Life on the edge: gastrointestinal parasites from the forest edge and interior primate groups
Bibliographic record
Abstract
Humans are responsible for massive changes to primate habitats, and one unanticipated consequence of these alterations may be changes in host-parasite interactions. Edges are a ubiquitous aspect of human disturbance to forest landscapes. Here we examine how changes associated with the creation of edges in Kibale National Park, Uganda, alter the parasite community that is supported by two species of African colobines: the endangered red colobus (Piliocolobus tephrosceles) and the black-and-white colobus (Colobus guereza). An analysis of 822 fecal samples from edge and forest interior groups revealed no difference in the richness of parasite communities (i.e., the number of parasite species recovered from the host's fecal sample). However, for both species the proportion of individuals with multiple infections was greater in edge than forest interior groups. The prevalence of specific parasites also varied between edge and forest interior groups. Oesophagostomum sp., a potentially deleterious parasite, was 7.4 times more prevalent in red colobus on the edge than in those in the forest interior, and Entamoeba coli was four times more prevalent in red colobus on the edge than in animals from the forest interior. Environmental contamination with parasites (measured as parasite eggs/gm feces) by red colobus from the edge and forest interior differed in a similar fashion to prevalence for red colobus, but it did not differ for black-and-white colobus. For example, egg counts of Oesophagostomum sp. were 10 times higher in red colobus from the edge than in those from the interior. The less severe infections in the black-and-white colobus relative to the red colobus may reflect the fact that black-and-white colobus raid agricultural crops while red colobus do not. This nutritional gain may facilitate a more effective immune response to parasites by the black-and-white colobus. The fact that animals on the edge are likely not nutritionally stressed raises an intriguing question as to what facilitates the elevated infections in edge animals. We speculate that interactions with humans may be linked to the observed patterns of infections, and hence that understanding the ecology of infectious diseases in nonhuman primates is of paramount importance for conservation and potentially for human-health planning.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".