Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Prediction of Spatial and Temporal Changes of Carbon Stocks in Anhui Province Based on PLUS-InVEST Model
[Objective] The spatio-temporal variation and spatial distribution of carbon stocks since 2000 were analyzed in order to provide effective guidance for land management decision-making and ecosystem carbon pool management in Anhui Province in the future. [Methods] The PLUS model was used with land use data in Anhui Province over five periods (2000, 2005, 2010, 2015, 2020) to simulate land use patterns under different scenarios in 2030 and 2040. The InVEST model was applied to quantitatively assess the spatial changes of carbon stocks in terrestrial ecosystems under different scenarios. [Results] ① Approximately 8.03% of the land changed classification from 2000 to 2020, and the change between cultivated land and construction land was the fundamental element of land use change in Anhui Province. ② Between 2000 and 2020, the total amount of carbon stored in terrestrial ecosystems decreased by 1.01×108 t. High values of carbon density were primarily found in the hilly regions of Southern and Western Anhui Province. The spatial distribution of carbon density exhibited a pattern of “high in the south and low in the north.” ③ From 2020 to 2040, carbon stocks for the natural development scenario clearly declined, while the decrease in carbon stocks for the cultivated land preservation scenario slowed down. Carbon stocks for the ecological protection scenario increased significantly, with an increment of 3.07×107 t. [Conclusion] Implementing ecological conservation policies can effectively increase carbon stocks of regional ecosystems and enhance ecosystem service functions. Ecological conservation and cultivated land protection should be considered in future land use management decisions to promote the environmentally harmless and sustainable development of regional ecosystems.
Prediction of Spatial and Temporal Changes of Carbon Stocks in Anhui Province Based on PLUS-InVEST Model
[Objective] The spatio-temporal variation and spatial distribution of carbon stocks since 2000 were analyzed in order to provide effective guidance for land management decision-making and ecosystem carbon pool management in Anhui Province in the future. [Methods] The PLUS model was used with land use data in Anhui Province over five periods (2000, 2005, 2010, 2015, 2020) to simulate land use patterns under different scenarios in 2030 and 2040. The InVEST model was applied to quantitatively assess the spatial changes of carbon stocks in terrestrial ecosystems under different scenarios. [Results] ① Approximately 8.03% of the land changed classification from 2000 to 2020, and the change between cultivated land and construction land was the fundamental element of land use change in Anhui Province. ② Between 2000 and 2020, the total amount of carbon stored in terrestrial ecosystems decreased by 1.01×108 t. High values of carbon density were primarily found in the hilly regions of Southern and Western Anhui Province. The spatial distribution of carbon density exhibited a pattern of “high in the south and low in the north.” ③ From 2020 to 2040, carbon stocks for the natural development scenario clearly declined, while the decrease in carbon stocks for the cultivated land preservation scenario slowed down. Carbon stocks for the ecological protection scenario increased significantly, with an increment of 3.07×107 t. [Conclusion] Implementing ecological conservation policies can effectively increase carbon stocks of regional ecosystems and enhance ecosystem service functions. Ecological conservation and cultivated land protection should be considered in future land use management decisions to promote the environmentally harmless and sustainable development of regional ecosystems.
Prediction of Spatial and Temporal Changes of Carbon Stocks in Anhui Province Based on PLUS-InVEST Model
Wang Yongzheng (Autor:in) / Xu Yali (Autor:in) / Yu Haoran (Autor:in)
2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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| DOAJ | 2023
| Springer Verlag | 2025
| DOAJ | 2023