Evaluation of three larval instars of the midge Chironomus petiolatus as bioassay tools using a computationally intensive statistical algorithm.
Sensitivity to toxicants is a major criterion for selecting organisms for bioassay testing. If a sensitive species is also abundant and occupies a role as prey for many other species within a community, then the species become a valuable tool in environmental monitoring. These features apply to larval midge Chironomus petiolatus in freshwater environments of central Chile. The youngest larval instar is the most sensitive and presents the additional feature of lower survival within control arenas, making it more difficult to discern toxicant-related mortality from background mortality. In this work, we perform acute bioassays with the three larval stages of C. petiolatus and K2Cr2O7 as reference toxicant, with the goal of selecting a particular instar as the best bioassay tool using two criteria: sensitivity and background mortality. Sensitivity is evaluated through Monte Carlo estimation of LC50 and background mortality through bootstrap resampling, and a final Bioassay Performance Index as the product of LC50 and background mortality. For this task we developed a new computationally intensive statistical algorithm. Results show that the best bioassay tool is not the youngest and most sensitive instar but an intermediate one.
Larrain
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Universidad de Concepción, Casilla 2407, Concepción, Chile.
Riveros
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Bay-Schmith
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Roa
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D000465:Algorithms; D000818:Animals; D001681:Biological Assay / Q000379:methods*; D002683:Chironomidae / Q000254:growth & development*; D005069:Evaluation Studies as Topic; D007814:Larva; D009010:Monte Carlo Method