Scale-dependent environmental controls over species composition in Alaskan black spruce communities
Bibliographic record
Abstract
The boreal forest is the second largest terrestrial biome, and the black spruce (Picea mariana (Mill.) BSP) forest type occupies a large extent of boreal North America. Black spruce communities occur in a variety of environmental conditions and are especially important in the context of climate change because of underlain permafrost in much of the northern black spruce forests, as well as their adaptation to fire disturbance. We used a classification and ordination approach to describe and name Alaskan black spruce communities and relate them to key environmental variables. We analyzed the relationship of species richness with topographic position and with soil pH using both univariate and multivariate analyses of variance. We also explored the variability in structural, physical, and soil characteristics. We described three black spruce community types and five subtypes based purely on floristic composition. Paludification and topography were the most important gradients explaining species composition for the Fairbanks region (61% variance explained). However, at the scale of interior Alaska, pH, drainage, and productivity were the strongest environmental gradients (81% variance explained). We conclude that species composition of mature black spruce forests in interior Alaska results from the complex interaction of landscape and fire history, soil pH, paludification, permafrost, and topographic position.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".