Potential impacts and priority areas of research of the on-going invasion of green crabs along the SW Atlantic
Bibliographic record
Abstract
The European green crab ( Carcinus maenas) is one of the most extensively studied decapod species worldwide, and it currently inhabits every continent except Antarctica. Its effects are observed across various spatio-temporal scales, impacting a wide range of taxa and environments. While extensive research has been conducted in the Northern Hemisphere, populations in the Southern Hemisphere (e.g., Argentina, Australia, and South Africa) have not been thoroughly investigated. This study has three main goals: (1) summarise and contextualise the invasion history of green crabs in the Southwest Atlantic since their initial detection in 2000, (2) present nine case studies identifying the potential ecological and economic impacts of green crabs on coastal ecosystems, and to highlight priority research areas, and (3) discuss appropriate management actions in response to the species' rapid spread in the region. Our findings suggest that green crabs are likely to impact foundation species along rocky shores, alter the physical characteristics of soft-bottom environments, and affect infaunal organisms in sandy shores. Most of these impacts are either occurring or expected to occur in numerous marine protected areas. We also examine green crab interactions with other key species, highlighting its dual role as both an invasive predator and prey for native species, thus serving as a novel food resource. Furthermore, we consider their effects on commercially important species, tourism, and implications for threatened native species. Finally, we recommend prioritising prevention and rapid response strategies for managing green crab invasions, emphasising the importance of early detection and prompt action to address new incursions.
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 | 0.002 | 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 | 0.000 | 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 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".