Preface
The problems of understanding complex system behavior and the challenge of
developing easy-to-use models are apparent in the fields of biology and ecology.
In real-world ecosystems, many parameters need to be assessed. This requires tools
that enhance the collection and organization of data, interdisciplinary model development, transparency of models, and visualization of the results. Neither purely
mathematical nor purely experimental approaches will suffice to help us better
understand the world we live in and shape so intensively.
Until recently, we needed significant preparation in mathematics and computer
programming to develop such models. Because of this hurdle, many have failed to
give serious consideration to preparing and manipulating computer models of
dynamic events in the world around them. This book, and the methods on which
it is built, will empower us to model and analyze the dynamics characteristic of
human–environment interactions.
Without computer models we are often left to choose between two strategies.
First, we may resort to theoretical, mathematical models that describe the world
around us. Mathematics offers powerful tools for such descriptions, adhering to
logic and providing a common language by sharing similar symbols and tools for
analysis. Mathematical models are appealing in social and natural science where
cause and effect relationships are confusing. These models, however, run the risk of
becoming detached from reality, sacrificing realism for analytical tractability. As a
result, these models are only accessible to the trained scientist, leaving others to
“believe or not believe” the model results.
Second, we may manipulate real systems in order to understand cause and effect.
One could modify the system experimentally, such as introduce a pesticide or some
CO 2 , or remove a population or introduce a new one, and then observe the effects.
If no significant effects are noted, one is free to assume the action has no effect
and increase the level of the system change. This is an exceedingly common approach.
It is an elaboration of the way an auto mechanic repairs an engine, by trial and error.
But social and ecological systems are not auto engines. Errors in tampering with
these systems can have substantial costs, both in the short and long term.
Despite growing evidence, the trial-and-error approach remains the meter of the day.
vii
The problems of understanding complex system behavior and the challenge of
developing easy-to-use models are apparent in the fields of biology and ecology.
In real-world ecosystems, many parameters need to be assessed. This requires tools
that enhance the collection and organization of data, interdisciplinary model development, transparency of models, and visualization of the results. Neither purely
mathematical nor purely experimental approaches will suffice to help us better
understand the world we live in and shape so intensively.
Until recently, we needed significant preparation in mathematics and computer
programming to develop such models. Because of this hurdle, many have failed to
give serious consideration to preparing and manipulating computer models of
dynamic events in the world around them. This book, and the methods on which
it is built, will empower us to model and analyze the dynamics characteristic of
human–environment interactions.
Without computer models we are often left to choose between two strategies.
First, we may resort to theoretical, mathematical models that describe the world
around us. Mathematics offers powerful tools for such descriptions, adhering to
logic and providing a common language by sharing similar symbols and tools for
analysis. Mathematical models are appealing in social and natural science where
cause and effect relationships are confusing. These models, however, run the risk of
becoming detached from reality, sacrificing realism for analytical tractability. As a
result, these models are only accessible to the trained scientist, leaving others to
“believe or not believe” the model results.
Second, we may manipulate real systems in order to understand cause and effect.
One could modify the system experimentally, such as introduce a pesticide or some
CO 2 , or remove a population or introduce a new one, and then observe the effects.
If no significant effects are noted, one is free to assume the action has no effect
and increase the level of the system change. This is an exceedingly common approach.
It is an elaboration of the way an auto mechanic repairs an engine, by trial and error.
But social and ecological systems are not auto engines. Errors in tampering with
these systems can have substantial costs, both in the short and long term.
Despite growing evidence, the trial-and-error approach remains the meter of the day.
vii