In the Canadian System of Soil Classification (CSSC), soils of the Organic order are classified at the great group level primarily based on the dominant organic material in the middle tier. The system recognizes four types of organic horizons: fibric (Of), mesic (Om), humic (Oh), and coprogenous earth (Oco), of which only the latter is not recognized at the great group level of the Organic order. Furthermore, at the subgroup level, Limnic subgroups cannot have terric or hydric layers. This is problematic in soils where the middle tier is dominated by limnic materials, and those which have dominantly limnic materials and have a terric layer. We describe 29 soil profiles in Ontario and Quebec, which are either poorly captured in the CSSC or that cannot be classified into the Organic order based on their diagnostic criteria. Based on an analysis of soil survey information in five provinces across Canada, we estimate 32057 ha of organic soils which potentially contain limnic deposits. In key vegetable-producing areas of Quebec, large organic deposits in agricultural production are subject to peat subsidence and erosion, resulting in shallower depths to underlying coprogenous earth, which is not a suitable medium for crop production. This can potentially have negative effects on crops when mixed with humic materials in the plow layer. Due to these taxonomic and agronomic considerations, we propose the addition of a new great group, Limnisol, and suggest further integration of limnic materials at the subgroup level for the Humisol, Mesisol, and Fibrisol great groups.

Wetland soil types, which can be distinguished based on calcium carbonate content, vary in their effect on ecosystem functions like phosphorus retention, salinity contributions, and greenhouse gas forcing. These soil types may be predictively mapped with machine learning models that use terrain derivatives calculated from high-resolution digital elevation models. Soil profiles from three Saskatchewan study sites were classified into three functional categories—upland, calcareous wetland, or noncalcareous wetland—and used to train random forest models for predictive soil mapping. Multiple terrain derivatives were included as predictor variables to capture local- and landscape-scale morphometry and hydrology influences, including five derivatives developed for this study. Models were developed at three spatial resolutions: 2, 5, and 10 m, and tested via internal cross-validation and independent validation with datasets from previous studies. Predictive accuracies were highest when mapping at 2 m resolution (independent validation accuracy range = 64%–100%) but also successful when mapping at 5 and 10 m resolutions (independent validation accuracy range = 63%–100%); however, visual inspection determined that the maps generated at 10 m resolution were less detailed and occasionally featured questionable discontinuous soil distributions. Three of the five terrain derivatives developed for this study were among the most important predictor variables (first, second, and 10th most important). Models trained using only data from a specific site had slightly better performance than models trained using data from all sites, except in regions where training data were lacking.

The major drivers of soil variation in Saskatchewan at scales finer than the existing soil maps are parent material variance, slope position, and salinity. There is therefore a need to generate finer-scale parent material maps as part of updating soil maps in Saskatchewan. As spatially referenced soil point data are lacking in Saskatchewan, predictive soil mapping methods that disaggregate existing soil parent material maps are required. This study focused on investigating important environmental covariates to use in parent material disaggregation, particularly bare soil composite imagery (BSCI). Synthetic point observations were generated using an area-proportional approach based on existing soil survey polygons and a random forest model was trained with those synthetic observations to predict parent material classes. Including BSCI as environmental covariates increased model accuracy from 0.38 to 0.52 and the model Kappa score from 0.19 to 0.35 compared with models where it was not included. Models that included training points from all locations, regardless of whether BSCI was available, and included BSCI as environmental covariates had similar results to the BSCI model with an accuracy of 0.48 and a Kappa value of 0.30. Based on these results, BSCI is an important covariate for parent material disaggregation in the Saskatchewan Prairies. Future work to disaggregate soil classes based on slope position and salinity, and to combine those methods with parent material disaggregation is needed to generate detailed soil maps for the Canadian Prairies.

Monitoring the changes in soil organic carbon (SOC) pools is critical for sustainable soil and agricultural management. This case study models total and active organic carbon dynamics (2015/2016 to 2019/2020) using digital soil mapping (DSM) techniques. Model predictors include topographic variables generated from light detection and ranging data; soil and vegetation indices derived from Landsat satellite images; and soil and crop inventory information from Agriculture and Agri-Food Canada to predict total organic carbon (TOC) and permanganate oxidizable carbon (POXc) at the 0–15 cm depth increment for a 37 km² study area in Truro, Nova Scotia. Quantile Regression Forest and stochastic Gradient Boosting Model were utilized for prediction. Although both models performed equally well for predicting TOC and POXc, the accuracy of TOC predictions (e.g., concordance correlation coefficient (CCC) = 0.67) was better than POXc predictions (e.g., CCC = 0.53). The Landsat variables and crop inventory were dominant predictors, while topographic variables across the relatively homogeneous terrain had relatively little influence. During the study period, changes in POXc were predicted across 98% of the study area, with a mean absolute loss of 5.77 (±11.48) mg/kg/year, and in TOC on 27% of the area, with a mean absolute loss of 0.15 (±0.09) g/kg/year. While the annual crop fields observed the highest loss of TOC and POXc, the decline in pasture–grassland–forage fields was relatively low. The study reinforced the effectiveness of DSM for modeling multiple SOC pools at the farm to landscape scales.

