Increasing Temperature Facilitates Polyp Spreading and Medusa Appearance of the Invasive Hydrozoan Craspedacusta sowerbii
Bibliographic record
Abstract
The freshwater jellyfish Craspedacusta sowerbii is among the most widespread invasive species, observed across a wide temperature range. The aim of this study is to analyze the polyp and medusa stages response to different temperatures by using (i) an experimental study on the polyp colony growth at 19 and 29 °C, and (ii) prediction of the Thermal Habitat Suitability (THS) based on the thermal tolerance of the medusa stage. The total number of polyps and colonies was greater at high temperature. At 19 °C, colonies with 1 to 5 polyps were present, with colonies of 1 to 3 polyps numerically dominating. At 29 °C, colonies were 80% composed of 1- to 2-polyps. Based on the published medusa pulsation rhythm data, a Thermal Performance Curve (TPC) regression was performed and used to monthly predict the THS for current and future (2050 and 2100) scenarios. The southern hemisphere offered optimal conditions (THS > 0.6) year-round. In the northern hemisphere, the optimum period was predicted to be between June and September. The future THS were considerably larger than at present with an increase in optimal THS at higher latitudes (up to 60° N). The combination of experimental and modeling approaches allows to identify the optimal thermal conditions of the polyp and medusa stages and to predict their invasive capacities.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".