Potential distribution of two invasive pineapple pests under climate change

Predicting the distribution pattern changes of dye plant habitats caused by climate change

Climate change has accelerated the habitat loss and fragmentation of wildlife. Dye plants of "Fengxiang dyeing" are important indigenous natural resources for traditional printing and dyeing craft in southwest China, is of practical and cultural importance for dozens of ethnic minorities. However, lack of the spatial distribution information of these plants has hampered holistic and efficient conservation management measures. We analyzed the potentially suitable areas of four dye plants (Liquidambar formosana, Strobilanthes cusia, Persicaria tinctoria and Indigofera tinctoria) necessary for "Fengxiang dyeing" based on their geographical distribution sites under different climatic situations using the maximum entropy (MaxEnt) model. The results showed that temperature, precipitation and elevation were the most important factors affecting the suitable geographical areas of the four dye plants. Under the current climate conditions, the overlapping suitable habitat areas of the four plants were mainly in the four southern provinces of China, including Guizhou, Guangxi, Guangdong and Hainan. L. formosana was used as the base plant for combination with the other three plants under the two future climate scenarios (SSP126 and SSP585), and the overlapping suitable habitat areas of the obtained seven combination patterns were considered suitable for potential craft development. Five patterns showed an increase, while two patterns showed a decreasing trend with the increasing carbon emission. The prediction results showed that the overlapping suitable habitat center of the four plants will gradually move to the northeast, indicating that the overlapping suitable habitat area and craft distribution area will be changed. These results provide the basis for understanding the spatial distribution pattern changes of dye plants caused by climate change and establishing measures for protecting and developing printing and dyeing craft.

Current and future potential distribution of two bamboo pests in China: Anakaburmensis and Cicadellaviridis (Hemiptera, Cicadellidae)

China's bamboo output is closely associated with its national economy; however, it is currently rapidly declining due to damage from the pests Anakaburmensis and Cicadellaviridis. Identifying regions that are environmentally suitable for these pests is a critical step in their effective control. Therefore, in this study, we used a Maxent model to predict their current and future potential areas of distribution (2021-2040, 2041-2060, and 2061-2080) and explored changes over time using distribution data and related environmental variables. The model results demonstrates that the current potential areas of distribution of A.burmensis are predominantly concentrated in several provinces of southern and central China, such as Guizhou, Guangxi, and Hubei, whereas the current potential areas of distribution of C.viridis are primarily in many provinces across southern, central, and northeastern China. In the future, the potential distribution of A.burmensis will increase and move minimally, whereas the potential distribution of C.viridis will decrease and move considerably. The results of the present study provide vital information for predicting the spread and outbreaks of C.viridis and A.burmensis and provide a reference framework for developing management strategies to control these two pests, thereby minimizing economic loss in the bamboo industry.

Novel insights into hotspots of insect vectors of GLRaV-3: Dynamics and global distribution

Grapevine leafroll-associated virus 3 (GLRaV-3) is the most prevalent and economically damaging virus in grapevines and is found on nearly all continents, except Antarctica. Ten mealybugs act as vector insects transmitting the GLRaV-3. Understanding the potential distribution range of vector insects under climate change is crucial for preventing and managing vector insects and controlling and delaying the spread of GLRaV-3. This study investigated the potential geographical range of insect vectors of GLRaV-3 worldwide using MaxEnt (maximum entropy) based on occurrence data under environmental variables. The potential distributions of these insects were projected for the 2030s, 2050s, 2070s, and 2090s under the three climate change scenarios. The results showed that the potential distribution range of most vector insects is concentrated in Southeastern North America, Europe, Asia, and Southeast Australia. Most vector insects contract their potential distribution ranges under climate-change conditions. The stacked model suggested that potential distribution hotspots of vector insects were present in Southeastern North America, Europe, Southeast Asia, and Southeast Australia. The potential distribution range of hotspots would shrink with climate change. These results provide important information for governmental decision-makers and farmers in developing control and management strategies against vector insects of GLRaV-3. They can also serve as references for studies on other insect vectors.

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.

Which SDM Model, CLIMEX vs. MaxEnt, Best Forecasts Aeolesthes sarta Distribution at a Global Scale under Climate Change Scenarios?

