Prediction of suitable areas of Eremochloa ophiuroides in China under different climate scenarios based on MaxEnt model
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摘要:目的
本研究通过生态位模型分析评价假俭草在中国的分布情况及制约其当代分布的主要因子，为草坪建植管理和引种栽培提供理论依据。
方法基于262个假俭草的地理分布记录和19个生物气候因子，利用最大熵(MaxEnt)模型和地理信息系统，对该物种当代和未来的适生分布区和面积进行预测，并通过受试者工作特征曲线对模型精度进行验证。
结果影响假俭草适生区分布的主要因子是最干季度降水量（bio17），次要因子是平均日较差（bio2）、温度季节性变化标准差（bio4）和年降水量（bio12）；在当代气候条件下，假俭草总适生区面积约为183.55 × 104 km2，主要集中在我国东南部亚热带地区；在未来气候情景下，假俭草的总适生区面积相较于当代有不同程度的增加，但低、高适生区相较于当代总体而言呈现下降的趋势；通过空间格局变化得出，假俭草适生区保留率为90.14% ~ 94.21%，另外，假俭草质心均位于湖南省湘潭市，推测该地区可能是假俭草的多样性分布中心。
结论本研究得出降水是影响假俭草分布的主要因素，在今后引种栽培以及草坪建植管理时应予以重视。
Abstract:ObjectiveIn this study, the ecological model was used to analyze and evaluate the distribution of Eremochloa ophiuroides in China and the main factors restricting its modern distribution, so as to provide theoretical basis for turf establishment, management, introduction and cultivation.
MethodBased on the geographical distribution records of 262 E. ophiuroides and 19 environmental factors, the maximum entropy (MaxEnt) model and geographic information system were used to predict the current and future suitable distribution area and area of the species, and the accuracy of the model was verified by the receiver operating characteristic curve.
ResultThe main factor affecting the distribution of suitable area of E. ophiuroides was precipitation of the driest quarter (bio17), and the secondary factors were the mean diurnal range (bio2), the standard deviation of seasonal temperature seasonality (bio4) and the annual precipitation (bio12). Under current climatic conditions, the total suitable area of E. ophiuroides was about 1.835 5 million km2, mainly concentrated in the subtropical region of southeast China. Under the future climate scenario, the total suitable area of E. ophiuroides will increase to varying degrees compared with the modern, but the low and high suitable areas will show a downward trend compared with the modern. According to the change of spatial pattern, the retention rate of the suitable area of E. ophiuroides was 90.14%−94.21%. In addition, the centroid of E. ophiuroides was located in Xiangtan City, Hunan Province of central China, suggesting that this area may be the diversity distribution center of E. ophiuroides.
ConclusionIt is concluded that precipitation is the main factor affecting the distribution of E. ophiuroides, which should be paid attention to in the future introduction and cultivation, and turf establishment and management.
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Keywords:
- Eremochloa ophiuroides /
- MaxEnt model /
- suitable area /
- bioclimatic factor
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图 1 假俭草有效分布点
A代表全球物种多样性信息库、中国植物图像库、中国数字植物标本馆和文献记载分布点，B代表野外实地调查分布点。A represents the distribution points of Global Biodiversity Information Facility, Plant Photo Bank of China, Chinese Virtual Herbarium and literature, and B represents the distribution points of field investigation.
