Potential distribution of two economic laver species-Neoporphyra haitanensis and Neopyropia yezoensis under climate change based on MaxEnt prediction and phylogeographic profiling

Zhou, Wei; Li, Baoxian; Xu, Hui; Liang, Zhourui; Lü, Xiaoping; Yang, Lintao; Wang, Wenjun

doi:10.1016/j.ecolind.2023.110219

Cited by 10 publications

(9 citation statements)

References 86 publications

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“…The FC parameters included L (Linear), LQ (Quadratic), LQH, H (Fragmentation), LQHP (Product), and LQHPT (Threshold). These parameters were cross-combined to facilitate the evaluation of the MaxEnt’s complexity under different parameter combinations using R 4.2.2 [ 40 , 41 ]. A total of 240 combinations were adjusted using the ENMeval package.…”

Section: Methodsmentioning

confidence: 99%

Prediction of Historical, Current, and Future Configuration of Tibetan Medicinal Herb Gymnadenia orchidis Based on the Optimized MaxEnt in the Qinghai–Tibet Plateau

Li,

Zhang,

Yang

et al. 2024

Plants

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Climate change plays a pivotal role in shaping the shifting patterns of plant distribution, and gaining insights into how medicinal plants in the plateau region adapt to climate change will be instrumental in safeguarding the rich biodiversity of the highlands. Gymnosia orchidis Lindl. (G. orchidis) is a valuable Tibetan medicinal resource with significant medicinal, ecological, and economic value. However, the growth of G. orchidis is severely constrained by stringent natural conditions, leading to a drastic decline in its resources. Therefore, it is crucial to study the suitable habitat areas of G. orchidis to facilitate future artificial cultivation and maintain ecological balance. In this study, we investigated the suitable zones of G. orchidis based on 79 occurrence points in the Qinghai–Tibet Plateau (QTP) and 23 major environmental variables, including climate, topography, and soil type. We employed the Maximum Entropy model (MaxEnt) to simulate and predict the spatial distribution and configuration changes in G. orchidis during different time periods, including the last interglacial (LIG), the Last Glacial Maximum (LGM), the Mid-Holocene (MH), the present, and future scenarios (2041–2060 and 2061–2080) under three different climate scenarios (SSP126, SSP370, and SSP585). Our results indicated that annual precipitation (Bio12, 613–2466 mm) and mean temperature of the coldest quarter (Bio11, −5.8–8.5 °C) were the primary factors influencing the suitable habitat of G. orchidis, with a cumulative contribution of 78.5%. The precipitation and temperature during the driest season had the most significant overall impact. Under current climate conditions, the suitable areas of G. orchidis covered approximately 63.72 × 104/km2, encompassing Yunnan, Gansu, Sichuan, and parts of Xizang provinces, with the highest suitability observed in the Hengduan, Yunlin, and Himalayan mountain regions. In the past, the suitable area of G. orchidis experienced significant changes during the Mid-Holocene, including variations in the total area and centroid migration direction. In future scenarios, the suitable habitat of G. orchidis is projected to expand significantly under SSP370 (30.33–46.19%), followed by SSP585 (1.41–22.3%), while contraction is expected under SSP126. Moreover, the centroids of suitable areas exhibited multidirectional movement, with the most extensive displacement observed under SSP585 (100.38 km2). This study provides a theoretical foundation for the conservation of biodiversity and endangered medicinal plants in the QTP.

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Section: Methodsmentioning

confidence: 99%

Prediction of Historical, Current, and Future Configuration of Tibetan Medicinal Herb Gymnadenia orchidis Based on the Optimized MaxEnt in the Qinghai–Tibet Plateau

Li,

Zhang,

Yang

et al. 2024

Plants

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“…In this study, the optimized MaxEnt was selected to overcome the complexity and limited portability of the default parameter settings in the initial model (Zhou et al 2023b). To determine the optimal parameter combination, the ENMeval package in R 4.2.2 was utilized.…”

Section: Construction Optimization and Evaluation Of Maxentmentioning

confidence: 99%

“…The FC parameters included L (Linear), LQ (Quadratic), LQH, H (Fragmentation), LQHP (Product), and LQHPT (Threshold). These parameters were cross-combined to facilitate the evaluation of MaxEnt's complexity under different parameter combinations using R (Robert et al 2014;Zhou and Li 2023b). A total of 240 combinations were adjusted using the ENMeval package.…”

Section: Construction Optimization and Evaluation Of Maxentmentioning

confidence: 99%

Prediction of historical, current and future configuration of Gymnadenia orchidis 1 based on the optimized MaxEnt in the Qinghai-Tibet Plateau

