to assess the global northward shift of agricultural climate zones under 21st-century climate change. Using ClimGen scenarios for seven global climate models (GCMs), based on greenhouse gas (GHG) emissions and transient GHGs, we delineated the future extent of GDD areas, feasible for small cereals, and assessed the projected changes in rainfall and potential evapotranspiration. By 2099, roughly 76% (55% to 89%) of the boreal region might reach crop feasible GDD conditions, compared to the current 32%. The leading edge of the feasible GDD will shift northwards up to 1200 km by 2099 while the altitudinal shift remains marginal. However, most of the newly gained areas are associated with highly seasonal and monthly variations in climatic water balances, a critical component of any future land-use and management decisions.