As the global human population and associated anthropogenic activities rapidly increase, so does the areal extent of disturbed soils. Regulatory frameworks must incorporate reclamation criteria and management options for these disturbed soils, requiring consistent descriptions and interpretations. Many human-altered soils cannot be classified using the current Canadian System of Soil Classification (CSSC), thus an Anthroposolic order is proposed. Anthroposols are soils that are highly modified or constructed by human activity, with one or more natural horizons removed and replaced, added to, or significantly modified. Disturbed horizons are anthropic in origin and contain materials significantly modified physically and/or chemically by human activities. Three great groups are defined by the presence of anthropogenic artefacts and organic carbon content. Eight subgroups are based on the amount of organic material, thickness of horizons, material composition, hydrologic regime, and presence of permafrost. Traditional phases and modifiers are used as in the CSSC. The proposed classification has been revised from the original publication in 2012 after field testing and discussion among soil scientists across Canada. This revised classification is proposed for inclusion in the revised CSSC, to account for the very large and expanding aerial extent of disturbed soils in Canada, and to remain current with other global soil taxonomy systems.

Large organic deposits in the southwestern plain of Montreal have been converted to agricultural land for vegetable production. In addition to the variable depth of the organic deposits, these soils commonly have an impermeable coprogenous layer between the peat and the underlying mineral substratum. Estimations of the depth and thickness of these materials are critical for soil management. Therefore, five drained and cultivated peatlands were studied to estimate their maximum peat thickness (MPT)—a potential key soil property that can help identify management zones for their conservation. MPT can be defined as the depth to the mineral layer (DML) minus the coprogenous layer thickness (CLT). The objective of this study was to estimate DML, CLT, and MPT at a regional scale using environmental covariates derived from remote sensing. Three machine-learning models (Cubist, Random Forest, and k-Nearest Neighbor) were compared to produce maps of DML and CLT, which were combined to generate MPT at a spatial resolution of 10 m. The Cubist model performed the best for predicting both features of interest, yielding Lin’s concordance correlation coefficients of 0.43 and 0.07 for DML and CLT, respectively, using a spatial cross-validation procedure. Interpretation of the drivers of CLT was limited by the poor predictive power of the final model. More precise data on MPT are needed to support soil conservation practices, and more CLT field observations are required to obtain a higher prediction accuracy. Nonetheless, digital soil mapping using open-access geospatial data shows promise for understanding and managing cultivated peatlands.

With respect to the pedosphere, human activities in the last 100 years have been the major driver of soil change. Despite human activities being one of the main soil forming factors recognized by soil scientists (in addition to climate, organisms, parent material, relief, groundwater, and time), the Canadian System of Soil Classification (CSSC) emphasizes soil as a natural body. We argue human agricultural activities are direct and indirect drivers of significant changes to the carbon balance and cycling in A horizons of Gray Luvisolic soils in western Canada, resulting in changes to A horizon carbon stocks, structure, and micromorphology. Evidence from scientific literature, in-field soil profile observations, and the National Pedon Database are presented in support of our argument. We propose a polygenetic, two-stage model of Gray Luvisol soil formation. The first stage is dominated by the climate forcing of the Holocene, resulting in a relatively stable boreal forest ecosystem including perturbations from natural and human-induced wildfire and other disturbances. The second stage is dominated by direct, human-driven disturbances such as cultivation, release of exotic fauna (earthworms), and indirect human-driven disturbances associated with anthropogenic climate change. Further, we propose modest amendments to the CSSC to reflect a polygenetic model of soil genesis in Gray Luvisolic soils that preserve the balance between observation and interpretation inherent in the system.

