Predicted current suitable regions for <i>Rhinoncus sibiricus</i> distribution in China.

Area distribution of suitable R. sibiricus habitats under current climatic conditions. Red: high-suitability area, yellow: moderate-suitability area, blue: low-suitability area, white: unsuitable area. The boundary was obtained from Natural Earth (http://www.naturalearthdata.com/). Based on the principles of national and territorial integrity, we modified and adjusted the vector boundary.</p

Environmental variables considered in the <i>Rhinoncus sibiricus</i> MaxEnt model and their contributions.

Environmental variables considered in the Rhinoncus sibiricus MaxEnt model and their contributions.</p

Jackknife test for determining the effect of major variables on <i>Rhinoncus sibiricus</i> distribution.

A: Regularized training gain for R. sibiricus (full model); B: Test gain for R. sibiricus. Effects of variables in the sample set were used to validate the model.</p

Relative changes in <i>Rhinoncus sibiricus</i> habitat area under climate scenarios ssp126 and ssp585.

Relative changes in Rhinoncus sibiricus habitat area under climate scenarios ssp126 and ssp585.</p

Flowchart of datasets and processes used.

In recent years, buckwheat (Fagopyrum spp.) is being increasingly damaged by the Siberian tortoise beetle (Rhinoncus sibiricus Faust). Adults and nymphs feed on leaf tissues and caulicles, thus damaging its stems and leaves. In this study, we investigated the habits, distribution, and environmental impact of R. sibiricus using MaxEnt, an ecological niche model. Geographic information about the infestation site from previous field surveys and climatic data from 2013 to 2018 were organized and optimized using R. The impact factors were calculated using MaxEnt software. The results indicate that population fluctuations in R. sibiricus are related to changes in temperature, humidity, and their spatial distribution. Under current climatic conditions, R. sibiricus is mainly distributed in northern China, with sporadic distribution in south–western China. The values for a survival probability threshold > 0.3 were: precipitation during the wettest month (bio13), 70.31–137.56 mm; mean temperature of the coldest quarter (bio11), -15.00–0.85°C; mean temperature of the warmest quarter (bio10), 11.88–23.16°C; precipitation during the coldest quarter (biol9), 0–24.39 mm. The main factors contributing > 70% to the models were precipitation during the wettest month and coldest quarter, and mean temperature during the warmest and coldest quarters. Under both future climate models, the center of the fitness zone moves northward. Our results will be useful in guiding administrative decisions and support farmers interested in establishing control and management strategies for R. sibiricus. This study could also serve as a reference for future research on other invasive pests.</div

Study area and distribution of <i>Rhinoncus sibiricus</i> (Siberian tortoise weevils).

General distribution of R. sibiricus in China. Red dots on the map represent filtered incidences of R. sibiricus. The boundary was obtained from Natural Earth (http://www.naturalearthdata.com/). Based on the principles of national and territorial integrity, we modified and adjusted the vector boundary.</p

TSS values for the <i>Rhinoncus sibiricus</i> Faust prediction model.

TSS values for the Rhinoncus sibiricus Faust prediction model.</p

Response curves of important environmental indices in the <i>Rhinoncus sibiricus</i> distribution model.

Response Curves for (A): precipitation during the wettest month; (B): mean temperature of the coldest quarter; (C): Response curve for mean temperature of the warmest quarter; (D): precipitation during the coldest quarter.</p

Analysis of collinearity among 19 climate variables.

Collinearity matrix of candidate R. sibiricus predictor climate variables. Collinearity threshold is R > 0.75. Collinearity of variables increases with the depth of blue and red colors. Correlation strength increases with circle size. (TIF)</p

The R package used.

In recent years, buckwheat (Fagopyrum spp.) is being increasingly damaged by the Siberian tortoise beetle (Rhinoncus sibiricus Faust). Adults and nymphs feed on leaf tissues and caulicles, thus damaging its stems and leaves. In this study, we investigated the habits, distribution, and environmental impact of R. sibiricus using MaxEnt, an ecological niche model. Geographic information about the infestation site from previous field surveys and climatic data from 2013 to 2018 were organized and optimized using R. The impact factors were calculated using MaxEnt software. The results indicate that population fluctuations in R. sibiricus are related to changes in temperature, humidity, and their spatial distribution. Under current climatic conditions, R. sibiricus is mainly distributed in northern China, with sporadic distribution in south–western China. The values for a survival probability threshold > 0.3 were: precipitation during the wettest month (bio13), 70.31–137.56 mm; mean temperature of the coldest quarter (bio11), -15.00–0.85°C; mean temperature of the warmest quarter (bio10), 11.88–23.16°C; precipitation during the coldest quarter (biol9), 0–24.39 mm. The main factors contributing > 70% to the models were precipitation during the wettest month and coldest quarter, and mean temperature during the warmest and coldest quarters. Under both future climate models, the center of the fitness zone moves northward. Our results will be useful in guiding administrative decisions and support farmers interested in establishing control and management strategies for R. sibiricus. This study could also serve as a reference for future research on other invasive pests.</div