In the classical Fisher Wright models of population genetics, allele frequency change was modelled as a forward in time process.
Other models of population growth with time delays were considered in [3, 5 7, 13].
The same situation can be noted in models of population dynamics [3].
Dispersal functions are an important tool for integrating dispersal into complex models of population and metapopulation dynamics.
In ecology, these are key questions for building better individual-based models of population and community dynamics.
On the one hand, more realistic and interesting models of population interactions should take the effects of time delay into account [6 8], such as their maturation time.
Many researchers have studied models of population dynamics: prey and predator dynamics [1 4], epidemic dynamics in a population [5 8], molecular systems [9 11], etc.
In recent years, a number of articles have been published on stochastic differential equation models of population dynamics of infectious diseases.
We will consider two canonical models of population oscillators, one based on interacting sub-populations of excitatory and inhibitory neurons and the other based on an excitatory network with synaptic depression.
The assessments we have designed help students construct their own models of population change, and apply them both qualitatively (in-class worksheet and review activities) and quantitatively (homework on calculating allele frequencies).
Moreover, in most models of population dynamics, increase in population due to birth are assumed to be time dependent, but many species reproduce only during a period of the year.
