Host-Parasite biogeographic interactions: modelling the distribution of Phyllotis xanthopygus rodents complex and their flea assemblage using the favorability function

Host-parasite systems play a key role in biogeography, with parasites influencing the distributions of their host and vice versa. The biodiversity of flea species on the subfamily Sigmodontinae is especially valuable for studying parasite-host-environment interactions. This study evaluates the biogeographic relationship between rodents of the Phyllotis xanthopygus complex and their flea assemblage applying the favorability function in the modelling distribution, to identify the different environmental factors that favor the distribution of both, and to detect areas of greater shared favorability. This is the first study on fleas using a methodology based on fuzzy logic that helps to disentangle the main factors that determine favorable environmental conditions for parasites and hosts. Using favorability functions as the fuzzy logic modelling technique and fuzzy intersection, union, and inclusion as the fuzzy operators, we were able to specify the territories with maximum simultaneous fl..., , # Host-Parasite biogeographic interactions: modelling the distribution of Phyllotis xanthopygus rodents complex and their flea assemblage using the favorability function

Files included (all files use semicolon delimiter and comma decimal):

1.S1.csv. Description: **Table S1.** Explanatory variables of environmentally favorable territories for *Phyllotis xanthopygus *rodents complex according to the favorability model. The variables are shown in order of entry in the construction of the model. Estimate: coefficient of variables. Std. Error: Standard Error. Wald: Significance of each variable in the model. p: statistical significance. Exp(B): Odds ratios. See Table 2 for abbreviatures of the variables.

2.S2.csv. Description: **Table S2.** Explanatory variables of environmentally favorable territories for flea assemblage according to the favorability model. The variables are shown in order of entry in the construction of the model. Estimate: coefficient of variables. Std. Error: Standard...,