Gimme shelter – the relative sensitivity of parasitic nematodes with direct and indirect life cycles to climate change
Bibliographic record
Abstract
Climate change is expected to alter the dynamics of host-parasite systems globally. One key element in developing predictive models for these impacts is the life cycle of the parasite. It is, for example, commonly assumed that parasites with an indirect life cycle would be more sensitive to changing environmental conditions than parasites with a direct life cycle due to the greater chance that at least one of their obligate host species will go extinct. Here, we challenge this notion by contrasting parasitic nematodes with a direct life cycle against those with an indirect life cycle. Specifically, we suggest that behavioral thermoregulation by the intermediate host may buffer the larvae of indirectly transmitted parasites against temperature extremes, and hence climate warming. We term this the 'shelter effect'. Formalizing each life cycle in a comprehensive model reveals a fitness advantage for the direct life cycle over the indirect life cycle at low temperatures, but the shelter effect reverses this advantage at high temperatures. When examined for seasonal environments, the models suggest that climate warming may in some regions create a temporal niche in mid-summer that excludes parasites with a direct life cycle, but allows parasites with an indirect life cycle to persist. These patterns are amplified if parasite larvae are able to manipulate their intermediate host to increase ingestion probability by definite hosts. Furthermore, our results suggest that exploiting the benefits of host sheltering may have aided the evolution of indirect life cycles. Our modeling framework utilizes the Metabolic Theory of Ecology to synthesize the complexities of host behavioral thermoregulation and its impacts on various temperature-dependent parasite life history components in a single measure of fitness, R0 . It allows quantitative predictions of climate change impacts, and is easily generalized to many host-parasite systems.
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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 | 0.000 |
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 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".