Historical plant introductions predict current insect invasions.

Thousands of insect species have been introduced outside of their native ranges, and some of them strongly impact ecosystems and human societies. Because a large fraction of insects feed on or are associated with plants, nonnative plants provide habitat and resources for invading insects, thereby facilitating their establishment. Furthermore, plant imports represent one of the main pathways for accidental nonnative insect introductions. Here, we tested the hypothesis that plant invasions precede and promote insect invasions. We found that geographical variation in current nonnative insect flows was best explained by nonnative plant flows dating back to 1900 rather than by more recent plant flows. Interestingly, nonnative plant flows were a better predictor of insect invasions than potentially confounding socioeconomic variables. Based on the observed time lag between plant and insect invasions, we estimated that the global insect invasion debt consists of 3,442 region-level introductions, representing a potential increase of 35% of insect invasions. This debt was most important in the Afrotropics, the Neotropics, and Indomalaya, where we expect a 10 to 20-fold increase in discoveries of new nonnative insect species. Overall, our results highlight the strong link between plant and insect invasions and show that limiting the spread of nonnative plants might be key to preventing future invasions of both plants and insects.

Alien insect dispersal mediated by the global movement of commodities.

Globalization and economic growth are recognized as key drivers of biological invasions. Alien species have become a feature of almost every biological community worldwide, and rates of new introductions continue to rise as the movement of people and goods accelerates. Insects are among the most numerous and problematic alien organisms, and are mainly introduced unintentionally with imported cargo or arriving passengers. However, the processes occurring prior to insect introductions remain poorly understood. We used a unique dataset of 1,902,392 border interception records from inspections at air, land, and maritime ports in Australia, New Zealand, Europe, Japan, USA, and Canada to identify key commodities associated with insect movement through trade and travel. In total, 8939 species were intercepted, and commodity association data were available for 1242 species recorded between 1960 and 2019. We used rarefaction and extrapolation methods to estimate the total species richness and diversity associated with different commodity types. Plant and wood products were the main commodities associated with insect movement across cargo, passenger baggage, and international mail. Furthermore, certain species were mainly associated with specific commodities within these, and other broad categories. More closely related species tended to share similar commodity associations, but this occurred largely at the genus level rather than within orders or families. These similarities within genera can potentially inform pathway management of new alien species. Combining interception records across regions provides a unique window into the unintentional movement of insects, and provides valuable information on establishment risks associated with different commodity types and pathways.

Worldwide border interceptions provide a window into human-mediated global insect movement.

As part of national biosecurity programs, cargo imports, passenger baggage, and international mail are inspected at ports of entry to verify compliance with phytosanitary regulations and to intercept potentially damaging nonnative species to prevent their introduction. Detection of organisms during inspections may also provide crucial information about the species composition and relative arrival rates in invasion pathways that can inform the implementation of other biosecurity practices such as quarantines and surveillance. In most regions, insects are the main taxonomic group encountered during inspections. We gathered insect interception data from nine world regions collected from 1995 to 2019 to compare the composition of species arriving at ports in these regions. Collectively, 8,716 insect species were intercepted in these regions over the last 25 yr, with the combined international data set comprising 1,899,573 interception events, of which 863,972 were identified to species level. Rarefaction analysis indicated that interceptions comprise only a small fraction of species present in invasion pathways. Despite differences in inspection methodologies, as well as differences in the composition of import source regions and imported commodities, we found strong positive correlations in species interception frequencies between regions, particularly within the Hemiptera and Thysanoptera. There were also significant differences in species frequencies among insects intercepted in different regions. Nevertheless, integrating interception data among multiple regions would be valuable for estimating invasion risks for insect species with high likelihoods of introduction as well as for identifying rare but potentially damaging species.

Global rise in emerging alien species results from increased accessibility of new source pools.

Our ability to predict the identity of future invasive alien species is largely based upon knowledge of prior invasion history. Emerging alien species-those never encountered as aliens before-therefore pose a significant challenge to biosecurity interventions worldwide. Understanding their temporal trends, origins, and the drivers of their spread is pivotal to improving prevention and risk assessment tools. Here, we use a database of 45,984 first records of 16,019 established alien species to investigate the temporal dynamics of occurrences of emerging alien species worldwide. Even after many centuries of invasions the rate of emergence of new alien species is still high: One-quarter of first records during 2000-2005 were of species that had not been previously recorded anywhere as alien, though with large variation across taxa. Model results show that the high proportion of emerging alien species cannot be solely explained by increases in well-known drivers such as the amount of imported commodities from historically important source regions. Instead, these dynamics reflect the incorporation of new regions into the pool of potential alien species, likely as a consequence of expanding trade networks and environmental change. This process compensates for the depletion of the historically important source species pool through successive invasions. We estimate that 1-16% of all species on Earth, depending on the taxonomic group, qualify as potential alien species. These results suggest that there remains a high proportion of emerging alien species we have yet to encounter, with future impacts that are difficult to predict.

