Cultivation and Grazing Impacts on Extracellular Enzyme Activity in Alberta Grasslands
Bibliographic record
Abstract
Grasslands cover a quarter of the planet’s terrestrial surface and constitute 70% of the world’s agricultural land area. Grasslands provide clean water, facilitate effective nutrient cycling, and provide necessary habitat and forage for livestock and wildlife. In addition, grasslands have the potential to mitigate greenhouse gas emissions by sequestering carbon (C) and nitrogen (N) in soil. Grazing is one of the most common uses of grasslands and may alter C and nutrient mineralisation. Therefore, understanding the impact of different grazing systems (i.e. continuous and rotational) on C and nutrient cycling, as well as past management practices (cultivation), climate and soil properties, is of significant interest. This study examined the role of grazing systems on soil biogeochemical cycling by measuring extracellular enzyme activity (EEA), which is an indicator of soil biological activity. The activities of six soil extracellular enzymes were analysed that are involved in C (xylosidase, β-glucosidase, cellobiosidase), nitrogen (N) (N-acetyl-β glucosaminidase, urease), and phosphorus (phosphatase) cycling. Soil samples were tested from 12 pairs of field sites (i.e., ranches) with varying grazing practices (i.e., AMP or non-AMP grazing, with divergent stocking rates) for at least five years prior. An information theoretic model selection approach was used to determine those independent variables (disturbance regime, climate, soil) that explained the variability of each EEA. Results showed that a long resting period (mainly present in AMP ranches) increased β-glucosidase activity, while a high stocking rate increased urease activity. In contrast, soils with known previous cultivation had lower xylosidase and phosphatase activities, suggesting a legacy effect of previous cropping. The main environmental factors regulating enzyme activity were available soil N and climatic aridity. Overall, grazing practices, as represented by grazing systems, appear capable of altering C and nutrient cycling, with AMP grazing increasing C mineralisation iniiithese Alberta grasslands. This finding highlights the importance of grazing practices that maintain soil biological activity.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".