Prediction of the potential geographical distribution of Betula platyphylla Suk. in China under climate change scenarios

Geng, Wenliang; Li, Yanyan; Sun, Dongqi; Li, Bin; Zhang, Pengyan; Chang, Hao; Rong, Tianqi; Liu, Ying; Shao, Jingwen; Liu, Zhenyue; Zhu, Huiru; Lou, Yuanyuan; Wang, Qianqian; Zhang, Jinbing

doi:10.1371/journal.pone.0262540

Cited by 16 publications

(4 citation statements)

References 73 publications

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“…Furthermore, with the intensifying global warming, the suitable area for C. luteoflora began to gradually become fragmented as it shifted to higher latitudes and altitudes. Other plants species ' Climate is the dominant factor affecting the geographical distribution of species at large scales in geographic regions [47]. Dai et al concluded that mainly the mean temperature of the warmest quarter, precipitation of the warmest quarter, and precipitation of the coldest quarter were the dominant factors affecting the potential geographical distribution of C. luteoflora.…”

Section: Discussionmentioning

confidence: 99%

Predicting Habitat Suitability and Adaptation Strategies of an Endangered Endemic Species, Camellia luteoflora Li ex Chang (Ericales: Theaceae) under Future Climate Change

Rong,

Luo,

et al. 2023

Forests

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Camellia luteoflora Li ex Chang is an endangered plant endemic to the East Asian flora with high ornamental value as well as phylogenetic and floristic research value. Predicting the impact of climate change on its distribution and suitable habitat is crucial until scientific conservation measures are implemented. Based on seven environmental variables and 17 occurrence records, this study optimized the MaxEnt model using the kuenm data package to obtain the optimal parameter combinations (RM = 1.3, FC = LPT) and predicted the potential distribution pattern of C. luteoflora in various future periods. The results revealed that the mean diurnal range, temperature annual range, and precipitation of the wettest month were the influential factors determining the distribution pattern of C. luteoflora, contributing 60.2%, 14.4%, and 12.3% of the variability in the data, respectively. Under the current conditions, the area of suitable habitats for C. luteoflora was only about 21.9 × 104 km2. Overall, the suitable area around the C. luteoflora distribution points will shrink in a circular pattern in response to future global warming, but some potentially suitable distribution areas will expand and migrate to higher latitudes and the Hengduan Mountains region, representing a survival strategy for coping with climate change. It is hypothesized that the future climate refugia will be the highly suitable area and the Hengduan Mountains region. Furthermore, a retrospective validation method was employed to assess the reliability of the predictions and estimate the model’s predictive performance in the future. This study proposes a survival strategy and adaptation measures for C. luteoflora in response to climate change, and the proposed measures can be generalized for application in conservation planning and restoration processes. We also recommend that future studies incorporate factors such as the anthropogenic disturbances and associated socio-economic activities related to C. luteoflora into the model and to further predict the distribution pattern for C. luteoflora in response to historical climatic changes, tracing the evolutionary history of its population.

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Section: Discussionmentioning

confidence: 99%

Predicting Habitat Suitability and Adaptation Strategies of an Endangered Endemic Species, Camellia luteoflora Li ex Chang (Ericales: Theaceae) under Future Climate Change

Rong,

Luo,

et al. 2023

Forests

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“…Since only CCSM4, MIROC–ESM and MPI–ESM–P Global Climate Models (GCMs) were available for the data of the LGM, to compare the prediction results of different GCMs, we selected the above three GCMs to simulate the ancient distribution of Polyspora . CCSM4 (The Community Climate System Model version 4) (Gent et al, 2011 ) is one of the most effective GCMs for predicting the impact of climate change on the distribution of animal and plant (Geng et al, 2022 ), and has the best precipitation prediction performance (Yang et al, 2020 ), especially for the precipitation prediction in southwest China (Yang, Yong, et al, 2021 ). MIROC–ESM (the Model for Interdisciplinary Research on Climate Earth System Model) has a good simulation of terrestrial carbon cycle and vegetation dynamics (Watanabe et al, 2011 ), and a good prediction of rainfall in the Yangtze River basin of China (Yang et al, 2020 ).…”

Section: Methodsmentioning

confidence: 99%

“…LGM, to compare the prediction results of different GCMs, we selected the above three GCMs to simulate the ancient distribution of Polyspora. CCSM4 (The Community Climate System Model version 4) (Gent et al, 2011) is one of the most effective GCMs for predicting the impact of climate change on the distribution of animal and plant (Geng et al, 2022), and has the best precipitation prediction performance (Yang et al, 2020), especially for the precipitation prediction in southwest China (Yang, Yong, et al, 2021) is a model specially designed for paleoclimate simulation (Braconnot et al, 2012;Jungclaus et al, 2013), which is accurate in simulating the trend of extreme temperature change in China (Jiang et al, 2017).…”

