Assessment of suitable cultivation region for Panax notoginseng under different climatic conditions using MaxEnt model and high-performance liquid chromatography in China

Zhan, Peng; Wang, Feiyang; Xia, Pengguo; Zhao, Guanghua; Wei, Meitang; Wei, Fang; Han, Ruilian

doi:10.1016/j.indcrop.2021.114416

Cited by 46 publications

(40 citation statements)

References 64 publications

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“…At present, many studies and observations have shown that climate change has affected and changed the distribution pattern of the species, and many species have migrated to high latitude or high altitude areas to find more suitable habitats (Parmesan and Yohe, 2003;Walther et al, 2005). As with our results, Zhan et al (2022) studied the effect of climate change on the distribution pattern of Panax Notoginseng in China and found that its suitable habitat would increase to high altitude. Guo et al (2021) found that moderate warming would expand the suitable habitat of Ophiocordyceps sinensis and expand the area of O. sinensis with high adenosine content.…”

Section: Discussionsupporting

confidence: 77%

“…The 127 distribution points of C. appendiculata were imported into MaxEnt model software; three quarters of the samples were chosen for model training, with the remaining samples being used for verification (Zhang et al, 2020). The maximum iteration number was set to 10,000, and the operation was repeated 10 times (Zhan et al, 2022). The area under the receiver operating characteristic curve (AUC) was utilized to assess the model prediction accuracy.…”

Section: Model Parameter Optimization and Model Buildingmentioning

confidence: 99%

“…The MaxEnt model has provided accurate predictions, even when there are few species distribution records to work with (Kumar and Stohlgren, 2009). The MaxEnt model has been widely used in the field of species distribution research and to study the suitable distribution of Chinese Ziziphus jujube (Zhao et al, 2021a), Semiliquidambar cathayensis (Ye et al, 2020), and Panax notoginseng (Zhan et al, 2022). Recent studies have demonstrated the utility of the MaxEnt model for simulating the possible distribution of species, and the complexity is often high, which is not conducive to model transfer.…”

Section: Introductionmentioning

confidence: 99%

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Simulation of the Potential Suitable Distribution of the Endangered Cremastra appendiculata in China Under Global Climate Change

Ouyang

Chen

Strachan

et al. 2022

Front. Environ. Sci.

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Predicting the spatial distribution of species in relation to suitable areas under global climate change could provide some references for conservation and long-term management strategies for the species. In this study, the MaxEnt was optimized by adjusting the feature combination and regulation magnification parameters with the ENMeval data package. Based on 127 Cremastra appendiculata spatial distribution locations and 14 environmental factors, the potential distribution areas of C. appendiculata under the present and future climate conditions (2050s, 2070s) were simulated, and the dominant environmental factors influencing the spatial distribution of C. appendiculata were analyzed. The feature combination (FC) and the regularization multiplier (RM) were selected as per the Akaike information criterion (AIC). The model showed complexity and degree of over-fitting (delta AICc = 0, omission rate = 0.106, the difference in the curve values between the training and testing areas was 0.021) after establishing the optimal model (FC = LQH and RM = 2.5), and the results indicated that the optimal model performed well in simulating the potential spatial distribution of C. appendiculata (the area under the receiver operating characteristic curve = 0.933). The results showed that the suitable habitat of C. appendiculata currently in China is 187.60 × 104 km2, while the highly suitable habitat is 118.47 × 104 km2, the moderately suitable habitat is 53.25 × 10 4 km2, and the poorly suitable habitat is 15.88 × 104 km2. There is an increasing trend in the suitable habitat of C. appendiculata under six climate scenarios, including SSP1-2.6, SSP2-4.5, and SSP5-8.5 in the 2050s and the 2070s, and that habitat will extend to the northwest as a whole. The highly suitable habitat of C. appendiculata in nature reserves is 0.47 × 104 km2; consequently, there is a large gap in the protection of C. appendiculata. The distribution of C. appendiculata was influenced by the temperature, precipitation, and normalized vegetation index.

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Section: Discussionsupporting

confidence: 77%

Section: Model Parameter Optimization and Model Buildingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Simulation of the Potential Suitable Distribution of the Endangered Cremastra appendiculata in China Under Global Climate Change

Ouyang

Chen

Strachan

et al. 2022

Front. Environ. Sci.

