Simulations of Population Adaptability and Individual Mortality

A More Accurate Population Model Than "Survival of the Fit Enough"

Version 3.0

Prior Versions: 1.0 2.0

This version 3 of Filtering of the Unfit adds two new simulations of evolution. It also changes references to "Survival of the Fittest" to "Survival of the Fit Enough." I made this particular change due to comments at James Randi's JREF skepticism forums. Changing the terms from "fittest" to "fit enough" radically redefines the evolutionary model of Survival, making the fitness functions far less important in the process of evolution. I was delightfully surprised, as it brings the Survival model closer to the Filter model.

A Short FAQ on FOTU

What is "Filtering of the Unfit?"
FOTU is a natural population model which describes how populations change and why. It is a model that attempts to explain population adaptability and individual mortality. "Survival of the fit enough" (SOFE) is also a model that attempts to explain what we observe in nature.
Is it just "Survival of the Fit Enough" reworded?
No. FOTU more accurately models what is observed in the wild. It more accurately portrays observed scientific facts, such as genetic limits and mutation effects, by filtering unfit individuals instead of promoting "fit survivors." SOFE depends on biological processes not yet proven or demonstrated in a lab to explain a population's survivability when the fitness landscape changes. In SOFE, a small percentage at the top of the population of organisms go on to reproduce. In FOTU, a small bottom percentage of individuals die and the rest go on to reproduce. The implications for SOFE is that the selection pressure is significantly reduced. The "fittest" are no longer dominating the population because "fit enough" is the new standard.
Evolution claims that populations change when the fitness landscape changes.
FOTU claims that same thing. It has been observed in nature that this is true.

What evolutionists don't tell you is that when a fitness landscape changes significantly enough, the population dies (extinction).

Real world observation leads us to conclude that changes in the genome are a hindrance to survival when the fitness landscape does not change. "Adapt" is a pro-active word being applied to a passive environmental filtering process. In reality, when populations that change due to a changing fitness landscape, they always remain within a given set of boundaries (dogs will always be dogs, no matter what environment you put them in; reptiles will never become birds, no matter what environment you put them in). Also, what we find in the real world is that critters and their environments seem to be created for each other. Studies show that when the fitness landscape changes too much, populations die (extinction). They don't evolve.
Can mutations ever result in an survival advantage?
Yes. There is one known instance where a mutation has provided a survival advantage: sickle-cell anemia. For someone in an environment where malaria is prevalent, having sickle-cell anemia is a survival advantage. However, sickle-cell anemia brings with it many detrimental side-effects, including death.

SOFE requires, not just beneficial mutations, but novel beneficial mutations. In other words, rearranging genes- sickle-cell anemia is caused by a substitution mutation- is not a path to evolution but to devolution. You can rearrange genes all you want and you'll never go from amoeba to man (which is what evolution claims is possible).
If FOTU is right, then all organisms are fit for their environment and mutants are culled. "Evolution" thus simply becomes a method of culling the herd and preserving the purity of our genes.
This is exactly what we observe in nature. Populations are fit in their environment (fitness landscape) and have no pressure to "evolve." It is only when a fitness landscape changes that there is pressure for the population to evolve. But, again, you can select all you want, you'll never go from amoeba to man that way.
What about beneficial mutations like one that gives a predator better eyesight? How does a mutation that makes a harmless frog look like a poisonous frog throw it outside the range of survivability?
There is no mutation that gives a predator better eyesight, nor is there one that makes a harmless frog look like a poisonous frog. In order for these things to happen, many multiple thousands (Dawkins speculates hundreds of thousands) of mutations must take place. So, no, there is no single mutation that will do these things.
Eugenie Scott rephrased "Survival of the Fittest" to "Survival of the Fit Enough," which really better describes the process.
E. Scott removes the pillar of "selection pressure" and evolution falls down.

What observations in nature and the lab show is that all individuals are fit unless they suffer a change in their genome which causes them to fall outside the boundary of survivability.

In the traditional "survival of the fit enough" adaptation, an organism in an environment with a changing fitness landscape must improve (and the mechanism is mutation) in order to have a better chance at reproductive success. If there is no change in the fitness landscape, there is no pressure to evolve. If there is no pressure to evolve, then "beneficial" mutations have no selection pressure acting on them to propagate into the population. By removing the pressure to evolve, you reach stasis. All organisms remain fit unless a mutation knocks them out of the fitness range.

Newsweek reports, "Animals are in a continuous struggle to survive and reproduce, and it was Darwin's insight that the winners, on average, must have some small advantage over those who fall behind."

Newsweek is describing a population change scenario, not a process whereby an amoeba turns into a man. For example, in a human population in Africa, those with sickle-cell anemia will survive malaria outbreaks and go on to reproduce. The progeny of these survivors will, of course, inherit the sickle-cell trait or the disease itself. Those without this sickle-cell protection will die before mating. No matter how many generations go by, however, they will always reproduce homo sapiens. In other words, this is not the process that turns amoebas into humans.

In nature, what we observe is that nature doesn't select the fittest, it eliminates the unfit. This removes the advantage of "fittest" for reproduction. This means that in a population of 100, the "top three" don't advance, but rather, the "bottom three" don't. The implication is that the "top three," those who are "most fit," don't have an advantage over the 98% who aren't as fit. Therefore, there's no selection pressure for these most fit organisms. There's just a filtering effect of those who are least fit (for instance, the sick, wounded, etc.).

