Bayesian Optimization of insect trap distribution for pest monitoring efficiency in agroecosystems

Insect trap networks targeting agricultural pests are commonplace but seldom optimized to improve precision or efficiency. Trap site selection is often driven by user convenience or predetermined trap densities relative to sensitive host crop abundance in the landscape. Monitoring for invasive pests often requires expedient decisions based on dispersal potential and ecology to inform trap placement. Optimization of trap networks using contemporary analytical approaches can help users determine the distribution of traps as information accumulates and priorities change. In this study, a Bayesian optimization (BO) algorithm was used to learn more about the optimal distribution of a fine-scale trap network targeting Helicoverpa zea (Boddie), a significant agricultural pest across North America. Four years of pheromone trap monitoring was conducted at the same 21 locations distributed across ~7,000 square kilometers in a five-county area in North Carolina, USA. Three years of data were used to train a BO model with a fourth year designated for testing. For any quantity of trap locations, the approach identified those that provide the most information, allowing optimization of trapping efficiency given either a constraint on the number of locations, or a set precision required for pest density estimation. Results suggest that BO is a powerful approach to enable optimized trap placement decisions by practitioners given finite resources and time

Current Distribution and Population Persistence of Five Lepidopteran Pests in U.S. Soybean

The distribution of lepidopteran pests in soybean (Glycine max (L.) Merr.) is a current knowledge gap limiting accurate prioritization of Integrated Pest Management (IPM) research. Regional characterizations of lepidopteran distribution in soybean are now more than 25 yr old. The goal of this study was to generate a contemporary assessment of the distribution and population persistence of lepidopteran soybean pests. To understand which species are currently infesting soybean and their persistence, we conducted a survey of soybean entomologists with responsibility for approximately 33.6 million hectares of production in 31 U.S. states. Soybean entomologists were asked questions about presence of lepidopteran pests and their persistence in their state. We focused this survey on five lepidopteran pests: corn earworm (Helicoverpa zea Boddie) (Lepidoptera: Noctuidae), green cloverworm (Hypena scabra Fabricius) (Lepidoptera: Erebidae), painted lady (Vanessa cardui L.) (Lepidoptera: Nymphalidae), soybean looper (Chrysodeixis includens Walker) (Lepidoptera: Noctuidae), and velvetbean caterpillar (Anticarsia gemmatalis Hübner) (Lepidoptera: Erebidae). Soybean entomologists also provided insight into regionally relevant or sporadic lepidopteran soybean pests. Participants were also questioned about common scouting practices in each state. Results of this survey highlight dissimilar geographic distribution and relative persistence of lepidopteran pests in soybean. Clear differences in occurrence and abundance among species provide important contemporary distributions and persistence estimates. Assessments of scouting practices demonstrate a need to improve IPM adoption in some states. Results of this study and its complementary pest profile (concurrently published in JIPM) provide a contemporary foundation for studies of lepidopteran soybean pests

Extended Sentinel Monitoring of Helicoverpa zea Resistance to Cry and Vip3Aa Toxins in Bt Sweet Corn: Assessing Changes in Phenotypic and Allele Frequencies of Resistance

Transgenic corn and cotton that produce Cry and Vip3Aa toxins derived from Bacillus thuringiensis (Bt) are widely planted in the United States to control lepidopteran pests. The sustainability of these Bt crops is threatened because the corn earworm/bollworm, Helicoverpa zea (Boddie), is evolving a resistance to these toxins. Using Bt sweet corn as a sentinel plant to monitor the evolution of resistance, collaborators established 146 trials in twenty-five states and five Canadian provinces during 2020–2022. The study evaluated overall changes in the phenotypic frequency of resistance (the ratio of larval densities in Bt ears relative to densities in non-Bt ears) in H. zea populations and the range of resistance allele frequencies for Cry1Ab and Vip3Aa. The results revealed a widespread resistance to Cry1Ab, Cry2Ab2, and Cry1A.105 Cry toxins, with higher numbers of larvae surviving in Bt ears than in non-Bt ears at many trial locations. Depending on assumptions about the inheritance of resistance, allele frequencies for Cry1Ab ranged from 0.465 (dominant resistance) to 0.995 (recessive resistance). Although Vip3Aa provided high control efficacy against H. zea, the results show a notable increase in ear damage and a number of surviving older larvae, particularly at southern locations. Assuming recessive resistance, the estimated resistance allele frequencies for Vip3Aa ranged from 0.115 in the Gulf states to 0.032 at more northern locations. These findings indicate that better resistance management practices are urgently needed to sustain efficacy the of corn and cotton that produce Vip3Aa

Extended Sentinel Monitoring of Helicoverpa zea Resistance to Cry and Vip3Aa Toxins in Bt Sweet Corn: Assessing Changes in Phenotypic and Allele Frequencies of Resistance

