Data sets

We used five variable groups (hereafter referred to as ecological factors) for our statistical models (full data set is given in the Supplement ¹):

1) host variables (H), which included (i) water frog relative population size (calling males per waterbody, or frogs in our Results tables) and (ii) average frog size in our parasitology samples (or host size);

2) parasites (P) – abundances (A, or average number of worms per host for all samples including uninfected frogs) of (i) diplostomid larvae, (ii) plagiorchiid larvae, (iii) plagiorchiid adults, (iv) nematode adults, and (v) total helminth infra-community species richness (S, average per host) (species richness of separate helminth groups were also analysed, but had no statistically significant relationships with predictors and therefore were dropped from the present paper);

3) waterbody (W) – (i) area (ha), (ii) depth (m), (iii) permanence (ratio), (iv) the degree of mud in bottoms (category), coverages of (v) submersed, (vi) floating and (vii) emergent vegetations (%), and proportions of viii) woody vegetation and ix) reeds on the shoreline;

4), and 5) land uses within 100 m (L100) and 500 m (L500) belts around the waterbody, each containing proportions of coverages of (i) other waterbodies, (ii) mires, (iii) wooded vegetation (or forest), (iv) agriculture lands and (v) human settlements.

Parasite variables had no correlation with the number of sampled frogs per site (zero-inflated negative binomial (ZINB) regressions, p > 0.1 in all the cases). Average variance inflation factor (VIF) in the environmental predictor (W, L100, L500) data set was 3.55, indicating moderate collinearity (Table ​(Table1).1). However, their effects were separable and some collinearity did not hinder interpretations of the results. For instance, the highest VIF values were caused by a negative correlation between the agriculture and forest variables in the L500 group, which contrarily showed the same more often than the opposite direction of the relationship in our models.

Values of variance inflation factor (VIF) for environmental variables in our regression analyses.