Spatial Population Models for Animals - Environmental Modelling: Finding Simplicity in Complexity - page 222

250 250

200 200

150 150

100 100

50 50

0 0 0 0

125 250 375 500 125 250 375 500

(a) (b)

250 250

200 200

150 150

100 100

50 50

0 0 0 0

125 250 375 500 125 250 375 500

Mean downstream distance (cells)

(c) (d)

Figure 13.5 Frequency distributions of average downstream distance travelled per landscape, for each landscape type. (a) 5%
obstacles, random settlement; (b) 15% obstacles, random settlement; (c) 5% obstacles, settlement in DWZ only; (d) 15% obstacles.
Mean obstacle sizes are 2

× 2 cells (white columns) and 6 × 6 cells (hatched columns). Source: Bond et al . (2000).

(i) reaction-diffusion systems, (ii) metapopulation and
patch-occupancymodels, and (iii) individual-basedmod-
els. Alongside recent methodological developments in
dynamic modelling, there have also been significant
advances in static, data-driven models of animal pop-
ulations. Such static models can be extremely useful

in identifying the important factors to be included in
dynamic models. The many approaches taken to spatial
modelling of animal populations have respective strengths
and weaknesses and there is no single approach to be rec-
ommended over others. Indeed, there is often much to
be gained from applying multiple approaches together.