Bald eagle nest site and nest tree characteristics in select biogeoclimatic zones of the 100 Mile House Forest District, British Columbia
Bibliographic record
Abstract
Bald eagle (Haliaeetus leucocephalus) nest site and nest tree characteristics were studied in the Sub-Boreal Spruce (SBS), Interior Cedar–Hemlock (ICH), Sub-Boreal Pine–Spruce (SBPS), and interior Douglas-fir (IDF) biogeoclimatic zones in the 100 Mile House Forest District, British Columbia. Dominant or codominant Douglas-fir (Pseudotsuga menziesii) containing large trunk forks or multiple forks of the trunk comprised 85% of 121 bald eagle nest trees. Black cottonwood (Populus trichocarpa) comprised 11% of known nest trees, and trembling aspen (Populus tremuloides), lodgepole pine (Pinus contorta), Ponderosa pine (Pinus ponderosa), and hybrid white spruce (Picea glauca x engelmannii) each contained 1% of known bald eagle nests. Tree height and diameter at breast height (DBH), nest height, and distance of nest to fish-bearing water were less for island nests compared to non-island nests. The mean distance of nests to fish-bearing water, by biogeoclimatic zone, was 78 m in the SBS, 104 m in the ICH, 241 m in the SBPS, and 368 m in the IDF. Ground slope and aspect were not factors in nest site location. The bald eagle nest trees studied were generally of low economic value to the forest industry as they contained less recoverable lumber than similar-sized trees with better form. To maintain bald eagle nesting habitat, large diameter, dominant or codominant trees containing large trunk forks, or multiple forks or leaders of the trunk and (or) large limbs should be identified and retained in groups, patches, or forest stands.
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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".