Spatial and population characteristics of dwarf mistletoe infected trees in an old-growth Douglas-fir western hemlock forest
Bibliographic record
Abstract
We investigated the distribution and severity of trees infected with western hemlock dwarf mistletoe (Arceuthobium tsugense (Rosendahl) G.N. Jones subsp. tsugense) in an old-growth Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) western hemlock (Tsuga heterophylla (Raf.) Sarg.) forest. With the use of Hawksworth six-class dwarf mistletoe rating system, infection status was assessed for 3516 hemlock and true firs ≥5 cm diameter on a 12-ha stem-mapped plot located in the Cascade Mountains of southwest Washington State. Within the plot, 33% of the area had some level of infection and 25% (719) of western hemlocks, 2.2% (12) of Pacific silver fir (Abies amabilis (Dougl.) Forbes), and 29% (2) of noble fir (Abies procera Rehd.) trees were infected. Infected trees are larger than uninfected trees, on average, and within the infected tree population, the severely infected trees averaged larger than lightly infected trees. Abundant dwarf mistletoe in larger trees definitely positions the dwarf mistletoe population for future spread. Ripley's K analysis indicates a negative association between infected and uninfected hemlock trees, confirming that the infected trees form distinct dwarf mistletoe infection centers. The infection centers are actively spreading at their margins, which was confirmed by nearest neighbor analysis. Heavily infected trees had a negative association with uninfected trees, while lightly infected trees had a positive association with uninfected trees.
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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 | 0.000 | 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) | 0.000 | 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".