Predicting plant species diversity in a longleaf pine landscape

In this study, we used a hierarchical, multifactor ecological classification system to examine how spatial patterns of biodiversity develop in one of the most species-rich ecosystems in North America, the fire-maintained longleaf pine-wiregrass ecosystem and associated depressional wetlands and riparian forests. Our goal was to determine which landscape features are important controls on species richness, to establish how these constraints are expressed at different levels of organization, and to identify hotspots of biological diversity for a particular locality. We examine the following questions: 1) How is the variance in patterns of plant species richness and diversity partitioned at different scales, or classification units, of the hierarchical ecosystem classification developed for the study area? 2) What are the compositional similarities among ecosystem types? 3) For our study area, what are the sites expected to harbour highest species richness? We used a spatially explicit map of biodiversity to project abundance of species-rich communities in the landscape based on a previously developed ecological classification system for a lower Gulf Coastal Plain landscape. The data indicate that high species richness in this ecosystem was found in sites with frequent fire and high soil moisture. Sites in fire-maintained landscapes with lower frequency of fire were associated with geomorphological characteristics, suggesting a dependence of the diversity-disturbance relationship with soil type. With more frequent fire on some sites, high diversity shifts from canopy component to ground flora, with an overall increase in total species richness. Our approach demonstrates how potential species richness can be identified as a restoration goal and that multiple vegetation endpoints may be appropriate vegetation objectives. We identify basic management needs for the maintenance of biodiversity in this ecosystem that can be derived from an understanding of the combination of factors that most strongly predict diverse plant communities.