Offspring Fitness in Daphnia: Is the Daphnia Reproduction Test Appropriate for Extrapolating Effects on the Population Level?

Abstract

Abstract-In the Daphnia reproduction test, the number of living offspring per living parent, mortality, and, occasionally, growth and time to first brood are used as endpoints for the determination of no-observed-effect concentration (NOEC)/lowest-observedeffect concentration (LOEC), or 50% effective concentration (EC50). It is known that chemicals can influence not only the number of neonates but also the offspring size (and, thus, possibly the neonate fitness) in daphnids. Changes in neonate size and fitness have not been routinely recorded in Daphnia reproduction tests, although they are an important factor in population growth. Some of our previous research with some dispersants showed clear effects on offspring quality (smaller neonates with enhanced mortality). We tested one of these dispersants in two different test designs: the reproduction test and a population growth experiment. The results from these two experimental designs differed completely: in the reproduction test, the living offspring number was increased (by up to 10.2 mg/L of the dispersant Dispersogen A) in comparison with the control, whereas in the population growth experiment, the population size was already reduced at concentrations of 1.64 mg/L. A F1-reproduction test, conducted in control medium with neonates born in the reproduction test, showed that neonate fitness was significantly reduced at concentrations of 1.64 mg/L and higher. Therefore, it appears absolutely necessary to take neonate fitness into account if we intend to assess population-level effects. This is easily considered in a population growth experiment but not in the Daphnia reproduction test. To evaluate the fitness of the neonates, an additional test with neonates (F1 test) or another test design (population growth experiment) is necessary.

The use of image analysis to estimate population growth rate in Daphnia magna

“…Daphnia magna is widely used to assess toxicant effects by measuring life-history parameters such as survivorship and fecundity, and more recently using count estimates of PGR. However, some toxicants may stimulate an increase in offspring number, but the offspring may be of low quality (small size, increased mortality risk and less fecund), as in Hammers-Wirtz & Ratte (2000). Count estimation during a short period of time then exaggerates population growth.…”

How do interactive maternal traits and environmental factors determine offspring size inDaphnia magna?

“…However, an important limitation of these available models is that none of them accounts for the natural variability in the offspring size (OS) in Daphnia magna. This trait, in fact, determines vital individual processes such as growth (Hammers-Wirtz and Ratte, 2000), size at first reproduction (Barata and Baird, 1998) or size-selective predation (Lampert, 1993;Gergs and Ratte, 2009), which in turn affect higher-order processes such as population growth rate, maturation (Sakwinska, 2004;Rinke, 2006), population survival rates (Sakwinska, 2004;Dudycha and Lynch, 2005) or resistance to starvation (Tessier and Consolatti, 1991).…”

Laudation to Prof. Dr. Hans-Toni Ratte--towards conceptual, theory-based ecological science and its transfer to the applied field of ecotoxicology

“…Here, I realized the importance of applied environmental research and its direct use in decision making. Here, I also met for the first time Hans Toni Ratte, a respected colleague with a broad scientific interest covering topics like applied ecology [1-3], ecotoxicology [4][5][6][7], ecotoxicological statistics [8,9], mechanistic effect models [10], and guidance development [11].…”

“…Here, I realized the importance of applied environmental research and its direct use in decision making. Here, I also met for the first time Hans Toni Ratte, a respected colleague with a broad scientific interest covering topics like applied ecology [1-3], ecotoxicology [4][5][6][7], ecotoxicological statistics [8,9], mechanistic effect models [10], and guidance development [11].Within the scientific community it is more and more recognized that the extrapolation of results from laboratory toxicity experiments to complex field communities requires the analysis of the interactions between different trophic levels in ecosystems, which can be done by means of model ecosystems and mechanistic modelling. Within this context it is worthwhile mentioning that already in the early 1990s of the past century Hans Toni Ratte started with the supervision of a research project at RWTH Aachen University to integrate and extrapolate ecotoxicological experiments by means of model ecosystem research and computer simulation models [10,12,13].…”