A precise evaluation of the risk of establishing insect pests is essential for national plant protection organizations. This accuracy is crucial in negotiating international trade agreements for forestry-related commodities, which have the potential to carry pests and lead to unintended introductions in the importing countries. In our study, we employed both mechanistic and correlative niche models to assess and map the global patterns of potential establishment for Aeolesthes sarta under current and future climates. This insect is a significant pest affecting tree species of the genus Populus, Salix, Acer, Malus, Juglans, and other hardwood trees. Notably, it is also categorized as a quarantine pest in countries where it is not currently present. The mechanistic model, CLIMEX, was calibrated using species-specific physiological tolerance thresholds, providing a detailed understanding of the environmental factors influencing the species. In contrast, the correlative model, maximum entropy (MaxEnt), utilized species occurrences and spatial climatic data, offering insights into the species' distribution based on observed data and environmental conditions. The projected potential distribution from CLIMEX and MaxEnt models aligns well with the currently known distribution of A. sarta. CLIMEX predicts a broader global distribution than MaxEnt, indicating that most central and southern hemispheres are suitable for its distribution, excluding the extreme northern hemisphere, central African countries, and the northern part of Australia. Both models accurately predict the known distribution of A. sarta in the Asian continent, and their projections suggest a slight overall increase in the global distribution range of A. sarta with future changes in climate temperature, majorly concentrating in the central and northern hemispheres. Furthermore, the models anticipate suitable conditions in Europe and North America, where A. sarta currently does not occur but where its preferred host species, Populus alba, is present. The main environmental variables associated with the distribution of A. sarta at a global level were the average annual temperature and precipitation rate. The predictive models developed in this study offer insights into the global risk of A. sarta establishment and can be valuable for monitoring potential pest introductions in different countries. Additionally, policymakers and trade negotiators can utilize these models to make science-based decisions regarding pest management and international trade agreements.

Potential Global Distribution of Paracoccus marginatus, under Climate Change Conditions, Using MaxEnt

The papaya mealybug, Paracoccus marginatus, is an invasive pest species found all over the world. It is native to Mexico and Central America, but is now present in more than 50 countries and regions, seriously threatening the economic viability of the agricultural and forestry industry. In the current study, the global potential distribution of P. marginatus was predicted under current and future climatic conditions using MaxEnt. The results of the model assessment indicated that the area under the curve of the receiver operating characteristic ( ROC-AUC) was 0.949, while the TSS value was 0.820. The results also showed that the three variables with the greatest impact on the model were min temperature of coldest month (bio6), precipitation of wettest month (bio13), and precipitation of coldest quarter (bio19), with corresponding contributions of 46.8%, 31.1%, and 13.1%, respectively. The results indicated that the highly suitable areas were mainly located in tropical and subtropical regions, including South America, southern North America, Central America, Central Africa, Australia, the Indian subcontinent, and Southeast Asia. Under four climate scenarios in the 2050s and 2070s, the area of suitability will change very little. Moreover, the results showed that the area of suitable areas in 2070s increased under all four climate scenarios compared to the current climate. In contrast, the area of suitable habitat increases from the current to the 2050s under the SSP370 and SSP585 climate scenarios. The current study could provide a reference framework for the future control and management of papaya mealybug and other invasive species.

Predicting the Potential Distribution of the Szechwan Rat Snake (Euprepiophis perlacea) and Its Response to Climate Change in the Yingjing Area of the Giant Panda National Park

