BODY COMPOSITION, MOVEMENT PHENOLOGY AND HABITAT USE OF COMMON EIDER ALONG THE SOUTHERN NEW ENGLAND COAST
Bibliographic record
Abstract
The nearshore and offshore waters of southern New England provide important winter habitat for many sea duck species including common eiders (Somateria mollissima). Sea ducks that inhabit these waters must contend with global climate change, disease, and anthropogenic disturbance including proposed offshore wind energy development; however, evaluating these potential impacts on sea ducks, in general, and eiders in particular is difficult because knowledge of their ecology during winter is limited. I conducted the first validation of a non-lethal method for estimating body composition (deuterium dilution) of eiders and then applied this method to assess changes in body composition throughout the winter of 2011-12. I constructed models using deuterium-estimated body water, structural measurements, body mass and sex that estimated wet lean mass with 2.0 % relative error, and fat mass with 20.2 % relative error. Both male and female eiders were heavier and had more fat in late winter compared to early winter, whereas wet lean mass remained constant for males and declined over time for females from early to late winter. Based on model accuracy, the deuterium dilution method provided a viable, non-lethal approach for estimating body composition of eider. Biologists interested in assessing the potential impacts of offshore wind energy development and exposure to diseases such as Wellfleet Bay Virus on body composition of eider could use the method to assess changes in body condition. In a complimentary second study, I used satellite telemetry to track the movements of 26 adult female common eiders from November 2011 to July 2013 to delineate the migratory phenology, home ranges, habitat use and site fidelity of eiders that were initially captured during early-winter in southern New England. Eiders exhibited high fidelity to the southern New England wintering area (19 of 23 birds returned to the same area between years), where birds spent approximately 38% of their annual cycle. Birds were relatively sedentary during winter with home ranges that tended to be smaller than other species of seaducks (x -50% kernel core use areas = 38.5 km2 and x -95% kernel utilization distributions = 199.3 km2). Satellite-tagged eiders wintering in southern New England migrated to 4 summer areas in Maine, USA, Nova Scotia, the St. Lawrence Estuary and the Gulf of St. Lawrence, Canada. During winter, eiders preferred shallow waters that were closer to shore, and that had relatively fine-sediment substrate and a higher probability of hard bottom. I used this information to develop a spatially-explicit model that predicted that approximately 13.1% of this 6,212 km2 study area had a medium-high to high relative probability of use by eiders, and identified relatively high-use areas. Managers and policy makers could use this information to evaluate certain siting scenarios for offshore wind energy development so that areas with a high probability of use by eiders are avoided, thus minimizing the chance of negative impacts on the species.
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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 | 0.000 |
| 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 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".