Time is of the essence! Tjalling Jager Dept. Theoretical Biology Challenges of ecotox Some 100,000 man-made chemicals For animals alone, >1 million species described Complex dynamic exposure situations Species interact dynamically in ecosystems We cannot (and should not) test all permutations! Extrapolation “Protection goal” Laboratory tests time is of the essence! Fate modelling environmental characteristics and emission pattern mechanistic fate model physico-chemical properties under laboratory conditions concentrations over time and space Fate modelling pesticide fate modelling oil-spill modelling Classic ecotox Description for: • one endpoint • one timepoint • constant exposure • one set of conditions NOEC EC50 effects data over time for one (or few) set(s) of conditions summary statistics prediction effects in dynamic environment Learn from fate modelling proper measures of toxicity that do not depend on time or conditions mechanistic model for species A effects data over time for one (or few) set(s) of conditions prediction effects in dynamic environment Data analysis life-history information of the species test conditions model parameters for toxicant mechanistic model for species A effects data over time for one (or few) set(s) of conditions model parameters for species model parameters that do not depend on time or conditions Educated predictions dynamic environment: exposure and conditions model parameters for toxicant prediction lifehistory traits over time only for one species ... mechanistic model for species A model parameters for species model parameters that do not depend on time or conditions Community effects model parameters for toxicant model parameters for species A mechanistic model for species A dynamic environment model parameters for toxicant model parameters for species A mechanistic model for species B mechanistic model for a community simulate community effects and recovery over time What individual model? model parameters for toxicant model parameters for species A mechanistic model for species A dynamic environment TKTD modelling toxicodynamics external concentration (in time) toxico-kinetic model internal concentration in time process model for the organism toxicokinetics effects on endpoints in time TKTD modelling external concentration (in time) toxico-kinetic model internal concentration in time toxicokinetics TKTD modelling toxicodynamics internal concentration in time process model for the organism effects on endpoints in time Organisms are complex … process model for the organism Learn from fate modellers Make an idealisation of the system how much biological detail do we minimally need … – – – – to explain how an organism grows, develops and reproduces to explain effects of stressors on life history to predict effects for untested situations without being species- or stressor-specific internal concentration in time process model for the organism effects on endpoints in time Dynamic Energy Budget Organisms obey mass and energy conservation – – – – find the simplest set of rules ... over the entire life cycle ... for all organisms (related species follow related rules) most appropriate DEB model depends on species and question resources offspring waste products growth maturation maintenance Kooijman (2010) The “DEBtox” concept external concentration (in time) toxicokinetics internal concentration in time DEB parameters in time repro growth DEB model survival feeding hatching … The “DEBtox” concept external concentration (in time) toxicokinetics internal concentration in time DEB parameters in time repro growth DEB model survival feeding hatching DEB parameter cannot be measured … Internal concentration are often not measured … … “Standard” tests ... mechanistic model for species A model parameters for toxicant model parameters for species constant exposure, ad libitum food Many DEBtox examples, e.g.: http://www.bio.vu.nl/thb/users/tjalling Dynamic exposure mechanistic model for species A model parameters for toxicant model parameters for species dynamic exposure pattern, different food levels ... Daphnia magna and fenvalerate – modified 21-day reproduction test – pulse exposure for 24 hours – two (more or less) constant food levels Pieters et al (2006) Pulse exposure Body length Cumulative offspring Fraction surviving 70 1 High food 4 60 40 2 0.6 30 0.4 20 1 0.2 ‘assimilation’ mode 10 of action: 0 0 Insights 70 • parameters independent of food1 60 • chemical effects fully reversible0.8 50 • reproduction rate slows down … 40 0 4 Low food 0.8 50 3 3 0.6 2 30 0.4 20 1 0.2 10 0 0 5 10 15 20 0 0 5 10 15 20 0 0 5 10 15 20 Work needed For the individual level – select relevant species and appropriate DEB models – adapt/develop model code, allow time-variable inputs – collect and analyse relevant existing test data Evaluate – – – – are DEB models useful? what are limitations? what are major gaps in knowledge? what test protocol is most useful? mechanistic model for species A mechanistic model for species B Community level What makes community different? – dynamic interactions between species – less or more sensitive to toxicants? mechanistic model for species A mechanistic model for species B mechanistic model for a community Community level Food web models can become rather complex … – – – – – results depend heavily on modelling choices difficult to parameterise focus on furry animals … little general insight gained not useful for generic RA Canonical community Start simple: – each species a simple DEB model – closed system (open for energy) – include nutrient recycling Canonical community Start simple: – each species a simple DEB model – closed system (open for energy) – include nutrient recycling nutrients producer light consumer decomposer detritus predator Using the DEB community previous project at VU-ThB (EU-MODELKEY) collaboration with SCK-CEN, Belgium (EU-STAR) nutrients producer light consumer decomposer detritus predator Using the DEB community previous collaborations, e.g., Univ. Antwerp (EU-NoMiracle, EU-OSIRIS) collaboration with UFZ, Leipzig (EU-CREAM) nutrients producer light consumer decomposer detritus predator Using the DEB community collaboration with Eawag, Switzerland (EU-CREAM) collaboration with IRSN, France nutrients producer light consumer decomposer detritus predator Using the DEB community previous projects at VU-ThB nutrients producer light consumer decomposer detritus predator Work needed For the community level – specify interactions between the species – code a community with DEB populations – simulations for various scenarios Evaluate – – – – what’s different at the community level? more or less effect? correspondence to e.g., mesocosm? identify major gaps in knowledge mechanistic model for a community Wrapping up Time is of the essence! – – – – an organism is a dynamic system … that interacts dynamically with others … in a dynamic environment … with dynamic exposure to chemicals NOEC, EC50 etc. are useless … time is of the essence! Wrapping up Mechanistic models essential for the individual – – – – to extract time-independent parameters from data to extrapolate to untested dynamic conditions to increase efficiency of risk assessment learn from fate and toxicokinetics modellers … Integrate models into a simple community – study how interactions affect toxicant responses – study recovery of the community Wrapping up Advantages of using DEB as basis – – – – – well-tested theory for individuals mechanistic, dynamic, yet (relatively) simple deals with the entire life cycle not species- or chemical-specific small but well-connected international DEB community resources offspring waste products growth maturation maintenance Wrapping up This project tries to deliver “proof of concept” – – – – can DEB serve as a general platform? can simple mechanistic community models help RA? how can we modify test protocols? where are the major stumbling blocks? More information on DEB: http://www.bio.vu.nl/thb on my work: http://www.bio.vu.nl/thb/users/tjalling time is of the essence! body length cumulative offspring Ex.1: maintenance costs time Jager et al. (2004) TPT time body length cumulative offspring Ex.2: growth costs time Alda Álvarez et al. (2006) Pentachlorobenzene time Ex.3: egg costs body length cumulative offspring Chlorpyrifos time Jager et al. (2007) time