Anthropogenic and climate impacts on subarctic forests in the Nain region, Nunatsiavut: Dendroecological and historical approaches
Bibliographic record
Abstract
Several recent dendrochronological, macrofossil and palynological studies have surveyed modern spruce forests at multiple locations in the Nain region of coastal Nunatsiavut (north-central Labrador) in order to reconstruct past forest composition, growth rates, species diversity and harvesting patterns. The present paper synthesizes original and previously collected data to evaluate the extent to which the dynamics of the region’s spruce forests over the past five centuries have been related to anthropogenic impacts. In three key case studies, Picea growth release events demonstrate multiple isolated forest disturbances prior to the late 19th century. In general, these events correspond to the local human settlement history rather than to regional climatic trends, suggesting that ongoing human impacts on the forest extend as far back as the 17th century. Disturbance regimes accelerated by ca 1875 and afterward in all of the study sites. This increase in forest disturbance corresponds to increased demands for wood triggered by socio-economic changes experienced by the region’s Inuit and Settler communities. Ongoing surveys demonstrate the presence of markers of human exploitation of forests throughout the study region, and especially in coastal locations, suggesting that anthropogenic impacts are in fact generalised and not limited to specific areas of recent settlement.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".