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Ecological interactions affecting population-level responses to chemical stress in Mesocyclops leuckarti

 
: Kulkarni, Devdutt; Hommen, Udo; Schäffer, Andreas; Preuss, Thomas G.

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Chemosphere 112 (2014), pp.340-347
ISSN: 0045-6535
ISSN: 0366-7111
English
Journal Article
Fraunhofer IME ()
individual-based model; population dynamics; density dependence; Triphenyltin; Cannibalism; copepod

Abstract
Higher tiers of ecological risk assessment (ERA) consider population and community-level endpoints. At the population level, the phenomenon of density dependence is one of the most important ecological processes that influence population dynamics. In this study, we investigated how different mechanisms of density dependence would influence population-level ERA of the cyclopoid copepod Mesocyclops leuckarti under toxicant exposure. We used a combined approach of laboratory experiments and individual-based modelling. An individual-based model was developed for M. leuckarti to simulate population dynamics under triphenyltin exposure based on individual-level ecological and toxicological data from laboratory experiments. The study primarily aimed to-(1) determine which life-cycle processes, based on feeding strategies, are most significant in determining density dependence (2) explore how these mechanisms of density dependence affect extrapolation from individual-level effects to the population level under toxicant exposure. Model simulations showed that cannibalism of nauplii that were already stressed by TPT exposure contributed to synergistic effects of biotic and abiotic factors and led to a twofold stress being exerted on the nauplii, thereby resulting in a higher population vulnerability compared to the scenario without cannibalism. Our results suggest that in population-level risk assessment, it is easy to underestimate toxicity unless underlying ecological interactions including mechanisms of population-level density regulation are considered. This study is an example of how a combined approach of experiments and mechanistic modelling can lead to a thorough understanding of ecological processes in ecotoxicology and enable a more realistic ERA.

: http://publica.fraunhofer.de/documents/N-290687.html