The Influence of Biological Soil Crusts on Soil Characteristics along a High Arctic Glacier Foreland, Nunavut, Canada
Bibliographic record
Abstract
This study explores the physical, chemical and microclimatological properties of soils along a High Arctic glacier foreland and adjacent moraine in relation to the development of biological soil crusts. We examine various edaphic properties: soil temperature, volumetric water content, organic carbon content, and texture in surface samples (∼1 cm) with and without a cover of biological soil crust as well as changes in nitrogen, phosphorus, potassium, organic carbon, pH, volumetric water content, bulk density, and texture in crusted surfaces (<1 cm) and soil cores (5 cm) along a chronosequence following deglaciation. Soil crusts developed within four years of deglaciation and subsequent peaks in crust cover and thickness coincided with an accumulation of nitrogen and organic carbon in the crust. Crusted surfaces had significantly higher volumetric water content, organic carbon, a greater silt and clay fraction, and lower temperature compared to uncrusted soils. A steady supply of water from glacier melt promoted rapid development of biological soil crusts, creating an edaphic environment with enhanced moisture and nutrient properties which contributed to the high rate of vascular plant succession previously observed on this foreland. Results presented in this study are compared with edaphic conditions at other circumpolar sites and glacier forelands.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".