Pest Population Dynamics Research Articles

Impact of Climate Change on Peach Fruit Moth Phenology: A Regional Perspective from China.

It is widely recognized that the phenology of insects, of which the life activities are closely tied to temperature, is shifting in response to global climate warming. This study aimed to investigate the impacts of climate change on the phenology of Carposina sasakii Matsumura, 1900 (Lepidoptera: Carposinidae) across large temporal and spatial scales, through collecting and systematically analyzing historical data on the pest's occurrence and population dynamics in China. The results showed that for overwintering adults, the first occurrence date in eastern, northwestern, and northern China has significantly advanced, along with the population peak in eastern and northwestern China. At the provincial level, the population peak date in Shandong province has also moved significantly earlier, as well as the population peak date in Shandong and Shaanxi and the end occurrence date in Ningxia. However, the population peak date in Jilin has experienced a delayed trend. For first-generation adults, the first occurrence date in northeastern, eastern, and central China has notably advanced, while the first appearance date in northwestern and northern China has significantly delayed. Additionally, the population peak in northwestern China has experienced significant delays, along with the final occurrence in northeastern and northwestern China. At the provincial level, the first occurrence date in Liaoning, Shandong, and Shanxi has significantly advanced, while Hebei has demonstrated a significant delay. The population peak time in Gansu and Shaanxi has displayed significant delays, and the end occurrence date in Liaoning, Shanxi, and Shaanxi has also shown significant delays. Furthermore, these findings integrated with the Pearson correlation results reveal spatial heterogeneity in C. sasakii's phenological responses to climate warming at both regional and provincial scales. The phenology of C. sasakii and their changing patterns with climate warming vary by geographical location. This study provides valuable information for the future monitoring, prediction, and prevention of peach fruit moths in the context of climate warming.

Population dynamics and diversity of pests and natural enemies in various organic rice regimes across different phenological stages in rice

A field study was conducted at the ICAR-Indian Institute of Rice Research to investigate insect pest populations and their natural enemies in different organic rice modules during the rabi 2020 season. Three organic rice regimes, farmers’ practice and untreated control were compared across three phenological stages in rice for the population dynamics of pests and natural enemies of Hemiptera and Hymenoptera. Sampling was done fortnightly for three months using various methods such as visual counting, sticky traps, sweep netting, and D-net. Pest and predator populations peaked during the vegetative stage, while parasitoids peaked during the reproductive stage. Pest population means were highest in untreated control during the reproductive and ripening stages exhibiting the impact of treatments. The predator population was highest in untreated control during the vegetative and reproductive stage, while parasitoid population size was highest in Pseudomonas treatment in the vegetative and reproduction stages of the crop and the Trichoderma treatment in the ripening stage. Predator diversity was highest in untreated control during vegetative and reproductive stages of the crop while parasitoid diversity was maximum during reproductive and ripening stage. Pearson’s correlation coefficient between the population of pests and natural enemies was found to be positive and highly significant.

Impact of Weather Parameters on the Population Fluctuation of Major Sucking Pest in Summer Mung Bean [Vigna radiata (L.) Wilczek

Background: Mungbean may be grown in an extensive range of agro climatic zones in India and across the world. It is a crucial component of our diet. Because of its capacity to fix nitrogen, it also plays a vital role in managing soil fertility. Mung beans are one of the most significant crops for farmers as a cash crop. In order to implement control measures effectively and on schedule, it is crucial to monitor the population dynamics of major sucking pests, such as aphids, jassids and whiteflies in relation of weather parameters. Methods: PDM-139 (Samrat) variety seeds were manually planted 5-7cm deep in the ground. Weekly observations were made from 10 randomly chosen plants Split cage methods were used to record the observations of jassids and whiteflies and aphids from the top and bottom surfaces of the first three trifoliate plants were tallied. Averages population were computed. Result: The incidence of pest population start on the 14-15th standard meteorological weeks which attain their peak population in 19th SMW. The insect-pest population was established positive correlation with the max and min temperature whereas population was negatively correlated with R.H. and Rainfall.

Role of eggplant trichome in whitefly oviposition and its relevance to biological control under greenhouse conditions.