Climate change is a significant driver of changes in the distribution patterns of species and poses a threat to biodiversity, potentially resulting in species extinctions. Investigating the potential distribution of rare and endangered species is crucial for understanding their responses to climate change and for the conservation of biodiversity and ecosystem management. The Szechwan rat snake (Euprepiophis perlacea) is an endemic and endangered species co-distributed with giant pandas, and studying its potential distribution contributes to a better understanding of the distribution pattern of endangered species. In this study, we confirmed seven presence points of this species in the Yingjing Area of the Giant Panda National Park, and selected eleven key factors to predict the potential distribution of E. perlacea under current and future scenarios using MaxEnt models. Our study consistently achieved AUC values exceeding 0.79, meeting the precision requirements of the models. The results indicated that the high potential distribution area of E. perlacea is mainly located near Yunwu mountain and the giant panda rewilding and reintroduction base, accounting for approximately 12% of the protected area. Moreover, we identified the primary environmental factors influencing the distribution of E. perlacea as the distance from streams and the slope degree, with their contribution rates exceeding 41% and 31%, respectively. In comparison to the current scenario, the potential habitat range for E. perlacea did not show an overall reduction in the context of future climate scenarios. To ensure the long-term preservation of E. perlacea, it is advisable to validate its actual distribution based on the models' results. Particular attention should be given to safeguarding its core distribution areas and raising awareness among residents within the potential distribution range about the conservation of E. perlacea.

Invasion risks presented by Gonopsis affinis and the use of Trissolcus mitsukurii as a biological control agent under present and future climate conditions

BACKGROUND

Gonopsis affinis (Uhler) is a stinkbug that represents a significant threat to the production of rice (Oryza sativa L.), sugarcane (Saccharum officinarum L.) and eulalia (Miscanthus sinensis (Andersson)), and has been listed as a sugarcane pest in Japan. Trissolcus mitsukurii Ashmead is an egg parasitoid of G. affinis. To determine the potential of T. mitsukurii to be a biological control agent for G. affinis, we aim to predict the current and future areas of suitable habitat for these two species and their overlap with areas of present crop production. We developed MaxEnt models using two different variable selection methods and compared the two for T. mitsukurii with a CLIMEX model.

RESULTS

The results showed extensive suitable areas for G. affinis under current climate conditions in East Asia, West Africa, Madagascar, and South America. These ranges overlap with areas currently being used for the production of the three crops in question. More than half overlap with areas of suitable habitat for T. mitsukurii. The most critical environmental variable determining habitat suitability for G. affinis was showed to be precipitation of warmest quarter, whilst for T. mitsukurii it was minimum temperature of the coldest month.

CONCLUSION

Based on our assessment we recommend the immediate implementation of monitoring and invasion prevention measures for G. affinis in southwest China, the Malay Archipelago and West Africa. We suggest that T. mitsukurii be considered for use as a biological control agent in East Asia, Madagascar, Florida and Brazil in the case of future invasions by G. affinis. © 2023 Society of Chemical Industry.

Species richness and endemism patterns of Sternorrhyncha (Insecta, Hemiptera) in China

One of the main goals in biogeography and ecology is the study of patterns of species diversity and the driving factors in these patterns. However, such studies have not focused on Sternorrhyncha in China, although this region hosts massive species distribution data. Here, based on the 15,450 distribution records of Sternorrhyncha species in China, we analyzed patterns in species richness and endemism at 1° × 1° grid size and determined the effects of environmental variables on these patterns using correlations analysis and the model averaging approach. We found that species richness and endemism of Sternorrhyncha species are unevenly distributed, with high values in the eastern and southeastern coastal regions of mainland China, as well as Taiwan Island. Furthermore, the key factors driving species richness and endemism patterns are inconsistent. Species richness patterns were strongly affected by the normalized difference vegetation index, which is closely related to the feeding habits of Sternorrhyncha, whereas endemism patterns were strongly affected by the elevation range. Therefore, our results indicate that the range size of species should be considered to understand the determinants of species diversity patterns.

Emerging Themes and Approaches in Plant Virus Epidemiology

Plant diseases caused by viruses share many common features with those caused by other pathogen taxa in terms of the host-pathogen interaction, but there are also distinctive features in epidemiology, most apparent where transmission is by vectors. Consequently, the host-virus-vector-environment interaction presents a continuing challenge in attempts to understand and predict the course of plant virus epidemics. Theoretical concepts, based on the underlying biology, can be expressed in mathematical models and tested through quantitative assessments of epidemics in the field; this remains a goal in understanding why plant virus epidemics occur and how they can be controlled. To this end, this review identifies recent emerging themes and approaches to fill in knowledge gaps in plant virus epidemiology. We review quantitative work on the impact of climatic fluctuations and change on plants, viruses, and vectors under different scenarios where impacts on the individual components of the plant-virus-vector interaction may vary disproportionately; there is a continuing, sometimes discordant, debate on host resistance and tolerance as plant defense mechanisms, including aspects of farmer behavior and attitudes toward disease management that may affect deployment in crops; disentangling host-virus-vector-environment interactions, as these contribute to temporal and spatial disease progress in field populations; computational techniques for estimating epidemiological parameters from field observations; and the use of optimal control analysis to assess disease control options. We end by proposing new challenges and questions in plant virus epidemiology.

