Abundance and distribution of birds from comprehensive surveys of the Canadian Arctic, 1994–2018
Bibliographic record
Abstract
Abstract Abundance and distribution are critical metrics of population status and foundational information for conservation. However, even these basic metrics have been difficult to obtain for birds in the Canadian Arctic, where costs are high and access is difficult. Here, we present estimates of population size and distribution for 24 species of shorebirds and 37 other species of birds across the Canadian Arctic, using ground-based surveys of 2,528 plots surveyed between 1994 and 2018. Plot locations were selected by stratified random sampling, within wet, moist, or dry habitat categories defined based on satellite remote sensing. Double-sampling was used to determine detection rates and correct the estimates to reflect birds breeding within the plots. Because this was the first large-scale survey effort across Arctic Canada, many of the results provide new insights with conservation implications. Nearly all estimated population sizes for shorebird species exceed prior estimates, many by several fold. The 6 most abundant shorebird species were Calidris pusilla (Semipalmated Sandpiper), Phalaropus fulicarius (Red Phalarope), Calidris fuscicollis (White-rumped Sandpiper), Calidris melanotos (Pectoral Sandpiper), Pluvialis dominica (American Golden-Plover), and Phalaropus lobatus (Red-necked Phalarope), all with estimated population sizes exceeding 3 million (CVs for these species ranged from 0.12 to 0.24). Although shorebird densities were much higher in wet and moist habitats, the large areal extent of dry habitats meant that 42% of all shorebirds were estimated to occupy these dry areas, previously considered to be of marginal importance. The estimates of abundance and distribution for the 37 non-shorebird species are, in many cases, the first-ever estimates of population size from the Arctic breeding grounds. This new understanding of population sizes will have important implications for several current conservation programs, such as those where areas are identified as key habitat on the basis of the percentage of populations using them.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".