[Computer simulation of different types of evolutionary process]

Area of Science:

• Evolutionary Biology
• Computational Biology
• Ecology

Background:

• Biological evolution can proceed through random (Darwinian) or directed (non-Darwinian) changes in individual traits.
• Understanding the comparative dynamics of these evolutionary models is crucial for ecological and evolutionary research.

Purpose of the Study:

• To develop and investigate a computer model comparing Darwinian and non-Darwinian evolution.
• To analyze the impact of each evolutionary variant on species diversity, adaptation, and evolutionary trajectory complexity.

Main Methods:

• A computer model simulating biological evolution using object-oriented programming.
• Application of fuzzy logic for mathematical analysis of evolutionary processes.
• Case study focusing on the evolution of freshwater fish communities.

Main Results:

• Darwinian evolution resulted in significantly higher species diversity and more variable evolutionary trajectories compared to non-Darwinian evolution.
• Non-Darwinian evolution achieved faster individual fitness gains, particularly in constant environments.
• Darwinian evolution facilitated major evolutionary transitions (e.g., predation) but incurred higher extinction rates and produced more complex phylogenetic trees.

Conclusions:

• Darwinian evolution offers greater long-term adaptability and biodiversity, albeit with slower progress and higher extinction rates.
• Non-Darwinian evolution excels in rapid adaptation to stable conditions but struggles with significant environmental changes or novel adaptations.
• The complexity of evolutionary outcomes, including phylogenetic structure, differs markedly between random and directed evolutionary models.