Prediction of Potential Suitable Distribution Areas for Populus euphratica Using the MaxEnt Model

被引：0
|
作者：
Guo F. [1 ]
Xu G. [1 ]
Lu M. [1 ,2 ]
Meng Y. [1 ]
Yuan C. [1 ]
Guo K. [1 ]
机构：
[1] The Laboratory of Forest Genetics, Central South University of Forestry and Technology, Changsha
[2] Zhejiang A & F University, Hangzhou
来源：
Linye Kexue/Scientia Silvae Sinicae | 2020年 / 56卷 / 05期
关键词：
Environmental variable; MaxEnt; Populus euphratica; Suitable distribution;
D O I：
10.11707/j.1001-7488.20200521
中图分类号：
学科分类号：
摘要：
Objective: Populus euphratica is an important tree species in arid areas, the species is of great significance for maintaining the ecological environment stability in arid areas. The paper tries to identify the dominant environmental variables that limit the distribution of P. euphratica, and to predict its suitable distribution area, in order to provide a theoretical basis for the protection and restoration of the species. Method: The geographical information of 226 existing occurrences of P. euphratica and four types of environmental variables, including climate, topography, soil and hydrology were analyzed using the MaxEnt ecological niche modeling to simulate the potential suitable distribution areas for the species. Evaluation of credibility of the MaxEnt model, comparison of the accuracies of simulation using single climate variable and four types of environmental variables, and identification of the environmental variables limiting the distribution of the species were carried out with combination of method of the receiver-operating characteristic curve (ROC), the jack knife, the percent contribution of the environment variables and the permutation importance for the analyses. Result: 1) The area under the receiver-operating characteristic curve (AUC) showed that the training data of the single climate variable and four types of environmental variables was 0.983±0.002 and 0.982±0.001, respectively. The test data was 0.980±0.006 and 0.967±0.009, respectively. It indicated that two different quantitative data sets had less influence on AUC value and the simulation performed well with a very high credibility. 2) The percent contribution, permutation importance and jack knife showed that the simulation with the four types of environmental variables could identify more effective environmental variables affecting the distribution of P. euphratica. The geographical distribution of the species was affected by precipitation of the driest month and the warmest quarter, the soil moisture content (10-40 cm underground), the soil moisture around root system and the evapotranspiration of soil water. 3) The simulated potential suitable area based on climate variable expanded by 4.33 times compared to that on the four types of environmental variables. The simulation based on the four types of environmental variables reflects more details of distribution such that along riverbank. 4) The suitable distribution area simulated by the MaxEnt model was much larger than the actual distribution area, implying great potential for development of plantations of P. euphratica. Conclusion: The distribution of P. euphratica is affected by many environment variables. There is large deviation between the simulated distribution area using only climate variable and the actual distribution range of this species. The simulation based on four types of environmental variables reflects more characteristics of the actual distribution. This study provides a theoretical basis for the protection and restoration of the degraded P. euphratica forest. © 2020, Editorial Department of Scientia Silvae Sinicae. All right reserved.
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页码：184 / 192
页数：8
相关论文
共 40 条
  • [1] Chen X M, Lei Y C, Zhang X Q, Et al., Effects of sample sizes on accuracy and stability of Maximum Entropy model in predicting species distribution, Scientia Silvae Sinicae, 48, 1, pp. 53-59, (2012)
  • [2] Li X, Li Y, Fang Y M., Prediction of potential suitable distribution areas of Quercus fabri in China based on an optimized MaxEnt model, Scientia Silvae Sinicae, 54, 8, pp. 153-164, (2018)
  • [3] Liu C, Huo H L, Tian L M, Et al., Potential geographical distribution of Pyrus calleryana under different climate change scenarios based on the MaxEnt model, Chinese Journal of Applied Ecology, 29, 11, pp. 3696-3704, (2018)
  • [4] Liu H X, Guan W K, Zayida S, Et al., Changes of wetland area before and after ecological water supplement project in the national nature reserve of Populus euphratica in Tarim, Scientia Silvae Sinicae, 54, 9, pp. 1-8, (2018)
  • [5] Tang S P, Mu L G, Wang X L, Et al., Habitat suitability assessment based on MaxEnt modeling of Chinese goral in Saihanwula National Nature Reserve, Inner Mongolia of northern China, Journal of Beijing Forestry University, 41, 1, pp. 102-108, (2019)
  • [6] Wang R L, Li Q, Feng C H, Et al., Predicting potential ecological distribution of Locusta migratoria tibetensis in China using MaxEnt ecological niche modeling, Acta Ecologica Sinica, 37, 24, pp. 8556-8566, (2017)
  • [7] Wang S J., The status, conservation and recovery of global resources of Populus euphratica, World Forestry Research, 6, pp. 38-45, (1996)
  • [8] Zhang N, Li B F, Xu T T, Et al., Spatiotemporal variations of drought index in Populus euphratica global distribution area during the past 50 years (1960-2012), Journal of Arid Land Resources and Environment, 31, 7, pp. 121-126, (2017)
  • [9] Zhang X Q., Geographical distribution and climatic suitability of typical eco-economical tree species in the dryland of northwest China, (2018)
  • [10] Zhao J Q, Shi J., Prediction of the potential geographical distribution of Obolodiplosis robiniae (Diptera: Cecidomyiidae) in China based on a novel Maximum Entropy model, Scientia Silvae Sinicae, 55, 2, pp. 118-127, (2019)
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