Estimating parasite host range

Abstract

Estimating the number of host species that a parasite can infect (i.e. host range) provides key insights into the evolution of host specialism and is a central concept in disease ecology. Host range is rarely estimated in real systems, however, because variation in species relative abundance and the detection of rare species makes it challenging to confidently estimate host range. We applied a non-parametric richness indicator to estimate host range in simulated and empirical data, allowing us to assess the influence of sampling heterogeneity and data completeness. After validating our method on simulated data, we estimated parasite host range for a sparsely sampled global parasite occurrence database (Global Mammal Parasite Database) and a repeatedly sampled set of parasites of small mammals from New Mexico (Sevilleta Long Term Ecological Research Program). Estimation accuracy varied strongly with parasite taxonomy, number of parasite occurrence records, and the shape of host species-abundance distribution (i.e. the dominance and rareness of species in the host community). Our findings suggest that between 20% and 40% of parasite host ranges are currently unknown, highlighting a major gap in our understanding of parasite specificity, host-parasite network structure, and parasite burdens.

Keywords: Global Mammal Parasite Database; Sevilleta LTER; abundance-based coverage estimator; host breadth; host specificity; species diversity estimation.

Figure 1.

Conceptual figure depicting the simulation of host–parasite sampling data, where colours represent the number of times a given host–parasite interaction was observed (cooler colours correspond to larger values). For each parasite species P (rows), a subset of host species H (columns) were selected at random to form the host community and corresponding host range (h* values for each P row). Parasite occurrences were then determined by sampling the susceptible host set based on host species relative abundance (top barplot), where species relative abundance is determined initially by drawing host species occurrences from the log-normal distribution. This serves to control the evenness of the host community, which changes the distribution of host relative abundance in the upper panel. (Online version in colour.)

Figure 2.

Host range estimation accuracy, measured as mean absolute per cent error (MAPE; indicated by colour gradient), as a function of the number of parasite occurrences (m; y-axis) and true parasite host breadth (h; x-axis). Panels correspond to the fraction of the parasite occurrence data used for host range estimation. Larger MAPE values (hotter colours) indicate larger error. (Online version in colour.)

Figure 3.

The distribution of parasite species of small mammals in the Sevilleta LTER, and for primates, ungulates, and carnivores in the Global Mammal Parasite Database along axes of the number of parasite occurrences (m; y-axis) and true parasite host breadth (h*; x-axis). The range of m and h* values corresponds directly to the range of conditions of the simulated data (figure 2). The colour legend corresponds to the log-transformed number of parasite species for a given combination of m and h* values. (Online version in colour.)

Figure 4.

Absolute PE as a function of data source and parasite type. Values closer to 0 correspond to more accurate host range prediction. Error (mean±2 s.e.) tended to be larger for parasites in the Global Mammal Parasite Database. Further, error rates varied based on parasite taxonomy, with viruses and protozoans tending to have larger error than bacteria and helminth parasites. (Online version in colour.)

Figure 5.

Estimates for the percentage of unknown hosts (mean±2 s.e.) suggest that many parasites, even those in sparsely populated global databases, may capture the susceptible host set. However, many parasite species had large estimated fractions of unknown hosts, suggesting that the susceptible host set may include many more currently undocumented host species. (Online version in colour.)