Predicting the suitable habitats of <i>Elwendia persica</i> in the Indian Himalayan Region (IHR)

Thakur, Sajan; Datt, Ishwari; Singh, Bikarma; Dutt, Harish Chander; Musarella, Carmelo Maria

doi:10.1080/11263504.2023.2204090

Cited by 4 publications

(3 citation statements)

References 43 publications

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“…Given the backdrop of significant global climate change, understanding the spatial distribution of biological populations and their interplay with the environment has become pivotal for unraveling biodiversity patterns and devising strategies for its preservation [ 2 ]. Extensive research demonstrates that climate change profoundly impacts and will continue to influence species distribution patterns [ 3 , 4 ]. Consequently, predicting species’ potential habitats and their migration trends in response to climate change is vital for informing future species management, ecological conservation, and cultivation strategies [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Modeling the Potential Distribution Patterns of the Invasive Plant Species Phytolacca americana in China in Response to Climate Change

Nan,

Li,

et al. 2024

Plants

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Phytolacca americana, introduced to China in the 20th century for its medicinal properties, has posed a significant ecological and agricultural challenge. Its prolific fruit production, high reproductive coefficient, adaptability, and toxic roots and fruits have led to the formation of monoculture communities, reducing native species diversity and posing threats to agriculture, human and animal health, and local ecosystems. Understanding its potential distribution patterns at a regional scale and its response to climate change is essential for effective monitoring, management, and control. In this study, we utilized the Maxent model to simulate potential habitat areas of P. americana across three timeframes (current, 2050s, and 2070s) under three climate change scenarios (SSP126, SSP245, and SSP585). Leveraging data from 556 P. americana sites across China, we employed ROC curves to assess the prediction accuracy. Our findings highlight key environmental factors influencing P. americana’s geographical distribution, including the driest month’s precipitation, the coldest month’s minimum temperature, the wettest month’s precipitation, isothermality, and temperature annual range. Under current climate conditions, P. americana potentially inhabits 280.26 × 104 km2 in China, with a concentration in 27 provinces and cities within the Yangtze River basin and its southern regions. While future climate change scenarios do not drastically alter the total suitable area, the proportions of high and low-suitability areas decrease over time, shifting towards moderate suitability. Specifically, in the SSP126 scenario, the centroid of the predicted suitable area shifts northeastward and then southwestward. In contrast, in the SSP245 and SSP585 scenarios, the centroid shifts northward.

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Section: Introductionmentioning

confidence: 99%

Modeling the Potential Distribution Patterns of the Invasive Plant Species Phytolacca americana in China in Response to Climate Change

Nan,

Li,

et al. 2024

Plants

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“…The short run time, ease of operation, and high accuracy were also important reasons for choosing this model [16]. The MaxEnt model has been used for different species in different countries, for example, Thakur et al [17] predicted suitable distribution areas for Elwendia persica (Boiss.) in the Indian Himalayan region, and Ji et al [18] predicted suitable distribution areas for Daktulosphaira vitifoliae (Fitch) globally.…”

Section: Introductionmentioning

confidence: 99%

Predicting the Distributions of Morus notabilis C. K. Schneid under Climate Change in China

Gao,

Qian,

Deng

et al. 2024

Forests

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As one of the common mulberry tree species, Morus notabilis C. K. Schneid plays a significant role in various industries such as silkworm rearing, papermaking, and medicine due to its valuable mulberry leaves, fruits, and wood. This study utilizes the maximum entropy (MaxEnt) model to predict the potential distribution of M. notabilis in China under future environmental changes. By integrating the relative percentage contribution score of environmental factors with jackknife test analysis, important variables influencing the distribution of M. notabilis were identified along with their optimal values. The results indicate that Annual Precipitation (bio12), Precipitation of Driest Month (bio14), Min Temperature of Coldest Month (bio6), Temperature Annual Range (bio5-bio6) (bio7), Precipitation of Warmest Quarter (bio18), and Precipitation of Coldest Quarter (bio19) are the primary environmental variables affecting its potential distribution. Currently, M. notabilis exhibits high suitability over an area spanning 11,568 km2, while medium suitability covers 34,244 km2. Both current and future suitable areas for M. notabilis are predominantly concentrated in Sichuan, Yunnan, and Guizhou provinces, as well as Chongqing city in southwest China. Under the SSP5-8.5 scenario representing high greenhouse gas concentrations by 2050s and 2090s, there is an increase in high suitability area by 2952 km2 and 3440 km2, with growth rates reaching 25.52% and 29.74%, respectively. Notably, these two scenarios exhibit substantial expansion in suitable habitats for this species compared to others analyzed within this study period.

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“…The development of species distribution models began with the development and application of BIOCLIM models, and over the next 20 years, HABITAT, DOMAIN, ecological niche factor analysis (ENFA), MaxEnt, the generalized linear model (GLM), generalized additive model (GAM), classification and regression tree (CART), boosted regression tree (BRT), artificial neural network (ANN), and other AI-based niche models have emerged [11]. In recent years, species distribution models have been widely used in conservation biology [12] and invasion biology [13]: they provides a lot of scientific basis and theoretical guidance for the protection of endangered animals and plants and the prevention and control of invasive species, biodiversity and ecosystem stability. MaxEnt is the most popular model, which has been proved to be the best model in species distribution modeling [14].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Suitable Habitat of Alien Invasive Plant Ambrosia trifida in Northeast China under Various Climatic Scenarios

Chen,

Bai,

et al. 2024

Diversity

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Ambrosia trifida is an invasive alien plant species, which has very high reproductive and environmental adaptability. Through strong resource acquisition ability and allelopathy, it could inhibit the growth and reproduction of surrounding plants and destroy the stability of an invasive ecosystem. It is very important to predict the change of suitable distribution area of A. trifida with climate change before implementing scientific control measures. Based on 106 A. trifida distribution data and 14 points of environmental data, the optimal parameter combination (RM = 0.1, FC = LQ) was obtained using the MaxEnt (version 3.4.1) model optimized by Kuenm package, and thus the potential suitable areas of A. trifida in Northeast China under three different climate scenarios (RCP2.6, RCP4.5, RCP8.5) with different emission intensities in the future (2050, 2070) were predicted. The changes of A. trifida suitable area in Northeast China under three climate scenarios were compared, and the relationship between the change of suitable area and emission intensity was analyzed. In general, the suitable area of A. trifida in Northeast China will expand gradually in the future, and the area of its highly suitable area will also increase with the increasing emission intensity, which is unfavorable to the control of A. trifida.

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Predicting the suitable habitats of Elwendia persica in the Indian Himalayan Region (IHR)

Cited by 4 publications

References 43 publications

Modeling the Potential Distribution Patterns of the Invasive Plant Species Phytolacca americana in China in Response to Climate Change

Modeling the Potential Distribution Patterns of the Invasive Plant Species Phytolacca americana in China in Response to Climate Change

Predicting the Distributions of Morus notabilis C. K. Schneid under Climate Change in China

Prediction of Suitable Habitat of Alien Invasive Plant Ambrosia trifida in Northeast China under Various Climatic Scenarios

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