Species Abundance Distribution of Ectoparasites on Norway Rats (Rattus norvegicus) from a Localized Area in Southwest China.
Bibliographic record
Abstract
BACKGROUND: The species of ectoparasites that live on a specific host in a geographical region form an ectoparasite community. Species abundance distributions describe the number of individuals observed for each different species that is encountered within a community. Based on properties of the species abundance distribution, the expected total number of species present in the community can be estimated. METHODS: Preston's lognormal distribution model was used to fit the expected species abundance distribution curve. Using the expected species abundance distribution curve, we estimated the total number of expected parasite species present and the amount of species that were likely missed by our sampling in the field. RESULTS: In total, 8040 ectoparasites (fleas, sucking lice, gamasid mites and chigger mites) were collected from 431 Norway rats (Rattus norvegicus) from a localized area in southwest China. These ectoparasites were identified to be 47 species from 26 genera in 10 families. The majority of ectoparasite species were chigger mites (family Trombiculidae) while the majority of individuals were sucking lice in the family Polyplacidae. The expected species abundance distribution curve demonstrated the classic pattern that the majority of ectoparasite species were rare and that there were a few common species. The total expected number of ectoparasite species on R. norvegicus was estimated to be 85 species, and 38 species were likely missed by our sampling in the field. CONCLUSIONS: Norway rats harbor a large suite of ectoparasites. Future field investigations should sample large numbers of host individuals to assess ectoparasite 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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".