Predicting suitable areas for Metcalfa pruinosa (Hemiptera: Flatidae) under climate change and implications for management

Climate change is a prominent factor reshaping the distribution of invasive species. Metcalfa pruinosa (Say 1830) (Hemiptera: Flatidae), native to North America, has invaded other continents and poses a serious threat to various agricultural crops and the human residential environment. Understanding the distribution of M. pruinosa based on climatic conditions is a critical first step to prevent its further invasion. Therefore, based on its occurrence records and associated environmental variables, a Maxent model was developed to predict suitable areas for this species in the present and future on a global scale. The model exhibited outstanding performance, with a mean area under the receiver operating characteristic curve and true skill statistic values of 0.9329 and 0.926, respectively. The model also indicated that annual precipitation (Bio12) and max temperature of the warmest month (Bio5) were the key environmental variables limiting the distribution of M. pruinosa. Moreover, the model revealed that the current suitable area is 1.01 × 107 km2 worldwide, with southern China, southern Europe, and the eastern United States predicted to be the primary and highly suitable areas in the latter 2 regions. This area is expected to increase under future climate scenarios, mainly in the northern direction. The study's findings contribute to our understanding of climate change's impact on M. pruinosa distribution, and they will aid governments in developing appropriate pest management strategies, including global monitoring and strict quarantine measures.

Potential habitat areas and priority protected areas of Tilia amurensis Rupr in China under the context of climate change

Introduction

Tilia amurensis Rupr (T. amurensis) is one endangered and national class II key protected wild plant in China. It has ornamental, material, economic, edible and medicinal values. At present, the resources of T. amurensis are decreasing, and the prediction of the distribution of its potential habitat in China can provide a theoretical basis for the cultivation and rational management of this species.

Methods

In this study, the R language was used to evaluate 358 distribution records and 38 environment variables. The MaxEnt model was used to predict the potential distribution areas of T. amurensis under the current and future climate scenarios. The dominant environmental factors affecting the distribution of T. amurensis were analyzed and the Marxan model was used to plan the priority protected areas of this species.

Results

The results showed that Bio18, Slope, Elev, Bio1, Bio9 and Bio2 were the dominant environmental factors affecting the distribution of T. amurensis. Under the future climatic scenarios, the potential suitable areas for T. amurensis will mainly distribute in the Northeast China, the total suitable area will reduce compared with the current climate scenarios, and the general trend of the centroid of suitable habitat will be towards higher latitudes. The SPF value of the best plan obtained from the priority conservation area planning was 1.1, the BLM value was 127,616, and the priority conservation area was about 57.61×104 km2. The results suggested that climate, soil and topographic factors jointly affected the potential geographical distribution of T. amurensis, and climate and topographic factors had greater influence than soil factors.

Discussion

The total suitable area of T. amurensis in China under different climate scenarios in the future will decrease, so more effective protection should be actively adopted.

Prediction of the potential distribution area of Spodoptera frugiperda and its parasitic wasp, Trichogramma pretiosum

Spodoptera frugiperda is a migratory agricultural pest with fast-spreading speed, long migration distance, and wide host range, which seriously threatens the safety of economic crops. To predict the trends of S. frugiperda and its parasitoid wasp Trichogramma pretiosum in their habitats under current and future climatic conditions, based on MaxEnt model and geographic distribution data of their historical occurrence, we project the feasibility of introducing T. pretiosum to control S. frugiperda by evaluating on their potential global distribution. The results show that, under the current greenhouse gas concentration, the potential distribution area of S. frugiperda is concentrated in 50° N-30° S, with a total area of 1.74 × 106  km2 , and the potential distribution area of T. pretiosum in the whole world is 2.91 × 106  km2 . The suitable areas of T. pretiosum cover almost all the suitable areas of S. frugiperda, which indicates that T. pretiosum can be introduced to control S. frugiperda. The results of this study can provide a theoretical basis for the monitoring and early warning of S. frugiperda and the use of T. pretiosum to control S. frugiperda.

Time to Step Up Conservation: Climate Change Will Further Reduce the Suitable Habitats for the Vulnerable Species Marbled Polecat (Vormela peregusna)

