Cascading Effects of Climate Change: Do Hurricane‐damaged Forests Increase Risk of Exposure to Parasites?
Bibliographic record
Abstract
Abstract Increased parasitism in animals in disturbed habitats is often understood to be the result of increased disease susceptibility due to low food availability resulting in nutritionally stressed and immunocompromised individuals. Such habitat change, however, might also lead to increased exposure to disease. In this article, we test measures of susceptibility and exposure to explain the prevalence and intensity of directly and indirectly transmitted helminths in black howler monkeys (Alouatta pigra) following a hurricane in Belize. None of these parasites were predicted by direct measures of susceptibility (as measured by fruit consumption and fecal cortisol levels). Rather, directly transmitted parasites (Trichurissp. and strongylid type eggs.) were predicted by host density and group size, both measures of exposure. Similarly, only the consumption ofCecropia peltata, a fast growing pioneer that has a mutualistic relationship with ants predicted levels of the indirectly transmitted trematodeControrchisspp., also suggesting exposure.Cecropia peltataalso increased in density post‐hurricane, was high in digestible protein, sugar, and salt and eaten by monkeys more frequently than predicted based on distribution. These data suggest that in this hurricane‐damaged forest the ingestion of this abundant and nutritious pioneer species increased exposure of the monkeys toControrchisthrough ingestion of ant intermediate hosts. These results may point to a pattern true of pioneer species in general, leaving animals in disturbed forests with higher levels of parasitism as a result of changes to forest structure. As severe weather events are expected to increase, this suggests a cascading effect of climate change on ecosystem interactions and disease ecology.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".