Advancing towards novel tree lines? A multispecies approach to recent tree line dynamics in subarctic alpine Labrador, northern Canada
Bibliographic record
Abstract
Abstract Aim Comparisons of how different species respond to changing climatic conditions offer insight into future community composition and the potential formation of novel communities. This study investigated changes at a subarctic forest–tundra ecotone, or ‘tree line’. Our objectives were: (1) to explore species‐specific growth forms; (2) to identify temporal patterns of establishment and stand density; and (3) to explore relationships between climate and recruitment/survival amongst co‐dominant tree species, with the expectation that climate change will affect species differentially. Location The Mealy Mountains in the High Subarctic Tundra ecoregion in central Labrador, Canada. Methods We examined tree line dynamics for four tree species over the past two centuries. Using ecological and age‐structure data, we compared diameter/height relationships across the tree line and generated static age structures from which changes in stand density through time were compared. In addition, model residuals were used to quantify relationships between multi‐decadal windows of temperature/palaeotemperature/Palmer Drought Severity Index and decadal tree recruitment. Results Trees were more stunted as elevation increased, except for white spruce ( Picea glauca ) for which tree islands became the dominant growth form. The only tree seedlings found at the tree line were of larch ( Larix laricina ) and to a lesser extent black spruce ( Picea mariana ). From the age structure of trees (height > 2.0 m), only black spruce showed evidence of an advancing tree line. Larch and balsam fir ( Abies balsamea ) have become established at the tree line most recently and have undergone greater increases in density over the past few decades. Variability in recruitment increased with elevation: larch recruitment was positively correlated with temperature and negatively correlated with drought at low elevations but negatively correlated with temperature and positively correlated with drought at high elevations, whereas black spruce recruitment was consistently positively correlated with temperature and drought. Main conclusions The multispecies approach provides evidence that species are responding differentially to climate. With continued climate change, we expect density increases and advances of larch and black spruce, giving rise to novel tree line communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".