Assessing Soil Physicochemical Properties and Soil Organic Matter Stability across a Grassland-Cropland Edge at an Ecotone in Saskatchewan
Bibliographic record
Abstract
Farming production may move northward since climate change is making the south warmer and drier. The expansion of agricultural land impacts several properties and functions of native soils due to changes in land use management and vegetation covers. The current edge between native land and cropland that exists within the prairie-forest ecotone might be the first area to be impacted by changes in both land use management and climatic conditions (i.e., temperature and moisture conditions). Our goal was to find out which land use in this area would be more stable under land use change induced by climatic conditions changes. To achieve our goal, we evaluated physicochemical properties, soil organic matter (SOM) fractionation and biological stability of two main aggregate size fractions (> 2000 µm, and 150–2000 µm) of soils across a grassland-cropland edge in central Saskatchewan, Canada. Additionally, we examined changes in SOM stability of these soils under different temperature and moisture conditions. Our result showed that both land use and soil depth were primary factors controlling soil physiochemical properties. The amount of TOC, TC, TN, and OC:TN ratio gradually declined from grassland to cropland in topsoil (0–12 cm). Since SOM light fraction (LF) is decomposed faster than heavy fraction (HF), HF had significantly higher mass, C and N contents, and C:N ratio compared to LF. Among land uses, cropland had the highest HF mass within two main aggregate size fractions, while all land uses had similar amount of LF mass. Furthermore, the proportion of decomposable C within two main aggregate size fractions of grassland was higher than that of cropland, but the large aggregate size fraction of cropland mineralized more N per g TN than that of grassland. As for SOM stability under different climatic conditions, soils from all land uses mineralized more C and N at higher temperatures regardless of moisture conditions. Besides temperature, land use was another main factor influencing C mineralization, but soil moisture was the other main factor affecting N mineralization. Our results indicated that cropland was more stable than the edge and grassland in terms of C mineralization, but less stable in terms of N mineralization. In addition, the edge was more sensitive to climactic conditions than other land uses in terms of N mineralization. Understanding soil physiochemical properties, SOM stabilization and fractionation, and how these properties of soil might react to land use management change induced by climate change would aid in developing sustainable management which brings benefits to both the producers and the environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".