Slow demography and limited dispersal constrain the expansion of north‐eastern temperate forests under climate change
Bibliographic record
Abstract
Abstract Aim Tree species may be vulnerable to migration lags because they are sessile, long‐lived, have a small intrinsic growth rate and relatively short dispersal. Our study assesses if those ecological mechanisms will mitigate the progression of the north‐eastern American temperate forest leading edge into the boreal forest. Location The North‐eastern boreal‐temperate forest ecotone (from 43° to 51° North and 80° to 60° West). Taxon Our approach involved 15 forest species classified into four representative forest communities of the eastern boreal‐temperate forest. Methods We performed simulations on the boreal‐temperate ecotone using a state and transition model (STM), wherein forest communities are classified in four states: boreal, temperate, mixed and stands in regeneration. We propose a new modelling approach based on metapopulation theory to account for dispersal limitations and the demography of the temperate and boreal forests. We calibrated the STM model with an extensive dataset of 48,940 forest inventory plots. We projected the boreal‐temperate forest landscape over 23 General Circulation models (GCMs) from the RCP 8.5 emission scenario to study the forest communities dynamics at the landscape scale under climate change. Results Simulations of climate changes predict a significant increase of temperate forest dominance within the ecotone, mainly due to the conversion of mixed stands into temperate stands. The leading edge of the temperate forest will however move only 304 m in latitude (95% CI: 0.18–0.56) into the boreal forest by the end of this century. In comparison, the average expansion rate was 2,555 m/year (95% CI: 1,969–2,932) when we released the dispersal constraint and even higher with an average rate of 7,197 m/year (95% CI: 5,722–9,776) when we released the dispersal and demography constraints. Main conclusions The northern edge of the temperate forest distribution does not change with almost no movement toward the north for either temperate or mixed communities by the end of this century. Slow demographic and dispersal rates prevent any substantial movement in temperate forests, with much faster migration rates when these constraints are removed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".