I've developed several computer programs that simulate FOTU and packaged them into one executable that you can download here (ZIP file). Each program has a simple accompanying information screen. Below, I've provided some general definitions and feature highlights of the Adaptation Simulation. Check it out and let me know if I've missed anything in the specs.

The FOTU Simulations

There are currently three simulations:

  1. The Reality of Mutations - What happens when an organism's DNA is mutated
  2. Cheating for Evolution's Sake - This simulation takes some liberties in evolution's favor. Will evolution take advantage?
  3. Adaptation (see below)

The Adaptation Simulation starts with a population of fit individuals.

The Adaptation Simulation manages four items:

  • Organisms - Our rollers.
  • Traits - Organisms have certain traits. In the case of rollers, they are Diameter, Weight, Skin, Father, Mother. These traits are generally heritable, but can be mutated during the copulation event.
  • Environment Filters - Environment Filters act on an organism's traits and determine whether or not that organism can survive in that environment.
    • Minimum Range Filters - These require that the trait of an organism meet a minimum value.
    • Maximum Range Filters - These require that the trait of an organism meet a maximum value.
    • Spotlight Filters - These require that the trait of an organism falls outside of a range, either above it or below it. For example, a Predator Filter acts on the Skin trait. If an organism's Skin value falls in the predator's "spotlight"- a narrow range of values within the population's genetic range for that trait- there is a much higher chance the predator will consume that particular organism. Organisms whose Skin value lie outside this spotlight have a far greater chance of not being filtered out.
  • DNA - Each organism's traits are encoded in a simple DNA structure. The DNA of male and female parents are used to determine the DNA of the couple's offspring. Generally, it randomly determines which parental trait will be inherited. However, more advanced inheritance rules can easily be plugged into the program for greater variety in this aspect of the simulation.

    Mutation Events - All traits are heritable, and any could be modified by mutation events. For instance, when and if a male and female are able to copulate, the offspring will inherit the combined characteristics of the male and female parents according to an inheritance algorithm. There is a very slight chance for a mutation event, which will modify one (or more) traits, and after which the offspring could fall outside the bounds of possible normally-inherited characteristics.

The simple organisms of the FOTU Simulation are called "rollers." The analogy I use is one of a ball rolling through an obstacle course of tubes and ramps (see diagram below). The roller must traverse these obstacles in order to "succeed" at life. Each obstacle in our analogy represents a natural filter in real life. For instance, the Predator filter represents an organism's ability to evade predators.

StageActivityLimit
1. BirthTube of Life - Stage 1Max diameter for tunnel diameter
2. InfantTube of Life - Stage 2Min diameter for gap
3. EvasionPredatorsSurvival color/pattern to evade predators
4. YouthRamp of LifeMax weight for incline
5. AdolescenceBlow HoleMin weight for air pressure
6. Mating DanceFinding a MateAn organism must find a mate before its lifespan variable reaches zero.
7. CopulationMating the MateAn organism must successfully copulate in order to produce offspring.
8. Mutation OpportunityGene ModificationA successful production of offspring has a chance for mutation.
Repeat.A New Roller is Born!This will repeat ad infinitum until 1) we get tired of the simulation, or 2) there are no more rollers alive.

I don't want to put too fine a point on any variable yet, but in the future, such things as the roller's size and weight can be determined or affected by additional variables, such as

  • Food supply - Decreasing the available food (maybe due to a population loss of the organism's primary food source) will decrease an organism's ability to eat and survive.
  • Reproductive Advantage - those Roller's that are most fit for their environment will have more energy remaining for the reproductive stage. More energy means a better chance to pass along those fit genes.
Simulation Diagram

In order to "reproduce," the roller must "survive" the variety of variables in its life. It will have certain characteristics which will determine whether or not an individual roller survives each of the life obstacles. Currently, those characteristics are as follows:

  • Diameter
  • Weight
  • Skin (patterns or a spectrum of colors could ultimately be used to represent the possibilities)

Other variables which affect a roller's life:

  • Population size of Males and Females - In the "Mating Ritual" event, if a male cannot find a female partner, or vice versa, then a copulation event will not occur. Even if a copulation event does occur, there is a slight chance the result will not be successful. This is a simple model of what we find occurs in real life, but it has huge implications. It is rare that a population starting with one male and one female is able to survive for very long.

Changes in the environment are simulated by simply changing a filter's parameters:

  • The diameter of the Tube of Life
  • The width of the gap between Stage 1 and Stage 2 Tubes
  • The preference of predators for a particular skin type
  • The slope of the incline
  • The strength of the airflow

As an example, the diameter of the Tube of Life will fluctuate randomly to represent slight changes in the environment. As the diameter changes, some rollers will not be able to "fit" through the opening. They will die. They are "filtered out." Only those who are small enough to "fit" (no pun intended) will survive. Also, there is a minimum weight required to not get blown off the incline by the airflow pressure (#5). Too light and the roller will fly off into space and perish. Too heavy, and the roller won't be able to ascend the incline to the mating area.

The starting population will be variable. The user will be prompted to enter a value for each at the beginning. This leads to interesting questions:

  • In real life, which came first? The male or female?
  • When the first male showed up ready for sexual reproduction, was the female ready (or vice versa)?
  • How did they know they could (or would need to) copulate when it had never ever happened before?

2007-12-09 at 00:00:00 | 2 comments
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