Predicting the Impact of Climate Change on the Geographical Distribution of Leafhopper, Cicadella viridis in China through the MaxEnt Model
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Species Presence Records
2.2. Environment Variables
2.3. Modeling Process and Statistical Analysis
3. Results
3.1. Model Performance and Variable Selection
3.2. Potential Distribution of C. viridis in the Current Period
3.3. Potential Distribution of C. viridis in the Future Period
3.4. Environmental Variables Affecting the Geographical Distribution of C. viridis
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Variable | Percent Contribution (%) | Permutation Importance (%) |
---|---|---|
Bio6 | 30.9 | 28.2 |
Bio19 | 28.7 | 29.6 |
Bio4 | 21.9 | 19.2 |
Bio1 | 18.5 | 23 |
Variable | Environmental Variables | Unit |
---|---|---|
Bio1 | Mean annual temperature | °C |
Bio4 | Temperature seasonality | °C |
Bio6 | Minimum temperature of the coldest month | °C |
Bio19 | Precipitation of the coldest quarter | °C |
Province | Highly Suitable Area (104 km2) | Total (104 km2) * | Percentage of Highly Suitable Areas in Province (%) | Percentage of Highly Suitable Areas in China (%) |
---|---|---|---|---|
Inner Mongolia | 3.73 | 118.30 | 0.0316 | 0.0039 |
Xinjiang | 11.35 | 166.00 | 0.0684 | 0.0118 |
Jilin | 0.00 | 18.74 | 0.0002 | 0.0000 |
Liaoning | 2.27 | 14.80 | 0.1532 | 0.0024 |
Gansu | 14.58 | 45.37 | 0.3213 | 0.0151 |
Hebei | 12.39 | 18.88 | 0.6561 | 0.0129 |
Beijing | 1.58 | 1.64 | 0.9644 | 0.0016 |
Shanxi | 11.59 | 15.67 | 0.7399 | 0.0120 |
Tianjin | 1.22 | 1.19 | 1.0271 | 0.0013 |
Shaanxi | 17.28 | 15.67 | 1.1028 | 0.0179 |
Ningxia | 4.49 | 6.64 | 0.6761 | 0.0047 |
Qinghai | 1.39 | 72.1 | 0.0193 | 0.0014 |
Shandong | 14.94 | 15.80 | 0.9454 | 0.0155 |
Henan | 10.44 | 16.70 | 0.6250 | 0.0108 |
Jiangsu | 0.69 | 10.72 | 0.0643 | 0.0007 |
Anhui | 0.10 | 14.01 | 0.0069 | 0.0001 |
Sichuan | 3.17 | 48.60 | 0.0652 | 0.0033 |
Hubei | 0.68 | 18.59 | 0.0365 | 0.0007 |
Taiwan | 0.04 | 3.60 | 0.0121 | 0.0000 |
Hainan | 0.38 | 3.54 | 0.1079 | 0.0004 |
China | 112.31 | / | / | 0.1166 |
Decade Scenarios | Predicted Area (km2) | Comparison with Current Distribution (%) | |||||
---|---|---|---|---|---|---|---|
Poorly Suitable Aera | Moderately Suitable Aera | Highly Suitable Aera | Poorly Suitable Aera | Moderately Suitable Area | Highly Suitable Aera | ||
Current | 436.34 | 222.63 | 111.62 | ||||
2050s | RCP2.6 | 500.63 | 202.94 | 105.39 | 0.1473 | −0.0884 | −0.0558 |
RCP4.5 | 496.27 | 193.73 | 101.55 | 0.1373 | −0.1298 | −0.0902 | |
RCP8.5 | 472.88 | 248.64 | 133.14 | 0.0837 | 0.1168 | 0.1928 | |
2090s | RCP2.6 | 509.70 | 197.93 | 104.00 | 0.1681 | −0.1109 | −0.0683 |
RCP4.5 | 505.06 | 198.74 | 102.62 | 0.1575 | −0.1073 | −0.0806 | |
RCP8.5 | 493.97 | 195.13 | 111.20 | 0.1321 | −0.1235 | −0.0038 |
Variable | Suitable Range (°C) | Best Survival Point (°C) |
---|---|---|
Bio1 | 7.18~15.10 | 10.13 |
Bio4 | 869.89~954.27 | 954.27 |
Bio6 | −14.48~−2.20 | −9.62 |
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Wei, X.; Xu, D.; Zhuo, Z. Predicting the Impact of Climate Change on the Geographical Distribution of Leafhopper, Cicadella viridis in China through the MaxEnt Model. Insects 2023, 14, 586. https://doi.org/10.3390/insects14070586
Wei X, Xu D, Zhuo Z. Predicting the Impact of Climate Change on the Geographical Distribution of Leafhopper, Cicadella viridis in China through the MaxEnt Model. Insects. 2023; 14(7):586. https://doi.org/10.3390/insects14070586
Chicago/Turabian StyleWei, Xinju, Danping Xu, and Zhihang Zhuo. 2023. "Predicting the Impact of Climate Change on the Geographical Distribution of Leafhopper, Cicadella viridis in China through the MaxEnt Model" Insects 14, no. 7: 586. https://doi.org/10.3390/insects14070586