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Large-scale ecotoxicological studies have technical and ethical limitations,both related to the need to expose individuals to potentially harmfulcompounds. Computational modeling is a complementary useful and predictive toolthat overcomes these limitations. Considering the increasing interest in theeffects of pesticides on behavioral traits, the aim of this study was toevaluate the effects of chlorpyrifos (CPF) on intra- and inter-specificinteractions of anuran tadpoles, complementing traditional ecotoxicologicaltools with a theoretical analysis verified by computational simulations.Experiments were developed under two consecutive phases: a first phase ofexposure, and a second phase of interactions. The second phase consisted ofevaluating the effects of CPF on intra- and inter-specific interactions ofexposed C. ornata (Co) tadpoles acting as predators and unexposed Rhinellafernandezae (Rf) tadpoles acting as prey, under different predator-preyproportions. Also, intraspecific interactions of three Co tadpoles underdifferent conditions of exposure were evaluated. During the exposure phase,chlorpyrifos induced significant mortality from 48h, irregular swimming, tailflexure, and the presence of subcutaneous air. Also, it induced effects on thesounds emitted after 96h of exposure, registering less number of pulses andhigher dominant frequencies, and altered intra- and inter-specificinteractions. During the interaction phase, the larvae continued to show soundeffects, however, the antipredator mechanism continued to be operating andefficient. Finally, it was possible to model the behavior of the larvae underthe effects of chlorpyrifos. We conclude that experimental data andcomputational modeling matched within errors. Therefore, computationalsimulation is a valuable ecotoxicological tool that provides new informationand allows predicting natural processes.

environmental pollution

Disruptive effects of chlorpyrifos on predator-prey interactions of  Ceratophrys ornata tadpoles: consequences at the population level using  computational modeling