Novel forest decline triggered by multiple interactions among climate, an introduced pathogen and bark beetles
Bibliographic record
Abstract
Novel forest decline is increasing due to global environmental change, yet the causal factors and their interactions remain poorly understood. Using tree ring analyses, we show how climate and multiple biotic factors caused the decline of whitebark pine (Pinus albicaulis) in 16 stands in the southern Canadian Rockies. In our study area, 72% of whitebark pines were dead and 18% had partially dead crowns. Tree mortality peaked in the 1970s; however, the annual basal area increment of disturbed trees began to decline significantly in the late 1940s. Growth decline persisted up to 30 years before trees died from mountain pine beetle (Dendroctonus ponderosae), Ips spp. bark beetles or non-native blister rust pathogen (Cronartium ribicola). Climate-growth relations varied over time and differed among the healthy and disturbed subpopulations of whitebark pine. Prior to the 1940s, cool temperatures limited the growth of all subpopulations. Growth of live, healthy trees became limited by drought during the cool phase (1947 -1976) of the Pacific Decadal Oscillation (PDO) and then reverted to positive correlations with temperature during the subsequent warm PDO phase. In the 1940s, the climate-growth relations of the disturbed subpopulations diverged from the live, healthy trees with trees ultimately killed by mountain pine beetle diverging the most. We propose that multiple factors interacted over several decades to cause unprecedented rates of whitebark pine mortality. Climatic variation during the cool PDO phase caused drought stress that may have predisposed trees to blister rust. Subsequent decline in snowpack and warming temperatures likely incited further climatic stress and with blister rust reduced tree resistance to bark beetles. Ultimately, bark beetles and blister rust contributed to tree death. Our findings suggest the complexity of whitebark pine decline and the importance of considering multiway drought-disease-insect interactions over various timescales when interpreting forest decline.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".