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Practical part of the DEB course 2011 in Lisbon; online versionSun 3 April

19:00 Reception at IST

Mon 4 (4 lect, 2.5 exer, 1 grp disc)09:00 PA2 Bas 1 chap 1,2: summary of tele-part10:00 PA2 Bas 2 chap 2,3,4,8: scaling, par estim11:00 Coffee11:30 V134 Exercises12:30 V134 Exercises13:30 Lunch14:30 PA2 Tiago 1: structure DEB theory15:30 PA2 Tiago 2: DEB theory in context16:30 Tea17:00 V125 grp discussion18:30 end

Tue 5 (4 lect, 2.5 exer, 1 grp disc)09:00 V004 Laure 1 chap 3,4: auxiliary theory10:00 V004 Mike chap 4: biophysical ecology11:00 Coffee11:30 V004 Exercises12:30 V004 Exercises13:30 Lunch14:30 PA2 Tania chap 4: thermodynamics15:30 PA2 Goncalo chap 5: multivar DEBs16:30 Tea17:00 E8 grp discussion18:30 end

Wed 6 (3 lect, 3.5 exer, 1 grp disc)09:00 PA2 Dina chap 4: covariation method10:00 F4 Tjalling 1 chap 6: toxico-kinetics11:00 Coffee11:30 F8 Exercises12:30 F8 Tjalling 2 chap 6: survival + aging13:30 Lunch14:30 V004 Exercises15:30 V004 Exercises16:30 Tea17:00 V004 grp discussion18:30 end

Thu 7 (3 lect, 2.5 exer, 1 grp + 1 plen disc)09:00 F3 Tjalling 3 chap 6: sublethal effects10:00 F3 Tjalling 4 chap 6: mixtures, QSARs11:00 Coffee11:30 F8 Exercises12:30 V004 grp discussion13:30 Lunch14:30 PA2 plenary discussion15:30 PA2 Laure 2 chap 4: reconstruction16:30 Tea17:00 V004 Exercises18:30 end

Fri 8 (3 lect, 3.5 exer, 1 grp disc)09:00 V004 Tjalling 5 chap 6: ind → population10:00 V004 Jaap 1 chap 9.2: unstructured pop dynamics11:00 Coffee11:30 V004 Exercises12:30 V004 Jaap 2 chap 9.2: structured pop dynamics13:30 Lunch14:30 V004 Exercises15:30 V004 Exercises16:30 Tea17:00 V004 grp discussion18:30 end19:30 dinner Cervejaria da Trindade Chiado

Sat 9 (1 lect, 1 grp disc)09:00 C22 Roger 1 chap 9.1: trophic interactions10:00 C22 grp discussion11:30 leave for lunch12:00 Lunch13:00 Excursion

Mon 11 (2 lect, 3 exer, 1 grp + 1.5 plen disc)09:00 PA2 Bob chap 9,10: adaptive dynamics10:00 PA2 Roger 2 chap 9.3: food chain & webs11:00 Coffee11:30 V134 Exercises12:30 F4 grp discussion13:30 Lunch14:30 P8 Exercises15:30 P8 Exercises16:30 Tea17:00 PA2 plenary discussion18:30 end

Tue 12 (0 lect, 3 exer, 3.5 pet, 1 grp disc)09:00 F8 Exercises10:00 F8 grp discussion11:00 Coffee11:30 V134 Exercises12:30 V136 Exercises13:30 Lunch14:30 PA2 Add my pet 115:30 PA2 Add my pet 216:30 Tea17:00 E8 Add my pet 318:00 E8 Add my pet 418:30 end

Coffee and tea will be held at the coffee room. Lunch will be held at the cafeteria

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south

north

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Participants with Matlab/Octave, pets

Maria Joao Almeida − Arturo Aguirre Velarde − Argopecten purpuratusSophie Arnall M Pseudemydura umbrina Roman Ashauer −Fariba Assadi-Porter − Starrlight Augustine M Danio rerioAurora Baluja O Alpar Barsi O Lymnaea stagnalisPierre-Albin Biron O Nicholas Colvard M Fucus gardneriSara Cruz M Escherichia coli Alessandro Dagnino −Ida Dolciotti O Tiago Domingos +Francesco Dondero − Virginie Ducrot M Lymnaea stagnalisMarie Eichinger − Yoan Eynaud M Acipenser ruthenusLorna Fassler-Teal O Solea solea Ramon Filgueira − Mytilus edulisJonathan Flye O Perna viridis Vania Freitas O Pleuronectus platessaBeatrice Gagnaire M Nika Galic −Andre Gergs − Jorge Gonzalez − Rattus norvegicusBenoit Goussen M Caenorhabditis elegans Soraia Gradvohl −Volker Grimm − Natnael Hamda MTessa vd Hammen M Limanda limanda Shannon Hanna M Mytilus galloprovincialisLianne Jacobson − Tjalling Jager M Folsomia candidaFred Jean O Argopecten purpuratus Dragan Jevtic MLeah Johnson − Tiphaine J. du Dot O Callorhinus ursinusMarko Jusup M Thunnus orientalis Michael Kearney O Sceloporus undulatusTin Klanjscek − Bob Kooi +Bas Kooijman + Bob Laarhoven M Lumbriculus variegatusRomain Lavaud O Pecten maximus Ryszard Laskowski −Sam Lew M Crangon crangon male Dina Lika MAntonio Lorena − Kimberley Louwrens −Frederico Lyra − James Maino M Drosophila melanogasterNina Marn M Goncalo Marques OAdrian Martin − Benjamin Martin O Daphnia magnaJaap van der Meer O Anguilla anguilla Cristian Monaco M Pisaster ochraceusClaudia Moreira − Erik Muller −Roger Nisbet M Valeria Palmeri MLaure Pecquerie M Oncorhynchus tshawytscha Heidi Pethybridge M Engraulis encrasicolusDelphine Plaire M Daphnia magna Jean-Christ. Poggiale −Maria Pozimski − Anopheles gambiae Warren Porter −Mofiz Rahman M Elisa Ravagnan M Maganyctiphanes norvegicaJessica Roberts − Gabriel Rodriguez −Filipa Roque M Saccharomyces cerevisiae Ilenia Saggese −Gianluca Sara M Sofia Saraiva M Mytilus edulisCamille Saurel M Tania Sousa +Julita Stadnicka O Pimephales promelas Louise Stevenson M Daphnia pulexJoseph Stover − Carlos Teixeira MKoji Tominaga O Esox lucius Ioannis Tsirigotakis −Maxime Vaugeois M Carolina Vogs −Andreas Waser O Carcinus maenas James Watson −Kelly Weinersmith − Elke Zimmer M Gammarus pulex

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Exercises (22 h)

We assume basic experience with Matlab/Octave and that you used DEBtool a few timesduring the tele-course. We will have 10 groups of 5 persons. Assistance is provided by

Mike, Tjalling, Laure, Goncalo, Dina, Sofia, Carlos, Jaap, Starrlight, Fred, JonathanTania, Tiago and Bas run around to solve any problems that might occur.

Add my pet (16 h) First complete the add my pet exercise with a set of parametersthat you evaluate.

mydata-file (0.5 h) This file has been prepared during the tele-part of thecourse. Discuss with your assistant the best way to compose a predict file; thisdepends on the type of data that you have (zero- versus univariate, etc).

predict-file (1.5 h) Writing a predict file should be relatively little work, usingthe copy-paste technique from statistics.

parameter estimation (4 h) First out-comment the estimation and varianceand goodness-of-fit mark computation.Then select starting values such that predictions are not too far off.Try to understand how the values affect the result.Then activate the estimation, releasing first some of the more uncertain parameters,then release more.Try to understand you your data determine the parameter values;don’t release parameter values about which your data don’t have information.Then activate variance and goodness-of-fit mark computation.Copy the results in a pars-file, together with the fit and the completeness mark.

pars-file (3 h) Run the pars-file and study the values of the 100 implied prop-erties.In the case of odd results, try to repair the problem by changing weight coefficientsin the mydata-file, or add more (pseudo)-data.

DEBtool graphs (2 h) Run the graphics routines, as called by DEBtool/animal/animal,and study the graphs. In the case of odd results, try to repair the problem by chang-ing weight coefficients in the mydata-file, or add more (pseudo)-data.

evaluation note (5 h) Write a short evaluation note and submit it, togetherwith the mydata-, predict- and pars-files.

Exercises of the DEB book (6 h) Continue with the exercises you possibly alreadyhave made during the tele-part or try a second species.

Group discussions (8h)

We will have 5 groups of about 10 persons, chaired byMike, Tjalling, Laure, Goncalo and Dina

Jaap will replace Dina as chairman on Monday and Tuesday. He, Tania, Tiago and Bas

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visit the groups and try to cross-link. The chair(wo)man appoints a reporter, who willserve for 5 min in the plenary discussions.

In each hour, 2 participants have a 10 min presentation on the problem that theysubmitted in 0.5 A4 at the end of the tele-part, followed by a 10 min discussion perpresentation. The notes are available in a document at the start of the L-course. Theremaining time (some 10 min per hour) we discuss

4-7 April MTE versus DEB

West, G. B., Brown, J. H. and Enquist, B. J. (2001) A general model for onto-genetic growth. Nature 413: 628-631

Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M. and West, G. B. (2004)Toward a metabolic theory of ecology. Ecology 85: 1771-1789

Meer, J. van der (2006) Metabolic theories in ecology. Trends in Ecology &Evolution 21: 136-140

Hou, C., Zuo, W., Moses, M. E., Woodruff, W. H., Brown, J. H. and West, G.B. (2008) Energy Uptake and Allocation During Ontogeny. Science 322: 736–739

Sousa,T., Marques, G. M. and Domingos, T. (2009) Comment on Energy Uptakeand Allocation During Ontogeny. Science 325: 1206-b

Zuo,W., Moses, M. E., Hou, C., Woodruff, W. H., West, G. B. and Brown, J. H.(2009) Response to Comments on Energy Uptake and Allocation During Ontogeny.Science 325: 1206-c

Kearney, M. R. and White, C. R. (2011) Testing metabolic theories in ecology.Submitted

Price, C. A.,6, Gillooly, J. F. and Allen, A. P., Weitz, J. S. and Niklas, K. J.(2010) The metabolic theory of ecology: prospects and challenges for plant biology.New Phytologist 188: 696-710

8 - 11 April The maturity concept or the separation and nature of reserve and structure.The Santa Barbara-group rises some discussion questions in this pdf-file

12 April course evaluation (tele and Lisbon parts)

The reporters will summarize the findings of these discussions in the plenary discussion.

