Modeling the distribution of cultural ecosystem services based on future climate variables under different scenarios

With the far-reaching consequences of worldwide climate variationon ecosystems and human societies, understanding and predicting changes in cultural ecosystem services (CES) is essential for sustainable development policy and resource planning. Past studies have focused on changes and impacts on natural ecosystems, while relatively few studies have been conducted on predictions of CES. This study combines POI datasets with future climate variables under different scenarios into the Maxent model for forecasting the spatial and temporal distribution of CES, which provides strong support for future decision-making. The results indicate that: (1) Under the SSP126 and SSP585 scenarios, the CES values in the northern, western, central, and northeastern parts of the study area are relatively high, while those in the southwestern, southern, and southeastern parts are relatively low. (2) Under the SSP126 scenario, the total CES shows an increasing trend from 2021 to 2040, but slightly declines from 2061 to 2080. In contrast, under the SSP585 scenario, the total CES significantly decreases from 2021 to 2040, especially in the provinces of Guizhou, Hunan, Zhejiang, and Anhui. (3) Temperature has a significant impact on CES predictions, with the annual mean temperature (Bio1) positively correlated with total CES, contributing between 0.75 and 0.78 to the distribution of CES across different years and scenarios. Additionally, the maximum temperature of the hottest month (Bio5) and the mean temperature of the wettest quarter (Bio8) also significantly influence CES under different scenarios and years. These findings reveal the regional characteristics and variations in CES distribution under different climate scenarios, providing crucial scientific evidence for future policy-making, resource management, and climate adaptation strategies. They also offer important insights into the impact of global climate change on ecosystems and human society, serving as a valuable reference for future national decision-making.

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Publication Details

Journal
Scientific Reports
Published
2024-11-08
DOI
https://doi.org/10.1038/s41598-024-78798-1
Citations
3
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.85

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article

Modeling the distribution of cultural ecosystem services based on future climate variables under different scenarios

Chang You, Lun Yin, Hongjiao Qu, Luo Guo
3 citations
Scientific Reports
Land Use and Ecosystem Services
0.85
article

Modeling the distribution of cultural ecosystem services based on future climate variables under different scenarios

Chang You, Lun Yin, Hongjiao Qu, Luo Guo
article en
3 citations

Abstract

With the far-reaching consequences of worldwide climate variationon ecosystems and human societies, understanding and predicting changes in cultural ecosystem services (CES) is essential for sustainable development policy and resource planning. Past studies have focused on changes and impacts on natural ecosystems, while relatively few studies have been conducted on predictions of CES. This study combines POI datasets with future climate variables under different scenarios into the Maxent model for forecasting the spatial and temporal distribution of CES, which provides strong support for future decision-making. The results indicate that: (1) Under the SSP126 and SSP585 scenarios, the CES values in the northern, western, central, and northeastern parts of the study area are relatively high, while those in the southwestern, southern, and southeastern parts are relatively low. (2) Under the SSP126 scenario, the total CES shows an increasing trend from 2021 to 2040, but slightly declines from 2061 to 2080. In contrast, under the SSP585 scenario, the total CES significantly decreases from 2021 to 2040, especially in the provinces of Guizhou, Hunan, Zhejiang, and Anhui. (3) Temperature has a significant impact on CES predictions, with the annual mean temperature (Bio1) positively correlated with total CES, contributing between 0.75 and 0.78 to the distribution of CES across different years and scenarios. Additionally, the maximum temperature of the hottest month (Bio5) and the mean temperature of the wettest quarter (Bio8) also significantly influence CES under different scenarios and years. These findings reveal the regional characteristics and variations in CES distribution under different climate scenarios, providing crucial scientific evidence for future policy-making, resource management, and climate adaptation strategies. They also offer important insights into the impact of global climate change on ecosystems and human society, serving as a valuable reference for future national decision-making.

Scientific ReportsVol. 14(1)
Minzu University of China (CN), Southwest Forestry University (CN)
Ministry of Science and Technology of the People's Republic of China, National Key Research and Development Program of China
Openalex Percentile: Top 27%
Land Use and Ecosystem Services
0.85
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