7.1. Model StructureThe model of Leslie (1945) describes 3 kinds of ecological processes:
Equation [1] represents development and mortality, whereas equation [2] represents reproduction. Equation [2] specifies the number of individuals in the first age class and equation [1] specifies the number of individuals in all other age classes. In the equation [1], the number of individuals in age x+1 in time t+1 equals to the number of individuals in the previous age and previous time multiplied by agespecific survival rate sx. In the equation [2] the number of newborn organisms equals to the number of mothers (Nx,t) multiplied by the numbers of offspring produced (mx). The number of offsprings is summed over all ages of mothers. These two equations can be combined into one matrix equation:
where Nx is the vector of age distribution in the population at time t, and A is the transition matrix. When a matrix is multiplied by a vector, we take the 1st row of the matrix, multiply each number by the corresponding number in the vectorcolumn and then sum all products. This sum is the value of the 1st element in the result vector. Then we take the 2nd row of the matrix, multiply it by the same vector and the sum becomes the 2nd element in the result vector. In the same way we can estimate all elements of the result vector. The first element of the result vector corresponds to the equation [2], and all other elements correspond to the equation [1].
How to read matrix models? Most simple stochastic process is defined by a matrix of transition probabilities between states:
In this case, the sum of matrix elements in each column equals to 1 because it is assumed that each system passes through a series of states and neither die nor reproduce. Leslie model is more complex because the sum of matrix elements in each column is not necessary equal to 1. This is a "branching process" because the life trajectory of a parent branches into life trajectories of its offsprings. Matrix models are easy to iterate in time. In the next time step we again multiply the transition matrix by the vector of age distribution:
This equation can be used to simulate as many time steps as necessary.
