What Are the General Conditions Under Which Ecological Models Can be Applied? - Modelling Complex Ecological Dynamics - page 14

we might never be able to fully understand these ecological systems structures and
functions and the resulting dynamics. On the other hand, there are many good
reasons why we should attempt to do so, e.g., the need to search for solutions of our
urgent environmental problems. Systems analysis (see Chap. 4) and modelling
provides steps and theories to cope with complexity in ecological systems.
Ecological modelling provides a large set of different approaches to analyse
drivers of systems dynamics and extrapolate developments. However, it also has to
be applied critically. The modeller should be conscious of the following:

l Models are observer-defined abstractions that can reflect reality only in the
framework of the observer's viewpoint, the amount and quality of input infor-
mation and the basic assumptions of the modeller
l There is an optimal degree of model complexity. This is not the highest com-
plexity because large and complicated models tend to be difficult to handle and
can increase uncertainty (Joergensen and Bendoricchio 2001)

In any case the model outputs comprise specific uncertainties. To optimize the
results, modelling needs extensive information about the investigated system
and about the modelled object or process, as well as a precise question or
hypothesis and data for both model development and model testing

l

2.2 Model Creation Should Be Carried Out
in a Systems-Analytical Procedure

To make the general modelling procedure more illustrative, Fig. 2.1 sketches the
single steps of a system analysis leading to an applicable ecological model. More
technical details are elaborated in Chaps. 4 and 23) on model development, while
the conceptual fundament is discussed here. The steps of model preparation begin
with basic questions like:

l What is the focal object of the model?
l What is the specific aim of the model and what is its role in solving the focal
problem?
l What are the spatial and temporal extents of the model and in what dimensions
should the outputs be provided?
l What are the spatial and temporal resolutions of the model and how detailed
should the processes be that are represented in the model ( model complexity )?
l What are the most important issues to be represented and what are the relations
between them?
l What data are necessary to (a) develop and (b) test the model?
l What are the forcing functions of the modelled systems and how do these
constraints affect the elements?
l How can the interrelations be depicted in a clear and understandable graphical
scheme?
l What are the basic assumptions made in model development?