Multi-Criteria Plant Clustering for Carbon-Centric Urban Forestry: Enhancing Sequestration Potential Through Adaptive Species Selection in the Zhengzhou Metropolitan Area, China
As global climate change and urban issues worsen, increasing carbon offsets is crucial, with urban plants playing a key role. However, research on assessing plant carbon sequestration (CSE) capacity at the regional scale, selecting urban plants, and optimizing CSE capacity-based scenarios is still l...
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Published in | Forests Vol. 16; no. 3; p. 536 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Basel
MDPI AG
19.03.2025
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Subjects | |
Online Access | Get full text |
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Summary: | As global climate change and urban issues worsen, increasing carbon offsets is crucial, with urban plants playing a key role. However, research on assessing plant carbon sequestration (CSE) capacity at the regional scale, selecting urban plants, and optimizing CSE capacity-based scenarios is still limited. A total of 272 plant species were surveyed in the nine cities of the Zhengzhou Metropolitan Area (ZMA). The i-Tree and biomass models estimated the average carbon storage (CS) density at 9.32 kg C m−2 and the CSE density at 0.55 kg C y−2 m−2 in the ZMA. The highest CS density (13.58 kg C m−2) was observed in Pingdingshan, while the lowest CSE density (0.36 kg C y−1 m−2) was observed in Xuchang. Hierarchical and cluster analyses identified plant species with balanced CSE capacity, adaptability, and ornamental value, such as Populus tomentosa Carr. and Salix babylonica L., as well as shrubs like Abelia biflora Turcz and Kerria japonica (L.) DC. Vegetation regeneration modeling indicated that CS could increase by 37%–41% along roads, 28%–43% in amenity areas, and 17%–30% near waterfronts over the next 50 years. These findings serve as a reference for urban regeneration and planning aimed at enhancing the carbon reduction potential of urban green spaces (UGS). |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 1999-4907 1999-4907 |
DOI: | 10.3390/f16030536 |