Disentangling the drivers of invasion spread in a vector-borne tree disease.

Pine wilt disease (PWD) invaded southern Japan in the early 1900s and has gradually expanded its range to northern Honshu (Japanese mainland). The disease is caused by a pathogenic North American nematode, which is transmitted by native pine sawyer beetles. Recently, the disease has invaded other portions of East Asia and Europe where extensive mortality of host pines is anticipated to resemble historical patterns seen in Japan. There is a critical need to identify the main drivers of PWD invasion spread so as to predict the future spread and evaluate containment strategies in newly invaded world regions. But the coupling of pathogen and vector population dynamics introduces considerable complexity that is important for understanding this and other plant disease invasions. In this study, we analysed historical (1980-2011) records of PWD infection and vector abundance, which were spatially extensive but recorded at coarse categorical levels (none, low and high) across 403 municipalities in northern Honshu. We employed a multistate occupancy model that accounted both for demographic stochasticity and observation errors in categorical data. Analysis revealed that sparse sawyer populations had lower probabilities of transition to high abundance than did more abundant populations even when regional abundance stayed the same, suggesting the existence of positive density dependence, that is an Allee effect, in sawyer dynamics. Climatic conditions (average accumulated degree days) substantially limited invasion spread in northern regions, but this climatic influence on sawyer dynamics was generally weaker than the Allee effect. Our results suggest that tactics (eg sanitation logging of infected pines) which strengthen Allee effects in sawyer dynamics may be effective strategies for slowing the spread of PWD.

Eradication of Invading Insect Populations: From Concepts to Applications.

Eradication is the deliberate elimination of a species from an area. Given that international quarantine measures can never be 100% effective, surveillance for newly arrived populations of nonnative species coupled with their eradication represents an important strategy for excluding potentially damaging insect species. Historically, eradication efforts have not always been successful and have sometimes been met with public opposition. But new developments in our understanding of the dynamics of low-density populations, the availability of highly effective treatment tactics, and bioeconomic analyses of eradication strategies offer new opportunities for developing more effective surveillance and eradication programs. A key component that connects these new developments is the harnessing of Allee effects, which naturally promote localized species extinction. Here we review these developments and suggest how research might enhance eradication strategies.

Characteristic features of statistical models and machine learning methods derived from pest and disease monitoring datasets.

While many studies have used traditional statistical methods when analysing monitoring data to predict future population dynamics of crop pests and diseases, increasing studies have used machine learning methods. The characteristic features of these methods have not been fully elucidated and arranged. We compared the prediction performance between two statistical and seven machine learning methods using 203 monitoring datasets recorded over several decades on four major crops in Japan and meteorological and geographical information as the explanatory variables. The decision tree and random forest of machine learning were found to be most efficient, while regression models of statistical and machine learning methods were relatively inferior. The best two methods were better for biased and scarce data, while the statistical Bayesian model was better for larger dataset sizes. Therefore, researchers should consider data characteristics when selecting the most appropriate method.

Generation separation in simple structured life cycles: models and 48 years of field data on a tea tortrix moth.

Population cycles have fascinated ecologists since the early nineteenth century, and the dynamics of insect populations have been central to understanding the intrinsic and extrinsic biological processes responsible for these cycles. We analyzed an extraordinary long-term data set (every 5 days for 48 years) of a tea tortrix moth (Adoxophyes honmai) that exhibits two dominant cycles: an annual cycle with a conspicuous pattern of four or five single-generation cycles superimposed on it. General theory offers several candidate mechanisms for generation cycles. To evaluate these, we construct and parameterize a series of temperature-dependent, stage-structured models that include intraspecific competition, parasitism, mate-finding Allee effects, and adult senescence, all in the context of a seasonal environment. By comparing the observed dynamics with predictions from the models, we find that even weak larval competition in the presence of seasonal temperature forcing predicts the two cycles accurately. None of the other mechanisms predicts the dynamics. Detailed dissection of the results shows that a short reproductive life span and differential winter mortality among stages are the additional life-cycle characteristics that permit the sustained cycles. Our general modeling approach is applicable to a wide range of organisms with temperature-dependent life histories and is likely to prove particularly useful in temperate systems where insect pest outbreaks are both density and temperature dependent.

