untitled

the fact that Nis enormous, the population will similarly display modest change from

year to year. This is because the per capita rate of growth is small, because either

birth rates are low or mortality rates are high. It is only when the population is of

intermediate size and growing at an intermediate per capita rate that growth is max-

imized (Fig. 8.13).

Population data displaying the classic sigmoid pattern of change are rare. It will

only be seen when a population is reduced to very low initial density and then mon-

itored closely over an extended period. So, logistic growth will not be obvious in

most populations that we might see around us in nature, which are presumably close

to their carrying capacity. In some cases, however, populations have been perturbed

(reduced) to low densities, and give us a rare glimpse of logistic growth in the field.

For example, as we discussed earlier, the Yellowstone elk herd has been aggressively

culled at various times in the past, particularly in the late 1960s. Cessation of culling

operations, stimulated by a new policy of natural regulation in US National Parks,

led to a subsequent pattern of elk recovery reminiscent of the sigmoid pattern pre-

dicted by the logistic model (Fig. 8.14). Similarly, release of the Serengeti wildebeest

population from the exotic disease rinderpest led to a subsequent sigmoid pattern

122 Chapter 8

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(^0051015)
t
N
t
Fig. 8.12Population
growth according to
the logistic equation,
with rmax=0.5, initial
population density
N 0 =1.5, and carrying
capacity K=100.
15
10
5
0
–5
0 20406080100120
N
Net recruitment
Fig. 8.13Net
recruitment (Nt+ 1 −Nt)
as a function of
population density Nt,
according to the Ricker
logistic growth model,
with rmax=0.5 and
K=100.