Two Species Delimitation of Pseudaulacaspis (Hemiptera: Diaspididae) Based on Morphology, Molecular Clustering, and Niche Differentiation

Pseudaucalaspis pentagona and P. prunicola are notorious pests and commonly feed on various ornamental plants and fruit trees worldwide. The two species share many host-plant species, and are similar in morphological characteristics and life cycle, making it difficult to distinguish to distinguish between them. In this study, morphological characteristics, molecular evidence, and ecological niches were used to define these species. We performed PCA analysis on 22 morphological characteristics that allowed the delineation of the species. We then sequenced the COI gene of both species revealing five populations of P. pentagona and one population of P. prunicola, and the higher support rate could distinguish the two species. We also identified the potential distribution area of the two species based on the MaxEnt niche model, which showed that the degree of niche overlap was high, but that they occupied different niches. Ultimately, we combined three lines of evidence to show that the two species are distinctly different. This study supports species definition using combined morphology, genetics, and ecology and provides a theoretical basis for the effective control of these two pests in the future.

Surveillance and invasive risk of the red imported fire ant, Solenopsis invicta Buren in China

BACKGROUND

The red imported fire ant, Solenopsis invicta Buren is one of the world's most successful and destructive invasive ant species. In mainland China, fast, monthly and annual pest reports on all pests have been established since 2010. The distribution of S. invicta resulting from climate change in China was predicted using MaxEnt modeling in combination with comprehensive surveillance data and 56 environmental factors.

RESULTS

The fast and monthly reports revealed that S. invicta had spread to new territories almost every year in this timeframe. The transportation of seedlings and deployment of turfgrass were the major artificial transmission pathways. Annual reports indicated that control efforts had effectively reduced its occurrence areas and degree of severity of infestations, and retrieved the economic loss caused by S. invicta. The MaxEnt model predicted that S. invicta would expand to 23 provinces in China as a result of climate change. Moisture variables were the key factors affecting the distribution of this pest.

CONCLUSION

Based on the theoretical reference framework of this research, China proposed the first-ever integrated tactics against a single pest, jointly involving nine ministries, which include clarifying responsibilities, cutting off transmission pathways, strengthening surveillance, declaring pest distributions and conducting preventive and control campaigns. Practical efforts and measures combating the devastation of S. invicta may shed light on its management and other invasive species worldwide. © 2022 Society of Chemical Industry.

Current and future potential distribution of the invasive scale Ceroplastes rusci (L., 1758) (Hemiptera: Coccidae) under climate niche

BACKGROUND

The fig wax scale, Ceroplastes rusci is an invasive pest that feeds on more than 94 genera from 52 families that is spread across 60 countries, causing negative impacts to agriculture and forestry. Understanding the potential distribution of invasive species under climate change is crucial for the management and monitoring purposes. Thus, we predicted the potential distribution areas of C. rusci using Maximum Entropy (MaxEnt) based on the occurrence data and environmental variables under current and future climatic scenarios.

RESULTS

Our results showed that the temperature annual range (Bio 7) and mean temperature of the warmest quarter (Bio 10) attributed to a higher contribution to the current model of the distribution of C. rusci. The potential distribution maps illustrated the main concentrated areas of C. rusci which included South America, Africa, Asia, and Oceania. In addition, potential range expansions or reductions were predicted under different future climate change scenarios, which showed that the total suitable areas of the fig wax scale presented an increasing trend until 2100.

CONCLUSION

Our study provides significant data to understand the potential distribution of C. rusci around the world. It also serves as an early warning for the highly suitable habitat areas that even offers a platform to the currently non-infested regions or countries who are yet to develop monitoring strategies in response to the possible C. rusci outbreak. © 2022 Society of Chemical Industry.

