Range expansion by invasive marine algae: rates and patterns of spread at a regional scale
Bibliographic record
Abstract
Abstract Aim Introduced macroalgae are widespread in the world’s oceans and, despite increasing awareness and attempts to limit the phenomenon, the number of species introductions in coastal waters has increased exponentially over time. Little is known about the rates and mechanisms of spread, even among species that have received the most attention. We compare patterns of range expansion for nine species of invasive algae across eight geographic regions. Location World‐wide. Methods We compiled records of introduced algae from the scientific literature, herbaria, and by contacting experts to reconstruct chronologies for 22 algal invasions. These were used to map patterns of spread at a regional scale (thousands of km). Results Range size tended to increase linearly with time, often after an initial lag. Range expansion occurred at rates of tens to hundreds of kilometres per year, often with large infrequent increases. Rates of range expansion differed significantly between species within the same region, and between regions for the same species. Main conclusions Our results suggest that anthropogenic vectors likely play a key role in the spread of introduced macroalgae at a regional scale, although natural long‐distance dispersal also may be important for some species. The lack of consistency in the rates within individual species and regions suggests that multiple interacting factors (e.g. algal traits, characteristics of invaded communities, environmental conditions and anthropogenic activities) determine where propagules of introduced algae are delivered and whether they become established.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".