DEBtox information
Making sense of ecotoxicity test results



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DEBtox information

DEBtox information

Publications / Papers on DEBtox

Explanation


The papers here are organised by year of publication. Each paper gets a few keys to facilitate searching by topic. Each paper has a Digital Object Identifier (DOI), that uniquely identifies it on the internet. Clicking the link provides the abstract, and also the PDF if you have access rights to that journal. Papers dealing with survival only, are located here. Inclusion of a paper in this list does not mean an endorsement or a quality mark of any kind.

Requirements to be included


Only models based on DEB-theory (or sufficiently similar) are included in the list below. There must be a toxicant in the study, although I included some papers with food or other stress as well.


Essential reading


Download of accepted versions


On this page, I will try to include downloadable PDF versions of my papers. These will be the my version of the paper; the last submitted version that was accepted (post peer review, but pre formatting by the journal). I will only offer that version for download below when the publisher/journal allows this, and adding the license information as prescribed by the publisher/journal. Furthermore, I am only offering downloads for papers on which I am the first author. It will take some time before all papers are added ... Note that there may be (small) differences with the published version.



Key

Description

key_gen
general paper
key_lif
dealing with life-cycle data
key_sur
survival data only
key_mix
dealing with mixtures of toxicants
key_db3
full model used (standard DEB)
key_pop
includes population effects
key_com
includes community level
key_alg
algal, bacterial or cell toxicity
key_mol
related to molecular level
key_gro
growth data only
key_tim
time-varying exposure

Full list by year


1984

  • Kooijman SALM and Metz JAJ (1984). On the dynamics of chemically stressed populations: the deduction of population consequences from effects on individuals. Ecotox Environ Saf 8:254-274 http://dx.doi.org/10.1016/0147-6513(84)90029-0 key_gen, key_pop
1996

1997

  • Klok C, De Roos AM, Marinissen JCY, Baveco HM and Ma WC (1997). Assessing the effects of abiotic environmental stress, on population growth in Lumbricus rubellus (Lubricidae, Oligochaeta). Soil Biol Biochem 29(3-4):287-293 http://dx.doi.org/10.1016/S0038-0717(96)00050-8 key_lif, key_pop
1998

  • Pablos MV, Boleas S, Tarazona JV (1998). Use of Mfu-galactoside enzymatic activity as ecotoxicological endpoint on rainbow trout red blood cells. Bull Environ Contam Toxicol 61:786-792 http://dx.doi.org/10.1007/s001289900829 key_alg
1999

  • Urrestarazu Ramos E, Vaes WHJ, Mayer P and Hermens JLM (1999). Algal growth inhibition of Chlorella pyrenoidosa by polar narcotic pollutants: toxic cell concentrations and QSAR modeling. Aquatic Toxicol 46(1):1-10 http://dx.doi.org/10.1016/S0166-445X(98)00111-8 key_alg
2004

2005

  • Alda Álvarez O, Jager T, Kooijman SALM and Kammenga JE (2005). Responses to stress of Caenorhabditis elegans populations with different reproductive strategies. Funct Ecol 19:656-664 http://dx.doi.org/10.1111/j.1365-2435.2005.01012.x key_lif, key_pop
2006

