Energy‐based modeling as a basis for the analysis of reproductive data with the midge (Chironomus riparius)

Abstract

We propose a biologically based approach to analyze reproductive data for the midge (Chironomus riparius). We showed in a previous study that its larval development can be divided in two distinct phases regarding the use of energy: The somatic growth period and the gametic growth period. We hypothesize here the gametic period to be a crucial period for the energetic investment for reproduction. To test this, we performed several assays with different feeding programs. Our results confirmed that energetic investment for reproduction mainly occurs during the gametic growth period. We could then propose energy-based models to analyze reproductive data. We assumed the effects to result from a perturbation in the use of energy. Two models corresponding to different physiological modes of actions--decreased efficiency of feeding (i.e., feeding decrease model) or increased cost of egg production (i.e., egg-cost increase model)--were built and used for the analysis of data obtained after an exposure to an artificially copper-spiked sediment. During this experiment, different exposure patterns were performed to investigate whether effects on reproduction resulted mainly from an exposure that occurs during the gametic growth period or from an exposure that occurs during the somatic growth period. These exposure patterns led to similar effects on reproduction, which suggests that the toxicant-induced stress persists during the whole life cycle, even in case of exposure occurring only during part of it. Both the feeding decrease model and egg-cost increase model were able to describe the data. We showed that addition of copper in the sediment, even in low quantity (<6.5 mg/kg), might affect reproduction at the individual level. If no-effect concentrations were derived from these results, this may lead to an overprotective value. A relevant no-effect concentration could be derived from further investigations at the population level.