At Eglin Air Force Base (AFB), this project undertook the refinement of reference models for longleaf pine (Pinus palustris) sandhills to incorporate temporal variation in ecosystems caused by disturbance and succession, as well as seasonal, interannual, or decadal variability. The project team then expanded two decision support tools as a framework for assessing ecosystem status and trends for the federally endangered red-cockaded woodpecker (Picoides borealis; RCW) and the longleaf pine sandhill ecosystems on which this species depends. Specific objectives were to: (1) quantify annual and decadal dynamics of reference longleaf pine sandhills to create practical and realistic benchmarks for vegetation and faunal restoration; (2) determine recovery rates of degraded sandhill ecosystems (vegetation, soils, fauna) over a 10-15 year period in response to hardwood removal treatments; (3) integrate 1 and 2 above into a dynamic habitat modeling tool for management of RCWs, which integrates an existing population model to incorporate population and forest habitat feedbacks; (4) integrate 1 and 2 above into a Decision Support Framework (DSF) that allows monitoring data and landscape-scale ecological condition to be evaluated, while enhancing decision making.

The project team re-sampled six large (81-ha) plots that were intensively studied reference sandhills from an experiment led by The Nature Conservancy from 1993-1999. To capture a wider range of variation, all 1-ha high-quality reference plots identified in the extensive monitoring program at Eglin AFB were also sampled. The rates of recovery in vegetation and faunal communities and soil processes 15 years post-restoration treatments were examined. Short-term (1-5 year) response of vegetation response to management actions across Eglin AFB were determined by comparing ecological monitoring plots with that of reference conditions. Expert opinion and field data from Eglin AFB were used to parameterize a dynamic habitat modeling tool in the program ST-SIM (the “ST-SIM landscape model”). Predictive habitat maps produced by this tool were used as landscape layers in the RCW population model to show how landscape change, including successional processes, disturbance, and anthropogenic development could affect RCW populations. An Oracle database was used to operate a DSF to automate statistical analysis of ecological monitoring data for spatial and temporal trends in ecological condition, relative to dynamic reference conditions monitored at Eglin over time. The DSF integrates with the ST-SIM landscape model by supplying base data layers.

Degraded longleaf pine ecosystems were found to move directionally towards the a priori reference sites with all of the restoration treatments. The reference conditions, however, also moved with a magnitude equivalent to the movement of restoration vectors. This reference movement highlights a fundamental challenge in understanding recovery in the context of a dynamic target. The reference sites in this study became more species rich, achieved greater abundance of understory plants, and showed greater evenness in response to a suite of changes from 1994 to 2011, including multiple fires, a longleaf pine mast event, and several hurricanes.

Faunal study results showed longleaf pine obligate species to be abundant across all recovering longleaf pine sites despite differences in structure (mainly oak [Quercus spp.] stem density) that were thought to preclude recovery in faunal communities. These results suggest that the range of reference conditions is broader than previously considered, furthering an understanding of the limits of subjective reference targets in a dynamic and variable ecosystem.

Forest dynamics modeling allowed the results of community recovery to be incorporated into a state-and-transition model of longleaf pine communities. This model, built in the program ST-SIM, was developed in conjunction with another SERDP project (RC-1472) and the North Carolina State University team. The project team joined a demographic model created through the prior SERDP work, which models RCW population dynamics, with an ST-SIM landscape model customized to simulate longleaf pine dynamics in response to habitat management and other landscape change at Eglin AFB over a 50-year timeframe. Lastly, the DSF was completed at Eglin AFB to display real-time analytical results for monitoring data that were developed in the field portion of this study.

The Dynamic Reference Concept and associated tools developed as part of this project use longleaf pine ecosystems to understand the ecological trajectories of recovery and management in the context of larger scale changes to reference site conditions over longer time frames. This study not only places restoration success in a theoretical construct that helps plan and organize conservation in the context of an uncertain future, its data analysis also provides managers and scientists tools to understand changes in the context of conservation objectives.