  • Alda Álvarez O, Jager T, Marco Redondo E and Kammenga JE (2006). Physiological modes of action of toxic chemicals in the nematode Acrobeloides nanus. Environ Toxicol Chem 25:3230-3237 http://dx.doi.org/10.1897/06-097R.1 key_lif, key_pop
  • Alda Álvarez O, Jager T, Nuñez Coloa B and Kammenga JE (2006). Temporal dynamics of effect concentrations. Environ Sci Technol 40:2478-2484 http://dx.doi.org/10.1021/es052260s key_lif
  • Arzul G, Quiniou F and Carrie C (2006). In vitro test-based comparison of pesticide-induced sensitivity in marine and freshwater phytoplankton. Toxicology Mechanisms and Methods 16(8): 431-437 http://dx.doi.org/10.1080/15376520600698717 key_alg
  • Jager T, Heugens EHW and Kooijman SALM (2006). Making sense of ecotoxicological test results: towards application of process-based models. Ecotoxicology 15:305-314 http://dx.doi.org/10.1007/s10646-006-0060-x key_gen, key_lif, key_pop accepted version.
  • Pieters BJ, Jager T, Kraak MHS and Admiraal W (2006). Modeling responses of Daphnia magna to pesticide pulse exposure under varying food conditions: intrinsic versus apparent sensitivity. Ecotoxicology 15:601-608 http://dx.doi.org/10.1007/s10646-006-0100-6 key_lif, key_tim
  • Smit MGD, Kater BJ, Jak RG and Van den Heuvel-Greve MJ (2006). Translating bioassay results to field population responses using a Leslie-matrix model for the marine amphipod Corophium volutator. Ecol Mod 196:515-526 http://dx.doi.org/10.1016/j.ecolmodel.2006.02.006 key_lif, key_pop
2007

  • Billoir E, Péry ARR and Charles S (2007). Integrating the lethal and sublethal effects of toxic compounds into the population dynamics of Daphnia magna: a combination of the DEBtox and matrix population models. Ecol Mod 203(3-4):204-214 http://dx.doi.org/10.1016/j.ecolmodel.2006.11.021 key_lif, key_pop
  • Ducrot V, Péry ARR, Mons R, Queau H, Charles S and Garric J (2007). Dynamic energy budget as a basis to model population-level effects of zinc-spiked sediments in the gastropod Valvata piscinalis. Environ Toxicol Chem 26(8):1774-1783 http://dx.doi.org/10.1897/06-556R.1 key_lif
  • Hall, SR, Becker, C and Cáceres, CE (2007). Parasitic castration: a perspective from a model of dynamic energy budgets. Integr Comp Biol 47(2):295-309 http://dx.doi.org/10.1093/icb/icm057 key_lif
  • Jager T, Crommentuijn T, Van Gestel CAM and Kooijman SALM (2007). Chronic exposure to chlorpyrifos reveals two modes of action in the springtail Folsomia candida. Environ Pollut 145:452-458 http://dx.doi.org/10.1016/j.envpol.2006.04.028 key_lif, key_pop
  • Klok C, Holmstrup M and Damgaardt C (2007). Extending a combined dynamic energy budget matrix population model with a Bayesian approach to assess variation in the intrinsic rate of population increase. An example in the earthworm Dendrobaena octaedra. Environ Toxicol Chem 26(11):2383-2388 http://dx.doi.org/10.1897/07-223R.1 key_lif, key_pop
2008

  • Billoir E, Delignette-Muller ML, Péry ARR, Geffard O and Charles S (2008). Statistical cautions when estimating DEBtox parameters. J Theor Biol 254(1):55-64 http://dx.doi.org/10.1016/j.jtbi.2008.05.006 key_lif, key_gen
  • Billoir E, Delignette-Muller ML, Péry ARR and Charles S (2008). A Bayesian approach to analyzing ecotoxicological data. Environ Sci Technol 42(23):8978-8984 http://dx.doi.org/10.1021/es801418x key_lif
  • Klok C (2008). Gaining insight in the interaction of zinc and population density with a combined Dynamic Energy Budget and population model. Environ Sci Technol 42(23):8803-8808 http://dx.doi.org/10.1021/es8016599 key_lif, key_pop
  • Kooi BW, Bontje D and Liebig M (2008). Model analysis of a simple aquatic ecosystems with sublethal toxic effects. Math Biosci Eng 5:771-787 http://dx.doi.org/10.3934/mbe.2008.5.771 key_alg, key_com
  • Kooi BW, Bontje D, Van Voorn GAK and Kooijman SALM (2008). Sublethal toxic effects in a simple aquatic food chain. Ecol Modelling 112:304-318 http://dx.doi.org/10.1016/j.ecolmodel.2007.10.042 key_alg, key_com
  • Péry ARR, Gust M, Vollat B, Mons R, Ramil M, Fink G, Ternes T, Garric J (2008). Fluoxetine effects assessment on the life cycle of aquatic invertebrates. Chemosphere 73:300–304 http://dx.doi.org/10.1016/j.chemosphere.2008.06.029 key_lif
2009

