The 3rd USGS Modeling Conference (7-11 June 2010)

Paper No. 5
Presentation Time: 4:15 PM

WILDLIFE CONSERVATION AND CLIMATE CHANGE: USING TOMORROW'S LANDSCAPE TO INFORM TODAY'S DECISIONS IN THE SOUTHEASTERN REGIONAL ASSESSMENT PROJECT


ABSTRACT WITHDRAWN

, grandjb@auburn.edu

Natural resource managers in the southeastern United States face unprecedented pressure to develop effective and efficient conservation strategies. Climate change and anthropogenic pressures further complicate the challenges associated with maintaining populations of trust species and the habitats they require. The great uncertainty associated with predicting future climates and landscapes, as well as wildlife responses to them present enormous difficulties for decision makers. In addition, opportunistic, reactive conservation strategies frequently have not been effective for stabilizing or bolstering already declining populations of many species of terrestrial and aquatic wildlife. If the benefits to wildlife populations are considered in the application of large-scale conservation policies, they could be much more effective at simultaneously accomplishing programmatic objectives and contributing to wildlife conservation. This may be possible by applying the principles of conservation biology and reserve network design for the strategic placement of focal areas, and making use of the growing body of literature on vulnerability and adaptation of wildlife populations to environmental change. Smart conservation decisions should appropriately be based on measurable conservation objectives and rigorous analyses that incorporate the values of stakeholders, consider numerous alternatives, and objectively evaluate the consequences of each alternative while paying close attention to the uncertainties associated with predicting the outcomes of conservation alternatives and the effects of linked decisions. If competing models are used to predict system response to management actions, these constitute the basic elements of adaptive management, which is an ideal tool for decision making when uncertainty is great and there is opportunity to learn by monitoring the consequences of management actions. This process will be illustrated using a model for longleaf pine bird conservation that incorporates land use change due to climate and urban growth.