Assessment of Rusty Blackbird Habitat Occupancy in the Long Range Mountains of Newfoundland, Canada Using Forest Inventory Data
Bibliographic record
Abstract
Rusty blackbirds (Euphagus carolinus), once common across their boreal breeding distribution, have undergone steep, range-wide population declines. Newfoundland is home to what has been described as one of just two known subspecies (E. c. nigrans) and hosts some of the highest known densities of the species across its extensive breeding range. To contribute to a growing body of literature examining rusty blackbird breeding ecology, we studied habitat occupancy in Western Newfoundland. We conducted 1960 point counts across a systematic survey grid during the 2016 and 2017 breeding seasons, and modeled blackbird occupancy using forest resource inventory data. We also assessed the relationship between the presence of introduced red squirrels (Tamiasciurus hudsonicus), an avian nest predator, and blackbird occupancy. We evaluated 31 a priori models of blackbird probability of occurrence. Consistent with existing literature, the best predictors of blackbird occupancy were lakes and ponds, streams, rivers, and bogs. Red squirrels did not appear to have a strong influence on blackbird habitat occupancy. We are among the first to model rusty blackbird habitat occupancy using remotely-sensed landcover data; given the widespread availability of forest resource inventory data, this approach may be useful in conservation efforts for this and other rare but widespread boreal species. Given that Newfoundland may be a geographic stronghold for rusty blackbirds, future research should focus on this distinct population.
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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 | 0.000 | 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 | 0.001 |
| 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".