Research biases create overrepresented “poster children” of marine invasion ecology
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
Abstract Nonnative marine species are increasingly recognized as a threat to the world's oceans, yet are poorly understood relative to their terrestrial and freshwater counterparts. Here, we conducted a systematic review of 2,203 research articles on nonnative marine animals to determine whether the current literature reflects the known diversity of marine invaders, how much we know about these species, and how frequently their impacts are measured. We found that only 39% of nonnative animals listed in the World Register of Introduced Marine Species appeared in the peer‐reviewed English literature. Of those, fewer than half were the subject of more than one study. There is currently little focus on the consequences of marine introductions: only 9.9% of studies quantified the impact of nonnative species. Finally, our knowledge of nonnative marine species is heavily limited by strong taxonomic biases consistent across all phyla, resulting in one or two disproportionately well‐studied representatives for each phylum, which we refer to as the “poster children” of invasion. These gaps in the literature make it difficult to effectively triage the most detrimental invasive species for management and illustrate the challenges in achieving the global biodiversity goals of preventing and managing the introduction and establishment of invasive species.
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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.020 | 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 it