Sex-Specific Enemy Amplification, Not Release, in Introduced House Sparrows
Bibliographic record
Abstract
Biological invasions disrupt ecosystems, economies, and disease transmission pathways, yet the mechanisms underlying invasion success remain debated. The Enemy Release Hypothesis (ERH) posits that non-native host populations thrive due to reduced pathogen pressure. While widely tested in plants and in vector-borne diseases, ERH remains understudied for enteric pathogens, which have generalist host ranges and are transmitted via faecal-oral and environmental routes. We examined the prevalence of two enteric bacteria, avian pathogenic Escherichia coli (APEC) and Salmonella enterica, in native and non-native house sparrows (Passer domesticus) from eight global populations (n = 200). We tested whether population status, sex, and urbanization influenced infection risk and examined effects on condition. Contrary to ERH, pathogen prevalence was not lower in non-native populations. Instead, we detected sex-specific amplification of infections: females from non-native populations had significantly higher odds of APEC infection than native females. Urbanization also disproportionately increased infection risk in females, highlighting sex-specific vulnerability. Infection had no measurable impact on condition, suggesting house sparrows may tolerate enteric infections, although differential mortality cannot be ruled out. These findings challenge the generality of ERH and suggest that successful invaders like house sparrows may persist by tolerating, rather than avoiding, pathogen exposure.
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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".