Print PageThe overall objective of this study is to define reference models for measuring ecological recovery for southeastern United States that can be coupled with the recovery of the Red-cockaded woodpecker (RCW), a species of high conservation priority on several military bases. The premise of the dynamic ecological reference model is that habitat recovery must be considered in the context of continually changing reference conditions. To develop a dynamic reference model to gauge the impact of common forest restoration and management practices (herbicides, fire and timber harvests) and predict the direction and rate of recovery with respect to ecosystem management objectives we: (1) resampled six large (81-ha) plots that were intensively studied reference sandhills for a landscape restoration experiment led by The Nature Conservancy from 1993-1998; (2) resampled all 1-ha plots identified as high quality reference conditions for sandhill sites in the extensive monitoring program at Eglin AFB; (3) resampled 20 81-ha oak removal plots from the original TNC study to document recovery of vegetation, fauna and soils over a 15 year time period in response to fire, herbicide, and mechanical treatments. During 2009-2010, we resampled vegetation plots for overstory and understory and a map of woody vegetation cover was developed for each restoration treatment.
Results/Conclusions
Our preliminary multivariate analyses of vegetation composition change relative to reference conditions from pre-treatment to final resample show that when understory, midstory, and overstory species data are included, the mechanical and herbicide (plus fire) plots have moved closer to reference plots in multivariate space than the other treatments. However, when only understory data is examined, compositional differences between the treatment plots at the final resample are minimal. In addition to providing insight into the impact of specific management practices, these results highlight the complexity of identifying which elements of reference conditions should be used to assess ecological recovery and management effectiveness. Ultimately, these data will be used to build a forest dynamics modeling tool that can simulate RCW population response to landscape-scale habitat changes through time. Finally, an Oracle-based Decision Support Framework will automate statistical analysis of ecological monitoring data to assess trends in ecological condition relative to trajectories in reference conditions, while feeding relevant data to the RCW model.
