Inter and intra-guild interactions in egg parasitoid species of the soybean stink bug complex

The objective of this research was to evaluate the parasitism behavior of Telenomus podisi Ashmead, Trissolcus basalis (Wollaston) e Trissolcus urichi Crawford (Hymenoptera: Scelionidae) on eggs of Nezara viridula L., Euschistus heros F., Piezodorus guildinii Westwood and Acrosternum aseadum Rolston (Heteroptera: Pentatomidae), in no choice and multiple choice experiments. For all parasitoid species, the results demonstrated the existence of a main host species that maximizes the reproductive success. The competitive interactions among the parasitoid species were investigated in experiments of sequential and simultaneous release of different combinations of parasitoid pairs on the hosts N. viridula, E. heros and A. aseadum. Exploitative competition was observed for egg batches at the genus level (Telenomus vs. Trissolcus) and interference competition at the species level (T. basalis vs. T. urichi). Trissolcus urichi was the most aggressive species, interfering with the parasitism of T. basalis. Generally, T. basalis showed an opportunistic behavior trying to parasitise eggs after T. urichi had abandoned the egg batch. The selection of parasitoid species for use in augmentative biological control programs should take into account the diversity of pentatomids present in soybean in addition to the interactions among the different species of parasitoids.

Heterogeneity and event dependence in the analysis of sickness absence

Sickness absence (SA) is an important social, economic and public health issue. Identifying and understanding the determinants, whether biological, regulatory or, health services-related, of variability in SA duration is essential for better management of SA. The conditional frailty model (CFM) is useful when repeated SA events occur within the same individual, as it allows simultaneous analysis of event dependence and heterogeneity due to unknown, unmeasured, or unmeasurable factors. However, its use may encounter computational limitations when applied to very large data sets, as may frequently occur in the analysis of SA duration. To overcome the computational issue, we propose a Poisson-based conditional frailty model (CFPM) for repeated SA events that accounts for both event dependence and heterogeneity. To demonstrate the usefulness of the model proposed in the SA duration context, we used data from all non-work-related SA episodes that occurred in Catalonia (Spain) in 2007, initiated by either a diagnosis of neoplasm or mental and behavioral disorders. As expected, the CFPM results were very similar to those of the CFM for both diagnosis groups. The CPU time for the CFPM was substantially shorter than the CFM. The CFPM is an suitable alternative to the CFM in survival analysis with recurrent events,especially with large databases.