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The identification of priority restoration areas (PRAs) for ecosystems is a critical step in establishing restoration programs. Because the majority of existing studies focused on improving the ecosystem supply, the PRAs selected are likely to be remote from human demand, and the restoration benefits will not flow to humans. To fill this gap, we constructed an improved framework integrating the ecological restoration projects' cost and benefits as indicators for choosing PRAs. Then, we identified PRAs for each ecosystem service (ES) with Marxan, and ranked the restoration priority grades according to the superimposed value of PRAs for each ES. Finally, we adjusted the restoration priority grades based on human demand and the concentration of those areas, and chose PRAs with a high ES supply and demand. This framework was applied to the Dongting Lake Eco-Economic Zone, one of China's most significant ecological restoration project sites. The results indicated that the areas with "high"-, "sub-high"-, and "low"-grade PRAs, based only on the increase in the ES supply, were equal to 82, 410, and 1696 km2, respectively. After considering human demand, the PRAs moved continuously towards places with a high human demand; high-priority areas grew to reach 144 km2, while low-priority areas decreased to 1498 km2. The upgrade of the proposed framework for the identification of PRAs can contribute to increasing human well-being, while also serving as a support tool for environmental restoration management. [ABSTRACT FROM AUTHOR]

The identification of priority restoration areas (PRAs) for ecosystems is a critical step in establishing restoration programs. Because the majority of existing studies focused on improving the ecosystem supply, the PRAs selected are likely to be remote from human demand, and the restoration benefits will not flow to humans. To fill this gap, we constructed an improved framework integrating the ecological restoration projects’ cost and benefits as indicators for choosing PRAs. Then, we identified PRAs for each ecosystem service (ES) with Marxan, and ranked the restoration priority grades according to the superimposed value of PRAs for each ES. Finally, we adjusted the restoration priority grades based on human demand and the concentration of those areas, and chose PRAs with a high ES supply and demand. This framework was applied to the Dongting Lake Eco-Economic Zone, one of China’s most significant ecological restoration project sites. The results indicated that the areas with “high”-, “sub-high”-, and “low”-grade PRAs, based only on the increase in the ES supply, were equal to 82, 410, and 1696 km2, respectively. After considering human demand, the PRAs moved continuously towards places with a high human demand; high-priority areas grew to reach 144 km2, while low-priority areas decreased to 1498 km2. The upgrade of the proposed framework for the identification of PRAs can contribute to increasing human well-being, while also serving as a support tool for environmental restoration management.