基于4种生态位模型的橘小实蝇在四川盆地潜在分布区

doi:10.11924/j.issn.1000-6850.casb2023-0202

中国农学通报 ›› 2024, Vol. 40 ›› Issue (5): 80-87.doi: 10.11924/j.issn.1000-6850.casb2023-0202

• 资源·环境·生态·土壤·气象 • 上一篇下一篇

基于4种生态位模型的橘小实蝇在四川盆地潜在分布区

张欣¹(), 冯晓¹, 裴玥², 王茹琳³, 赵金鹏³()

¹ 四川省气象灾害防御技术中心，成都 610072
² 宜宾市人工影响天气中心，四川宜宾 644108
³ 四川省农村经济综合信息中心，成都 610072

收稿日期:2023-03-14 修回日期:2023-08-22 出版日期:2024-02-01 发布日期:2024-02-01
通讯作者:
赵金鹏，男，1988年出生，副高，硕士，主要从事应用气象与气象服务方面的工作。通信地址：610072 四川省成都市光华村街20号，Tel：028-87362165，E-mail：421508153@qq.com。
作者简介:
张欣，男，1980年出生，工程师，本科，主要从事应用气象与气象服务方面的工作。通信地址：610072 四川省成都市光华村街20号，Tel：028-87396730，E-mail：Justin1230@qq.com。
基金资助:
四川省科技厅自然科学基金项目(2022NSFSC0589)

Potential Distribution of Bactrocera dorsalis Hendel in Sichuan Basin Based on Four Niche Models

ZHANG Xin¹(), FENG Xiao¹, PEI Yue², WANG Rulin³, ZHAO Jinpeng³()

¹ Sichuan Meteorological Disaster Prevention Technology Center, Chengdu 610072
² Yibin Weather Modification Center, Yibin, Sichuan 644108
³ Sichuan Provincial Rural Economic Information Center, Chengdu 610072

Received:2023-03-14 Revised:2023-08-22 Published-:2024-02-01 Online:2024-02-01

摘要/Abstract

摘要：

研究旨为橘小实蝇在四川盆地的检疫检测、综合防治及风险分析提供科学决策参考。运用基于最大熵(Maxent)、遗传算法(Garp)、环境包络原理(Bioclim)和Gower距离算法(Domain)的4种生态位预测模型预测橘小实蝇在四川盆地潜在适生区，并采用受试者工作特征曲线(ROC)和Kappa统计量分析方法检验模型预测效果。结果表明，4种模型的ROC曲线下的面积AUC(area under the ROC curve)平均值均大于0.9，Kappa统计量平均值亦大于0.75，预测模型具有较高的预测精度。通过“刀切法”分析得出最干季降水量、最干季平均温度、温度季节性变化和温度日较差是主导橘小实蝇潜在分布的关键环境变量，对当前橘小实蝇分布格局的形成起决定性作用。4种模型预测橘小实蝇适生面积和位置相差较大，但均包含川中丘陵区、川东平行岭谷区和盆边南部低山区，且川中丘陵区东部、川东平行岭谷区和盆边南部低山区的西部均为高、中适生区集中区域。由此可见，橘小实蝇在四川盆地适生范围较广，鉴于柑橘对四川盆地经济的重要性，当地相关部门应加强对其的检测检疫工作，避免造成较大的损失。

关键词: 橘小实蝇, 生态位模型, 潜在适生区, 四川盆地

Abstract:

The purpose of this study is to provide scientific reference for the quarantine detection, comprehensive control and risk analysis of Bactrocera dorsalis Hendel in Sichuan Basin. Four niche prediction models, i.e. Maxent, GARP, Bioclim and Domain were used to predict the areas of potential distribution of B. dorsalis in Sichuan Basin. The results of different models were analyzed and compared using two statistical criteria: the area under the receiver operating characteristic curve (AUC) and Kappa value. The AUC average values of the four models are all above 0.9 and the Kappa average values are above 0.75, indicating that the prediction model has high prediction accuracy. Furthermore, the paper shows that precipitation of the driest month, mean temperature of the wettest quarter, temperature seasonality and mean diurnal range are the key environmental variables that dominated the potential distribution of B. dorsalis, which play a decisive role in the formation of the current distribution of B. dorsalis. The suitable areas and locations of B. dorsalis predicted by four models are quite different, but they all contain the hilly area in central Sichuan Basin, the parallel rank-valley area in eastern Sichuan Basin and the low mountain area in southern Sichuan Basin. The highly and moderately suitable areas are concentrated in the east of the hilly area in central Sichuan Basin, the west of the parallel rank-valley area in eastern Sichuan Basin and the low mountain area in southern Sichuan Basin. It can be seen that the suitable areas of B. dorsalis in Sichuan Basin is wide. In view of the economic importance of citrus to Sichuan Basin, the local relevant departments should strengthen the detection and quarantine work of B. dorsalis to avoid large losses.

Key words: Bactrocera dorsalis Hendel, Niche models, potential suitable habitat, Sichuan Basin

张欣, 冯晓, 裴玥, 王茹琳, 赵金鹏. 基于4种生态位模型的橘小实蝇在四川盆地潜在分布区[J]. 中国农学通报, 2024, 40(5): 80-87.

