Woody encroachment effects on the calcareous prairie soils of Louisiana
Bibliographic record
Abstract
The calcareous prairies of Louisiana have been threatened by the encroachment of woody plants, primarily eastern red cedar (Juniperus virginiana). The knowledge of whether eastern red cedar encroachment has altered the soil chemical characteristics is of interest in light of the restoration and management of these rare plant communities. The objectives of this study were to investigate differences in soil nutrient levels among prairie, transition and forest soils and to determine which soil properties could be used to differentiate prairie soils from soils impacted by woody vegetation. We collected soil samples along transects traversing prairie, transition, and forest from three remnant calcareous prairies in Louisiana. We also measured relative elevation (RE) at the points where soil samples were taken. The transition was the area heavily encroached by red cedar. The soil samples were analyzed for pH, electrical conductivity (EC), and Mehlich III extractable nutrients. Factor analysis and stepwise discriminant analysis were used to determine differences in these soil properties among the vegetation types and to identify the soil properties that could be used to discriminate the soil types (prairie soil, transition soil and forest soil). The prairie soil was distinctly different from the forest soil in nutrient levels while the transition soil shared the properties of both the forest soil and the prairie soil but with a change toward the forest soil, indicating that eastern red cedar impacted the prairie soil. The discriminating soil and topographical attributes were pH, nutrients (Ca, Mg, Fe, and Mn) and RE. The discriminant functions derived from these attributes reasonably predicted the soil types and may be used as a predictive and classification tool in the effort to delineate similar prairie‐forest associations encroached upon by eastern red cedar. In addition, these findings provide land managers of natural areas, especially of humid regions, a better perspective on eastern red cedar impact on prairie soil nutrient levels.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".