Evaluating noninvasive methods for estimating cestode prevalence in a wild carnivore population

Abstract

Helminth infections are cryptic and can be difficult to study in wildlife species. Helminth research in wildlife hosts has historically required invasive animal handling and necropsy, while results from noninvasive parasite research, like scat analysis, may not be possible at the helminth species or individual host levels. To increase the utility of noninvasive sampling, individual hosts can be identified by applying molecular methods. This allows for longitudinal sampling of known hosts and can be paired with individual-level covariates. Here we evaluate a combination of methods and existing long-term monitoring data to identify patterns of cestode infections in gray wolves in Yellowstone National Park. Our goals were: (1) Identify the species and apparent prevalence of cestodes infecting Yellowstone wolves; (2) Assess the relationships between wolf biological and social characteristics and cestode infections; (3) Examine how wolf samples were affected by environmental conditions with respect to the success of individual genotyping. We collected over 200 wolf scats from 2018-2020 and conducted laboratory analyses including individual wolf genotyping, sex identification, cestode identification, and fecal glucocorticoid measurements. Wolf genotyping success rate was 45%, which was higher in the winter but decreased with higher precipitation and as more time elapsed between scat deposit and collection. One cestode species was detected in 28% of all fecal samples, and 38% of known individuals. The most common infection was Echinococcus granulosus sensu lato (primarily E. canadensis). Adult wolves had 4x greater odds of having a cestode infection than pups, as well as wolves sampled in the winter. Our methods provide an alternative approach to estimate cestode prevalence and to linking parasites to known individuals in a wild host system, but may be most useful when employed in existing study systems and when field collections are designed to minimize the time between fecal deposition and collection.

Fig 1. Flow diagram of our methods for analyzing wolf scats.

Scats were collected in the field (left), and then processed in three ways: (A) wolf DNA was extracted, genotyped based on microsatellites, and sex was identified; (B) cestode DNA was extracted and genotyped to species; and (C) metabolites of fecal glucocorticoids (molecule shown) were quantified, resulting in a measure of stress. Scat analyses were then matched (right) to known collared wolves, who were monitored throughout their lives, or uncollared wolves. Photo credit: Ellen E. Brandell (wolf scat, left), Jort Vanderveen (collared wolf, right).

Fig 2

Proportion of cestode-infected (red) and uninfected (blue) wolves stratified by (A) sex (Female/Male), (B) age class, (C) season, (D) breeding status (0 = non-breeder, 1 = breeder), (E) coat color (Black/Gray), (F) canine distemper virus exposure (Negative/Positive), (G) N. caninum infection (Negative/Positive), and (H) T. gondii infection (Negative/Positive). Stars * and ** denote p < 0.10 and p<0.05 using Fisher’s Exact Test; sample sizes are displayed above columns.

Fig 3. Coefficient estimates for the cestode model (log-odds ratios; points).

Error lines represent 50% (thick) and 95% (thin) confidence intervals. For categorical variables, SEASON winter is with reference to summer, AGE CLASS pup to adult, and SEX male to female.

Fig 4

(A) Proportion of scats successfully genotyped when collected within 5 days of deposition (n = 22), or more than 5 days (n = 85), with 95% confidence intervals. Stars ** denote p < 0.05 using Fisher’s Exact Test. (B) Coefficient estimates for the success model (log-odds ratios; points). Error lines represent 50% (thick) and 95% (thin) confidence intervals. Collection PERIOD den and winter are with reference to summer, and COVER is closed with reference to open canopy.