Comparing soil biogeochemical processes in novel and natural boreal forest ecosystems
Bibliographic record
Abstract
Abstract. Emulating the variability that exists in the natural landscape prior to disturbance should be a goal of soil reconstruction and land reclamation efforts following resource extraction. Long-term ecosystem sustainability within reclaimed landscapes can only be achieved with the re-establishment of biogeochemical processes between reconstructed soils and plants. In this study, we assessed key soil biogeochemical attributes (nutrient availability, organic matter composition, and microbial communities) in reconstructed, novel, anthropogenic ecosystems, covering different reclamation treatments following open-cast mining for oil extraction. We compared the attributes to those present in a range of natural soils representative of mature boreal forest ecosystems in the same area of Northern Alberta. Soil nutrient availability was determined in situ with resin probes, organic matter composition was described with 13C nuclear magnetic resonance spectroscopy and soil microbial community structure was characterized using phospholipid fatty acid analysis. Significant differences among natural ecosystems were apparent in nutrient availability and seemed more related to the dominant tree cover than to soil type. When analyzed together, all natural forests differed significantly from the novel ecosystems, in particular with respect to soil organic matter composition. However, there was some overlap between the reconstructed soils and some of the natural ecosystems in nutrient availability and microbial communities, but not in organic matter characteristics. Hence, our results illustrate the importance of considering the range of natural landscape variability and including several soil biogeochemical attributes when comparing novel, anthropogenic ecosystems to the mature ecosystems that constitute ecological targets.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".