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(Brent) #1
when NI=∆. We can rearrange terms to isolate kangaroo density on the left-hand
side of the equation, N=∆/I. Both null isoclines for the kangaroo–plant system are
plotted as broken lines in Fig. 12.7.
We can now reassemble the response functions of the system in their proper rela-
tionships to examine dynamics in the absence of stochastic variability in rainfall. We
shall see what these in combination reveal about the system’s dynamic behavior:

V(t) =∆[V(t), R(t)] −N(t)I[V(t)]

N(t) =N(t)r[V(t)]

Under a constant rainfall regime (in this case 60 mm per 3-month period), the
system converges on the equilibrium, that is, the point of intersection of both null
isoclines (Fig. 12.7). This shows that the equilibrium is stable, as one might have
guessed, based on the negative slope of the plant null isocline. Convergence on
the equilibrium is circuitous, involving a burst of plant growth, followed by plant
decline as the kangaroo population stabilizes.
Rainfall can also be simulated as a sequence of random events from a normal
distribution with a mean and standard deviation identical to the Australian data
(Fig. 12.8), and the consequent changes in plant biomass and kangaroo numbers can
be calculated accordingly.
Figure 12.9 demonstrates a typical time trend for kangaroos as generated by the
equations describing the unpredictable rainfall (Fig. 12.8) and the responses to it of
the plants and herbivores. The only external input other than starting conditions are
the random values from the 3-monthly rainfall distributions whose observed means
and standard deviations are given above. The kangaroo population trajectory is a
mathematical consequence of that rainfall, as its effect feeds through to plant growth,
herbivore population growth, and grazing pressure.

d
dt

d
dt

CONSUMER–RESOURCE DYNAMICS 205

0 100 200 300 400
Plant biomass (kg / ha)

Kangaroo density (individuals / ha)

2.0

1.5

1.0

0.5

0

Fig. 12.7Dynamics of
kangaroos and plants
over time, based on
the Australian model
discussed in the text.

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