Environmental Engineering Reference
In-Depth Information
distinguishable, not necessarily responsive. For example, Bousquet
et al
. (2001)
produced a spatially explicit model of the interaction between hunters and duikers
in Cameroon. Duikers are territorial species, and so the model is spatially explicit,
with each duiker occupying a particular cell on a grid, taken from a GIS of the area
around the village in Cameroon. The duikers make movement decisions based on
the presence of other duikers in the region, while hunters make decisions about
where to place their trap networks. It is then possible to overlay a management
regime controlling the hunters, in a way reminiscent of the operating model
approach to fisheries management (Section 7.5.2.3). Agent-based models are
also potentially useful for simulating strategic interactions between people
(e.g. poachers and monitors in community conservation schemes) when the
system is too complex for standard game theoretic approaches. They have also been
used to simulate the multiple institutional levels at which decision-making occurs
in the management of natural resources (e.g. Walker and Janssen 2002).
A more standard way of simulating economic behaviour is the
household utility
model, where households or individuals act to maximise their utility in the face of
different productive options and a limited amount of available labour; this is the
type of model used by Barrett and Arcese (1998; Box 5.3) and Damania
et al
.
(2005). Utility is the basic unit of economics, and measures happiness or human
welfare. It is often approximated by money and/or consumption, although
resources are clearly also valued by people in ways that are difficult or impossible to
quantify. A purely financial definition of utility is therefore convenient, but likely
to be misleading when non-financial values, such as cultural significance, are
important.
All models that aim to say something about sustainability need to include both the
biological and the human components of the system, and how they interact. Basic
models of this type include those founded in logistic population growth and
open access harvesting, such as those discussed in Chapter 1. But these are very
simplistic, and so are more useful in helping us to understand the broad behaviour of
bio-economic systems, rather than for making management recommendations in
real systems. In real systems, issues like the lag between a change in the system and
the response to it can be critical to system behaviour—for example, hunters take time
to change their behaviour if the cost of hunting increases, while prey populations
need time to reproduce and grow if hunting pressure is reduced. These lags can lead
to cycles in the system's dynamics, at least in theory (Sanchirico and Wilen 1999).
As usual, fisheries modellers are leading the field in producing models that
include both human and biological elements in more and more realistic settings.
For example, Pelletier and Mahevas (2005) review a huge range of models that
have been used to assess the performance of Marine Protected Areas (MPAs) in
conserving fish stocks while at the same time providing a sustainable yield for
fishers. The models started very simple and highly theoretical, with only two
patches and dynamics based on the Schaefer model (Chapter 1). More recently,
