Comparison of laboratory batch and flow-through microcosm bioassays

Clément, Bernard; Delhaye, Hélène; Triffault-Bouchet, Gaëlle

doi:10.1016/j.ecoenv.2014.07.015

Cited by 11 publications

(11 citation statements)

References 41 publications

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“…, EC 50 ). We obtained a very high but imprecise estimate for E k (47.9 [18.2, 2042] µ g/L) indicating that daphnids were less sensitive in our experiment than in the one conducted by [Clément et al, 2014]. However, the narrow posterior distribution for curvature coefficient b k (0.56 [0.21, 1.04] µ g/L) indicated that daphnid growth rate was already affected at the lowest concentrations, as also mentioned by [Billoir et al, 2012].…”

Section: Discussionmentioning

confidence: 71%

“…In the literature, the effects of cadmium on daphnid growth may vary a lot from one study to another: EC 10 = 7.3 µg/L for 17 days in (Knops et al, 2001) (monospecific bioassay conditions), N EC = 0.15 µg/L in (Billoir, Delhaye, Forfait, et al, 2012) indicating that daphnids were less sensitive in our experiment than in the one conducted by (BJP Clément et al, 2014). However, the narrow posterior distribution for curvature coefficient b k (0.56 [0.21, 1.04] µg/L) indicated that daphnid growth rate was already affected at the lowest concentrations, as also mentioned by (Billoir, Delhaye, Forfait, et al, 2012).…”

Section: On Parameters and Processesmentioning

confidence: 79%

“…As mentioned in (Lamonica, Herbach, et al, 2016), we used measured cadmium concentrations in the medium instead of nominal ones. For that purpose, we measured dissolved cadmium concentrations as described by Clement et al (BJP Clément et al, 2014) at days 2, 7, 14…”

Section: Experiments and Observed Datamentioning

confidence: 99%

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Chemical effects on ecological interactions within a model-experiment loop

Lamonica

Charles

Clément

et al. 2022

Preprint

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We propose in this paper a method to assess the effects of a contaminant on a micro-ecosystem, integrating the population dynamics and the interactions between species. For that, we developed a dynamic model to describe the functioning of a microcosm exposed to a contaminant and to discriminate direct and indirect effects. Then, we get back from modelling to experimentation in order to identify which of the collected data have really been necessary and sufficient to estimate model parameters in order to propose a more efficient experimental design for further investigations. We illustrated our approach using a 2-L laboratory microcosm involving three species (the duckweed Lemna minor, the microalgae Pseudokirchneriella subcapitata and the daphnids Daphnia magna) exposed to cadmium contamination. We modelled the dynamics of the three species and their interactions using a mechanistic model based on coupled ordinary differential equations. The main processes occurring in this three-species microcosm were thus formalized, including growth and settling of algae, growth of duckweeds, interspecific competition between algae and duckweeds, growth, survival and grazing of daphnids, as well as cadmium effects. We estimated model parameters by Bayesian inference, using simultaneously all the data issued from multiple laboratory experiments specifically conducted for this study. Cadmium concentrations ranged between 0 and 50 mug.L-1. For all parameters of our model, we obtained biologically realistic values and reasonable uncertainties. The cascade of cadmium effects, both direct and indirect, was identified. Critical effect concentrations were provided for the life history traits of each species. An example of experimental design adapted to this kind a microcosm was also proposed. This approach appears promising when studying contaminant effects on ecosystem functioning.

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Section: Discussionmentioning

confidence: 71%

Section: On Parameters and Processesmentioning

confidence: 79%

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Chemical effects on ecological interactions within a model-experiment loop

Lamonica

Charles

Clément

et al. 2022

Preprint

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“…The main issue associated with the use of toxicity data from field studies is that such data lack standardization and replication (Sanderson 2002; Clément et al 2014). To date, various studies have been conducted to investigate community responses to stresses in the field (see Boyle et al 2016; Jeppe et al 2017; Cadmus et al 2018), although there is no standard on how to report toxicity values based on field studies.…”

Section: Discussionmentioning

confidence: 99%

Comparing the Impacts of Sediment‐Spiked Cadmium on Chironomidae Larvae in Laboratory Bioassays and Field Microcosms and the Implications for Field Validation of Site‐Specific Threshold Concentrations

