The Effects of Long‐Term Land‐Use Change on Soil Properties in Perth, Ontario Canada
Bibliographic record
Abstract
Land‐use change can have a major impact on soil properties, leading to long‐term changes in soilnutrient cycling rates and carbon storage. While a substantial amount of research has been conducted onland‐use change in tropical regions, empirical evidence of long‐term conversion of forested land toagricultural land in North America is lacking. Pervasive deforestation for the sake of agriculturethroughout much of North America is likely to have modified soil properties, with implications for theglobal climate. Here, we examined the response of physical, chemical and biological soil properties toconversion of forest to agricultural land (100 years ago) on Roebuck Farm near Perth, Ontario, Canada.Soil samples were collected at three sites from under forest and agricultural vegetative cover on bothhigh‐ and low‐lying topographic positions (12 locations in total; soil profile sampled to a depth of 40cm).Our results revealed that bulk density, pH, and nitrate concentrations were all higher in soils collectedfrom cultivate sites. In contrast, samples from forested sites exhibited greater water‐holding capacity,porosity, organic matter content, ammonia concentrations and cation exchange capacity. Many of these characteristics are linked to greater organic matter abundance and diversity in soils under forestvegetation as compared with agricultural soils. Microbial activity and Q10 values were also higher in theforest soils. While soil properties in the forest were fairly similar across topographic gradients, low‐lyingpositions under agricultural regions had higher bulk density and organic matter content than upslopepositions, suggesting significant movement of material along topographic gradients. Differences in soilproperties are attributed largely to increased compaction and loss of organic matter inputs in theagricultural system. Our results suggest that the conversion of forested land cover to agriculture landcover reduces soil quality and carbon storage, alters long‐term site productivity, and contributes toincreased atmospheric carbon dioxide concentrations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".