Mapping the Distribution of Curculio davidi Fairmaire 1878 under Climate Change via Geographical Data and the MaxEnt Model (CMIP6)
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Species Distribution Data
2.2. Environmental Variables
2.3. Modelling Process
2.4. Classification of Suitable Grades
3. Results
3.1. Model Result Verification
3.2. Current Distribution Forecast
3.3. Environmental Variable Analysis
3.4. Future Distribution Forecast
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Variable | Percent Contribution (%) | Permutation Importance (%) |
---|---|---|
Precipitation from July (Prec7) | 42.3 | 25.3 |
Precipitation of warmest quarter (Bio18) | 22.3 | 3.4 |
Temperature seasonality (standard deviation × 100) (Bio4) | 21.7 | 28.3 |
Precipitation Seasonality (Coefficient of Variation) (Bio15) | 7.2 | 8.2 |
Mean Temperature of Warmest Quarter (Bio10) | 4.1 | 28.9 |
Precipitation from May (Prec5) | 2.4 | 5.8 |
Province | High Suitable Area (km2) | Percentage of High Suitable Areas in Province (%) | Percentage of High Suitable Areas in China (%) |
---|---|---|---|
Gansu | 68 | 0.02 | 0.10 |
Hebei | 72 | 0.04 | 0.11 |
Shanxi | 183 | 0.12 | 0.28 |
Yunnan | 208 | 0.05 | 0.32 |
Shanghai | 265 | 4.18 | 0.41 |
Guangxi | 271 | 0.11 | 0.42 |
Liaoning | 341 | 0.23 | 0.52 |
Guangdong | 358 | 0.20 | 0.55 |
Fujian | 899 | 0.74 | 1.38 |
Shanxi | 1881 | 0.91 | 2.88 |
Zhejiang | 3150 | 3.09 | 4.83 |
Shandong | 3255 | 2.06 | 4.99 |
Chongqing | 3650 | 4.43 | 5.59 |
Hunan | 4887 | 2.31 | 7.49 |
Guizhou | 5031 | 2.86 | 7.71 |
Jiangsu | 5107 | 4.76 | 7.83 |
Jiangxi | 5506 | 3.30 | 8.44 |
Anhui | 6918 | 4.94 | 10.60 |
Sichuan | 7256 | 1.49 | 11.12 |
Henan | 7519 | 4.50 | 11.52 |
Hubei | 8426 | 4.53 | 12.91 |
China | 65,251 | - | 0.68 |
Environmental Variables | Suitable Range | Optimum Value |
---|---|---|
Prec7/mm | 107.22~324.13 | 103.13 |
Bio18/mm | 305.02~1498.07 | 490.35 |
Bio10/°C | 20.55~29.90; 29.90~39.95 | 23.58 |
Prec5/mm | 44.08~299.32 | 55.15 |
Bio4/°C | 674.2~1301.02 | 798.1 |
Bio15/mm | 45.68~250.36 | 58.63 |
Predicted Area (km2) | Comparison with Current Distribution (%) | ||||||
---|---|---|---|---|---|---|---|
Decade | Scenarios | Poor Suitable Area | Moderate Suitable Area | High Suitable Area | Poor Suitable Area | Moderate Suitable Area | High Suitable Area |
current | 103,894 | 53,050 | 65,251 | ||||
2050 s | SSP1-2.6 | 102,064 | 64,784 | 56,843 | −1.76 | 22.12 | −12.89 |
SSP2-4.5 | 111,728 | 67,547 | 56,868 | 7.54 | 27.33 | −12.85 | |
SSP5-8.5 | 111,812 | 65,076 | 54,977 | 7.62 | 22.67 | −15.75 | |
2080 s | SSP1-2.6 | 97,362 | 62,492 | 55,799 | −6.29 | 17.80 | −14.49 |
SSP2-4.5 | 102,121 | 73,324 | 45,859 | −1.71 | 38.22 | −29.72 | |
SSP5-8.5 | 119,996 | 64,867 | 47,705 | 15.5 | 22.28 | −26.89 |
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Wu, J.; Wei, X.; Wang, Z.; Peng, Y.; Liu, B.; Zhuo, Z. Mapping the Distribution of Curculio davidi Fairmaire 1878 under Climate Change via Geographical Data and the MaxEnt Model (CMIP6). Insects 2024, 15, 583. https://doi.org/10.3390/insects15080583
Wu J, Wei X, Wang Z, Peng Y, Liu B, Zhuo Z. Mapping the Distribution of Curculio davidi Fairmaire 1878 under Climate Change via Geographical Data and the MaxEnt Model (CMIP6). Insects. 2024; 15(8):583. https://doi.org/10.3390/insects15080583
Chicago/Turabian StyleWu, Junhao, Xinju Wei, Zhuoyuan Wang, Yaqin Peng, Biyu Liu, and Zhihang Zhuo. 2024. "Mapping the Distribution of Curculio davidi Fairmaire 1878 under Climate Change via Geographical Data and the MaxEnt Model (CMIP6)" Insects 15, no. 8: 583. https://doi.org/10.3390/insects15080583