The cost of travel: How dispersal ability limits local adaptation in host–parasite interactions
Bibliographic record
Abstract
Classical theory suggests that parasites will exhibit higher fitness in sympatric relative to allopatric host populations (local adaptation). However, evidence for local adaptation in natural host-parasite systems is often equivocal, emphasizing the need for infection experiments conducted over realistic geographic scales and comparisons among species with varied life history traits. Here, we used infection experiments to test how two trematode (flatworm) species (Paralechriorchis syntomentera and Ribeiroia ondatrae) with differing dispersal abilities varied in the strength of local adaptation to their amphibian hosts. Both parasites have complex life cycles involving sequential transmission among aquatic snails, larval amphibians and vertebrate definitive hosts that control dispersal across the landscape. By experimentally pairing 26 host-by-parasite population infection combinations from across the western USA with analyses of host and parasite spatial genetic structure, we found that increasing geographic distance-and corresponding increases in host population genetic distance-reduced infection success for P. syntomentera, which is dispersed by snake definitive hosts. For the avian-dispersed R. ondatrae, in contrast, the geographic distance between the parasite and host populations had no influence on infection success. Differences in local adaptation corresponded to parasite genetic structure; although populations of P. syntomentera exhibited ~10% mtDNA sequence divergence, those of R. ondatrae were nearly identical (<0.5%), even across a 900 km range. Taken together, these results offer empirical evidence that high levels of dispersal can limit opportunities for parasites to adapt to local host populations.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".