@article{lawton_huseth_kennedy_morey_hutchison_reisig_dorman_dillard_venette_groves_et al._2022, title={Pest population dynamics are related to a continental overwintering gradient}, volume={119}, ISSN={0027-8424 1091-6490}, url={http://dx.doi.org/10.1073/pnas.2203230119}, DOI={10.1073/pnas.2203230119}, abstractNote={ 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. }, number={37}, journal={Proceedings of the National Academy of Sciences}, publisher={Proceedings of the National Academy of Sciences}, author={Lawton, Douglas and Huseth, Anders S. and Kennedy, George G. and Morey, Amy C. and Hutchison, William D. and Reisig, Dominic D. and Dorman, Seth J. and Dillard, DeShae and Venette, Robert C. and Groves, Russell L. and et al.}, year={2022}, month={Sep} } @article{dorman_taylor_malone_roberts_greene_reisig_smith_jacobson_reay-jones_paula-moraes_et al._2022, title={Sampling Optimization and Crop Interface Effects on Lygus lineolaris Populations in Southeastern USA Cotton}, volume={13}, ISSN={2075-4450}, url={http://dx.doi.org/10.3390/insects13010088}, DOI={10.3390/insects13010088}, abstractNote={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 (<0.5 km from field edges) effects on 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.}, number={1}, journal={Insects}, publisher={MDPI AG}, author={Dorman, Seth J. and Taylor, Sally V. and Malone, Sean and Roberts, Phillip M. and Greene, Jeremy K. and Reisig, Dominic D. and Smith, Ronald H. and Jacobson, Alana L. and Reay-Jones, Francis P. F. and Paula-Moraes, Silvana and et al.}, year={2022}, month={Jan}, pages={88} } @article{goethe_dorman_wang_kennedy_huseth_2022, title={Spatial and temporal patterns of Frankliniella fusca (Thysanoptera: Thripidae) in wheat agroecosystems}, volume={146}, ISSN={0931-2048 1439-0418}, url={http://dx.doi.org/10.1111/jen.12979}, DOI={10.1111/jen.12979}, abstractNote={Abstract}, number={5}, journal={Journal of Applied Entomology}, publisher={Wiley}, author={Goethe, James and Dorman, Seth and Wang, Hehe and Kennedy, George and Huseth, Anders}, year={2022}, month={Feb}, pages={570–578} } @article{dorman_kudenov_lytle_griffith_huseth_2021, title={Computer vision for detecting field‐evolved lepidopteran resistance to Bt maize}, volume={77}, ISSN={1526-498X 1526-4998}, url={http://dx.doi.org/10.1002/ps.6566}, DOI={10.1002/ps.6566}, abstractNote={Abstract}, number={11}, journal={Pest Management Science}, publisher={Wiley}, author={Dorman, Seth J and Kudenov, Michael W and Lytle, Amanda J and Griffith, Emily H and Huseth, Anders S}, year={2021}, month={Aug}, pages={5236–5245} } @article{pellegrino_dorman_williams_millar_huseth_2021, title={Evaluation of 13-Tetradecenyl Acetate Pheromone for Melanotus communis (Coleoptera: Elateridae) Detection in North Carolina Row Crop Agroecosystems}, volume={50}, ISSN={0046-225X 1938-2936}, url={http://dx.doi.org/10.1093/ee/nvab075}, DOI={10.1093/ee/nvab075}, abstractNote={Abstract}, number={5}, journal={Environmental Entomology}, publisher={Oxford University Press (OUP)}, author={Pellegrino, Alyssa M and Dorman, Seth J and Williams, Livy, III and Millar, Jocelyn G and Huseth, Anders S}, editor={Stelinski, LukaszEditor}, year={2021}, month={Aug}, pages={1248–1254} } @article{dorman_hopperstad_reich_majumder_kennedy_reisig_greene_reay‐jones_collins_bacheler_et al._2021, title={Landscape‐level variation in Bt crops predict Helicoverpa ze a ( Lepidoptera: Noctuidae ) resistance in cotton agroecosystems}, volume={77}, ISSN={1526-498X 1526-4998}, url={http://dx.doi.org/10.1002/ps.6585}, DOI={10.1002/ps.6585}, abstractNote={Abstract}, number={12}, journal={Pest Management Science}, publisher={Wiley}, author={Dorman, Seth J and Hopperstad, Kristen A and Reich, Brian J and Majumder, Suman and Kennedy, George and Reisig, Dominic D and Greene, Jeremy K and Reay‐Jones, Francis PF and Collins, Guy and Bacheler, Jack S and et al.