Cropping systems with perennial forages and reduced fallow frequency generally increase soil organic carbon and thus subsequent soil health and crop yield. We evaluated the impact of prior cropping systems on subsequent yields and soil properties in a semiarid region by using crop yields as a bioassay of soil health following the termination of a 24-year crop rotation study in the Brown soil zone in Alberta. During 24 growing seasons from 1992 to 2015, the study included three fallow-containing rotations, two annual crop rotations that were cropped continuously, and perennial grass hay, each with two to six fertilizer treatments. During the bioassay period from 2016 through 2020, all plots in the study were uniformly cropped. Compared to unfertilized fallow wheat, soil organic C in the fall of 2015 was 54% higher after 24 years of fertilized grass and up to 14% higher following annual crops in rotations without fallow. The most notable impact of the previous cropping system on yield during the bioassay years was low yield following perennial grass in 2016 and 2018. Soil electrical conductivity measurements showed that subsoil salinity was elevated following perennial grass, demonstrating the importance of subsoil characteristics for healthy soils. Crop yields in the fifth year of the crop bioassay were 10%–20% greater due to reduced fallow frequency or increased crop diversity. The long-term impact of the cropping system on crop yield in this study depended on drought intensity due to counteracting changes in soil organic matter and subsoil salinity.

Soil respiration measurements are commonly used as soil health indicators. Several ex situ soil respiration methods exist, but comparative performances between them have rarely been analyzed. Specifically, there is a lack of comparisons between intact microcosms and destructive methods. The objective of this study was to analyze and compare three different ex situ soil respiration methodologies: minimally disturbed microcosms using fresh soil, dried–sieved 24 h burst test, and dried–sieved 10-day incubation. We hypothesized that (i) the respiration rates for the three methods are correlated to each other; (ii) the respiration rates are strongly correlated with soil physico-chemical parameters; (iii) disturbance caused by drying and sieving reduces regression coefficients compared with microcosms; and (iv) drying and sieving soil produces larger respiration rates. Soil was collected in the Province of New Brunswick, Canada. Total carbon and nitrogen (C:N), pH, aggregate stability, total dissolved C and N, NO₃ and NH₄, texture, and labile C were determined prior to incubations. Our results showed that the three methods had CO₂ efflux in similar ranges. However, all the methods had low to no significant correlations between soil physico-chemical parameters and respiration. Total dissolved N had the strongest correlation with CO₂ efflux. The results of the microcosm method significantly correlated with the results for 24 h burst test but not with the 10-day incubation method. We conclude that drying and sieving soil prior to performing ex situ soil heterotrophic respiration measurements using the 24 h burst tests can produce cautiously reliable results. Despite the disturbance, results from the 24 h burst tests are comparable with the results of the microcosm method.

Since soil health is impacted by inherent soil properties, it is, therefore, challenging to apply the same soil health frameworks across multiple regions and soil types. Here, we examined the effect of soil textural group (coarse, medium, and fine) on four soil health indicators of soils sampled from diverse agricultural systems across Ontario. Scoring functions were developed by calculating cumulative normal distributions, using the mean and standard deviation of each soil health indicator, for three or five soil textural groups. For each soil health indicator, soil health scoring values were provided using the “more is better” approach, where greater soil health scores implied better soil health. Soil health indicators were significantly affected by three but not all five soil textural groups. Evolved NH₃ and CO₂, and potentially mineralizable N had stronger associations with each other as revealed by correlation and principal component analysis. Our results also suggested that mean separation of the tested soil health indicators was more consistent with three soil textural groups (coarse, medium, and fine) than five soil textural groups (clays, clay loams, loams, sandy loams, and sand); therefore, we recommend using three soil textural groups to develop soil health scoring functions. The findings of this study lay a groundwork for future soil health assessment involving a larger number of samples across Ontario and more soil indicators, which will facilitate the regional interpretation of soil health.

Canada's interest in agricultural lands has changed with time from a desire of crop yields at Confederation through to discussions in the Senate on adaptation and resilience in 2018. Long-term research experiments (LTRs) have been present and utilized by federal and university researchers to provide answers throughout. Here we highlight the importance of LTRs by identifying the historical context of LTRs and soil health research in Canada. We then briefly describe the history and key results from select LTRs and illustrate the wealth of information collected from the North American Project to Evaluate Soil Health Measurements cross-country point-in-time soil sampling from these LTRs. We discuss the LTRs, and the knowledge gained from them, with the hope that by showing the distinctive narratives associated with each of these study sites, researchers will be inspired to use them to address their research questions and make sound predictions to facilitate the adaptation of Canadian agroecosystems to climate challenges. Through identifying the value generated by these unique LTRs, we hope that the importance of these sites will inspire not only their continued maintenance but also the next generation of LTRs.