Modeling of the potential geographical distribution of naked oat under climate change

INTRODUCTION

Naked oat (Avena sativa L.), is an important miscellaneous grain crop in China, which is rich in protein, amino acids, fat and soluble dietary fiber. The demand for functional foods is gradually increasing as living standards rise, and the output of minor cereals in China is increasing annually. The planting layout of naked oat is scattered and lacks planning, which seriously restricts the development of the naked oat industry. The increase in miscellaneous grain production will not only be impacted by cultivation methods and management techniques, but the potential impact of global climate change needs to be considered. North China is the main area for naked oat production, worldwide.

METHODS

In this study, the potential distribution range of naked oat in North China was forecast based on historical distribution data and the Maxent model under climate change conditions. The performance of the model was relatively high.

RESULTS

The results indicated that the most suitable area for the potential geographic distribution of naked oat in North China was 27.89×104 km², including central and northeastern Shanxi, and northeastern and western Hebei and Beijing, gradually moving northward. The core suitable area increased, and the distribution of naked oat had an obvious regional response to climate warming; the main environmental factors affecting the potential geographic distribution were precipitation factor variables (precipitation seasonality (variation coefficient)), terrain factor variables (elevation) and temperature factor variables (temperature seasonality (Standard Deviation*100)).

DISCUSSION

In this study, the Maxent model was used to analyze and predict suitable areas for naked oat in North China, and the distribution of suitable areas was accurately divided, and the main climatic factors affecting the distribution of naked oat were identified. This research provides data support and theoretical support for the optimal planting zone of naked oat in North China.

Predicting the potential suitable habitats of genus Nymphaea in India using MaxEnt modeling

Modeling and mapping the distribution of suitable habitats of aquatic plants are critical for assessing the impact of factors like changing climate on species habitat range shifts, declines, and expansions. Nymphaea is an aquatic perennial herb considered valuable because of its ornamental, economic, medicinal, and ecological importance. In India, the geographical distribution of Nymphaea is diverse, and the suitable habitats of individual species are vulnerable to the changing climate and global warming effects. Despite its increased vulnerability, only a few limited conservation efforts in aquatic environments are being made to date. In several places, the distribution of Nymphaea has been impacted by both anthropogenic and climate-related disturbances. A comprehensive strategy will be needed to meet the socio-ecological challenge of Nymphaea conservation. In this study, we employed maximum entropy (MaxEnt) method to assess how climate change affects the distribution of Nymphaea suitable habitat. The occurrence records of Nymphaea were collected from primary surveys, Global Biodiversity Information Facility (GBIF), and published works. Bioclimatic variables obtained from the Coupled Model Intercomparison Project (CMIP6) were employed as predictor variables in distribution modeling. The projections were made using three SSPs (stringent mitigation scenarios) for the future period of 2050. Our results showed shifts in the suitability ranges of Nymphaea under different projection scenarios. The study provides information about the distribution of suitable habitats for Nymphaea in India, which may be helpful for ongoing efforts to conserve and manage the aquatic plants, particularly in areas that are losing suitable climate conditions.

Modelling the current and future potential distribution of the bean bug Riptortus pedestris with increasingly serious damage to soybean

BACKGROUND

The bean bug, Riptortus pedestris, has received intense attention in recent years because of its involvement in increasing outbreaks of staygreen syndrome in soybean (Glycine max (L.)), often causing almost 100% loss of soybean yield in China. However, for this pest of great economic importance, potential current and future distribution patterns and their underlying driving factors remain unclear.

RESULTS

Maxent modelling under climate, elevation and land-use (including the distribution information of G. max) variables showed that the current potential distribution covered a vast geographic range, primarily including most parts of south, South East and east Asia. Under future environmental scenarios, suitable habitat expanded markedly. Areas that would become highly suitable for R. pedestris were primarily located in north-east China and west India. Five bioclimatic (BIO13, BIO08, BIO18, BIO02 and BIO07) and one land-use (C3 annual crops) predictors contributed approximately 95% to the modelling, and analyses of curve responses showed that to a certain extent, R. pedestris preferred relatively high temperature and precipitation. Our results indicate that a high risk of R. pedestris outbreaks is present in parts of Asia, especially in the soybean-growing regions of China, and this risk will continue in the future.

