Invasive alien birds in Denmark
Bibliographic record
Abstract
Avian Introduced Alien Species (IAS) constitute a threat to the integrity of native biodiversity, the economy and human health, so here we briefly review some of the problems posed by such species around the world in relation to such bird species in Denmark. A new European Union Regulation on Invasive Alien Species implemented in January 2015 establishes a framework for actions to combat alien species, which requires Member States to prevent the spread of alien species, provide early warning and rapid responses to their presence and management of established alien species where they occur. We show the importance of mechanisms such as DOF’s (Dansk Ornitologisk Forening, BirdLife Denmark) Atlas project, Common Bird Census (breeding and wintering species) and DOFbasen to contribute data on the current geographical and numerical distribution of the few serious alien avian species already present in Denmark. We review the status, abundance and distribution of seven critical IAS that do, or have, occurred in Denmark in the last 10 years and conclude that none of these pose a major threat as things stand at the present, although breeding Egyptian Geese <em>Alopochen aegyptiaca</em> and Canada Geese <em>Branta canadensis</em> potentially give cause for future concern. We underline the need for continued surveillance of all avian IAS through data collection via DOF’s monitoring programmes and Aarhus University’s mid-winter waterbird census, hunting bag and wing surveys. These programmes are essential if we are to continue to effectively monitor the extent and nature of the problems constituted by IAS in support of the Danish Nature Agency in their direct management of alien species problems in this country.
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 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) | 0.000 | 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".