Plenary discussions (2h)

The 5 reporters of the discussion groups report at the plenary session for 5 min each,leaving some 30 min for discussion with all of the participants simultaneously.

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Pet presentations (4h)

We ask 4× 6 reporters to give a 10-min presentation of the evaluation notes, which mightinclude a trouble report. So each reporter will discuss one (his/her own) or two evaluationnotes. If time allows we (Dina, Laure, Jaap, Bas) will compare the parameter values andgive a short presentation of the findings.

Essays of the DEB course 2011

Maria Almeida The DEB of Carcinus.

Kimberley Louwrens An evaluation of two controversial metabolic theories of ecology.

Claudia Moreira The DEB of the brown shrimp.

Valeria Palmeri The DEB model as tool tp predict ecological responses of Brachidontespharaonis.

Maria Pozimski DEB from the outside.

Jess Roberts Applying Dynamic energy Budget (DEB) theory to kangaroo energetics.

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Lectures (20 h)

Bas Kooijman 2011/04/04/09

Summary of the DEB-tele course 2011

I will not just summarize the material of the tele-part of the course, but

• focus on concepts

• discuss the function of these concepts in the theory

• compare these concepts with alternatives that can be found in the literature

Topics:

• Strong & weak homeostasis: supply-demand spectrum

• Effects of temperature

• Macrochemical reaction equations: conservation of chemical elements

• Synthesizing Units for transformations & behaviour: time conservation

• Turnover of pools, residence times: stomach & gut, reserve, structure & somaticmaintenance

• Maturation & maturity maintenance

• Changes in shape & size control: V0-, iso, V1-morphy; von Bertalanffy

• Stochastic version of the standard DEB model

Bas Kooijman 2011/04/04/10

Covariation & estimation of parameter values

Topics:

• scales of life in space & time

• intra- vs inter-specific comparisons

• primary vs compound parameters Lm, [Em], Pow, K

• Covariation of parameter values

intensive & extensive parameters

functions of parameters: body weight feeding rate respiration von Bertalanffygrowth rate reserve residence time reproduction rate population growth rate

• what parameters can be estimated from what data?

• pseudo vs real data

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Tiago Domingos 2011/04/04/14:30

The structure of DEB theoryBuilding on a recent axiomatic formalisation of DEB theory (Sousa, T., T. Domingos,

S. A. L. M. Kooijman, 2008, From empirical patterns to theory: A formal metabolic theoryof life, Philosophical Transactions of the Royal Society of London B 363: 24532464), herewe show that DEB theory can be built from

1 the fundamental thermodynamic constraints that all processes obey mass and energyconservation but lead to entropy production,

2 a physical assumption of quite general applicability, that local flows are proportionalto differences in intensive variables (and, hence, total flows are proportional to surfaceareas),

3 a biological assumption, that cells are metabolically very similar, independently ofthe organism or its size, and,

4 in a systems theory type of approach, an application of Occams razor, in alwayschoosing the simplest possible formulation of a mathematical theory (minimize thenumber of state variables; choose linear over non-linear functions; minimize the num-ber of parameters).

Having condensed DEB theory in this compact definition, we then show how thesefundamental assumptions lead to the strong and weak homeostasis principles, and thento partitionability of reserve dynamics and the reserve dynamics itself. With this, weobtain the von Bertallanfy growth curve and Kleibers rule, for intra- and inter-specificcomparisons.

Tiago Domingos 2011/04/04/15:30

DEB theory within a general scientific contextIn contrast to what have been frequent statements in the ecological literature, DEB

theory has shown that it is possible to obtain a unified mathematical theory for biology,similar to physical theories. At the same time, DEB has attained this aim by establishing atheory which is compatible with physical constraints, again something which is frequentlydisregarded in biology, thus ensuring Edwards Wilsons aim of consilience between thesciences.

Thermodynamic constraints must be obeyed, but are not enough to build theories inbiological and social systems. This is the underlying cause for two major divisions in twoscientific areas: Ecology and Economics. In Ecology, it is the division between Ecosystemand Physiological Ecology, where the accounting units are energy and mass flows, andPopulation and Community Ecology, where the accounting unit is number of individuals.In Economics, it is the division between Ecological Economics (a clear minority), based onenergy and mass flows, and Neoclassical economics (the mainstream), based on utility andprofit.

In this lecture, we address how DEB theory contributes to addressing these issues,placing it within a general context of philosophy of science (reviewing the epistemological

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theories of Popper, Kuhn and Lakatos), of the role of (mathematical) theory in science,and of the dichotomy between fundamental and applied science. Within this context,we then point to future directions for the DEB research program, introducing the recentapplication by a team of DEB scientists to the European Unions International TrainingNetwork program. This project is called THE ECONSILIENT: Training Researchers forConsilience in Addressing Complex Ecological Problems - The Case of Biodiversity andEcosystem Services.

Tania Sousa 2011/04/05/14:30

Thermodynamical aspects of DEB theoryThe topics of my lecture are:

1 Chemical composition of structure, reserve and biomass

2 Organic and mineral chemical compounds in the organism.

3 Aggregated chemical transformations in the organism.

4 Mass, energy and entropy balance equations. Parameters yV E, yXE and yPE.

5 Mass, energy, heat and entropy production fluxes in the organism.

6 Indirect calorimetry.

Laure Pecquerie 2011/04/05/09

Linking DEB variables to data:1 Essential step preceding parameter estimation

To apply DEB theory to a particular question and a particular organism, we first needto define the link between DEB predictions and our measurements. DEB variables cannotbe measured directly and we need additional assumptions to make this link between modelvariables and data. This additional set of assumptions is defined as an auxiliary theorythat is distinct from the core theory. This auxiliary theory can be species- specific. We aregoing to review which questions should be address when defining such an auxiliary theory.It is an essential step preceding the estimation of DEB parameters.

Mike Kearney 2011/04/05/10

Biophysical ecologyThe energy budgets of organisms are intimately connected to the flow of heat to and

from their environments. First, rates of metabolism are highly sensitive to body temper-ature, which varies with environmental conditions in most organisms. Second, metabolicprocesses also produce heat and in endothermic species substantial energy is invested toregulate body temperature. Finally, heat balance is directly tied to water balance throughrespiratory and cutaneous evaporation. The principles of biophysical ecology permit quan-tification of heat fluxes in organisms and their consequences for energy budgets. In thislecture I will provide a brief introduction to the principles of biophysical ecology and howthey can be integrated with Dynamic Energy Budget theory. Biophysical ecology provides

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an important set of tools for tying the energy budgets of organisms to environmental gra-dients and can lead to powerful inferences about a species’ ecology, including constraintson its behaviour, population dynamics and geographic range.

Literature:

Porter W.P. & Gates D.M. (1969). Thermodynamic equilibria of animals with environ-ment. Ecological Monographs, 39, 227-244.

Gates D.M. (1980). Biophysical Ecology. Springer Verlag, New York.

Campbell G.S. & Norman J.M. (1998). Environmental Biophysics. Springer, New York.

Porter W.P. & Kearney M. (2009). Size, shape, and the thermal niche of endotherms.Proceedings of the National Academy of Sciences, 106, 19666-19672.

Kearney M. & Porter W.P. (2009). Mechanistic niche modelling: combining physiologicaland spatial data to predict species’ ranges. Ecology Letters, 12, 334-350.

Goncalo Marques 2011/04/05/15:30

Generalization of the standard DEB model for multiple state variablesThe standard DEB model is built with one reserve, one structure, one maturity and

one reproduction buffer for an organism that feeds on one substrate. There are situationswhen the standard DEB model is not enough to realistically simulate an organism or aspecific feature of an organism. However DEB theory gives us the tools to build modelsbeyond the standard DEB model. The construction of the generalized DEB models willbe the theme of this presentation. The topics will be:

1 Quick review of what is a state variable and what defines each class of state variables

2 Multiple substrates

3 Multiple reserves

4 Multiple structures

5 Does it make sense to talk about multiple maturities?

6 Multiple products

Dina Lika 2011/04/06/09

Covariation method for parameter estimationThe Dynamic Energy Budget (DEB) theory for metabolic organisation captures the

processes of development, growth, maintenance, reproduction and ageing for any kind oforganism throughout its life-cycle. However, the state variables and the parameters cannotbe measured directly. This poses challenges for applying the theory and for comparativeanalysis because, until now, the estimation of some parameters requires very specific datathat is not commonly available for most taxa in the literature. The covariation methodis a new approach to estimate all parameters of the standard DEB model simultaneouslyfrom a collection of common empirical measurements. Apart from the real data, theestimation method makes use of pseudo-data, exploiting the rules for the covariation of

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parameter values among species that are implied by the standard DEB model. My lecturewill include

1 a brief discussion of the variables and parameters of the standard DEB model andthe rules for the covariation of parameter values

2 the covariation method for estimation based on the weighted least squares criterionand

3 supporting software DEBtool and practical use of the estimation method.

