Abundance, not diversity, of host beetle communities determines abundance and diversity of parasitoids in deadwood
Bibliographic record
Abstract
Most parasites and parasitoids are adapted to overcome defense mechanisms of their specific hosts and hence colonize a narrow range of host species. Accordingly, an increase in host functional or phylogenetic dissimilarity is expected to increase the species diversity of parasitoids. However, the local diversity of parasitoids may be driven by the accessibility and detectability of hosts, both increasing with increasing host abundance. Yet, the relative importance of these two mechanisms remains unclear. We parallelly reared communities of saproxylic beetle as potential hosts and associated parasitoid Hymenoptera from experimentally felled trees. The dissimilarity of beetle communities was inferred from distances in seven functional traits and from their evolutionary ancestry. We tested the effect of host abundance, species richness, functional, and phylogenetic dissimilarities on the abundance, species richness, and Shannon diversity of parasitoids. Our results showed an increase of abundance, species richness, and Shannon diversity of parasitoids with increasing beetle abundance. Additionally, abundance of parasitoids increased with increasing species richness of beetles. However, functional and phylogenetic dissimilarity showed no effect on the diversity of parasitoids. Our results suggest that the local diversity of parasitoids, of ephemeral and hidden resources like saproxylic beetles, is highest when resources are abundant and thereby detectable and accessible. Hence, in some cases, resources do not need to be diverse to promote parasitoid diversity.
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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 | 0.001 | 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".