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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.

Abstract Genetically engineered crops expressing Bacillus thuringiensis (Bt) Cry toxins have transformed insect management in maize and cotton, reducing insecticide use and associated off-target effects. To mitigate the risk that pests evolve resistance to Bt crops, the US Environmental Protection Agency requires resistance management measures. The approved resistance management plan for Bt maize in cotton production regions requires a structured refuge of non-Bt maize equal to 20% of the maize planted; that for Bt cotton relies on the presence of an unstructured natural refuge comprising both non-Bt crop and non-crop hosts. We examined how abundance of Bt crops (cotton and maize) and an important non-Bt crop (soybean) component of the natural refuge affect resistance to Bt Cry1Ac toxin in local populations of Helicoverpa zea, an important lepidopteran pest impacted by Bt cotton and maize. We show refuge effectiveness is responsive to local abundances of maize and cotton and non-Bt soybean, and maize, in its role as a source of H. zea infesting cotton and non-Bt hosts, influences refuge effectiveness. These findings have important implications for commercial and regulatory decisions regarding deployment of Bt toxins targeting H. zea in maize, cotton, and other crops and for assumptions regarding efficacy of natural refuges.

The invasive Melanaphis sorghi (Theobald; =Melanaphis sacchari Zehntner) is a serious pest of sorghum production in the southern USA. Demonstration of technologies that provide effective control is key to management of this pest. Here, we investigated the effect of host plant resistance (resistant cultivar: DKS37-07 and susceptible cultivar: DKS53-53) and a single foliar insecticide (flupyradifurone: Sivanto Prime) application on M. sorghi infestations and the role of natural enemy populations in grain sorghum production across five locations in four states in southeastern USA. Foliar insecticide application significantly suppressed M. sorghi infestations on both the resistant and susceptible sorghum cultivars across all locations. Planting the host plant resistant cultivar (DKS37-07) significantly reduced aphid infestation across all locations. Plant damage ratings did not vary widely, but there was generally a positive association between aphid counts and observed plant damage, suggesting that increasing aphid numbers resulted in corresponding increase in plant damage. Planting a host plant resistant cultivar and foliar insecticide application generally preserved grain yield. Both sorghum hybrids supported an array of different life stages of natural enemies (predators [lady beetle larvae and adults; hoverfly larvae and lacewing larvae] and parasitoids [a braconid and aphelinid]) for both the sprayed and non-sprayed treatments. We found a strong and significant positive relationship between the natural enemies and the M. sorghi infestation. Results suggest that planting a host plant resistant cultivar and the integration of natural enemies with insecticide control methods in the management of M. sorghi is central to the development of an effective pest management strategy against this invasive pest.

Tarnished plant bug, Lygus lineolaris (Hemiptera: Miridae), is an economically damaging pest in cotton production systems across the southern United States. We systematically scouted 120 commercial cotton fields across five southeastern states during susceptible growth stages in 2019 and 2020 to investigate sampling optimization and the effect of interface crop and landscape composition on L. lineolaris abundance. Variance component analysis determined field and within-field spatial scales, compared with agricultural district and state, accounted for more variation in L. lineolaris density using sweep net and drop cloth sampling. This result highlights the importance of field-level scouting efforts. Using within-field samples, a fixed-precision sampling plan determined 8 and 23 sampling units were needed to determine L. lineolaris population estimates with 0.25 precision for sweep net (100 sweeps per unit) and drop cloth (1.5 row-m per unit) sampling, respectively. A spatial Bayesian hierarchical model was developed to determine local landscape (L. lineolaris in cotton. The proportion of agricultural area and double-crop wheat and soybeans were positively associated with L. lineolaris density, and fields with more contiguous cotton areas negatively predicted L. lineolaris populations. These results will improve L. lineolaris monitoring programs and treatment management decisions in southeastern USA cotton.

Transgenic cotton expressing Cry51Aa2.834_16 Bt toxin (hereafter referred to as MON 88702) has the potential to be an important tool for pest management due to its unique activity against tobacco thrips, Frankliniella fusca. Unlike other Bt toxins targeting lepidopteran cotton pests, MON 88702 does not cause direct mortality but has an antixenotic effect that suppresses F. fusca oviposition. Previous work has shown neonicotinoid seed treated (NST) crops have similar behavioral effects on thrips. This study used non-choice and common garden experiments to examine how the presence of MON 88702 cotton and soybean (another F. fusca host) with and without NSTs might alter F. fusca infestation distributions. In a no-choice environment, significant larval establishment differences were observed, with untreated soybean plants becoming most heavily infested. In choice experiments, plants expressing MON 88702 or were neonicotinoid treated had significantly lower larval establishment. Larval density decreased as dispersal distance increased, suggesting reproductive decisions were negatively related to distance from the release point. Understanding how F. fusca responds to MON 88702 in an environment where adults can choose among multiple host plants will provide valuable context for projections regarding design of MON 88702 resistance refuges. Reduced larval establishment on NST cotton and soybean suggests that area-wide use of NSTs could reduce the number of susceptible F. fusca generated in unstructured crop refuges for MON 88702. These results also suggest that although the presence of NST MON 88702 could suppress reproduction and resistance selection, over time this benefit could erode resulting in increased larval establishment on NST cotton and soybean due to increased frequency of neonicotinoid resistant F. fusca populations.

