Interactions between macro and micro climate and anthropogenic disturbance on the distribution of aspen near its northern edge in Quebec: implications for climate change related range expansions
Bibliographic record
Abstract
Predictions of shifting tree species distributions in boreal forests require policy that is based on a sound understanding of the principal drivers of forest response to environmental change. This research characterizes the regional distribution and abundance of trembling aspen (Populus tremuloides Michx.) near its northern range limit in northwestern Quebec, Canada, using a combination of remote sensing, geographic information systems (GIS) analysis, and ground-based techniques. Although not regionally abundant, aspen is the main deciduous tree species in this conifer dominated landscape. Regionally, the ~51,200 km2 study area has few settlements or roads, and is without industrial activity that affects the land. Most of the region is inaccessible except by foot or water travel. We utilized Landsat Thematic Mapper images from 2010 and 2011, a robust collection of ground reference data developed from aerial photography, supported by field verification (vegetation sampling) where access permitted, to construct a thematic map of 11 land cover classes. The map highlights the spatial distribution of aspen, which represents only 0.3% of the study area. Map validation indicated an overall mapping accuracy of 74%, while the aspen predicted class was assessed at over 77% accurate. The regional scale distribution of aspen stands ≥ 0.5 ha within the study area shows two patterns: (1) a shift toward greatest abundance on south-facing aspects with increasing latitude; and (2) a highly clustered pattern that includes concentrations in areas of human disturbance. These patterns suggest that aspen range expansion due to climate-change related warming will vary with topographic and other microclimatic factors, i.e. be a function of climate change interacting with landscapes, and that anthropogenic disturbances have the potential to influence future aspen abundance independently of climate. Forest management policies concerned with changing forest composition in these northern landscapes should recognize the potentially important role of human activity in driving the abundance of aspen. Keywords: Boreal forest ecology, climate change, land cover classification, aspen, species distribution.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".