Section: Environmental Datamentioning

confidence: 99%

Impacts of climate change on species distribution patterns of Polyspora sweet in China

Fan

Zhou

Chang-le

et al. 2022

Ecology and Evolution

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Climate change is an important driver of species distribution and biodiversity. Understanding the response of plants to climate change is helpful to understand species differentiation and formulate conservation strategies. The genus Polyspora (Theaceae) has an ancient origin and is widely distributed in subtropical evergreen broad‐leaved forests. Studies on the impacts of climate change on species geographical distribution of Chinese Polyspora can provide an important reference for exploring the responses of plant groups in subtropical evergreen broad‐leaved forests with geological events and climate change in China. Based on the environmental variables, distribution records, and chloroplast genomes, we modeled the potential distribution of Chinese Polyspora in the Last Glacial Maximum, middle Holocene, current, and future by using MaxEnt‐ArcGIS model and molecular phylogenetic method. The changes in the species distribution area, centroid shift, and ecological niche in each periods were analyzed to speculate the response modes of Chinese Polyspora to climate change in different periods. The most important environmental factor affecting the distribution of Polyspora was the precipitation of the driest month, ranging from 13 to 25 mm for the highly suitable habitats. At present, highly suitable distribution areas of Polyspora were mainly located in the south of 25°N, and had species‐specificity. The main glacial refugia of the Chinese Polyspora might be located in the Ailao, Gaoligong, and Dawei Mountains of Yunnan Province. Jinping County, Pingbian County, and the Maguan County at the border of China and Vietnam might be the species differentiation center of the Chinese Polyspora . Moderate climate warming in the future would be beneficial to the survival of P. axillaris , P. chrysandra , and P. speciosa . However, climate warming under different shared socio‐economic pathways would reduce the suitable habitats of P. hainanensis and P. longicarpa .

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“…We understood the spatial autocorrelation to be due to overfitting of the data results caused by an overdense sample size in some regions 45 . These operations can greatly reduce the spatial autocorrelation of species occurrence data and effectively reduce the error 46 . Finally, data from 2529 samples of C. sinensis , C. cicadae , C. militaris and C. gunnii were obtained (Fig.…”

Section: Methodsmentioning

confidence: 99%

Cordyceps cicadae and Cordyceps gunnii have closer species correlation with Cordyceps sinensis: from the perspective of metabonomic and MaxEnt models

Zhang

Sun

Miao

et al. 2022

Sci Rep

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Cordyceps sinensis is a second-class nationally-protected medicinal fungus and functional food. Cordyceps sinensis resources are endangered, and finding new medicinal materials is a fast and economical way to meet the current demonstrated demand, which can effectively solve the shortage of C. sinensis resources. In this study, the metabolite characteristics of Cordyceps were comprehensively revealed by LC-QTOF-MS technology. The maxent model can be used to predict the habitat suitability distribution of Cordyceps and screen out the main climatic factors affecting its distribution. The correlation model between climate factors and chemical components was established by Pearson correlation analysis. Finally, based on the analysis of climate factors and metabolites, we will analyze the high correlation species with C. sinensis, and develop them as possible alternative species of C. sinensis in the future. The results showed that the suitable area of Cordyceps cicadae demonstrated a downward trend, while that of C. sinensis, Cordyceps militaris and Cordyceps gunnii demonstrated an upwards trend. The suitable areas all shifted to the northwest. The temperature seasonality and max temperature of the warmest month are the maximum climatic factors affecting nucleosides. Compared with C. sinensis, the metabolic spectrum similarities of C. cicadae, C. militaris, and C. gunnii were 94.42%, 80.82%, and 91.00%, respectively. Cordyceps sinensis, C. cicadae, and C. gunnii were correlated well for compounds and climate factors. This study will explore whether C. cicadae, C. militaris and C. gunnii can be used as substitutes for C. sinensis. Our results may provide a reference for resource conservation and sustainable utilization of endangered C. sinensis.

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Prediction of the potential geographical distribution of Betula platyphylla Suk. in China under climate change scenarios

Cited by 16 publications

References 73 publications

Predicting Habitat Suitability and Adaptation Strategies of an Endangered Endemic Species, Camellia luteoflora Li ex Chang (Ericales: Theaceae) under Future Climate Change

Predicting Habitat Suitability and Adaptation Strategies of an Endangered Endemic Species, Camellia luteoflora Li ex Chang (Ericales: Theaceae) under Future Climate Change

Impacts of climate change on species distribution patterns of Polyspora sweet in China

Cordyceps cicadae and Cordyceps gunnii have closer species correlation with Cordyceps sinensis: from the perspective of metabonomic and MaxEnt models

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