Forest restoration: a global dataset for biodiversity and vegetation structure

Area of Science:

• Restoration Ecology
• Forest Ecosystems
• Biodiversity Conservation

Background:

• Ecological restoration initiatives are widespread globally, receiving substantial investment.
• Restoration outcomes vary significantly due to diverse socioeconomic and ecological contexts.
• A comprehensive understanding of factors influencing restoration success is crucial.

Purpose of the Study:

• To present the most comprehensive dataset on forest restoration compiled to date.
• To facilitate global analyses of factors influencing forest restoration success at local and landscape scales.
• To guide future restoration initiatives and advance ecological restoration knowledge.

Main Methods:

• Compiled data from 269 primary studies across 221 landscapes in 53 countries.
• Included 4,645 quantitative comparisons of biodiversity and vegetation structure between reference and restored/degraded forest ecosystems.
• Collected data on study location, year, disturbance history, restoration activities, and ecological metrics, alongside landscape-scale forest cover and configuration.

Main Results:

• The dataset encompasses five taxonomic groups (mammals, birds, invertebrates, herpetofauna, plants) and five vegetation structure measures.
• Data includes detailed information on study context, restoration interventions, and quantitative ecological outcomes.
• Forest cover and configuration metrics (patch size, edge:area ratio) were estimated for each study landscape.

Conclusions:

• The presented dataset is a valuable resource for global analyses of forest restoration.
• Understanding local and landscape factors is critical for improving restoration effectiveness.
• Further research is needed to synthesize findings and inform evidence-based restoration practices.