The Ginkgo biloba L. in China: Current Distribution and Possible Future Habitat

Zhang, Ying; Zhang, Jinbing; Tian, Li; Huang, Yaohui; Shao, Changliang

doi:10.3390/f14122284

Cited by 2 publications

(1 citation statement)

References 61 publications

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“…Simultaneously, decision-makers need to plan and establish nature reserves following the actual local conditions, which is the principal method to protect endangered species. Priority should be given to areas where current climate scenarios overlap with potentially suitable areas under future climate scenarios [95]. For the low habitat area suitable for the growth of D. involucrata, there are further reasons to introduce policy according to the predicted results under different scenarios and the actual local conditions.…”

Section: Discussionmentioning

confidence: 99%

Predicting the Potential Habitat Distribution of Relict Plant Davidia involucrata in China Based on the MaxEnt Model

Wang,

Li,

Cui

et al. 2024

Forests

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Davidia involucrata Baill. 1871 (D. involucrata), as a tertiary relict plant unique to China, is a national Class I protected plant with high economic value. Oil extracted from its seeds and peels can be used for both consumption and industrial purposes. It has become a popular income-earning export tree in China because of its graceful posture and beautiful white bracts. Climate change affects the distribution of the species’ potential habitat areas. Thus, studying its natural distribution pattern and future potential habitat distribution changes has great significance for the sustainable resource utilization and biodiversity conservation of D. involucrata. Here, we employed the MaxEnt model and ArcGIS software to predict the current and future (the 2050s and 2070s) potential habitats of D. involucrata via 130 species distribution records and 37 environmental variables. Meanwhile, we used the jackknife method to assess the importance of environmental factors. Our results showed the following: (1) When the RM = 4 and FC = LQHPT, the MaxEnt model exhibited the lowest complexity and overfitting degree while achieving high model prediction accuracy. The area under the curve (AUC) value of the simulated training was 0.958, indicating an excellent forecast. (2) Under the current climate scenario, D. involucrata was mainly concentrated in eastern Sichuan, western Hubei, northern Guizhou, and northwestern Hunan, with an area of 98.02 × 104 km2. (3) The precipitation in the warmest quarter (Bio18, 30%), mean temperature in the driest quarter (Bio9, 24.4%), annual mean radiation (Bio20, 14.6%), and elevation (ele, 12.7%) were the main environmental factors affecting its habitat distribution; the t contribution was 82.1%. (4) Under different future climate scenarios, the potential habitat area of D. involucrata decreased overall. Compared with the current climate scenario, the areas of potential habitats gradually decreased in both the 2050s and 2070s under the ssp126 and ssp585 climate scenarios but decreased in the 2050s and then increased in the 2070s under the ssp370 climate scenario. Therefore, it is of great significance to track and monitor the existing population or community on the basis of the possible changes in its distribution area. Moreover, the artificial breeding of its seedlings should be considered in the future to improve the quality of its germplasm resources. In summary, our findings can provide a scientific understanding of D. involucrata distribution in China and are conducive to conservation and utilization.

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Section: Discussionmentioning

confidence: 99%

Predicting the Potential Habitat Distribution of Relict Plant Davidia involucrata in China Based on the MaxEnt Model

Wang,

Li,

Cui

et al. 2024

Forests

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Predicting the Potential Distribution of Aralia chinensis L. (Wild Vegetable) in China Under Different Climate Change Scenarios

Liu,

Liang,

Xie

et al. 2024

Biology

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Global climate change has a main impact on the distribution of plants. Aralia chinensis L. is economically valuable, making it necessary to predict the impact of climate change on its distribution. It is important for researching the effects of climate change on A. chinensis distribution to achieve sustainable utilization. Based on 340 occurrence records of A. chinensis covering all known provinces and 58 environmental factor data, we used MaxEnt to simulate the potential distribution of A. chinensis under current and different future climate scenarios, analyzing the key environmental variables affecting its distribution. The results were as follows: (1) Suitable A. chinensis habitats under current and different future climate scenarios were mainly distributed in the southern region of China, east of the Hu Huanyong line. (2) Annual precipitation, minimum temperature during the coldest month, precipitation during the driest month, and slope were the key environmental variables affecting its potential distribution, and annual precipitation was more important. (3) Suitable habitat areas were projected to increase under different future climate scenarios and expand westward and northward while shrinking in the central regions, such as Hubei and Hunan. The results provide a theoretical reference for the conservation and cultivation of A. chinensis.

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The Ginkgo biloba L. in China: Current Distribution and Possible Future Habitat

Cited by 2 publications

References 61 publications

Predicting the Potential Habitat Distribution of Relict Plant Davidia involucrata in China Based on the MaxEnt Model

Predicting the Potential Habitat Distribution of Relict Plant Davidia involucrata in China Based on the MaxEnt Model

Predicting the Potential Distribution of Aralia chinensis L. (Wild Vegetable) in China Under Different Climate Change Scenarios

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