Pollen pool heterogeneity in natural stands of upland and lowland black spruce (Picea marinana (Mill.) B.S.P.)
Bibliographic record
Abstract
One of the basic assumptions of the mixed-mating model is that \nthe pollen pool of a population is homogeneous. However mounting \nevidence would suggest that a homogeneous pollen pool is not the \nnorm in populations of forest tree species. Such a phenomenon may \nhave major implications upon the mating systems and genetic \nstructure of forest tree species. The present study was conducted \nin order to develop a better understanding of the nature and \nimplications of pollen pool heterogeneity in natural populations of \nblack spruce. Four natural stands of black spruce within 100 \nkilometers of Thunder Bay, Ontario were studied using isozyme \nmarkers from eight polymorphic loci. The stands studied represent \nthe two basic ecological conditions under which black spruce is \nfound, i.e. upland and lowland stands. Both log-likelihood G tests \nand multiple group discriminant analysis indicated the presence of \nheterogeneous pollen pools for all four sites. However, as \nindicated by the canonical for the first discriminant function \nof each site, the separation power of data from three of the four \nsites was quite small (R2 of 0.063 to 0.127) . Only for Raith 2 was \nthe seperation power strong (R2 of 0.379). Overall the \nheterogeneity tended to be random in nature. Due to the apparent \nrandom nature of the heterogeneity it was not possible to associate \nthe examined site characteristics with the relative degree of \npollen pool heterogeneity observed in the four sites. Possible \nagents which may have produced a heterogeneous pollen pool are \nconsidered as are potential implications of this phenomenon on the \ngenetics of black spruce.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".