1. Scope for quantitative bioeconomics
Bas Kooijman
Dept theoretical biology
VU University Amsterdam
A manuscript with this title has been submitted to J BioEcon at 2016/06/10.
It discusses more issues than I can present is this 20 min lecture
Copenhagen, 2016/06/22

2. Contents Introduction Allocation to soma Waste – to – hurry
Supply-demand spectra
Overview over this 20 min lecture

3. Biology ↔ Economy similarities at various levels
internal organisation: individual ↔ firm
resource acquisition: specialist ↔ generalist
interaction: syntrophy, competition, predation, parasitism
dynamics: merging ↔ splitting
broad picture: micro ↔ macro level
individual: central point of focus of DEB theory
unit of evolutionary selection
input – output fluxes most clear at this level
can be a single bacterial cell, a tree, an animal

4. Space-time scales
Each process has its characteristic domain of space-time scales
molecule
cell
individual
population
ecosystem
system earth
time
space
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
Basic to DEB theory is the coherence between levels of organisation, using the life cycle of an individual as primary focus, from which sub- and supra-organismic levels are considered.
Space and time scales are tightly coupled methodologically.
Since many species are unicellular, the step to biochemical systems is not always big.
Populations are considered as sets of interacting individuals, ecosystems as sets of interacting populations.
While walking up- and down the time-space-scale, some processes loose their importance, others gain.
The primary motivation in my research on the theory is to answer the question:
how can we deal with the local coherence of levels of metabolic organisation, while avoiding the massive complexity of models with many variables and parameters;
I have never seen useful conclusions coming out of complex models.

5. Standard DEB scheme offspring food faeces reserve structure 
1 food type, 1 reserve, 1 structure, isomorph
1-
maturity
maintenance
offspring
maturation
reproduction
food
faeces
assimilation
reserve
feeding
defecation
structure
somatic
growth 
Assumptions of standard DEB model as member of DEB models
One food type of constant composition and particle size that can be used to complete life cycle
One reserve type
One structure type
Isomorphy
only food is limiting, not e.g. dioxygen
Extensions that are sometimes included in the standard DEB model
foetal development (as alternative to egg development)
ageing
metabolic acceleration between birth and metamorphosis
Applies to most animals, which live off other organisms, so uptake of all required chemical compounds are coupled.
The number of required reserves equals the number of required resources that are taken up independently.

6. Homeostasis strong homeostasis weak homeostasis structural 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
Homeostasis is the ability to run metabolism independent from environmental conditions.
This can obviously not be perfect, all organisms require food and/or nutrients.
We need 5 difference homeostasis concepts to capture the extent organisms sport homeostasis.

7. Allocation to soma sR = actual max reprod rate
413 animal species at 2016/06/11
Population growth (where ageing is the only cause of death) and maximum reproduction are optimum functions of the allocation fraction to soma.
The optimum fraction is about kappa = 0.45, the median observed value in the add_my_pet collection is 0.85.
For each of the 413 species the value of kappa is computed that maximizes max reproduction, given the other parameters.
50% of the species reproduce at 0.1 times their maximum possible rate, 20% reproduce at 0.01 times their maximum possible rate..
sR = actual max reprod rate
as fraction of that with optimized κ
Lika et al 2011 , Kooijman & Lika 2014
J. Sea Res, 22: , Biol Rev, 89:

8. Selection for reproduction
Red Jungle fowl IR RJ IR WL
Indian
River
broiler WL RJ
White Leghorn
Kooijman & Lika 2014
Biol Rev, 89:
If selection is for maximum reproduction, like here in the White Leghorn, kappa has the value that maximizes reproduction rate.
Notice that selection hardly affected specific assimilation in Indian River females, and reduced it in Indian River makes; it is the other way around in the White Leghorn.
Selection hardly affected energy conductance, but reduced somatic maintenance a bit. The latter might be related to lack of natural behaviour.
Selection reduced life span is substantially.

9. Type R acceleration 12 °C Crinia georgiana Pseudophryne bibronii hatch
Mueller et al 2012,
Comp. Physiol. Biochem. A,
163:
Crinia georgiana
max dry weight 500 mg
hatch
birth
hatch
birth
metam
metam
12 °C
Pseudophryne bibronii
age, d
These two myobatrachid frogs are very similar in many respects, but the tadpoles of P. bibronii live in permament pools, while that of C. georgiana in temporary ones that dry up, soon after their metamorphosis. The latter accelerate development by lowering  temporarily, which also reduces growth.
In this way it can leave the pond at the age of 110 days, while P. bibronii needs 200 d. Hatch coincides with birth for P. bibronii.
C. georgiana is 4 mg at metamorphosis, P. bibrionii 35 mg dry, while the maximum weights are 500 and 200 mg, respectively.
Both frogs have a (constant) somatic maintenance rate of some 400 J/d.cm3.
The graphs in the middle just enlarge the graph on the right till birth.
The step-up in respiration at birth is due to the onset of assimilation.
Mueller C., Augustine, S., Kearney, M., Seymour, R. and Kooijman, S.A.L.M. 2011
Tradeoffs between maturation and growth during accelerated development in frogs
Comp. Physiol. Biochem. A, 163:
Data: Casey Mueller
Model fit: Starrlight Augustine
max dry weight 200 mg
hatch
birth
hatch
birth
metam
metam

10. Waste to hurry Exploiting blooming resources
Kooijman 2013
Oikos 122:
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
Waste-to-hurry is the hypothesis that species increase somatic maintenance for the purpose of boosting growth and reproduction, such that max body size remains small. This strategy is possible because of the kappa-rule.
Fast growth and reproduction is only possible if specific assimilation is large.
If that would be the only difference a very large body size results, which comes with a long life cycle.
Not fit for profiting from temporary resources.

11. Supply-demand spectrum
Species can be ranked in the gradient from supply to demand systems as stages in the evolution toward a high level of homeostasis.
Extreme supply or demand systems don’t exist, all species represent a mixture of these extremes.
Plants come close to the supply-end of the spectrum and can adapt their metabolism to the local environment relatively well.
Demand systems adapt their metabolism much less and compensate that by a high level of behavioural flexibility.
The characterizing property of demand systems is that the use of resources (growth, reproduction) is `pre-programmed’, which causes a particular need for food and growth curves that are given functions of age.

12. Supply-demand spectrum
Lika et al 2014
J. Theor. Biol., 354:35-47
Supply-demand spectrum
The constraint R_m > 0 can be translated into the constraint kap^2 (1 – kap) < s_s, from which follows that s_s < 4/27.
Moreover kap must be between the two positive roots of kap^2 (1 – kap) – s_s = 0.
The metric s_s has the interpretation of the distance to the supply-end of the supply-demand spectrum
The metric s_d = 4/27 – s_s has the interpretation of the distance to the demand-end of the supply-demand spectrum.
Most species are supply species, only vertebrates classify as demand species.
The 2 plots are identical, but the abscissa is logarithmically the left plot to expose extreme supply species. The colour coding is also different.
identical points & plots
colour coding different
413 species 2016/06/11

13. DEB tele course 2017 Audience: thank you for your attention
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
More info can be found on the web
The organisation of courses for specialised audience is negotiable
Cambridge Univ Press 2009
Audience:
thank you for your attention