Parasite and viral species richness of Southeast Asian bats: Fragmentation of area distribution matters

Gay, Noellie; Olival, Kevin J.; Bumrungsri, Sara; Siriaroonrat, Boripat; Bourgarel, Mathieu; Morand, Serge

We calculated independent contrasts for each of the investigated variables with the package APE (Paradis et al., 2004) implemented in R (R Development Core Team, 2008). Independent contrasts were calculated for three groups of parasites (viruses, endoparasitic helminths and ectoparasite arthropods) for which we had a full set of explanatory variables: sampling effort or investigation effort; bat body mass; bat distribution range size; distribution shape (fragmentation); bat colony size; number of breading seasons; and bat gregarious behavior. Parasite species richness (PSR), viral richness, investigation effort, sampling effort, range, body weight were log transformed in order to stabilize variance. Distribution shape was transformed using arcsine of square root transformation. To confirm the proper standardisation of contrasts, the absolute values of standardised contrasts were regressed against their standard deviations (Garland et al., 1992) . Then contrasts were analyzed using standard multiple regressions, with all intercepts forced through the origin (Garland et al., 1992) . We selected the model using a backward procedure and due to potential co-linearity among variables we performed a Principal Component Analysis in order to select variables. We used Akaike's Information Criteria (AIC) to select the best models.