Reproductive Interference Alters Species Coexistence in Nematodes due to Asymmetric Sperm‐Induced Harm
Bibliographic record
Abstract
Species coexistence is shaped by a range of biotic and abiotic factors. Beyond predation, parasitism and competition, one species may interfere with another's reproduction to induce sexual exclusion from a habitat. Here, we test for reproductive interference from inter-species mating between sympatric nematodes Caenorhabditis macrosperma and C. nouraguensis. Higher intrinsic population growth of C. nouraguensis arises from greater reproductive output by both sexes, predicting it to be superior in resource competition. Mate discrimination between species is incomplete, however, with inter-species mating errors reducing lifespan and reproductive fitness of female C. nouraguensis only. These asymmetric costs arise within hours, due to ectopic migration of C. macrosperma's giant sperm cells. We modelled the population dynamic impacts of reproductive interference, then confirmed rapid sexual exclusion in mixed-species communities with multi-generation experiments. These findings demonstrate the profound ecological implications of reproductive interference for demographic parameters and species coexistence through a cell-mediated mechanism of inter-species harm.
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 | 0.000 | 0.001 |
| 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".