Area change of glaciers in the Canadian Rocky Mountains, 1919 to 2006
Bibliographic record
Abstract
Abstract. We used Interprovincial Boundary Commission Survey (IBCS) maps of the Alberta–British Columbia (BC) border (1903–1924), BC Terrain Resource Information Management (TRIM) data (1982–1987), and Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery (2000–2002 and 2006) to document planimetric changes in glacier cover in the Central and Southern Canadian Rocky Mountains between 1919 and 2006. Total glacierized area decreased by 590 ± 100 km2 (40 ± 7%), with 17 of 523 glaciers disappearing and 124 glaciers fragmenting into multiple ice masses. Fourteen of the glaciers that disappeared were less than 0.5 km2, and glaciers smaller than 1.0 km2 experienced the greatest relative area loss (64 ± 17%). Variation in area loss increased with small glaciers, suggesting local topographic setting controls the response of these glaciers to climate change. Absolute area loss negatively correlates with slope and minimum elevation, and relative area change negatively correlates with mean and median elevations. Similar average rates of area change were observed for the periods 1919–1985 and 1985–2001, at −6.3 ± 0.9 km2 yr−1 (−0.4 ± 0.1% yr−1) and −5.0 ± 0.5 km2 yr−1 (−0.3 ± 0.1% yr−1), respectively. The rate of area loss significantly increased for the period 2001–2006, −19.3 ± 2.4 km2 yr−1 (−1.3 ± 0.2% yr−1), with continued high minimum and accumulation season temperature anomalies and variable precipitation anomalies.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".