  • Billoir E, Ferrao AD, Delignette-Muller ML and Charles S (2009). DEBtox theory and matrix population models as helpful tools in understanding the interaction between toxic cyanobacteria and zooplankton. J Theor Biol 258(3):380-388 http://dx.doi.org/10.1016/j.jtbi.2008.07.029 key_lif, key_pop
  • Bontje D, Kooi BW, Liebig M and Kooijman SALM (2009). Modelling long-term ecotoxicological effects on an algal population under dynamic nutrient stress. Wat Res 43:3292-3300 http://dx.doi.org/10.1016/j.watres.2009.04.036 key_alg, key_pop
2010

  • Baas J, Jager T and Kooijman SALM (2010). Understanding toxicity as processes in time. Sci Total Environ 408:3735-3739 http://dx.doi.org/10.1016/j.scitotenv.2009.10.066 key_gen
  • Baas J, Jager T and Kooijman SALM (2010). A review of DEB theory in assessing toxic effects of mixtures. Sci Total Environ 408:3740-3745 http://dx.doi.org/10.1016/j.scitotenv.2009.09.037 key_gen, key_mix
  • Heckmann LH, Baas J and Jager T (2010). Time is of the essence. Environ Toxicol Chem 29:1396-1398 http://dx.doi.org/10.1002/etc.163 key_gen, key_tim
  • Jager T and C Klok (2010). Extrapolating toxic effects on individuals to the population level: the role of dynamic energy budgets. Phil Trans R Soc B 365:3531-3540 http://dx.doi.org/10.1098/rstb.2010.0137 key_gen, key_pop, key_db3, key_lif
  • Jager T, Vandenbrouck T, Baas J, De Coen WM and Kooijman SALM (2010). A biology-based approach for mixture toxicity of multiple endpoints over the life cycle. Ecotoxicology 19:351-361 http://dx.doi.org/10.1007/s10646-009-0417-z key_gen, key_mix, key_db3, key_lif
  • Miller RJ, Lenihan HS, Muller EB, Tseng N, Hanna SK, Keller AA (2010). Impacts of metal oxide nanoparticles on marine phytoplankton. Environ Sci Technol 44(19):7329-7334 http://dx.doi.org/10.1021/es100247x key_alg
  • Muller EB, Nisbet RM and Berkley HA (2010). Sublethal toxicant effects with dynamic energy budget theory: model formulation. Ecotoxicology 19(1):48-60 http://dx.doi.org/10.1007/s10646-009-0385-3 key_lif, key_pop
  • Muller EB, Osenberg CW, Schmitt RJ, Holbrook SJ and Nisbet RM (2010). Sublethal toxicant effects with dynamic energy budget theory: application to mussel outplants. Ecotoxicology 19(1): 38-47 http://dx.doi.org/10.1007/s10646-009-0384-4 key_lif
  • Swain S, Wren J, Stürzenbaum SR, Kille P, Morgan AJ, Jager T, Jonker MJ, Hankard PK, Svendsen C, Chaseley J, Hedley BA, Blaxter M and Spurgeon D (2010). Linking toxicant physiological mode of action in with induced gene expression changes Caenorhabditis elegans. BMC Systems Biology 4:32 http://dx.doi.org/10.1186/1752-0509-4-32 key_mol, key_lif
2011

