Competition, species interaction and ageing control tree mortality in boreal forests
Bibliographic record
Abstract
Summary 1. Tree mortality has important influences on forest structure and composition, but the mechanisms that cause tree mortality are not well understood. Asymmetric competition is known to be a dominant cause of plant mortality, but this idea has not received much attention in studies of long‐lived trees. 2. We hypothesised that while tree mortality is dependent on size relative to neighbours as a result of asymmetric competition, tree mortality of shade‐tolerant species varies little with size because of their physiological and morphological adaptations to shaded environments. Furthermore, we hypothesised that tree mortality is higher in more crowded stands because of higher average resource competition, in conspecific stands because of potential negative intra‐specific interactions, and in older stands because of the physiological limitations and susceptibility to minor disturbances of large trees. 3. Using data from repeatedly measured permanent sampling plots that covered a wide range of tree sizes, stand developmental stages and stand compositions in boreal forests, we simultaneously tested, by boosted regression tree models, the effects of an individual’s relative size, stand crowding, species interaction and ageing on mortality of Pinus banksiana, Populus tremuloides, Betula papyrifera and Picea mariana. 4. Mortality increased strongly with decreasing relative size for all study species, and the size‐dependent mortality was stronger for shade‐intolerant than for shade‐tolerant species. With increasing stand basal area, mortality increased for Pinus banksiana, Populus tremuloides and Picea mariana but decreased for Betula papyrifera. Mortality was higher in stands with more conspecific neighbours for Populus tremuloides, Betula papyrifera and Picea mariana, but was slightly lower for Pinus banksiana. Mortality also increased with stand age for all species. Furthermore, the size‐dependent mortality was generally stronger in more crowded stands. 5. Synthesis. Our findings show that tree mortality over a wide range of tree sizes, stand developmental stages and stand compositions in non‐equilibrium boreal forests was strongly controlled by competition, but species interactions and ageing were also important mechanisms. Furthermore, the relative importance of these mechanisms to tree mortality differed with the shade tolerance of species.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".