Predicting current and future distributions of Mentha pulegium in Tunisia under climate change conditions, using the MaxEnt model

Desert locusts are notorious for their widespread distribution and strong destructive power. Their influence extends from the vast arid and semiarid regions of western Africa to northwestern India. Large-scale locust outbreaks can have devastating consequences for food security, and their social impact may be long-lasting. Climate change has increased the uncertainty of desert locust outbreaks, and predicting suitable habitats for this species under climate change scenarios will help humans deal with the potential threat of locust outbreaks. By comprehensively considering climate, soil, and terrain variables, the maximum entropy (MaxEnt) model was used to predict the potential habitats of solitary desert locusts in the 2050s and 2070s under the four shared socioeconomic pathways (SSP126, SSP245, SSP370, and SSP585) in the CMIP6 model. The modeling results show that the average area under the curve (AUC) and true skill statistic (TSS) reached 0.908 ± 0.002 and 0.701, respectively, indicating that the MaxEnt model performed extremely well and provided outstanding prediction results. The prediction results indicate that climate change will have an impact on the distribution of the potential habitat of solitary desert locusts. With the increase in radiative forcing overtime, the suitable areas for desert locusts will continue to contract, especially in the 2070s under the SSP585 scenario, and the moderately and highly suitable areas will decrease by 0.88 × 106 km2 and 1.55 × 106 km2, respectively. Although the potentially suitable area for desert locusts is contracting, the future threat posed by the desert locust to agricultural production and food security cannot be underestimated, given the combination of maintained breeding areas, frequent extreme weather events, pressure from population growth, and volatile sociopolitical environments. In conclusion, methods such as monitoring and early warning, financial support, regional cooperation, and scientific prevention and control of desert locust plagues should be further implemented.

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Predicting the Suitable Geographical Distribution of Sinadoxa Corydalifolia under Different Climate Change Scenarios in the Three-River Region Using the MaxEnt Model

Plants ◽

10.3390/plants9081015 ◽

2020 ◽

Vol 9 (8) ◽

pp. 1015

Author(s):

Xiaotao Huang ◽

Li Ma ◽

Chunbo Chen ◽

Huakun Zhou ◽

Buqing Yao ◽

...

Keyword(s):

Climate Change ◽

Air Temperature ◽

Habitat Destruction ◽

Distribution Model ◽

Distribution Area ◽

Climate Change Scenarios ◽

Maxent Model ◽

Co2 Concentrations ◽

River Region ◽

Temperature Seasonality

Sinadoxa corydalifolia is a perennial grass with considerable academic value as a rare species owing to habitat destruction and a narrow distribution. However, its distribution remains unclear. In this study, we predicted the distribution of Sinadoxa corydalifolia in the three-river region (the source of the Yangtze River, Yellow River, and Lancang River) under the context of climate change using the maximum entropy (MaxEnt) model. Under the current climate scenario, the suitable distribution mainly occurred in Yushu County and Nangqian County. The suitable distribution area of Sinadoxa corydalifolia covered 3107 km2, accounting for 0.57% of the three-river region. The mean diurnal air temperature range (Bio2), temperature seasonality (Bio4), and mean air temperature of the driest quarter (Bio9) contributed the most to the distribution model for Sinadoxa corydalifolia, with a cumulative contribution of 81.4%. The highest suitability occurred when air temperature seasonality (Bio4) ranged from 6500 to 6900. The highest suitable mean air temperature of the driest quarter ranged from −5 to 0 °C. The highest suitable mean diurnal temperature (Bio2) ranged from 8.9 to 9.7 °C. In future (2041–2060) scenarios, the suitable distribution areas of Sinadoxa corydalifolia from high to low are as follows: representative concentration pathway (RCP)26 (6171 km2) > RCP45 (6017 km2) > RCP80 (4238 km2) > RCP60 (2505 km2). In future (2061–2080) scenarios, the suitable distribution areas of Sinadoxa corydalifolia from high to low are as follows: RCP26 (18,299 km2) > RCP60 (11,977 km2) > RCP45 (10,354 km2) > RCP80 (7539 km2). In general, the suitable distribution will increase in the future. The distribution area of Sinadoxa corydalifolia will generally be larger under low CO2 concentrations than under high CO2 concentrations. This study will facilitate the development of appropriate conservation measures for Sinadoxa corydalifolia in the three-river region.

