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

3. 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.

4. 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.

5. 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

6. Gaia Theory • Organisms both affect and regulate their environment. – James Lovelock

7. 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

8. Carbon Cycle Carbohydrates Herbivores, detritivores Photosynthesising plants Carbon dioxide

9. 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

10. 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

11. 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

12. Criticisms of Daisyworld • Small genotype space: doesn’t 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

13. 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

14. Guild Model • Biochemical Guild: Organisms that have the same nutrient inputs and outputs • Organisms cannot consume and produce the same chemical

15. 1 … n 1 … n 1 … n 1 … n At the Environmental Level • Nutrients N1…Nn • Input fluxes • Output fluxes • Environment chemicals (internal amount)

16. 1 … n 1 … n 1 … n 1 … n At the Genome Level • enZyme genes: Zk = 1 means that organism produces an enzyme to free Nk from the detritus • Chemical genes • Finpercentage of each nutrient consumed (input) • Foutpercentage of each nutrient produced (output)

17. Organism characteristics • Rf : base feeding rate • Rm : metabolism rate • X : biomass • ksat : satisfaction

18. 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 ratio • An individual’s 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

19. Local Chemical Ratio

20. 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)

21. 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

22. 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)

23. 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

24. 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

25. 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

26. 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

27. 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]

28. Population Size

29. 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.

30. Diversity

31. 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

32. 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

33. 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

36. 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

37. Cycling Ratio

38. 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

39. 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

40. 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

41. 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

42. 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?

43. 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

44. 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/111.html • http://www.alife.org/links.html