Models in stress research Bas Kooijmanvu nl http

Models in stress research Bas. Kooijman@vu. nl http: //www. bio. vu. nl/thb Brest, 2016/08/29/14: 00 MEMS Summer school

Contents Stress Research - in biology - in energetics - in stress Meta-models

stress Stress 0 too little enough too much factor No stress for a range of factor values Stress = difference from no-stress Consequence: We need to know the no-stress situation to recognize stress, including `variability’

Arrhenius relationship ln pop growth rate, h-1 stress 103/T, K-1 103/TH 103/TL

Space-time scales Each process has its characteristic domain of space-time scales space system earth ecosystem population individual When changing the space-time scale, new processes will become important other will become less important This can be used to simplify models, by coupling space-time scales Complex models are required for small time and big space scales and vv Models with many variables & parameters hardly contribute to insight cell molecule time

Biochemical ↔ Pools • many compounds need for selection • conservation laws cannot be used • wide range in scales • complex dynamics • few pools • use of homeostasis • conservation laws can be used • narrow range in scales • simple dynamics • easy connection with molecular level with literature • complex connection with molecular level with literature Bridge calls for intermediary levels of organisation

Homeostasis strong homeostasis constant composition of pools (reserves/structures) generalized compounds, stoichiometric constraints on synthesis weak homeostasis constant composition of biomass during growth in constant environments determines reserve dynamics (in combination with strong homeostasis) structural homeostasis constant relative proportions during growth in constant environments isomorphy. work load allocation thermal homeostasis ectothermy homeothermy endothermy acquisition homeostasis supply demand systems development of sensors, behavioural adaptations

Static vs Dynamic Budgets Net production models • time-dependent static models • no damping by reserve Assimilation models • dynamics by nature • reserve damps food fluctuations

Criteria for general energetic models • Quantitative Based on explicit assumptions that together specify all quantitative aspects to allow for mass and energy balancing • Consistency Assumptions should be consistent in terms of internal logic, with physics and chemistry, as well as with empirical patterns • Simplicity Implied model(s) should be simple (numbers of variables and parameters) enough to allow testing against data • Generality The conditions species should fulfill to be captured by the model(s) must be explicit and make evolutionary sense • Explanatory The more empirical patterns are explained, the better the model

Stress by chemical compounds Par values depend on internal concentration: transport 1 compartment partition coef = 1 -1 compartment internal conc external conc dim(partition coef) = dim(accum rate) = vol environ vol organism time × vol environ dim(elim rate) = 1 time

n, n-compartment models 6. 3 a 1, 1 -comparment model film model Compound can cross, interface between media with different rates vice versa sub-layers with equal rates for all sublayers

Meta models for parameter values Null model: • • group pars in either intensive or extensive find a simple function of pars that contains 1 extensitive par x example: max struct length for standard DEB model, example: bioconc factor for 1 compartment model find ratios of extensive pars that are intensive and contains x this links all extensive parameters to x write property of interest as function of pars and study how is scales with x

Primary parameters standard DEB model Kooijman 1986 J. Theor. Biol. 121: 269 -282

time to reach x-level saturation Primary parameters 1 -1 compartment, film model Kooijman et al 2007 SAR & QSAR Environ. Res. 18: 315 -330

DEB tele course 2017 http: //deb. akvaplan. com/debschool. html Free of financial costs; Some 108 or 216 h effort investment Program for 2017: Feb/Mar general theory (5 w) May symposium in Tromso (N) (8 d +3 d) Target audience: Ph. D students We encourage participation in groups who organize local meetings weekly Cambridge Univ Press 2009 Software package DEBtool for Octave/ Matlab freely downloadable Slides of this presentation are downloadable from http: //www. bio. vu. nl/thb/users/bas/lectures/ Audience: thank you for your attention