Potential vegetation estimations help to assess feasibility and expected effort needed in grassland restoration by shrub removal

Shrub removal is a common practice for restoring and conserving biodiverse open ecosystems, such as species-rich grasslands. However, a single intervention is often not sufficient; many sites require ongoing management to prevent shrub regrowth and sustain the desired vegetation state. This study explores whether we can anticipate those long-term management needs using ecological modeling.

Researchers from the HUN-REN Centre for Ecological Research applied MPNV models to grassland restoration projects in Hungary, using the restoration project database of Török et al. (2019), supplemented by expert input from national park directorates. MPNV models developed by Somodi and colleagues estimate the relative self-sustainability of different vegetation types at a given site. They investigated whether the predicted self-sustainability of forest and grassland types could explain the intensity of post-treatment required after shrub removal.

The study found that higher self-sustainability of forest vegetation, as predicted by the MPNV model, was strongly associated with greater post-treatment requirements—even when grassland vegetation was also considered self-sustaining. This suggests that sites with a strong natural tendency toward forest may resist stable grassland restoration unless actively managed.

By incorporating MPNV predictions into planning, restoration efforts can be directed toward sites where long-term success is more likely and maintenance needs are lower. This allows for more strategic use of limited resources and improves the cost-effectiveness of grassland restoration. . These findings can also contribute to providing a robust scientific basis for achieving the objectives set out in the EU Nature Restoration Regulation.