Patterns and processes: Monitoring and understanding plant diversity in frequently burned longleaf pine (Pinus palustris) landscapes
Longleaf pine (Pinus palustris) ecosystems are remarkably rich in plant species and represent the dominant upland forest type in several southeastern military installations. Management of these forests on installations is critical both to fulfill the military mission and to conserve this unique natural resource. The researchers will couple a series of field experiments with data mining exercises to help managers meet their objectives for monitoring the impact of various activities on the understory plant community. Results from this project will also aid development of modeling tools to help evaluate different management scenarios based on the intimate link between overstory structure, fire, and understory plant diversity. The project goals are to: (1) understand how the accuracy and effectiveness of sampling and monitoring programs are affected by the scale and timing of measurements, (2) increase plant sampling efficiency and efficacy by identifying and developing statistical approaches for dealing with complex spatial patterns of species distributions, and (3) examine the mechanisms driving patterns of plant diversity and then use this information to find linkages between small scale patterns in understory plant diversity and coarser scale stand characteristics that are more easily monitored and manipulated by managers. The overarching goal will be to develop sampling tools and spatially explicit models that predict the outcomes of various fire- and stand-management practices relative to understory diversity.