Variation in soil and foliar nutrition status along a forest edge–interior gradient in sugar maple forest fragments
Bibliographic record
Abstract
The consequences of forest fragmentation and edge effects on soil nutrient availability and nutrition of sugar maple (Acer saccharum Marsh.) forests remain understudied. We assessed soil chemistry (bulk pH, total carbon (C) and nitrogen (N), extractable phosphorus (P), exchangeable cations, and mineralizable N) and foliar nutrition (N, P, potassium (K), calcium (Ca), and magnesium (Mg)) of mature sugar maple forests along an edge–interior gradient (10, 20, 30, 50, 70, and 120 m from the forest edges) in seven sugar maple forest stands (three on sandstone and four on dolomite bedrock) that are embedded within an agricultural landscape in southern Quebec, Canada. We hypothesized that foliar nutritional imbalances of sugar maple forests would decline along this gradient. Foliar nutrition was analyzed using the diagnosis and recommendation integrated system (DRIS) and the compositional nutrient diagnosis with isometric log-ratio (CND-ilr) method. At the sandstone sites, rates of N mineralization and nitrification increased with increasing distance from the forest edge. Other soil chemical properties and all sugar maple foliar indices of nutritional diagnostics varied weakly along the edge–interior gradient. Assessment of sugar maple forest nutritional status through different nutritional indices revealed K and P deficiencies in all stands that were sampled and at all distances from the forest edge. Overall, we found weak forest-edge effects on soil chemical properties and sugar maple forest nutritional status.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".