The combined release of the predatory mite Amblyseius swirskii (Athias-Henriot) and the mirid Nesidiocoris tenuis (Reuter) provides effective biological control of the tobacco whitefly (Bemisia tabaci (Gennadius)) in greenhouse eggplant. However, knowing how plants' trichomes affect pest-predator interactions could improve whitefly management. Here, the effect of two varieties with either the presence or absence of trichomes was assessed on naturally occurring whitefly populations and predator abundance in a first experiment under field conditions. Predator-prey models were developed to assess the effect of trichomes on pest and predator population dynamics under field conditions. In a second semi-field experiment, the occurrence and oviposition preferences of B. tabaci and A. swirskii in the same eggplant varieties were compared. Significantly higher numbers of whitefly and mite, adults and eggs, were found on the hairy variety in both experiments. However, no differences were found in N. tenuis abundance between varieties under field conditions. Predator-prey models showed that whitefly growth rate increased in the hairy variety. N. tenuis and A. swirskii showed different fitness parameters according to the variety, with the former displaying better performance in the hairless variety and the latter in the hairy variety. Both predators effectively controlled the increase in whitefly populations in both varieties. Overall, the findings suggest that the hairless variety is more effective in deterring whiteflies. Additionally, the higher population of A. swirskii on the hairy variety indicates that this predator benefited from both the presence of trichomes and the prey.

Potential distribution of rice thrips (Stenchaetothrips biformis) in India under changing climate

Sudden outbreaks of agricultural pests are increasing in India due to the growing prominence of environmental issues like global warming, the occurrence of weather extremes, and hydrological extremes. Climate change impacts the developmental rates and population dynamics of agricultural pests. As rice is a staple food widely used in India, it often suffers intensive damage by various pests, leading to a considerable decrease in crop yield. One of the most common pests in rice fields in India and neighboring countries is the rice thrips (Stenchaetothrips biformis). However, the degree of pest infestation of rice crops under climate change scenarios is poorly known. Therefore, this study aimed to understand the potential geographical distribution of the rice thrips in India for future scenarios using the MaxEnt modeling framework. Future projections from global climate models (GCMs), such as HadGEM3-GC31 and MPI-ESMI-2, are used to predict the most affected regions in 2050 under three greenhouse gas emission scenarios: SSP1-2.6, SSP3-4.5, and SSP5-8.5. The results from the MaxEnt indicate that the southern and northeastern parts of India will be highly affected by rice thrips in 2050. The affected number of districts are found to be 256, 330 and 313 under SSP1-2.6, SSP3-4.5, and SSP5-8.5 scenarios, respectively. It has been observed that the maximum temperature is the most influential climatic parameter for the geographical distribution of rice thrips, followed by the annual mean and minimum temperatures. It can be concluded from these results that the elevated temperature enhances the growth and distribution of rice thrips.

Population dynamics of major insect pest of lentil and correlation with weather factors

Population dynamics of major insect pest of lentil and correlation with weather factors

Population Dynamics of Major Insect Pests and Natural Enemies in Tomato

An experiment on major insect pests and natural enemies of tomato was conducted during rabi, 2022-23 at the experimental farm for PG research, Biswanath College of Agriculture, Sonitpur. Results revealed eleven insect pests; whitefly, Bemisia tabaci (Gennadius); aphid, Aphis craccivora Koch; leafminer, Lyriomyza trifolii (Burgess); fruitborer, Helicoverpa armigera (Hubner); jassid, Amrasca biguttula biguttula (Ishida); semilooper, Trichoplusia ni (Hubner) were found to be the most dominant species. Two coccinellid predators viz., Micraspis discolor(F) and Cheilomenes sexmaculata (F) and two spiders Lycosa tista Tikader, Anyphaena accentuata (Walckenaer) were recorded as natural enemies. It was observed that the incidence of B. tabaci, A. craccivora and A. biguttula biguttula showed significant negative correlation with both maximum and minimum temperature. B. tabaci population registered a positive significant correlation with morning relative humidity. Both L. trifolii and H. armigera exhibited significant negative correlation with bright sunshine hour. Furthermore, T. ni showed significant negative correlation with maximum temperature and bright sunshine hour. As regards coccinellids, a significant negative correlation existed with maximum and minimum temperature, and rainfall and significant positive correlation with morning relative humidity. A significant positive correlation of aphids was also observed with coccinellids.

Artificial neural networks as a tool for seasonal forecast of attack intensity of Spodoptera spp. in Bt soybean.

Soybean (Glycine max) is the world's most cultivated legume; currently, most of its varieties are Bt. Spodoptera spp. (Lepidoptera: Noctuidae) are important pests of soybean. An artificial neural network (ANN) is an artificial intelligence tool that can be used in the study of spatiotemporal dynamics of pest populations. Thus, this work aims to determine ANN to identify population regulation factors of Spodoptera spp. and predict its density in Bt soybean. For two years, the density of Spodoptera spp. caterpillars, predators, and parasitoids, climate data, and plant age was evaluated in commercial soybean fields. The selected ANN was the one with the weather data from 25 days before the pest's density evaluation. ANN forecasting and pest densities in soybean fields presented a correlation of 0.863. It was found that higher densities of the pest occurred in dry seasons, with less wind, higher atmospheric pressure and with increasing plant age. Pest density increased with the increase in temperature until this curve reached its maximum value. ANN forecasting and pest densities in soybean fields in different years, seasons, and stages of plant development were similar. Therefore, this ANN is promising to be implemented into integrated pest management programs in soybean fields.