Tjalling Jager 2011/04/06/10

Chemical (and other) stress in DEB. 1) IntroductionToxicity is an inherent part of life; all chemicals are toxic to some extent, and many

organisms synthesise or accumulate chemicals, e.g., to protect themselves against predators,or to poison their prey. In the first lecture of this series, I will introduce the topic of chemicalstress on organisms. To understand stress effects, we first need to understand the unstressedsystem. Stress is than simply a particular deviation from the unstressed situation. Theenergy budget is a particularly useful level of detail, as it deals with the quantitative aspectsof life-cycle traits such as growth and reproduction, and the connections between them.Chemical effects can be seen as a disruption of the normal functioning of an organism, andneed to be considered without violating conservation of mass and energy.

Topics covered in this lecture:

• Examples of chemical use by organisms.

• Man-made chemicals and how they differ from natural ones.

• The normal approach in ecotoxicology.

• The natural role of DEB theory to address ecotoxicological questions.

• Brief history of toxic effects in DEB models.

Tjalling Jager 2011/04/06/12:30

Chemical (and other) stress in DEB. 2) ToxicokineticsBefore a chemical can exert a toxic effect on the individual, the chemical first needs to

be taken up into the organism. The processes of uptake, redistribution, metabolism andexcretion are collectively knows as toxicokinetics (TK). Toxicokinetic models thus providethe link between (time-varying) concentrations in the environment and the time course ofthe internal concentration (in the whole organism or in specific organs). In this lecture,I will discuss how TK can be integrated into DEB theory, starting from the simplest TKmodel possible, and progressing towards more realism.

Topics covered in this lecture:

• Starting simple: one-compartment behaviour and diffusion.

• Adding some realism: accounting for growth.

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• Consistent application of DEB principles: the influence of reserves, reproductionbuffer, and reproduction on TK.

• TK for the developing embryo.

• More complications: toxicants in soil or sediment, and the influence of feeding.

Tjalling Jager 2011/04/07/09

Chemical (and other) stress in DEB. 3) the target site and effects on survival

Chemicals inside the organism interact with the internal physiology, and affect metabolism.The first step is to choose the most useful dose metric; how is exposure to the chemicalbest expressed? The classic dose metric in ecotoxicology is the external concentration.However, it is well accepted that this metric has a poor connection to the observed effects.Internal concentrations are usually a better choice, but which internal concentration? Forsome chemicals, the whole-body concentration might be a good representation, but forothers, the concentration in some organ might be more appropriate. Furthermore, manychemicals interact with specific receptors, which in turn lead to toxic effects. For suchcompounds, receptor occupation can be more appropriate than an internal concentration,which thus requires an additional model. The dose metric can subsequently be linked tothe value of one or more DEB parameters. This will be illustrated with the simplest effectmodel in the DEBtox family; the model for effects on survival in non-growing organisms.

Topics covered in this lecture:

• Target sites and appropriate dose metrics.

• Target sites are linked to DEB parameters.

• A simple hazard approach for effects on survival.

• Relationships between model parameters.

• A receptor example: acetyl cholinesterase inhibition.

• Ageing as effect of compounds.

Tjalling Jager 2011/04/07/10

Chemical (and other) stress in DEB. 4: effects on the energy budget

Toxic effects do not only lead to mortality; also sub-lethal effects occur. Examples are adecrease in growth rate, a smaller ultimate size, delay of the start of reproduction, decreasein reproduction rate, or effects on offspring size. In the previous lecture, the dose metricwas linked to the hazard rate. Now, I will extend this approach to more, in principle all,DEB parameters. A change in each DEB parameter has a specific set of consequencesfor the organisms life cycle. Indeed, over the years we have managed to explain observedeffects patterns on growth and reproduction by changes in specific DEB parameters. Inthis lecture, I will present a few examples, and illustrate the approach taken to identifyaffected parameters.

Topics covered in this lecture:

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• Target sites are linked to DEB parameters, and different chemicals affect differentparameters.

• The effect on a DEB parameter causes recognisable effect patterns on life-historytraits.

• Examples and case studies.

Laure Pecquerie 2011/04/07/15:30

Linking DEB variables to data:2 Reconstructing environmental conditions experienced by an individual

Tjalling Jager 2011/04/08/09

Chemical (and other) stress in DEB. 5: extrapolationsExplaining the observed effects observed in a controlled laboratory experiment is scien-

tifically quite interesting, but not so useful for environmental risk assessment. We do notwish to protect organisms in the laboratory, but rather those in the real world. In reality,organism that we are interested in are often of a different species than we have tested,they live in a population, and are exposed to a cocktail of chemicals, also encounter otherstresses such as food limitation and parasites, etcetera, etcetera. The power of mechanistictheories lies in their ability to make predictions about untested situations. In this lecture,I will illustrate several extrapolation steps with examples.

Topics covered in this lecture:

• Why extrapolation is necessary.

• Examples of extrapolation; individual to population, high to low food, mixture tox-icity, constant to time-varying exposure, one species to another, one chemical toanother.

Further reading: If you are interested in the effects of toxicants in a DEB context, andwant to read more: check out the list of papers.

Jaap van der Meer 2011/04/08/10

Introduction to population dynamicsMost simple theoretical population models in continuous time relate the rate of change

of the size of one or two populations by means of a (coupled set of) non-linear differentialequation(s) to the population size itself. Mathematical analysis of such equations merelyfocuses on the stability of the equilibria. In the first lecture I introduce several well-knownmodels, such as the logistic growth model and the Lotka-Volterra predator-prey model,and discuss the mathematical tools needed for their stability analysis. I start with a singlehomogeneous linear differential equation and via a non-linear equation, a coupled set of twolinear differential equations, I finally arrive at a set of two non-linear differential equations,with the Lotka-Volterra model as the main example.

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Jaap van der Meer 2011/04/08/12:30

DEB-structured population dynamics

In the second lecture I introduce population models based on Dynamic Energy Budget(DEB) theory for a specific group of organisms, called V1-morphs, whose assimilation rateand maintenance rate are both thought to be related to their volume. As such, these popu-lation models do not require the introduction of size-structure and V1-morphs are thereforemuch easier to handle than isomorphs, for which size-structured population models are theappropriate approach. DEB theory assumes that assimilation rate of isomorphs is relatedto their surface-area, whereas maintenance rate is related to volume, for which reasonsize-structure plays such important role in their population energetics. As a specific ex-ample, I compare the DEB model for a substrate eating V1-morph in a chemostat, with aLotka-Volterra type model.

Roger Nisbet 2011/04/09/09

Introduction to ecosystem processes

The term ecosystem will be introduced, and some general problems described. I shallreview some empirical information, and then introduce the key abstractions used in currentand emerging (non-DEB) ecological theory for ecosystems. I shall define trophic levels andillustrate the limitations of the concept. The main dynamic properties of standard modelsof food chains will be summarized with reference to trophic cascades. There will be a(very) brief review of the stabilizing effects of material cycling. The lecture will end byasking how DEB theory can further advance the theory and what are the impediments.

Reference: Any introductory ecology text book (background) plus chapter 7 of EcologicalDynamics by W.S.C. Gurney and R.M. Nisbet (for dynamics)

Bob Kooi 2011/04/11/09

Adaptive dynamics of DEB structured systems & bifurcation theory

In ecosystem models parameters describing rates of physiological processes in popula-tions, such as growth, reproduction and mortality, are taken constant. Due to mutationsthese parameters can change at an evolutionary time scale and are then called traits.Generally, in adaptive dynamics this evolutionary time scale is assumed to be much slowerthat the ecological time scale. This means that the next mutation occurs when the changescaused by the previous one are gone. In this lecture the competition between the residentand the mutant population is formulated in the context of nonlinear dynamical systemstheory. Competition takes place in the environment of the populations set by the ecosys-tem. Then, the evolutionary dynamics of a population can be studied by the calculation oftranscritical bifurcations of stationary states of a system (for instance equilibrium of limitcycle) consisting of the competing populations. A sequence of evolutionary steps can leadto trait values where the population is uninvadable by any mutant population. This givesdirectly stable strategy trait values.

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The link between AD and DEB was investigated by Tineke Troost reported in a numberof papers:

Troost, T.A., Kooi, B.W. & Kooijman, S.A.L.M. 2005. When do mixotrophs specialize?Adaptive dynamics theory applied to a dynamic energy budget model. Math. Biosci.,193(2): 159-182.

Troost, T.A., Kooi, B.W. & Kooijman, S.A.L.M. 2005. Ecological specializaton of mixotrophicplankton in a mixed water column. The American Naturalist, 166(3): E45-E61.

Kooi, B.W. & Troost, T. 2006. Advantages of storage in a fluctuating environment. The-oretical Population Biology, 70(4):527-541.

Troost, T.A., Kooi, B.W. & Kooijman, S.A.L.M. 2007. Bifurcation analysis of ecologicaland evolutionary processes in ecosystems. Ecological Modelling, 204:253-268.

Troost, T.A., Kooi, B.W. & Dieckmann, U. 2008. Joint evolution of predator body sizeand prey-size preference. Evolutionary Ecology, 22:771-799.

Troost, T.A., Dam, J.A. van, Kooi, B.W., & Tuenter, E. 2009. Seasonality, climate cyclesand body size evolution. Mathematical Modelling of Natural Phenomena, 4(6): 137-157.

Kooi, B.W. & J. van der Meer, 2010. Bifurcation theory, adaptive dynamics and DEB-structured populations of iteroparous species. Philosophical Transactions of the RoyalSociety, 365:3579-3590.

Roger Nisbet 2011/04/11/10

DEB theory for ecosystemsDEB theory offers a systematic approach to describing species interactions, especially

some forms of symbiosis. The methodology involves no new principles - just very carefulwork with energy and mass balance equations, and precise assumptions about stoichiometry(through macrochemical equations). The same principles allow representation of simpleconsumer-resource interactions (e.g. prey eats predator), as well as more complex symbioseslike those leading to apparent ’photosynthetic animals’ such as corals or giant clams. Onceinteractions are defined more hard work can lead to complete ecosystem models (e;g thecanonical community in section 9.4 of DEB3). The lecture will end with a list of challengesfacing future researchers in this area.