CONCLUSION

The predicted distribution pattern and key regulating factors identified herein could provide a vital reference for developing pest management policies and further alleviate the incidence of staygreen syndrome in soybean. © 2022 Society of Chemical Industry.

Study on the Potential Distribution of Leptinotarsa decemlineata and Its Natural Enemy Picromerus bidens Under Climate Change

The Colorado potato beetle (CPB), scientifically known as Leptinotarsa decemlineata, is a destructive quarantine pest that has invaded more than 40 countries and regions worldwide. It causes a 20–100% reduction in plant production, leading to severe economic losses. Picromerus bidens L. is a predatory insect that preys on CPB. This study used the MaxEnt model to predict the current and future potential distribution areas of CPB and P. bidens under different climatic scenarios to determine the possibility of using P. bidens as a natural enemy to control CPB. The possible introduction routes of CPB and P. bidens were subsequently predicted by combining their potential distribution with the current distribution of airports and ports. Notably, the potential distribution area of P. bidens was similar to that of CPB, suggesting that P. bidens could be used as a natural enemy to control CPB. Future changes in the suitable growth areas of CPB under different climate scenarios increased and decreased but were insignificant, while those of P. bidens decreased. Consequently, a reduction of the suitable habitats of P. bidens may cause a decrease in its population density, leading to a lack of adequate and timely prevention and control of invasive pests. Active measures should thus be enacted to minimize global warming and protect biodiversity. This study provides a theoretical basis and data support for early warning, monitoring, and control of the CPB spread.

Including Host Availability and Climate Change Impacts on the Global Risk Area of Carpomya pardalina (Diptera: Tephritidae)

Fruit flies are a well-known invasive species, and climate-based risk modeling is used to inform risk analysis of these pests. However, such research tends to focus on already well-known invasive species. This paper illustrates that appropriate risk modeling can also provide valuable insights for flies which are not yet “on the radar.” Carpomya pardalina is a locally important cucurbit-infesting fruit fly of western and central Asia, but it may present a risk to other temperate countries where melons are grown. MaxEnt models were used to map the risk area for this species under historical and future climate conditions averaged from three global climate models under two shared socio-economic pathways in 2030 and 2070 from higher climate sensitivity models based on the upcoming 2021 IPCC sixth assessment report. The results showed that a total of 47.64% of the world’s land mass is climatically suitable for the fly; it could establish widely around the globe both under current and future climates with host availability. Our MaxEnt modeling highlights particularly that Western China, Russia, and other European countries should pay attention to this currently lesser-known melon fly and the melons exported from the present countries. The current and expanding melon trade could offer direct invasion pathways to those regions. While this study offers specific risk information on C. pardalina, it also illustrates the value of applying climate-based distribution modeling to species with limited geographic distributions.

Two new invasive Ips bark beetles (Coleoptera: Curculionidae) in mainland China and their potential distribution in Asia

BACKGROUND

Ips is a bark beetle genus of 45 species, many of which are pests of conifer forests and plantations under stress. Twelve Ips species are recorded from China and presumably native there. From 2016 to 2018, specimens suspected to be Ips calligraphus and Ips grandicollis, were collected from traps with ethanol as a sole lure in Zhuhai, Guangdong, China. Both species originate in North America and infest various species of native or introduced pines. Since Ips species are known to cause or exacerbate problems in pine plantations, and a regional survey using traps baited with attractants were implemented in this study to investigate the extent of the introduction.

RESULTS

Both I. calligraphus and I. grandicollis have been collected repeatedly from several traps with Ips attractants in Zhuhai, Guangdong, China since 2016. Potential distributions of these two species in Asia, inferred using MaxEnt, is extensive, given the high projected environmental suitability in North America, South America, Mediterranean Europe, Northern Africa, and Eastern Asia. The host plant of I. calligraphus from Zhuhai was identified as slash pine Pinus elliottii using DNA barcoding of gut contents from trapped individuals.

