Predicting shifts in parasite distribution with climate change: a multitrophic level approach
Bibliographic record
Abstract
Climate change likely will lead to increasingly favourable environmental conditions for many parasites. However, predictions regarding parasitism's impacts often fail to account for the likely variability in host distribution and how this may alter parasite occurrence. Here, we investigate potential distributional shifts in the meningeal worm, Parelaphostrongylosis tenuis, a protostrongylid nematode commonly found in white-tailed deer in North America, whose life cycle also involves a free-living stage and a gastropod intermediate host. We modelled the distribution of the hosts and free-living larva as a complete assemblage to assess whether a complex trophic system will lead to an overall increase in parasite distribution with climate change, or whether divergent environmental niches may promote an ecological mismatch. Using an ensemble approach to climate modelling under two different carbon emission scenarios, we show that whereas the overall trend is for an increase in niche breadth for each species, mismatches arise in habitat suitability of the free-living larva vs. the definitive and intermediate hosts. By incorporating these projected mismatches into a combined model, we project a shift in parasite distribution accounting for all steps in the transmission cycle, and identify that overall habitat suitability of the parasite will decline in the Great Plains and southeastern USA, but will increase in the Boreal Forest ecoregion, particularly in Alberta. These results have important implications for wildlife conservation and management due to the known pathogenicity of parelaphostrongylosis to alternate hosts including moose, caribou and elk. Our results suggest that disease risk forecasts which fail to consider biotic interactions may be overly simplistic, and that accounting for each of the parasite's life stages is key to refining predicted responses to climate change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".