with acknowledgements to Titles Self-assembling plants and integration across ecological scales Philip Grime ( Sheffield, UK ) Andrew Askew ( Sheffield, UK ) Presentation ready Roderick Hunt ( Exeter, UK ) Ric Colasanti ( Corvallis, OR )

Community image patches of resource depletion showing above- and below-ground A community of self-assembling virtual plants

CSR type, frame 1 A single propagule … … about to grow

ditto f. 2

ditto f. 3

ditto f. 4

ditto f. 5

ditto f. 6

ditto f. 7

ditto f. 8

ditto f. 9

ditto f. 10

ditto f. 11

ditto f. 12

ditto f. 13

ditto f. 14

ditto f. 15

ditto f. 16

ditto f. 17

ditto f. 18

ditto f. 19

ditto f. 20 Abundant growth above- and below-ground … … with zones of resource depletion

Binary tree diagram 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 like this … … only a diagram, not a painting !

Water and nutrients from below-ground Parent or offspring modules can pass resources to any adjoining modules Explanation End-modules capture resources: Light and carbon dioxide from above-ground … so whole plants can grow

The virtual plants interact with their environment and neighbours They possess most properties of real individuals and populations Explanation For example …

S-shaped growth curves Partitioning between root and shoot Validation Functional equilibria Foraging towards resources Self-thinning in crowded populations Size Time Allometric coefficient Below-ground resource Individual size Self-thinning line Population density

The foregoing plants all have the same functional specification ( modular rulebase ) But specifications can be changed if we want some plants to behave differently … Explanation … and we can simulate plant functional types … not yet comparative plant ecology !

Some working definitions … Species within one functional group share a single important trait Species within one functional type share a similar set of traits. Definitions

Functional types are multi-species levels of organization, lying above the population but below the community … and some implications A single species can simultaneously be a member of several functional groups, e.g. both ‘legume’ and ’woody’ … Implications … but a member of only one functional type, e.g. ‘ K -strategist’

Why use functional types? They reduce the high dimensionality of real plant life “ There are many more actors on the stage than roles that can be played ” Why use?

PFTs give a continuous view of vegetation even when relative abundances and identities of species are in flux Tools exist to allocate types to species (and type- mixes to whole communities) Large-scale (or cross-scale) studies of effects of environment or management on (e.g.) biodiversity, vulnerability and stability become possible... continued

How do we recreate basic PFTs within the self- assembling model ? … we change the modular rulebases controlling morphology, physiology and reproduction … PFTs in CA … but we must begin to model at a high enough level to get “ airborne ”... we need access to the emergent properties

Building blocks So we don’t build with these… we build with these !

Specifications TypeMorphologyPhysiologyReproduction module size,tissue longevity,flowering speed, 1LargeFastSlow 2SmallSlowSlow 3SmallFastFast 4MediumMediumSlow 5SmallMediumMedium 6MediumFastMedium 7MediumMediumMedium resource demandRGR, SLA, allocation, decomposabilitypropagule size Building a set of PFTs …

Three levels in each of our three ‘ super-traits ’ = 27 possible PFTs … … but we model only 7 types the other 20 would include Darwinian Demons that do not respect evolutionary tradeoffs Explanation

Competition between two different types of plant … Explanation

R-CSR-R, frame 1 Small size, rapid growth and fast reproduction Medium size, moderately fast in growth and reproduction

ditto f. 2

ditto f. 3

ditto f. 4

ditto f. 5

ditto f. 6

ditto f. 7

ditto f. 8

ditto f. 9 ( Red enters its 2 nd generation)

ditto f. 10

ditto f. 11

ditto f. 12

ditto f. 13

ditto f. 14

ditto f. 15

ditto f. 16

ditto f. 17

ditto f. 18

ditto f. 19

ditto f. 20 White has won !

This one-on-one competition is very realistic … … but most communities involve more than two types of plant Explanation

Seven PFTs can cover the entire range of variation shown by herbaceous plant life … … and to a first approximation, these seven can simulate complex community processes very realistically Explanation

For example, we grow an equal mixture of all seven types together … … in an environment with high levels of resource above- and below-ground Explanation

7 types, high nutrient, f.1

ditto f.2

ditto f.3

ditto f.4

ditto f.5

ditto f.6

ditto f.7

ditto f.8

ditto f.9

ditto f.10

ditto f.11

ditto f.12

ditto f.13

ditto f.14

ditto f.15

ditto f.16

ditto f.17

ditto f.18

ditto f.19

ditto f.20

Blue has eliminated almost everything except White and Green … … and the simulation has almost run out of space Explanation

ditto f.20 again

Environmental gradients = stepwise increases in resource level Explanation Whittaker-type niches emerge for each PFT

Whittaker-type gradient (types) Three PFTs in an initially equal mixture

The equal mixture of all seven types again … … but under environmental gradients of increasing mineral nutrient resource or increasing trampling disturbance Explanation

Stress-driven hump Greatest biodiversity at intermediate stress

Disturbance-driven hump Greatest biodiversity at intermediate disturbance

Stresses and disturbances can be applied together … Explanation … in many forms and combinations, generating a big range of productivity classes

Productivity-driven hump Greatest biodiversity at intermediate productivity

The biomass-driven ‘humpbacked’ relationship … one of the highest-level properties of real plant communities … … emerges solely from the resource-capturing activity of modules in the self-assembling plants Explanation

In our closed system, the biodiversity-productivity hump eventually collapses with time … Explanation

Surface 1

But additional treatments can prevent this collapse … Explanation Environmental heterogeneity (spatial and / or temporal) ‘ Seed rain ’ (propagules introduced from external sources)

Surface 2 No external seed rain Probability of one external seeding event per cell per iteration (random plant types)

Real experiments with virtual plants … individual, population and community processes emerge from one modular rulebase We can ‘plant’ communities in any PFT mix and grow them under any environmental or management regime … … to look at topics like biodiversity, vulnerability, resistance, resilience, stability, habitat / community heterogeneity, etc, etc. Summary

The modular rulebase is simply a string of numbers controlling how big, how much, how long, how often … … so we can modify this virtual genome when / wherever we like either accurately or inaccurately and follow the downstream community consequences of GM

In real experiments with virtual plants … One overnight run on one PC Approx. 100 person-years of growth experiments  Want to get airborne with us ? Signoff

(Dissolve to black)