A Daphnia population model that considers pesticide exposure and demographic stochasticity

Richard A. Erickson, Stephen B. Cox, Jessica L. Oates, Todd A. Anderson, Christopher J. Salice, Kevin R. Long

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Population models have emerged as a powerful tool to better understand the ecological effects of toxicant exposure. Currently, most ecotoxicology population models are deterministic and fail to account for natural variability in biological processes and uncertainty in parameter estimates. We developed, parameterized, and analyzed a Daphnia population model with three different levels of demographic stochasticity to examine how a pesticide, pendimethalin, affects population dynamics. We conducted laboratory studies to generate the data used for the modeling process. The simplest model only included parameter uncertainty and variability. The second model included daily stochastic fecundities. The third model included stochastic fecundities and stochastic mortalities. Of the three models, the second model with stochastic fecundity best described our laboratory test system. All three models were used to test hypotheses about how pesticides would affect population dynamics. We found that pendimethalin either decreased the baseline juvenile survivorship rate or the carrying capacity. We could differentiate the two test effects with our system. Our findings demonstrate how stochastic population models may provide insight into pesticide exposure.

Original languageEnglish
Pages (from-to)37-47
Number of pages11
JournalEcological Modelling
Volume275
DOIs
StatePublished - Mar 10 2014

Keywords

  • Demographic stochasticity
  • Ecotoxicology
  • Population modeling
  • Stochastic

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