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).
Table 1.
Fecal prevalence (number of detected infections/number of samples) and apparent maximum prevalence (number of infected wolves/number of unique wolves) in northern Yellowstone wolves years 2018–2020.
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.