Liu

Zhang

Xin

et al. 2021

Enviro Toxic and Chemistry

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Information on the effects of pollutants in sediments at an ecosystem level to validate current and proposed risk‐assessment procedures is scarce. The most frequent criticism of these procedures is that responses of surrogate species in the laboratory are not representative of responses of natural populations. A tiered approach using both laboratory and microcosm exposures (96‐h and 21‐d laboratory bioassays and a 3‐mo field microcosm) was conducted to compare the impacts of sediment‐spiked cadmium on the mortality, development, and abundance of Chironomidae larvae. The 96‐h and 21‐d lethal concentrations of sediment‐spiked Cd to 50% of the species Chironomus riparius were estimated to be 201.07 and 172.66 mg/kg, respectively. In the 21‐d laboratory bioassay, the endpoints, including the development rate and emergence ratio, were compared, and the lowest‐observed‐effect concentration (LOEC) values were 325.8 and 10.7 mg/kg, respectively. The abundance, richness, and biomass of field‐collected larvae were compared among the different treatments in the field microcosm, and it was found that the order of sensitivities using different endpoints was biomass (2.6/5.2 mg/kg of no‐observed‐effect concentration/LOEC) > diversity (10.7/21.2 mg/kg) > abundance (41.2/82.7 mg/kg). The toxicity values based on lethal/sublethal changes in the laboratory bioassays might not fully protect field organisms against damage from chemicals, such as Cd, unless an assessment factor of 5 is used. These findings highlight the need to conduct field validation of criteria/guidelines before they are introduced to protect organisms/ecosystems in the field and provide a preliminary template for future field validation of criteria elsewhere. Environ Toxicol Chem 2021;40:2450–2462. © 2021 SETAC

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“…Axenic cultures were maintained by weekly transferring a few mL of an exponentially growing culture in fresh medium sterilized by autoclaving. The microalgae were exposed in 48-well plates filled with exposure medium used in previous microcosm assays (Clément et al 2013(Clément et al , 2014. This synthetic medium presented the following 3 characteristics : pH 8.0, hardness 60 mg CaCO3 L −1 , alkalinity 120 mg CaCO3 L −1 , conductivity 290 μS cm −1 , phosphorous 100 μg L −1 , nitrogen 1308 μg L −1 , FeEDTANa26H2O 109.4 μg L −1 , oligo-elements and vitamins of M4 medium (Elendt and Bias 1990).…”

Section: Bioassaysmentioning

confidence: 99%

The toxicity of cadmium-copper mixtures on daphnids and microalgae analysed using the Biotic Ligand Model

Clément¹,

FELIX

Bertrand

2021

Preprint

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For the prediction of metals mixture ecotoxicity, the BLM approach is promising since it evaluates the amount of metals accumulated on the biotic ligand on the basis of water chemistry, i.e. species (major cations) competing with metals, and related toxicity. Based on previous work by Farley et al. 2015 (MMME research project), this study aimed at modelling toxicity of Cd:Cu mixtures (0:1–1:1–1:0–1:2 − 1:3 − 2:1–3:1–4:1–5:1–6:1) to the crustacean Daphnia magna (48h immobilization tests) and the microalga Pseudokirchneriella subcapitata (72h growth inhibition tests). The USGS model was chosen, assuming additivity of effects and accumulation of metals on a single site. The assumption that EDTA could contribute to toxicity through metals complexing was also tested, and potential effects due to reduction of ions Ca2+ absorption by metals were considered. Modelling started with parameter values of Farley et al. 2015 and some of these parameters were adjusted to fit modelled data on observed data. The results show that toxicity can be correctly predicted for the microalgae and that the hypothesis of additivity is verified. For daphnids, the prediction was roughly correct, but taking into account CuEDTA led to more realistic parameter values close to that reported by Farley et al. 2015. However, It seems that, for daphnids responses, metals interact either antagonistically or synergistically depending on the Cu:Cd ratio. Furthermore, synergy could not be explained by additional effects linked to a reduction of Ca absorption since this reduction, mainly due to Cd, increased inversely to synergy. Finally, the USGS model applied to our data was able to predict Cu:Cd mixture toxicity to microalgae and daphnids, giving rise to estimated EC50s roughly reflecting EC50s calculated from observed toxicity.

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Comparison of laboratory batch and flow-through microcosm bioassays

Cited by 11 publications

References 41 publications

Chemical effects on ecological interactions within a model-experiment loop

Chemical effects on ecological interactions within a model-experiment loop

Comparing the Impacts of Sediment‐Spiked Cadmium on Chironomidae Larvae in Laboratory Bioassays and Field Microcosms and the Implications for Field Validation of Site‐Specific Threshold Concentrations

The toxicity of cadmium-copper mixtures on daphnids and microalgae analysed using the Biotic Ligand Model

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