Quantifying the impact of disease on threatened species
Hamish McCallum
Pacific Conservation Biology
1(2) 107 - 117
Published: 1994
Abstract
Determining whether a disease or parasite is having a substantial impact on a population of a threatened species is not straightforward. Highly pathogenic parasites are not those which have the greatest influence on hosts, and diseases present at high prevalence are not likely to have a major effect on the host population. I develop simple mathematical models which show that a microparasitic disease such as a viral or bacterial disease will have the greatest impact on its host if it prevents host reproduction, but does not affect host mortality. If infected hosts can still reproduce, intermediate levels of pathogenicity have the greatest impact on hosts. Macroparasites such as helminths likewise have maximum impact on hosts at intermediate pathogenicity. The impact of a helminth on its host population is, however, determined by a complex interplay between pathogenicity per parasite and the nature of the host response to infection. For example, in the absence of density-dependent constraints on parasites within individual hosts, the smaller the impact per parasite on the host, the greater the impact of the parasitic infection on the overall population. Several recommendations can be made to wildlife managers who detect a disease or parasite and wish to determine its impact on a population of a threatened species. There is no entirely satisfactory alternative to experimental manipulation. Treating part of a population and comparing suvivorship or fecundity with controls is the only way to confirm the impact of a disease on a free-ranging population. Such an approach is impractical with every potential pathogen in a population. Some idea as to which pathogens may be of significance to the population can be gained from comparison of disease prevalence or parasite burden between dead and dying hosts and the overall population. Overall high prevalence or high pathogenicity are not good indicators on their own.https://doi.org/10.1071/PC940107
© CSIRO 1994