Reference: sections 9.1 and 9.4 of DEB3. Possible reference to model in Troost et al.Mathematical Biosciences 193 (2005) 159182. Students will be expected to memorizeTables 9.2 and 9.6 of DEB3 and explain them to the instructor after a glass of good wine.

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Discussion contributions

Sophie Arnall

The western swamp tortoise (Pseudemydura umbrina) is a species that, like many others, isat the mercy of the environment. Not only is it ectothermic, but it has two separate states ofdormancy in its life that are influenced by environmental conditions. Firstly, as an embryo,a drop in air temperature (nest temperature) causes cessation of diapause and subsequenthatching from the egg. Secondly, rainfall during autumn or winter fills the ephemeralswamps that these tortoises inhabit, triggering the end of an annual summer aestivationperiod that adults and juveniles complete during each year of their life. Both periods ofdormancy therefore have no fixed length, and are driven by environmental conditions. Inparticular, rainfall plays a major role as it determines the how long the swamps stay full ofwater and food (these tortoises are carnivorous, feeding on aquatic prey). Higher rainfallleads to a longer hydro-period, allowing a greater length of time for the tortoises to feedand to accumulate energy before the swamps dry out and they must leave for aestivation.As such, environmental conditions and energy availability are strongly tied.

Energy availability is a very important driver of population success in this species. Forrecruitment to occur there must be two good environmental rainfall years - in the first yearthe female must gain enough energy to produce eggs (fill the egg buffer/provide reserve)and in the second year the hatchlings must accumulate enough energy to reach a criticalmass that will allow them to survive their first summer aestivation period. For thesereasons, DEB theory is particularly relevant to understanding the population dynamics ofthis species. I hope to be able to couple DEB theory to mechanistic niche modelling, tobe able to predict the survival, growth rates, and reproductive success of western swamptortoises under both current and future climates. In order to do this I wonder, how dowe accurately quantify variable parameters and real data (such as ’age at birth’) that areinfluenced by fluctuating environmental conditions? How can we parameterize periods ofdormancy (4.1.7), and to what extent will periods of dormancy influence our ability toconstruct past trajectories (body temperature, respiration rates and food availability arenot constant and deviate from von Bertalanffy growth; 4.11)? I hope we can discuss thesepoints so that I can better understand how to apply DEB theory to this species, and decidewhat experimental methods may best compliment the application of DEB theory to thewestern swamp tortoise.

Starrlight Augustine

At present, the general tendency is to use nuclear power as main energy source to meetcurrent industrial and societal demand. Uranium, an element belonging to the actinidefamily, is found in most rivers and lakes. Human activities linked to the nuclear fuelindustry bring up background levels which may be detrimental to the health of aquaticorganisms. My research project focusses on the chemical toxicity of uranium on zebrafish,Danio rerio.

I dedicated the first part of my project to making a functional model of zebrafish

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metabolism which gives realistic quantitative predictions of growth, reproduction and res-piration at different levels of food intake and temperatures. The add my pet exerciseduring the DEB telecourse of 2009 was great incentive to do this and laid the foundationsfor this work. The next natural step is to use these quantitative predictions to detectmetabolic deviations which are induced by the presence of uranium in the environment.DEB theory provides solid methodologies to do this (Chap 6). However I wish to bring upthe questions I have on the subject.

1 I have followed individual growth and reproduction of 20 fish exposed to three levelsof uranium (0, 20 and 100µg). However not all of the fish reproduced, and thisis a rather typical situation. So if I work with mean reproductive output I haveenormous standard deviations because values range from zero to hundreds. If I workwith individual fish only then I must explain why some of the fish did not reproduce.I was wondering if some methods exist which deal with this situation.

2 An empirical observation is that (i) zebrafish spawn more non-viable eggs as theygrow older and (ii) the fraction of non-viable eggs in a spawn is somehow relatedto inter-spawn interval. I think this phenomena must somehow be tied to ageing...Does anyone else encounter this phenomena with their organisms? Is there a waythis is explained in DEB theory?

3 A number of examples in the book show that feeding history might be an impor-tant player in patterns of variability in biological data, i.e low variability in lengthscombined with high variability in mass. I would like to analyse data by compar-ing the ranges in measurable endpoints between conditions and not the means anduse Monte Carlo simulations with stochastic food input to generate the predicteddistributions of each endpoint. I am interested in how the mode of action of ura-nium on the metabolism might impact these distributions. I am interested in anythoughts/comments/suggestions the participants might have on this subject

Alpar Barsi

Effects of endocrine active chemicals on Lymnaea stagnalisThere is a great concern about the effects of endocrine disruptors on humans and non-target species across Europe. However, there is currently no agreed guidance on how toidentify and evaluate endocrine activity and disruption. Thus, the aim of my PhD projectis to get better understanding of the mechanisms of acting the endocrine active chemicals(EAC) in invertebrates and to improve environmental risk assessment of EAC throughdevelopment of test methods and data analysis tools for assessing the effects of endocrineactive substances on pond snail Lymnaea stagnalis. I will use the DEB framework tointerpret and model the effects of EAC on individuals of this test species and afterwardsthe individual-based modeling approach to extrapolate effects on the population-level.

A non-monotonic dose-response curve is common finding when EAC act in organism.It emerges from multiple mechanisms: very low doses of hormones and hormone-mimickingchemicals can stimulate receptors resulting in an increase in responses, whereas high dosescan inhibit receptors, resulting in decrease in responses. When multiple outcomes are

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examined, qualitatively different outcomes are observed at low and high doses of EAC.Moreover, within one class of EAC not all chemicals exert an identical response. Also, todescribe variability of EAC acting mechanisms, nonspecific toxicity can occur at high, butnot low doses.

I am interested to explore how does the DEB theory deal with complex animal responsesto toxicants, such as EAC? Does, how, and when an animal switches its metabolism de-pending on a toxicant dose, e.g. in case of hormesis or inverted U-shaped dose-responsecurve, and food availability? Is there more than one DEB parameter influenced by a tox-icant, and if so, how to deal with this in modeling? How to cope in DEB with severalmodes-of-action if they exist?

Nick Colvard

I propose to measure different physiological parameters of a rocky intertidal alga, Fucusgardneri and to develop a DEB model that describes the energy allocation of this organismin light of changes in environmental conditions. The main objectives of this project are: (a) measure the photophysiological capacity and spectral composition analysis of Fucus spp.with changes in tidal height, position within the intertidal, and time of day; (b) developa temperature and humidity sensor within the thallus of Fucus spp. in order to assesschanges in thallus temperature and water retention with environmental variation, and (c)develop a mathematical model that will synthesize the results of (a) and (b) to provide amore complete understanding of the physiological response of intertidal algae to ensuingclimate change.

I understand that for this organism it requires a multivariate DEB model, thoughmy pet file is for a simple (univariate) model. I know this is not correct, but I wanted tostart with a simple model before it got too complicated.

My question for the workshop is: How would you account for variations in temperature,light, salinity, oxygen, and nutrients available to the algae for both the aerial (exposed)conditions and the seawater (submerged) conditions in the same DEB model? And tofollow that, how would you account for the transition period, where the tide is going out,or coming in, and the algae are both submerged and exposed for brief periods of time?

So beyond algae, applying this to other aquatic or terrestrial based organisms thatexperience large environmental variations based on the diel cycle of their habitat, howwould the DEB account for this?

Sara Cruz

Escherichia Coli simulation applying DEB on a multi-agent environmentSystems’ computer modelling is a very important area of research nowadays. By trans-

lating knowledge obtained through experimentation so it can be processed by a computer,it is possible to watch a realistic simulation of the world it represents and easily alterits parameters dynamically. This takes particular relevance in areas such as genetics andother biological research fields. By developing a coherent and realistic simulation, it ispossible to study a given environment in a much more detailed way than with laboratorial

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experimentation. It is also possible to freeze the simulation, have it running at any desiredspeed, capture any information available and go back and forth in time to examine thecause of a given event in a maximum detail level.

Furthermore, by applying an individual-based modelling approach to the simulation, itis also possible to study the life of a microorganism at an individual or even at a sub-cellularlevel. However, only recently has biochemistry evolved to the point of providing individualinformation about each microorganism in a colony. By allying this knowledge to the agent-based approach and high processing power of recent computers, it is possible to createsimulations at a colony level as the emergent behaviour of a high number of individuallyprogrammed agents. The Escherichia Coli bacterium is one of the most widely studiedbacteria, especially in the field of Genetics. As a reference organism in microbiology,it becomes both feasible and relevant to invest an effort towards its accurate modellingand simulation. There are two basic approaches used to develop a biological computersimulation: analyse experimental data to develop empirical algorithms that try to mimicthe displayed behaviours, and apply pre-defined models which can, through the input ofcertain parameters, recreate the desired behaviour. The DEB theory becomes, therefore,a useful tool to describe the life cycle of each bacterium.

The goal of this project will be to implement the DEB theory as a computer model inorder to describe the development of the bacterial agents through time, and according toenvironmental conditions. It will be applied to generate the events that define their lifecycle, such as birth, reproduction and death. Furthermore, DEB will also be employed todefine the bacterium’s interaction with the environment it dwells in, as well as with otherorganisms. To achieve this, it will be necessary to deeply understand how DEB theorydescribes the life cycle of individuals such as Escherichia Coli, and also to define the specificparameters to be applied for its accurate modelling. The DEB course, and particularlythe add my pet exercise come as a much faster way to get the knowledge needed for thesimulation as well as to determine the DEB parameters for my pet, Escherichia Coli. Thedeveloped model will later be compared to reported simulations, which use mathematicalmodels as well as others that employ empirical approaches. Finally, the main goal will beto take the results I get at individual and colony levels and match them to laboratorialexperiments that display the kind of behaviour I intend to model.