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Predictive Modeling of Suitable Habitats for Cinnamomum Camphora (L.) Presl Using Maxent Model under Climate Change in China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16173185 ◽

2019 ◽

Vol 16 (17) ◽

pp. 3185 ◽

Cited By ~ 3

Author(s):

Zhang ◽

Jing ◽

Li ◽

Liu ◽

Fang

Keyword(s):

Climate Change ◽

Global Climate ◽

Economic Value ◽

Distribution Data ◽

Cinnamomum Camphora ◽

Jackknife Test ◽

Maxent Model ◽

Resource Protection ◽

Suitable Habitats ◽

The Impact

Rapid changes in global climate exert tremendous pressure on forest ecosystems. Cinnamomum camphora (L.) Presl is a multi-functional tree species, and its distribution and growth are also affected by climate warming. In order to realize its economic value and ecological function, it is necessary to explore the impact of climate change on its suitable habitats under different scenarios. In this experiment, 181 geographical distribution data were collected, and the MaxEnt algorithm was used to predict the distribution of suitable habitats. To complete the simulation, we selected two greenhouse gas release scenarios, RCP4.5 and RCP8.5, and also three future time periods, 2025s, 2055s, and 2085s. The importance of environmental variables for modeling was evaluated by jackknife test. Our study found that accumulated temperature played a key role in the distribution of camphor trees. With the change of climate, the area of suitable range will increase and continue to move to the northwest of China. These findings could provide guidance for the plantation establishment and resource protection of camphor in China.

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Assessment of alpine mean response to climate change in Southwest China based on MaxEnt Model

Acta Ecologica Sinica ◽

10.5846/stxb201809262085 ◽

2019 ◽

Vol 39 (24) ◽

Author(s):

熊巧利 XIONG Qiaoli ◽

何云玲 HE Yunling ◽

邓福英 DE Fuying ◽

李同艳 LI Tongyan ◽

余岚 YU Lan

Keyword(s):

Climate Change ◽

Southwest China ◽

Maxent Model

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Prediction of Spatiotemporal Invasive Risk of the Red Import Fire Ant, Solenopsis invicta (Hymenoptera: Formicidae), in China

Insects ◽

10.3390/insects12100874 ◽

2021 ◽

Vol 12 (10) ◽

pp. 874

Author(s):

Jinyue Song ◽

Hua Zhang ◽

Ming Li ◽

Wuhong Han ◽

Yuxin Yin ◽

...

Keyword(s):

Climate Change ◽

Environmental Factors ◽

Solenopsis Invicta ◽

Climatic Conditions ◽

Fire Ant ◽

Invasive Pest ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Maxent Model ◽

Suitable Area

The red imported fire ant, Solenopsis invicta (Hymenoptera: Formicidae), is an invasive pest, and it has spread rapidly all over the world. Predicting the suitable area of S. invicta growth in China will provide a reference that will allow for its invasion to be curbed. In this study, based on the 354 geographical distribution records of S. invicta, combined with 24 environmental factors, the suitable areas of S. invicta growth in China under current (2000s) and future (2030s and 2050s) climate scenarios (SSPs1-2.5s, SSPs2-3.5s and SSPs5-8.5s) were predicted by using the optimized MaxEnt model and geo-detector model. An iterative algorithm and knife-cut test were used to evaluate the important environmental factors that restrict the suitable area under the current climatic conditions. This study also used the response curve to determine the appropriate value of environmental factors to further predict the change and the center of gravity transfer of the suitable area under climate change. The optimized MaxEnt model has high prediction accuracy, and the working curve area (AUC) of the subjects is 0.974. Under climatic conditions, the suitable area is 81.37 × 104 km2 in size and is mainly located in the south and southeast of China. The main environmental factors affecting the suitable area are temperature (Bio1, Bio6, and Bio9), precipitation (Bio12 and Bio14) and NDVI. In future climate change scenarios, the total suitable area will spread to higher latitudes. This distribution will provide an important theoretical basis for relevant departments to rapidly prevent and control the invasion of S. invicta.

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The Distribution and Sustainable Utilization of Buckwheat Resources under Climate Change in China

Plants ◽

10.3390/plants10102081 ◽

2021 ◽

Vol 10 (10) ◽

pp. 2081

Author(s):

Wen Wen ◽

Zhiqiang Li ◽

Jirong Shao ◽

Yu Tang ◽

Zhijun Zhao ◽

...

