Modeling habitat suitability of Houttuynia cordata Thunb (Ceercao) using MaxEnt under climate change in China

Liu, Lei; Guan, Lingliang; Hong-yan, Zhao; Huang, Yi; Mou, Qiuyu; Chen, Tingting; Wang, Xuying; Zhang, Ying; Wei, Bo; Hu, Jinyao

doi:10.1016/j.ecoinf.2021.101324

Cited by 80 publications

(51 citation statements)

References 38 publications

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“…The MaxEnt model was used according to the distribution characteristics of C. mairei H. Lév because the MaxEnt model had a more accurate prediction ability when there were fewer species distribution points [13,33]. There are also some other studies on the prediction of Chinese medicinal plants using the MaxEnt model [34,35], but this model does not take into account human factors, biological factors, or other variables [36] and only takes into account the climate and geographical factors that are the most important for plant growth and distribution. Therefore, considering the development and utilization of medicinal plants by human beings, the actual distribution will decrease to a certain extent.…”

Section: Discussionmentioning

confidence: 99%

The Prediction of the Potentially Suitable Distribution Area of Cinnamomum mairei H. Lév in China Based on the MaxEnt Model

Luo

Chen

et al. 2022

Sustainability

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Cinnamomum mairei H. Lév is a rare and valuable medicinal and timber species in China. It not only has a narrow distribution, but also has few resources, is an endangered species, and is a nationally protected plant. Climate change impacts the growth and development of plants; therefore, it is of great practical significance to predict the current and future distribution of C. mairei H. Lév in suitable areas of China and to protect these endangered plants. In this study, the MaxEnt model was used to predict the suitable growing areas for C. mairei H. Lév according to six environmental factors (the temperature seasonality, max. temperature in the warmest month, min. temperature in the coldest month, precipitation seasonality, precipitation in the coldest quarter and aspect), and three different climate models (SSP126, SSP245, and SSP585) were simulated for three periods (the 2030s, 2050s, and 2070s). In the present study, the suitable ecological environment for C. mairei H. Lév comprised the following: a min. temperature in the coldest month from −0.63 to 4.36 °C, temperature seasonality from 130.67 to 642.58, a max. temperature in the warmest month from 28.86 to 45.97 °C, and precipitation in the coldest quarter from 40.12 to 101.13 mm. Highly suitable habitats for C. mairei H. Lév are located in the Yunnan Province, Guizhou Province, Sichuan Province, and Chongqing City, China (southwestern part of China), and to a lesser extent in the Xizang Province and Shaanxi Province, China. The moderately suitable habitat district overlaps with the highly suitable habitat district, and a small number of suitable habitats are distributed in Guangxi Province, Hunan Province, Hubei Province, and Henan Province. In the future, the highly suitable areas for C. mairei H. Lév will increase slightly, and the gravity points will shift toward northeast China. Our simulations are helpful for understanding the geoecological characteristics of this species and provide a basis for regional projections of this species under current and future climate change scenarios in China. It is proposed to establish nature reserves for C. mairei H. Lév in the Chongqing, Yunnan, Sichuan and Guizhou provinces of China.

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Section: Discussionmentioning

confidence: 99%

The Prediction of the Potentially Suitable Distribution Area of Cinnamomum mairei H. Lév in China Based on the MaxEnt Model

Luo

Chen

et al. 2022

Sustainability

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“…The MaxEnt model is one of the most widely used species distribution models. Many studies have confirmed that MaxEnt is reliable in modeling the potential distribution of species [108,109]. However, the MaxEnt model is greatly dependent on the field observation data.…”

Section: Limitations Of the Current Studymentioning

confidence: 99%

Differential Impacts of Climatic and Land Use Changes on Habitat Suitability and Protected Area Adequacy Across the Asian Elephant’s Range

Yang¹,

Ma²,

Jing³

et al. 2022

Preprint

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The reduction of biodiversity loss is one of the targets of the 2030 Agenda for Sustainable Development. The protection of endangered species is critical for conserving global biodiversity. Asian elephants，as one of the last few mega-herbivores on Earth, are currently threatened by climate changes and anthropogenic modifications. The modelling of their living habitats is of top priority to the conservation of Asian elephant. In this study, we used the maximum entropy model (MaxEnt) to identify the current and potential future habitats of Asian elephants in South and Southeast Asia. We performed analyses for future projections with 17 scenarios by using the present results as baseline. To optimise the modelling results, we delineated the core habitats by using the Core Mapper Tool and compared them with existing protected areas (PAs) through gap analysis. The results showed that the current total area of core habitats is 491,455 km2 in size and will be reduced to 332,544 km2 by 2090 under SSP585 (the shared socioeconomic pathway). The projection analysis under differential scenarios suggested that most of the core habitats in the current protected areas would remain stable and suitable for elephants in the future. However, the remaining 75.17% of the core habitats lay outside the current PAs, and finally we mapped approximately 219,545 km2 of suitable habitats as priority protected areas in the future. Although our model did not perform well in some regions, our analyses and findings still could provide useful references to the planning of protected areas and conservation of Asian elephant.