Virginie Ducrot

Use of the Standard DEB model for the study ofthe life-cycle in control and polluted semi-field conditions

My focus is on the study of toxic effects of pesticides on the life-cycle of invertebrates, andmore particularly on an isomorphic freshwater gastropod; Lymnaea stagnalis. Most of thework that has been done so far with this snail has been performed in clean conditions atthe lab (e.g. PhD of C. Zonneveld and other former publications by Bas, which are usedas examples in the book / PhD of E. Zimmer). Some data from full- or partial- life-cycletests where snails were exposed to toxicants alone (in lab conditions) or in mixtures (inmesocosms, i.e. semi-field condition) are also available but have not been studied yet inthe DEB framework. Semi-field data include duration of embryonic development, hatching

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rate, juvenile growth, age at first reproduction and fecundity for control and exposed snails.Yet, the type of food that is eaten by the snails in mesocosms is unknown and probablychanges over the life-cycle. The amount of available food and the fraction of this food thatis actually eaten for each food type is unknown too, and probably varies depending ontemperature and photoperiod (which are variable in time). In this context, I do not seehow to proceed in order to model the life-cycle of the snails with low, or no informationon food input. I would like to discuss with people whom are using DEB models to studyfield data, which also have encountered these issues about the characterization of feedingprocesses, and understand how they solved them, and how this previous work could apply tomy question. Would it be possible e.g. to use lab-based parameter estimates to reconstructthe feeding behaviour in semi-field conditions? Could proxys be used to model the feedingbehaviour? What is the influence of the use of proxys/assumptions about feeding on theoutput of the models in organisms that are exposed to toxicants (i.e. when, how and towhich extend can it lead to a misinterpretation of toxic effects?). Or, is the only solutionto develop/implement methods to analyse food preferences and track food ingestion is thefield?

Yoan Eynaud

From individual to ecosystem: How far can we use DEB theory ?

The role played by carbon in the global change led researchers to focus on its cycle withinthe biosphere. Since the ocean covers 70% of the earth surface, understanding the reminer-alization processes occurring among oceanic realms is crucial. However our knowledge ofthe mesopelagic layer is still poor and if technical issues can partially explain this lack, ourlimited capacity in modelling marine ecosystems are responsible as well. Thus we need toimprove our way to model marine ecosystems and more precisely to understand how theybehave. An analysis of the role played by details in ecological modelling is essential, and ifsome works have been done on simple models (Fussmann and Blasius, 2005; Poggiale et al.,2010), it appears interesting to study more complex systems, such as a mesopelagic model.A few models already exist (Anderson and Tang, 2010; Jackson et al., 2002; Stemmann etal., 2004) but none of them have used a detailed biological approach in their constructionhypotheses, which leads to a complexity of the model at the physiological scale.

Since the goal of my Phd project is to understand the role played by details in modellingthe mesopelagic layer, we here work on both different level of physiological complexity andtrophic web organization. DEB theory offers such a frame of physiological complexity, andallows us to widely represent the specificity of each species. However, if DEB modelling isregularly used for individual model, ecosystem models are rare. Chapter 9 discusses thispoint and outlines how V1-morph DEB model works both at the individual and populationscale by comparing it to usual models (Lotka-Volterra, Monod etc.). Again, former modelsseem to be specific cases of the DEB-model but one question arises from using DEB theoryin population/ecosystem modelling:

How far can we use DEB properties in ecosystem modelling?

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Benoit Goussen

Caenorhabditis elegans dauer larva in the DEB theoryThe assessment of pollutant effects at biologically and ecologically relevant scales is animportant issue in ecosystem protection. Mathematical models exist to predict effects ofpollutant on population dynamics from individually data. Nevertheless there are only afew datasets and models that account for adaptive phenomena which may appear in astressed population. The selection pressure exerted by a pollutant is known to amplifythe phenomenon of natural selection. It is thus essential to understand and quantify theadaptive dynamics governing populations under stress in order to assess ecological risk.

The aim of my PhD project is to study adaptive phenomena in Caenorhabditis eleganspopulation dynamic. To fulfil this objective, I plan to develop a model which will groupa DEB theory approach with an adaptive dynamic model. The ultimate target of thisproject is to increase knowledge about links between assimilation disruptions, growth andreproduction fluctuations in exposed organisms and to assess potential consequences onthe population.

C. elegans is an ubiquitous free nematoda which is mainly found in the resistance stage(dauer) in the wild [1]. This resistance stage occurs when environmental conditions (food,population density or temperature) are not favorable to its growth. This dauer larva isformed after a pre-dauer stage. During the resistance stage, the larva does not feed andmoves very little. How can it be taken into account in the DEB model?

[1] Barriere, A. and Felix, M.-A. (2005). High local genetic diversity and low outcross-ing rate in Caenorhabditis elegans natural populations. Current Biology, 15:1176-1184.Biological Resource Center

Tessa van der Hammen

Most fish species go through a number of life-history stages (eggs, larvae, juveniles andadults) and through different size classes. These stages depend on spatially separatedhabitats, which differ in many aspects such as food availability and temperature. For eachlife-history stage or size class the temperature tolerance range to survive, grow and/orreproduce differs, causing the optimal habitats to vary for different life stages or differentsizes of individuals.

As the environment changes (f.e. increase in temperature) habitats will change insuitability for each life history stage or size class. As a result, populations may shiftto more Northern areas or to deeper water (for example plaice shifts to deeper waters).Alternatively, species may experience reduced population growth or adapt to the habitat.

Using DEB will help to

1 determine the habitat quality for different habitats life-stages and sizes of fish and

2 determine the effect of different temperature and food conditions on habitat qualityand how these may explain observed and help predict potential changes in spatio-temporal distribution of fish species. For the DEB course I will use Turbot (Psettamaxima) as a case study.

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Tjalling Jager

The ageing model in DEB currently only considers effects on survival. With age, thesurvival probability decreases. However, there are more changes in the organism withage. Generally, you will see a decrease in feeding and a decrease in reproductive output.Obviously, we would need to consider these aspects to obtain a full picture of an organism’slife cycle. What would be a good approach to link the effects on survival to effects onmetabolic performance (in a consistent manner)?

Tiphaine Jeanniard du Dot

My research investigates how changes in foraging efficiency (due to changes in prey avail-ability/quality in their environment) affect lactation efficiency of female northern fur sealsduring the breeding season, and ultimately survival of pups/juveniles. Northern fur sealsare central place foragers during the breeding season and only have a short period of timeto provide their pups with enough energy to survive on their own (abrupt weaning at 4months). Consequently, they are likely very sensitive to shifts in environmental condi-tions during this period. Less than optimal foraging costs/benefits of females during 4months are not likely to affect health of adults, but might have drastic effects on survivalof pup/juveniles if they do not get enough initial reserves from their mother.

I am interested in using DEB models to determine how changes in energy budget linkedto changes in foraging efficiencies (energy spent foraging versus fish intake) might affectenergy allocation to reproduction in females, and how changes in lactation efficiency willaffect pup/young of the year survival. DEB models are a great framework to answer thesetypes of questions related to energy fluxes in animals and decisions regarding allocationsto different physiological functions. However, to my knowledge they do not take intoaccount the essential behavioural component of animals when facing changes in their localenvironment. Differences in foraging strategies are extremely important in determiningthe success of animals in similar conditions. Behaviours are highly species-specific andnot generalizable, which goes against the DEB concepts, so I am expecting to come acrossproblems with this core aspect of my research. However, the ultimate goal of bioenergeticmodels is to be applicable to concrete cases, such as in conservation management of specificpopulations for example. Consequently, there is a need to be able to easily input some ofthese more ‘flexible’ traits. In the same line, I am also concerned about how DEBs modelenergy costs of locomotion and activity levels, as it seems to be considered negligible inthe standard DEB model (book chap 2.1.3, p31), while it is also highly species-specific(inexistent for corals, and arguably the greatest part of energy output in pinnipeds at sea).

Dragan Jevtic

From Individual to Population:Integrating DEB into matrix population models - a good choice?

The overall aim of my PhD project (CREAM Soil-2) is to estimate collembolan populationresponse to elevated metal (and possibly pesticide) concentrations in soil and environmental

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stochasticity (fluctuating temperature) of different magnitude and frequency. The speciesto be used represent two contrasting reproduction strategies: parthenogenesis (Folsomiacandida) and sexual reproduction (Sinella curviseta), allowing a comparison of effects onotherwise similar species. Basic population parameters and extinction probabilities will becalculated to give better insight into collembolan population dynamics in such conditions.Obtained data will be used by my colleague (Natnael Hamda, CREAM Soil-3) and meto construct, tune and validate mechanistic effect models for collembolan populations.Both projects are part of EU FP7 project ‘Mechanistic Effect Models for Ecological RiskAssessment of Chemicals’ - CREAM. Matrix modelling approach (Caswell 2001) will bedominantly used for obtained data sets. Constructed stochastic matrix model can beintegrated with other type of models developed on the same grounds. At this point weare focusing on the DEB Theory as potentially most suitable theoretical framework forthe parameterization of our matrix models. Possible link between these models can beconceptually represented as follows:

Leslie-type matrix models can be expanded to express vital rates and consequentlythe population growth rate λ as a function of exposure concentration. The difficulty ofthis approach lies in the choice of effect models relating matrix entries to the exposureconcentration. Dynamical Energy Budget in Toxicology (DEBtox) theory provides a set ofmechanistic models of survival, reproduction and growth continuously as a function of timeand exposure concentration, and therefore can provide this relation. During this decadeseveral authors have worked on incorporating DEB into matrix models. One of interestingpapers (and possibly a starting point for discussion) was published by Klanjscek et al(2006). It demonstrates a way to construct a simple matrix population model from adynamic energy budget model in a constant or seasonally variable environment. Among(not so many) papers dealing with integrating DEBtox into matrix models, an interestingread for this discussion could be the ones published by Lopes et al (2005), Billoir et al(2007) and Jager & Klok (2010). I hope to discuss pros and cons for integrating DEBTheory into Matrix population models - how convenient and reliable is this integratedapproach, what are the best ways to do it, in which cases it should/shouldn’t be done,etc. We could also discuss the alternatives in terms of using other population modellingtechniques combined with DEB Theory and compare it to DEB-matrix approach.