Bioeconomic synergy between tactics for insect eradication in the presence of Allee effects.

Preventing the establishment of invading pest species can be beneficial with respect to averting future environmental and economic impacts and also in preventing the accumulation of control costs. Allee effects play an important role in the dynamics of newly established, low-density populations by driving small populations into self-extinction, making Allee effects critical in influencing outcomes of eradication efforts. We consider interactions between management tactics in the presence of Allee effects to determine cost-effective and time-efficient combinations to achieve eradication by developing a model that considers pesticide application, predator augmentation and mating disruption as control tactics, using the gypsy moth as a case study. Our findings indicate that given a range of constant expenditure levels, applying moderate levels of pesticides in conjunction with mating disruption increases the Allee threshold which simultaneously substantially decreases the time to eradication relative to either tactic alone. In contrast, increasing predation in conjunction with other tactics requires larger economic expenditures to achieve similar outcomes for the use of pesticide application or mating disruption alone. These results demonstrate the beneficial synergy that may arise from nonlinearities associated with the simultaneous application of multiple eradication tactics and offer new prospects for preventing the establishment of damaging non-native species.

Model analysis for plant disease dynamics co-mediated by herbivory and herbivore-borne phytopathogens.

Plants are subject to diseases caused by pathogens, many of which are transmitted by herbivorous arthropod vectors. To understand plant disease dynamics, we studied a minimum hybrid model combining consumer-resource (herbivore-plant) and susceptible-infected models, in which the disease is transmitted bi-directionally between the consumer and the resource from the infected to susceptible classes. Model analysis showed that: (i) the disease is more likely to persist when the herbivore feeds on the susceptible plants rather than the infected plants, and (ii) alternative stable states can exist in which the system converges to either a disease-free or an endemic state, depending on the initial conditions. The second finding is particularly important because it suggests that the disease may persist once established, even though the initial prevalence is low (i.e. the R(0) rule does not always hold). This situation is likely to occur when the infection improves the plant nutritive quality, and the herbivore preferentially feeds on the infected resource (i.e. indirect vector-pathogen mutualism). Our results highlight the importance of the eco-epidemiological perspective that integration of tripartite interactions among host plant, plant pathogen and herbivore vector is crucial for the successful control of plant diseases.

Long-term survey of longhorn beetles revealed changes in faunal features in Ito on the Izu peninsula.

Long-term biodiversity monitoring is essential for unveiling the impact of environmental changes on local fauna. Although private local records can contribute significantly to biodiversity evaluation, they are seldom published in scientific journals. In this study, a retired scientist recorded the longhorn beetles (Distiniidae and Cerambycidae) present in Ito on the Izu peninsula, Japan, for 12 years. The records showed the dynamical changes in longhorn beetles, which indicated the environmental changes around the survey site over 12 years. We also compared the longhorn beetle composition in the Ito study site to those in the survey records in 13 other locations in Kanto, Japan. We found that the species composition in Ito was stable throughout the 12 years, while the general composition in Ito reflected the land-use pattern of urban areas and the collecting methods. The species composition in the Ito study site differed from that in some of the other satoyama locations (human-influenced natural environment), but this was possibly due to methodological differences. Long-term backyard biodiversity surveys, especially those conducted by retired professionals, can play important roles in future investigations of insect groups, such as longhorn beetles, even if they are not agricultural pests nor endangered species.

JustDeepIt: Software tool with graphical and character user interfaces for deep learning-based object detection and segmentation in image analysis.

Image processing and analysis based on deep learning are becoming mainstream and increasingly accessible for solving various scientific problems in diverse fields. However, it requires advanced computer programming skills and a basic familiarity with character user interfaces (CUIs). Consequently, programming beginners face a considerable technical hurdle. Because potential users of image analysis are experimentalists, who often use graphical user interfaces (GUIs) in their daily work, there is a need to develop GUI-based easy-to-use deep learning software to support their work. Here, we introduce JustDeepIt, a software written in Python, to simplify object detection and instance segmentation using deep learning. JustDeepIt provides both a GUI and a CUI. It contains various functional modules for model building and inference, and it is built upon the popular PyTorch, MMDetection, and Detectron2 libraries. The GUI is implemented using the Python library FastAPI, simplifying model building for various deep learning approaches for beginners. As practical examples of JustDeepIt, we prepared four case studies that cover critical issues in plant science: (1) wheat head detection with Faster R-CNN, YOLOv3, SSD, and RetinaNet; (2) sugar beet and weed segmentation with Mask R-CNN; (3) plant segmentation with U2-Net; and (4) leaf segmentation with U2-Net. The results support the wide applicability of JustDeepIt in plant science applications. In addition, we believe that JustDeepIt has the potential to be applied to deep learning-based image analysis in various fields beyond plant science.

