Environmental Engineering Reference
In-Depth Information
population's parameters can be highly non-predictable and non-linear. This has
caused a surge of interest in the use of different non-linear modelling techniques for
modelling population dynamics (see e.g. Chaps. 8, 10, 12). Furthermore, these
include neural networks (Lek and Guegan 1999; Recknagel et al. 1997; Schleiter
et al. 1999), equation discovery (D
ˇ
eroski et al. 1999; Todorovski et al. 1998) and
decision trees.
Classification and regression trees can be used for modelling population dynam-
ics as follows. The task of predictive modelling is to forecast the future state of the
population or the change in the state of the population over a specified time period,
given the current state of the population and the environment. For instance,
Kompare and D
ˇ
eroski (1995) used regression trees discovery to model the growth
of the dominant species of algae (
Ulva rigida
) in the lagoon of Venice in relation to
water temperature, dissolved nitrogen and phosphorus, and dissolved oxygen.
In the area of forestry, decision trees have been successfully used to model
population dynamics of red deer and spruce bark beetles population dynamics in
forest ecosystems. The study about the population dynamics of red deer focused on
the effects of different meteorological conditions, habitat properties and hunting
regimes on the population dynamic of red deer (Stankovski et al. 1998; Debeljak
et al. 1999). A highlight of the results of the red deer studies was the discovery of
the strong influence of meteorological parameters on the browsing intensity for new
growth of woody plants (beech and maple) and consequently the body weight of
1-year-olds, 2-year-olds, and hinds (important parameters of the studied red deer
population). These results challenge previous simplistic approaches, assuming
simpler and more direct relationships between the density of the red deer population
and its parameters and the browsing rate of new forest growth.
The study of spruce bark beetles (Ogris and Jurc 2010) focused on environmen-
tal conditions that stimulate population growth of the spruce bark beetles
Ips
typographus
and
Pityogenes chalcographus
. The results show a strong correlation
between the appearance of
I. typographus
at Northeast (NE) expositions, while
P. chalcographus
prefers West (W) and North (N) sites. The discovered habitat
preferences of bark beetles confirm the adaptation of spruce to drought conditions at
southern expositions, where its root system penetrates deeper in the soil. At N, NE
and W sites, the individual trees are more sensitive to drought and mechanical
destabilization due to the shallow root system and thus they are more prone to
attack by bark beetles.
Decision trees are also used in agro-ecology. The population dynamics of soil
organisms is affected by the changes of different biological and physicochemical
environmental attributes and agricultural practices. A study about the effects of
growing Bt-maize cultivation on abundances of earthworms populations (Oligo-
chaeta) (Debeljak et al. 2007) used farming practices, soil parameters, the
biological structure of soil communities, and the type and age of the crop at the
time of sampling as attributes to predict the total abundance of three functional
groups of earthworms (epigeic - live and feed on plant litter (Fig.
14.1
); endogeic -
geophagous and live in the soil; anecic - live in soil but feed on plant litter on the
surface). The highly accurate (r
2
¼
0.83) regression tree model for anecic worms