CONCLUSION

This is the first report of the establishment of two American pine bark beetles, I. calligraphus and I. grandicollis in continental Asia. The gut content of both species suggests that these pest feeds on a non-native host. Whether the two species present high-risk to Asian forests will become clear with more research on their interactions with native pines.

Risk assessment of insect pest expansion in alpine ecosystems under climate change

BACKGROUND

Growth in insect pest populations poses a significant threat to ecosystem functions and services, societal development, and food security in alpine regions under climate change. Risk assessments are important prioritization tools for pest management, which must be used to study insect pest expansion in alpine ecosystems under global warming. We used species distribution modeling to simulate the current and future distribution probabilities of 58 insect pest species in the Qinghai Province, China, based on a comprehensive field investigation. Subsequently, general linear modeling was used to explore the relationship between the distribution probability of these species and the damage caused by them. Finally, we assessed the ecological risk of insect pest expansion across different alpine ecosystems under climate change.

RESULTS

Climate change could increase the distribution probabilities of insect pest species across different alpine ecosystems. However, the presence of insect pest species may not correspond to the damage occurrence in alpine ecosystems based on percent leaf loss, amount of stunting, and seedling death of their host species. Significant positive relationships between distribution probability and damage occurrence were found for several of the examined insect pest species. Insect pest expansion is likely to increase extensively in alpine ecosystems under increasing carbon dioxide (CO₂ ) emission scenarios.

CONCLUSION

The relationships between distribution probability and damage occurrence should be considered in species distribution modeling for risk assessment of insect pest expansion under climate change. Our study could improve the effectiveness of risk assessment of insect pest expansion under changing climate conditions. © 2021 Society of Chemical Industry.

Maximum Entropy Modeling to Predict the Impact of Climate Change on Pine Wilt Disease in China

Pine wilt disease is a devastating forest disease caused by the pinewood nematode Bursaphelenchus xylophilus, which has been listed as the object of quarantine in China. Climate change influences species and may exacerbate the risk of forest diseases, such as the pine wilt disease. The maximum entropy (MaxEnt) model was used in this study to identify the current and potential distribution and habitat suitability of three pine species and B. xylophilus in China. Further, the potential distribution was modeled using the current (1970-2000) and the projected (2050 and 2070) climate data based on two representative concentration pathways (RCP 2.6 and RCP 8.5), and fairly robust prediction results were obtained. Our model identified that the area south of the Yangtze River in China was the most severely affected place by pine wilt disease, and the eastern foothills of the Tibetan Plateau acted as a geographical barrier to pest distribution. Bioclimatic variables related to temperature influenced pine trees' distribution, while those related to precipitation affected B. xylophilus's distribution. In the future, the suitable area of B. xylophilus will continue to increase; the shifts in the center of gravity of the suitable habitats of the three pine species and B. xylophilus will be different under climate change. The area ideal for pine trees will migrate slightly northward under RCP 8.5. The pine species will continue to face B. xylophilus threat in 2050 and 2070 under the two distinct climate change scenarios. Therefore, we should plan appropriate measures to prevent its expansion. Predicting the distribution of pine species and the impact of climate change on forest diseases is critical for controlling the pests according to local conditions. Thus, the MaxEnt model proposed in this study can be potentially used to forecast the species distribution and disease risks and provide guidance for the timely prevention and management of B. xylophilus.

Modeling the Invasion of the Large Hive Beetle, Oplostomusfuligineus, into North Africa and South Europe under a Changing Climate

Simple Summary

Large Hive Beetles (LHBs) are common pests of honeybee colonies, especially in the African continent. The ability of this pest to invade new regions in North Africa and Europe is highlighted in the present study using a species distribution modeling technique in current and future climate change scenarios in 2050 and 2070. In brief, this pest will be a new burden on the beekeeping sector outside Africa, and therefore the development of early monitoring strategies is recommended.

