MaxEnt modeling to predict current and future distributions of Batocera lineolata (Coleoptera: Cerambycidae) under climate change in China

Ecological forecasts of insect range dynamics: a broad range of taxa includes winners and losers under future climate

Species distribution models are the primary tools to project future species' distributions, but this complex task is influenced by data limitations and evolving best practices. The majority of the 53 studies we examined utilized correlative models and did not follow current best practices for validating retrospective or future environmental data layers. Despite this, a summary of results is largely unsurprising: shifts toward cooler regions, but otherwise mixed dynamics emphasizing winners and losers. Harmful insects were more likely to show positive outcomes compared with beneficial species. Our restricted ability to consider mechanisms complicates interpretation of any single study. To improve this area of modeling, more classic field and lab studies to uncover basic ecology and physiology are crucial.

Potential impact of climatic factors on the distribution of Graphium sarpedon in China

Graphium sarpedon is a significant foliar pest of Laurel plants in China. In this study, the MaxEnt model was used to investigate the distribution of G. sarpedon and predict its potential distribution areas in China in the future (2050s and 2090s) based on three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5), and key environmental variables affecting its distribution were identified. The results showed that under the current climatic conditions, the suitable distribution areas of G. sarpedon were 92.17°-134.96° E and 18.04°-33.61° N, including Yangtze Plain (Middle and Lower), Pearl River Delta, Yangtze River Delta, and Lingnan areas. Under the future climate conditions, the total suitable distribution area of G. sarpedon decreased, but the area of medium suitable area increased. The study identified 11 key environmental variables affecting the distribution of G. sarpedon, the most critical of which was Precipitation of Warmest Quarter (bio18) and precipitation in April, May, June, and September (prec4, prec5, prec6, and prec9). This study is beneficial for monitoring and preventing the possible changes of G. sarpedon and provides theoretical references for its prevention and control.

SMRT Sequencing Technology Was Used to Construct the Batocera horsfieldi (Hope) Transcriptome and Reveal Its Features

Batocera horsfieldi (Hope) (Coleoptera: Cerambycidae) is an important forest pest in China that mainly infests timber and economic forests. This pest primarily causes plant tissue to necrotize, rot, and eventually die by feeding on the woody parts of tree trunks. To gain a deeper understanding of the genetic mechanism of B. horsfieldi, this study employed single-molecule real-time sequencing (SMRT) and Illumina RNA-seq technologies to conduct full-length transcriptome sequencing of the insect. Total RNA extracted from male and female adults was mixed and subjected to SMRT sequencing, generating a complete transcriptome. Transcriptome analysis, prediction of long non-coding RNA (lncRNA), coding sequences (CDs), analysis of simple sequence repeats (SSR), prediction of transcription factors, and functional annotation of transcripts were performed in this study. The collective 20,356,793 subreads (38.26 G, clean reads) were generated, including 432,091 circular consensus sequences and 395,851 full-length non-chimera reads. The full-length non-chimera reads (FLNC) were clustered and redundancies were removed, resulting in 39,912 consensus reads. SSR and ANGEL software v3.0 were used for predicting SSR and CDs. In addition, four tools were used for annotating 6058 lncRNAs, identifying 636 transcription factors. Furthermore, a total of 84,650 transcripts were functionally annotated in seven different databases. This is the first time that the full-length transcriptome of B. horsfieldi has been obtained using SMRT sequencing. This provides an important foundation for investigating the gene regulation underlying the interaction between B. horsfieldi and its host plants through gene editing in the future and provides a scientific basis for the prevention and control of B. horsfieldi.

Predicting the Impact of Climate Change on the Geographical Distribution of Leafhopper, Cicadella viridis in China through the MaxEnt Model

Cicadella viridis (Hemiptera: Cicadellidae) is an omnivorous leafhopper that feeds on plant sap. It significantly reduces the yield of agricultural and forestry crops while feeding or ovipositing on the host plant. In recent years, the rapid expansion of C. viridis has posed a serious threat to agricultural and forestry crops. To study the impact of climate change on the geographical distribution of the leafhopper, the maximum entropy (MaxEnt) model and ArcGIS software, combined with 253 geographic distribution records of the pest and 24 environmental variables, were used, for the first time, to predict the potential distribution of C. viridis in China under conditions of climatic change. The results showed that the currently suitable areas for C. viridis are 29.06-43° N, 65.25-85.15° E, and 93.45-128.85° E, with an estimated area of 11,231,423.79 km², i.e., 11.66% of China. The Loess Plateau, the North China Plain, and the Shandong Peninsula are the main suitable areas. The potential distribution of the leafhopper for the high and medium suitability areas decreased under each climate scenario (except RCP8.5 in the 2090s). Several key variables that have the most significant effect on the distribution of C. viridis were identified, including the mean annual temperature (Bio1), the standard deviation of temperature seasonality (Bio4), the minimum temperature of the coldest month (Bio6), and the precipitation of the coldest quarter (Bio19). Our research provides important guidance for developing effective monitoring and pest control methods for C. viridis, given the predicted challenges of altered pest dynamics related to future climate change.

