Growing biodiverse carbon-rich forests.

Area of Science:

• Ecology
• Forestry
• Conservation Science

Background:

• Forest restoration is crucial for biodiversity and climate change mitigation.
• Maximizing these co-benefits is complex due to ecological interactions, climate, and landscape factors.
• Current restoration strategies may not always optimize both carbon sequestration and biodiversity.

Purpose of the Study:

• To develop a mechanistic framework for managing forest restoration to maximize co-benefits.
• To demonstrate how plant functional traits and their interactions influence carbon sequestration and biodiversity.
• To provide decision-making rules for optimizing forest restoration in diverse contexts.

Main Methods:

• Synthesized three decades of research on forest dynamics and plant functional traits.
• Integrated decision science principles with ecological knowledge.
• Developed a framework to manage trait 'identities' and 'complementarities' for maximal co-benefits.

Main Results:

• Increasing tree functional trait diversity does not always maximize carbon sequestration.
• The relationship between plant functional diversity, carbon sequestration, and biodiversity is context-dependent (climate, landscape).
• Identified optimal planting and thinning rules for maximizing carbon and biodiversity.

Conclusions:

• A novel mechanistic approach guides forest management for multiple objectives.
• The framework supports initiatives like Reducing Emissions from Deforestation and forest Degradation (REDD+).
• Provides a foundation for cost-effective, adaptable forest management rules under global change.