Simulistics

Population age-class models

Explicit compartments

The simplest way of making an age-class model is to have a separate compartment for the number in each class. The compartments are connected by flows representing the movement of animals between classes as they age. Reproduction feeds into the first class, and all classes have a mortality outflow. This particular model includes density-dependent reproduction.

The model eventually equilibrates with a fixed number in each class.

You can use this page to get a quick overview of the wide range of models that can be constructed in Simile. Each entry gives some text on the model, a model diagram (usually an outline view for all but the simplest of models), and a sample screen display from the running model. Models are arranged roughly in order of increasing complexity and increasing sophistication of the Simile techniques used.

Classic (Lotka-Volterra) population dynamics

Exponential population growth

Separate compilation of submodels applies only to version 4. It was dropped from version 5 because it was difficult to use and was made obsolete by general improvements to the speed of code generation on version 5.

Complex models — that is, models with a large number of symbols and equations — can take a significant to build (i.e. generate the program for simulating the behaviour of the model). It can be as long as 10+ minutes for a complex model (100s of equations) on a slow computer.

By default, Simile uses the same time step to update all the model state variables. However, if you are modelling a system containing trees and crops, then you might very well want to model the trees on an annual basis (time step of one year), and the growth of the crop on a weekly basis (time step of 1 week).

Let’s say that you have a multiple-instance submodel containing information on the species and volume of a set of individual trees: each instance is one tree. You would like to find the total volume of all trees belong to species 1.

This is easy to do if you have model the trees using a fixed-membership submodel (i.e. assuming that you have a fixed number of trees). You simply take influence arrows from the species and volume variables inside the submodel to a variable outside (say total), and give total the equation:

total = sum(if [species]==1 then [volume] else 0)