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“…El rango de distribución del Lycalopex culpaeus (Molina, 1782) se determinó mediante la aplicación de MaxEnt, un software que en este análisis mostró una excelente capacidad predictiva, y que en general ha creado un nuevo dinamismo a la disciplina biogeográfica [47], pues es ampliamente utilizado para crear modelos de distribución de especies [98][99][100] y el software ArcGIS. De esta forma el conjunto de datos de entrenamiento y el modelo optimizado reflejaron un AUC de 0,98 y 0,985 respectivamente, lo que indica que ambos modelos se desempeñaron bien y generaron evaluaciones excelentes [101],…”

Section: Rango De Distribución Potencial De La Especieunclassified

Potential Distribution Range of Lycalopex culpaeus Species (Molina, 1782) in the Province of Chimborazo

Asqui

Rodríguez

Arma

et al. 2022

espoch

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Species distribution models are very useful for understanding and conserving the patterns and processes that explain biodiversity. The present study determined the potential distribution range of Lycalopex culpaeus (Molina, 1782) species in Chimborazo, Ecuador. A documentary research was conducted that included geographic and bibliographic information and the application of the MaxEnt software for data collection, estimation, and validation of the model. The results showed that the potential distribution range of the L. culpaeus species (Molina, 1782) modeled in the MaxEnt and filtered through the Jackknife test has a high predictive capacity, as indicated by the area under the curve (AUC) that reflects a value of 0.985 for which 28 occurrence sites and four environmental variables were used. The key environmental variables that shape the potential distribution of L. culpaeus (Molina, 1782) are temperature, precipitation, land use, and ecosystems. Therefore, in the province of Chimborazo, the habitat suitability for the L. culpaeus (Molina, 1782) species with a probability of >50% (0.49–0.99 points) corresponds to 34,255 hectares of its territory and is mainly found in the “paramo” grassland ecosystem in altitudes ranging from 2781 to 3345 masl. Keywords: Biodiversity, Fauna, Habitat, MaxEnt. Resumen Los modelos de distribución de especies son de gran utilidad para entender y conservar los patrones y los procesos que explican la biodiversidad. En tal sentido el presente estudio determinó el rango de distribución potencial de la especie Lycalopex culpaeus (Molina, 1782) en la provincia de Chimborazo. Este proceso se llevó a cabo a través de métodos de investigación documental que incluye información geográfica y bibliográfica y la aplicación del software MaxEnt a través del cual se desarrolló la obtención de datos, la estimación y validación del modelo. Los resultados reflejan que el rango de distribución potencial de la especie Lycalopex culpaeus (Molina, 1782) modelado en MaxEnt y filtrado a través de la prueba de Jackknife posee una alta capacidad predictiva, tal como lo indica el área bajo la curva (AUC) que refleja un valor de 0,985, para el cual se utilizó 28 sitios de ocurrencia y cuatro variables ambientales. Las variables ambientales clave que dan forma a la distribución potencial de Lycalopex culpaeus (Molina, 1782) son temperatura, precipitación, uso de suelo y ecosistemas, por tanto en la provincia de Chimborazo la idoneidad de hábitat para la especie Lycalopex culpaeus (Molina, 1782) con probabilidad mayor al 50 % (0,49-0,99 puntos) corresponde a 34.255 hectáreas de territorio para su distribución, y se encuentra principalmente en el ecosistema herbazal de páramo, en rangos altitudinales que varían de los 2781 a los 3345 msnm. Palabras Clave: Biodiversidad, Fauna, Hábitat, MaxEnt.

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Modeling habitat suitability of Houttuynia cordata Thunb (Ceercao) using MaxEnt under climate change in China

Cited by 80 publications

References 38 publications

The Prediction of the Potentially Suitable Distribution Area of Cinnamomum mairei H. Lév in China Based on the MaxEnt Model

The Prediction of the Potentially Suitable Distribution Area of Cinnamomum mairei H. Lév in China Based on the MaxEnt Model

Differential Impacts of Climatic and Land Use Changes on Habitat Suitability and Protected Area Adequacy Across the Asian Elephant’s Range

Potential Distribution Range of Lycalopex culpaeus Species (Molina, 1782) in the Province of Chimborazo

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