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with acknowledgements to
Travels in (C-S-R) space:
adventures with cellular automata
Ric Colasanti (Corvallis)Andrew Askew (Sheffield)
Presentation ready
CA in a community of virtual plants
Contrasting tones represent patches of resource depletion
This is a single propagule of a virtual plant
It is about to grow in a resource-rich above- and
below-ground environment
The plant has produced abundant growth above- and below-ground
and zones of resource depletion have appeared
Above-ground binary tree base module
Below-ground binary tree base module
Above-ground array
Below-ground array
Above-ground binary tree ( = shoot system)
Below-ground binary tree ( = root system)
A branching module
An end module
Each plant is built-up like this
This is only a diagram, not a painting !
Water and nutrients from below-ground
The branching modules (parent or offspring) can pass resources to any adjoining modules
The end-modules capture resources:
Light and carbon dioxide from above-ground
In this way whole plants can grow
The virtual plants interact with their environment (and with their neighbours) just like real ones do
They possess most of the properties of real individuals and populations
For example …
S-shaped growth curves Partitioning between root and shoot
Functional equilibria
Foraging towards resources
Self-thinning in crowded populations
0
500
1000
1500
2000
2500
3000
0 20 40 60 80 100 120 140Time (iterations)
Bio
mas
s (m
odul
es p
er p
lant
)
Light 1 Nutrient 6 Light 2 Nutrient 6
Light 1 Nutrient 8 Light 2 Nutrient 8
0.9
1
1.1
1.2
1.3
0 5 10 15 20Units of nutrient per cell
1 Light unit
2 Light units
Root/shoot allometric coefficient
1
10
100
1000
10000
1 10 100
Planting density
Bio
mass (
mo
du
les)
per
pla
nt
Slope -2/1
Size
Time
Allometric coefficient
Below-ground resource
Individual sizeSelf-thinning line
Population density
All of these plants have the same specification (modular rulebase)
And this specification can easily be changed if we want the plants to behave differently…
For example, we can recreate J P Grime’s system of C-S-R plant functional types
But what is that exactly?
‘ The external factors which limit the amount of living and dead plant material present in any habitat may be classified into two categories ’
Opening sentence from J P Grime’s 1979 book Plant Strategies and Vegetation Processes
Category 1: Stress
Phenomena which restrict plant production
e.g. shortages of light, water, mineral nutrients, or non-optimal temperature
Category 2: Disturbance
Phenomena which destroy plant production
e.g. herbivory, pathogenicity, trampling, mowing, ploughing, wind damage, frosting, droughting, soil erosion, burning
Habitats may experience stress and disturbance to any degree and in any combination
Stress
Disturbance
Low or moderate combinations of stress and disturbance can support vegetation …
Stress
Disturbance… but extreme combinations of stress and disturbance cannot
There are other ways of describing stress and disturbance
Stress
Disturbance
Habitat duration
Habitat productivity (= resource level)
In the domain where vegetation is possible …
Stress
Disturbance
… plant life has evolved different strategies for dealing with the different combinations
Competitor where both S and D are low
Stress-tolerator where S is high but D is low
Ruderal where S is low but D is high
C
S
R
C
S
RSo this is ‘C-S-R space’ …
… and these are the ‘habitats’ where no plant life occurs at all
C
S
R
To navigate in C-S-R space we bend the universe a little …
C
S
R
C
S
R
C
S
R
C
S
R
C
S
R
C
S
R
C S
R
C
S
R
C
S
R
C
SR
C
R S
C
R S
C
R S
CSR
… and recognize an intermediate type
C
R S
CSRCR CS
SR
… with further intermediates here
C
R S
CSRCR CS
SR
… and yet more intermediates here
So, how does all this relate to real vegetation?
The high dimensionality of real plant life is reduced to plant functional types
“ There are many more actors on the stage than roles that can be played ”
And what does that mean, exactly?
Functional types provide a continuous view of vegetation when relative abundances, and even identities, of constituent species are in flux
Tools that allocate C-S-R type to species, and C-S-R position to whole communities, can link separate vegetation into one conceptual framework
Then effects of environment or management on biodiversity, vulnerability and stability can be evaluated on a common basis
We can recreate C-S-R plant functional types within the self-assembling model …
… if we change the rulebases controlling morphology, physiology and reproductive behaviour …
Combinations of plant attributes for seven C-S-R functional types ————————————————————————————— Functional Module Module Propensity to type size longevity flowering ————————————————————————————— C High Low Low S Low High Low R Low Low High SC Medium Medium Low SR Low Medium Medium CR Medium Low Medium CSR Medium Medium Medium —————————————————————————————
With three levels possible in each of three traits, 27 simple functional types could be constructed
However, we model only 7 types; the other 20 would include Darwinian Demons that do not respect evolutionary tradeoffs
Let’s see some competition between different types of plant
Initially we will use only two types …
Small size, rapid growth and fast reproduction
Medium size, moderately fast in growth and reproduction
(Red enters its 2nd generation)
White has won !
