Topography and Climate Influence on Radial Growth and Climate Sensitivity of Conifer Tree Species in Kananaskis, Alberta
Bibliographic record
Abstract
High elevation temperate forest at its upper limit are delimited by temperature. Climate warming would impose changes by altering growth conditions in these previously constrained environments. Growth response to climate will vary depending on topography and tree species. A dendroclimatological approach was employed to investigate spatial (tundra, treeline and forest along with north and south aspect) and temporal (1900-2017) variations in climate-growth sensitivity of four tree species: subalpine fir, subalpine larch, Engelmann spruce, and lodgepole pine in Kananaskis, Alberta. Correlation analyses showed similar climate-growth sensitivity for subalpine fir and Engelmann spruce at forest and treeline sites. Lodgepole pine only found on south-facing forest sites was not comparable with other species, but subalpine larch growth sensitivity was different from subalpine fir and Engelmann spruce. Treeline and tundra sites were only responsive to temperature; while precipitation was negatively significant at forest sites. Moving interval analysis revealed increased sensitivity to summer and winter temperatures in recent years, which is attributable to the climate change induced temperature increase in the study area. Tree growth was determined by calculating basal area increment for the studied tree species at all sites. Overall, south-facing sites had higher growth rates across elevations. Engelmann spruce had the highest growth rate at treeline and forest sites. Given projected climate change induced temperature and precipitation in the study area, the greatest growth increase will likely be at treeline, specifically for Engelmann spruce. Forest sites wouldn’t likely change as much as treeline sites as the precipitation increase that would offset temperature induced growth increases. To conclude, topography will continue to be the determinant of climate-growth response in future. The interaction between topography with regional climate parameters makes for complex patterns of vegetation response in this region.
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".