Buckwheat as a companion plant in soybean fields: Implications for management of major pests

Abstract Many studies have explored the potential of companion plants to manage pests through top–down or bottom–up effects in agricultural fields. Buckwheat is known as a good candidate for companion planting with various crops to enhance pest management, but rarely in soybeans. We investigated the impact of planting buckwheat as a new companion plant on the population dynamics of major soybean pests and their natural enemies in soybean fields in Andong, Republic of Korea. We recorded numbers of pests and natural enemies at 9–10‐day intervals from 20 soybean plants each in eight small experimental fields throughout the cropping season. Significant reduction in pests, such as Riptortus pedestris (F.) (Hemiptera: Alydidae) adults, and a significant increase in natural enemies, such as Orius species (Hemiptera: Anthocoridae) and crab spiders (Araneae: Thomisidae), were observed in the buckwheat treatment plots. However, there were significant increases in other pests, such as leafminers and leafhoppers, in the buckwheat treatment plots. While we observed effects on R. pedestris adult density, we did not find significant effects on other developmental stages of this pest or its parasitoids. Although there were some concerns in the buckwheat treatment plots, the positive effects of buckwheat in soybean fields appear to outweigh the drawbacks. Buckwheat is likely a suitable companion plant for use in soybeans to manage pests.

Seasonal occurrence of the shoot fly complex on Rabi sorghum in the Marathwada area of Maharashtra

The present study was conducted to investigate the variety and abundance of shoot flies in the Postgraduate Experimental Field, Department of Agricultural Entomology, College of Agriculture, Latur Campus, Maharashtra, India, during rabi season 2020-21. Analysis of insect pest population dynamics indicated that Atherigona soccata attained its maximum population density during the 51st standard meteorological week, with an average of 3.60 maggots per quadrat. Correlation studies exhibited that wind speed had a detrimental impact on the population of A soccata maggots. During the first sampling period of the study, Oscinella sp. achieved its peak population density, with an average of 13.00 maggots per quadrat. Link tests revealed a positive link between the relative humidity before noon and the population of Oscinella sp., but a substantial negative correlation was seen between wind speed and the population. The population of Ectecephala sp. reached its highest level during the second sampling week, with an average of 2.33 maggots per quadrat. Correlation studies demonstrated a substantial negative correlation between wind speed and the population of Ectecephala sp.

Exploring the impact of cover crops in integrated pest management: pest and natural enemies population dynamics in no-tillage cotton production.

Conservation agriculture plays an important role in the sustainability of production systems, notably for globally significant crops such as cotton. This study explores the integration of the no-tillage system (NTS) with integrated pest management (IPM) by incorporating cover crops. The aim is to assess the impact of these living or dead covers on the management of insect populations, the indices diversity of phytophagous insects and natural enemies, and to investigate the population fluctuation of these arthropods, considering a variety of crops in the NTS before and after cotton planting. The trial, conducted over two consecutive cropping seasons in Mato Grosso do Sul State, Brazil, employed a randomised block design with four repetitions. The treatments included cover crops with the highest potential for use in the region, such as millet (Pennisetum glaucum glaucum L.), corn (Zea mays L.), brachiaria (Urochloa ruziziensis), black velvet bean (Stizolobium aterrimum), forage sorghum (Sorghum bicolor L.), and white oats (Avena sativa L.) and a mix of white oats with brachiaria. The results indicated that the black velvet bean stands out as the most effective cover crop, providing the best performance in terms of non-preference to the attack of the evaluated pest insects. Conversely, brachiaria proves to be more susceptible to infestations of Dalbulus maidis (DeLong and Wolcott) (Hemiptera: Cicadellidae), and Diabrotica speciosa (Germar, 1824) (Coleoptera: Chrysomelidae). The study underscores the relevance of the judicious choice of cover crops in IPM and in promoting agricultural biodiversity, creating a strategic tool to enhance the sustainability and efficiency of the cotton production system in the context of the NTS.

Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards

Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards

Lethal and sublethal effects of spinosad on dengue vector mosquito, Aedes albopictus and bancroftian filariasis vector mosquito, Culex pipiens pallens.

