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BACKGROUND
CHAPTER 1
INTRODUCTION
Aquatic and terrestrial environments may be viewed as being primarily structured by
large-scale physical processes (currents and winds in aquatic systems) that cause
gradients on the one hand and patchy structures separated by discontinuities on the
other (Platt and Sathyendranath, 1992). These large-scale patches and gradients
induce the formation of similar responses in biological systems, both spatially and
temporally (Legendre and Fortin, 1989; Raffaelli et al., 1993). For example, within
the relatively homogeneous zones within large-scale patches, smaller-scale biological
processes such as reproduction, predator-prey interactions and parasitism take place
resulting in more spatial structuring. Legendre (1990) stated that several theories and
models, such as those for predator-prey interactions, implicitly or explicitly assume
that elements of an ecosystem that are close to one another in space are more likely to
be influenced by the same process. Spatial heterogeneity is therefore functional in
ecosystems and not the result of some random, noise-generating process (Legendre,
1993). The realisation that almost every ecological variable, biotic or abiotic, has a
non-random spatial distribution (Valiela, 1984; Addicott et al., 1987; Caswell and
Cohen, 1991) has resulted in ecologists not treating spatial heterogeneity as a
'nuisance' in ecological studies (Legendre, 1993) which hinders the estimation of
population densities (Reise, 1979; Valiela, 1984; McArdle et al., 1990), but as a
useful tool in assessing the processes operating within a particular system (Hall et al.,
1993). Observing patterns of variation in space helps with the understanding of
population processes which occur over time scales too long to be amenable to studies
(Sokal and Wartenberg, 1981). More fundamentally, assessment of spatial patterns
also helps to determine suitable study areas (Livingston, 1987), appropriate sampling-
scales (Downing, 1979; Eckman, 1979; Taylor, 1984) and the optimisation of
mathematical models (Hanski, 1994; Petersen and DeAngelis, 1996).
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