Environmental Engineering Reference
In-Depth Information
Fig. 12.3 Simulation results of the IPP model simulating a simple individual-based predator-prey
interaction. For a description of symbols see Fig.
12.2
.
Left
: The initial distribution is random.
Center
: After 100 time steps - if the prey moves randomly, and the predators exhibit a directed
movement with a partial auto-correlation, a pronounced cluster structure of the prey occurs.
Right
:
after 400 time steps
12.4 Application Example II: Cyclic Rodent Communities
in Northern Scandinavia
In order to illustrate the potential of the individual based-modelling approach we
outline a more complex example relating to population cycles in Northern Scandi-
navian rodents. In community ecology, cyclic population dynamics constitute an
interesting example for complex dynamics often involving a multitude of species-
intrinsic factors and environmental influences (Myers 1988; Bascompte et al. 1997;
Sanderson et al. 1999; Haydon et al. 2002; Bauer et al. 2002).
Rodents, mostly in the Northern Hemisphere, often exhibit drastic changes in
population size with numbers at peak times reaching up to 500-fold of numbers in
the minimum phase. In Northern Scandinavia, where the changes in abundances
are most regular with peaks every 3-5 years, cyclic dynamics impact the whole
local biocenosis and are synchronous over large areas (Huitu et al. 2003). These
community interactions of small rodents have fascinated ecologists for many
decades (e.g. Elton 1927; Chitty 1960; Stenseth 1999; Korpimaeki et al. 2005)
and gave rise to many controversial discussions (Rosenzweig and Abramsky
1980) on the driving factors. Numerous hypotheses have been put forward
including abiotic influences (Aars and Ims 2002; Sundell et al. 2004) and biotic
intrinsic factors (Chitty 1967; Boonstra 1994; Oli and Dobson 2001). In the last
years, biotic extrinsic interactions (mostly trophic relationships) have been widely
recognized as the most important processes. However, it is still discussed,
whether rodent population dynamics are controlled by bottom-up causation (e.g.
Jedrzejewski and Jedrzejewska 1996; Selas 1997) or are top-down limited (e.g.
Norrdahl 1995; Klemola et al. 2003). Further more it is not clear how important
the role of pathogens is (e.g. Hoernfeldt 1978; Cavanagh et al. 2004) and if
driving factors change with cycle phase. Despite the long lasting controversy and
the numerous field investigations, the causalities for population cycles are not yet
