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Evolution, Complexity, and Life History Theory.

Walter Veit1,2,3, Samuel J L Gascoigne3,4, Roberto Salguero-Gómez3,5,6

  • 1Department of Philosophy, University of Reading, Reading, UK.

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Summary
This summary is machine-generated.

Evolution may favor increasing organismal complexity, but a quantitative measure is needed. Life history theory offers a framework to measure this complexity using survival and reproduction strategies.

Keywords:
Biological complexityEntropyEvolutionary trendsFitnessGoal directednessLife history complexityLife history theoryOptimalityTeleonomy

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Area of Science:

  • Evolutionary Biology
  • Theoretical Biology
  • Life History Theory

Background:

  • The debate on whether evolution trends towards increased organismal complexity is ongoing.
  • Current discussions are hampered by the absence of a quantitative measure for complexity linked to the goal-directed nature of life.
  • Life history theory provides a potential avenue for developing such a measure.

Purpose of the Study:

  • To propose a quantitative measure of biological complexity rooted in life history theory.
  • To outline a framework for testing the hypothesis of increasing complexity in evolution.
  • To establish an agenda for future research on measuring and comparing evolutionary complexity.

Main Methods:

  • Revisiting the debate on evolutionary complexity using an interdisciplinary approach.
  • Identifying life history strategies as a proxy for quantifying biological complexity.
  • Proposing mathematical methods for measuring complexity and comparative analyses across species.

Main Results:

  • Life history strategies, encompassing schedules of survival and reproduction, can serve as a quantitative measure of biological complexity.
  • This measure is directly linked to the teleonomic (goal-directed) nature of living systems.
  • The proposed framework allows for the investigation of evolutionary forces driving changes in complexity.

Conclusions:

  • Life history theory offers a robust framework for quantifying biological complexity.
  • Measuring complexity via life history strategies can advance the study of evolutionary patterns.
  • Future research should focus on mathematical quantification and cross-species comparative analyses of teleonomic complexity.