Keyword(s):

Climate Change ◽

Green Revolution ◽

Morphological Characteristics ◽

Healthy Life ◽

Wild Buckwheat ◽

Maxent Model ◽

Development And Utilization ◽

Sustainable Yield Index ◽

First Time ◽

Cultivation History

Buckwheat is a promising pseudo cereal and its cultivation history can be traced back to thousands of years ago in China. Nowadays, buckwheat is not only an ordinary crop but also a symbol of healthy life because of its rich nutritional and pharmacological properties. In this research, the current suitable areas of 19 wild buckwheat species were analyzed by the MaxEnt model, which proved that southwestern China was the diversity center of buckwheat. Their morphological characteristics and geographical distribution were analyzed for the first time. In addition, it was found that the change of buckwheat cultivation in three periods might be related to the green revolution of main crops and national policies. Meanwhile, the Sustainable Yield Index (SYI) value of buckwheat in China was the lowest from 1959 to 2016. Through the MaxEnt model, the potentially suitable areas of wild buckwheat would contract while cultivated buckwheat would expand under climate change. Accordingly, the diversity of wild buckwheat will decrease. Therefore, it is necessary to protect buckwheat resources as much as possible to strengthen the development and utilization of buckwheat resources. Moreover, the promotion of buckwheat diversity will be an important trade-off between food security, population growth, and land use under climate change.

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Predicting the Potential Distribution of Hylomecon japonica in China under Current and Future Climate Change Based on Maxent Model

Sustainability ◽

10.3390/su132011253 ◽

2021 ◽

Vol 13 (20) ◽

pp. 11253

Author(s):

Zhen Cao ◽

Lei Zhang ◽

Xinxin Zhang ◽

Zengjun Guo

Keyword(s):

Climate Change ◽

Potential Distribution ◽

Characteristic Curve ◽

Future Climate Change ◽

Mean Annual Temperature ◽

Suitable Habitat ◽

Entropy Model ◽

Factors Affecting ◽

Jackknife Test ◽

Maxent Model

Hylomecon japonica is considered a natural medicinal plant with anti-inflammatory, anticancer and antibacterial activity. The assessment of climate change impact on its habitat suitability is important for the wild cultivation and standardized planting of H. japonica. In this study, the maximum entropy model (Maxent) and geographic information system (ArcGIS) were applied to predict the current and future distribution of H. japonica species, and the contributions of variables were evaluated by using the jackknife test. The area under the receiver operating characteristic curve (AUC) value confirmed the accuracy of the model prediction based on 102 occurrence records. The predicted potential distributions of H. japonica were mainly concentrated in Jilin, Liaoning, Shaanxi, Chongqing, Henan, Heilongjiang and other provinces (adaptability index > 0.6). The jackknife experiment showed that the precipitation of driest month (40.5%), mean annual temperature (12.4%), the precipitation of wettest quarter (11.6%) and the subclass of soil (9.7%) were the most important factors affecting the potential distribution of H. japonica. In the future, only under the shared socioeconomic Pathway 245 (SSP 245) scenario model in 2061–2080, the suitable habitat area for H. japonica is expected to show a significant upward trend. The area under other scenarios may not increase or decrease significantly.

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Range Shift in Response to Climate Change of Chinese Caterpillar Fungus Based on Species Redundancy

10.22541/au.163299108.87031097/v1 ◽

2021 ◽

Author(s):

Jian Chen ◽

Yuan Feng ◽

Wu Kui ◽

Dai Dong ◽

Wang Dong ◽

...

Keyword(s):

Climate Change ◽

Distribution Pattern ◽

Host Plants ◽

Climatic Conditions ◽

Range Shift ◽

Distribution Area ◽

Maxent Model ◽

Pattern Similarity ◽

Caterpillar Fungus ◽

Suitable Area

The presence of the Chinese caterpillar fungus (CCF) depends on the distribution of its host insects and host plants. However, its distribution pattern in response to climate change and interspecific relationships in geographical distribution is unknown. We used the MaxEnt model to obtain areas suitable for the CCF, considering its host insects and host plants under different historical climate backgrounds. We then superimposed and analyzed them to explore the range shift in response to climate change of Chinese caterpillar fungus based on species redundancy. From the Last Glacial Maximum (LGM) to 2050, the suitable distribution pattern of the CCF is estimated to change from fragmentized to concentrated and connected. The high redundancy area (HRA) continued to increase from the Middle Holocene (MH) to the present and 2050, with an increased area of 31.46×104 km2. The suitable area moved to the northwest and the total movement distance of its average coordinates was about 500 km. The altitude of the suitable area increased continuously from the LGM to the present and to 2050, and the average altitude of HRA increased from 2740.89 m (LGM) to 4246.76 m (2050). The distribution pattern and changes of CCF under different climatic conditions provides a reference for the current and future geographical regional planning for conservation and sustainable utilization. The distribution pattern similarity of the CCF suitable area, suitable area for host insects, and host plants HRA of distribution area, might be the result of their long-term co-evolution. The decreasing trend of CCF yield under human disturbance was not as severe as expected, suggesting that climate change may be beneficial to distribution expansion of the CCF.

