Modelling and Model Building - Environmental Modelling: Finding Simplicity in Complexity - page 9

2002; Steffen et al ., 2007; Zalasiewicz et al ., 2010; Brown,
2011). The Holocene was an epoch of unprecedented
stability that enabled complex societies, cultures, agri-
cultures and infrastructures to be developed eventually
supporting some seven billion people (Ruddiman, 2007).
In the Anthropocene, humans are a major geological force
generating planetary scale change in climate, land, water
and ecosystems. Our increasing individual impacts on the
environment coupled with our sheer numbers and their
growth promises to put an end to this era of stability
in favour of an epoch of unprecedented instability. In
order to maintain and sustain water, food, shelter, liveli-
hoods and culture we will need to manage our impact
on nature much more effectively than ever before. We
can only manage what we understand, so researching
environmental systems is more important than ever.
Modelling has grown significantly as a research activity
since the 1950s, reflecting conceptual developments in the
modelling techniques themselves, technological develop-
ments in computation, scientific developments indicating
increased need to study systems (especially environmental
ones) in an integrated manner and an increased demand
for extrapolation (especially prediction) in space and time.
Modelling has become one of the most powerful
tools in the workshop of environmental scientists who
are charged with better understanding the interactions
between the environment, ecosystems and the popula-
tions of humans and other animals. This understanding
is increasingly important in environmental stewardship
(monitoring and management) and the development
of increasingly sustainable means of human depen-
dency on environmental systems and the services that
they provide.
Environmental systems are, of course, the same systems
as those studied by physicists, chemists and biologists but
the level of abstraction of the environmental scientist
is very different from that of many of these scientists.
Whereas a physicist might study the behaviour of gases,
liquids or solids under controlled conditions of tempera-
ture or pressure and a chemist might study the interaction
of molecules in aqueous solution, a biologist must inte-
grate what we know from these sciences to understand
how a cell - or a plant - or an animal, lives and functions.
The environmental scientist or geographer or ecologist
approaches their science at a much greater level of abstrac-
tion in which physical and chemical 'laws' provide the
rule base for understanding the interaction between living
organisms and their nonliving environments, the char-
acteristics of each and the processes through which each
functions.

Integrated environmental systems are different in many
ways from the isolated objects of study in physics and
chemistry although the integrated study of the envi-
ronment cannot take place without the building blocks
provided by research in physics and chemistry. The
systems studied by environmental scientists are char-
acteristically:

Large scale, long term. Though the environmental scientist
may only study a small time- and space-scale slice of
the system, this slice invariably fits within the context
of a system that has evolved over hundreds, thousands
or millions of years and which will continue to evolve
into the future. It is also a slice that takes in mate-
rial and energy from a hierarchy of neighbours from
the local, through regional, to global scale. It is this
context, which provides much of the complexity of
environmental systems compared with the much more
reductionist systems of the traditional 'hard' sciences.
To the environmental scientist models are a means of
integrating across time and through space in order to
understand how these contexts determine the nature
and functioning of the system under study.
Multicomponent. Environmental scientists rarely have the
good fortune of studying a single component of their
system in isolation. Most questions asked of environ-
mental scientists require understanding of interactions
between multiple living (biotic) and nonliving (abiotic)
systems and their interaction. Complexity increases
greatly as number of components increases, where
their interactions are also taken into account. Since the
human mind has some considerable difficulty in deal-
ing with chains of causality with more than a few links,
to an environmental scientist models are an important
means of breaking systems into intellectually manage-
able components and combining them and making
explicit the interactions between them.
Non-laboratory controllable. The luxury of controlled con-
ditions under which to test the impact of individual
forcing factors on the behaviour of the study system
is very rarely available to environmental scientists.
Very few environmental systems can be rebuilt in
the laboratory (laboratory-based physical modelling)
with an appropriate level of sophistication to repre-
sent them adequately. Taking the laboratory to the
field (field-based physical modelling) is an alterna-
tive as has been shown by the Free Atmosphere
CO 2 Enrichment (FACE) experiments (Hall, 2001),
BIOSPHERE 2 (Cohn, 2002) and a range of other
environmental manipulation experiments. Field-based