}, year={2021}, month={Aug}, pages={5454–5462} } @article{goethe_dorman_huseth_2021, title={Local and landscape scale drivers of Euschistus servus and Lygus lineolaris in North Carolina small grain agroecosystems}, volume={23}, ISSN={1461-9555 1461-9563}, url={http://dx.doi.org/10.1111/afe.12445}, DOI={10.1111/afe.12445}, abstractNote={ Crop production sequences influence arthropod populations in temporally unstable row crop systems. Winter wheat (Triticum aestivum L.) represents one of the earliest abundant crops in south‐eastern United States. This study aims to understand primary source habitats driving brown stink bug, Euschistus servus (Say), and tarnished plant bug, Lygus lineolaris (Palisot de Beauvois), population abundance in wheat. To better understand these relationships, adult and nymphal densities were in wheat fields weekly from flowering through harvest in 2019 and 2020. Geospatial data were used to measure landscape composition surrounding sampled fields. We investigated the influence of landscape predictors on E. servus and L. lineolaris abundance using generalized linear mixed modelling. Field size, proportion of agriculture, proportion of wheat area, and proportion of soybean Glycine max L.) area from the previous year in the surrounding landscape were associated with E. servus abundance in wheat. Similarly, L. lineolaris abundance was associated with proportion of wheat area and soybean area from the previous year. These results reveal the influence of soybean area planted the previous year on insect pest densities the following spring in wheat. Further, results suggest agricultural landscapes dominated by wheat are associated with decreased pest abundance across the sampled region. }, number={4}, journal={Agricultural and Forest Entomology}, publisher={Wiley}, author={Goethe, James K. and Dorman, Seth J. and Huseth, Anders S.}, year={2021}, month={Apr}, pages={441–451} } @article{dorman_hopperstad_reich_kennedy_huseth_2021, title={Soybeans as a non-Bt refuge for Helicoverpa zea in maize-cotton agroecosystems}, volume={322}, ISSN={0167-8809}, url={http://dx.doi.org/10.1016/j.agee.2021.107642}, DOI={10.1016/j.agee.2021.107642}, abstractNote={Geospatial models are crucial for identifying likely ‘hot-spots’ of Bt resistance evolution in Helicoverpa zea (Lepidoptera: Noctuidae), thereby improving regional insecticide resistance management (IRM) strategies and planted refuge compliance. To characterize H. zea distributions in relation to land use , we used historical trapping data collected from 2008 to 2019 in North Carolina to model the spatial and temporal abundance of H. zea populations across Bt -dominated landscapes. Helicoverpa zea abundance was standardized across site-year observations, and candidate landscape composition and configuration predictors of H. zea abundance were obtained. Spatiotemporal Bayesian hierarchical models were developed to make posterior predictions of H. zea abundance from environmental covariates, and results were used to generate interpolation prediction maps to visualize H. zea abundance across the sampled region. Our results suggest inverse distance weighted (IDW) soybeans is the most important predictor of H. zea abundance through time in row crop agroecosystems in North Carolina. Soybeans in North Carolina and southeastern U.S. likely serves as a critical non- Bt refuge for delaying H. zea resistance to Bt toxins in landscapes dominated by Bt maize and cotton. Moreover, soybean abundance can be used to predict the spatial abundance of H. zea in this region. Results can be applied to understand population dynamics of H. zea in landscapes dominated by genetically engineered (GE) crops expressing Bt toxins and will enable the development of sound insect resistance management strategies of H. zea populations to GE toxins targeting noctuid pests of maize and cotton. This work will also drive future geospatial studies investigating environmental predictors of resistance evolution in arthropod pests to GE technologies in crop production systems. Landscape-level variation in soybeans predicts spatial and temporal Helicoverpa zea abundance and likely serves as important non- Bt refugia in maize and cotton agroecosystems. • Helicoverpa zea population dynamics in row crops relate to landscape drivers • Landscape-level soybean and cotton variation in the southeastern U.S. associate with increased H. zea abundance through time • Soybeans likely serve as critical non- Bt refugia for delaying H. zea resistance in maize and cotton agroecosystems}, journal={Agriculture, Ecosystems & Environment}, publisher={Elsevier BV}, author={Dorman, Seth J. and Hopperstad, Kristen A. and Reich, Brian J. and Kennedy, George and Huseth, Anders S.}, year={2021}, month={Dec}, pages={107642} }