Responses of the Hybrid between Sphagneticola trilobata and Sphagneticola calendulacea to Low Temperature and Weak Light Characteristic in South China
Bibliographic record
Abstract
Hybridization between exotic and native species is of great interest to evolutionary biologists and ecologists because it usually shows a quick evolution of species and invasiveness. It has been reported that such hybridization frequently increases the adaptation and aggressiveness of the new hybrids. A hybrid between invasive Sphagneticola trilobata and its native congener S. calendulacea was recently found in subtropical China. S. calendulacea has a significantly higher tolerance to low temperature and weak light stress than S. trilobata, and its range includes both tropical and temperate regions. This study examined how the tolerance of the new hybrid to low temperature and weak light conditions (LTWL), expanded its geographical range. All changes of phenotype, gas exchange parameters, chlorophyll fluorescence parameters, contents of malonaldehyde (MDA) and activity of superoxide dismutase (SOD) and peroxidase (POD) indicated that hybridization slightly catalyzed the tolerance of the hybrid to LTWL condition and the responses of the hybrid were more similar with their invasive parent. The results demonstrate that the current hybrid populations may not expand their geographical distribution ranges in a short period, but the distribution of the backcrossed generations is still uncertain. The threat of the hybrid to its native parent in subtropical region should be concerned.
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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 | 0.001 |
| 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".