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An Alternative Formulation for a Distributed Delayed Logistic Equation.
Chiu-Ju Lin1, Lin Wang2, Gail S K Wolkowicz3
1Department of Mathematics & Statistics, McMaster University, Hamilton, ON, Canada. cjlin886@gmail.com.
This study introduces a new logistic delay differential equation model that prevents population oscillations, unlike classical models. It establishes survival thresholds and confirms that evolutionary trends favor shorter growth delays, supporting biological evidence.
Area of Science:
- Mathematical Biology
- Ecology
- Population Dynamics
Background:
- Classical logistic delay differential equations (DDEs) can produce unrealistic population oscillations.
- Alternative models, like the discrete delay model by Arino et al., exclude oscillatory behavior.
- Population oscillations are rarely observed in natural populations.
Purpose of the Study:
- To generalize the Arino et al. discrete delay model using a decay-consistent delay.
- To investigate the survival and extinction thresholds of the proposed logistic DDE.
- To explore the evolutionary trends in growth delay using adaptive dynamics.
Main Methods:
- Development of an alternative single species logistic distributed delay differential equation (DDE).
- Establishment of survival and extinction thresholds using Lyapunov functionals and fluctuation lemma.
- Application of adaptive dynamics to determine evolutionary trends in growth delay.
Main Results:
- The generalized model excludes population oscillations, aligning with natural observations.
- A clear threshold for population survival and extinction was established.
- Lyapunov functionals confirmed population convergence to a delay-modified carrying capacity for survival.
- The fluctuation lemma proved population extinction under specific conditions.
Conclusions:
- The study confirms Hutchinson's conjecture regarding evolutionary trends towards shorter mean growth delays.
- The proposed model and findings align with biological evidence of population dynamics.
- The generalized DDE provides a more realistic framework for studying population dynamics with delays.
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