Chapter 22
Adaptive Population Control
To make increased population the cause of improved
agriculture, is to commit the absurd blunder of confounding
cause and effect.
(Rogers, Political Economy, 1868)
22.1 Adaptive Population Control Model
In this chapter we model the action of a population that is collectively trying to
control their population size by imperfectly recalling much of what they have done
in terms of birth rate control over the recent past. They assess the gap between their
current population size and that size dictated by their physical environment. It takes
time to gain the information about these two population sizes. Once the population
knows these levels, we assume they react by changing their birth rate. The new birth
rate is an average of the ones remembered over the recent past. The death rate for
this population and the level of the desired population size are dependent on the
population density.
Figure 22.1 shows that part of the model that captures the relationships among
area, population density, death rates, and desired population level. Here we also
introduce a multiplier A to scale the variable area for alternative runs. By defining
population density as
A save-disabled version of STELLA and the computer models of this book are available at
www.iseesystems.com/modelingdynamicbiologicalsystems.
B. Hannon and M. Ruth, Modeling Dynamic Biological Systems,
Modeling Dynamic Systems, DOI 10.1007/978-3-319-05615-9_22,
© Springer International Publishing Switzerland 2014
183
Adaptive Population Control
To make increased population the cause of improved
agriculture, is to commit the absurd blunder of confounding
cause and effect.
(Rogers, Political Economy, 1868)
22.1 Adaptive Population Control Model
In this chapter we model the action of a population that is collectively trying to
control their population size by imperfectly recalling much of what they have done
in terms of birth rate control over the recent past. They assess the gap between their
current population size and that size dictated by their physical environment. It takes
time to gain the information about these two population sizes. Once the population
knows these levels, we assume they react by changing their birth rate. The new birth
rate is an average of the ones remembered over the recent past. The death rate for
this population and the level of the desired population size are dependent on the
population density.
Figure 22.1 shows that part of the model that captures the relationships among
area, population density, death rates, and desired population level. Here we also
introduce a multiplier A to scale the variable area for alternative runs. By defining
population density as
A save-disabled version of STELLA and the computer models of this book are available at
www.iseesystems.com/modelingdynamicbiologicalsystems.
B. Hannon and M. Ruth, Modeling Dynamic Biological Systems,
Modeling Dynamic Systems, DOI 10.1007/978-3-319-05615-9_22,
© Springer International Publishing Switzerland 2014
183