Figure 1. Effective distribution points of Eremochloa ophsuroides
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图 3 假俭草生物气候因子刀切法检验结果
Figure 3. Bioclimatic factor test results of E. ophsuroides byJackknife method
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图 6 未来不同气候情景下假俭草在中国的适生分布区
Figure 6. Suitable distribution areas of E. ophsuroides in China under future climate scenarios
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图 7 不同时期假俭草适生区空间变换格局
Figure 7. Spatial transformation pattern of the suitable area of E. ophsuroides in different periods
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图 8 假俭草当代适生区分布及质心转移
Figure 8. Distribution of current suitable area and centroid transfer of E. ophsuroides
表 1 生物气候因子预模拟贡献率和排列重要性
Table 1 Pre-simulation contribution rate and importance of bioclimatic factors
变量编号
Variable No.生物气候因子变量
Bioclimatic factor variable贡献率
Contribution rate/%排列重要性
Permutation importancebio17 最干季度降水量 Precipitation of the driest quarter 78.9 12.6 bio4 温度季节性变化标准差 Standard deviation of the seasonal temperature change 6.6 0.0 bio8 最湿季度平均温度 Mean temperature of the wettest quarter 4.1 14.6 bio3 等温性 Isothermality 3.0 24.2 bio14 最干月降水量 Precipitation of the driest month 2.5 0.0 bio12 年降水量 Annual precipitation 1.9 18.4 bio2 平均日较差 Mean diurnal range 1.3 4.0 bio10 最暖季度平均温度 Mean temperature of the warmest quarter 0.7 1.9 bio13 最湿月降水量 Precipitation of the wettest month 0.4 11.6 bio6 最冷月最低温度 Min. temperature of the coldest month 0.4 2.0 bio11 最冷季度平均温度 Mean temperature of the coldest quarter 0.2 6.8 bio9 最干季度平均温度 Mean temperature of the driest quarter 0.0 2.1 bio1 年平均气温 Annual mean temperature 0.0 0.9 bio5 最暖月最高温度 Max. temperature of the warmest month 0.0 0.8 bio15 降水量变异系数 Coefficient of variation of precipitation 0.0 0.0 bio16 最湿季度降水量 Precipitation of the wettest quarter 0.0 0.0 bio18 最暖季度降水量 Precipitation of the warmest quarter 0.0 0.0 bio19 最冷季度降水量 Precipitation of the coldest quarter 0.0 0.0 bio7 年均温变化范围 Variation range of annual average temperature 0.0 0.0 
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表 2 生物气候因子相关性分析
Table 2 Correlation analysis of bioclimatic variables
变量编号
Variable No.bio2 bio3 bio4 bio6 bio8 bio10 bio11 bio12 bio13 bio14 bio17 bio2 1.00 bio3 0.13 1.00 bio4 0.57** –0.72** 1.00 bio6 –0.65** 0.51** –0.87** 1.00 bio8 0.40** 0.14 0.23 –0.08 1.00 bio10 –0.09 –0.11 0.04 0.43** 0.37** 1.00 bio11 –0.55** 0.59** –0.86** 0.99** –0.01 0.47** 1.00 bio12 –0.50** 0.40** –0.69** 0.81** –0.28* 0.39** 0.81** 1.00 bio13 –0.26* 0.60** –0.67** 0.67** –0.13 0.21 0.70** 0.79** 1.00 bio14 –0.45** –0.25* –0.12 0.43** –0.37** 0.56** 0.40** 0.63** 0.23 1.00 bio17 –0.35** –0.33** 0.014 0.32** –0.35** 0.60** 0.30* 0.58** 0.16 0.96** 1.00 注：*表示在0.05水平上差异显著；**在0.01水平上差异显著。Notes: * means significant difference at the 0.05 level; **means significant difference at 0.01 level.
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表 3 生物气候因子基于MaxEnt模型对假俭草当代时期预测的贡献率
Table 3 Contribution rates of bioclimatic factor based on MaxEnt model to the current period prediction of E. ophsuroides
变量编号
Variable No.贡献率
Contribution rate/%排列重要性
Permutation importancebio2 1.4 15.9 bio3 2.1 6.7 bio4 4.2 9.6 bio8 1.2 7.3 bio10 1.2 3.6 bio12 4.6 21.7 bio13 1.1 15.0 bio17 84.2 20.2
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表 4 不同时期潜在适生分布区预测面积
Table 4 Prediction area of potential suitable distribution area in different periods
104 km2 时期
Period当代
Current2050s 2070s SSPs126 SSPs245 SSPs585 SSPs126 SSPs245 SSPs585 低适生区 Low suitable area 64.85 54.05 42.88 43.66 49.47 49.11 51.44 中适生区 Medium suitable area 92.63 108.89 126.24 122.25 112.14 114.45 110.69 高适生区 High suitable area 26.07 25.81 19.60 23.01 27.74 25.90 25.16 总适生区 Total suitable area 183.55 188.75 188.72 188.92 189.36 189.45 187.29 相比当代增加 Compare with the current increase 5.20 5.17 5.37 5.81 5.90 3.74
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表 5 不同时期假俭草适生区空间变化
Table 5 Spatial variation of suitable area of E. ophsuroides in different periods
时期-气候情景
Period-climate scenario面积 Area / 104 km2 变化 Change/% 增加 Increase 保留 Reserve 丧失 Lost 增加率 Increase rate 保留率 Reserved rate 丧失率 Lost rate 2050s-SSPs126 22.98 106.99 8.54 19.36 90.14 7.19 2050s-SSPs245 29.48 111.32 4.07 24.84 93.78 3.43 2050s-SSPs585 28.38 111.83 3.56 23.91 94.21 3.00 2070s-SSPs126 26.62 108.54 6.94 22.43 91.44 5.84 2070s-SSPs245 26.49 108.85 6.55 22.31 91.70 5.52 2070s-SSPs585 21.22 107.51 7.97 17.88 90.58 6.72
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