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WHAT IS EVOLUTIONARY
FITNESS FOR?
Mississippi State University, 11/6/2015
Charles H. Pence
Department of Philosophy
and Re...
NATURAL
SELECTION
t = 0
t = 0 t = 1
t = 0 t = 1 t = 2
FITNESS
>
Orange organisms
leave more offspring
than teal organisms.
Orange organisms
leave more offspring
than teal organisms.
A circle: the tautology problem
Orange organisms will
probably (are disposed to)
leave more offspring than
teal organisms.
THE PROPENSITY
INTERPRETATION
OF FITNESS
TWO
NOTIONS
OF FITNESS
Matthen and Ariew (2002)
[F]or many this notion of an organism’s overall
competitive advantage traceable to heritable trai...
Matthen and Ariew (2002)
Fitness occurs also in equations of population
genetics which predict, with some level of
probabi...
Causal (vernacular) fitness: general
(causal) notion in natural selection
Predictive (mathematical) fitness:
predict future ...
THE
CLAIM
Causal fitness can be made to
survive counterexamples against it,
but at a cost.
It’s not clear just what predictive
fitness...
CAUSAL
FITNESS
The basic idea: Define the propensity
interpretation in terms of facts about
the possible lives an organism (with
a given g...
F(G, E) = exp
(
lim
t→∞
1
t ∫ω∈Ω
Pr(ω) ⋅ ln(ϕ(ω, t)) dω
)
F(G, E) = exp
(
lim
t→∞
1
t ∫ω∈Ω
Pr(ω) ⋅ ln(ϕ(ω, t)) dω
)
• Multi-generational life histories
F(G, E) = exp
(
lim
t→∞
1
t ∫ω∈Ω
Pr(ω) ⋅ ln(ϕ(ω, t)) dω
)
• Multi-generational life histories
• Changing genotypes and env...
F(G, E) = exp
(
lim
t→∞
1
t ∫ω∈Ω
Pr(ω) ⋅ ln(ϕ(ω, t)) dω
)
• Multi-generational life histories
• Changing genotypes and env...
Can plausibly be saved from
counterexamples
Results in a potential
metaphysical mess
PREDICTIVE
FITNESS
What is our inferential basis
for determining the values of
predictive fitness?
“Darwinian fitness” in basic population
genetics:
pt
qt
= wt ⋅
p0
q0
Expected number of offspring:
A(O, E) = ∑ P(QOE
i )QOE...
Fitness Property Inferential Basis Sample
Individual fitness,
relativizing to
environmental
conditions
One individual
life-...
Fitness Property Inferential Basis Sample
Trait fitness,
including envi-
ronmental and
pleiotropic effects
One trait-histor...
Fitness Property Inferential Basis Sample
Type fitness, natu-
ral populations
A moderate
number of type-
histories in simil...
Best-case (long-term
experimental evolution): great
inferential basis
Almost all natural populations:
poor inferential bas...
Another test case: chaotic
population dynamics
Assumption of most models of
fitness: non-chaotic population
dynamics
Question: How common is
non-chaotic dynamics in evolv...
Approach of Doebeli & Ispolatov (2014):
Investigate by simulating populations with
two features:
1. Density-dependent sele...
“Our main result is that the probability of
chaos increases with the dimensionality d
of the evolving system, approaching ...
-100 0 100
-100
0
100
x1
x2
Doebeli and Ispolatov (2014), fig. 5
Surely there’s no way to define
predictive fitness in these
scenarios?
“The invasion is exponential, but nonlinear
dynamics of the resident type produce
fluctuations around this trend. [Fitness]...
Chaotic population dynamics:
Common, and render
predictive fitness meaningless
Predictive fitness isn’t very
predictive after all
THE MORAL
Causal fitness can be saved
from counterexamples at the
cost of being made
metaphysically problematic
Predictive fitness … i...
Many uses of fitness:
• Mathematical parameter in models
• Causal property
• Proxies for strength of selection in
populatio...
Fitness concepts are far
more complex than a
dichotomy between two
simple roles for fitness.
QUESTIONS?
charles@charlespence.net
http://charlespence.net
@pencechp
What is Evolutionary Fitness For?
What is Evolutionary Fitness For?
What is Evolutionary Fitness For?
What is Evolutionary Fitness For?
What is Evolutionary Fitness For?
What is Evolutionary Fitness For?
What is Evolutionary Fitness For?
What is Evolutionary Fitness For?
What is Evolutionary Fitness For?
What is Evolutionary Fitness For?
What is Evolutionary Fitness For?
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What is Evolutionary Fitness For?

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I’ll argue that the conventional distinction between predictive and vernacular or causal fitness lies somewhere between misleading and false, and the landscape of evolutionary fitness is much more confusing than this dichotomy would suggest. While some advances have been made in understanding the causal role of fitness, resolving counterexamples to it leads us to a property that behaves in unexpected ways, and may well be metaphysically problematic. And on the other side, thanks to its own set of difficulties, it’s not clear just what predictive fitness was ever supposed to predict in the first place.

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What is Evolutionary Fitness For?

