Nutrient distribution and cycling along a forest chronosequence following the regreening of a mining and smelting degraded landscape
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Context The regreening (the one-time application of soil amendments and tree planting) of mining and smelting degraded landscapes can increase site productivity and ecosystem nutrients in the short-term, but uncertainties exist regarding long-term nutrient status. Aims This study investigated whether nutrient distribution and cycling change with stand age in regreened forests on a mining and smelting degraded landscape in the City of Greater Sudbury, Canada. Methods We measured soil and vegetation nutrient concentrations (calcium (Ca), magnesium (Mg), nitrogen (N), phosphorus (P), and potassium (K)), nutrient resorption, litter decomposition, and N mineralisation along a chronosequence of forested sites (n = 12) that were regreened 15–40 years prior to sampling. Key results As regreening stands aged, concentrations of Mg, K, and P increased in lower soil horizons, but foliar concentrations of nutrients did not change. The regreening sites were very rich in Ca and Mg but soils were poor in P, K, inorganic N, and N mineralisation rates were very low. We found few relationships between nutrient cycling and stand age. Potassium and P are thought to be the limiting nutrients in the region and while resorption efficiency of K was much higher than expected, foliar N, P and K concentrations were comparable to ‘healthy’ values. Conclusions The lack of change in foliar nutrients and nutrient cycling with stand age suggest that nutrient limitation is not inhibiting forest function 40 years following a one-time regreening treatment. Implications This study provides perspective to the long-term success of a one-time regreening on an immensely degraded industrial landscape.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it