Using ecosystem water and carbon fluxes as integrated measures of reclamation success
Bibliographic record
Abstract
The cycling of water, energy, and carbon are ecosystem functions that support the overall health and success of vegetated ecosystems. With insufficient water and/or nutrients, water use and carbon uptake are reduced and ecosystems experience stress. In most of western and northern Canada, ecosystems experience growing-season water stresses that limit growth. Understanding the linkages between climate, water availability and use, and carbon assimilation is central to understanding of the magnitude of this limitation, and of key ecosystem functions. We assembled and synthesized over 15 years of research on water and carbon fluxes and ecosystem development on reclaimed oil-sands mine sites and on non-mine reference sites in the Athabasca Oil Sands Region of northern Alberta. A central premise of this work is that if reclaimed and reference sites with similar moisture and nutrient availability are using water and assimilating carbon at similar rates under the same climate, this suggests that the reclaimed sites are experiencing no greater levels of environmental stress than the reference sites, and no greater limitations to utilizing available site resources. Results of our work indicate similar functional processes of water storage and use, and carbon assimilation, between mine sites reclaimed to boreal-forest communities and non-mine reference sites.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".