Tree vulnerability to climate change: improving exposure‐based assessments using traits as indicators of sensitivity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Projected changes in climate conditions vary widely across Canada's 350 M ha of forests, and so does the capacity of forest species to cope with these changes (sensitivity). Development and prioritization of adaptation strategies for sustainable forest management will depend on integrated assessments of relative stand vulnerability. We developed species‐specific indices of sensitivity to (1) drought‐induced mortality and (2) migration failure, based on traits for 22 of the most abundant tree species in Canada. By combining this information with stand composition data and spatially explicit climate change projections, we were able to map Canadian forest vulnerability to drought and migration failure. Our maps show forest vulnerability changing rapidly under a high carbon emission scenario ( RCP 8.5) between short‐ (2011–2040), medium‐ (2041–2070), and long‐term projections (2071–2100). Several zones of special concern emerged based on the biomass involved, stand sensitivity, and vulnerability trends across time. Boreal forests in the central regions of Alberta and Saskatchewan appeared most vulnerable to drought‐induced mortality in the mid to long term. In the short term, distance to suitable habitat is projected to shift quickly along latitudinal gradients, particularly in Central Canada, while zones of vulnerability to migration failure appeared across the Rockies region in the long term as suitable conditions disappear from mountainous areas. This spatial assessment of vulnerability, which integrates species‐specific sensitivity, highlights important regional contrasts between vulnerability to drought (from high exposure, high proportion of sensitive species, or both) and to migration failure. By affecting either species’ ability to persist in place or to migrate, different climate change impacts can yield distinct biotic responses, with important implications for regional climate change adaptation strategies. Multi‐faceted vulnerability assessments, integrating both exposure and sensitivity indices specific to expected impacts of climate change, have the potential to provide crucial information to managers. We discuss some of these implications, explore the current limitations of our approach, and suggest a path forward.
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.
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 | 0.000 | 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) | 0.002 | 0.001 |
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 it