Incorporating expert knowledge in decision-support models for avian conservation

Abstract

Bird abundance in the United States has been declining for more than half a century, likely as a result of habitat changes (Valiela and Martinetto 2007; North American Bird Conservation, U.S. Committee 2009). In the Southeastern United States, habitat and management changes including deforestation, reforestation, urban growth, and fi re suppression have reduced the availability of high-quality habitats and have increased habitat fragmentation (Wear 2002; Griffi th et al. 2003; Van Lear et al. 2005). Short-term projections suggest that urbanization will continue to reduce forest areas and increase their fragmentation (Wear et al. 2004). In the long term, climate change will alter precipitation and temperature patterns, and rising sea levels will reduce coastal habitat (IPCC 2007). It is therefore important to conserve what is currently available (species, habitats, and ecosystems) and plan for future conservation. To effectively protect or increase bird populations in this context, conservation must maintain or increase habitat quality and quantity. However, given limited resources, it is important to focus efforts where they have the greatest benefi t rather than where land is economically unimportant (Pressey et al. 1996). Furthermore, complex systems with multiple species and habitats may require trade-offs among confl icting conservation objectives.