  • Ashauer R, Agatz A, Albert C, Ducrot V, Galic N, Hendriks J, Jager T, Kretschmann A, O’Connor I, Rubach MN, Nyman A-M, Schmitt W, Stadnicka J, van den Brink PJ and Preuss TG (2011). Toxicokinetic-toxicodynamic modelling of quantal and graded sub-lethal endpoints - a brief discussion of concepts. Environ Toxicol Chem 30(11):2519-2524 http://dx.doi.org/10.1002/etc.639 key_gen, key_lif
  • Billoir E, Delhaye H, Clément B, Delignette-Muller ML and Charles S (2011). Bayesian modelling of daphnid responses to time-varying cadmium exposure in laboratory aquatic microcosms. Ecotoxicol Environ Saf 74:693–702. http://dx.doi.org/10.1016/j.ecoenv.2010.10.023 key_lif
  • Eynaud Y, Nisbet RM and Muller EB (2011). Impact of excess and harmful radiation on energy budgets in scleractinian corals. Ecol Mod 222(7):1315-1322 http://dx.doi.org/10.1016/j.ecolmodel.2011.01.004 key_lif, key_alg
  • Jager T and Selck H (2011). Interpreting toxicity data in a DEB framework; a case study for nonylphenol in the marine polychaete Capitella teleta. J Sea Res 66:456-462 http://dx.doi.org/10.1016/j.seares.2011.04.003 key_gen, key_lif, key_db3
  • Massarin S, Beaudouin R, Zeman F, Floriani M, Gilbin R, Alonzo F and Pery ARR (2011). Biology-based modeling to analyze uranium toxicity data on Daphnia magna in a multigeneration study. Environ Sci Technol 45(9):4151-4158 http://dx.doi.org/10.1021/es104082e key_lif
  • Wren, JF, Kille P, Spurgeon DJ, Swain S, Sturzenbaum SR, and Jager T (2011). Application of physiologically based modelling and transcriptomics to probe the systems toxicology of aldicarb for Caenorhabditis elegans (Maupas 1900). Ecotoxicology 20:397-408 http://dx.doi.org/10.1007/s10646-010-0591-z key_mol, key_lif
  • Zaldivar JM and Baraibar J (2011). A biology-based dynamic approach for the reconciliation of acute and chronic toxicity tests: Application to Daphnia magna. Chemosphere 82(11): 1547-1555 http://dx.doi.org/10.1016/j.chemosphere.2010.11.062 key_lif, key_pop
2012

  • Augustine S, Gagnaire B, Adam-Guillermin C and Kooijman SALM (2012). Effects of uranium on the metabolism of zebrafish, Danio rerio. Aquat Toxicol 118:9-26 http://dx.doi.org/10.1016/j.aquatox.2012.02.029 key_db3, key_lif
  • Billoir E, Delhaye H, Forfait C, Clément B, Triffault-Bouchet G, Charles S and Delignette-Muller ML (2012). Comparison of bioassays with different exposure time patterns: the added value of dynamic modelling in predictive ecotoxicology. Ecotoxicol Environ Saf 75:80-86. http://dx.doi.org/10.1016/j.ecoenv.2011.08.006 key_lif
  • Biron PA, Massarin S, Alonzo F, Garcia-Sanchez L, Charles S and Billoir E (2012). Population-level modeling to account for multigenerational effects of uranium in Daphnia magna. Environ Sci Technol 46:1136−1143 http://dx.doi.org/10.1021/es202658b key_lif, key_pop
  • Jager T and Zimmer EI (2012). Simplified Dynamic Energy Budget model for analysing ecotoxicity data. Ecol. Mod. 225:74-81 http://dx.doi.org/10.1016/j.ecolmodel.2011.11.012 key_gen, key_pop, key_lif. accepted version and SI.
  • Klanjscek T, Nisbet RM, Priester JH, Holden PA (2012). Modeling physiological processes that relate toxicant exposure and bacterial population dynamics. PLoS ONE 7(2): e26955 http://dx.doi.org/10.1371/journal.pone.0026955 key_alg, key_pop
  • Klok C, Hjorth M and Dahllöf I (2012). Qualitative use of Dynamic Energy Budget theory in ecotoxicology. Case study on oil contamination and Arctic copepods. J Sea Res 73:24–31 http://dx.doi.org/10.1016/j.seares.2012.06.004 key_gen
  • Martin B, Zimmer EI, Grimm V and Jager T (2012). Dynamic Energy Budget theory meets individual-based modelling: a generic and accessible implementation. Methods Ecol Evol 3:445-449 http://dx.doi.org/10.1111/j.2041-210X.2011.00168.x key_gen, key_db3, key_pop (does not include toxicants, but can easily accommodate that!)
  • Zimmer EI, Jager T, Ducrot V, Lagadic L and Kooijman SALM (2012). Juvenile food limitation in standardized tests - a warning to ecotoxicologists. Ecotoxicology 21:2195-2204 http://dx.doi.org/10.1007/s10646-012-0973-5 key_gen, key_gro
2013

