Oak regeneration at the arid boundary of the temperate deciduous forest biome: insights from a seeding and watering experiment
Bibliographic record
Abstract
Abstract Temperate deciduous forests dominated by oaks cover extensive areas in European lowlands. These ecosystems have been under intense anthropogenic use for millennia, thus their natural dynamics, and their regeneration in particular, is still not well understood. Previous studies found that pedunculate oak ( Quercus robur ), one of the most widespread and abundant species in European deciduous forests, regenerates in open habitats and forest edges, but not in closed forest interiors. However, these observations usually come from the core areas of the biome, and much less is known about such processes at its arid boundary, where limiting factors may be different, and climate change may first exert its effects. In a full factorial field experiment, we tested the effects of different habitats and increased growing season precipitation on the early regeneration of pedunculate oak in a forest-steppe ecosystem in Central Hungary, at the arid boundary of temperate deciduous forests. We planted acorns into three neighbouring habitats (grassland, forest edge, forest interior) and studied seedling emergence and plant performance under ambient weather and additional watering for four years. In the grassland habitat, seedling emergence was very low, and no seedlings survived by the fourth year. In contrast, seedling emergence was high and similar at forest edges and forest interiors, and was not affected by water addition. Most seedlings survived until the fourth year, with no difference between forest edge and forest interior habitats in numbers, and only minor or transient differences in size (leaf number, height). The lack of oak regeneration in the grassland contradicts previous reports on successful oak regeneration in open habitats, and may be related to a shift from light limitation to other limiting factors, such as moisture or microclimatic extremes, when moving away from the core of the deciduous forest biome towards its arid boundary. The similar number and performance of seedlings in forest edges and forest interiors may also be related to the decreasing importance of light limitation. The above-average precipitation in the year of seedling emergence (2016) might be a reason why watering had no effect on oak regeneration. Overall, our results highlight that oak regeneration and thus forest dynamics may be limited by different factors at a biome boundary compared to its core areas. Indeed, this very simple mechanism (inability of oak regeneration in grassland habitats) may contribute to the opening up of the closed forest biome, and the emergence of a biome transition zone.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".