Prediction of potentially suitable areas for the introduction of Magnolia wufengensis under climate change

Shi, Xiaodeng; Yin, Qun; Sang, Ziyang; Zhu, Zhonglong; Jia, Zhongkui; Li, Ma

doi:10.1016/j.ecolind.2021.107762

Cited by 39 publications

(29 citation statements)

References 43 publications

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“…AUC is a threshold-independent metric that is often used to evaluate the performance of MaxEnt models. The performance of the model was evaluated using the following criteria: fair (0.7 < AUC < 0.8), good (0.8 < AUC < 0.9), and excellent (0.9 < AUC < 1) ( Jimenez-Valverde, 2012 ; Shi et al, 2021 ). The CBI is also often used to evaluate the transferability and performance of presence–absence models; it is a reliable measure of presence-only-based predictions ( Hirzel et al, 2006 ).…”

Section: Methodsmentioning

confidence: 99%

Predicting the distribution of suitable habitat of the poisonous weed Astragalus variabilis in China under current and future climate conditions

Huang

Du²,

Wen³

et al. 2022

Front. Plant Sci.

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Astragalus variabilis is a locoweed of northwest China that can seriously impede livestock development. However, it also plays various ecological roles, such as wind protection and sand fixation. Here, we used an optimized MaxEnt model to predict the distribution of suitable habitat of A. variabilis under current (1970–2000) conditions and future (2021–2080) climate change scenarios based on recent occurrence records. The most important environmental variables (suitability ranges in parentheses) affecting the distribution of A. variabilis were average maximum temperature of February (–2.12–5.34°C), followed by total precipitation of June (2.06–37.33 mm), and topsoil organic carbon (0.36–0.69%). The habitat suitability of A. variabilis was significantly correlated with the frequency of livestock poisoning (p < 0.05). Under current climate conditions, the suitable environment of A. variabilis was distributed in central and western Inner Mongolia, Ningxia, central and northwestern Gansu, central and northwestern Qinghai, and the four basins around the Tianshan Mountains in Xinjiang. Under future climate conditions, the suitable habitat of A. variabilis shifted to higher latitudes and altitudes. No previous studies have used niche models to predict the suitable environment of this species nor analyzed the relationship between the habitat suitability of poisonous plants and the frequency of animal poisoning. Our findings provide new insights that will aid the prevention of livestock animal poisoning and the control of poisonous plants, promote the development of the livestock husbandry industry, and provide basic information that will facilitate the maintenance of the ecological balance of grassland ecosystems.

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Section: Methodsmentioning

confidence: 99%

Predicting the distribution of suitable habitat of the poisonous weed Astragalus variabilis in China under current and future climate conditions

Huang

Du²,

Wen³

et al. 2022

Front. Plant Sci.

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“…In order to make the probability of occurrence close to a normal distribution, 75% of the data were selected for model training, the remaining data were used for model testing and other values were the default values [18][19][20][21]. The EMNeval [41,47] package in R (Cran) version 3.6.1 [48] was used to optimize the MaxEnt model and the regularization multiplier (RM) was set to 0.5-4, with intervals of 0.5 each and a total of 8 regulated frequency multipliers. The MaxEnt model provides five features, which are linear features (L), quadratic features (Q), hinge features (H), product features (P) and threshold features (T).…”

Section: Model Building Optimization and Evaluationmentioning

confidence: 99%

Prediction of Suitable Distribution of a Critically Endangered Plant Glyptostrobus pensilis

Zhang

Yang

et al. 2022

Forests

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Glyptostrobus pensilis is a critically endangered living fossil plant species of the Mesozoic era, with high scientific research and economic value. The aim of this study was to assess the impact of climate change on the potential habitat area of G. pensilis in East Asia. The MaxEnt (maximum entropy) model optimized by the ENMeval data package was used to simulate the potential distribution habitats of G. pensilis since the last interglacial period (LIG, 120–140 ka). The results showed that the optimized MaxEnt model has a high prediction accuracy with the area under the receiver operating characteristic curve (AUC) of 0.9843 ± 0.005. The current highly suitable habitats were found in the northeast of Jiangxi, the east of Fujian; the main climatic factors affecting the geographic distribution of G. pensilis are temperature and precipitation, with precipitation as the dominant factor. The minimum temperature of coldest month (Bio6) may be the key factor restricting the northward distribution of G. pensilis; during the LIG, it contracted greatly in the highly suitable habitat area. In the 2070s, the suitable distribution area will move northward and the area of highly suitable habitat will increase. Seasonal changes in temperature and precipitation may be important climatic factors causing the changes in geographic distribution. The results will provide a theoretical basis for the management and resource protection of G. pensilis.

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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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Prediction of potentially suitable areas for the introduction of Magnolia wufengensis under climate change

Cited by 39 publications

References 43 publications

Predicting the distribution of suitable habitat of the poisonous weed Astragalus variabilis in China under current and future climate conditions

Predicting the distribution of suitable habitat of the poisonous weed Astragalus variabilis in China under current and future climate conditions

Prediction of Suitable Distribution of a Critically Endangered Plant Glyptostrobus pensilis

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

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