Author
Listed:
- Mo Bi
(School of Foreign Languages, Southeast University, Nanjing 211189, China
African Studies Center, Institute of International and Regional Studies, Southeast University, Nanjing 211189, China)
- Fangyi Ren
(School of Geographic & Oceanographic Sciences, Nanjing University, Nanjing 210023, China)
- Yian Xu
(School of Geographic & Oceanographic Sciences, Nanjing University, Nanjing 210023, China)
- Xinya Guo
(School of Geographic & Oceanographic Sciences, Nanjing University, Nanjing 210023, China)
- Xixi Zhou
(School of Foreign Languages, Southeast University, Nanjing 211189, China)
- Dmitri van den Bersselaar
(Institute of African Studies, Leipzig University, D-04107 Leipzig, Germany)
- Xinfeng Li
(School of Foreign Languages, Southeast University, Nanjing 211189, China
African Studies Center, Institute of International and Regional Studies, Southeast University, Nanjing 211189, China)
- Hang Ren
(Institute of Population Studies, Nanjing University of Posts and Telecommunications, Nanjing 210042, China)
Abstract
This study investigates the spatio-temporal dynamics of Climate Potential Productivity (CPP) in Central Africa during 1901–2019 using the Thornthwaite Memorial model coupled with Mann–Kendall tests based on high spatial and temporal resolution data. The results demonstrate the climate–vegetation interactions under global warming: (1) Central Africa exhibited a statistically significant warming trend (r 2 = 0.33, p < 0.01) coupled with non-significant rainfall reduction, suggesting an emerging warm–dry climate regime that parallels meteorological trends observed in North Africa. (2) Central Africa exhibited an overall increasing trend in CPP, with temporal fluctuations closely aligned with precipitation variability. Specifically, the CPP in Central Africa has undergone three distinct phases: an increasing phase (1901–1960), a decreasing phase (1960–1980), and a slow recovery phase (1980–2019). The multiple intersection points between the UF and UB curves indicate that Central Africa’s CPP has been significantly affected by climate change under global warming. (3) The correlation of CPP–Temperature was mainly positive, mainly distributed in the Lower Guinea Plateau and the northern part of the Congo Basin (r 2 = 0.26, p < 0.1). The relationship of CPP–Precipitation showed predominantly a very strong positive correlation (r 2 = 0.91, p < 0.01).
Suggested Citation
Mo Bi & Fangyi Ren & Yian Xu & Xinya Guo & Xixi Zhou & Dmitri van den Bersselaar & Xinfeng Li & Hang Ren, 2025.
"Impact Assessment of Climate Change on Climate Potential Productivity in Central Africa Based on High Spatial and Temporal Resolution Data,"
Land, MDPI, vol. 14(8), pages 1-16, July.
Handle:
RePEc:gam:jlands:v:14:y:2025:i:8:p:1535-:d:1710740
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:jlands:v:14:y:2025:i:8:p:1535-:d:1710740. 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.