An initial assessment of the sustainability of waterbird harvest in the United Kingdom
Bibliographic record
Abstract
Abstract There is a need to assess the sustainability of wild bird harvest in the United Kingdom (UK), and more widely, across Europe. Yet data on populations and harvest sizes are limited. We used a Demographic Invariant Method (DIM) to estimate Potential Excess Growth (PEG) for populations of UK wintering waterbirds and calculated a Sustainable Harvest Index (SHI) for each. We compared this with population trends and conservation classifications (e.g. Birds of Conservation Concern; BoCC) to assess the sustainability of harvests and the utility of these classifications. Our approach found evidence for potential overharvest of mallard Anas platyrhynchos , Eurasian teal Anas crecca , gadwall Mareca strepera , Canada geese Branta canadensis , greylag geese Anser anser and woodcock Scolopax rusticola . Whether DIM methods predict overharvest is highly dependent on estimates of maximum population growth rates inferring PEG. We found estimates of maximum population growth to be variable across a range of different methods. We found no relationship between SHI and short-term wintering trends or conservation classification under the UK’s BoCC framework. There was however a positive relationship between SHI and long-term wintering trends. Policy Implications : Our results suggest that UK based harvest is unlikely to be a major determinant of population trends for the majority of UK overwintering waterbirds, but harvest rates for some species may exceed that required to maintain stationary population growth. The lack of a relationship between conservation classifications and SHI strongly suggests that such conservation classifications are not an appropriate tool for making decisions about harvest management. Instead, our assessment provides the basis for a framework to make evidence-based decisions on sustainable harvest levels in the face of incomplete data. There is currently no clear policy instrument in the UK to support such a framework via controls on either harvest effort or mortality of waterfowl.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".