Chemical (and other) stress in DEB 5: extrapolations Tjalling Jager Dept. Theoretical Biology TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A AA A

Contents Extrapolations  Why extrapolation?  Examples of extrapolation

Why extrapolation “Protection goal” Available data different exposure time different temperature different species time-varying exposure species interactions populations other stresses mixture toxicity …

Contents Example life-cycle dataset Bindesbøl et al (2007), re-analysed in Jager and Klok (2010) copper in Dendrobaena octaedra size, survival, cocoons over 20 weeks here, only [Cu] > 80 mg/kg

DEB analysis of data Assumption copper leads to a decrease in ingestion rate Jager and Klok,

external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time DEB parameters in time DEB model DEB model life-history traits TK parstox parsDEB pars to population model … Parameter estimates

Population effects  Type of information that risk assessors should be most interested in...  Popular endpoints intrinsic rate of increase toxicant concentration where this rate is zero (or multiplication factor lambda, and where it is one)  Popular (simple) approaches matrix models Euler-Lotka equation...

Matrix models  In combination with DEB(tox) Klok & De Roos (1996), Lopes et al (2005), Klanjscek et al (2006), Smit et al (2006), Liao et al (2006)  Discrete time and discrete stages... one state variable (size or age) for the organism … DEB generally requires more

Euler-Lotka equation  In combination with DEB(tox) Kooijman & Metz (1984), Jager et al (2004), Alda Álvarez et al (2005, 2006)...  Continuous time and continuous states... straightforward for DEB animals only for constant environment...  In constant environment, populations grow exponentially

Individual-based models Kooijman (2000)  Follow all individuals seperately …  Full flexibility for dynamic environments but calculation intensive … see Martin et al (subm.)

Population effects concentration (mg/kg soil) population growth rate (d -1 ) no-effects Jager and Klok, 2010 But, this is extinction at: abundant food no predation no disease optimal temperature low competition …

external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time DEB parameters in time DEB model DEB model life-history traits TK parstox parsDEB pars less food in environment Extrapolation: food

Energy budget … growth reproduction feeding maintenance maturation 5% ad libitum

Energy budget … growth reproduction feeding maintenance maturation 50% limiting

Food limitation (90%)

concentration (mg/kg soil) population growth rate (d -1 ) Food limitation food 100% food 90% Jager and Klok, 2010

external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time DEB parameters in time DEB model DEB model life-history traits TK parstox parsDEB pars other compounds (related) Extrapolation: chemicals

Process-based QSAR Jager and Kooijman, 2009

external concentration (in time) toxico- kinetics internal concentration in time external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time DEB parameters in time DEB model DEB model life-history traits TK parstox parsDEB pars other compounds (mixtures) Extrapolation: mixtures

external concentration A (in time) external concentration B (in time) toxico- kinetics toxico- kinetics toxico- kinetics toxico- kinetics internal concentration A in time internal concentration B in time DEB parameters in time DEB model DEB model life-history traits theory implies interactions … growth Mixtures

external concentration A (in time) toxico- kinetics toxico- kinetics external concentration B (in time) toxico- kinetics toxico- kinetics DEB model DEB model internal concentration A in time DEB parameters in time internal concentration B in time life-history traits Mixtures

Simple mixture rules assimilation maintenance … compound‘target’metabolic process toxicity parameters linked (compare CA)

Simple mixture rules assimilation maintenance … compound‘target’metabolic process

Simple mixture rules assimilation maintenance … compound‘target’metabolic process toxicity parameters independent (compare IA)

Visual representation  For binary mixture, model represents surface that changes in time … Baas et al (2007)

fluoranthene pyrene PAHs in Daphnia  Based on standard 21-day OECD test 10 animals per treatment length, reproduction and survival every 2 days no body residues (TK inferred from effects) Jager et al (2010)

costs reproduction (and costs growth) costs reproduction (and costs growth) same target

Iso-effect lines for body length <50% effect

external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time DEB parameters in time DEB model DEB model life-history traits TK parstox parsDEB pars other (related) species Extrapolation: species ? ?

Experiments nematodes Species Caenorhabditis elegans and Acrobeloides nanus Chemicals cadmium, pentachlorobenzene and carbendazim Exposure in agar Endpoints survival, body size, reproduction over full life cycle analysed with extended DEBtox Studies published as: Alda Álvarez et al., 2005 (Func. Ecol.), 2006 (ES&T), 2006 (ET&C)

PeCB in A. nanus Effects on assimilation A. nanus

PeCB in C. elegans Costs for growth and reproduction C. elegans

A. nanus PeCB (narcotic) Cadmium (heavy metal) Carbendazim (inhibits mitosis) Physiological MoA

C. elegansA. nanus PeCB (narcotic) costs for growth and reproduction assimilation Cadmium (heavy metal) Carbendazim (inhibits mitosis) Physiological MoA

C. elegansA. nanus PeCB (narcotic) costs for growth and reproduction assimilation Cadmium (heavy metal) assimilationcosts for growth (+ ageing) Carbendazim (inhibits mitosis) Physiological MoA

C. elegansA. nanus PeCB (narcotic) costs for growth and reproduction assimilation Cadmium (heavy metal) assimilationcosts for growth (+ ageing) Carbendazim (inhibits mitosis) assimilation (- ageing) Physiological MoA

Species differences? Species ASpecies B target sitetoxicanttarget sitetoxicant maintenance reproduction … maintenance reproduction …

Species differences? target sitetoxicant maintenance reproduction …

external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time metabolic processes in time DEB model DEB model life-history traits TK parstox parsDEB pars time-varying concentrations Extrapolation: exposure

Time-varying exposure Specifically relevant for risk assessment  Such as: accidental spills plant-protection products industrial chemicals; batch production  Impractical and costly to test each scenario experimentally

Fate modelling oil-spill modelling pesticide fate modelling

time environ. conc. Time-varying exposure

time environ. conc. time internal conc. Assumption toxicokinetics follows first-order, one-comp. model Time-varying exposure

time environ. conc. time internal conc. assimilation eff. NEC blank value Assumption effects on energetic processes are reversible Time-varying exposure

time body length time cumul. reproduction Time-varying exposure

Experimental validation 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 High food Low food mode of action: ‘assimilation’ Insights tox. parameters independent of food chemical effects fully reversible reproduction rate slows down …

Summary  Extrapolation is crucial for environmental management extrapolation requires mechanistic theory DEB provides a framework for extrapolation  But, hypotheses for toxicant effects must be ‘correct’  More work is needed, e.g., starvation responses and interaction with toxicants patterns in DEB parameter values between species patterns in toxicity parameters (species and chemicals) reversibility of toxic effects interactions between chemicals in a mixture etc. etc....

species specific DEB model Outlook target sitetoxicant effect on life cycle ?  number of chemicals and species is very large …  but number of target sites and DEB parameters is limited! DEB parameters DEB theorybiochemistry

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