Modelling Distributions of Asian and African Rice Based on MaxEnt

Yunan Lin, Hao Wang, Yanqing Chen, Jiarui Tan, Jingpeng Hong, Shen Yan, Yongsheng Cao () and Wei Fang ()
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Yunan Lin: The Innovation Team of Crop Germplasm Resources Preservation and Information, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Hao Wang: The Innovation Team of Crop Germplasm Resources Preservation and Information, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Yanqing Chen: The Innovation Team of Crop Germplasm Resources Preservation and Information, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Jiarui Tan: The Innovation Team of Crop Germplasm Resources Preservation and Information, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Jingpeng Hong: The Innovation Team of Crop Germplasm Resources Preservation and Information, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Shen Yan: The Innovation Team of Crop Germplasm Resources Preservation and Information, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Yongsheng Cao: The Innovation Team of Crop Germplasm Resources Preservation and Information, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Wei Fang: The Innovation Team of Crop Germplasm Resources Preservation and Information, Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China

Sustainability, 2023, vol. 15, issue 3, 1-11

Abstract: Rice landraces, including Asian rice ( Oryza sativa L.) and African rice ( Oryza glaberrima Steud.), provide important genetic resources for rice breeding to address challenges related to food security. Due to climate change and farm destruction, rice landraces require urgent conservation action. Recognition of the geographical distributions of rice landraces will promote further collecting efforts. Here we modelled the potential distributions of eight rice landrace subgroups using 8351 occurrence records combined with environmental predictors with Maximum Entropy (MaxEnt) algorithm. The results showed they were predicted in eight sub-regions, including the Indus, Ganges, Meghna, Mekong, Yangtze, Pearl, Niger, and Senegal river basins. We then further revealed the changes in suitable areas of rice landraces under future climate change. Suitable areas showed an upward trend in most of study areas, while sub-regions of North and Central China and West Coast of West Africa displayed an unsuitable trend indicating rice landraces are more likely to disappear from fields in these areas. The above changes were mainly determined by changing global temperature and precipitation. Those increasingly unsuitable areas should receive high priority in further collections. Overall, these results provide valuable references for further collecting efforts of rice landraces, while shedding light on global biodiversity conservation.

Keywords: rice landraces; crop genetic resources; ex situ conservation; food security; maximum entropy (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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