Effects of reforestation on near‐surface saturated hydraulic conductivity in a managed forest landscape, southern Ontario, Canada
Bibliographic record
Abstract
ABSTRACT Reforestation of previously deforested landscapes often increases soil organic matter content and porosity as the plantation forest ages, leading to increased soil saturated hydraulic conductivity (KH). However, the time required for a reforested soil's KH to recover to that of the original forest differs considerably between locations because of variations in forest, climatic and soil properties. We examined a chronosequence of sites on similar soils in a managed forest landscape in southern Ontario, Canada, ranging from open fields deforested in the late 19th century, through red pine (Pinus resinosa) stands of varying age, to 100+ year‐old mixed conifer–hardwoods. Soil texture, organic matter content, bulk density, KH, and overstory and understory forest characteristics were measured. For sites with similar soil textures, there was a general increase in KH in the following sequence: open fields → red pine plantations → mixed conifer–hardwood stands. There were no significant changes in near‐surface organic matter contents or soil bulk densities with forest age, and neither factor was related to temporal changes in KH. Temporal trends in KH were associated with increased understory density with forest age, suggesting that increases in KH were driven by understory root development and greater macroporosity. It may take ~25 years before reforestation begins to affect soil infiltration characteristics at the stand scale and at least 40 years following planting before the KH of soils under red pine plantations begins to equal that for undisturbed mixed conifer–hardwood stands. This recovery may be assisted by management activities such as thinning of red pine stands, which promotes understory development. Copyright © 2012 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".