Effects of shading and humus fertility on growth, competition, and ectomycorrhizal colonization of boreal forest tree seedlings
Bibliographic record
Abstract
We performed a pot experiment to study the effects of varying levels of vegetation shade and humus fertility, simulating natural conditions of the boreal forest, on growth, interspecific competition, and ectomycorrhizal colonization of seedlings of three coexisting tree species: Pinus sylvestris L., Picea abies (L.) Karst., and Betula pendula Roth. In contrast to late-successional Picea abies, early-successional species Pinus sylvestris and particularly B. pendula responded to shade with an increase in stem height and with some changes in biomass, especially in the high-fertility humus. Humus fertility had greater effects on biomass of seedlings than did shade treatments. Interspecific competition among pairwise combinations of the three species was greatest in the high-fertility humus, but was not affected by shade. Betula pendula was the strongest competitor among species; it was not affected by the presence of coexisting species and strongly suppressed coniferous seedlings, especially in the high-fertility humus. Generally, ectomycorrhizal colonization was not affected by shade treatments, but was highest in the low-fertility humus. These results show that effects of light, humus fertility, and presence of neighbours are species specific, and these differences are important for the competitive and recruitment abilities of seedlings of coexisting tree species and ultimately for the species composition of developing forests.
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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) | 0.001 | 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 | 0.001 |
| 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".