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Scope for quantitative bioeconomics

Scope for quantitative bioeconomics. Bas Kooijman Dept theoretical biology VU University Amsterdam Bas.Kooijman@vu.nl http://www.bio.vu.nl/thb. Copenhagen, 2016/06/22. Contents. Introduction Allocation to soma Waste – to – hurry Supply-demand spectra.

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Scope for quantitative bioeconomics

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  1. Scope for quantitative bioeconomics Bas Kooijman Dept theoretical biology VU University Amsterdam Bas.Kooijman@vu.nl http://www.bio.vu.nl/thb Copenhagen, 2016/06/22

  2. Contents • Introduction • Allocation to soma • Waste – to – hurry • Supply-demand spectra

  3. Biology ↔ Economysimilarities at various levels internal organisation: individual ↔ firm resource acquisition: specialist ↔ generalist interaction: syntrophy, competition, predation, parasitism dynamics: merging ↔ splitting broad picture: micro ↔ macro level

  4. system earth space ecosystem population individual cell time molecule Space-time scales Each process has its characteristic domain of space-time scales 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

  5. defecation feeding food faeces assimilation reserve somatic maintenance maturity maintenance  1- maturation reproduction growth maturity offspring structure Standard DEB scheme 1 food type, 1 reserve, 1 structure, isomorph

  6. 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

  7. Allocation to soma 413 animal species at 2016/06/11 sR = actual max reprod rate as fraction of that with optimized κ Lika et al 2011 , Kooijman & Lika 2014 J. Sea Res,22: 278-288, Biol Rev, 89: 849-859

  8. Selection for reproduction Red Jungle fowl IR RJ IR WL Indian River broiler WL RJ White Leghorn Kooijman & Lika 2014 Biol Rev, 89: 849-859

  9. Type R acceleration Mueller et al 2012, Comp. Physiol. Biochem. A, 163:103-110 Crinia georgiana max dry weight 500 mg hatch birth hatch birth metam metam 12 °C Pseudophryne bibronii age, d max dry weight 200 mg birth hatch birth hatch metam metam

  10. Kooijman 2013 Oikos122: 348-357 Waste to hurry Exploiting blooming resources requires blooming yourself • high numerical response • short life cycle • small body size • fast reproduction • fast growth • high feeding rate • resting stages between blooms -rule explains why [pM] needs to be high Ecosystem significance: flux through basis food pyramid

  11. Supply-demand spectrum

  12. Lika et al 2014 J. Theor. Biol., 354:35-47 Supply-demand spectrum identical points & plots colour coding different 413 species 2016/06/11

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

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