Environmental Engineering Reference
In-Depth Information
Box 5.3
Linking wildlife harvesting to household economics in the Serengeti.
Barrett and Arcese (1998) used a model to examine the relative effectiveness of
different interventions for conserving wildebeest in the Serengeti ecosystem.
Their model was innovative in not just focussing on the sustainable levels of
wildebeest hunting, but including household economics—specifically demand
for meat and the wage rate from agriculture, as well as a constraint on the amount
of work time available for people to allocate either to hunting or to agriculture.
This meant that they could look at the way in which people changed their behav-
iour dependent on the relative profitability of hunting and farming. Their output
parameter was the time until the wildebeest population reached crisis levels, and
they examined 27 different scenarios with differing levels of correlation between
rainfall, wildebeest survival and agricultural productivity; different amounts
of meat given to households by the conservation project; and different human
population growth rates. Each scenario was simulated 300 times, and the results
were presented as the median and range of the time to crisis.
One result was that by giving people meat, the project might actually worsen
the situation for wildebeest, as this effectively increases people's incomes and
so increases their demand for meat, which is then met by poaching. They next
simulated some possible solutions to the problem, which revolved around redu-
cing the correlation between bad years for wildebeest survival and bad years for
agricultural productivity, and hence ensuring that wildebeest were not turned to
as an alternative to crops when they were themselves vulnerable. This might
include improving cropping practices to conserve water and offering employ-
ment in years of crop failure.
2002; Courchamp
et al
. 2006)? It is also useful to examine best case and worst case
scenarios, to get a feel for the range of potential outcomes of conservation inter-
ventions. Another type of scenario analysis is when particular parameters trend
over time, hence ensuring that the system cannot reach equilibrium—human
population size increasing, perhaps, or carrying capacity decreasing as habitat
is destroyed by logging or agriculture. Perhaps the most famous set of scenario
analyses are those employed by the Intergovernmental Panel on Climate Change
(IPCC), who have four 'storylines' about the future trajectory of climate change
depending on the development path that the world takes (IPCC 2001).
The scenarios you choose will reflect the potential issues that conservationists
need to address. Then for each scenario, you can examine the outcome of the
proposed conservation actions. For example, how quickly would the population
recover if there was a moratorium on hunting, under each scenario? Perhaps under
some scenarios, the population will continue to decline regardless of the hunting
level, due to the effects of habitat loss. The range of situations you can address is -
limited only by your model structure and your imagination. Both sensitivity analy-