Now let’s see if white always wins
This time, the opposition is rather different …
Medium size, moderately fast in growth and reproduction
Large size, very fast growing, slow reproduction
The huge blue type has out-competed both of the white plants, both above- and below-ground
And the simulation has run out of space …
So competition can be demonstrated realistically …
… but most real communities involve more than two types of plant
We need seven functional types to cover the entire range of variation shown by herbaceous plant life
To a first approximation, these seven types can simulate complex community processes very realistically
For example, an equal mixture of all seven types can be grown together …
… in an environment which has high levels of resource, both above- and below-ground
The blue type has eliminated almost everything except white and green types
And the simulation has almost run out of space again …
Now let’s grow the equal mixture of all seven types again …
… but this time the environment has low levels of mineral nutrient resource
(as indicated by the many grey cells)
(a gap has appeared here)
(red tries to colonize)
(but is unsuccessful)
White, green and yellow finally predominate …
… blue is nowhere to be seen …
… and total biomass is much reduced
Environmental gradients can be simulated by increasing resource levels in steps
Whittaker-type niches then appear for contrasting plant types within these gradients
0
20
40
60
80
100
0 5 10 15 20 25 30
Resource (= 1/stress)
% B
iom
ass
in m
ixtu
re
C
S
SC
(types)
Let’s grow the equal mixture of all seven types again …
… but this time under an environmental gradient of increasing mineral nutrient resource
0
1
2
3
4
5
0 5 10 15 20 25 30 35
Resources (= 1/stress)
Num
ber o
f pla
nt ty
pes
surv
ivin
g (m
ax 7
)
Greatest biodiversity is at intermediate stress
Remember that environmental disturbance was defined as ‘removal of biomass after it has been created’
Trampling is therefore a disturbance
It can be simulated by removing shoot material from certain sizes of patch at certain intervals of time and in a certain number of places
So we grow the equal mixture of all seven types again …
… under an environmental gradient of increasing ‘trampling’ disturbance
0
1
2
0 0.2 0.4 0.6 0.8 1
Probability of disturbance
Num
ber
of p
lant
type
s su
rviv
ing
(max
7)
Greatest biodiversity is at intermediate disturbance …
… but the final number of types is
low
Environmental stress and disturbance can, of course, be applied together …
… and this can be done in all forms and combinations
So, again we grow the equal mixture of all seven types …
… but in all factorial combinations of seven levels of stress and seven levels of disturbance
R 2 = 0.534
0
1
2
3
4
5
0 2000 4000 6000 8000 10000 12000
Total biomass (productivity)
Num
ber o
f pla
nt ty
pes
surv
ivin
g (m
ax 7
)
Greatest biodiversity is at intermediate productivity
The biomass-driven ‘humpbacked’ relationship is one of the highest-level properties that real plant communities possess
Yet it emerges from the model solely because of the resource-capturing activity of modules in the self-assembling plants
R 2 = 0.534
0
1
2
3
4
5
0 2000 4000 6000 8000 10000 12000
Total biomass (productivity)
Num
ber o
f pla
nt ty
pes
surv
ivin
g (m
ax 7
)
These are all real experiments with virtual plants
… and the plant, population and community processes all emerge from the one modular rulebase
We can now ‘plant’ whole communities of any kind and subject them to different environments or management regimes
Then we can look at topics such as biodiversity, vulnerability, resistance, resilience, stability, habitat / community heterogeneity, etc, etc.
And as the modular rulebase is simply a string of numbers2 3 1 4 2 3 2 1 2 2 1 3 3 1 2 3
which controls how big, how much, how long, how often …
2 3 1 4 2 3 2 1 2 2 1 3 3 1 2 3
2 3 1 4 2 3 2 1 2 2 1 2 3 1 2 3
2 3 1 4 2 3 2 1 2 2 3 2 1 1 2 3
(seems familiar?)
… we can modify this virtual genome wherever we like
either accurately
or inaccurately
and then follow the downstream consequences of GM
In real experiments with virtual plants …
One overnight run on one PC
Approx. 100 person-years of growth experiments
(not including the transgenic work!)
Any takers?
http://www.ex.ac.uk/~rh203/