Billoir E, Pery ARR and Charles S (2007) Integrating the lethal and sublethal effects oftoxic compounds into the population dynamics of Daphnia magna: A combination of theDEBtox and matrix population models. Ecological Modelling 203(3-4): 204-214.

Caswell H (2001) Matrix population models: construction, analysis, and interpretation.Sinauer Associates, Sunderland, MA, USA.

Jager T and Klok C (2010) Extrapolating toxic effects on individuals to the populationlevel; the role of dynamic energy budgets. Phil. Trans. R. Soc. B 365:3531-3540.

Klanjscek T, Caswell H, Neubert MG and Nisbet RM (2006) Integrating dynamic energy

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budgets into matrix population models. Ecological Modelling 196(3-4): 407-420.

Bob Laarhoven

From waste to worm. Pet: Lumbriculus variegates/black wormMy two questions are directly related to my research. In my project I investigate thepossibility to produce a high quality feed source by converting industrial by-products intoa high quality worm biomass. The freshwater worm of the species Lumbriculus variegatesis used in this project for the valorisation of ‘clean’ organic (waste) streams originatedmainly from industrial food industry. The main objective of the research project is todevelop a suitable bioreactor to convert organic by-products into worm biomass, consistingof a monoculture of the aquatic oligochaete Lumbriculus variegates.

The reactor setup applied in this research, showed below is important to understandmy questions.

Figure 1. Reactor concept for sludge reduction by L. variegatusUnder the right environmental conditions the worms position themselves between the

two compartments (water and substrate) in order to fulfil their simultaneous needs for feedand oxygen. In this stage the dorsal area is positioned in the substrate itself for feed-ing and its anterior part is exposed into the water compartment for respiratory exchangethrough the skin (see enlargement of the carrier material fig. 1). In this stage the worm issupported by the carrier material and reduced in its distribution through the sludge com-partment and partly immobilized by the carrier material itself. Due to this positioning, theworms will mainly consume the waste sludge on the edge of the sludge(bed) compartmentand defecate the non-digested waste sludge in the water compartment, this results in aseparation between the waste sludge, the worm biomass and the faeces produced.

Why have black worms a reduced growth rate in the reactor situation? For non-immobilised worms feeding on waste sludges, Buys et al. (2008) reported biomass growthrates of 0.05-0.11 d−1, whereas the growth rate in our continuous reactor with a 350µmmesh carrier material was only 0.013 d−1. Clearly growth is limited by immobilising theworms in a carrier material, although in all experiments the worms in the sludge compart-ment remained lively and healthy. In the reactor design worms have a reduced growthwhen compared with the situation that worms have free access to the same substrate (X),

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they can crawl around in the substrate and eat and defecate in the same unit. Substratelevel/composition in batch experiment alters over time because it is converted into worm,faeces and natural aerobic breakdown; in the reactor setup substrate level/composition ismore stable and is not mixed with any faeces. I am surprised that in the reactor conceptworms grow slower. Food availability is unlimited (Xm) and directly available. I assumefeeding costs are lower in the reactor setup but growth is still reduced. Interesting thingsin relation with this question is that L. variegatus feeding on several sediments. With alower organic fraction of the sediment, the faeces production rate (as a measure for sedi-ment consumption rate) increased. They postulated that the feeding rate of the worms isdominated by net energy gain, i.e. less needs to be consumed of a food source with a highnutritional value.

How would density of worms (worms/ m2) on the carrier material effectsbiomass production?

An important factor for the upscale of the reactor concept is the worm density. Incombination with the worm specific consumption rate, it will determine the required carriersurface area for a given daily waste sludge amount. Whether an optimum worm density isdetermined by the supply rate of substrate or by the mesh size of the carrier material (ora combination of both) is currently investigated.

How can the deb model give me a clear view on the effect of density ongrowth?

James Maino

I am interested in the co-variation of DEB parameters between related species. Specifically,I would like to find out to what extent observed differences in the physical design parametersof similar species can be explained by body-size scaling (zoom factor in DEB theory)and how one might go about explaining differences in intensive and extensive parametersthrough examination of phylogeny and present life styles.

I am only just beginning my PhD, but so far one possible project to explore suchrelationships will be to look at a clade of Australian skinks. There is also the possibility ofworking with Drosophila - another suitable species due to the existence of clines in bodysize, rich quantitative data ,and selection experiements. It is hypothesised that due to theirphysiological similarity (thus relative constancy of extensive parameters) a considerableproportion of the variation in parameters between such sets of species will be accountedfor by the co-variation with body-size scaling as predicted by DEB theory.

Topics I would like to discuss include the following:

• In which circumstances is the body-size scaling of parameters as prescribed by DEBtheory more likely to apply (and not apply)?

• Is there some systematic way in which DEB theory can translate observations of be-haviour or knowledge of the evolutionary history of a species into parameter changes?e.g. suppose we observe some behaviour or inter-species interaction in the field thatwould not be present under lab conditions and want to incorporate such informationinto our parameter estimates.

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Cristian Monaco

I am currently interested on the underlying mechanisms that drive the dynamics of a keypredator-prey interaction system of the west coast of North America, the predatory sea starPisaster ochraceus and its main prey the mussel Mytilus californianus. Initially I am solelyfocusing on Pisaster, and hope to use the DEB theory to model the effects of temperatureand food supply on their physiological condition and body size dynamics. Dr. Kooijmanrequested only one research inquiry, but since there is no harm in asking, I laid out severalelements of this interaction that I wonder about (my apologies anyhow):

1 Effect of temperature:

a) Pisaster is regularly forced to deal with varying air and water temperatures.Previous studies showed that conversion efficiency of consumed mussels under varyingthermal conditions is higher than under constant temperature (Eric Sanford 2002,JEMBE). I would like to use DEB theory to explain this phenomenon.

b) Pisaster gonado-somatic index has been observed to follow an annual cycle, inaccordance to temperature fluctuations and foraging activity. Individuals normallyforage on summer, accumulate reserves in their pyloric caecum during fall, turn itinto gametes and release them on spring (figure on the bottom from: Sanford andMenge 2007, MEPS). Based on DEB’s concept of metabolic memory I hope to modelthese energy dynamics.

2 Effect of food supply: This system has a strong bottom-up component. Mytilus’recruitments can determine the fate of Pisaster body size at a specific site. I wouldlike to use DEB model to explain body size dynamics on Pisaster in relation to musselbed structure (i.e. intertidal height and recruitment).

3 Effect of Pisaster’s body size An evident size-dependent distribution and foragingbehavior can be seen in Pisaster. In particular, small individuals are more frequentlyfound higher on the intertidal. Considering potential differences on how energy iscanalized depending on body size (as discussed during the class), I hope to use DEBto explain differences in behavior between large and small Pisaster.

4 Pisaster lab and field conditions: Lab reared individuals will gain weight but notelongate (Feder 1956, Thesis, Fig. 69). On the field however, they will grow inlength. If lab measurements are primarily used for the modeling, how can I accountfor the difference in estimates? Furthermore, this inquire applies to any measurementtaken from the lab to the field.

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Delphine Plaire

Daphnids are freshwater micro-invertebrates which are commonly used for toxicologicaltest. Until now, chronic effects of different radionuclides have been studied on successiveparthenogenetic generations of Daphnia magna. However in the environment, sexual gen-erations, involving male emergence and fertilization of resting eggs, appear under autumnalconditions. Increasing ecological relevance and realism would imply that toxic effects onboth the asexual and sexual cycles are examined.

The aim of my doctoral project is to study the toxicity of different radionuclides onphysiology (nutrition, respiration, and energetic reserves) and life history (growth, repro-duction and survival) over three successive generations representing a sexual episode ofDaphnia magna. Simultaneous actions of two stimuli were required to induce male emer-gence: reduce photoperiod and starvation of females during 4 days. Those conditionssimulate autumn conditions.

The objective is to evaluate consequences of environmental factor (autumn condition)combined to radionuclides contamination on physiology and life history of daphnids. Inthis context, DEBtox model will be used to quantify energy flow through organism fromfood uptake to the allocation of energy on physiological function (maintenance, growth,reproduction) under combined reduced feeding and toxic stress. Data will be integrated in

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Leslie matrices to describe the dynamic at the population level.In my experiments, I will reduce frequency of food addition in adults: 4 days of star-

vation followed by one day of ad-libidum food. The scaled functional response f will bemodulated accordingly every 5 days. How reduced feeding conditions influence moultingcycle is a point that I would be interested in discussing. According to the DEB book, themoulting cycle in daphnids is linked to somatic maintenance and is independent of thenutritional status (2.7.2). However, I can easily observe experimentally that moulting isdelayed when food supply decreases (e.g. when somatic maintenance remains unchangedand nutritional status declines). How can that be parameterized in the DEB model?

Elisa Ravagnan

Krill life-stages characterisation and exposure to oilKrill are key components in sub-Arctic and boreal North Atlantic ecosystems. They rep-resent a large proportion of the pelagic invertebrate biomass in the Barents Sea and arean important food source for young herring, cod and capelin.

The main goal of the DEB theory application in this project is to study the physiologicalsensitivity of Northern krill (Meganyctiphanes norvegica) to oil exposure. Basic life-historyand physiological parameters will be assessed from controlled conditions, and compared toresponses in individuals exposed to toxicant. At the moment, literature covering the life-history of Northern krill is relatively scarce, while many studies have been performed onAntarctic krill (Euphausia superba).