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show abstract

“…The human footprint (HF) index data were obtained from: (1) built environments; (2) population density; (3) electric infra-structure; (4) croplands; (5) pasture lands; (6) roads; (7) railways; and (8) navigable waterways [30]. Among them, we eliminated independent variables with a variance inflation factor (VIF) less than 10, for the climatic variables, and the soil&HF variables [31]. We used ClimateAP software (Available online: http://ClimateAP.net/default.aspx, accessed on 18 November 2021) to obtain 16 climate predictors (Table 1).…”

Section: Data Collectionmentioning

confidence: 99%

Predicting Potential Habitat of a Plant Species with Small Populations under Climate Change: Ostryarehderiana

Feng

Sun

El‐Kassaby

et al. 2022

Forests

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Ostrya rehderiana is a famous plant species with extremely small populations. With ongoing global climate change, the extremely small populations would face more uncertainties and risks, including the loss of genetic diversity and extirpation. Thus, assessing the impact of climate change on suitable habitat of O. rehderiana is particularly important for its conservation and restoration. Here, we built niche models with climate variables and soil and human footprint variables. Furthermore, new methods were applied to avoid confounding effects between climate and soil and human footprint variables to simulate the potential habitats of O. rehderiana in current and future climates. We found that the Hargreaves climatic moisture deficit, degree-days below 0 °C, chilling degree-days, and the temperature difference between mean warmest month temperature and mean coldest month temperature, or continentality, were the most important climate factors. The topsoil USDA texture classification, topsoil cation exchange capacity of (clay), and topsoil sodicity (ESP) were the key soil factors determining the suitable distribution of O. rehderiana. Compared with soil factors, human footprint has less influence on the suitable distribution of O. rehderiana. The niche range of this species was projected to expand and shift to north in the Representative Concentration Pathway (RCP) 4.5 scenario for the 2050s. Our study results could be referenced in further extremely small populations ecological restoration studies and provide the scientific strategies for the conservation and restoration of O. rehderiana.

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“…Climatic factors are considered to be the main environmental drivers of species distribution at the macro-scale, and this has been established in extensive studies of the dispersal distribution of invasive species [41][42][43]. However, there are still many important factors that need to be considered when predicting the potential range of invasive alien species, such as topography, soil type, land use/cover change, and human activity.…”

Section: Introductionmentioning

confidence: 99%

Mapping the Distribution and Dispersal Risks of the Alien Invasive Plant Ageratina adenophora in China

et al. 2022

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Identifying the distribution dynamics of invasive alien species can help in the early detection of and rapid response to these invasive species in newly invaded sites. Ageratina adenophora, a worldwide invasive plant, has spread rapidly since its invasion in China in the 1940s, causing serious damage to the local socioeconomic and ecological environment. To better control the spread of this invasive plant, we used the MaxEnt model and ArcGIS based on field survey data and online databases to simulate and predict the spatial and temporal distribution patterns and risk areas for the spread of this species in China, and thus examined the key factors responsible for this weed’s spread. The results showed that the risk areas for the invasion of A. adenophora in the current period were 18.394° N–33.653° N and 91.099° E–121.756° E, mainly in the tropical and subtropical regions of China, and densely distributed along rivers and well-developed roads. The high-risk areas are mainly located in the basins of the Lancang, Jinsha, Yalong, and Anning Rivers. With global climate change, the trend of continued invasion of A. adenophora is more evident, with further expansion of the dispersal zone towards the northeast and coastal areas in all climatic scenarios, and a slight contraction in the Yunnan–Guizhou plateau. Temperature, precipitation, altitude, and human activity are key factors in shaping the distribution pattern of A. adenophora. This weed prefers to grow in warm and precipitation-rich environments such as plains, hills, and mountains; in addition, increasing human activities provide more opportunities for its invasion, and well-developed water systems and roads can facilitate its spread. Measures should be taken to prevent its spread into these risk areas.

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Assessment of suitable cultivation region for Panax notoginseng under different climatic conditions using MaxEnt model and high-performance liquid chromatography in China

Cited by 46 publications

References 64 publications

Simulation of the Potential Suitable Distribution of the Endangered Cremastra appendiculata in China Under Global Climate Change

Simulation of the Potential Suitable Distribution of the Endangered Cremastra appendiculata in China Under Global Climate Change

Predicting Potential Habitat of a Plant Species with Small Populations under Climate Change: Ostryarehderiana

Mapping the Distribution and Dispersal Risks of the Alien Invasive Plant Ageratina adenophora in China

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