  • Holden PA, Nisbet RM, Lenihan HS, Miller RJ, Cherr GN, Schimel JP and Gardea-Torresdey JL (2013). Ecological nanotoxicology: integrating nanomaterial hazard considerations across the subcellular, population, community, and ecosystems levels. Acc Chem Res 46(3):813-822 http://dx.doi.org/10.1021/ar300069t key_gen
  • Jager T (2013). All individuals are not created equal; accounting for inter-individual variation in fitting life-history responses to toxicants. Environ Sci Technol 47:1664-1669 http://dx.doi.org/10.1021/es303870g key_gro, key_gen accepted version and SI.
  • Jager T, Barsi A and Ducrot V (2013). Hormesis on life-history traits: is there such a thing as a free lunch? Ecotoxicology 22:263-270 http://dx.doi.org/ 10.1007/s10646-012-1022-0 key_gen accepted version.
  • Jager T, Martin BT and Zimmer EI (2013). DEBkiss or the quest for the simplest generic model of animal life history. J Theor Biol 328:9-18 http://dx.doi.org/10.1016/j.jtbi.2013.03.011 key_lif, key_gen. (toxicant stress is discussed in supp. info.) accepted version and SI.
  • Klanjscek T, Nisbet RM, Priester JH and Holden PA (2013). Dynamic energy budget approach to modeling mechanisms of CdSe quantum dot toxicity. Ecotoxicology 22:319–330 http://dx.doi.org/10.1007/s10646-012-1028-7 key_alg, key_pop
  • Martin B, Jager T, Nisbet RM, Preuss TG and Grimm V (2013). Predicting population dynamics from the properties of individuals: a cross-level test of Dynamic Energy Budget theory. American Naturalist 181(4):506-519 http://dx.doi.org/10.1086/669904 key_lif, key_pop, key_db3. (does not include toxicant stress but food stress)
  • Martin BT, Jager T, Nisbet RM, Preuss TG, Hammers-Wirtz M and Grimm V (2013). Extrapolating ecotoxicological effects from individuals to populations: a generic approach based on Dynamic Energy Budget theory and individual-based modeling. Ecotoxicology 22:574-583 http://dx.doi.org/10.1007/s10646-013-1049-x key_pop, key_db3
2014

  • Barsi A, Jager T, Collinet M, Lagadic L and Ducrot V (2014). Considerations for test design to accommodate energy-budget models in ecotoxicology: a case study for acetone in the pond snail Lymnaea stagnalis. Environ Toxicol Chem 33(7):1466-1475 http://dx.doi.org/10.1002/etc.2399 key_lif
  • Jager T, Barsi A, Hamda NT, Martin BT, Zimmer EI and Ducrot V. (2014). Dynamic energy budgets in population ecotoxicology: applications and outlook. Ecol Mod 280:140-147 http://dx.doi.org/10.1016/j.ecolmodel.2013.06.024 key_gen, key_pop accepted version.
  • Jager T, Gudmundsdóttir EM and Cedergreen N (2014). Dynamic modeling of sub-lethal mixture toxicity in the nematode Caenorhabditis elegans. Environ Sci Technol 48:7026-7033 http://dx.doi.org/10.1021/es501306t key_lif, key_mix accepted version and SI.
  • Martin B, Jager T, Nisbet RM, Preuss TG and Grimm V (2014). Limitations of extrapolating toxic effects on reproduction to the population level. Ecol Appl 24(8):1972-1983 http://dx.doi.org/10.1890/14-0656.1 key_pop, key_db3
  • Muller EB, Hanna SK, Lenihan HS, Miller RJ and Nisbet RM (2014). Impact of engineered zinc oxide nanoparticles on the energy budgets of Mytilus galloprovincialis. J Sea Res 94:29–36 http://dx.doi.org/10.1016/j.seares.2013.12.013 key_lif
  • Muller EB and Nisbet RM (2014). Dynamic energy budget modeling reveals the potential of future growth and calcification for the coccolithophore Emiliania huxleyi in an acidified ocean. Global Change Biology 20(6):2031-2038 http://dx.doi.org/10.1111/gcb.12547 key_alg (deals with pH stress)
  • Zimmer EI, Ducrot V, Jager T, Koene J, Lagadic L and Kooijman SALM (2014). Metabolic acceleration in the pond snail Lymnaea stagnalis? J Sea Res 94:84-91 http://dx.doi.org/10.1016/j.seares.2014.07.006 key_db3, key_lif (does not include toxicant stress but food stress)
2015


