Active interventions accelerate native plant recolonization following agricultural abandonment

A key challenge in restoration planning is predicting how passive and active processes may best be used together to promote successful landscape recovery. While passive recolonization of native plant communities can drive recovery, this process is often slow, and success is variable. Active restoration practices, such as reinstating historical disturbance regimes, may accelerate recolonization. However, few studies have empirically tested how specific active interventions can be used to facilitate recovery across heterogenous landscapes. We conducted a 13-year field experiment monitoring the recolonization of longleaf pine savanna ground-layer communities in landscapes recovering from agricultural use in the southeastern USA. Across 12 sites, we established pairs of 1-ha plots in untilled, fire-suppressed remnant savannas and adjacent pine plantations previously under agriculture (recovering areas). Each pair was randomly assigned a restoration treatment: canopy thinning in the remnant,..., , # Active interventions accelerate native plant recolonization following agricultural abandonment Dataset DOI: [10.5061/dryad.9cnp5hr03](https://doi.org/10.5061/dryad.9cnp5hr03) ## Description of the data and file structure We conducted a 13-year field experiment monitoring the recolonization of longleaf pine savanna ground-layer communities in landscapes recovering from agricultural use in the southeastern USA. Across 12 sites, we established pairs of 1-ha plots in untilled, fire-suppressed remnant savannas and adjacent pine plantations previously under agriculture (recovering areas). Each pair was randomly assigned a restoration treatment: canopy thinning in the remnant, the recovering area, both, or neither (control), combined with either low or high frequency of prescribed fire. In each recovering area, we measured the spread of remnant indicator plant species along a 100 m transect extending away from the remnant. ### Files and variables #### File: IndicatorSppDatasetJAN2026.cs..., ,