A feasibility trial of genomics-based diagnosis detecting insecticide resistance of the diamondback moth.

BACKGROUND: Insecticide resistance management has been key for crop protection for over 70 years and is increasingly important because the development of new active ingredients has decreased in recent years. By monitoring the development of resistance in a timely manner, we can effectively prolong insecticide efficacy. Genomic-based diagnosis can reliably predict resistance development if information on resistant mutations against major pesticides is available. Here, we developed a feasibility trial of genomics-based diagnosis of insecticide resistance in diamondback moth (Plutella xylostella) populations in Nagano Prefecture, Japan. Amplicon sequencing analyses using a next-generation sequencer (Illumina MiSeq) for major insecticides, including diamides, pyrethroids, Bacillus thuringiensis (Bt) toxin (Cry1Ac), organophosphates, and spinosyns, were conducted. RESULTS: Mutations related to the resistance of pyrethroids, organophosphates, and diamides (flubendiamide and chlorantraniliprole) prevailed, while those of a diamide (cyantraniliprole), Bt (Cry1Ac), and spinosyns were scanty, suggesting that they are still effective. The results of the genomics-based diagnosis were generally concordant with the results of bioassays. Resistance development tendencies were generally uniform across Nagano. CONCLUSION: An insecticide-resistance management campaign can be conducted in Nagano Prefecture with a quick genomic-based diagnosis in early spring while bioassay is the only option for monitoring resistances whose mutations are unavailable. Our study is the first step in the future management of insecticide resistance in all significant pests. © 2022 Society of Chemical Industry.

Estimating the proportion of resistance alleles from bulk Sanger sequencing, circumventing the variability of individual DNA.

Specimens should be examined as much as possible to obtain a precise estimate of the proportion of resistance alleles in agricultural fields. Monitoring traps that use semiochemicals on sticky sheets are helpful in this regard. However, insects captured by such traps are ordinarily left in the field until collection. Owing to DNA degradation, the amount of DNA greatly varies among insects, causing serious problems in obtaining maximum likelihood estimates and confidence intervals of the proportion of the resistance alleles. We propose a statistical procedure that can circumvent this degradation issue. R scripts for the calculation are provided for readers. We also propose the utilization of a Sanger sequencer. We demonstrate these procedures using field samples of diamide-resistant strains of the diamondback moth, Plutella xylostella (Lepidoptera: Plutellidae). The validity of the assumptions used in the statistical analysis is examined using the same data.

Hidden patterns of insect establishment risk revealed from two centuries of alien species discoveries.

Understanding the socioeconomic drivers of biological invasion informs policy development for curtailing future invasions. While early 20th-century plant trade expansions preceded increased establishments of plant pests in Northern America, increased establishments did not follow accelerating imports later that century. To explore this puzzle, we estimate the historical establishment of plant-feeding Hemiptera in Northern America as a function of historical U.S. imports of live plants from seven world regions. Delays between establishment and discovery are modeled using a previously unused proxy for dynamic discovery effort. By recovering the timing of pest arrivals from their historical discoveries, we disentangle the joint establishment-discovery process. We estimate long delays to discovery, which are partially attributable to the low detectability of less economically important insect species. We estimate that many introduced species remain undiscovered, ranging from around one-fifth for Eurasian regions to two-fifths for Central and South America.

Factors affecting flight activity of Ophraella communa (Coleoptera: Chrysomelidae), an exotic insect in Japan.

The exotic beetle Ophraella communa LeSage was first found in 1996 in Japan and has rapidly expanded its distribution. This study examined the effect of several factors on the flight activity of this beetle and estimated its dispersal potential by measuring its flight time on a flight mill system. The beetles exhibited low flight activity at the age of 1-3 d posteclosion; however, after 4 d, it increased and thereafter remained high. The beetles reduced flight activity under the dark photophase, although they flew during both light and dark phases. Flight activity was lower in adults reared from hatching under a 12:12 (L:D)-h photoperiod than in those reared under a 16:8-h photoperiod; the shorter photoperiod was found to induce reproductive diapause. This photoperiodic response could explain seasonal changes in flight activities in which fourth-generation adults displayed the lowest activity before overwintering. The female beetles flew, at maximum, for 385 min during a 23-h experimental period. Based on this value, the flight distance was estimated to be 25 km/23 h, suggesting a high dispersal potential of this beetle.

