Population models provide a logical knowledge base before conducting laborious and expensive field experiments. Historically, two types of population models have been developed: highly realistic ...simulations and simple analytical models. Highly realistic simulations comprise a complicated systems model, whereas simple analytical models comprise various analytical models that focus only on the fundamental structure of the target pest population. Although both approaches have contributed to pest management science, each has limitations, poor predictability, and lacks substantial connections to reality. Assimilation by state-space modeling, in which observation and process models are jointly incorporated, is a good compromise between a simple model and reality in nature. In the big data era, artificial intelligence (AI), specifically aimed at high predictability, has recently become popular. If vital physical and biological records are automatically censored in the field with high precision, AI will produce the most plausible predictions, providing the best practical solution given our current knowledge. AI can be a powerful tool in the contemporary world; however, deductive modeling approaches are still important when considering the behavior of AIs and may also provide important insights to detect deficient information in the data.
Although research on human-mediated exchanges of species has substantially intensified during the last centuries, we know surprisingly little about temporal dynamics of alien species accumulations ...across regions and taxa. Using a novel database of 45,813 first records of 16,926 established alien species, we show that the annual rate of first records worldwide has increased during the last 200 years, with 37% of all first records reported most recently (1970-2014). Inter-continental and inter-taxonomic variation can be largely attributed to the diaspora of European settlers in the nineteenth century and to the acceleration in trade in the twentieth century. For all taxonomic groups, the increase in numbers of alien species does not show any sign of saturation and most taxa even show increases in the rate of first records over time. This highlights that past efforts to mitigate invasions have not been effective enough to keep up with increasing globalization.
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.
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.
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 U
2
-Net; and (4) leaf segmentation with U
2
-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.
Insects often undergo regular outbreaks in population density but identifying the causal mechanism for such outbreaks in any particular species has proven difficult. Here, we show that outbreak ...cycles in the tea tortrix Adoxophyes honmai can be explained by temperature-driven changes in system stability. Wavelet analysis of a 51-year time series spanning more than 200 outbreaks reveals a threshold in outbreak amplitude each spring when temperature exceeds 15°C and a secession of outbreaks each fall as temperature decreases. This is in close agreement with our independently parameterized mathematical model that predicts the system crosses a Hopf bifurcation from stability to sustained cycles as temperature increases. These results suggest that temperature can alter system stability and provide an explanation for generation cycles in multivoltine insects.
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.
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.
Nesidiocoris tenuis
(Reuter) (Hemiptera: Miridae) is a zoophytophagous predator that feeds on plants as well as prey. Several non-crop host plant species have been used to maintain this mirid as a ...biological control agent in different crop systems. To evaluate the benefit of these non-crop host plants on biological control services, data on the life-history traits of
N. tenuis
on these plants are important as fundamental information. Herein, we studied the demographic growth parameters of
N. tenuis
reared on three alternative non-crop host plants (
Cleome hassleriana
Chod., Brassicales: Cleomaceae;
Verbena
×
hybrida
Voss, Lamiales: Verbenaceae; and
Sesamum indicum
L., Lamiales: Pedaliaceae) and one crop plant (tomato) in the absence of prey under laboratory conditions (25 ± 1 °C, 16:8 h L:D). The estimated intrinsic rate of increase in each plant was significantly greater in the following order:
S. indicum
(0.094) >
C. hassleriana
(0.074) > tomato (−0.002) >
Verbena
×
hybrida
(−0.060). The results indicated that
C. hassleriana
and
S. indicum
were able to fully support the development and reproduction of
N. tenuis
with nutrients derived from only its plant tissues, whereas
Verbena
×
hybrida
and tomato were not. Our findings revealed that
C. hassleriana
is a promising resource for the conservation or mass rearing of
N. tenuis
besides
S. indicum
.
I have constructed a simulation model applicable to both mass trapping and mating disruption for lepidopteran insect pests. The basic structure of the model is based on mass trapping model proposed ...by Knipling and McGuire (Agric Info Bull 308:1–20 1966), but this was modified to include mechanistic competition among females and lures. Several new implications are derived from the model. (1) Long‐living pests are hard to control. (2) Protandry does not improve control efficiency for pests with low survival rates. (3) Sexual communication across large distances is more difficult to control than that across a short range. (4) There is an upper limit to improvement which can be achieved by increasing the number of pheromone traps. (5) Improving the catching efficiency of traps does not improve mating suppression although improvement of lure efficiency does substantially. The last implication, in particular, has practical importance. If an efficient lure attracts males or inhibits their ability to locate females and mate, mating disruption works as well as mass trapping with the same number of lures. In such circumstances mating disruption should be preferred to mass trapping because the former does not incur the cost of the trapping devices. Mass trapping should, however, be considered in preference to mating disruption if the lure is not efficient enough and no other methods are available.
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