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. 2024 Nov 13;14(11):e70520.
doi: 10.1002/ece3.70520. eCollection 2024 Nov.

Spatial Distribution Pattern of Aromia bungii Within China and Its Potential Distribution Under Climate Change and Human Activity

Liang Zhang  1 , Ping Wang  1   2 , Guanglin Xie  1   2 , Wenkai Wang  1   2
Affiliations

Spatial Distribution Pattern of Aromia bungii Within China and Its Potential Distribution Under Climate Change and Human Activity

Liang Zhang et al. Ecol Evol. .

Abstract

Aromia bungii is a pest that interferes with the health of forests and hinders the development of the fruit tree industry, and its spread is influenced by changes in abiotic factors and human activities. Therefore, exploring their spatial distribution patterns and potential distribution areas under such conditions is crucial for maintaining forest ecosystem security. This study analyzed the spatial differentiation characteristics of the geographic distribution pattern of A. bungii in China using Moran's I and the Getis-Ord General G index. Hot spot distribution areas were identified using Getis-Ord Gi*. An optimized MaxEnt model was used to predict the potential distribution areas of A. bungii within China under four shared economic pathways by combining multivariate environmental data: (1) prediction of natural environmental variables predicted under current climate models; (2) prediction of natural environmental variables + human activities under current climate models; and (3) prediction of natural environmental variables under the future climate models (2050s and 2070s). Meanwhile, MigClim was used to simulate the unoccupied suitable area in the presence of obstacles under future climate change. The results showed that human activities, minimum temperature of the coldest month, and precipitation of the wettest month had positive effects on the distribution of A. bungii. However, in the current period, human activities drastically reduced the survival area of A. bungii, and its suitable distribution area was mainly concentrated in the eastern and central regions of China. Under the influence of climate change in the future, the habitat of A. bungii will gradually increase. Additionally, the MigClim model indicates that the area unoccupied by A. bungii has been on a continuous increasing trend. This study provides a positive reference for the prevention and control of A. bungii and the maintenance of forest health and ecosystem security, and provides important theoretical guidance for researchers, policymakers, and governments.

Keywords: MaxEnt model; MigClim model; climate change; human activity; spatial autocorrelation.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Occurrence records of the Aromia bungii population. (A) Records of the occurrence of A. bungii worldwide. (B) Field collection of A. bungii occurrences. (C) Records of the occurrence of A. bungii within China.
FIGURE 2
FIGURE 2
Spatial analysis of Aromia bungii (100 × 100 km). (A) Occurrence of A. bungii distributed within China. (B) Local Moran's I of A. bungii. (C) Hot spot analysis of A. bungii.
FIGURE 3
FIGURE 3
The contribution rates of the environmental variables in MaxEnt model.
FIGURE 4
FIGURE 4
Impact of the most important environmental variables on Aromia bungii. (A) Bio6, minimum temperature of coldest month. (B) Bio13, precipitation of wettest month. (C) Bio30, global human footprint. (D) Bio31, global human influence index.
FIGURE 5
FIGURE 5
Distribution of suitable habitat for Aromia bungii with (A) and without (B) human activity under current climate models.
FIGURE 6
FIGURE 6
Suitable habitat area for Aromia bungii under different climate scenarios.
FIGURE 7
FIGURE 7
Potential suitable distribution areas for Aromia bungii in China under future climate scenarios. (A) SSP1‐2.5‐2050s; (B) SSP1‐2.5‐2070s; (C) SSP2‐4.5‐2050s; (D) SSP2‐4.5‐2070s; (E) SSP3‐7.0‐2050s; (F) SSP3‐7.0‐2070s; (G) SSP5‐8.5‐2050s; (H) SSP5‐8.5‐2070s.
FIGURE 8
FIGURE 8
Changes in the distribution of potential habitats of Aromia bungii under future climate scenarios. (A) SSP1‐2.5‐2050s; (B) SSP1‐2.5‐2070s; (C) SSP2‐4.5‐2050s; (D) SSP2‐4.5‐2070s; (E) SSP3‐7.0‐2050s; (F) SSP3‐7.0‐2070s; (G) SSP5‐8.5‐2050s; (H) SSP5‐8.5‐2070s.
FIGURE 9
FIGURE 9
Multivariate environmental similarity surface (MESS) analysis for Aromia bungii under future climate scenarios. (A) SSP1‐2.5‐2050s; (B) SSP1‐2.5‐2070s; (C) SSP2‐4.5‐2050s; (D) SSP2‐4.5‐2070s; (E) SSP3‐7.0‐2050s; (F) SSP3‐7.0‐2070s; (G) SSP5‐8.5‐2050s; (H) SSP5‐8.5‐2070s.
FIGURE 10
FIGURE 10
Transfer trajectories of potential distribution center routes for Aromia bungii. (A) Moving trajectories of potential distribution center routes for A. bungii in China. (B) The A. bungii movement routes under different shared socioeconomic path models. (C) SSP1‐2.6. (D) SSP2‐4.5. (E) SSP3‐7.0. (F) SSP5‐8.5.
FIGURE 11
FIGURE 11
Occupied habitat maps of Aromia bungii under future climate scenarios. (A) SSP1‐2.5‐2050s; (B) SSP1‐2.5‐2070s; (C) SSP2‐4.5‐2050s; (D) SSP2‐4.5‐2070s; (E) SSP3‐7.0‐2050s; (F) SSP3‐7.0‐2070s; (G) SSP5‐8.5‐2050s; (H) SSP5‐8.5‐2070s.
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