Unveiling the hidden economic toll of biological invasions in the European Union
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Biological invasions threaten the functioning of ecosystems, biodiversity, and human well-being by degrading ecosystem services and eliciting massive economic costs. The European Union has historically been a hub for cultural development and global trade, and thus, has extensive opportunities for the introduction and spread of alien species. While reported costs of biological invasions to some member states have been recently assessed, ongoing knowledge gaps in taxonomic and spatio-temporal data suggest that these costs were considerably underestimated. Results: (v4.1)-the most comprehensive database on the costs of biological invasions-to assess the magnitude of this underestimation within the European Union via projections of current and future invasion costs. We used macroeconomic scaling and temporal modelling approaches to project available cost information over gaps in taxa, space, and time, thereby producing a more complete estimate for the European Union economy. We identified that only 259 out of 13,331 (~ 1%) known invasive alien species have reported costs in the European Union. Using a conservative subset of highly reliable, observed, country-level cost entries from 49 species (totalling US$4.7 billion; 2017 value), combined with the establishment data of alien species within European Union member states, we projected unreported cost data for all member states. Conclusions: Our corrected estimate of observed costs was potentially 501% higher (US$28.0 billion) than currently recorded. Using future projections of current estimates, we also identified a substantial increase in costs and costly species (US$148.2 billion) by 2040. We urge that cost reporting be improved to clarify the economic impacts of greatest concern, concomitant with coordinated international action to prevent and mitigate the impacts of invasive alien species in the European Union and globally. Supplementary Information: The online version contains supplementary material available at 10.1186/s12302-023-00750-3.
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.
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 | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.005 |
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 it