  • Goussen B, Beaudouin R, Dutilleul M, Buisset-Goussen A, Bonzom JM and Péry ARR (2015). Energy-based modelling to assess effects of chemicals on Caenorhabditis elegans: a case study on uranium. Chemosphere 120:507–514 http://dx.doi.org/10.1016/j.chemosphere.2014.09.006 key_lif
  • Goussen B, Péry ARR, Bonzom JM and Beaudouin R (2015). Transgenerational adaptation to pollution changes energy allocation in populations of nematodes. Environ Sci Technol 49:12500−12508 http://dx.doi.org/10.1021/acs.est.5b03405 key_lif

2016


  • Cedergreen N, Nørhave NJ, Svendsen C and Spurgeon DJ (2016). Variable temperature stress in the nematode Caenorhabditis elegans (Maupas) and its implications for sensitivity to an additional chemical stressor. PLoS ONE 11(1):e0140277. http://dx.doi.org/10.1371/journal.pone.0140277 key_lif, key_mix
  • Goussen B, Price OR, Rendal C and Ashauer R (2016). Integrated presentation of ecological risk from multiple stressors. Sci Rep 6:36004 http://dx.doi.org/10.1038/srep36004 key_pop, key_mix
  • Jager T (2016). Predicting environmental risk: a road map for the future. J Toxicol Env Health Part A 79:572-584. key_gen http://dx.doi.org/10.1080/15287394.2016.1171986. (general paper on the role of TKTD models and energy budgets in risk assessment) accepted version.
  • Jager T, Ravagnan E and Dupont S (2016). Near-future ocean acidification impacts maintenance costs in sea-urchin larvae: identification of stress factors and tipping points using a DEB modelling approach. J Exp Mar Biol Ecol 474:11-17. http://dx.doi.org/10.1016/j.jembe.2015.09.016 key_gro (deals with pH stress) accepted version and SI.
  • Margerit A, Gomez E and Gilbin R (2016). Dynamic energy-based modeling of uranium and cadmium joint toxicity to Caenorhabditis elegans. Chemosphere 146:405–412. http://dx.doi.org/10.1016/j.chemosphere.2015.12.029 key_lif, key_mix

2017


  • Desforges JPW, Sonne C and Dietz R (2017). Using energy budgets to combine ecology and toxicology in a mammalian sentinel species. Scientific Reports 7:46267. http://dx.doi.org/10.1038/srep46267 key_lif
  • Miller RJ,Muller EB, Cole B, Martin T, Nisbet R, Bielmyer-Fraser GK, Jarvis TA, Keller AA, Cherr G and Lenihan HS (2017). Photosynthetic efficiency predicts toxic effects of metal nanomaterials in phytoplankton. Aquatic Toxicol 183:85-93. http://dx.doi.org/10.1016/j.aquatox.2016.12.009 key_alg
  • Lecomte-Pradines C, Hertel-Aas T, Coutris C, Gilbin R, Oughton D, Alonzo F (2017). A dynamic energy-based model to analyze sublethal effects of chronic gamma irradiation in the nematode Caenorhabditis elegans. J Toxicol Environ Health, Part A 80(16–18):830–844. https://doi.org/10.1080/15287394.2017.1352194 key_lif

