Using air photos to interpret quality of Marbled Murrelet nesting habitat in south coastal British Columbia
Bibliographic record
Abstract
Reliable habitat assessment methods are needed to ensure the adequate management of Marbled Murrelet (Brachyramphus marmoratus) habitat in British Columbia. In two south coastal study regions, the Sunshine Coast and Clayoquot Sound, we evaluated the effectiveness of a qualitative habitat classification that uses air photo-interpreted forest structural characteristics for identifying and ranking habitat quality. Using a sample of 118 nest sites and 157 random sites within forests greater than 140 years old, we found that murrelets selected nest patches non-randomly with respect to forest characteristics. While selectivity varied between study regions, generally nest patches had taller and larger trees, exhibited more complex forest structure, and were located at lower meso-slope positions near large gaps or nearby edges. In addition, these patches were more often ranked higher in terms of habitat quality. However, we found that probable breeding success was greater in habitats classified as lower quality. Thus, further research is needed to understand our findings relative to other influences on breeding productivity, such as predators and hierarchal habitat selection. In summary, while our study supports the use of the current air photo habitat classification standards to improve identification and selection of murrelet nesting habitat for management, some modifications to these standards may be needed.
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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".