Relationships between individual‐tree mortality and water‐balance variables indicate positive trends in water stress‐induced tree mortality across North America
Bibliographic record
Abstract
Abstract Accounting for water stress‐induced tree mortality in forest productivity models remains a challenge due to uncertainty in stress tolerance of tree populations. In this study, logistic regression models were developed to assess species‐specific relationships between probability of mortality ( P m ) and drought, drawing on 8.1 million observations of change in vital status ( m ) of individual trees across North America. Drought was defined by standardized (relative) values of soil water content ( W s,z ) and reference evapotranspiration ( ET r,z ) at each field plot. The models additionally tested for interactions between the water‐balance variables, aridity class of the site ( AC ), and estimated tree height ( h ). Considering drought improved model performance in 95 (80) per cent of the 64 tested species during calibration (cross‐validation). On average, sensitivity to relative drought increased with site AC (i.e. aridity). Interaction between water‐balance variables and estimated tree height indicated that drought sensitivity commonly decreased during early height development and increased during late height development, which may reflect expansion of the root system and decreasing whole‐plant, leaf‐specific hydraulic conductance, respectively. Across North America, predictions suggested that changes in the water balance caused mortality to increase from 1.1% yr −1 in 1951 to 2.0% yr −1 in 2014 (a net change of 0.9 ± 0.3% yr −1 ). Interannual variation in mortality also increased, driven by increasingly severe droughts in 1988, 1998, 2006, 2007 and 2012. With strong confidence, this study indicates that water stress is a common cause of tree mortality. With weak‐to‐moderate confidence, this study strengthens previous claims attributing positive trends in mortality to increasing levels of water stress. This ‘learn‐as‐we‐go’ approach – defined by sampling rare drought events as they continue to intensify – will help to constrain the hydraulic limits of dominant tree species and the viability of boreal and temperate forest biomes under continued climate change.
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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 | 0.000 |
| 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".