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Ecological Modelling
Enhancing experimental data for the Environmental Risk Assessment

ibacon supports chemical industries since 1994 with efficient experimental labortory and field studies for the environmental risk assessment of their products. Experience shows that  experimental data cannot answer all questions risk assessors have. Often, further experiments may be too laborious, too time-consuming or even technically unfeasible. This is where Ecological Modelling can help.

Please find our latest flyer for download at the bottom of the page.

Based on the results of laboratory and field studies, Ecological Modelling can help understand the mechanisms underlying the observed effects and to answer questions like these:

  • Most susceptible stage: Which life stage or developmental phase of an organism is most susceptible to an exposure?
  • Recovery potential: Can recovery be expected after an initial effect on populations of non-target organisms? How much time will a population need to recover?
  • Extrapolations to different exposure scenarios or different environmental conditions: If experimental data exist for certain exposure conditions, specific environmental conditions or a certain experimental region, what can we expect under different exposure conditions, in other regions or at changed environmental conditions?
  • Long-term effects: How will an impact discovered in laboratory experiments influence population development in the real world?

 

 

EFSA: Experiments and models support the environmental risk assessment: Tier 1 and tier 2 effect assessments are based on single-species laboratory toxicity tests, but tier 2 assessment may be complemented with TK-TD models. Tier 3 and tier 4 may concern a combination of experimental data and modelling to assess population and/or community level responses (e.g. recovery, indirect effects) at relevant spatio-temporal scales.
(EFSA, 2014)

 

ibacon's modelling portfolio

Please find below some examples of our ecological modelling portfolio. We will be happy to explain to you  more details fitted to your needs.

  • For survival data, we offer analysis with the Generalized Unified Threshold model of Survival (GUTS)
  • For the analysis of sublethal effects, we provide analysis with DEBtox models
  • For Toxicokinetic – toxicodynamic (TKTD) modelling on population level, we offer analysis and predictions with DEB-IBM
  • For the Honey Bee population level,  we are working on the application of BEEHAVE (Becher et al, 2014)

Ecological modelling is a highly dynamic field, and we are actively taking part in the development of models and quality assessment of modelling results. Most important to us is compliance of our work with good modelling practice according to EFSA (2014).

For your products, we are happy to discuss with you how model applications may support the environmental risk assessment. Contact us about any ecological modelling you are interested in, we will find a solution for you!

 

Literature

  • EFSA Panel on Plant Protection Products and their Residues (2014). Scientific Opinion on good modelling practice in the context of mechanistic effect models for risk assessment of plant protection products. EFSA Journal. 12(3), 3589, 92 pp.
  • Zimmer EI, Jager T, Ducrot V, Lagadic L, Kooijman SALM (2012). Juvenile food limitation in standardized tests - a warning to ecotoxicologists. Ecotoxicology. 21(8), 2195-2204
  • Jager T, Zimmer EI (2012). Simplified dynamic energy budget model for analysing ecotoxicity data. Ecological Modelling. 225, 74-81
  • Jager T, Martin BT, Zimmer EI (2013). DEBkiss or the quest for the simplest generic model of animal life history.  Journal of Theoretical Biology. 328, 9-18.
  • Martin BT, Zimmer EI, Grimm V & Jager T (2012). Dynamic Energy Budget theory meets individual-based modelling: a generic and accessible implementation. Methods in Ecology and Evolution. 3, 445-449
  • Becher MA, Grimm V, Thorbek P, Horn J, Kennedy PJ, Osborne JL (2014). BEEHAVE: a systems model of honeybee colony dynamics and foraging to explore multifactorial causes of colony failure. Journal of Applied Ecology. 51, 470-482

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