With increasing site quality asymmetric competition and mortality reduces Scots pine (Pinus sylvestris L.) stand structuring across Europe
Bibliographic record
Abstract
Heterogeneity of structure can increase mechanical stability, stress resistance and resilience, biodiversity and many other functions and services of forest stands. That is why many silvicultural measures aim at enhancing structural diversity. However, the effectiveness and potential of structuring may depend on the site conditions. Here, we revealed how the stand structure is determined by site quality and results from site-dependent partitioning of growth and mortality among the trees. We based our study on 90 mature, even-aged, fully stocked monocultures of Scots pine (Pinus sylvestris L.) sampled in 21 countries along a productivity gradient across Europe. A mini-simulation study further analyzed the site-dependency of the interplay between growth and mortality and the resulting stand structure. The overarching hypothesis was that the stand structure changes with site quality and results from the site-dependent asymmetry of competition and mortality. First, we show that Scots pine stands structure across Europe become more homogeneous with increasing site quality. The coefficient of variation and Gini coefficient of stem diameter and tree height continuously decreased, whereas Stand Density Index and stand basal area increased with site index. Second, we reveal a site-dependency of the growth distribution among the trees and the mortality. With increasing site index, the asymmetry of both competition and growth distribution increased and suggested, at first glance, an increase in stand heterogeneity. However, with increasing site index, mortality eliminates mainly small instead of all-sized trees, cancels the size variation and reduces the structural heterogeneity. Third, we modelled the site-dependent interplay between growth partitioning and mortality. By scenario runs for different site conditions, we can show how the site-dependent structure at the stand level emerges from the asymmetric competition and mortality at the tree level and how the interplay changes with increasing site quality across Europe. Our most interesting finding was that the growth partitioning became more asymmetric and structuring with increasing site quality, but that the mortality eliminated predominantly small trees, reduced their size variation and thus reversed the impact of site quality on the structure. Finally, the reverse effects of mode of growth partitioning and mortality on the stand structure resulted in the highest size variation on poor sites and decreased structural heterogeneity with increasing site quality. Since our results indicate where heterogeneous structures need silviculture interventions and where they emerge naturally, we conclude that these findings may improve system understanding and modelling and guide forest management aiming at structurally rich forests.
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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 | 0.001 | 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 | 0.002 |
| 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".