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. 2023 Jan 31;9(2):189.
doi: 10.3390/jof9020189.

Prediction of the Potential Distributions of Prunus salicina Lindl., Monilinia fructicola, and Their Overlap in China Using MaxEnt

Zhe Zhang  1 , Lin Chen  1 , Xueyan Zhang  1 , Qing Li  1
Affiliations

Prediction of the Potential Distributions of Prunus salicina Lindl., Monilinia fructicola, and Their Overlap in China Using MaxEnt

Zhe Zhang et al. J Fungi (Basel). .

Abstract

Prunus salicina Lindl. (P. salicina) is an essential cash crop in China, and brown rot (BR) is one of its most important diseases. In this study, we collected geographic location information on P. salicina and Monilinia fructicola (G. Winter) Honey (M. fructicola), one of the BR pathogenic species, and applied the MaxEnt model to simulate its potential suitable distribution in China. There have been discussions about the dominant environmental variables restricting its geographical distribution and their overlap. The results showed that the mean temperature of the coldest quarter, precipitation of the warmest quarter, precipitation in July, and minimum temperatures in January and November were the main climatic variables affecting the potential distribution of P. salicina, while the coldest quarter, precipitation of the driest month, precipitation of March, precipitation of October, maximum temperatures of February, October, and November, and minimum temperature of January were related to the location of M. fructicola. Southern China had suitable conditions for both P. salicina and M. fructicola. Notably, the overlap area of P. salicina and M. fructicola was primarily located southeast of 91°48' E 27°38' N to 126°47' E 41°45' N. The potential overlap area predicted by our research provided theoretical evidence for the prevention of BR during plum planting.

Keywords: brown rot; distribution prediction; ecological modelling; environmental variables; pathogenic microorganism.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Species occurrence records of P. salicina and M. fructicola. Notes: The black circles for P. salicina (a) and red triangles for M. fructicola (b) indicate distribution points.
Figure 2
Figure 2
ROC curve and AUC values for the reconstructed model for P. salicina (a) and M. fructicola (b).
Figure 3
Figure 3
The importance of climate variables on the distribution of P. salicina (a) and M. fructicola (b).
Figure 4
Figure 4
Relationship between distribution area of suitable areas and dominant climate variables ((a) mean temperature of coldest quarter; (b) precipitation of warmest quarter; (c) precipitation of July; (d) minimum temperature of January; (e) minimum temperature of November) of P. salicina.
Figure 5
Figure 5
Relationship between distribution area of suitable areas and dominant climate variables ((a) mean temperature of coldest quarter; (b) precipitation of driest month; (c) precipitation of March; (d) precipitation of October; (e) maximum temperature of February; (f) maximum temperature of October; (g) maximum temperature of November; (h) minimum temperature of January) of M. fructicola.
Figure 6
Figure 6
Potential distribution of P. salicina (a) and M. fructicola (b) in China.
Figure 7
Figure 7
Hot spot map of distribution consistency between P. salicina and M. fructicola in China (a) and their percentage of suitable areas (b and c).
Figure 8
Figure 8
The representative figure of the plum fruit with BR (a) and cultured M. fructicola (b).
See this image and copyright information in PMC

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