Physical fractions of soil organic matter (SOM) are established indicators of management-induced change and have been used to estimate the soil carbon storage capacity and storage potential. Here, we use SOM physical fractions and soil textures to identify management practices that maintain or enhance soil health and carbon storage in agricultural soils in Ontario. Metadata from the National Soil Database were used to estimate carbon storage potentials and calculate carbon deficits. A map was created showing carbon deficits in Ontario's agricultural soils and indicates that these soils have the potential to store an additional 0 to 2kgm⁻² in the top 20cm of the soil. Tillage system generally had no effect on the size of the carbon deficit at four long-term agricultural experiments (Delhi, Elora, Ottawa, and Ridgetown). There was only a significant tillage effect at Ridgetown and only in the maize–soybean crop rotation, where the carbon deficit was 2.95gCkgsoil⁻¹ under conventional tillage compared to 8.97gCkgsoil⁻¹ with no tillage. A statistically significant effect of crop rotation was detected in Elora and Ridgetown. In Elora, continuous alfalfa had the smallest carbon deficit (7.25gCkgsoil⁻¹) and maize–soybean rotation had the largest deficit (12.07gCkgsoil⁻¹). In Ridgetown, the maize–soybean rotation had the smallest carbon deficit (2.95gCkgsoil⁻¹). Regression analysis showed a weak negative relationship (R²=0.11; P<0.001) between carbon storage deficits and soil health scores. This suggests that increasing SOM levels alone may not improve soil health.

Effects of biochar–compost (B+Com) mixture and cover crop were assessed on soil and grapevine productivity in an irrigated Merlot (Vitis vinifera L.) vineyard in Okanagan Valley, British Columbia (BC), Canada, from 2017 to 2020. The experimental design was a factorial arrangement of control, B+Com, cover crop, and combination of cover crop and B+Com (cover crop/B+Com) treatments in alleys with four replications. The B+Com comprised a 1:1 ratio of biochar and compost and was applied at a rate of 22 Mg ha⁻¹ dry weight basis in May 2017 and 2019. The cover crop consisted of a dryland forage mixture and bird’s-foot trefoil (Lotus corniculatus L.). B+Com treatment did not affect cover crop biomass or tissue C and N concentrations except for a 12% reduction in 2019 biomass. B+Com and cover crop/B+Com increased soil C content averaged across sampling dates by 11% and 17% (P < 0.05), respectively, only at the 0–15 cm soil depth compared with the control. Cover crop treatment did not affect (P < 0.05) soil C content at two soil depths in all sampling dates. Soil N content was not affected by B+Com, decreased by an average of 12.5% at both soil depths with cover crop, and increased with cover crop/B+Com by 4% only at the 0–15 cm soil depth averaged across sampling dates (P < 0.05). Grape yield was increased by 32% by cover crop/B+Com relative to control only in 2020. The cover crop reduced petiole N and pruning weights in one or two years out of three.

Crop rotational diversity is an important part of sustainable agricultural and soil management to improve crop yield and soil fertility including enhancing soil organic matter (SOM) stabilization. Because of the physical protection via interactions with soil minerals, SOM in mineral-associated fractions is believed to be longer-lived and more stable relative to SOM in particulate (light) fractions. However, it is still unclear how crop rotational diversity alters soil carbon distribution, composition and stabilization in soil physical fractions. To address this, we studied a 37 years’ agricultural site with different crop rotational diversity (from continuous corn or alfalfa up to four species (corn, soybean, winter wheat, and red clover)). Soil carbon analysis, targeted compound analysis and nuclear magnetic resonance spectroscopy methods were used to obtain the distribution and degradation of SOM components in light and mineral-associated (F_{53–2000 µm}, F_{2–53 µm}, and F_{<2 µm}) fractions. Higher soil organic carbon (SOC) concentrations were observed in F_{<2 µm} with relatively high diversified crop rotations (three and four types of crops) compared to monoculture or two crops in the rotations, which suggests that carbon storage is enhanced in mineral-stabilized pools. Higher concentrations of long-chain aliphatic compounds as well as increased accumulation and preservation of lignin-derived compounds in fine aggregates (<53 µm) were also observed with relatively high diversified crop rotations. Overall, the increased concentration and preservation of specific SOM compounds as well as increased SOC in finer mineral-associated fractions (<53 µm) suggests that crop rotational diversity may enhance the long-term stability of SOM in agroecosystems.

