Differential Growth and Rooting of Upland and Peatland Black Spruce, Picea mariana, in Drained and Flooded Soils
Bibliographic record
Abstract
Abstract A reciprocal experiment was analyzed to determine whether 30 open-pollinated families of peatland and upland populations of black spruce [Picea mariana (Mill.) B.S.P.] sampled from a single area in north-central Alberta, Canada, performed consistently when grown in either flooded or well-drained soils (i.e., if there is a family x soil interaction or generally called genotype x environment interaction (GEI)). The data for the analysis consisted of five traits (height, root dry weight, shoot dry weight, root/shoot dry weight ratio and number of braches) describing growth and rooting performance of tree seedlings in flooded and drained soils (root environments) in a greenhouse for 16 weeks. A mixed-model analysis was used to characterize GEI. The analysis revealed an interesting contrast of GEI patterns between the peatland vs. upland populations: GEI was absent (as indicated by a perfect correlation between flooded and drained soils) in peatland population but present in the upland population. Our results from the characterization of GEI are also consistent with the well-known theory about selection in different environments that correlated responses due to indirect selection are in general less than direct responses. The contrasting patterns of GEI in peatland vs. upland populations may be reflective of different strategies of adaptation to the contrasting environmental conditions, with the peatland trees growing slowly but steadily and with the upland populations growing fast and very responsive to environmental changes.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".