Annual Cycle Phenology and Winter Habitat Selection of White-Winged Scoters in Eastern North America
Bibliographic record
Abstract
Concern over declining populations of several North American sea duck species has led to research addressing how environmental and anthropogenic factors in various stages of the annual cycle affect survival, habitat use, site fidelity, and migratory strategies. Southern New England provides key wintering habitat for White-winged Scoters (Melanitta fusca). This area has also pioneered the development of offshore wind energy in North America. I deployed implanted satellite transmitters in 52 adult female White-winged Scoters captured during the wintering period in southern New England, and on a molting area in the St. Lawrence River estuary in Quebec between 2015 and 2016. I used winter movement data to determine winter arrival and departure dates, total length of stay, home ranges, and site fidelity for scoters wintering in southern New England. Scoters spent over half of the annual cycle on the wintering grounds and demonstrated a high degree of inter-annual site fidelity to composite core-use areas. Sizes of individual 50% core-use home ranges were variable (x̅ = 868 km2; range = 32 to 4,220 km2) and individual 95% utilization distributions ranged widely (x̅ = 4,388 km2; range = 272 to 18,235 km2). More than half of all tagged birds occupied two or more discrete core-use areas that were up to 400 km apart. I combined these home range estimates with biotic and abiotic habitat data to calculate resource selection functions to model predicted relative probability of use for White-winged Scoters throughout the southern New England study area. Scoters selected for areas with lower salinity, lower sea surface temperature, higher chlorophyll-a concentrations, and higher hard-bottom substrate probability. Resource selection function models classified 18,649 km2 (23%) of the study area as high probability of use, which included or immediately bordered ~420 km2 of proposed Wind Energy Area lease blocks. Important habitats and key environmental characteristics identified by this study should be carefully considered when siting and developing future offshore wind energy areas. Understanding full annual cycle movements of long-distance migrants is essential for delineating populations, assessing connectivity, evaluating crossover effects between life stages, and informing management strategies for vulnerable or declining species. In a complementary second study, I used the same 52 satellite-tagged female White-winged Scoters to document annual cycle phenology, delineate migration routes, identify primary areas used during winter, stopover, breeding, and molt, and to assess the strength of migratory connectivity and spatial population structure. Most scoters wintered along the Atlantic coast from Nova
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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 | 0.000 |
| 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".