Published online by Cambridge University Press: 20 May 2010
A common justification of ecological research is that it allows predictions of the consequences of environmental change. There is a considerable need to be able to make realistic and justifiable predictions. With many environmental issues, such as genetically modified (GM) crops, climate change, habitat loss and exploitation, there is an urgent need to be able to produce quantified predictions. Such quantified predictions are essential for policy-makers if they are to consider ecological consequences within their framework of social and economic costs and benefits (Sutherland & Watkinson 2001).
Conservation biologists regularly carry out analyses (usually referred to as population-viability analyses) to evaluate the likelihood of a population persisting in the presence of existing or novel conditions (for reviews see Beissinger & Westphal (1998); Norris & Stillman (2002)). These are then often used to determine the conservation measures required to maintain the population, such as the release of additional individuals, a reduction in exploitation levels or the expansion of the available habitat (see Beissinger (1995); Green et al. (1996); Hiraldo et al. (1996); Root (1998) for a range of avian examples that illustrate these applications).
The basic elements of all population models are the population growth rate in the absence of interspecific competition, the extent of density dependence and the level of stochasticity (Burgman et al. 1992). However, in practice, population-viability analyses very rarely use measured parameters for density dependence, particularly when models are applied to the management of endangered species due to the paucity of data (see Green & Hirons (1991)).