Mapping the Distribution of Curculio davidi Fairmaire 1878 under Climate Change via Geographical Data and the MaxEnt Model (CMIP6)

Abstract

Curculio davidi is a major pest in chestnut-producing regions in China, and there have been many studies on its occurrence, biological characteristics, and management strategies. However, few of them have focused on the distribution changes of the pest under climate change. In this study, the MaxEnt model (version 3.3.4) and ArcGIS software (version 10.8) were first employed to map the current and future (2050 s and 2080 s) suitable habitat distribution of the weevil under climate change (CMIP 6: SSP1-2.6, SSP2-4.5, and SSP5-8.5). The results indicate that the highly suitable areas for C. davidi are mainly concentrated in Hubei, Henan, Anhui, Jiangxi, Jiangsu, Zhejiang, the coastal areas of Shandong, and eastern Guizhou, northwestern Hunan, and northeastern Sichuan provinces in China. Through the Jackknife test of 19 climate factors, six climate factors affecting the distribution of C. davidi were identified, with precipitation from July (Prec7), precipitation of warmest quarter (Bio18), and temperature seasonality (standard deviation × 100) (Bio4) contributing a combined percentage of 86.3%. Under three different climate scenarios (CMIP 6: SSP1-2.6, SSP2-4.5, and SSP5-8.5), the area of moderately suitable regions is projected to increase by 22.12-27.33% in the 2050 s and by 17.80-38.22% in the 2080 s compared to the current distribution, while the area of highly suitable regions shows a shrinking trend. This study provides data support for the management strategies of C. davidi and offers new insights into the dynamic changes of similar forestry pests.

Keywords: Curculio davidi; MaxEnt model; climate change; potential distribution.

Figure 1

Adult of C. davidi.

Figure 2

Holes in the nutshell of chestnuts. (A): the site of egg laying; (B): Symptoms of C. davidi infestation.

Figure 3

Geographical distribution points of C. davidi and C. mollissima in China. Pink points: C. davidi; green triangle: C. mollissima; dark blue: average annual low temperature; positive red: average annual high temperature.

Figure 4

The accuracy of the MaxEnt model on C. davidi. (A): Curve of omission and predicted area; (B): ROC curve of potential distribution prediction.

Figure 5

Current suitable climatic distribution of C. davidi in China. Red: highly suitable area with a probability of higher than 0.66; orange: moderately suitable area with a probability of 0.33–0.66; yellow: poorly suitable area with a probability ranging from 0.05–0.33; White: unsuitable areas.

Figure 6

Importance of environmental variables to C. davidi via Jackknife test.

Figure 7

Response curves of the environmental variables that contributed most to the MaxEnt models. (A): Precipitation of July (prec 7); (B): Precipitation of Warmest Quarter (bio 18); (C): Mean Temperature of Warmest Quarter (bio 10); (D): Precipitation of May (prec 5); (E): Temperature Seasonality (Standard Deviation of × 100) (bio 4); (F): Precipitation Seasonality (Coefficient of Variation) (bio 15).

Figure 8

Appropriate potential distribution of C. davidi under different climate change scenarios in China. The color level of this area shows the probability of C. davidi, with red indicating that the area is highly suitable for a probability higher than 0.66, orange representing a moderately suitable area with a probability of 0.33–0.66, yellow indicating a poorly suitable area with a probability of 0.05–0.33, and white representing the unsuitable area response curves of the environmental variables that contributed most to the MaxEnt models. (A): SSP1-2.6 (2050S); (B): SSP1-2.6 (2080S); (C): SSP2-4.5 (2050S); (D): SSP2-4.5 (2080S); (E): SSP5-8.5 (2050S); (F): SSP5-8.5 (2080S).

Figure 9

The area changes of suitable habitat for C. davidi under different climate change scenarios. (A): highly suitability area; (B): moderate suitability area; (C): low suitability area.