|dc.description.abstract||The Southeastern United States has high conservation importance because of the region's habitat and species diversity, ecological processes, and evolutionary potential; however, it also warrants strong concern because of historical habitat loss, future threats, and inadequate protection. Based on data from United States Geological Survey, we estimate that only 12\% of Southern Coastal Plain ecoregion is under permanent protection. Conservation planning for this large and varied ecoregion is complicated by variable data availability across regions, habitats, and species. As part of a larger project to ensure adequate current and future habitat for bird populations, I defined a suite of focal species; developed a method to determine conservation priorities; and integrated future land cover conditions into conservation priorities. As part of a larger project to ensure adequate current and future habitat for bird populations, I defined a suite of focal species; developed a method to determine conservation priorities; and integrated future land cover conditions into conservation priorities. For my first chapter, I elicited expert knowledge of species–habitat associations in order to define a suite of focal species for species–habitat modeling. I wanted to use multiple focal species to reduce the risk of missing endemic or range-restricted species, to include species with substantial public interest or conservation resources, and to represent all habitat types in the study region. Fifty-three experts attended elicitation meetings and were asked to identify and score the habitat characteristics required for each potential focal species. I used two selection methods to develop focal species lists based on expert knowledge. The Lambeck method systematically selected species based on their threat category and the structured decision making process based on species with non-overlapping habitat associations. I assessed the overall list composed of species on both lists using an online survey. From online responses, I added 11 species to the focal species list which we then used to model conservation priorities in the Southeastern US.
In order to prioritize large areas for conservation, I developed a process that integrates spatial reserve design principles including prioritizing vegetation patches that are large, round and close to other patches. I compare the results of this prioritization process using three different conservation proxies: vegetation types, focal species, and focal species values derived from online expert elicitation. Three binary grids were used to develop priority surfaces based on vegetation type – suitability, conservation lands, and urban. The other two prioritization methods used focal species to identify priority areas by using additional species-specific datasets – potential habitat and putative source populations. We used the density of each binary grid, calculated by a two-dimensional kernel density estimator, to calculate conservation priority for each location in a regular 200m grid across the entire SAMBI area. Using only vegetation type density to create conservation priority maps resulted in more high conservation priority areas compared to focal species prioritization except for the most restricted vegetation types, such as those that were maritime-associated. Conservation priority surfaces created using focal species and fsv were very similar. Using vegetation type alone to create priority surfaces required fewer data and the data are more readily available (all sourced from publically available datasets), but it did not reflect species habitat use making it problematic for conservation efforts targeted at species.
Finally, in order to provide a tool to enable stakeholders to conserve species and habitats that are currently present and to integrate future habitat conditions to allow species to respond to climate change, I designed conservation priority areas for two habitats, open pine and maritime forest, that are expected to respond to different aspects of climate change, increased fragmentation and sea level rise, respectively. Land cover projections were developed for years 2000 to 2100 at 10-year time intervals for three global climate change models. We included five binary spatio-temporal grids to prepare habitat priority maps: (1) potential habitat and (2) putative source population distributions for each of the focal species; (3) suitability models for each habitat; (4) conservation lands; and (5) urban areas. Overall priority surfaces were created by combining priority surfaces from each time interval. For both habitats, differences between priority surfaces created with discounted or summed future conditions affected how valuable areas were to conservation but not where those areas were within the region, and surfaces did not differ significantly between climate scenarios. Similarities among alternatives of future conditions may be a result of scale because climate change may have a strong local, but weak regional effect. Having six similar alternatives suggests a set of consistent conservation priorities that can be relied upon to conserve bird populations in the study region. As additional information is gathered relating to climate-change-driven land cover changes, alternatives may diverge which makes repeating the modeling process very important.||en_US