Research Critique:The Simulated Evolution of

Biochemical Guilds: Reconciling Gaia Theory and Natural Selection

K. Downing & P. Zvirinsky, 2000

Presenter: Joanne LeeDate: 30th August, 2004

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Talk Outline

Neo-Darwinism vs. Gaia Theory

Daisyworld

Guild Model

Simulation Results

Critique of Guild Model

Conclusion

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Question: How did giraffes get their long necks?

Inheritability of Acquired Characteristics: The giraffes stretched their necks, and so their children and subsequent generations were born with long necks.

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Question: How did giraffes get their long necks?

Survival of the fittest: Giraffes born with long necks had a better chance of survival than those born with short necks, and so had an increased reproduction rate. Over time, the giraffe population became long-necked.

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Neo-Darwinism

Main ideas:Survival of the fittest: individual selection, not group selection

Combines Darwin’s views with genetics

Neo-Darwinism is the most widely taught and accepted view on evolution

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Gaia Theory

Organisms both affect and regulate their environment. – James Lovelock

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Observation

Local biotic mechanisms regulate global chemical concentrations

N:P ratio in oceans is identical to N:P ratio in algae and zooplankton

There exist efficient recycling pathways for poorly-supplied nutrients

High cycling ratios for carbon, nitrogen and phosphorus support far more biomass than what external fluxes alone can support

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Carbon Cycle

Carbon dioxide

Carbohydrates

Photosynthesising plants

Herbivores, detritivores

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Neo-Darwinism vs. Gaia Theory

How do recycling networks and chemical regulation emerge? Neo-Darwinists accuse Gaia theory of:

Group selection

Teleology

Adaptationist wing of Neo-Darwinism states that organisms adapt to their environment, while Gaia Theory claims that organisms adapt but also influence their environment

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Daisyworld

Simple differential-equation model to refute Gaia theory criticismsSimulation of two species of daisies living on a planet

Same preferred temperature of 22.5CBlack daisies have a low albedo, creating warmer local temperatures White daisies have a high albedo, creating cooler local temperatures

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Scenario

Daisyworld is subject to levels of increasing temperature

At low temperatures, black daisies proliferateAs the temperature increases, white daisies take overInevitably, temperature becomes too hot and no daisies survive

Observation: For a limited range of temperature inputs, daisies are able to keep the temperature at 22.5 CConclusion: Simple local interactions among the biota can have global regulatory consequences

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Criticisms of Daisyworld

Small genotype space: doesn’t show relationship between evolution and regulationWhat if Daisyworld was extended to include genotypes for temperature preference? At any point in the simulation, the population comprises daisies that:

prefer the current temperature; prefer a higher temperature and have a low albedo; orprefer a lower temperature and have a high albedo

Simulations show that daisies will simply adapt to the rising temperature, rather than regulate it

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Guild Model

Objective: To simulate the emergence of nutrient recycling networks and chemical ratio regulation using natural selection mechanisms

Key element borrowed from Daisyworld:

Organisms are able to create local buffers against the environment

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Guild Model

Biochemical Guild: Organisms that have the same nutrient inputs and outputs

Organisms cannot consume and produce the same chemical

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At the Environmental Level

Nutrients N1…Nn

Input fluxes

Output fluxes

Environment chemicals (internal amount)

1 … n

1 … n

1 … n

1 … n

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At the Genome Level

enZyme genes: Zk = 1 means that organism produces an enzyme to free Nk from the detritusChemical genes

Fin percentage of each nutrient consumed (input)

Fout percentage of each nutrient produced (output)

1 … n

1 … n

1 … n

1 … n

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Organism characteristics

Rf : base feeding rate

Rm : metabolism rate

X : biomass

ksat : satisfaction

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Satisfaction

An organism’s satisfaction is based the deviation of its local perception of the relative fractions of the environmental nutrients from a user-defined optimal ratioAn individual’s input and output fractions are taken into account when computing the effective nutrient fractions that it experiencesThe closer the ratio is to the user-defined optimal ratio, the higher the satisfaction

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Local Chemical Ratio

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Feeding and Metabolism

Afeed = X0.75 * rf * S

Example: X0.75 = 900, rf = 0.01, S = 1, then Afeed = 9. The organism attempts to consume 9 units of nutrients, in the proportion specified by its input alleles.The input nutrients are immediately converted into biomass

Ametab = X0.75 (rm + nz * costz)

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Death and Decay

An organism dies if it cannot access sufficient input nutrientsMortality rate is dependent on population densityThe biomass of a dead organism is partitioned into the detritus in direct proportion to its input nutrientsAn organism feeds on detritus only if there are no available nutrients left to feed on, and if it produces a nutrient-specific enzyme to free the nutrient from the detritus

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Reproduction

Reproduction is permitted only if the population has not reached its carrying capacityReproduction through replication: an organism splits into two when it has doubled its biomassMutations may occur during replication A percentage of organisms are randomly selected for conjugation (chromosomal crossover)

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Global Measures of System Performance

An efficiently recycling ecosystem is where:

The outputs of one guild are consumed by another guildThe detritus of one guild is freed by the enzymes of another guild and immediately consumed

These processes prevent chemical loss from the environment and increase the biomass

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Global Measures of System Performance: Cycling Ratio

The amount of nutrients consumed over the amount available from the input flux

The higher the ratio, the more self-sufficient the environment is

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Ideal Free Distribution (IFD)

IFD error compares the ratio of the available nutrients (environment and detritus) against the average input nutrient ratio of the biota.

