Community Disturbance and Host-parasite Interactions at the Wildlife-domestic Interface in a Neotropical Biodiversity Hotspot
Bibliographic record
Abstract
Tropical ecosystems worldwide are threatened by land-use change. The resulting increased interaction between wildlife, domestic species, and humans can lead to parasite spillover and emerging diseases that can significantly impact wildlife. Measuring spillover risk presents multiple challenges, including identifying drivers of species interaction, quantifying host densities and overlap, and estimating parasite prevalence. I studied anthropogenic pressures and the associated risk of parasite spillover in the Osa peninsula, an important biodiversity hotspot in southern Costa Rica. In Chapter 1, I analyzed how anthropogenic disturbance, land protection, and habitat quality shape the vertebrate community. In collaboration with multiple institutions, I conducted a region-wide camera-trap survey and analyzed the occurrence of terrestrial mammals and ground birds using a joint species distribution model. Overall disturbance had negative impacts on occupancy of large predators and herbivores. Mesopredators like ocelots (Leopardus pardalis) were only marginally affected by disturbance and could therefore be exposed to parasites of domestic species. In Chapter 2, I used camera trap data, and estimation frameworks for marked and unmarked species, to determine ocelot density, a key determinant of epidemiological dynamics. I found important design incompatibilities between frameworks regarding camera distribution, which should be considered for density comparisons. The estimated density (34 individuals/100 km2 ) suggests a healthy population. However, ocelots frequently use trails, exposing them further to parasites of domestic species, particularly dogs. In Chapter 3, I analyzed the spillover risk of soil transmitted helminths from domestic hosts to wild felids using microscopy, molecular diagnostic, and mathematical modelling tools. I found high prevalence of hookworms (Ancylostoma caninum) in dog scats (74%). I could not identify a related parasite found in feline scat. The hookworm prevalence observed in ocelots (25%), however, was higher than the prediction from a mathematical model (5%), suggesting there is no regular transmission of helminths across species. Human encroachment on natural habitats will continue to represent a risk of emerging disease for vulnerable wildlife, domestic animals, and humans, particularly in highly biodiverse systems like the Osa. Parasite monitoring therefore must become an integral part of conservation studies at the wildlife-domestic interface. These urgent efforts will necessarily require multidisciplinary, local-based approaches.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".