Abstract

Some beetle species can attack honeybee colonies, causing severe damage to beekeeping. These pests include Oplostomus fuligineus, which is also known as the Large Hive Beetle (LHB). This beetle is native to Sub-Saharan Africa and has recently also been recorded in some parts of North Africa. It feeds mainly on young bee larvae and stored food within the colonies, causing severe damage to weak colonies. The present work sheds light on the current and future distribution (from 2050 to 2070) of this beetle in Africa and South Europe using species distribution modeling. Maxent was used to model the invasion of LHB. The Shared Socioeconomic Pathways (SSPs) 126 and 585 were used to model the future distribution of LHB. The Maxent models showed satisfactory results with a high Area Under Curve (AUC) value (0.85 ± 0.02). Furthermore, the True Skill Statistics (TSS) value was equal to 0.87. The current and future maps showed a high risk of invasion because of temperature variation in most of the parts of North Africa and South Europe. The maps also predicted the future invasion of LHB into other countries, mainly through southern Europe. These predictive risk maps will help quarantine authorities in highly relevant countries to prevent the expansion of this pest outside of its natural range.

Estimating Potential Distribution of Sweetgum Pest Acanthotomicus suncei and Potential Economic Losses in Nursery Stock and Urban Areas in China

Simple Summary

American sweetgum Liquidambar styraciflua (Altingiaceae) was introduced to China over 60 years ago. It is an important tree species for increasing landscape value and promoting afforestation in urbanized areas of eastern China in the past 20 years. Sweetgum inscriber Acanthotomicus suncei is a local bark beetle pest and lethal to the introduced American sweetgum. To estimate the potential economic losses caused by the sweetgum inscriber, we survey the beetles’ natural distribution in China. Based on field collections, potential distribution was predicted. Nurseries stocking American sweetgum were found in the high suitability area of this pest. Additionally, we predict the direct loss incorporating tree and removal cost. A questionnaire was sent to maintenance companies, growers, and gardener associations for tree removal prices. In addition, the market price and inventory were also gained from telephone interview. Our economic analysis indicates that if sweetgum inscriber were to become established in the main American sweetgum business, the potential losses of nursery stock and urban area could range from USD 12.81 to 14.41 million. The results will serve as a baseline measure to control urban forest pests.

Abstract

American sweetgum Liquidambar styraciflua (Altingiaceae) was first introduced to China over 60 years ago. It is an important tree species for increasing landscape value and promoting afforestation in urbanized areas of eastern China in the past 20 years. Sweetgum inscriber Acanthotomicus suncei (Coleoptera: Curculionidae) is a local bark beetle pest and lethal to the introduced American sweetgum. To provide preliminary estimates of the potential economic losses caused by the sweetgum inscriber, a field investigation was conducted to survey the beetles’ natural distribution in China. Based on field collections, potential distribution was predicted using Maxent. All nurseries stocking American sweetgum were in the high and very high suitability area of sweetgum inscriber. Additionally, we employed a model of direct loss incorporating tree and removal cost. A questionnaire was sent to maintenance companies, growers, and gardener associations for tree removal prices. We estimated the removal cost of each tree. In addition, the market price and inventory were also gained from telephone interview. Our economic analysis indicates that if sweetgum inscriber were to become established in the main American sweetgum business, the potential losses of nursery stock and urban area could range from USD 12.81 to 14.41 million.

Identifying Potentially Climatic Suitability Areas for Arma custos (Hemiptera: Pentatomidae) in China under Climate Change

Spodoptera frugiperda is a notorious pest that feeds on more than 80 crops, and has spread over 100 countries. Many biological agents have been employed to regulate it, such as Arma custos. A. custos is a polyphagous predatory heteropteran, which can effectively suppress several agricultural and forest pests. Thus, in order to understand where A. custos can survive and where can be released, MaxEnt was used to predict the potentially suitable areas for A. custos in China under climate change conditions. The results show that the annual mean temperature (bio1) and annual precipitation (bio12) are the major factors influencing the distribution of A. custos. The optimal range of the two are 7.5 to 15 °C, 750 to 1200 mm, respectively. The current climate is highly suitable for A. custos in Hebei, Henan, Shandong, Anhui, Hubei, Jiangsu, and Zhejiang Provinces. Considering the currently suitable distribution area of S. frugiperda, artificially reared A. custos is suitable for release in Fujian, Zhejiang, Jiangxi, Hunan, and southeastern Sichuan Provinces. Under the future climatic scenarios, the suitable area will decrease and shift towards the north. Overall, this result can provide a reference framework for future application of A. custos for biological control.