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Conservation and restoration of biodiversity and ecosystems is increasingly important due to negative impacts caused by expanding human populations, changing land use, and climate change. Understanding drivers of system processes supports efficient restoration and successful conservation of biodiversity and ecosystems. We describe a long-term forest monitoring program established as a component of a long-term ecological monitoring approach and used in conjunction with adaptive management to actively restore a longleaf pine (Pinus palustris) system. Eight panels of 108 monitoring points were selected within our 11,740 ha study area near Newton, GA, USA using a Random Tessellation Stratified design with hierarchical randomization. Each year two panels were sampled, resulting in a complete survey of all points every four years. To date, data have been collected over four sampling intervals (2002-2017). Collected data included basic forestry measurements and quantification of understory conditions. For an initial analysis of the data, we calculated estimates and error of average volume, change in volume, mortality, diameter distribution, and ingrowth. Additionally, we compared effects of management practices, which varied between plots, on these estimates. The tree volume on the study area is comprised primarily of longleaf pine with similar to 80% of this volume from trees >= 34 cm DBH. Pine tree volume increased by 13.29 (+/- 2.03) m(3)/ha between Intervals 1 and 4. Pine mortality during each sample interval was relatively stable over the study period, 2.98 (+/- 0.39) -4.56% (+/- 0.58), and primarily attributed to timber harvest. Management activities resulted in increased longleaf pine ingrowth and reduced hardwood volume. Our analyses indicate that through our management actions we have successfully made progress towards achieving our overall restoration goals for the site. Data collected from the long-term monitoring program were also used to provide information for scientific studies regarding water conservation in longleaf pine systems and wildlifehabitat relationships. As monitoring progresses, collected data will be used to assess progress and guide further restoration using adaptive management and dynamic reference models.