Environmental Engineering Reference
In-Depth Information
In the following section we explain the general strategy of the integrated
modelling approach for Everglades restoration. As a first step, the empirical data
are analysed and checked for consistency, which helps to fill-up knowledge gaps.
The empirical sectors involved are “classical” ecologically: landscape data (e.g.
topology, hydrology, soil, vegetation), and population data (e.g. plant and animal
populations and their interactions). Then, in a second integration process, sector-
specific model-frameworks are applied, which are used for forecasting purposes.
Examples of such model-frameworks are the South Florida Water Management
Model (SFWMD 1992) and Natural Systems Model (Fennema et al. 1994), the
Everglades Landscape Model (ELM; Fitz and Sklar 1999) and the Across Trophic
Level System Simulation Complex (ATLSS; Gross and DeAngelis 2001). The last
two model frameworks and their working principles will be explained in detail in
the next paragraph.
After the developmental process of representing the data and describing the
system dynamics is accomplished, the model frameworks can be used to generate
computer scenarios and make projections. In computer scenarios, a characteristic
set of conditions and traits is grouped within a special case. The procedure referred
to as computer scenario is when different sets of conditions are sensibly grouped
into alternative cases and the reaction of the model components to the variation of
these characteristics is assessed through computer simulation. The scenario tech-
nique is used to evaluate the outcomes of possible future situations on the target
variables. A possible goal of such an approach could be to generate scenarios on
breeding and foraging behaviour of animals under different conditions of hydrology
and vegetation types (DeAngelis et al. 1998).
In providing input for ecosystem restoration, special emphasis is put on model
evaluation (see also Chap. 23), which normally begins with a sensitivity analysis
and visualization processes, to display model outcomes on the landscape level (see
Fig.
21.3
). If more than one model or model type is available for the same or close
related issues, these model attempts are thoroughly compared and their relative
advantages and disadvantages are evaluated. This procedure guarantees that the
different “powers” of the model systems are systematically evaluated. For all steps
of the evaluation processes described here, expert advice and opinions are obtained
and integrated before the outcome is finally communicated to stakeholders on
management decisions on Everglades restoration.
Figure
21.4
focuses on the integrating power of modelling within an ecological
project. Here, even at the starting point of data and information collecting, (see
Fig.
21.4
left, upper corner) modelling techniques can help to overcome possible
difficulties. Basically, these difficulties have to do with aggravating circumstances
during data collection or with intrinsic characteristics of the natural phenomena in
focus, such as heterogeneities and variabilities that can lead to data gaps and, later,
to inconsistencies. Appropriate modelling tools can help to evaluate these first data
structures, understand the heterogeneities, and fill-up the data gaps. When dealing
with complex ecological phenomena, the following aspects of knowledge visuali-
zation are important: (1) Providing for spatially explicit model representations
is more and more requested, which also helps to encourage the communication