Essentially, IFD measures how well the biota has adapted to its environment. The biota has completely adapted when IFD = 0

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Guild Simulation in 1D

Initial population size: 100Max population size: 2000Number of generations: 800Timesteps per generation: 50Mutation rate / individual: 0.5Conjugation fraction / generation: 0.2Number of nutrients: 4Initial biomass units: 20

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Guild Simulation in 1D

Homogenous population of 100 individuals: All individuals produce N1

All individuals consume N2

No individuals produce enzymes

Nutrient inputs: [20,20,20,20] (Generations 1 – 400)[5,10,25,50] (Generations 401 – 600)[50,25,10,5] (Generations 601 – 800)

Goal environmental chemical ratios:[0.4,0.3,0.2,0.1]

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Population Size

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Population Size

Initially every individual consumes N2, but there is not enough N2 to support the whole population. Population size drops to below 50 at startup.Due to mutation, some individuals can now consume a nutrient other than N2. With an alternative nutrient to feed on, the population starts increasing after 100 generations.

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Diversity

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Diversity

At startup, all individuals produce N1 and consume N2

Over 300 generations, the production and consumption of the 4 nutrients converge to an equal proportion

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Enzyme Production

Increasing enzyme production in the first 100 generations is followed by decreased enzyme production in generations 101 - 300

There is insufficient detritus to support the growing number of decomposers, and so the metabolic cost of producing enzymes does not pay off

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Increase in N1-only Consumers

After 300 generations, an N1-only consumer emerges

Because all individuals produced N1 at startup, there is an abundant amount of N1 in the environment

Conditions for N1-only consumers are ideal, and so the population of N1-only consumers multiplies rapidly

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Population Boom

Increased diversity, but constant biomass

Advent of N1-only consumer allows conversion of N1 into biomass

The output nutrients of the N1-only consumers supply other organisms with nutrients – this triggers a population boom as organisms feed and multiply. Population size is now over 900Throughput of the recycling networks increase. Cycling ratios increase

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Population Limit Reached

When the population exceeds 900, the system reaches a new steady-state limit, which can only be increased by changes in the external nutrient fluxesAt this density, competition for nutrients is fierce. Enzyme production is an advantage, allowing individuals to tap into the nutrients stored in the detritus.Increased detritus feeding increases the cycling ratio

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Emergence of global nutrient-ratio control

Prior to the population-size and recycling booms, N1 made up a large fraction of the environmental nutrients.After generation 300, the input diversity is diverse enough to ensure the consumption of most available nutrients, rather than having them left untouched in the environment.

Recycling loops primed by N1 consumption then facilitate a biomass increase

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Cycling Ratio

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Extreme Control Problems

Input flux: [5,10,25,50]

Optimal ratio: [1/18,10/18,5/18,2/18]

Control is only feasible when biotic diversity reduces the dominance of any one nutrient. After this, the chemicals partition into values close to the desired ratios

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Guild Model in 2D: Implementation in SWARM

Agents move around a 2D grid, eat nutrients and produce other nutrients as metabolic wasteAdditional vision and metabolic genesGene mutations occur throughout a lifetime, but phenotypic results are manifest only in the next generationFindings are consistent with the simulations in the 1D environment

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Simulation Results

Emergence of nutrient recycling networksSet of nutrients + vast number of organisms resource competition emergence of many biochemical guilds nutrient recycling networks

Emergence of global regulation of chemical ratiosUnder-consumed nutrients + new consumers population explosion increase in cycling ratios high transfer fluxes between guilds control of global chemical ratios, via their cumulative production and consumption.

Coordinated behaviour is not due to group selection or teleology. It can be explained by individual-based natural selection

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Significance of Findings

Previous models such as Daisyworld support the compatibility of Gaia and natural selection, but they exhibit a certain hard-wiredness

The Guild Model showed that global regulation can also emerge from the aggregate metabolism of a community

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Critique of Guild Model

In the real world, recycling networks refer to when the same nutrient cycles through the network (albeit in different forms). An organism cannot feed on a nutrient and then output an arbitrary nutrient as waste

Recall the Law of Conservation of Matter: Matter cannot be created or destroyed

Limited genotype space: what if biota adapted to the current chemical ratios, rather than trying to change it?

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Conclusion

Guild Model supports the view that the emergence of nutrient recycling networks and regulation of chemical ratios are consequences of natural selection

Needs to strengthen its argument by revising its chemical model and the issue of evolving preferences

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References

http://alife.tuke.sk/projekty/mag_html/guild/guild.htmlhttp://neuron-ai.tuke.sk/~zvirinsk/projects.htmhttp://neuron.tuke.sk/~zvirinsk/thesis/index.htmlhttp://www.idi.ntnu.no/grupper/ai/eval/guild/guild.htmlhttp://userpage.chemie.fu-berlin.de/~steffen/bcc/111.htmlhttp://www.alife.org/links.html