Environmental Engineering Reference
In-Depth Information
cases plausible predictions can be made while in others we can only study
scenarios and learn more about the type and range of uncertainties. Ecological
systems are structurally diverse and complex systems. These systems are known
to express complex interaction networks with a high number of interrelationships
and context-specific feedback processes. The outcome finally evolving from this
interaction network is highly dynamic. Only parts of the entire system are
accessible for empirical measurements. Any kind of modelling that tries to fill
these empirical gaps will have to take the complexity and the dynamics of
ecological systems into account. This was also eponymous for the title of this
topic:
Modelling Complex Ecological Dynamics
. The conceptual approaches,
techniques and applications compiled in the following chapters will attempt to
give an overview of what is feasible and what can be achieved.
You, the reader,
are invited to share the findings in this field, and eventually pick up the thread as a
researcher and expand the knowledge in an interesting discipline of environmen-
tal science.
For a long time ecological work had focused on making an inventory of biota,
collecting, gathering and classifying organisms in the diverse range of habitats
(e.g., Linn´ 1748; Lamarck 1815-1822; Darwin 1859; Haeckel 1866; all of which
also included the development of criteria and hypotheses on processes leading to
the diversification of biota). This was then followed by studying how the biological
entities respond to the environment and relate with each other. In physical systems,
the experimental setup to decide on hypotheses of relations of material objects can
be intentionally constructed (“framework constellation”, McCarthy 1963). How-
ever, the precision in assessing ecological relations is usually much lower. In an
early phase of scientific development, a general formalization and mathematization
of natural systems was seriously considered. The French mathematician and astron-
omer Pierre Simon de Laplace (1749-1842) developed the idea, that in an ideal
situation, when the precise location and impetus of all components moving in the
universe would be known, the physical laws of dynamic interaction should allow to
forecast any state in the future, and would equally enable to recalculate (backwards)
all states in the past. Achieving this goal, of course would require infinite calcula-
tion capacities with infinite precision. Such an infinitely fast and capable calculator,
called Laplace's demon, certainly was meant only as a theoretical consideration
(de Laplace 1814), but outlined what was considered as the field of scientific
intelligence.
Today in ecology, we are satisfied if we can make some cautious steps towards
better understanding. To globally summarize all aspects of how organisms relate to
each other and their environment in strict and quantitative cause-effect relation-
ships does not seem to be reasonable. In this context, understanding ecological
dynamics will remain incomplete and approximate, as suggested by theoretical
consideration as well as practical experience. Nevertheless, it remains a challenge
to find out where, to what extent and why forecasts are possible. Or to set up rules
that lead to satisfying explanations and rationales when this is not the case.
Understanding complex environmental relations also requires inclusion of an
abstract representation of the phenomena in focus. This abstract representation can