Transgenic corn and cotton that produce Cry and Vip3Aa toxins derived from Bacillus thuringiensis (Bt) are widely planted in the United States to control lepidopteran pests. The sustainability of these Bt crops is threatened because the corn earworm/bollworm, Helicoverpa zea (Boddie), is evolving a resistance to these toxins. Using Bt sweet corn as a sentinel plant to monitor the evolution of resistance, collaborators established 146 trials in twenty-five states and five Canadian provinces during 2020–2022. The study evaluated overall changes in the phenotypic frequency of resistance (the ratio of larval densities in Bt ears relative to densities in non-Bt ears) in H. zea populations and the range of resistance allele frequencies for Cry1Ab and Vip3Aa. The results revealed a widespread resistance to Cry1Ab, Cry2Ab2, and Cry1A.105 Cry toxins, with higher numbers of larvae surviving in Bt ears than in non-Bt ears at many trial locations. Depending on assumptions about the inheritance of resistance, allele frequencies for Cry1Ab ranged from 0.465 (dominant resistance) to 0.995 (recessive resistance). Although Vip3Aa provided high control efficacy against H. zea, the results show a notable increase in ear damage and a number of surviving older larvae, particularly at southern locations. Assuming recessive resistance, the estimated resistance allele frequencies for Vip3Aa ranged from 0.115 in the Gulf states to 0.032 at more northern locations. These findings indicate that better resistance management practices are urgently needed to sustain efficacy the of corn and cotton that produce Vip3Aa

Pest population dynamics are related to a continental overwintering gradient

Overwintering success is an important determinant of arthropod populations that must be considered as climate change continues to influence the spatiotemporal population dynamics of agricultural pests. Using a long-term monitoring database and biologically relevant overwintering zones, we modeled the annual and seasonal population dynamics of a common pest, Helicoverpa zea (Boddie), based on three overwintering suitability zones throughout North America using four decades of soil temperatures: the southern range (able to persist through winter), transitional zone (uncertain overwintering survivorship), and northern limits (unable to survive winter). Our model indicates H. zea population dynamics are hierarchically structured with continental-level effects that are partitioned into three geographic zones. Seasonal populations were initially detected in the southern range, where they experienced multiple large population peaks. All three zones experienced a final peak between late July (southern range) and mid-August to mid-September (transitional zone and northern limits). The southern range expanded by 3% since 1981 and is projected to increase by twofold by 2099 but the areas of other zones are expected to decrease in the future. These changes suggest larger populations may persist at higher latitudes in the future due to reduced low-temperature lethal events during winter. Because H. zea is a highly migratory pest, predicting when populations accumulate in one region can inform synchronous or lagged population development in other regions. We show the value of combining long-term datasets, remotely sensed data, and laboratory findings to inform forecasting of insect pests

Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

This is the final version of the article. Available from National Academy of Sciences via the DOI in this recordThe idea that noncrop habitat enhances pest control and represents a win–win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win–win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.This work was supported through the National Socio-Environmental Synthesis Center (SESYNC)—National Science Foundation Award DBI-1052875 for the project “Evidence and Decision-Support Tools for Controlling Agricultural Pests with Conservation Interventions” organized by D.S.K. and R.C.-K

Establishing an IPM System for Tarnished Plant Bug (Hemiptera: Miridae) in North Carolina

Prior to 2010, Lygus lineolaris Palisot de Beauvois was a minor pest in North Carolina cotton, Gossypium hirsutum L., but became one of the top pests by 2017. This insect was already a persistent pest in other US cotton-producing regions. Initial work focused on addressing near-term management needs and documenting locally relevant ecology and population dynamics of the pest in North Carolina. Landscape factors were found that correlated with tarnished plant bug incidence. Adult numbers tended to be higher in fragmented fields (more field edges) and nymph numbers were higher near field edges. The minimum required sample for estimating tarnished plant bug populations was studied. Thresholds developed in the Midsouth were proven to be useful in a study between both southeastern Virginia and northeastern North Carolina. Furthermore, an insecticide application sequence was recommended based on efficacy trials, number of expected insecticides, and preserving beneficial insects early in the season. These were evaluated in a study investigating IPM systems approaches. Finally, new management tactics for tarnished plant bug, such as ThryvOn cotton, are being evaluated. As new management strategies and tactics are developed, they will need to be evaluated for their fit in this IPM system

Evaluating an Action Threshold-Based Insecticide Program on Onion Cultivars Varying in Resistance to Onion Thrips (Thysanoptera: Thripidae)

Onion thrips, Thrips tabaci Lindeman (Thysanoptera: Thripidae), is a highly destructive pest of onion, Allium cepa L., and its management relies on multiple applications of foliar insecticides. Development of insecticide resistance is common in T. tabaci populations, and new strategies are needed to relax existing levels of insecticide use, but still provide protection against T. tabaci without compromising marketable onion yield. An action threshold-based insecticide program combined with or without a thrips-resistant onion cultivar was investigated as an improved approach for managing T. tabaci infestations in commercial onion fields. Regardless of cultivar type, the average number of insecticide applications needed to manage T. tabaci infestations in the action-threshold based program was 4.3, while the average number of sprays in the standard weekly program was 7.2 (a 40% reduction). The mean percent reduction in numbers of applications following the action threshold treatment in the thrips-resistant onion cultivar, ‘Advantage', was 46.7% (range 40-50%) compared with the standard program, whereas the percentage reduction in applications in action threshold treatments in the thrips-susceptible onion cultivar, ‘Santana', was 34.3% (range 13-50%) compared with the standard program, suggesting a benefit of the thrips-resistant cultivar. Marketable bulb yields for both ‘Advantage' and ‘Santana' in the action threshold-based program were nearly identical to those in the standard program, indicating that commercially acceptable bulb yields will be generated with fewer insecticide sprays following an action threshold-based program, saving money, time and benefiting the environment