A conceptual model of community dynamics during the transport stage of the invasion process: a case study of ships’ ballast
Bibliographic record
Abstract
Abstract Aim After J. L. Lockwood, P. Cassey and T. Blackburn (2009, Diversity and Distributions , 15 , 904–910) first described a theoretical relationship between propagule pressure and colonization pressure, two empirical studies demonstrated that the transport stage of the invasion process can profoundly influence the strength of the relationship among multiple events, as well as predictions of introduction risk. However, studies exploring dynamics of transported communities are rare, as repeated‐measures sampling during transportation by any vector is logistically difficult. We constructed a conceptual model of community dynamics during transportation and supported it by empirical data for propagule pressure and colonization pressure of plankton. Location Global. Methods A conceptual model of community dynamics was developed based on lognormal species abundance distribution and the simulation model of J. L. Lockwood, P. Cassey and T. Blackburn (2009, Diversity and Distributions , 15 , 904–910). We considered four cases: case ‘A’ – no reduction in propagule nor colonization pressure; case ‘B’ – strong reduction in propagule and mild reduction in colonization pressure; case ‘C’ – mild reduction in propagule and strong reduction in colonization pressure; and case ‘D’ – strong reduction in both propagule and colonization pressures. Results The cases ‘B’, ‘C’ and ‘D’ were supported by empirical data for invertebrates, dinoflagellates and diatoms from ships’ ballast tanks, respectively. Propagule pressure of invertebrates, dinoflagellates and diatoms decreased 99.95%, 80% and 94% in 25 days, respectively, while colonization pressure decreased 34%, 57% and 64%. Main conclusions Transport affects both propagule pressure and colonization pressure of taxa, with the magnitude of change dependent on length of transport and taxon‐specific survival and reproduction. Our model demonstrates that introduction risk varies substantially across and within taxa depending on the occurrence and severity of selection pressures during transportation which serve to change species abundance distributions.
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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 | 0.001 | 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) | 0.000 | 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".