  1. 1. WHAT IS EVOLUTIONARY FITNESS FOR? Mississippi State University, 11/6/2015 Charles H. Pence Department of Philosophy and Religious Studies
  2. 2. NATURAL SELECTION
  3. 3. t = 0
  4. 4. t = 0 t = 1
  5. 5. t = 0 t = 1 t = 2
  6. 6. FITNESS
  7. 7. >
  8. 8. Orange organisms leave more offspring than teal organisms.
  9. 9. Orange organisms leave more offspring than teal organisms. A circle: the tautology problem
  10. 10. Orange organisms will probably (are disposed to) leave more offspring than teal organisms.
  11. 11. THE PROPENSITY INTERPRETATION OF FITNESS
  12. 12. TWO NOTIONS OF FITNESS
  13. 13. Matthen and Ariew (2002) [F]or many this notion of an organism’s overall competitive advantage traceable to heritable traits is at the heart of the theory of natural selection. Recognizing this, we shall call this measure of an organism’s selective advantage its vernacular fitness. According to one standard way of understanding natural selection, vernacular fitness – or rather the variation thereof – is a cause of evolutionary change. (56)
  14. 14. Matthen and Ariew (2002) Fitness occurs also in equations of population genetics which predict, with some level of probability, the frequency with which a gene occurs in a population in generation n + 1 given its frequency in generation n. In population genetics, predictive fitness (as we shall call it) is a statistical measure of evolutionary change, the expected rate of increase (normalized relative to others) of a gene … in future generations…. (56)
  15. 15. Causal (vernacular) fitness: general (causal) notion in natural selection Predictive (mathematical) fitness: predict future representation from central tendency/expected value
  16. 16. THE CLAIM
  17. 17. Causal fitness can be made to survive counterexamples against it, but at a cost. It’s not clear just what predictive fitness is supposed to predict.
  18. 18. CAUSAL FITNESS
  19. 19. The basic idea: Define the propensity interpretation in terms of facts about the possible lives an organism (with a given genotype, in a given environment) could have lived.
  20. 20. F(G, E) = exp ( lim t→∞ 1 t ∫ω∈Ω Pr(ω) ⋅ ln(ϕ(ω, t)) dω )
  21. 21. F(G, E) = exp ( lim t→∞ 1 t ∫ω∈Ω Pr(ω) ⋅ ln(ϕ(ω, t)) dω ) • Multi-generational life histories
  22. 22. F(G, E) = exp ( lim t→∞ 1 t ∫ω∈Ω Pr(ω) ⋅ ln(ϕ(ω, t)) dω ) • Multi-generational life histories • Changing genotypes and environments over time
  23. 23. F(G, E) = exp ( lim t→∞ 1 t ∫ω∈Ω Pr(ω) ⋅ ln(ϕ(ω, t)) dω ) • Multi-generational life histories • Changing genotypes and environments over time • Disposition (propensity) defined over modal facts about other possible lives of organisms
  24. 24. Can plausibly be saved from counterexamples Results in a potential metaphysical mess
  25. 25. PREDICTIVE FITNESS
  26. 26. What is our inferential basis for determining the values of predictive fitness?
  27. 27. “Darwinian fitness” in basic population genetics: pt qt = wt ⋅ p0 q0 Expected number of offspring: A(O, E) = ∑ P(QOE i )QOE i
  28. 28. Fitness Property Inferential Basis Sample Individual fitness, relativizing to environmental conditions One individual life-history Very small, un- representative Individual fit- ness, including similar/clonal organisms A small number of life-histories in similar environ- mental conditions Small, likely un- representative
  29. 29. Fitness Property Inferential Basis Sample Trait fitness, including envi- ronmental and pleiotropic effects One trait-history Very small, un- representative Trait fitness, in- cluding similar traits A small number of trait-histories in similar environ- mental conditions Small, likely un- representative
  30. 30. Fitness Property Inferential Basis Sample Type fitness, natu- ral populations A moderate number of type- histories in similar environmental conditions Moderately- sized, possibly representative Type fitness, experimental evolution A huge number of type-histories in nearly identical environmental conditions Large and rep- resentative, high-quality predictions
  31. 31. Best-case (long-term experimental evolution): great inferential basis Almost all natural populations: poor inferential basis
  32. 32. Another test case: chaotic population dynamics
  33. 33. Assumption of most models of fitness: non-chaotic population dynamics Question: How common is non-chaotic dynamics in evolving systems?
  34. 34. Approach of Doebeli & Ispolatov (2014): Investigate by simulating populations with two features: 1. Density-dependent selection pressures 2. High-dimensional phenotype space
  35. 35. “Our main result is that the probability of chaos increases with the dimensionality d of the evolving system, approaching 1 for d ∼ 75. Moreover, our simulations indicate that already for d ≳ 15, the majority of chaotic trajectories essentially fill out the available phenotype space over evolutionary time….” (D&I, 1368)
  36. 36. -100 0 100 -100 0 100 x1 x2 Doebeli and Ispolatov (2014), fig. 5
  37. 37. Surely there’s no way to define predictive fitness in these scenarios?
  38. 38. “The invasion is exponential, but nonlinear dynamics of the resident type produce fluctuations around this trend. [Fitness] can therefore be most accurately estimated by the slope of the least squares regression of [daughter population size] on t.” (Grant 1997)
  39. 39. Chaotic population dynamics: Common, and render predictive fitness meaningless
  40. 40. Predictive fitness isn’t very predictive after all
  41. 41. THE MORAL
  42. 42. Causal fitness can be saved from counterexamples at the cost of being made metaphysically problematic Predictive fitness … isn’t
  43. 43. Many uses of fitness: • Mathematical parameter in models • Causal property • Proxies for strength of selection in populations • Statistical estimator for any of the above
  44. 44. Fitness concepts are far more complex than a dichotomy between two simple roles for fitness.
  45. 45. QUESTIONS? charles@charlespence.net http://charlespence.net @pencechp

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