ArticleEcology2017
When can we infer mechanism from parasite aggregation? A constraint-based approach to disease ecology.
Article in Ecology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- High-throughput microfluidic real-time PCR as a promising tool in disease ecology.The Journal of animal ecology · 2025Article
- Do fungi look like macroparasites? Quantifying the patterns and mechanisms of aggregation for host-fungal parasite relationships.Proceedings. Biological sciences · 2025Article
- Do fungi look like macroparasites? Quantifying the patterns and mechanisms of aggregation for host-fungal parasite relationships.bioRxiv : the preprint server for biology · 2024Article
- Reconstructing multi-strain pathogen interactions from cross-sectional survey data via statistical network inference.Journal of the Royal Society, Interface · 2023Article
- Article
- Transient disease dynamics across ecological scales.Theoretical ecology · 2021Article
- Measuring aggregation in parasite populations.Journal of the Royal Society, Interface · 2020Article
- Heterogeneity in helminth infections: factors influencing aggregation in a simple host-parasite system.Parasitology · 2020Article
- Article
- Parasite resource manipulation drives bimodal variation in infection duration.Proceedings. Biological sciences · 2019Article
- Biological and statistical processes jointly drive population aggregation: using host-parasite interactions to understand Taylor's power law.Proceedings. Biological sciences · 2017Article
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Authors and funding
3 authors.
Funding
Abstract
Few hosts have many parasites while many hosts have few parasites. This axiom of macroparasite aggregation is so pervasive it is considered a general law in disease ecology, with important implications for the dynamics of host-parasite systems. Because of these dynamical implications, a significant amount of work has explored both the various mechanisms leading to parasite aggregation patterns and how to infer mechanism from these patterns. However, as many disease mechanisms can produce similar aggregation patterns, it is not clear whether aggregation itself provides any additional information about mechanism. Here we apply a "constraint-based" approach developed in macroecology that allows us to explore whether parasite aggregation contains any additional information beyond what is provided by mean parasite load. We tested two constraint-based null models, both of which were constrained on the total number of parasites P and hosts H found in a sample, using data from 842 observed amphibian host-trematode parasite distributions. We found that constraint-based models captured ~85% of the observed variation in host-parasite distributions, suggesting that the constraints P and H contain much of the information about the shape of the host-parasite distribution. However, we also found that extending the constraint-based null models can identify the potential role of known aggregating mechanisms (such as host heterogeneity) and disaggregating mechanisms (such as parasite-induced host mortality) in constraining host-parasite distributions. Thus, by providing robust null models, constraint-based approaches can help guide investigations aimed at detecting biological processes that directly affect parasite aggregation above and beyond those that indirectly affect aggregation through P and H.
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