Research Critique:

1
Research Critique

• The Simulated Evolution of Biochemical Guilds
  Reconciling Gaia Theory and Natural Selection
• K. Downing P. Zvirinsky, 2000

Presenter Joanne Lee Date 30th August, 2004
2
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 Darwins 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
• NP ratio in oceans is identical to NP 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
Carbohydrates
Herbivores, detritivores
Photosynthesising plants
Carbon dioxide
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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 criticisms
• Simulation of two species of daisies living on a
  planet
• Same preferred temperature of 22.5C
• Black 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 proliferate
• As the temperature increases, white daisies take
  over
• Inevitably, 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 C
• Conclusion Simple local interactions among the
  biota can have global regulatory consequences

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Criticisms of Daisyworld

• Small genotype space doesnt show relationship
  between evolution and regulation
• What 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 or
• prefer 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 N1Nn
• Input fluxes
• Output fluxes
• Environment chemicals (internal amount)

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At the Genome Level

• enZyme genes Zk 1 means that organism produces
  an enzyme to free Nk from the detritus
• Chemical genes
• Fin percentage of each nutrient consumed (input)
• Fout percentage of each nutrient produced (output)

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Organism characteristics

• Rf base feeding rate
• Rm metabolism rate
• X biomass
• ksat satisfaction

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Satisfaction

• An organisms satisfaction is based the deviation
  of its local perception of the relative fractions
  of the environmental nutrients from a
  user-defined optimal ratio
• An individuals input and output fractions are
  taken into account when computing the effective
  nutrient fractions that it experiences
• The 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 nutrients
• Mortality rate is dependent on population density
• The biomass of a dead organism is partitioned
  into the detritus in direct proportion to its
  input nutrients
• An 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 capacity
• Reproduction through replication an organism
  splits into two when it has doubled its biomass
• Mutations 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
  guild
• The 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 100
• Max population size 2000
• Number of generations 800
• Timesteps per generation 50
• Mutation rate / individual 0.5
• Conjugation fraction / generation 0.2
• Number of nutrients 4
• Initial 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

34
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 900
• Throughput of the recycling networks increase.
  Cycling ratios increase

35
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
  fluxes
• At 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 waste
• Additional vision and metabolic genes
• Gene mutations occur throughout a lifetime, but
  phenotypic results are manifest only in the next
  generation
• Findings are consistent with the simulations in
  the 1D environment

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Simulation Results

• Emergence of nutrient recycling networks
• Set of nutrients vast number of organisms ?
  resource competition ? emergence of many
  biochemical guilds ? nutrient recycling networks
• Emergence of global regulation of chemical ratios
• Under-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
  .html
• http//neuron-ai.tuke.sk/zvirinsk/projects.htm
• http//neuron.tuke.sk/zvirinsk/thesis/index.html
• http//www.idi.ntnu.no/grupper/ai/eval/guild/guild
  .html
• http//userpage.chemie.fu-berlin.de/steffen/bcc/1
  11.html
• http//www.alife.org/links.html