LI,

Zhang,

Wang

et al. 2024

Preprint

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Gymnosia orchidis (G. orchidis) is a valuable Tibetan medicinal resource with significant medicinal, ecological, and economic value. However, the growth of G. orchidis is severely constrained by stringent natural conditions, leading to a drastic decline in its resources. Therefore, it is crucial to study the suitable habitat areas of G. orchidis to facilitate future artificial cultivation and maintain ecological balance. In this study, we investigated the suitable zones of G. orchidis based on 79 occurrence points in the Qinghai-Tibet Plateau (QTP) and 23 major environmental variables, including climate, topography, and soil type. We employed the Maximum Entropy model (MaxEnt) to simulate and predict the spatial distribution and configuration changes of G. orchidis during different time periods, including the last inter-glacial (LIG), the last glacial Maximum (LGM), the Mid-Holocene (MH), the present, and future scenarios (2041—2060 and 2061—2080) under three different climate scenarios (SSP126, SSP370, and SSP585). Our results indicated that annual precipitation (Bio12, 613—2466 mm) and mean temperature of the coldest quarter (Bio11, -5.8—8.5 °C) were the primary factors influencing the suitable habitat of G. orchidis, with a cumulative contribution of 78.5%. The precipitation and temperature during the driest season had the most significant overall impact. Under current climate conditions, the suitable areas of G. orchidis covered approximately 63.72×104/km², encompassing Yunnan, Gansu, Sichuan, and parts of Xizang provinces, with the highest suitability observed in the Hengduan, Yunlin, and Himalayan mountain regions. In the past, the suitable area of G. orchidis experienced significant changes during the Mid-Holocene, including variations in total area and centroid migration direction. In future scenarios, the suitable habitat of G. orchidis is projected to expand significantly under SSP370 (30.33%—46.19%), followed by SSP585 (1.41%—22.3%), while contraction is expected under SSP126. Moreover, the centroids of suitable areas exhibited multidirectional movement, with the most extensive displacement observed under SSP585 (100.38 km²). This research provides valuable insights for guiding the selection of introduced species, artificial cultivation, and resource conservation in the future, while also offering theoretical support for the protection of endangered species.

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“…The outstanding advantage of the MaxEnt model is its reliable prediction accuracy even with limited sample size and insufficient data (Shi et al, 2023;Zhou et al, 2023). Many studies have demonstrated the reliability of MaxEnt in predicting the potential distribution of fungi (Banasiak et al, 2019;Cogliati et al, 2023;Wei et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Among SDMs, the MaxEnt model based on the principle of maximum entropy, has proven most effective in simulating the geographical distribution of species (Phillips et al, 2006; Phillips & Dudík, 2008; West et al, 2016). The outstanding advantage of the MaxEnt model is its reliable prediction accuracy even with limited sample size and insufficient data (Shi et al, 2023; Zhou et al, 2023). Many studies have demonstrated the reliability of MaxEnt in predicting the potential distribution of fungi (Banasiak et al, 2019; Cogliati et al, 2023; Wei et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Analysis of the distribution pattern of the ectomycorrhizal fungus Cenococcum geophilum under climate change using the optimized MaxEnt model

Zheng,

Yuan,

Matsushita

et al. 2023

Ecology and Evolution

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Cenococcum geophilum (C. geophilum) is a widely distributed ectomycorrhizal fungus that plays a crucial role in forest ecosystems worldwide. However, the specific ecological factors influencing its global distribution and how climate change will affect its range are still relatively unknown. In this study, we used the MaxEnt model optimized with the kuenm package to simulate changes in the distribution pattern of C. geophilum from the Last Glacial Maximum to the future based on 164 global distribution records and 17 environmental variables and investigated the key environmental factors influencing its distribution. We employed the optimal parameter combination of RM = 4 and FC = QPH, resulting in a highly accurate predictive model. Our study clearly shows that the mean temperature of the coldest quarter and annual precipitation are the key environmental factors influencing the suitable habitats of C. geophilum. Currently, appropriate habitats of C. geophilum are mainly distributed in eastern Asia, west‐central Europe, the western seaboard and eastern regions of North America, and southeastern Australia, covering a total area of approximately 36,578,300 km2 globally. During the Last Glacial Maximum and the mid‐Holocene, C. geophilum had a much smaller distribution area, being mainly concentrated in the Qinling‐Huaihe Line region of China and eastern Peninsular Malaysia. As global warming continues, the future suitable habitat for C. geophilum is projected to shift northward, leading to an expected expansion of the suitable area from 9.21% to 21.02%. This study provides a theoretical foundation for global conservation efforts and biogeographic understanding of C. geophilum, offering new insights into its distribution patterns and evolutionary trends.

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Potential distribution of two economic laver species-Neoporphyra haitanensis and Neopyropia yezoensis under climate change based on MaxEnt prediction and phylogeographic profiling

Cited by 10 publications

References 86 publications

Prediction of Historical, Current, and Future Configuration of Tibetan Medicinal Herb Gymnadenia orchidis Based on the Optimized MaxEnt in the Qinghai–Tibet Plateau

Prediction of Historical, Current, and Future Configuration of Tibetan Medicinal Herb Gymnadenia orchidis Based on the Optimized MaxEnt in the Qinghai–Tibet Plateau

Prediction of historical, current and future configuration of Gymnadenia orchidis 1 based on the optimized MaxEnt in the Qinghai-Tibet Plateau

Analysis of the distribution pattern of the ectomycorrhizal fungus Cenococcum geophilum under climate change using the optimized MaxEnt model

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