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Prediction of potential suitable habitats of Malania oleifera under future climate scenarios based on the MaxEnt model
by
Liu, Hailong
, Qin, Zihai
, Li, Mimi
, Wang, Ping
, Zhang, Ye
, Zhang, Xiaoning
in
631/158
/ 631/181
/ Biodiversity
/ China
/ Climate Change
/ Conservation of Natural Resources
/ Distribution records
/ Ecological balance
/ Ecology
/ Ecosystem
/ Habitats
/ Humanities and Social Sciences
/ Karst
/ multidisciplinary
/ Precipitation
/ Radiation
/ Science
/ Science (multidisciplinary)
/ Seasonal variations
/ Seeds
/ Soil temperature
/ Sustainability management
/ Temperature
/ Threatened species
/ Topsoil
/ Variables
/ Wild plants
2025
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Prediction of potential suitable habitats of Malania oleifera under future climate scenarios based on the MaxEnt model
by
Liu, Hailong
, Qin, Zihai
, Li, Mimi
, Wang, Ping
, Zhang, Ye
, Zhang, Xiaoning
in
631/158
/ 631/181
/ Biodiversity
/ China
/ Climate Change
/ Conservation of Natural Resources
/ Distribution records
/ Ecological balance
/ Ecology
/ Ecosystem
/ Habitats
/ Humanities and Social Sciences
/ Karst
/ multidisciplinary
/ Precipitation
/ Radiation
/ Science
/ Science (multidisciplinary)
/ Seasonal variations
/ Seeds
/ Soil temperature
/ Sustainability management
/ Temperature
/ Threatened species
/ Topsoil
/ Variables
/ Wild plants
2025
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Prediction of potential suitable habitats of Malania oleifera under future climate scenarios based on the MaxEnt model
by
Liu, Hailong
, Qin, Zihai
, Li, Mimi
, Wang, Ping
, Zhang, Ye
, Zhang, Xiaoning
in
631/158
/ 631/181
/ Biodiversity
/ China
/ Climate Change
/ Conservation of Natural Resources
/ Distribution records
/ Ecological balance
/ Ecology
/ Ecosystem
/ Habitats
/ Humanities and Social Sciences
/ Karst
/ multidisciplinary
/ Precipitation
/ Radiation
/ Science
/ Science (multidisciplinary)
/ Seasonal variations
/ Seeds
/ Soil temperature
/ Sustainability management
/ Temperature
/ Threatened species
/ Topsoil
/ Variables
/ Wild plants
2025
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Prediction of potential suitable habitats of Malania oleifera under future climate scenarios based on the MaxEnt model
Journal Article
Prediction of potential suitable habitats of Malania oleifera under future climate scenarios based on the MaxEnt model
2025
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Overview
Malania oleifera
is a nationally Category II protected wild plant in China and a Vulnerable species on the IUCN Red List, specifically distributed in the karst forest, playing a crucial role in maintaining biodiversity and ecological balance in karst fragile ecosystems. In this study, the potential suitable habitats for
M. oleifera
were simulated by the MaxEnt model using 126 distribution records and 19 environment variables. The key environmental variables influencing its distribution were identified: topsoil USDA texture classification (t_usda_tex), precipitation of warmest quarter (Bio18), isothermality (Bio03), precipitation of driest quarter (Bio17), precipitation seasonality (Bio15), and temperature annual range (Bio07), which are clay soil, 606–882 mm, 33.1–43.5, 40.7–67.2 mm, 76.9–86.7%, and 20.6–23.1 °C, respectively. Under the future climate scenarios, the total area of suitable habitats for
M. oleifera
is expected to decrease, with a more significant reduction under the SSP585 scenario compared to the SSP126 and SSP245 scenarios. Compared to the current centroid of the suitable habitat, the future centroid is projected to shift southeastward. This study identifies stable habitats of
M. oleifera
in the Guangxi-Yunnan-Guizhou border region, recommending prioritized
in situ
conservation and breeding base development. Environmentally sensitive zones require continuous monitoring and adaptive protection strategies. Climate-adaptive cultivation trials are proposed for expansion areas like Guangdong. These findings offer scientific and practical guidance for sustainable management of this vulnerable species under climate change.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
/ 631/181
/ China
/ Conservation of Natural Resources
/ Ecology
/ Habitats
/ Humanities and Social Sciences
/ Karst
/ Science
/ Seeds
/ Topsoil
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