数字农科院2.0

Modelling Distributions of Asian and African Rice Based on MaxEnt

文献类型： 外文期刊

作者： Lin Y.;Wang H.;Chen Y.;Tan J.;Hong J.;Yan S.;Cao Y.;Fang W.

作者机构：

关键词： crop genetic resources;ex situ conservation;food security;maximum entropy;rice landraces

期刊名称： Sustainability (Switzerland)

ISSN： 2071-1050

年卷期： 2023 年 15 卷 3 期

页码：

收录情况： SCIE（2023版） ; ; SSCI（2023版）

摘要： 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. © 2023 by the authors.

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