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Similarly, we can state r = b − d where b and d are per capita instanteous rates. Such an advance in understanding the determinants would be great. Perhaps now is a good time to think about all the assumptions others might tell us we are making when we present the above formulation. Are all individuals in the population equally likely to produce progeny and/or die? Will birth and death rates vary over time or as the size of the population changes more? How will resource supply rate influence these rates?

Although these values do not tell us which stages and transitions will, in reality, be influenced by natural phenomona or management practices, they provide us with the predicted effects on λ of a proportional change in a demographic rate, P or F. This is particularly important in the management of invasive (or endangered) species where we seek to have the maximum impact for the minimum amount of effort and resources [23, 48]. 6 More demographic model details Births For demographic models, a “birth” is merely the appearance in the first stage.

2053 + 1) Fig. 10: Exploratory graphs of the distributions of the final simulated population sizes. Can we really believe this output? To what can we compare our output? One thing that occurs to me is to compare it to the lower and upper bounds that we might contrive from deterministic projections. To compare the simulation to deterministic projections, we could find the 95% t-distribution based confidence limits for the geometric mean of R. If we use our rules regarding the geometric mean, we would find that the logarithm of the geometric mean of R is the arthmetic mean of the log R.

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