Over a dozen soil phosphorus (P) extraction procedures have been designed for agri-environmental purposes (P-tests). Sustainable expansion of agriculture into boreal regions dominated by Podzols requires further insights into P extractability. We extracted P from Podzol samples (n = 96) using nine P-tests followed by both colorimetric (P_Col) and inductively coupled plasma (P_ICP) quantifications and assessed the relationships between P-tests. Samples were collected by depth or horizon from agricultural fields and reference sites in eastern, central, and western Newfoundland, Canada. The soil P was extracted with water, citric acid, ammonium bicarbonate diethylenetriaminepentaacetic acid (AB-DTPA), Morgan, Olsen, Bray-1, Bray-2, Mehlich-1, and Mehlich-3 solutions, thus targeting a wide range of extractable P pools in managed and natural Podzols. The soils had a pH of 3.4–6.9, organic matter of 0.5%–47.2%, and Al-M3 of 977–2561 mg kg⁻¹. On average, water extracted the lowest P_Col (1.0) and P_ICP (5.7) mg kg⁻¹, while citric acid extracted the highest P_Col (151) and P_ICP (290) mg kg⁻¹. For the managed podzolic soils, the extractability of P followed the sequence water < Morgan < AB-DTPA < Mehlich-1 < Bray-1 < Mehlich-3 ≤ Olsen ≤ Bray-2 < citric acid; this varied slightly by quantification techniques and soil groups. The differences between P_ICP and P_Col were most significant for the citric acid extracts. Most P-tests measurements were moderately to strongly correlated to P-M3_ICP measurements (r² > 0.50) but variable with quantification techniques and soil depths. Given the diversity in extractable P pools across management-induced soil conditions, it is evident that a fully informed P management for the Newfoundland Podzols will require calibration of P-tests against crop P uptake.

Buried wood is an important yet understudied component of natural and anthropogenic soils. Nutrient immobilization as a response to wood addition during oil sands' reclamation may be a concern since surface wood is salvaged with the soil, thereby becoming buried wood in reclamation cover soils. This project investigated the impact of buried wood on macronutrient supply and microbial communities in different reclamation soils. A 60-day incubation was performed with different rates and types of wood (0%–50%, aspen and pine) and four different soils: fine and coarse forest floor-mineral mix (fFFMM and cFFMM), peat-mineral mix (PMM), and peat. Analysis of macronutrient supply rates using Plant Root Simulator (PRS™) probes and a community-level physiological profiling (CLPP) to assess metabolic potential was performed at the end of the incubation period; microbial activity was measured through soil respiration during the incubation. Responses varied by soil type; however, buried wood caused nitrogen immobilization in three soils due to an increase in the C:N ratio. Soils with lower C:N ratios like fFFMM and PMM were more susceptible to immobilization with a decrease in available nitrogen by up to 95% at a 10% of wood addition. Phosphorus immobilization was observed in cFFMM, and potassium supply increased at 20% of wood and above. Soil microbial activity and metabolic potential increased but no significant changes in the soil profiles were observed. The findings of this study demonstrate that buried wood increases the soil C:N ratio and can potentially cause nitrogen immobilization when added by 10% of volume or more.

Wastewater-derived struvite is a promising phosphorus (P) fertilizer but more information on its behaviour in soil is needed to guide management practices for this slow-release fertilizer. After 20 days of incubation in two contrasting low-P soils in Petri dishes at two temperatures, the Olsen-P concentrations in soil surrounding struvite granules were 30–122 mg kg⁻¹, which were much lower than after amendment with monoammonium phosphate (MAP) (435–1063 mg kg⁻¹). Olsen-P concentrations further from the granule showed that MAP fertilized a larger volume of soil than struvite. Thus, the fertilizing effect of struvite may be very localized in soil.

Rhizomes of wild lowbush blueberry (Vaccinium angustifolium Aiton) extend horizontally, creating spatial dependency when fertilization trials are performed. Knowing this spatial dependency would help researchers to better design field studies. Here, we used labelled nitrogen (N) fertilizer (¹⁵N-(NH₄)₂SO₄) to measure N translocation among blueberry stems for one old (56year) and one younger (15year) commercial field. Leaf ¹⁵N concentrations at the tip-dieback stage were used to monitor N acquisition. No difference between sites suggests no field age effect on N translocation. Spatial dependency and independency were reached for distances of ≤0.75 and ≥1.75m from the fertilizer application point, respectively.