A model is a representation of part or the totality of a reality made by human
beings with the hope that models can help us (i) represent the structural complexity
of the reality in a simpler way eliminating unnecessary elements that create
confusions, (ii) understand processes which are difficult to work out with the
complexity of the real world, (iii) assess multiple interaction individually and as a
whole (iv) predict the behavior of a system within the limitations imposed by the
simplification accepted as necessary for the sake of the understanding.
Models are simplifications of real systems. They can be used as tools to better
understand a system and to make predictions of what will happen to all of the
system components following a disturbance or a change in any one of them. The
human brain cannot keep track of an array of complex interactions all at one time,
but it can easily understand individual interactions one at a time. By adding
components to a model one by one, we develop an ability to consider the whole
system together, not just one interaction at a time. Models are hypotheses. They are
proposed representations of how a system is structured, which can be rejected in
light of contradictory evidence.
No model is a 'perfect' representation of the system because, as mentioned
above, all models are simplifications and in some cases needed over simplifications.
In working together to build your own models, you will generate new hypotheses
about interactions occurring within the ecosystem that provide a better
understanding of the complexities of the ecosystem as a whole and the multiplicity
of interactions.
Modeling has become an important tool in the study and management of
ecological systems. Sometimes it is not possible to manipulate an ecological system to
test rival hypotheses in field tests. For example, costs and time constraints can limit
large-scale experiments for testing community responses to an environmental
disturbance. In contrast, models can help explore hypotheses quickly and rigorously,
and can help to define research questions and identify data needs. While modeling is
widely considered by ecologists to be an important component of ecological
education, most ecology students have the misconception that ecological models
(particularly those dealing with ecosystems and communities) are always extremely
complex and filled with mathematical equations (a quantitative approach). On the
contrary, a complex ecological system can be simply yet formally described with a set
of 'boxes and arrows' (a qualitative approach).
The following is a model trying to explain the ecological behavior of complex human
Models can be qualitative, semi-quantitative and quantitative on the basis of
the use of numerical data about the storages and flows in the system. There are
systems in many different areas of human activity, for example in ecology,
mathematics, sociology, astronomy, robotics and so.
Your Task:
a) Analyze the model above in order to state and explain the strong aspects of this
b) State and explain the weak points of this model.
c) Re-write this model with the improvements you consider necessary to improve it.
Describe and explain (justify) the additions or deletions that you made.
d) Explain how this model could be used in areas such as (i) social studies, (ii)
economics, (iii) social planning and development and (iv) politics.