Deriving crop information from remotely sensed data is an important strategy for precision agriculture. Small unmanned aerial systems (UAS) have emerged in recent years as a versatile remote sensing tool that can provide precisely-timed, fine-grained data for informing management responses to intra-field crop variability (e.g., nutrient status and pest damage). UAS sensors with high spectral resolution used to compute informative vegetation indices, however, are practically limited by high cost and data dimensionality. This research extends spectral analysis for remote crop monitoring to investigate the relationship between crop health and 3D canopy structure using low-cost UAS equipped with consumer-grade RGB cameras. We used flue-cured tobacco as a case study due to its known sensitivity to fertility variation and nutrient-specific symptomology. Fertilizer treatments were applied to induce plant health variability in a 0.5 ha field of flue-cured tobacco. Multi-view stereo images from three UAS surveys collected during crop development were processed into orthoimages used to compute a visible band spectral index and photogrammetric point clouds using Structure from Motion (SfM). Plant structural metrics were then computed from detailed high resolution canopy surface models (0.05 m resolution) interpolated from the photogrammetric point clouds. The UAS surveys were complimented by nutrient status measurements obtained from plant tissues. The relationships between foliar nitrogen (N), phosphorus (P), potassium (K), and boron (B) concentrations and the UAS-derived metrics were assessed using multiple linear regression. Symptoms of N and K deficiencies were well captured and differentiated by the structural metrics. The strongest relationship observed was between canopy shape and N foliar concentration (adj. r2 = 0.59, increasing to adj. r2 = 0.81 when combined with the spectral index). B foliar concentration was consistently better predicted by canopy structure with a maximum adj. r2 = 0.41 observed at the latest growth stage surveyed. Overall, combining information about canopy structure and spectral reflectance increased model fit for all measured nutrients compared to spectral alone. These results suggest that an important relationship exists between relative canopy shape and crop health that can be leveraged to improve the usefulness of low cost UAS for precision agriculture.

Neonicotinoids are a popular and widely-used class of insecticides whose heavy usage rates and purported negative impacts on bees and other beneficial insects has led to questions about their mobility and accumulation in the environment. Neonicotinoid compounds are currently registered for over 140 different crop uses in the United States, with commercial growers continuing to rely heavily on neonicotinoid insecticides for the control of key insect pests through a combination of in-ground and foliar applications. In 2008, the Wisconsin Department of Agriculture, Trade and Consumer Protection (DATCP) began testing for neonicotinoids in groundwater test wells in the state, reporting detections of one or more neonicotinoids in dozens of shallow groundwater test wells. In 2011, similar detection levels were confirmed in several high-capacity overhead center-pivot irrigation systems in central Wisconsin. The current study was initiated to investigate the spatial extent and magnitude of neonicotinoid contamination in groundwater in and around areas of irrigated commercial agriculture in central Wisconsin. From 2013-2015 a total of 317 samples were collected from 91 unique high-capacity irrigation wells and tested for the presence of thiamethoxam (TMX), a neonicotinoid, using enzyme-linked immunosorbent assays. 67% of all samples were positive for TMX at a concentration above the analytical limit of quantification (0.05 μg/L) and 78% of all wells tested positive at least once. Mean detection was 0.28 μg/L, with a maximum detection of 1.67 μg/L. Five wells had at least one detection exceeding 1.00 μg/L. Furthermore, an analysis of the spatial structure of these well detects suggests that contamination profiles vary across the landscape, with differences in mean detection levels observed from landscape (25 km), to farm (5 km), to individual well (500 m) scales. We also provide an update of DATCP's neonicotinoid monitoring in Wisconsin's shallow groundwater test wells and private potable wells for the years 2011-2017.

Landscape-scale intensification of individual crops and pesticide use that is associated with this intensification is an emerging, environmental problem that is expected to have unequal effects on pests with different lifecycles, host ranges, and dispersal abilities. We investigate if intensification of a single crop in an agroecosystem has a direct effect on insecticide resistance in a specialist insect herbivore. Using a major potato pest, Leptinotarsa decemlineata, we measured imidacloprid (neonicotinoid) resistance in populations across a spatiotemporal crop production gradient where potato production has increased in Michigan and Wisconsin, USA. We found that concurrent estimates of area and temporal frequency of potato production better described patterns of imidacloprid resistance among L. decemlineata populations than general measures of agricultural production (% cropland, landscape diversity). This study defines the effects individual crop rotation patterns can have on specialist herbivore insecticide resistance in an agroecosystem context, and how impacts of intensive production can be estimated with general estimates of insecticide use. Our results provide empirical evidence that variation in the intensity of neonicotinoid-treated potato in an agricultural landscape can have unequal impacts on L. decemlineata insecticide insensitivity, a process that can lead to resistance and locally intensive insecticide use. Our study provides a novel approach applicable in other agricultural systems to estimate impacts of crop rotation, increased pesticide dependence, insecticide resistance, and external costs of pest management practices on ecosystem health.

Since 1995, neonicotinoid insecticides have been a critical component of arthropod management in potato, Solanum tuberosum L. Recent detections of neonicotinoids in groundwater have generated questions about the sources of these contaminants and the relative contribution from commodities in U.S. agriculture. Delivery of neonicotinoids to crops typically occurs as a seed or in-furrow treatment to manage early season insect herbivores. Applied in this way, these insecticides become systemically mobile in the plant and provide control of key pest species. An outcome of this project links these soil insecticide application strategies in crop plants with neonicotinoid contamination of water leaching from the application zone. In 2011 and 2012, our objectives were to document the temporal patterns of neonicotinoid leachate below the planting furrow following common insecticide delivery methods in potato. Leaching loss of thiamethoxam from potato was measured using pan lysimeters from three at-plant treatments and one foliar application treatment. Insecticide concentration in leachate was assessed for six consecutive months using liquid chromatography-tandem mass spectrometry. Findings from this study suggest leaching of neonicotinoids from potato may be greater following crop harvest in comparison to other times during the growing season. Furthermore, this study documented recycling of neonicotinoid insecticides from contaminated groundwater back onto the crop via high capacity irrigation wells. These results document interactions between cultivated potato, different neonicotinoid delivery methods, and the potential for subsurface water contamination via leaching.