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A SPATIALLY EXPLICIT STOCHASTIC MODEL DEMONSTRATES THE FEASIBILITY OF WRIGHT'S SHIFTING BALANCE THEORY
Steven L Peck1,2, Stephen P Ellner1, Fred Gould2
1Graduate Program in Biomathematics, Department of Statistics, North Carolina State University, Raleigh, North Carolina, 27695-8203.
Summary
Wright's Shifting Balance Theory (SBT) explains trait evolution through adaptive valleys. Our models show that Phase III of SBT, the spread of new traits, occurs under broader conditions with local, random migration of individuals.
Area of Science:
- Evolutionary biology
- Population genetics
Background:
- Wright's Shifting Balance Theory (SBT) models trait evolution in substructured populations.
- SBT explains how traits may evolve across adaptive valleys.
- Recent theoretical work suggests Phase III of SBT has restricted conditions.
Purpose of the Study:
- To re-evaluate the conditions for Phase III of the Shifting Balance Theory.
- To investigate the role of local, random migration in trait spread.
- To demonstrate broader applicability of SBT under specific migration models.
Main Methods:
- Theoretical modeling of population genetics.
- Simulation of discrete individuals with local, random migration.
- Analysis of trait spread (Phase III) under varying conditions.
Main Results:
- Phase III of SBT can proceed under a wider range of conditions than previously suggested.
- Local, random migration of discrete individuals is a key factor enabling Phase III.
- Models incorporating this migration pattern support broader SBT applicability.
Conclusions:
- The Shifting Balance Theory's Phase III is more robust than previously assumed.
- Local, discrete individual migration is crucial for the theory's validity.
- This research expands the theoretical understanding of evolutionary mechanisms.
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