Evaluation of the Copper River Delta Dusky Canada Goose Survey and the Pacific Flyway's Management Index
Bibliographic record
Abstract
The Copper River Delta (CRD) in south-central Alaska is the primary breeding area for dusky Canada geese (Branta canadensis occidentalis). The Alaska Department of Fish and Game (ADFG), United States Forest Service (USFS), and United States Fish and Wildlife Service (USFWS) conduct breeding-ground surveys to inform the Pacific Flyway Council harvest management decisions and regulations. The current management index (described in detail below) uses aerial survey counts corrected for detection by the long-term average ratio of aerial counts to ground-based nest counts. Because of the 1964 earthquake that resulted in uplift and subsequent vegetation growth, the aerial detection of geese has been thought to decrease through time and the use of a constant correction factor is suspect. During the summer of 2020, personnel from the 3 agencies met to discuss the appropriateness of the index as it was currently calculated. The greatest concern identified was in the use of a constant detection correction derived from sparse historic data, and this report is an attempt to evaluate the components of the detection correction constant, as well as the management index in general, and provide potential alternatives going forward. Because the detection correction involves a ratio of the ground-based nest estimates to aerial-observed indicated pairs (hereafter 'ratio' or 'ground-to-air ratio'), change in the ratio could be due to change in either the numerator or denominator. Therefore, we evaluated methods and any change in methods or protocol associated with all survey components. Our goal is to evaluate the current design of surveys, the calculation of the management index, and to assess change in various components of the index, not to provide detailed recommendations for re-design of a survey. Such a re-design should take place in a separate effort after this evaluation, and after a general approach, perhaps different than the current one, is decided upon by the various stakeholders. Previous attempts at examining the ratio and change in ground-to-air ratio was limited to simple linear regression between air and ground point estimates calculated at the scale of each nest plot strata (Hodges 2007). This made the assumption that the relationship is linear, that the nest strata are the appropriate scale to calculate the ratio, that all point estimates are equally estimated, and a mean ratio across time is appropriate for calculating a correction factor. Because there is now more data available and more statistical techniques available to estimate the relationship between nests and aerially-observed geese, we also estimated the ratio at various scales and using different techniques to see if this leads to different conclusions. We were primarily concerned with annual variation in the ratio and distinguishing true process variation in this ratio from sampling variance (statistical noise). Current treatment of the ratio ignores annual (process) variation in the ratio, and we feel strongly that this is not appropriate if there is evidence for annual variation. Because annual variation in the ratio has never been estimated, we attempt to estimate this and apply it to the calculation of the management index.
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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) | 0.016 | 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".