2018


  • Ashauer R and Jager T (2018). Physiological modes of action across species and toxicants: The key to predictive ecotoxicology. Environ. Sci.: Processes Impacts. http://dx.doi.org/10.1039/C7EM00328E (Open Access) key_gen (review)
  • Baas J, Augustine S, Marques GM and Dorne JL (2018). Dynamic energy budget models in ecological risk assessment: from principles to applications. Sci Total Environ 628-629:249-260 https://doi.org/10.1016/j.scitotenv.2018.02.058 key_gen (review)
  • EFSA (2018). Scientific Opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) effect models for regulatory risk assessment of pesticides for aquatic organisms. EFSA journal 16(8): 5377. https://doi.org/10.2903/j.efsa.2018.5377 key_gen
  • Jager T and Ashauer R (2018). How to evaluate the quality of toxicokinetic-toxicodynamic models in the context of environmental risk assessment. IEAM 14(5):604-614. https://doi.org/10.1002/ieam.2026 key_gen (general paper on TKTD models, using GUTS as example) accepted version.
  • Murphy CA, Nisbet RM, Antczak P, Garcia-Reyero N, Gergs A, Lika K, Mathews T, Muller EB, Nacci D, Peace A, Remien CH, Schultz IR, Stevenson LM and Watanabe KH (2018). Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment. IEAM 14(5):615-624 https://doi.org/10.1002/ieam.4063 key_gen, key_mol
  • Zimmer EI, TG Preuss, S Norman, B Minten and V Ducrot (2018). Modelling effects of time-variable exposure to the pyrethroid beta-cyfluthrin on rainbow trout early life stages. Environ Sci Europe 30:36. https://doi.org/10.1186/s12302-018-0162-0 key_db3, key_gro

2019


  • Accolla C, M Vaugeois and VE Forbes (2019). Similar individual-level responses to stressors have different population-level consequences among closely related species of trout. Sci Total Environ 693, 133295. https://doi.org/10.1016/j.scitotenv.2019.07.101 key_db3, key_pop
  • Martin T, H Thompson, P Thorbek and R Ashauer (2019). Toxicokinetic−toxicodynamic modeling of the effects of pesticides on growth of Rattus norvegicus. Chem Res Toxicol 32(11):2281-2294. http://dx.doi.org/10.1021/acs.chemrestox.9b00294 key_gro
  • Muller EB, K Lika, RM Nisbet, IR Schultz, J Casas, A Gergs, CA Murphy, D Nacci and KH Watanabe (2019). Regulation of reproductive processes with Dynamic Energy Budgets. Functional Ecology 33(5):819-832. https://dx.doi.org/10.1111/1365-2435.13298 key_db3
  • Pereira CMS, K Vlaeminck, K Viaene and KAC De Schamphelaere (2019). The unexpected absence of nickel effects on a Daphnia population at 3 temperatures is correctly predicted by a dynamic energy budget individual‐based model. Environ Toxicol Chem 38(7):1423–1433. https://doi.org/ 10.1002/etc.4407 key_pop
  • Sadoul B, S Augustine, E Zimmer, ML Bégout and MM Vijayan (2019). Prediction of long-term variation in offspring metabolism due to BPA in eggs
    in rainbow trout using the DEB model. J Sea Res 143:222-230. https://doi.org/10.1016/j.seares.2018.05.011 key_db3
  • Vighi M, A Barsi, A Focks and F Grisoni (2019). Predictive models in ecotoxicology: bridging the gap between scientific progress and regulatory applicability - remarks and research needs. IEAM 15(3):345-351. https://dx.doi.org/10.1002/ieam.4136 key_gen (review)
  • Vlaeminck K, KPJ Viaene, P Van Sprang, S Baken and KAC De Schamphelaere (2019). The use of mechanistic population models in metal risk assessment: combined effects of copper and food source on Lymnaea stagnalis populations. Environ Tox Chem 38(5):1104-1119. https://dx.doi.org/10.1002/etc.4391 key_db3, key_pop