Habitat loss and human threats are putting the marbled polecat (Vormela peregusna) on the brink of extinction. Numerous recent studies have found that climate change will further deteriorate the living environment of endangered species, leading to their eventual extinction. In this study, we used the results of infrared camera surveys in China and worldwide distribution data to construct an ensemble model consisting of 10 commonly used ecological niche models to specify potential suitable habitat areas for V. peregusna under current conditions with similar environments to the sighting record sites. Changes in the suitable habitat for V. peregusna under future climate change scenarios were simulated using mid-century (2050s) and the end of the century (2090s) climate scenarios provided by the Coupled Model Intercomparison Project Phase 6 (CMIP6). We evaluated the accuracy of the model to obtain the environmental probability values (cutoff) of the V. peregusna distribution, the current distribution of suitable habitats, and future changes in moderately and highly suitable habitat areas. The results showed that the general linear model (GLM) was the best single model for predicting suitable habitats for V. peregusna, and the kappa coefficient, area under the curve (AUC), and true skill statistic (TSS) of the ensemble model all exceeded 0.9, reflecting greater accuracy and stability than single models. Under the current conditions, the area of suitable habitat for V. peregusna reached 3935.92 × 10⁴ km², suggesting a wide distribution range. In the future, climate change is predicted to severely affect the distribution of V. peregusna and substantially reduce the area of suitable habitats for the species, with 11.91 to 33.55% of moderately and highly suitable habitat areas no longer suitable for the survival of V. peregusna. This shift poses an extremely serious challenge to the conservation of this species. We suggest that attention be given to this problem in Europe, especially the countries surrounding the Black Sea, Asia, China, and Mongolia, and that measures be taken, such as regular monitoring and designating protected areas for the conservation of vulnerable animals.

Assessment on Potential Suitable Habitats of the Grasshopper Oedaleus decorus asiaticus in North China based on MaxEnt Modeling and Remote Sensing Data

Grasshopper populations can quickly grow to catastrophic levels, causing a huge amount of damage in a short time. Oedaleus decorus asiaticus (Bey-Bienko) (O. d. asiaticus) is the most serious species in Xilingol League of the Inner Mongolia Autonomous Region. The region is not only an important grassland but also a site of agricultural heritage systems in China. Therefore, projecting the potential geographic distribution of O. d. asiaticus to provide an early warning is vital. Here, we combined temperature, precipitation, soil, vegetation, and topography with remote sensing data to screen the predictors that best characterize the current geographical distribution of O. d. asiaticus. A MaxEnt model approach was applied to project the potential suitable distribution of O. d. asiaticus in Xilingol League (the Inner Mongolia Autonomous Region of China) combined with a set of optimized parameters. The modeling results indicated that there were six main habitat factors that determined the suitable distribution of O. d. asiaticus such as the soil type (ST), grassland type (GT), elevation, precipitation during the growing period (GP), precipitation during the spawning period (SP), and normalized difference vegetation index during the overwintering period (ONDVI). The simulated result was good, with average AUC and TSS values of 0.875 and 0.812, respectively. The potential inhabitable areas of grasshoppers were 198,527 km², distributed mainly in West Urumqi, Xilinhot City, East Urumqi, Abaga Banner, and Xianghuang Banner of Xilingol League. This study is valuable to guide managers and decision-makers to prevent and control the occurrence of O. d. asiaticus early on and this study may facilitate meaningful reductions in pesticide application.

Prediction of Spatiotemporal Invasive Risk of the Red Import Fire Ant, Solenopsis invicta (Hymenoptera: Formicidae), in China

Simple Summary

The red imported fire ant, Solenopsis invicta (Hymenoptera: Formicidae), is an invasive pest, and it has spread rapidly all over the world. In this study, based on the distribution data and environmental factor data of S. invicta, the optimized MaxEnt model was used to predict the suitable areas of S. invicta growth in China under current and future climatic conditions. The results show that the potential suitable area of S. invicta growth in the current climate is 81.37 × 10⁴ km² in size and is mainly located in the south and southeast of China. The total suitable area of S. invicta growth is expected to increase in the future climate change scenario, and the suitable area is likely to spread to higher latitudes.

Abstract

The red imported fire ant, Solenopsis invicta (Hymenoptera: Formicidae), is an invasive pest, and it has spread rapidly all over the world. Predicting the suitable area of S. invicta growth in China will provide a reference that will allow for its invasion to be curbed. In this study, based on the 354 geographical distribution records of S. invicta, combined with 24 environmental factors, the suitable areas of S. invicta growth in China under current (2000s) and future (2030s and 2050s) climate scenarios (SSPs1-2.5s, SSPs2-3.5s and SSPs5-8.5s) were predicted by using the optimized MaxEnt model and geo-detector model. An iterative algorithm and knife-cut test were used to evaluate the important environmental factors that restrict the suitable area under the current climatic conditions. This study also used the response curve to determine the appropriate value of environmental factors to further predict the change and the center of gravity transfer of the suitable area under climate change. The optimized MaxEnt model has high prediction accuracy, and the working curve area (AUC) of the subjects is 0.974. Under climatic conditions, the suitable area is 81.37 × 10⁴ km² in size and is mainly located in the south and southeast of China. The main environmental factors affecting the suitable area are temperature (Bio1, Bio6, and Bio9), precipitation (Bio12 and Bio14) and NDVI. In future climate change scenarios, the total suitable area will spread to higher latitudes. This distribution will provide an important theoretical basis for relevant departments to rapidly prevent and control the invasion of S. invicta.

