Suitable distribution simulation and local environmental adaptability differentiation of Lycium ruthenicum in Xinjiang, China

doi:10.17521/cjpe.2021.0179

Abstract

Abstract:

Aims Lycium ruthenicum is a very important medicinal and edible species that plays an essential role in wind prevention and sand fixation in the arid desert areas. However, it is currently facing a serious situation of fragmented distribution.
Methods In this study, 19 environmental variables of L. ruthenicum were collected from 87 natural distribution points distributed in Xinjiang under current climate (1971-2000). The GIS spatial analysis and R software Biomod2 modeling platform were employed to simulate and analyze the suitable distribution, spatial distribution characteristics, and key limiting factors of L. ruthenicum in Xinjiang, and evaluate the distribution potential by combining the current land use/land cover situation in the study area. The distribution of L. ruthenicum in southern and northern Xinjiang was modeled by subspecies grouping to analyze the niche differentiation of this species.
Important findings The results showed that: (1) The true skill statistic (TSS) and area under the curve of receiver operator characteristic curves (AUC) of the ensemble model were obviously improved compared with those of individual models. The TSS and AUC of the ensemble models were uniformly greater than 0.75 and 0.85, respectively. The simulation accuracy of the subspecies grouping modeling was significantly improved compared with the species-level simulation, and the TSS and AUC were higher than 0.78 and 0.88. (2) According to the simulation results obtained by the ensemble model, the proportion of the suitable distribution area of L. ruthenicum in Xinjiang accounts for about 36.72% of the total area of the province, and it was mainly distributed in the Junggar Basin, the northern slope of the Tianshan Mountain and the northwest and southwest margins of the Tarim Basin. Among them, the area of highly suitable distribution accounted for 5.19%, which was concentrated in the Fuhai County, the eastern of the Tacheng Region, and the line from Bole to Fukang on the northern slope of the Tianshan Mountains, Korla, Keping County, and the southwest margin of the Tarim Basin. The overlap between highly and moderately suitable areas and the cultivated land in the study area amounted to 80.6% and 50.8%. (3) There was a significant niche differentiation of L. ruthenicum populations in northern and southern Xinjiang, and mean temperature of warmest quarter, isothermality, and precipitation seasonality were the main factors causing the local environmental adaptation differentiation of L. ruthenicum in Xinjiang.

Key words: Lycium ruthenicum, suitable for distribution, niche differentiation, driving factor, subspecies grouping simulation

YAN Han, ZHANG Yun-Ling, MA Song-Mei, WANG Chun-Cheng, ZHANG Dan. Suitable distribution simulation and local environmental adaptability differentiation of Lycium ruthenicum in Xinjiang, China[J]. Chin J Plant Ecol, 2021, 45(11): 1221-1230.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2021.0179

https://www.plant-ecology.com/EN/Y2021/V45/I11/1221

Figures/Tables 7

Fig. 1 Suitable distribution of Lycium ruthenicum in Xinjiang by the species-level simulation (A) and grouping simulation (B) and its superposition with land use/land cover (LUCC)(C). I, most suitable; II, moderate suitable; a, the cultivated land; b, land for industrial, mining and residents in urban and rural areas; c, the grassland; d, woodland; e, waters; f-k are unused land (f, sandy land; g, gobi; h, saline and alkaline land; i, marshland; j, bare land; k, bare rock and rocky ground).

Table 1 Evaluation indices of each model (mean ± SD)

