Both the boreal and Arctic regions are facing substantial structural changes induced by accelerated warming. This also facilitates a rapid northward shift of the agricultural zone to historically forest dominant land cover. Expansion and intensification of agriculture into the boreal and Arctic regions, while supporting diversification of local economies through the creation of new income opportunities, create multiple challenges as they (i) threaten the fragile ecosystems, (ii) alter the carbon sink capacity of northern ecosystems, (iii) affect indigenous and non-indigenous food cultures, and (iv) require significant infrastructural changes that might also affect the local demographics and induce cultural changes. Thus, strategies aiming to support agricultural expansion and intensification in the boreal and Arctic regions must include multiple nations and cultures of the North leading to the development and implementation of tailored and context-specific standards and policies. The central challenge for supporting agricultural expansion and intensification in the boreal and Arctic regions is to achieve a sustainable balance between opportunities and risks at multiple spatial and temporal scales. Many governments already take steps to promote expansion and intensification of northern agriculture. However, accelerated warming already exceeds the adaptation capacity of numerous agricultural systems in boreal and Arctic regions (Unc et al.). This Research Topic on “Sustainable and Climate-Smart Agriculture in the Boreal and Arctic Regions” aimed to gather knowledge outlining the actual and potential impacts of agricultural expansion and intensification on (i) diversity of natural ecosystems and agro-ecosystems, (ii) carbon and nutrient cycles, (iii) agricultural systems, and (iv) social structures, indigenous cultures, and local economies in the boreal and Arctic regions.
Long-term farming might lead to an accumulation of large amounts of total P which might not be immediately available to crops but, on the other hand, might be a potential pollutant source by erosion into surface water bodies resulting eutrophication. Batch adsorption was used to assess the P sorption capacity of Cochrane series soil, St. John’s, and Wooddale soil in central Newfoundland.
Boreal agriculture struggles with soils of lower agronomic value, most of which are sandy with a low water holding capacity (WHC) and prone to nutrient leaching. Biochar amendments are associated with positive effects on soil hydraulic properties and enhanced nutrient retention. However, these effects are strongly related to feedstock type and pyrolysis parameters and depend on biochar application rates and soil types. While biochar could increase the productivity of boreal agriculture by improving water and nutrient use efficiency, little is known about its effects on hydraulic processes in podzol. In this study, we investigated the effects of biochar rates (10, 20, 40, 80 Mg carbon ha−1) and maturity on soil hydrology for an agriculturally used Podzol in Labrador, Canada. The in-situ soil water content (SWC) and weather data over an entire growing season were analysed. Hydrus 1D simulations were used to estimate changes in water fluxes. SWC showed clear differentiation among storage parameters (i.e., initial, peak and final SWC) and kinetic parameters (i.e., rate of SWC change). Storage parameters and soil wetting and drying rates were significantly affected by biochar rates and its maturity. The magnitude of the changes in SWC after either wetting or drying events was statistically not affected by the biochar rate. This confirms that biochar mostly affected the WHC. Nevertheless, reductions in cumulative lower boundary fluxes were directly related to biochar incorporation rates. Overall, biochar had positive effects on hydrological properties. The biochar rate of 40 Mg C ha−1 was the most beneficial to agriculturally relevant hydraulic conditions for the tested Podzol.
GCM data presentation using ClimGen sourced data, ArcGIS and Python methodological approach in analysis towards a base dataset that can be utilized in various research capacities.
Conversion of boreal forest into agricultural land is likely to occur due to the shift of climatic zones and increasing food demand. However, any land conversion will affect the water balance and hence solute fluxes within the soil column and connected ecosystems. Understanding the consequences of land conversion on soil hydrology is essential to support an economically viable agriculture while minimizing its environmental footprint. Hydrological models can simulate these effects based on regionally adjusted climate scenarios. Here, we combined a local climate analysis with hydrological simulations (Hydrus-1D) of boreal soils before and after agricultural conversion. Historical climate analysis showed increasing temperatures and growing degree days while precipitation remains stable. Hydrological simulations revealed lower saturation and higher infiltration rates for unconverted soils, indicating lower runoff and increased infiltration and deep percolation. In contrast, agricultural soils have slower infiltration rates, particularly in the upper horizon. Over the long term, agricultural conversion consequently increases erosion risk and nutrient loss by runoff. This might further progressively limit groundwater recharge, affect hydrological processes and functions and future drought/flood conditions at catchment levels. Hence, conversion of boreal soils demands a primary identification of suitable areas to minimize its impacts.
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.
Electromagnetic induction (EMI) is an established method for mapping field-scale soil water content (SWC). However, the correlation between the recorded apparent electrical conductivity (ECa) and SWC is affected by several factors that can vary across test sites and with environmental conditions. As agricultural practices affect both, ECa and SWC, it is likely that the mismatch in SWC predictions using ECa can be directly or indirectly attributed to agronomic treatment effects. Hence, EMI based SWC predictions are often limited to sites with one soil amendment and strong ECa-SWC correlations. However, non-invasive SWC mapping is particularly desirable for larger agricultural fields, covering different soil amendments. We hypothesized that different agro-nomic treatments altered the ECa-SWC correlations and consequently the EMI based SWC prediction accuracy. We further hypothesized that a model established on areas with high positive ECa-SWC correlation could be used to predict SWC for areas with unsuitable ECa-SWC correlations. A field-scale experiment was conducted to investigate the effects of six agronomic treatments (including biochar, BC) on SWC, ECa, and ECa-SWC correlation in a silage corn field. We tested the accuracy of three models to predict the SWC of independent data sets using data from i) all treatments (T all), ii) plots with lowest and iii) plots with highest ECa-SWC correlations. We found statistically significant treatment effects on both, ECa and SWC, although overlapping data ranges were given. Furthermore, the correlations between ECa and SWC were affected by the treatments. Correlations were found to be lowest on nutrient-rich dairy manure plots (T2) and highest on the control plots (T6), likely due to differences in the ionic strength of pore water. BC mitigated the effect of ionic strength for T2 while it showed no measurable effects on ECa on plots receiving inorganic fertilizers. Most accurate SWC predictions were reached by employing T all data (RMSEP 1.40-3.13% vol.). However, models based on T6 data provided similar accuracies (RMSEP 1.46-3.96% vol.) using only 12.5% of the area. The T2 based model performance failed (RMSEP 3.02-7.21% vol.). Results suggest that ECa-SWC models established on non-manured areas could provide best possible SWC predictions and are recommended as training areas if soil texture and mineralogical composition can be expected to be relatively homogeneous.