Host-enemy interactions provide limited biotic resistance for a range-expanding species via reduced apparent competition
Bibliographic record
Abstract
Abstract As species ranges shift in response to anthropogenic change, they lose coevolved or coadapted interactions and gain novel ones in recipient communities. Range-expanding species may lose or experience weak antagonistic interactions with competitors and enemies, and traits of interacting species will determine the strength of interactions. We leveraged a poleward range expansion of an oak gall wasp that co-occurs on its host plant with other gall wasp species and interacts with shared natural enemies (largely parasitoid wasps). We created quantitative host-parasitoid interaction networks by sampling galls on 400 trees. We compared network structure and function and traits of hosts and parasitoids in the native and expanded range. Interaction networks were less diverse in the expanded range, with low complementarity of parasitoid assemblages among hosts. While whole networks were more generalized in the expanded range, interactions with the range-expanding species were more specialized. This was not due to a loss of specialist enemies but weak apparent competition by shared generalist enemies. Phenological divergence of enemy assemblages attacking the novel and co-occurring hosts was greater in the expanded range that may contribute to weak apparent competition. Given the rate and extent of anthropogenic-driven range expansions, it is pressing to uncover how complex biotic interactions are reassembled.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".