2020


  • Accolla C, M Vaugeois, P Rueda-Cediel, A Moore, GM Marques, P Marella and VE Forbes (2020). DEB-tox and data gaps: consequences for individual-level outputs. Ecol Modell 431:109107. https://doi.org/10.1016/j.ecolmodel.2020.109107 key_db3
  • Ashauer R, R Kuhl, E Zimmer and M Junghans (2020), Effect modelling quantifies the difference between the toxicity of average pesticide concentrations and time‐variable exposures from water quality monitoring. Environ Toxicol Chem 39(11):2158-2168. https://doi.org/10.1002/etc.4838 key_tim
  • Goussen B, C Rendal, D Sheffield, E Butler, OR Price and R Ashauer (2020). Bioenergetics modelling to analyse and predict the joint effects of multiple stressors: meta-analysis and model corroboration. Sci Total Environ 749:141509. https://doi.org/10.1016/j.scitotenv.2020.141509 key_mix, key_lif (Open Access)
  • Jager T (2020). Revisiting simplified DEBtox models for analysing ecotoxicity data. Ecol Modell 416:108904. https://doi.org/10.1016/j.ecolmodel.2019.108904 key_gen accepted version and SI.
  • Matyja K, J Rybak, B Hanus-Lorenz, M Wróbel and R Rutkowski (2020). Effects of polystyrene diet on Tenebrio molitor larval growth, development and survival: Dynamic Energy Budget (DEB) model analysis. Environmental Pollution (in press). https://doi.org/10.1016/j.envpol.2020.114740 key_gro
  • Sherborne N and N Galic (2020). Modelling sublethal effects of chemicals: application of a simplified dynamic energy budget model to standard ecotoxicity data. Environ Sci Technol 54(12):7420-7429. https://doi.org/10.1021/acs.est.0c00140 key_gen
  • Sherborne N, N Galic and R Ashauer (2020). Sublethal effect modelling for environmental risk assessment of chemicals: problem definition, model variants, application and challenges. Sci Total Environ 745:141027. https://doi.org/10.1016/j.scitotenv.2020.141027 key_gen
  • Vaugeois M, PA Venturelli, SL Hummel, C Accolla and VE Forbes (2020). Population context matters: Predicting the effects of metabolic stress mediated by food availability and predation with an agent- and energy budget-based model. Ecological Modelling 416:108903. https://doi.org/10.1016/j.ecolmodel.2019.108903 key_pop, key_db3
  • ...

2021


  • Gergs, A, J Hager, E Bruns and TG Preuss (acc.), Disentangling mechanisms behind chronic lethality through toxicokinetic‐toxicodynamic modelling. Environ Toxicol Chem. Accepted Manuscript. https://doi.org/10.1002/etc.5027 key_gro, key_tim, key_db3
  • Jager, T, M Trijau, N Sherborne, B Goussen and R Ashauer (2021). Considerations for using reproduction data in toxicokinetic-toxicodynamic modelling. Preprint deposited at bioRxiv: https://doi.org/10.1101/2021.05.03.442410 key_gen
  • Koch, J and KAC De Schamphelaere (2021), Making sense of life‐history effects of the antidepressant citalopram in the copepod Nitocra spinipes using a bioenergetics model. Accepted in Environ Toxicol Chem. https://doi-org.vu-nl.idm.oclc.org/10.1002/etc.5044 key_db3
  • Schultz CL, S Bart, E Lahive and DJ Spurgeon (acc.). What is on the outside matters - surface charge and dissolve organic matter association affect the toxicity and physiological mode of action of polystyrene nanoplastics to C. elegans. Accepted for publication in Environ Sci Technol. https://doi.org/10.1021/acs.est.0c07121 key_lif 
  • Vlaeminck K, KPJ Viaene, P Van Sprang and KAC De Schamphelaere (2021). Development and validation of a mixture toxicity implementation in the dynamic energy budget–individual‐based model: effects of copper and zinc on Daphnia magna populations. Environ Toxicol Chem 40(2):513-527. https://doi.org/10.1002/etc.4946 key_lif, key_mix
  • ...



The DEBtox information site, www.debtox.info, since July 2011