Author
Listed:
- Runping Ma
(Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin 541004, China)
- Maofa Wang
(School of Applied Science, Beijing Information Science and Technology University, Beijing 102206, China)
- Chengcheng Wang
(Jilin Provincial Meteorological Information and Network Center, Changchun 130062, China)
- Yibo Zhang
(Jilin Provincial Meteorological Information and Network Center, Changchun 130062, China)
- Xiang Zhou
(Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin 541004, China)
- Li Jiang
(Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin 541004, China)
Abstract
Understanding the spatiotemporal dynamics of vegetation net primary productivity (NPP) and its drivers is critical to sustainable land -carbon management, carbon-neutral development, and ecological restoration in fragile karst landscapes. This study proposes a Pearson Correlation—Deep Transformer (PCADT) model that integrates attention mechanisms and geospatial covariates to enhance NPP estimation accuracy in Guangxi, China—a global karst hotspot. Leveraging multisource remote sensing data (2015–2020), PCADT achieves 10.7% higher predictive accuracy (R 2 = 0.83 vs. conventional models) at 500 m resolution, thereby capturing the fine-scale heterogeneity essential for sustainability planning. The results reveal a significant annual NPP increase (4.14 gC·m −2 ·a −1 , p < 0.05), with eastern areas exhibiting higher baseline productivity (1129 gC·m −2 in Wuzhou) but western regions showing steeper growth rates (5.2% vs. 2.1%). Vegetation carbon sequestration capacity, validated against MOD17A3HGF data (R 2 = 0.998), demonstrates spatial consistency (east > west), with forest-dominated Wuzhou contributing 6.5 TgC annually. Mechanistic analyses identify precipitation as the dominant climatic driver (partial r = 0.62, p < 0.01), surpassing temperature sensitivity, while bimodal NPP-altitude peaks (300 m and 900 m) and land -use transitions (e.g., forest-to-cropland conversions) explain 18.5% of NPP variability and reduce regional carbon stocks by 4593 tC. The PCADT framework offers a scalable solution for precision carbon management by emphasizing the role of anthropogenic interventions—such as afforestation—in alleviating climatic constraints. It advocates for spatially adaptive strategies to optimize water resource utilization, enhance forest conservation, and promote sustainable land -use transitions. By identifying areas where water -scarcity relief and targeted afforestation would yield the highest carbon returns, the PCADT framework directly supports SDG 13 (Climate Action) and SDG 15 (Life on Land), providing a strategic blueprint for sustainable development in water-limited karst regions globally.
Suggested Citation
Runping Ma & Maofa Wang & Chengcheng Wang & Yibo Zhang & Xiang Zhou & Li Jiang, 2025.
"Spatiotemporal Decoupling of Vegetation Productivity and Sustainable Carbon Sequestration in Karst Ecosystems: A Deep-Learning Synthesis of Climatic and Anthropogenic Drivers,"
Sustainability, MDPI, vol. 17(13), pages 1-25, June.
Handle:
RePEc:gam:jsusta:v:17:y:2025:i:13:p:5840-:d:1686855
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:13:p:5840-:d:1686855. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.