Demographic models can guide management decisions
In Chapters 10 and 11, we introduced population demographic characteristics such as birth and death rates, and models that use them to project the growth of populations. Demographic models have been used to address the following questions, among others: Is the growth rate of the Yellowstone grizzly bear population high enough to allow it to persist? At what life stages are loggerhead sea turtles most vulnerable to predation, and what management decisions would be most expedient to ensure their continued viability? How much old-growth forest habitat must be preserved to ensure the persistence of the northern spotted owl?
There are hundreds of quantitative demographic models in use, tailored to the specific biological traits of particular species.
The quantitative approach most widely used for projecting the potential future status of populations is referred to as population viability analysis (PVA). This approach allows ecologists to assess extinction risks and evaluate management options for populations of rare or threatened species (Morris and Doak 2002). PVA is a process by which biologists can calculate the likelihood that a population will persist for a certain amount of time under various scenarios. A variety of PVA models have been developed, ranging from relatively simple stage- or age-based demographic models like those described in Concept 10.2 to more complex, spatially explicit models that can take actual landscape features and dispersal of individuals from multiple populations into account.PVA provides conservation biologists with the probabilities that certain outcomes will occur, given assumptions about future conditions (e.g., changes in threats or in management efforts). Thus, PVA is a tool with which ecologists can synthesize data collected in the field, assess the risk of extinction for a population, identify particularly vulnerable age or stage classes, determine how many animals to release or how many plants to propagate to ensure the establishment of a new population, or determine what might be a safe number of animals to harvest (Beissinger and Westphal 1998).
PVA has been used to make a wide variety of decisions about how best to manage rare species.
In Florida, the fire regime that would best serve population growth in the rare plant Chamaecrista keyensis was determined through PVA simulations of burns at different times of year and at different intervals (Liu et al. 2005). In Australia, the forest-cutting practices that would best serve the persistence of two endangered arboreal marsupial species, the greater glider and Leadbeater's possum, were determined through extensive PVA modeling coupled with long-term monitoring to verify the accuracy of the data going into the model (Lindenmayer and McCarthy 2006). Such analyses have played a critical role in management decisions for a number of species.Some conservation biologists, however, caution against excessive reliance on conclusions based on the results of PVA. They point to the high level of uncertainty in the dynamics of small populations, the paucity of demographic and environmental data for many endangered species, and the high probability that a model will leave critical factors unaccounted for. To be used effectively, PVA models need to be constantly refined and revisited by different researchers to check their validity against field observations, just as management strategies must be checked and adjusted for effectiveness (Beissinger and Westphal 1998).