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Patterns of macroparasite aggregation in wildlife host populations
D J Shaw1, B T Grenfell, A P Dobson
1Department of Zoology, University of Cambridge, UK.
Parasitology
|January 9, 1999
Summary
Wildlife host-macroparasite data often fit the negative binomial distribution, indicating high parasite aggregation. Analyzing host subgroups reveals variations in aggregation, crucial for accurate ecological studies.
Area of Science:
- Ecology
- Parasitology
- Biostatistics
Background:
- Macroparasite distributions in wildlife hosts frequently exhibit aggregation.
- The negative binomial distribution is commonly used to model these aggregated patterns.
Purpose of the Study:
- To assess the goodness of fit of the negative binomial distribution to wildlife host-macroparasite systems.
- To investigate the impact of data aggregation on estimates of parasite distribution and aggregation.
Main Methods:
- Analysis of frequency distributions from 49 published wildlife host-macroparasite systems.
- Maximum likelihood estimation to test goodness of fit to the negative binomial distribution.
- Comparison of aggregated (pooled) versus disaggregated (subgroup) host data.
Main Results:
- The negative binomial distribution provided a statistically satisfactory fit for 90% of the datasets.
- High degrees of aggregation (k < 1) were prevalent across most host-parasite systems.
- Analyzing host subgroups revealed significant variations in aggregation within systems, which were masked by pooling data.
Conclusions:
- The negative binomial distribution is a robust model for wildlife host-macroparasite aggregation.
- Pooling host data can obscure important variations in parasite aggregation and overestimate the true degree of aggregation.
- Disaggregating host data by relevant subgroups (sex, age, location, time) is recommended for more accurate ecological insights.