模拟方式 Simulation method	评估指标 Evaluation index	随机森林 RF	广义线性模型GLM	柔性判别分析FDA	最大熵模型 MaxEnt	广义相加模型GAM	组合模型 Ensemble Model
北疆种群模拟 Simulation of populations in northern Xinjiang	TSS	0.774 ± 0.057	0.793 ± 0.069	0.753 ± 0.065	0.801 ± 0.054	0.756 ± 0.052	0.792 ± 0.042
北疆种群模拟 Simulation of populations in northern Xinjiang	AUC	0.929 ± 0.020	0.909 ± 0.046	0.873 ± 0.046	0.911 ± 0.053	0.818 ± 0.065	0.888 ± 0.021
南疆种群模拟 Simulation of populations in southern Xinjiang	TSS	0.782 ± 0.055	0.762 ± 0.061	0.753 ± 0.064	0.760 ± 0.068	0.753 ± 0.069	0.782 ± 0.049
南疆种群模拟 Simulation of populations in southern Xinjiang	AUC	0.895 ± 0.045	0.907 ± 0.040	0.901 ± 0.054	0.905 ± 0.041	0.895 ± 0.046	0.905 ± 0.046
物种模拟 Simulation of species	TSS	0.766 ± 0.064	0.759 ± 0.084	0.762 ± 0.038	0.751 ± 0.060	0.754 ± 0.081	0.773 ± 0.055
物种模拟 Simulation of species	AUC	0.834 ± 0.031	0.823 ± 0.052	0.781 ± 0.031	0.775 ± 0.043	0.761 ± 0.044	0.853 ± 0.059

Table 2 Proportion of the suitable distribution area of Lycium ruthenicum in Xinjiang simulated by each model (%)

模拟方式 Simulation method	适生等级 Suitable grade
模拟方式 Simulation method	高度适生区面积比例 Proportion of most suitable areas	中度适生区面积比例 Proportion of moderate suitable areas	低度适生区面积比例 Proportion of low suitable areas
北疆种群模拟 Simulation of populations in northern Xinjiang	2.50	4.33	8.42
南疆种群模拟 Simulation of populations in southern Xinjiang	3.91	3.47	7.75
物种模拟 Simulation of species	5.19	9.06	22.47

Table 3 Contribution rate and range of threshold of each environmental factor to the suitable distribution of Lycium ruthenicum by each model

环境变量 Environmental variable	贡献率 Contribution rate (%)			数值范围 Range of threshold
环境变量 Environmental variable	北疆种群 Northern population	南疆种群 Southern population	全部种群 Whole populations	数值范围 Range of threshold
等温性 Isothermality	23.4	5.4	15.0	(12, 40)
气温年较差 Temperature annual range (℃)	14.4	21.2	14.4	(33, 63)
最暖季平均气温 Mean temperature of warmest quarter (℃)	5.4	7.5	9.3	(-9, 31)
最冷季平均气温 Mean temperature of coldest quarter (℃)	9.3	49.0	26.8	(-33, -1)
最湿月降水量 Precipitation of wettest month (mm)	26.4	9.0	10.9	(3, 96)
最干月降水量 Precipitation of driest month (mm)	40.3	7.1	17.2	(0, 15)
降水季节性 Precipitation seasonality	6.6	0.8	6.3	(22, 140)

Fig. 2 Value ranges of mean temperature of coldest quarter (Bio11), precipitation of driest month (Bio14), isothermality (Bio03) and temperature annual range (Bio07) were extracted based on the most and moderate suitable areas of Lycium ruthenicum in Xinjiang, China.

Fig. 3 Niche similarity analysis (A), equivalence test (B) and correlation circle of contribution rates of environmental factors (C) of Lycium ruthenicum in southern and northern Xinjiang, China. In figure A, green and red represent niche spaces of different populations, and blue represent overlapping spaces. In figure C, red to blue indicates that the contribution rate rank of climate variables varies. Bio03, isothermality; Bio07, temperature annual range; Bio10, mean temperature of warmest quarter; Bio11, mean temperature of coldest quarter; Bio13, precipitation of wettest month; Bio14, precipitation of driest month; Bio15, precipitation seasonality.

Fig. 4 Kernel density plots of environmental factors of niche differentiation of Lycium ruthenicum in southern and northern Xinjiang, China. Bio03, isothermality; Bio07, temperature annual range; Bio10, mean temperature of warmest quarter; Bio11, mean temperature of coldest quarter ; Bio13, precipitation of wettest month; Bio14, precipitation of driest month; Bio15, precipitation seasonality.

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