Our research is concerned with understanding the behaviour of
systems in the marine environment. This involves developing means to
how the interactions between biological, physical, chemical and
influences affect these systems. We do this by formulating mathematical
computer models to help synthesize available information about these
influences and their effects on marine systems.If these models are
they should be able to accurately predict how the ecosystem will react
changes in external forcings (e.g., a change in nutrients resulting
changes in land usage). Developing models helps increase our
of how these systems work.
The process of developing and testing the models relies
on the availability of data. Comparing the results of the model with
can have at least two important consequences. Firstly, the model can be
so that agreement between the model predictions and data is improved.
addition, the model may help identify important gaps in the available
- e.g., parameters that have never been measured and which are crucial
improving our understanding of the system. So there is a two-way
between data and models.
There are different types of models, each having their own
- Empirical Models: These are models that formed by
a simple function (e.g., a straight line) to a set of data. These
models are relatively easy to develop, but their predictive power
is restricted by the limitations of the data set. For example, the
model cannot reliably predict the system's response to an influence
greater than those appearing in the original data set.
- Mechanistic Models: These models are developed from
principles and are usually expressed as systems of differential and
algebraic equations. These models are difficult to develop and rapidly
become very complicated as more interactions are included. If they
are successful, they are able to predict how a given system will
to a very wide range of influences.
- Inverse Models: Frequently, the sheer complexity of
biological systems limits the amount of data that can be collected.
Inverse techniques allow the modeler to estimate parameter values,
fluxes and other variables which cannot be measured in the field.
The estimates one gets depend strongly on the structure of the inverse
model and on the data used.
There are four broad classes of problem that we are presently working
None of these four problems is independent of the others. For example,
particle aggregation affects the flux of material from the surface to
the deep ocean.
Changes in this flux affect the ecosystem throughout the water column.
- Coagulation and
- Understanding the aggregation of marine particles
and how it affects their vertical distribution and flux.
Last modified: Wed Dec 20 11:12:37 CST 2000