An Individual-Based Simulation Approach to the Evolution of Locomotor Performance

Area of Science:

• Evolutionary Biology
• Animal Performance
• Ecological Physiology

Background:

• A mismatch exists between maximal organismal performance measured in labs and field performance, hindering understanding of evolutionary selection pressures.
• Locomotor performance is crucial for survival and reproduction, but the evolutionary drivers of its variation remain unclear.

Purpose of the Study:

• To investigate the evolutionary selection pressures on locomotor performance using an individual-based simulation model.
• To determine if intra-individual variation in performance traits confers a selective advantage compared to consistently maximal performance.

Main Methods:

• Developed an individual-based simulation modeling populations with two correlated performance traits.
• Simulated individuals facing diverse ecological challenges requiring varying performance levels throughout their lifespan.
• Compared evolutionary outcomes between populations with fixed maximal performance and those with adjustable performance levels.

Main Results:

• Intra-individual variation in locomotor speed provides a significant selective advantage, irrespective of the degree of variation.
• The correlation's direction and strength between performance traits influence the evolutionary trajectory of phenotypic change.
• Infrequent, high-demand events like predator evasion impose strong selection for maximal performance, despite most challenges being sub-maximal.

Conclusions:

• Adjustable, rather than consistently maximal, performance is evolutionarily advantageous for locomotor traits.
• The interplay between trait correlation and environmental challenges shapes the evolution of performance.
• This model offers insights into the relationship between optimal and maximal performance in evolutionary contexts.