As the UN Decade on Ecosystem Restoration begins, grassland restoration projects are being scaled up globally. However, a new generation of opportunities and challenges requires a new generation of scientific guidance, particularly for grassland ecosystems that need of restoration. Our meta‐analysis indicated that grassland restoration significantly enhances biodiversity and ecosystem multifunctionality. However, biodiversity and ecosystem multifunctionality both increased in only half of the restoration observations, indicating that the effectiveness of global grassland restoration needs to be improved. Restoration methods and time were identified as important predictors of the effectiveness of grassland restoration. To address this, we conducted a multi‐objective optimization to assess when, where and how to better implement grassland restoration projects globally. This optimization aimed to provide targeted strategies for different grassland types and regions, considering the varying characteristics and needs of each biome. Our results revealed specific optimal restoration strategies for different biomes: 4 years after seeding in desert and semi‐desert biomes, continued grazing management for 10 years in polar and alpine biomes, and 26 years after soil inoculation in savanna and grassland biomes. Our findings offer clear guidance for enhancing the effectiveness of grassland restoration efforts across diverse ecosystems. Policy implications : Grassland restoration is crucial for global biodiversity conservation and ecosystem function maintenance. Our work provides scientific insights into the key factors influencing restoration effectiveness and specific optimal strategies for different biomes. This understanding is vital for formulating public policies that promote large‐scale, effective grassland restoration, thereby maximizing biodiversity gains and improving ecosystem multifunctionality.
Assessing and improving global grassland restoration: Drivers, current effectiveness and future design
Lingfan Wan,Guo-qing Liu,Bojie Fu,Ying Hu,Xukun Su
Published 2025 in Journal of Applied Ecology
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2025
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Journal of Applied Ecology
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2025-11-15
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