Isotope applications to soil science at the University of Alberta — an historical perspective
Bibliographic record
Abstract
For the past 70 yr, researchers in the Soil Science/Renewable Resources Department at the University of Alberta have used isotopes to study topics of ecological importance. This review highlights the soil isotope research conducted within our department over this time, including an historical overview of studies of interest. Analytical techniques and advances in instrumentation are discussed, focusing on the measurement of light stable isotope ratios (i.e., for C, H, N, S, and O) using isotope ratio mass spectrometry (IRMS). Early soil isotope work (1950–2000s) focused on agricultural soils and soil fertility issues. These studies included the use of radioactive isotopes such as 14C and 35S, and (or) artificially enriched stable isotopes including 15N-labelled fertilizers. More recently (2000–present), the scope of research widened to include natural-abundance stable isotope ratio studies as higher-sensitivity IRMS systems became more prevalent. Current isotope research topics include N biogeochemistry in natural and managed ecosystems, land management effects on greenhouse gas emissions, carbon cycling in northern landscapes, paleo-reconstruction in peatlands, carbon sequestration in boreal forests, and biodegradation of petroleum hydrocarbons. Further technological progress also enabled new techniques such as compound-specific IRMS analysis, including δ13C and δ2H measurements of soil n-alkanes and phospholipid fatty acids. In conclusion, current IRMS instrumentation presents unparalleled opportunities for multidisciplinary research to track carbon, plant nutrients, and pollutants as they move through soils.
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 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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".