Anatomical Links between White Matter Hyperintensity and Medial Temporal Atrophy Reveal Impairment of Executive Functions.

Although several studies have demonstrated correlation between white matter hyperintensities (WMH) and impairment of executive functions, the underlying anatomical-functional relationships are not fully understood. The present study sought to investigate the correlations between the volume of WMH and medial temporal lobe atrophy (MTA) using quantitative magnetic resonance image (MRI) and a variety of executive function assessments. A total of 91 patients ranging in age from 58 to 90 years with mild cognitive impairment (MCI) due to Alzheimer's disease (AD) or early phase AD were recruited from the outpatient clinic at the Department of Neurology of Nagoya City University Hospital. We administered neuropsychological batteries evaluating verbal memory, orientation, spatial ability, sustained attention, and a variety of executive functions, including verbal fluency, flexibility, inhibition, and working memory. Quantitative MRI analyses were performed using Dr. View/Linux software and a voxel-based specific regional analysis system. Significant correlations were observed between WMH, as well as MTA, and some executive function scores. Regression analysis revealed that MTA was the strongest predictor of flexibility and verbal fluency. These findings provide new insight into the relationship between quantitative MRI analyses and various types of executive dysfunction in elderly people with MCI due to AD and/or early phase AD. When cognitive function is examined in elderly patients with MCI due to AD or early phase AD, it is important to consider the involvement of WMH and MTA, which is indicative of AD pathology in cognitive dysfunction, particularly executive function.

Adaptation to the new land or effect of global warming? An age-structured model for rapid voltinism change in an alien lepidopteran pest.

1. Hyphantria cunea Drury invaded Japan at Tokyo in 1945 and expanded its distribution gradually into northern and south-western Japan. All populations in Japan were bivoltine until the early 1970s, at which time trivoltine populations appeared in several southern regions. Presently, H. cunea exists as separate bivoltine and trivoltine populations divided around latitude 36 degrees . In the course of this voltinism change, the mean surface temperature in Japan rose by 1.0 degrees C. 2. To determine whether and how this temperature increase might be responsible for the voltinism change, we constructed an age-structured model incorporating growth speed driven by actual daily temperature and detailed mechanisms of diapause induction triggered by both daily photoperiod and temperature. 3. The simulation result suggests that both the acceleration of the growth speed and the prolongation of diapause induction are necessary to cause changes in voltinism, regardless of temperature increase. We concluded that the H. cunea population changed its life-history traits as an adaptation parallel with its invasion into the south-western parts of Japan. 4. Though the temperature increase had little effect on the fitness and heat stress in bivoltine and trivoltine populations, the trivoltine life cycle has become advantageous at least in marginal regions such as Tokyo.

Optimal management strategy of insecticide resistance under various insect life histories: Heterogeneous timing of selection and interpatch dispersal.

Although theoretical studies have shown that the mixture strategy, which uses multiple toxins simultaneously, can effectively delay the evolution of insecticide resistance, whether it is the optimal management strategy under different insect life histories and insecticide types remains unknown. To test the robustness of this management strategy over different life histories, we developed a series of simulation models that cover almost all the diploid insect types and have the same basic structure describing pest population dynamics and resistance evolution with discrete time steps. For each of two insecticidal toxins, independent one-locus two-allele autosomal inheritance of resistance was assumed. The simulations demonstrated the optimality of the mixture strategy either when insecticide efficacy was incomplete or when some part of the population disperses between patches before mating. The rotation strategy, which uses one insecticide on one pest generation and a different one on the next, did not differ from sequential usage in the time to resistance, except when dominance was low. It was the optimal strategy when insecticide efficacy was high and premating selection and dispersal occur.

Plant diversity drives global patterns of insect invasions.

During the last two centuries, thousands of insect species have been transported (largely inadvertently) and established outside of their native ranges worldwide, some with catastrophic ecological and economic impacts. Global variation in numbers of invading species depends on geographic variation in propagule pressure and heterogeneity of environmental resistance to invasions. Elton's diversity-invasibility hypothesis, proposed over sixty years ago, has been widely explored for plants but little is known on how biodiversity affects insect invasions. Here we use species inventories from 44 land areas, ranging from small oceanic islands to entire continents in various world regions, to show that numbers of established insect species are primarily driven by diversity of plants, with both native and non-native plant species richness being the strongest predictor of insect invasions. We find that at large spatial scales, plant diversity directly explains variation in non-native insect species richness among world regions, while geographic factors such as land area, climate and insularity largely affect insect invasions indirectly via their effects on local plant richness.