Potentially Suitable Geographical Area for Monochamus alternatus under Current and Future Climatic Scenarios Based on Optimized MaxEnt Model

M. alternatus is considered to be an important and effective insect vector for the spread of the important international forest quarantine pest, Bursaphelenchus xylophilus. The precise determination of potential suitable areas of M. alternatus is essential to monitor, prevent, and control M. alternatus worldwide. According to the distribution points and climatic variables, the optimized MaxEnt model and ArcGIS were used to predict the current and future potentially suitable areas of M. alternatus worldwide. The optimized MaxEnt model parameters were set as feature combination (FC) = LQHP and β = 1.5, which were determined by the values of AUC_diff, OR₁₀, and ΔAICc. Bio2, Bio6, Bio10, Bio12, and Bio14 were the dominant bioclimatic variables affecting the distribution of M. alternatus. Under the current climate conditions, the potentially suitable habitats of M. alternatus were distributed across all continents except Antarctica, accounting for 4.17% of the Earth's total land area. Under future climate scenarios, the potentially suitable habitats of M. alternatus increased significantly, spreading to a global scale. The results of this study could provide a theoretical basis for the risk analysis of the global distribution and dispersal of M. alternatus as well as the precise monitoring and prevention of this beetle.

Predicting the potential suitable distribution area of Emeia pseudosauteri in Zhejiang Province based on the MaxEnt model

Human activities, including urbanization, industrialization, agricultural pollution, and land use, have contributed to the increased fragmentation of natural habitats and decreased biodiversity in Zhejiang Province as a result of socioeconomic development. Numerous studies have demonstrated that the protection of ecologically significant species can play a crucial role in restoring biodiversity. Emeia pseudosauteri is regarded as an excellent environmental indicator, umbrella and flagship species because of its unique ecological attributes and strong public appeal. Assessing and predicting the potential suitable distribution area of this species in Zhejiang Province can help in the widespread conservation of biodiversity. We used the MaxEnt ecological niche model to evaluate the habitat suitability of E. pseudosauteri in Zhejiang Province to understand the potential distribution pattern and environmental characteristics of suitable habitats for this species, and used the AUC (area under the receiver operating characteristic curve) and TSS (true skill statistics) to evaluate the model performance. The results showed that the mean AUC value was 0.985, the standard deviation was 0.011, the TSS average value was 0.81, and the model prediction results were excellent. Among the 11 environmental variables used for modeling, temperature seasonality (Bio_4), altitude (Alt) and distance to rivers (Riv_dis) were the key variables affecting the distribution area of E. pseudosauteri, with contributions of 33.5%, 30% and 15.9%, respectively. Its main suitable distribution area is in southern Zhejiang Province and near rivers, at an altitude of 50-300 m, with a seasonal variation in temperature of 7.7-8 °C. Examples include the Ou River, Nanxi River, Wuxi River, and their tributary watersheds. This study can provide a theoretical basis for determining the scope of E. pseudosauteri habitat protection, population restoration, resource management and industrial development in local areas.

Prediction of the Current and Future Distributions of the Hessian Fly, Mayetiola destructor (Say), under Climatic Change in China

The Hessian fly, Mayetiola destructor (Say) (Diptera: Cecidomyiidae), is a destructive wheat pest worldwide and an important alien species in China. Based on 258 distribution records and nine environmental factors of the Hessian fly, we predicted the potential distribution area in China under three current and future (2050s and 2070s) climate change scenarios (RCP2.6, RCP4.5, and RCP8.5) via the optimized MaxEnt model. Under the current climate conditions, the suitable distribution areas of the Hessian fly in China were 25-48° N, 81-123° E, and the total highly suitable distribution area is approximately 9.63 × 10⁵ km², accounting for 9.99% of the total national area. The highly suitable areas are mainly located in northern Xinjiang and central and eastern China. With the rising global temperatures, except for the high-suitable areas under the RCP8.5 scenario, most potential geographic distribution areas would expand in the future. The minimum temperature in February (tmin-2), precipitation in March (prec-3), maximum temperature in November (tmax-11), and precipitation seasonality (bio-15) are important factors that affect the potential geographic distribution of the Hessian fly. This study provides an important reference and empirical basis for management of the Hessian fly in the future.