Challenges:

• To perform laboratory experiments covering the different life stages. Northern krillis very sensitive to handling and laboratory conditions. The same challenge appliesto the toxicant exposure setup.

• How to combine literature information when experimental data are not available,avoiding over-generalization and/or case-specificity?

Main questions to answer are:

• How to describe the life-cycle of Northern krill from an incomplete dataset? How toestimate the DEB parameters?

• The early life-stages are considered the most sensitive to toxicant exposure; how toexpress this sensitivity if data at embryo or early juvenile stages are not available?

Julita Stadnicka

Predicting toxicity to fish based on in vitro data via a 2-step modelOne of the main goals of my project is to predict sub-lethal effect endpoints (i.e. changes ingrowth and reproduction rate) in fathead minnow (Pimephales promelas) based on exper-iments on cell lines. To achieve this aim, I would like to use a combination of toxicokineticand toxicodynamic approaches: PBTK-DEBtox model.

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The PBTK (Physiologically Based Toxicokinetic) model is a multi-compartment ap-proach which will deliver information about the internal concentration of a chemical. I willuse this concentration as an input in the DEBtox model. Then I will be able to predict theimpact of a chemical on fish growth and reproduction rate based on a toxicant concentra-tion in the whole body. However, I would like to develop a model which will require onlyparameters obtained in vitro. For this reason I would like to predict/measure chemicalconcentration in cells, and use it as an input in the DEBtox model in order to predict celldivision rate. The last step in this project part, and probably the most challenging, willbe to link changes in cell division with changes in fish effect endpoints.

Nowadays, the link between cell division and organism growth is known quite well, andI have already found some models which allow doing this. The link between cell divisionand organism reproduction will be more complex, indirect, and for sure will require moredata and experiments on cells; however, to predict this effect endpoint, I would also liketo base on energy as common currency.

During the course in Lisbon, I would like to learn how to apply the Dynamic EnergyBudget theory into cell scale in order to predict organism responses for a toxicant, basedon in vitro data.

Louise Stevenson

Im interested in the application of DEB theory to ecotoxicological research. As a first yearPhD student, my research will focus on the effect of nanoparticles on freshwater ecosys-tems, focusing on an algae-herbivore (Daphnia) system. The small size of nanoparticlesbring with them novel physicochemical attributes that have been utilized for a wide varietyof applications, ranging from biomedical, electronic, to cosmetic use. However, these novelproperties also carry with them unknown effects on humans and our environment. Numer-ous studies have found toxic effects of nanoparticles on aquatic organisms, such as acutetoxicity, genotoxicity, and impaired reproduction, development, and immune function, butwe are missing key knowledge on how these toxic effects amplify in ecological systems.

Nanoparticles small size causes large changes in physicochemical properties from thoseof these particles bulk states. Our lab will probably focus on nanosilver whose chemicalcharacteristics, solubility, and ability to aggregate differ from those of bulk silver. Thesechanges in properties between the nano and bulk state of silver can lead to different effectsand potentially increased reactivity and toxicity of nanosilver. How can I incorporatepotential (preexperiment) and analyze realized (post-experiment) toxic effects of nanosilverin a DEB framework? The difference in toxic behavior between elemental or bulk silver andnanosilver makes me wonder how I would identify which parameters are potentially mostimportant when designing my experiments. Further, individuals in the same experimentalsystem may be experiencing different forms of these nanoparticles. This can result fromaggregation of nanosilver into large bunches of particles (although this occurs less frequentlyin freshwater environments). Also, many particles are coated with a different material toenhance stability that may be removed or altered (e.g. through digestion and excretion byorganisms), releasing the particle into a more or less toxic form. These examples, alongwith others, mean that individuals in the same experimental system may be experiencing

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different forms of these nanoparticles and, potentially, different toxic effects.

Lorna Teal

Using DEB to underpin spatio-temporal dynamics of fish

Knowledge on the spatio-temporal dynamics of fish species and which biotic and abioticfactors act as drivers is key to identifying essential fish habitat and exploring the change inhabitat quality under uncertain environmental futures. Flatfish (Plaice, Sole, Turbot) areimportant commercial species in the North Sea, with a strong size and season-dependantspatial distribution.

Because growth rates are influenced by the environment, and are closely linked toreproductive potential, one approach to assessing habitat quality is to derive spatially-explicit models of growth potentials. Using dynamic energy budget models, we aim tocalculate size-, temperature-, and food density-dependant growth rates to assess the spatialdifferences in growth potentials for varying size classes of flatfish species under differenttemperature and food conditions.

Having implemented this approach reasonably successfully for plaice, I aim to extendthe approach to sole. Specific difficulties and questions that have arisen from the exercisewith plaice are:

• How best to estimate f when the functional response curve is not known?

• How best to implement non-constant food-conditions? i.e. we use food productionfrom an ecosystem model which gives us food conditions on a daily basis. So nowwe are calculation growth separately each day - but this seems to lose the benefit ofbeing able to deal with the reserves/metabolic memory of the organism.

• Is the kappa rule really valid? We know that e.g. plaice stop feeding when spawning- it seems unrealistic to assume that they would still then give a fraction of energyto growth?

Koji Tominaga

I would like to raise a discussion question about how we can estimate parameters in sucha complex non-linear formulation, like in the DEB Theory. Most often when we dealwith messy data (observation) and we try to ’fit’ our conceptual understanding, we startby playing around with parameters that govern the conceptual understanding. Questionsarise when we wish to determine the best parameters that agree with the observed data.In fact these are some of my thoughts and would probably enjoy hearing what others mayponder.

1 There are many different criteria (such as those based on a statistic or likelihood)that one could deploy, and they may conclude different best parameters. This im-ply existence of multiple ambiguously best different parameters. Does this appearproblematic as a scientific approach (or a knowledge gaining tool) to you?

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2 Do we need to find the best parameter set to begin with? In other words, are weimplicitly assuming that there is ’a’ best parameter set, for our purpose? Alterna-tive approach is to find parameter spaces (ranges). There are some probabilisticallyformulated framework to find parameter probability distribution that equally well,or likely predict observation. This question has something to do with the fact thatindividuals differ (Chapter 8?), but I’m even wondering about estimating DEB pa-rameters for one single individual with a data observed for that individual.

3 Last and the most important question that I have is how we best protect fromgetting the right answer with wrong reasons. I am, to be honest, very new withphysiology and perhaps it is not much a concern in this field. But with a systemwith a much simpler formulation in the pollution ecology that I have experiences, onecan easily appear correct (i.e., agreeing with observation, or good criteria, see point1), with wrong reasons. I would like to know the relevance of such difficult questionin modelling. It is an often an important discussion about model uncertainty, evenfor a conceptual model, to learn more about the system.

I am currently doing a research on nutrient dynamics in a Norwegian lake. So mytendency is to look perhaps too much from the ecological perspective. But as somebodydrew an analogy whose name I cannot remember, an ecosystem functions like an individualorganism. It gets energy, gets chemical compounds, processes them, releases them, andit even gets sick (pollution, or population collapse). So I still see the relevance there,and would like to see what relevance other participants see from the more physiologicalperspective, or in their application of the DEB Theory.

Maxime Vaugeois

My research focuses on better understanding the ecological impact of appendicularians(gelatinous zooplankton) on the global carbon cycle (carbon export to the deep ocean)and their general role in the ecosystem. Appendicularians are unique organisms becausethey live in a structure that they periodically produce themselves which is called thehouse. It allows them to be less dependent on their environment (longer response time toenvironmental changes) because it provides a kind of external food stock. It also allowsthem to have a large prey size spectrum and a high grazing rate. These properties alongwith high metabolic rates suggest that they have an important role on the biologicallyexported part of the carbon cycle (production of a large amount of detritic organic matter)but also on the food web structure (capacity to circumvent the microbial loop associatedwith important grazing rates).

To study appendicularians I use a modeling approach at different scales from individualto ecosystem. Firstly, I am modeling an Oikopleura dioica organism to better understandthe impact of house production and food storage in the house on the dynamics of thisorganism. I would like to apply DEB theory because it provides a clear way of reasoningbased on well-defined assumptions.

I know that house production can be seen as a part of the maintenance and thatthe effect of the house can be taken into account in the formulation of the functional

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response. Nevertheless I think that two structures are needed to fully answer my questions:One for the house and the other for the trunk. The house structure (which won’t haveany maintenance) would have priority over the trunk structure (and its maintenance).Concerning what I would like to discuss in Lisbon, I don’t have fully understood the point2.7.1 of the DEB book which is about the cumulative reproduction of Oikopleura I amworking on. Also I would like discuss how DEB theory can be applied to other scales(population and ecosystem scales) for my future research activities.

Andreas Waser

Mussel beds (Mytulis edulis) are central biogenic structures in the ecosystem of the WaddenSea. They stabilize the substrate, improve the water quality and they provide importanthabitats for many (benthic) species. Furthermore, they are an essential food source foraquatic organisms like crustaceans and fishes and for many avian species. In the past,intertidal mussel beds formed a prominent part of the European Wadden Sea. In the DutchWadden Sea though, mussel beds almost disappeared completely on the intertidal mudflats in the early 1990’s mainly due to intensive mussel fishery. Since closure of intertidalbeds for fishery in 1993, and after strong mussel recruitment in several subsequent years,intertidal mussel bed area has increased again. The most recent estimate is 1400 hectaresof intertidal mussel beds. However the recovery has been slower than hoped and mainlyoccurred in the eastern part of the Dutch Wadden Sea. In the western part only a fewhectares of mussel beds have re-established.