Aedes albopictu and Culex pipiens pallens are important vectors of many viruses and have had resistance to chemical pesticide. Spinosad is a selective biological insecticide to control urban mosquito. The aim of this study was to reveal the sublethal effects of spinosad on mosquito and provide reference basis for integrated mosquito management. The toxicity of spinosad against Ae. albopictus and Cx. pipiens pallens were determined under laboratory conditions by exposing early third-instar larvae to different concentrations. The LC50 values of spinosad to Ae. albopictus and Cx. Pipiens pallens larvaes were 4.44×10-3 mg∙L-1 and 1.93×10-3 mg∙L-1 respectively after 72 h exposure. Spinosad at sublethal concentrations has many negative effects on Ae. albopictus and Cx. Pipiens pallens larval, pupae, adult and offspring eggs, including significantly reduced their larvae pupation rate by 51.37% and 58.47%, significantly prolonged pupae length by 21.43% and 16.18%, reduced female wing-spans by 20.19% and 14.89%, reduced male wing-spans by 3.84% and 7.54%, reduced female weight by 29.04% and 31.52%, reduced male weight by 7.47% and 9.07%, reduced female and male ratio by 51.98% and 45.21%, reduced individual egg-laying amount by 15.73% and 35.51%, in addition, offspring egg hatchability were dramatically decreased by 25.71% and 34.04%, egg periods were significantly prolonged by 14.42% and 62.82% respectively. No significant effect on larval period, pupae emergence rate, female bite rates were observed. These results suggest that spinosad might affect pest population dynamics significantly and is fairly expected to be a candidate biological pesticide for mosquito control.

Population Dynamics of Major Sucking Pests of Mung bean in Western Rajasthan and Their Management Using Newer Insecticides

Population Dynamics of Major Sucking Pests of Mung bean in Western Rajasthan and Their Management Using Newer Insecticides

A stochastic hormesis Ricker model and its application to multiple fields

Random noise pervades ecosystems and has the potential for having major impacts on the growth processes of pest populations. In this paper, we aim to investigate the impact of random perturbations on the hormesis Ricker model by considering control measures applied within each generation which can generate hormetic effects, where randomness is characterized by a uniform discrete distribution and white noise, respectively. The main results indicate that the addition of discrete randomness will make the model appear with blurred orbits when the intrinsic growth rate is large enough. The position of the random variable, at the end of each generation or within each generation, cause the blurred orbits to exhibit various forms. Moreover, the effects of variances and expectations of the discrete uniform random variable on the dynamics are evaluated. Further, the introduction of randomness increases the hormetic zone and the maximum response, but can increase or decrease the monotonically increasing interval under different parameter values. In contrast, the stochastic model characterized by white noise, exhibits only a small effect on the bifurcation diagrams with respect to the intrinsic growth rate and the hormesis, which may be attributed to the mean of its noise being zero. Finally, we fit the stochastic model to experimental hormetic data sets observed in multiple fields, and our results demonstrate that the stochastic hormesis Ricker model can capture the characteristics of these data accurately. These findings could provide valuable insights into the understanding of the complexities of pest population dynamics, with implications for better pest control, resource management and for other complex biological systems such as toxicology and drug development.

Seasonal incidence of major sucking pests of Bt cotton and their natural enemies with relation to weather parameters

Study on population dynamics of major sucking pests infesting Bt cotton showed that aphid, jassid, whitefly and thrips initiated from 28th SMW (2nd week of July), 28th SMW (2nd week of July), 29th SMW (3rd week of July) and 27th SMW (1st week of July), respectively. Peak infestation of aphid (21.20 aphid per 3 leaves) observed during 1st week of December (49th SMW). Jassid population observed highest in 40th SMW (14th WAS) with 9.88 jassid per 3 leaves, while the maximum whitefly population was observed during 43rd with 11.84 whitefly per 3 leaves. Population of thrips reached its peak during 34th SMW (8th WAS) with 15.32 thrips per 3 leaves. The peak population of lady bird beetles (4.52 grubs and adults per plant) was recorded during 43rd SMW (17th WAS) and the peak population of spider was recorded during 34th SMW (8th WAS) i.e. 1.36 spider per plant. Among the different abiotic environmental factors, jassid and whitefly had significant positive correlation with maximum temperature. Significant positive correlation was showed by thrips with minimum temperature. Morning relative humidity and evening relative humidity showed non-significant negative correlation with all sucking pest except thrips. Rainfall had non-significant positive correlation with jassid, whitefly and thrips. Bright sunshine had non-significant positive correlation with all sucking pests except thrips.

