Bibliographic record
Abstract
The boreal forest is a major ecosystem in Alberta, subject to a number of anthropogenic disturbances such as oil and gas extraction. Prior to disturbance, top soils are salvaged for use in future reclamation projects; however, a large portion of this soil ends up in stockpiles, undergoing changes to soil physical properties, aggregate and carbon distributions, as well as carbon dynamics. This study sought to assess changes in these parameters, relative to natural sites, to determine implications on the suitability of stockpiled topsoil for use in reclamation. Sampling sites were established at an open pit mine and an in situ development in the boreal forest. Eight stockpiles and six natural sites were selected, with three soil pits being dug per site and three depths sampled per pit. Soil physical quality (SPQ) was assessed using basic soil properties, capacity-based measurements, and energy parameters as all of these variables relate to S, defined as the slope at the inflection point of a water retention curve. As such, S provides insight on the pore-size distribution of a soil, with larger values denoting higher SPQ. Clay content and bulk density were higher in natural soils, whereas total soil carbon, S, capacity-based measurements, and energy parameters were higher in stockpiled soils. Significant differences between natural and stockpiled soils were present only in the two subsurface depths. Differences existed within natural soil profiles between the surface and two subsurface depths, while stockpiled soils remained similar across all depths. Higher levels of soil carbon, lower bulk densities, and lower clay contents in stockpiled soils were associated with the highest S values for sampled soils, supporting previous observations published in scientific literature. S was significantly correlated with most capacity-based measurements, supporting additional theories that link these parameters together. Energy parameters were also significantly correlated with S, though lower values for these parameters are associated with higher SPQ. Together, natural soils had lower SPQ than stockpiles using basic soil properties, capacity-based measurements, and S, while outcomes using air and water retention energies were inconclusive. Changes to aggregate size class and carbon distributions, carbon dynamics, and soil organic matter lability criteria were assessed at both the whole soil and individual aggregate scale. No significant differences in relative proportions of aggregate size classes were found between natural and stockpiled soils for any of the sampling depths, although natural soils did have higher proportions of both aggregate sizes. Higher basal respiration rates and 13C values were found in natural soils, whereas stockpiled soils had greater total and light fraction carbon quantities, along with higher C:N ratios. Significant differences between natural and stockpiled soils were largely confined to the two subsurface sampling depths. Differences within natural soils were between surface and subsurface depths, whereas stockpiles remained uniform across all depths. Basal respiration rates significantly correlated with total carbon, light fraction carbon proportions, whole soil C:N ratios, and 13C values. Similar trends were observed for each aggregate size. The results of this study differed greatly from the majority of findings present in the current literature base and demonstrate the importance of looking at the physical, chemical, and biological components of soil quality together. In the case of this study, taking a more holistic approach allowed for the identification of lower biological quality in stockpiled materials, despite these same materials having higher soil physical and chemical quality regardless of sampling depth. Identifying these limitations, in turn, would then allow for a more thorough assessment on the suitability of stockpiled topsoil for use in future reclamation activities and the potential for reclamation success post-placement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".