The extermination symbol is used to specify the conditions under which one instance of a population submodel ceases to exist. It is sometimes called the loss or mortality symbol. It belongs to the group of symbols known as channels. The symbol's icon represents an axe.

The extermination symbol only has meaning in the context of a population submodel. Therefore, it makes sense to construct a population submodel first, then add the mortality symbol to it. This is not strictly necessary: you can add the mortality symbol first, then construct a submodel around it, then make the submodel into a population submodel, but it is better practice to construct the population submodel first.

See Adding node-type elements.

- The mortality symbol can receive influences from anywhere in the model, both inside and outside the population submodel of which it is a part. This means that the chances of an individual instance being destroyed can depend on both factors that are external to the population, and on the characteristics of that particular individual.

- There can be multiple mortality symbols in the same population submodel.
- It is possible to draw an influence arrow from the mortality symbol to another element. The usual use of this is with the dies_of( ) function. The value of the mortality symbol is the value of its equation.

A mortality channel represents a 'risk factor' for the individuals in its population. Its value should be a fraction between 0 and 1, and this represents the probability of the individual for whom it has that value being removed over one time unit. In this sense it works like radioactive decay; the individuals do not 'lose health' before they die, but rather any surviving individual's chance of dying is determined solely by its current mortality, no matter what it has been in the past. Note that this is different from the behaviour of the migration and reproduction channels, where the rate is summed over multiple time steps. If you require your model to capture a situation in which individuals do die as a result of losing health, the process of health loss must be represented explicitly in the model, with the mortality channel only becoming nonzero when they actually go.

The rate of removal is spread over every time step; if there are 10 time steps in a time unit, and an individual's mortality is 0.3, then there is a roughly 0.03 (exactly 1- (1-0.3)^{0.1}) chance of removal in each time step. Multiple mortality channels act independently; if there are two, and for a given individual they each have a value of 0.5 over a time unit, then the probability of that individual being removed in that time unit is 0.75. A value of 1 in any time step makes it certain that the individual will be removed in that time step.

Individuals are removed at the start of the time step following the one in which their number came up. This means other values from their submodel instances can be used in that time step. A function is available in the equation language, dies_of(), which returns true if the argument is from a mortality symbol that results in the individual's removal in that time step (cf. channel_is( ))

A removal channel can also be discrete-event valued, if it has an influence from an event or squirt. In this case, when the triggering event happens, individuals may be removed immediately. The magnitude of the removal event is the probability, as a fraction of 1, that the individual will be removed at that point. If the value is 1 or greater, removal is certain. In order to avoid any random behaviour in a model containing removal channels, they should only ever have values of 0 or 1. Removal symbols, whether discrete or continuous valued, can have boolean units ("true" or "false") which have the same effect as 1 and 0.

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