2023
DOI: 10.3389/fpls.2022.1009577
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Modeling of the potential geographical distribution of naked oat under climate change

Abstract: IntroductionNaked oat (Avena sativa L.), is an important miscellaneous grain crop in China, which is rich in protein, amino acids, fat and soluble dietary fiber. The demand for functional foods is gradually increasing as living standards rise, and the output of minor cereals in China is increasing annually. The planting layout of naked oat is scattered and lacks planning, which seriously restricts the development of the naked oat industry. The increase in miscellaneous grain production will not only be impacte… Show more

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Cited by 4 publications
(4 citation statements)
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“…Among these, the contribution rate and the importance value of Annual precipitation (Bio12) were the highest, indicating that in arid and semi-arid regions, precipitation is more important than temperature. This is consistent with the findings of Qin et al (2023), who observed that extreme drought in certain areas consumed soil moisture reserves, restricting plant survival and growth. Furthermore, when Annual precipitation (Bio12) exceeded 150 mm, C. multiflorus can survive, and when it exceeded 500 mm, the survival rate was 0.60 (Figure 6).…”
Section: Constraints Of Environmental Variables On the Potential Dist...supporting
confidence: 92%
“…Among these, the contribution rate and the importance value of Annual precipitation (Bio12) were the highest, indicating that in arid and semi-arid regions, precipitation is more important than temperature. This is consistent with the findings of Qin et al (2023), who observed that extreme drought in certain areas consumed soil moisture reserves, restricting plant survival and growth. Furthermore, when Annual precipitation (Bio12) exceeded 150 mm, C. multiflorus can survive, and when it exceeded 500 mm, the survival rate was 0.60 (Figure 6).…”
Section: Constraints Of Environmental Variables On the Potential Dist...supporting
confidence: 92%
“…Predicting the adaptive geographic distribution of species under climate change scenarios is a common method for understanding species adaptation [28]. Currently, species distribution models (SDMs) are a popular approach to predicting the adaptive geographical ranges of species, using data on the geographical distribution of species, bioclimatic and environmental factors, and other relevant information [29,30]. As a commonly used ecological niche model [31], the maximum entropy model (MaxEnt) has attracted more attention due to its relatively superior predictive power [32][33][34][35].…”
Section: Introductionmentioning
confidence: 99%
“…[8]. Species distribution models have been widely used to study the potential geographic distribution of species under various climate conditions [9]. Species distribution models (SDMs), also called 'habitat' models, can assess the distribution of a given species simply based on presence data and various environmental parameters.…”
Section: Introductionmentioning
confidence: 99%