Climatic ecological suitability and potential distribution of Tricholoma matsutake in western Sichuan Plateau, China based on MaxEnt model

Based on the distribution data of Tricholoma matsutake obtained from field investigation and literature, the ecological-niche factor analysis (ENFA) and the maximum entropy model (MaxEnt) were used to simulate the distribution law and suitable area of T. matsutake in the western Sichuan Plateau. The prediction was made for the future changes in the suitable area of T. matsutake by analyzing the relationship between climate factors and dynamic distribution. The results showed that the area under curve (AUC) values of both the model training set and validation set were greater than 0.90, indicating that the model prediction results were extremely accurate. The environmental variables affecting the potential distribution of T. matsutake were mainly the lowest temperature in the coldest month, the coldest season precipitation, annual temperature difference and soil type, with accumulative contribution of 90.3%. The niche parameters of suitable distribution areas of T. matsutake were as follows: the lowest temperature in the coldest month was -18.5--5.4 ℃, the coldest season precipitation was less than 15.7 mm, the annual temperature difference was 39.5-45 ℃, and soil type was semi-leached soil, including dry red soil, cinnamon soil, gray cinnamon soil, black soil and grey forest soil. The suitable areas of T. matsutake were distributed in the southwest, south, central and east of the plateau at an altitude range of 1900-3600 m. The highly suita-ble areas were mainly distributed in some towns of Yajiang, Xiangcheng, Kangding, Jiulong, Daocheng, Litang, Batang, Danba, Maerkang, Xiaojin, Jinchuan, Lixian, Maoxian, etc. The moderately and lowly suitable areas were located in some towns of Derong, Daofu, Xinlong, Luhuo, Baiyu, Luding, Rangtang, Wenchuan, Heishui, Jiuzhaigou. The highly suitable areas were discontinuously distributed according to the direction of rivers and mountains. The moderately suitable areas were connected with the highly suitable areas, while the lowly suitable areas were the extension of the highly and moderately suitable areas. Future climate change would be beneficial to the growth of T. matsutake on the western Sichuan Plateau, while the climate-suitable areas would show an overall increasing trend. Suitable areas in the low-altitude Minjiang River Basin would be more affected by climate change than those located in high-altitude areas.

[Potential geographical distribution and changes of Artemisia ordosica in China under future climate change]

Artemisia ordosica is a forerunner species of wind-break and sand-fixation in desert steppe in China, which plays an important role in ecosystem restoration and reconstruction. How-ever, it could influence human health. Based on 89 valid data of current distribution of A. ordosica in China and 19 typical climatic factors, the MaxEnt model was used to simulate the potential distribution of A. ordosica in China under current and two scenarios (RCP 4.5 and RCP 8.5; 2050s and 2070s). The SDM toolbox of ArcGIS software was used to analyze the potential distribution range of A. ordosica and its changes in China. The importance of key climatic factors was evaluated by comprehensive contribution rate, Jackknife method, and response curve of environmental variables. The accuracy of model was tested and evaluated by area under the curve (AUC) of the test subject working characteristic (ROC). The results showed that the MaxEnt model worked well (AUC=0.980). which predicted that A. ordosica was mainly concentrated in and around Mu Us Sandy Land, consistent with the current actual distribution range. The distribution area of A. ordosica of potential high fitness under the future two scenarios decreased by 5.2%-26.8%, which was negatively affected by future climate change. Seasonal variation of temperature, mean precipitation in the coldest season, and mean annual temperature had the greatest impact. The core area of future potential distribution of A. ordosica in China was located in Mu Us Sandy Land, with a tendency for spreading to northeast (Jilin, Heilongjiang, Liaoning and some parts of Hebei).

[Impacts of climate change on the distribution of Cymbidium kanran and the simulation of distribution pattern]

In this study, data of 19 climatic factors were downloaded from the World Climate website. A total of 233 Cymbidium kanran distribution data were obtained through online review and field visits. Using MaxEnt model and combined with ArcGIS spatial analysis technology, the potential distribution area and distribution pattern of C. kanran in different periods were simulated, as well as its distribution during the last glacial period and 2070. The results showed that the curve indexes (AUC) value of the model training set was 0.957, and the AUC value of the verification set was 0.953, indicating that the prediction accuracy of the model was very high. The current distribution of C. kanran was mostly affected by the driest quarter precipitation, mean annual precipitation, wettest quarter precipitation, and mean annual temperature range. The contribution rates were 50.3%, 15.9%, 8.4% and 4.4%, respectively, with the total contribution rate being 79.0%. In the last glacial period, C. kanran mainly distributed in Wuyi Mountain, Luojing Mountain, Nanling, Taiwan's five major mountains and some hills in the northern part of Guangxi. From now to 2070, the distribution of C. kanran area will decrease by 22.4%. The southwestern part of Guangxi, the central part of Yunnan, and the junctions of Jiangxi, Fujian and Guangdong provinces will expand, while that in eastern Jiangxi, western Fujian, and the border between these two provinces will shrink.