Relations between red alder composition and understory vegetation in young mixed forests of southeast Alaska
Bibliographic record
Abstract
Interest in mixed red alder (Alnus rubra Bong.) conifer young-growth stands has grown in southeast Alaska, USA, because they appear to provide much more productive understory vegetation and wildlife habitat than do similar-aged pure conifer stands. We studied understory vegetation in nine even-aged young-growth stands (3842 years old) comprising a gradient of red alder conifer overstory composition, with red alder ranging from 0% to 86% of stand basal area. Conifers were Sitka spruce (Picea sitchensis (Bong.) Carr.), western hemlock (Tsuga heterophylla (Raf.) Sarg.), and western redcedar (Thuja plicata Donn ex D. Don). We measured understory biomass and net production (current annual growth) in each stand by species and plant part and estimated carrying capacity for black-tailed deer (Odocoileus hemionus sitkensis Cowan) with a food-based habitat model. Highly significant positive relations (P < 0.002) were found between red alder basal area and all of the following: total understory biomass (r2 = 0.743), net production of shrubs (r2 = 0.758) and herbs (r2 = 0.855), and summer carrying capacity for deer (r2 = 0.846). The high correlation between red alder and herbaceous production is especially important, because herbs are least abundant and most difficult to maintain in young-growth conifer forests of this region. Red alder offers prospects for increasing understory vegetation biomass and its food value for deer and other wildlife when included as a hardwood overstory species in mixed hardwoodconifer young-growth forests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".