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Assessing the Impacts of Climate Change on Distribution of Major Non-Timber Forest Plants in Chitwan Annapurna Landscape, Nepal

Resources ◽

10.3390/resources7040066 ◽

2018 ◽

Vol 7 (4) ◽

pp. 66 ◽

Cited By ~ 3

Author(s):

Vishwas Chitale ◽

Ramesh Silwal ◽

Mir Matin

Keyword(s):

Climate Change ◽

Forest Products ◽

Ecological Significance ◽

Maxent Model ◽

Planning And Management ◽

Non Timber Forest Products ◽

Forest Plants ◽

Effective Conservation ◽

Anthropogenic Drivers ◽

Impacts Of Climate Change

For many decades, non-timber forest products (NTFPs) have been an important livelihood commodity in Nepal as a traditional source of food, fiber, and medicines. However, the importance of NTFPs have been recognized only recently. NTFPs form more than 5% of Nepal’s national gross domestic product and are facing threat due to anthropogenic drivers and changing climate. Understanding of the current distribution and future dynamics of NTFPs is essential for effective conservation planning and management. In the maiden attempt, we used the Maxent model to understand the current and predict the future distribution by 2050 of 10 major NTFPs in Chitwan Annapurna Landscape, Nepal. The prediction accuracy of the models calculated based on the area under curve was high (>90%) and the prediction by 2050 highlights potential increase in distribution range of seven NTFPs and potential decrease in that of three NTFPs in the study area. The results from our study could play an important role in planning and management of these NTFPs considering their high economic and ecological significance and sensitivity to predicted climate change.

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Throwing light on dark diversity of vascular plants in China: predicting the distribution of dark and threatened species under global climate change

PeerJ ◽

10.7717/peerj.6731 ◽

2019 ◽

Vol 7 ◽

pp. e6731 ◽

Cited By ~ 3

Author(s):

Lili Tang ◽

Runxi Wang ◽

Kate S. He ◽

Cong Shi ◽

Tong Yang ◽

...

Keyword(s):

Climate Change ◽

Species Distribution ◽

Global Climate Change ◽

Vascular Plants ◽

Global Climate ◽

Ex Situ ◽

Climate Change Scenarios ◽

Distribution Models ◽

Maxent Model ◽

Maxent Modeling

Background As global climate change accelerates, ecologists and conservationists are increasingly investigating changes in biodiversity and predicting species distribution based on species observed at sites, but rarely consider those plant species that could potentially inhabit but are absent from these areas (i.e., the dark diversity and its distribution). Here, we estimated the dark diversity of vascular plants in China and picked up threatened dark species from the result, and applied maximum entropy (MaxEnt) model to project current and future distributions of those dark species in their potential regions (those regions that have these dark species). Methods We used the Beals probability index to estimate dark diversity in China based on available species distribution information and explored which environmental variables had significant impacts on dark diversity by incorporating bioclimatic data into the random forest (RF) model. We collected occurrence data of threatened dark species (Eucommia ulmoides, Liriodendron chinense, Phoebe bournei, Fagus longipetiolata, Amentotaxus argotaenia, and Cathaya argyrophylla) and related bioclimatic information that can be used to predict their distributions. In addition, we used MaxEnt modeling to project their distributions in suitable areas under future (2050 and 2070) climate change scenarios. Results We found that every study region’s dark diversity was lower than its observed species richness. In these areas, their numbers of dark species are ranging from 0 to 215, with a generally increasing trend from western regions to the east. RF results showed that temperature variables had a more significant effect on dark diversity than those associated with precipitation. The results of MaxEnt modeling showed that most threatened dark species were climatically suitable in their potential regions from current to 2070. Discussions The results of this study provide the first ever dark diversity patterns concentrated in China, even though it was estimated at the provincial scale. A combination of dark diversity and MaxEnt modeling is an effective way to shed light on the species that make up the dark diversity, such as projecting the distribution of specific dark species under global climate change. Besides, the combination of dark diversity and species distribution models (SDMs) may also be of value for ex situ conservation, ecological restoration, and species invasion prevention in the future.

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