Interaction between the effects of genetic structure and habitat conditions on douglas fir growth in provenance tests in Bosnia and Herzegovina
Bibliographic record
Abstract
Douglas fir (Pseudotsuga menziesii (Mirbel) Franco) is the most important and most productive species in Europe, outside its natural range. This study aimed to examine the presence of interaction between the effects of the genetic structure of provenances from the United States and Canada and three localities of provenance tests in Bosnia and Herzegovina. For this research, we measured diameters at breast height of all trees, and heights of 10 trees per provenance in three tests of Douglas fir at the age of plants 32 years. Four provenances are represented in all three tests and additional two provenances in two tests. We examined the variance between provenances and habitats using multivariate analysis, for four provenances in all three habitats, and six provenances in two habitats (Bosanska Gradiška and Zavidovići). Multivariate analysis of variance for four provenances at all three localities showed that there were no statistically significant differences in diameters at breast height and heights caused by the interaction of provenances x localities. Multivariate analysis for six joint provenances at Bosanska Gradiška and Zavidovići tests showed that there were no statistically significant differences for diameter at breast height caused by interaction locality x provenance, and there were statistically significant differences caused by interactions of locality x provenances for height. The obtained results can be used for the introduction of Douglas fir on predefined habitats that correspond to the conditions of the experimental plots, as well as for the selection of the best provenances for raising clone plantations or seed plantations.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".