Modeling the potential distribution of different types of Dendrocalamus sinicus, the strongest woody bamboo in the world, with MaxEnt model

Climate change will significantly affect the distribution area of species. Through establishing distribution model, we can simulate the current and future potential distribution range and provide reference for the introduction and cultivation planning of rare or economic plants. Dendrocalamus sinicus, endemic to Yunnan Province of China, is the strongest woody bamboo in the world. In the present study, the MaxEnt model was performed to simulate the distribution of different types of D. sinicus in China and neighboring countries or regions. The results suggested that the suitable distribution range of "straight type", the main type for cultivation and utilization, was 8°-30°N and 73°-122°E under the current climate conditions, while the potential distribution range of "bending type" was 6°-31°N and 79°-109°E. The two most key climate variables associated with distribution of "straight type" were "Temperature Annual Range" with 36.6% contribution rate and "Temperature Seasonality" (32.4%), while "Isothermality" (47.8%) and "Precipitation of Driest Month" (24.8%) for "bending type". Under different climate change scenarios (SSP1-2.6, SSP5-8.5) and periods (2050, 2090), the potential distribution area of the "straight type" were apparently different, indicating that the distribution area of D. sinicus will be affected significantly by climate changes in the future. Our findings would be not only beneficial to understanding limiting factors for natural distribution of D. sinicus, but also helpful for further germplasm conservation, introduction and cultivation planning of this rare woody bamboo.

Modeling and Prediction of the Species’ Range of Neurobasis chinensis (Linnaeus, 1758) under Climate Change

Simple Summary

Global climate change is accelerating and modifying the distribution of many extant species. Dragonflies, as a group, inhabit aquatic as well as terrestrial environments and are considered sensitive climate change indicators. In this study, we model and predict the range of a large, tropical damselfly Neurobasis chinensis L. under the last glacial maximum (LGM), the current, and four future warming scenarios. The models show that the species mainly occupies forest ecosystems below 1200 m (preferring 500 to 1200 m) and had two historic core distribution areas in LGM, one of which survived, namely south-central Vietnam. The future scenarios show that the core distribution, high suitable habitats, and even the whole species range of N. chinensis will extend northwards.

Abstract

Neurobasis chinensis is widely distributed in eastern tropical Asia. Its only congener in China, the N. anderssoni, has not been observed for decades. To protect N. chinensis, it is necessary to understand the ecological properties of its habitats and specie’s range shift under climate change. In the present study, we modeled its potential distribution under one historical, current, and four future scenarios. We evaluated the importance of the factors that shape its distribution and habitats and predicted the historical and current core spatial distributions and their shifting in the future. Two historical core distribution areas were identified: the inland region of the Bay of Bengal and south-central Vietnam. The current potential distribution includes south China, Vietnam, Laos, Thailand, Myanmar, Luzon of Philippines, Malaysia, southwest and northeast India, Sri Lanka, Indonesia (Java, Sumatera), Bangladesh, Nepal, Bhutan, and foothills of the Himalayas, in total, ca. 3.59 × 10⁶ km². Only one core distribution remained, concentrated in south-central Vietnam. In a warming future, the core distribution, high suitable habitats, and even the whole range of N. chinensis will expand and shift northwards. Currently, N. chinensis mainly resides in forest ecosystems below 1200 m above sea level (preferred 500 m to 1200 m a.s.l.). Annual precipitation, mean temperature of driest quarter, and seasonality of precipitation are important factors shaping the species distribution. Our study provides systematic information on habitats and geographical distribution, which is useful for the conservation of N. chinensis.

Climate Change and Major Pests of Mediterranean Olive Orchards: Are We Ready to Face the Global Heating?

Simple Summary

The phenomenon of climate change affects the entire world, especially the most vulnerable areas such as the Mediterranean. Since the olive growing is one of the main economic sources for the Mediterranean countries, investigations on olive pests under global heating are necessary. Nowadays, knowledge on the topic is scarce, and nothing is known about the effects of climate change on olive pest parasitoids and predators. This information could be fundamental to understand the phenomena of pest outbreaks that are spreading in the Mediterranean olive orchards. The use of prevention tools (e.g., monitoring, prediction models) may help in controlling olive pests under a climate change scenario.

Abstract

Evidence of the impact of climate change on natural and agroecosystems is nowadays established worldwide, especially in the Mediterranean Basin, an area known to be very susceptible to heatwaves and drought. Olea europaea is one of the main income sources for the Mediterranean agroeconomy, and it is considered a sensitive indicator of the climate change degree because of the tight relationship between its biology and temperature trend. Despite the economic importance of the olive, few studies are nowadays available concerning the consequences that global heating may have on its major pests. Among the climatic parameters, temperature is the key one influencing the relation between the olive tree and its most threatening parasites, including Bactrocera oleae and Prays oleae. Therefore, several prediction models are based on this climatic parameter (e.g., cumulative degree day models). Even if the use of models could be a promising tool to improve pest control strategies and to safeguard the Mediterranean olive patrimony, they are not currently available for most O. europaea pests, and they have to be used considering their limits. This work stresses the lack of knowledge about the biology and the ethology of olive pests under a climate change scenario, inviting the scientific community to focus on the topic.

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.