A study of the distribution of the parasitic herb Cynomorium songaricum based on the optimized MaxEnt model： Current status assessment and future predictions

doi:10.11686/cyxb2024319

Abstract

Abstract:

Cynomorium songaricum is a nationally protected plant in China， and appears on a list of species accorded “second-class” protection. C. songaricum is esteemed for its high medicinal value， and thrives in ecologically fragile desert regions. In recent years， climate change has posed a significant threat to the geographical distribution of C. songaricum. This study aimed to clarify the main environmental factors affecting the distribution of C. songaricum in China and to emphasize the significance of identifying potential suitable areas for effective protection and management. Based on 166 valid distribution records and 39 natural environmental variables， this study employed the maximum entropy model （MaxEnt） to simulate the potential geographical distribution of C. songaricum along two representative climate change projection pathways （SSP126 and SSP585） for both the current period and future scenarios （2050s and 2070s）. The study explored the most critical environmental factors affecting C. songaricum distribution and predicted the spatial distribution pattern of suitable habitat areas in response to climate change. The knife-cut method was employed to assess the contribution rate of environmental variables to the model， helping to identify the primary factors influencing the distribution of C. songaricum. The model’s prediction results indicated that the currently simulated potential distribution area of C. songaricum closely aligns with its actual distribution. The area under the receiver operating characteristic curve （AUC value） was 0.900， indicating strong predictive performance. The results indicate that precipitation in the wettest month and average temperature during the coldest season are critical variables determining the habitat of C. songaricum. These two criteria are followed in importance by basic soil saturation， altitude， the highest temperature in the warmest month and precipitation in the driest season， in that order. Future climate change is expected to narrow the habitat of C. songaricum and shift its distribution eastward. The predictions of potential suitable habitat areas for C. songaricum in this study can provide guidelines for its protection and management.

Key words: environmental factors, potential fitness zones, center-of-mass changes

Yu-xia AN, Wen-qiang WANG, Dian YU, Yong-liang LIANG, Jun-long YANG, Xiao-wei LI. A study of the distribution of the parasitic herb Cynomorium songaricum based on the optimized MaxEnt model： Current status assessment and future predictions[J]. Acta Prataculturae Sinica, 2025, 34(7): 1-12.

Figures/Tables 10

References 53

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分布概率Distribution probability （P）	评价等级Evaluation level
P<0.2382	非适生区Non-suitable areas
0.2382≤P<0.4000	低适生区Low suitable area
0.4≤P<0.6	中适生区Medium suitable area
0.6≤P≤1.0	高适生区Highly suitable area

分布概率Distribution probability （P）	评价等级Evaluation level
P<0.2382	非适生区Non-suitable areas
0.2382≤P<0.4000	低适生区Low suitable area
0.4≤P<0.6	中适生区Medium suitable area
0.6≤P≤1.0	高适生区Highly suitable area

代码Code	环境因子Environmental factor	贡献率Contribution percent	置换重要性Permutation importance
bio13	最湿月的降水量Precipitation in the wettest month	48.9	54.1
bio11	最冷季的平均气温The average temperature of the coldest season	11.8	21.1
t_bs	基本饱和度Basic saturation	9.1	2.3
elev	海拔Elevation	7.5	3.6
bio05	最暖月的最高温度The highest temperature of the warmest month	7.4	6.2
bio17	最干燥季的降水量Precipitation in the driest season	5.6	3.3
t_caco₃	碳酸盐或石灰含量Carbonate or lime content	2.9	0.9
awc_class	土壤有效水含量Soil available water content	2.7	4.6
slope	坡度Gradient	2.3	1.2
t_oc	有机碳含量Organic carbon content	1.9	2.7

代码Code	环境因子Environmental factor	贡献率Contribution percent	置换重要性Permutation importance
bio13	最湿月的降水量Precipitation in the wettest month	48.9	54.1
bio11	最冷季的平均气温The average temperature of the coldest season	11.8	21.1
t_bs	基本饱和度Basic saturation	9.1	2.3
elev	海拔Elevation	7.5	3.6
bio05	最暖月的最高温度The highest temperature of the warmest month	7.4	6.2
bio17	最干燥季的降水量Precipitation in the driest season	5.6	3.3
t_caco₃	碳酸盐或石灰含量Carbonate or lime content	2.9	0.9
awc_class	土壤有效水含量Soil available water content	2.7	4.6
slope	坡度Gradient	2.3	1.2
t_oc	有机碳含量Organic carbon content	1.9	2.7

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