It is still not well understood why there is such a big difference in the mussel bed recoveryand why the mussel beds have not come back to the western part of the Dutch Wadden Sea.In the West newly developed mussel beds often disappear after one or two years, when themussels are hardly larger than 30 mm. Only a few make it to a stable mussel bed, whereregularly new spat settles next to older cohorts and refreshes the mussel bed. Amongstother things (e.g. bed erosion caused by hydrodynamic forces) predation plays a crucialrole on the disappearance of mussel beds. The predators feeding on intertidal mussels areOystercatchers, Common Eiders, Herring Gulls, Red Knots and Shore Crabs. They differstrongly in their prey preferences. Oystercatchers and Eiders prefer larger mussels, whilethe others mainly feed on small mussels (< 20 mm). The aim of my doctoral project isstudy the impact of different predators on the survival of littoral mussel beds. I’m hopingto use the DEB theory for a modelling approach of bed survival.

I would like to discuss how the DEB theory can help to describe and later on alsopredict the survival of mussel beds in respect of different predators. What would be thebest strategy to approach such a model? ’m currently thinking of two different possibleapproaches:

1 make use of population models of the predators and also of the mussels

2 consider a mussel bed as a super organism and the predators as parasites/toxicantswhich weaken a mussel bed to avoid the population level.

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Elke Zimmer

Embryonic development Lymnaea stagnalisThe main purpose of my PhD project is to assess how the impact of toxicants on individ-uals during different parts of the life-cycle propagates to the population level; my modelorganism is the great pond snail Lymnaea stagnalis. While working on the DEB model forthe individual, I had some difficulties to find a parameter set: a parameter set that predictsperfectly the growth and reproduction pattern from the late juvenile stage on could notpredict the observed size and age at hatching. My hypotheses is that the reason lies in thedescription of the embryonic development in the standard DEB model: I question whetherthe reserve density at birth equals the reserve density of the mother in the moment of re-production. Observations on the embryonic development, that I found in literature and inpersonal communication, suggest that the embryos start eating on the reserves in the eggafter reaching a certain developmental stage: after 4-6 days, they leave the veliger stageand reach an adult-like form, and they do not seem to change in shape but only grow.

I recently conducted experiments to assess the impact of different food levels and feedingintervals on the reproductive investment and the consequences for the embryonic develop-ment (i.e. size, age and reserve density at birth). In the photographic study with highmagnification I conducted to follow the the development in a single egg, I could see thatthe embryo moves its ’mouth’ and seems to swallow material from the inside of the egg.

In the discussion, I would like to tackle the question how to deal with this finding inthe model. Does the embryo enter the juvenile phase in the moment it starts feeding? Ifso, is this the moment of birth, and the theoretical definition of birth does not relate to themoment of hatching, when the snails leave the clutch? If so, what determines the amountof reserves left in the egg? The amount of reserves left for the embryo to eat will relatedirectly to its reserve density when it leaves the clutch.

Evaluation

Tele part

All course material has been updated for the course (adapted to the 3rd edition of the DEBbook): the life-cycle collection for a survey of phylogeny, basic methods for theoretical bi-ology, introductory material (several papers for various audiences), a video to introducethe book, quizzes, exercises, micro-lectures (with sound tracks), summary of concepts,comments, a pdf with selected chapters of the DEB book 3rd edition, software packageDEBtool for Matlab/Octave (with Matlab/Octave exercises and an introduction to Mat-lab/Octave), the website for the course and the BlackBoard site. The participants listand this course file were new to this course, together with the add my pet collection anddocument. The micro-lectures, comments and the summary of concepts were frequentlyupdated during the course in response to discussions on BB.

With 93 participants in 17 local groups plus 11 single-person groups, this course wasthe biggest of the DEB tele courses so far and had the best group structure. As expected,

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the single-person groups had the largest problems to follow the course, followed by thesmall groups; some of them did not have weekly local meetings (despite my attempts toarrange such meetings). The activity in the groups was larger than visible from the dis-cussion board; the larger groups had active discussions but did only partly feel the need topost conclusions on the discussion board. This was confirmed in contacts with discussionleaders and by the hit-frequency on BB

Discussions in Lisbon learned that the decline in contributions on the discussion board wasdue to 1) competition on the time budget with other tasks outside the course; 2) manyfelt thresholds to post ‘stupid’ questions that are visible for all and stay on BlackBoard fora long time; 3) some experienced workers posed questions that starting individuals foundintimidating; 4) the course went too fast and a delay developed for many participants. Aconfusingly large amount of material was available (consistent with the last observation),but the summary of concepts and the micro-lectures were found to be very useful. Manyparticipants liked the introductory material, both the video and the papers. I receivedfeedback on the quizzes; the add my pet document was found to be difficult. Most sub-missions of discussion notes and add my pet contributions were too late to be used forpreparation of the Lisbon part; many arrived the day before departure to Lisbon. Theresulting essays were added to the essay collection and several errata were found duringthe course and processed.

53 participants expressed interest to receive a certificate, 20 of which with a mark. 28qualify for a certificate (i.e. they submitted an essay or a discussion note), 11 of which witha mark.

My conclusions are

• generally the tele-part went satisfactory, but there is certainly room for further im-provement.

• this course needs to be followed more than once to accommodate the long learningcurve that is required by DEB theory; as long as the motivation is high, its is not aproblem at all that part of the material is skipped. This has the positive side effectthat a diversity of experience with DEB theory among participants develops so thatthe experienced ones can assist the less experienced ones.

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• development of delays should be avoided by providing better guidance for reading.Contact with group discussion leaders should be more intensive to control speed, i.e.topics that are indicated as having a lower priority should not delay the speed of thecourse.

• thresholds to contribute to the discussion board should be reduced by stimulatingguidance by participants of previous courses and we should look for communicationmedia that reduce discussion thresholds (less permanent registration of questions andremarks).

Lisbon part

The 50 participants were typically the most active among the 93 tele participants. Myimpression is that the setup of the Lisbon part was close to maximum efficiency. Thefrequent changes of rooms were found to be less optimal (though this is hard to avoid this atany university campus; IST did not allow room reservation well beforehand). Some roomswere less suitable for the discussions, but availability of grass patches on the campus incombination with great weather solved that problem in a very convenient way. The level ofenthusiasm and active participation was very high. This was confirmed by the observationthat 1) Many discussions in spare time were about course material; 2) Several participantsexpressed their interest for a double doctorate at the VU-University Amsterdam; 3) Allsaid the have learned a lot; 4) Many indicated to plan frequent use of the DEB network inthe future using the participants file; 5) Many expressed their interest for another go onthe course on 2013. 6) I received many warm thanks orally and several also my email; Thealternation of modules within each day (lectures, group & plenary discussions, exercises,add my pet presentations) were found to be very stimulating. Many liked the stay inLisbon a lot and the young participants frequently went for a drink at night, when theolder ones were sleeping.

Exercises of 1 hour were too short and changes in the original program were made tohave blocks of at least 2 hours. The add my pet exercises were found to be difficult, butthe intense help of experienced DEB workers was effective. Despite advice on pre-courseactivities, many had no experience at all with Matlab or Octave. 22 mydata-submissionwere available at the start of the Lisbon-course; almost all had mydata-files at the course(so half of them were not submitted), some were about organisms that cannot be capturedby the standard DEB model (bacteria, worms, brown weed) and hardly had data at theindividual level. Many appreciated this exercise because it allowed them to apply DEBtheory in their own research. Nine participants presented their results plenary and allfound the comments by experience DEB workers on their results during the presentationsvery helpful. The time allocated to the exercises was optimal.

24 participants submitted discussion notes, introduced their topics for 10 minutes,followed by 30 minutes of discussion in the 5 parallel groups. All participants liked thissetup very much and found the diversity of topics stimulating. Few participants found thetime to read the papers on the ‘Metabolic Theory of Ecology’; the choice of this centralised

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discussion topic should be reconsidered. The discussion topic ‘maturity’ was satisfactory,including the ‘course evaluation’ on the last day.

Symposium

The symposium was very successful. Most contributors followed DEB courses in previousyears; some contributors also had a presentation in the 2009 symposium. Where the2009 symposium had a large contribution from people linked to Ifremer, so to applied searesearch, the 2011 symposium had more diversity. (The AQUAdeb group had a closingmeeting at Camaret-sur-Mer in December 2010). The general quality of the presentationsimproved, compared to 2009, mainly due to an increased knowledge of DEB theory by alarger community. Two of the 5 keynote speakers dropped out shortly before the start ofthe symposium due to medical reasons; the organisation found successful replacements justin time. Several persons left the symposium on friday before the end, did not participateto the excursion on friday-afternoon, probably to save the weekend at home.

Conclusions for 2013

• Guidance for what to read must be improved.

• The starters in 2011 were invited at my closing lecture at the symposium (Lisbon, 15April 2011) to organise a 1 week course ahead of the 2013 tele course to organise a pre-course to prepare of the tele-course with the primary purpose of lowering thresholdsfor contributions to the discussion board and providing guidance for those elementsthat they considered to be most hard to understand. If this pre-course proves to besuccessful, future courses might expand this module at the expense of the rest of thetele-part. The total size of the course (1 week pre-course, 5 weeks tele-course, 8 dayspractical course, 3 days symposium) should not expand.

• We study application of Google groups and other facilities to ease discussions andfacilitate networking.

• The exercises will be in blocks of at least 2 hours.

• The suggestions of centralised discussion topics will be asked from participants whoplan to attend the practical part.

• We aim to increase the activity on the discussion board, possibly splitting the themin parallel boards, depending on the number of participants. We also aim to increasethe percentage of participants that follow the practical part to submit discussionnotes and add my pet contributions.

• I will improve the add my pet document and study possibilities to smooth out soft-ware to reduce the complexity of the add my pet exercises. Templates for other DEBmodels than the standard one should be considered as well.

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• We should try harder to link single person groups and small groups to bigger onesusing Skype.

• We should try to make sure that elementary knowledge about Matlab/Octave ispresent before participants start with the partical part of the course.