Phototactic Changes in Phthorimaea absoluta Long-Wavelength Opsin Gene Mutants (LW2-/-) and Short-Wavelength Opsin Gene Mutant (BL-/-) Strains.

Phthorimaea absoluta (Meyrick) is an invasive pest that has caused damage to tomatoes and other crops in China since 2017. Pest control is mainly based on chemical methods that pose significant threats to food safety and environmental and ecological security. Light-induced control, a green prevention and control technology, has gained attention recently. However, current light-trapping technology is non-specific, attracting targeted pests alongside natural enemies and non-target organisms. In this study, we characterized the phototactic behavior of tomato leaf miners for the development a specific light-trapping technology for pest control. In situ hybridization revealed opsin expression throughout the body. Furthermore, we investigated the tropism of pests (wild T. absoluta, Toxoptera graminum, and Bemisia tabaci) and natural enemies (Nesidiocoris tenuis and Trichogramma pintoi) using a wavelength-lamp tropism experiment. We found that 365 ± 5 nm light could accurately trap wild P. absoluta without trapping natural enemies and other insects. Finally, we analyzed the phototactic behavior of the mutant strains LW2(-/-) and BL(-/-). LW2 and BL mutants showed significant differences in phototactic behavior. The LW2(-/-) strain was attracted to light at 390 ± 5 nm and the BL(-/-) strain was unresponsive to any light. Our findings will help to develop specific light-trapping technology for controlling tomato leaf miners, providing a basis for understanding pest population dynamics and protecting crops against natural enemies.

Biomonitoring of biocontrol across the full annual cycle in temperate climates: Post‐harvest, winter and early‐season interaction data and methodological considerations for its collection

Abstract Conservation biocontrol, the regulation of crop pests by naturally occurring biocontrol agents (e.g., predators and parasitoids), is predominantly monitored throughout periods of primary crop growth when pests exert the most observable impact on yields. Pest‐focused agricultural biomonitoring often overlooks post‐harvest, winter and even early‐season biocontrol, despite the significant predator–pest interactions during these periods that profoundly affect pest abundance and, consequently, crop yields. Rapid advances in biomonitoring, particularly in the detection of predator–pest interactions that underpin biocontrol, provide an opportunity to reconsider how and when we monitor these interactions. Advances in agricultural biomonitoring must transcend methodological innovation and encompass conceptual changes in the monitoring of agricultural systems. Here, we assess existing evidence supporting the importance of periods beyond primary crop growth for biocontrol and how predator–pest interactions are likely to evolve during these periods, subsequently influencing pest population dynamics during the primary crop growth period. We advocate for a greater concerted effort to establish continuous monitoring of biocontrol interactions, particularly beyond primary crop growth periods in temperate climates. To facilitate this, we also summarise the methodological approaches that can make it possible and explore how extending sampling across the full annual cycle might impact the practicalities and outcomes of these approaches. Year‐round monitoring of biocontrol interactions, both in crops and adjacent semi‐natural habitats, will provide a previously intractable understanding of predator–pest dynamics, offering significant potential to enhance our ability to optimise and manipulate these systems. This would manifest in reduced crop yield losses, pest infestation rates and disease transmission, with concomitant long‐term financial, environmental and land‐use benefits.

Influence of weather factors on population dynamics of major insect pests in moringa (Moringa oleifera Lam.) in south Tamil Nadu

Influence of weather factors on population dynamics of major insect pests in moringa (Moringa oleifera Lam.) in south Tamil Nadu

Fine-Tuning Artificial Neural Networks to Predict Pest Numbers in Grain Crops: A Case Study in Kazakhstan

This study investigates the application of different ML methods for predicting pest outbreaks in Kazakhstan for grain crops. Comprehensive data spanning from 2005 to 2022, including pest population metrics, meteorological data, and geographical parameters, were employed to train the neural network for forecasting the population dynamics of Phyllotreta vittula pests in Kazakhstan. By evaluating various network configurations and hyperparameters, this research considers the application of MLP, MT-ANN, LSTM, transformer, and SVR. The transformer consistently demonstrates superior predictive accuracy in terms of MSE. Additionally, this work highlights the impact of several training hyperparameters such as epochs and batch size on predictive accuracy. Interestingly, the second season exhibits unique responses, stressing the effect of some features on model performance. By advancing our understanding of fine-tuning ANNs for accurate pest prediction in grain crops, this research contributes to the development of more precise and efficient pest control strategies. In addition, the consistent dominance of the transformer model makes it suitable for its implementation in practical applications. Finally, this work contributes to sustainable agricultural practices by promoting targeted interventions and potentially reducing reliance on chemical pesticides.