Chapter 26
Multi-Stage Insect Models
We may define insects to be little animals without red blood,
bones or cartilages, furnished with a trunk or else a mouth,
opening lengthwise, with eyes which they are incapable of covering, and with lungs which have their openings in the sides.
(Goldsmith, 1774)
26.1 Matching Experiments and Models
of Insect Life Cycles
One of the most advanced areas of dynamic modeling at the organism level is found
in entomology. Insects have received much attention in part because they are
animals of great economic significance: they cause billions of dollars of damage
to food supplies around the world every year. We try to control their population
levels, having long ago realized they multiply and evolve too fast for elimination.
To better understand the dynamics of insect populations, we model the life cycle
of an insect, simplified into two stages, egg and adult. Typically, the data used in
understanding insect population dynamics come from laboratory experiments
in which one watches each egg and notes when it dies or hatches. Data from such
an experiment (at constant temperature) might look like those shown in Table 26.1
of the life history of 100 new insect eggs. Note how the final number of survivors
must equal the total number hatched. ESF is the experimental survival fraction and
T is the mean maturation time or the mean time to hatch, in days.
Time is measured in days in this case, with data displayed for the beginning of
the next day (the result of the previous day). This table yields two important
averaged numbers, the experimental survival fraction, ESF (0.699, say 0.7), and
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_26,
© Springer International Publishing Switzerland 2014
211
Multi-Stage Insect Models
We may define insects to be little animals without red blood,
bones or cartilages, furnished with a trunk or else a mouth,
opening lengthwise, with eyes which they are incapable of covering, and with lungs which have their openings in the sides.
(Goldsmith, 1774)
26.1 Matching Experiments and Models
of Insect Life Cycles
One of the most advanced areas of dynamic modeling at the organism level is found
in entomology. Insects have received much attention in part because they are
animals of great economic significance: they cause billions of dollars of damage
to food supplies around the world every year. We try to control their population
levels, having long ago realized they multiply and evolve too fast for elimination.
To better understand the dynamics of insect populations, we model the life cycle
of an insect, simplified into two stages, egg and adult. Typically, the data used in
understanding insect population dynamics come from laboratory experiments
in which one watches each egg and notes when it dies or hatches. Data from such
an experiment (at constant temperature) might look like those shown in Table 26.1
of the life history of 100 new insect eggs. Note how the final number of survivors
must equal the total number hatched. ESF is the experimental survival fraction and
T is the mean maturation time or the mean time to hatch, in days.
Time is measured in days in this case, with data displayed for the beginning of
the next day (the result of the previous day). This table yields two important
averaged numbers, the experimental survival fraction, ESF (0.699, say 0.7), and
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_26,
© Springer International Publishing Switzerland 2014
211