ZHANG Xin, FENG Xiao, PEI Yue, WANG Rulin, ZHAO Jinpeng. Potential Distribution of Bactrocera dorsalis Hendel in Sichuan Basin Based on Four Niche Models[J]. Chinese Agricultural Science Bulletin, 2024, 40(5): 80-87.

图/表 7

参考文献 38

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编码	含义	单位	编码	含义	单位
Bio2	温度日较差	℃	Bio10	最暖季平均温度	℃
Bio3	等温性(Bio2/Bio7)(×100)	/	Bio12	年降水量	mm
Bio4	温度季节性变化（标准差×100）	/	Bio13	最湿月降水量	mm
Bio5	最暖月最高温度	℃	Bio14	最干月降水量	mm
Bio6	最冷月最低温度	℃	Bio14	最干月降水量	mm
Bio9	最干季平均温度	℃	Alt	海拔	m

编码	含义	单位	编码	含义	单位
Bio2	温度日较差	℃	Bio10	最暖季平均温度	℃
Bio3	等温性(Bio2/Bio7)(×100)	/	Bio12	年降水量	mm
Bio4	温度季节性变化（标准差×100）	/	Bio13	最湿月降水量	mm
Bio5	最暖月最高温度	℃	Bio14	最干月降水量	mm
Bio6	最冷月最低温度	℃	Bio14	最干月降水量	mm
Bio9	最干季平均温度	℃	Alt	海拔	m

组别	受试者工作特征曲线下的面积							一致性检验统计量
组别	Maxent		Garp	Bioclim		Domain		Maxent		Garp	Bioclim		Domain
1	0.985		0.925	0.922		0.966		0.754		0.815	0.801		0.831
2	0.981		0.923	0.944		0.955		0.720		0.794	0.796		0.821
3	0.984		0.911	0.956		0.947		0.760		0.790	0.810		0.830
4	0.977		0.907	0.968		0.934		0.751		0.768	0.821		0.856
5	0.989		0.911	0.978		0.927		0.732		0.816	0.810		0.832
6	0.992		0.928	0.964		0.947		0.744		0.827	0.814		0.801
7		0.997	0.906		0.922		0.942		0.715	0.779		0.783		0.792
8		0.981	0.913		0.937		0.927		0.806	0.792		0.788		0.827
9		0.976	0.918		0.958		0.937		0.769	0.811		0.814		0.831
10		0.988	0.922		0.949		0.945		0.774	0.785		0.792		0.828
均值		0.985	0.916		0.950		0.943		0.753	0.798		0.803		0.825

组别	受试者工作特征曲线下的面积							一致性检验统计量
组别	Maxent		Garp	Bioclim		Domain		Maxent		Garp	Bioclim		Domain
1	0.985		0.925	0.922		0.966		0.754		0.815	0.801		0.831
2	0.981		0.923	0.944		0.955		0.720		0.794	0.796		0.821
3	0.984		0.911	0.956		0.947		0.760		0.790	0.810		0.830
4	0.977		0.907	0.968		0.934		0.751		0.768	0.821		0.856
5	0.989		0.911	0.978		0.927		0.732		0.816	0.810		0.832
6	0.992		0.928	0.964		0.947		0.744		0.827	0.814		0.801
7		0.997	0.906		0.922		0.942		0.715	0.779		0.783		0.792
8		0.981	0.913		0.937		0.927		0.806	0.792		0.788		0.827
9		0.976	0.918		0.958		0.937		0.769	0.811		0.814		0.831
10		0.988	0.922		0.949		0.945		0.774	0.785		0.792		0.828
均值		0.985	0.916		0.950		0.943		0.753	0.798		0.803		0.825

区域	模型类别	高适生区面积	中适生区面积	低适生区面积	不适生区面积
盆周低山	Maxent	451.39	14548.61	54149.31	11093.75
	Garp	22604.17	1701.39	22135.42	33802.08
	Bioclim	1805.56	5833.33	14982.64	57621.53
	Domain	10868.06	27847.22	34392.36	7135.42
成都平原	Maxent	0	7656.25	16215.28	607.64
	Garp	5763.89	781.25	14097.22	3836.81
	Bioclim	0	0	225.69	24253.47
	Domain	312.5	2829.86	20763.89	572.92
川中丘陵	Maxent	12777.78	52291.67	9166.67	0
	Garp	49322.92	5399.31	19479.17	34.72
	Bioclim	4027.78	13784.72	27777.78	28645.83
	Domain	24878.47	34635.42	14704.86	17.36
川东平行岭谷	Maxent	12986.11	35052.08	19618.06	0
	Garp	51736.11	260.42	15069.44	590.28
	Bioclim	6684.03	24461.82	18645.83	17864.58
	Domain	41475.7	16076.39	9704.86	399.31

基于4种生态位模型的橘小实蝇在四川盆地潜在分布区

Potential Distribution of Bactrocera dorsalis Hendel in Sichuan Basin Based on Four Niche Models

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编码	贡献率/%	置换重要性/%
bio14	58.57	3.64
bio9	25.43	42.92
bio4	5.73	26.05
Bio2	1.78	15.7

编码	贡献率/%	置换重要性/%
bio14	58.57	3.64
bio9	25.43	42.92
bio4	5.73	26.05
Bio2	1.78	15.7