Odor Preference, Feeding, Survival, and Reproductive Fitness of the Invasive Larger Grain Borer Prostephanus truncatus on Acorns of Three Native North America Oak Species

Odor Preference, Feeding, Survival, and Reproductive Fitness of the Invasive Larger Grain Borer Prostephanus truncatus on Acorns of Three Native North America Oak Species | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Odor Preference, Feeding, Survival, and Reproductive Fitness of the Invasive Larger Grain Borer Prostephanus truncatus on Acorns of Three Native North America Oak Species Qinglei Ming, Matthew Hetherington, Melanie Kessler-Mathieu, Bruna Mattioni, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7545462/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Nov, 2025 Read the published version in Journal of Chemical Ecology → Version 1 posted 9 You are reading this latest preprint version Abstract The larger grain borer, Prostephanus truncatus (Horn), is an invasive pest on stored grains but can also exploit non-grain food sources. Currently, this species has a limited distribution in North America but possesses the potential to further expand across the continent. Alternative non-grain foods could play a role in range expansion and previous research has shown that acorns can be a suitable food for the lesser grain borer Rhyzopertha dominica (F.), a closely related grain pest. Here, we assessed the odor preference of P. truncatus for acorns from black oak ( Quercus velutina ), red oak ( Quercus rubra ), and bur oak ( Quercus macrocarpa ) compared to maize and wheat, and analyzed their volatile organic compound (VOC) profiles. Further, we measured P. truncatus feeding and reproduction on these acorns. Results demonstrated that P. truncatus responded to volatiles of each acorn species but responded most positively to bur oak acorns. Interestingly, bur oak acorns were also more attractive than maize, its main host grain. VOC profiles showed that two compounds emitted from bur oak acorns, 3-hepten-2-one and 2-(5-methyl-furan-2-yl)-propionaldehyde, were unique compared to other treatments, which may be important for odor preference. P. truncatus also preferred to feed on bur oak acorns over other oak species. Bur oak was the only acorn species tested in which F 1 progeny were detected. These results suggest that P. truncatus exhibits evolutionary plasticity that enables it to survive on acorns in the absence of grains, highlighting an elevated risk of landscape-level invasion by this pest in North America. Invasive insect species Larger grain borer Oak acorns Odor preference Volatile organic compound Host suitability Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction The larger grain borer, Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae), is an invasive stored-product insect pest that is native to Mexico and Central America (Hodges 1986 ). The species was accidentally introduced into Tanzania in the late 1970s (Hodges et al. 1983 ) and subsequently spread across much of sub-Saharan Africa (Holst and Meikle 2003 ). It has also occasionally been intercepted in the southern USA, Asia, and Europe (Quellhorst et al. 2021 ) and interceptions are expected to increase moving forward (Harman et al. 2024 ). Although it is not established outside of Mexico, Central America, or Africa, Arthur et al. ( 2019 ) used species distribution models (SDMs) based on current climate data from locations with documented populations to predict that large areas of the tropics in Asia and the Western Hemisphere could support P. truncatus populations if the species was introduced. Moreover, Harman et al. ( 2024 ) demonstrated that the threat of range expansion by P. truncatus was most likely to worsen in the coming decades, and that future changes in environmental conditions could result in a higher risk to temperate regions. In a two-year study involving trapping at 19 locations along a latitudinal gradient across North America, Quellhorst et al. ( 2025 ) only found P. truncatus in Mexico. However, the continued range expansion of P. truncatus is a global concern due to climate change and globalization. P. truncatus is hypothesized to have originally been a wood-boring insect and still retains this capability (Nang’ayo et al. 1993 ; Ramírez-Martínez et al. 1994 ; Scholz et al. 1997a ), but it has expanded its host range to include maize and cassava (Hodges et al. 1985 ; Sadiku et al. 2019 ). Maize can become infested with P. truncatus while still on the cob in the field, and infestations continue at storage facilities (Golob and Hanks 1990 ). The ability of P. truncatus to infest root and tuber crops such as cassava, yam, and sweet potato has also been documented (Nyakunga 1982 ; Osipitan et al. 2015 ; Ejiro et al. 2018 ; Sadiku et al. 2019 ). Interestingly, a variety of other commodities, including wheat, barley, oats, rice, and beans, are considered inferior food sources for P. truncatus and all fail to serve as reproductive hosts (Hodges 1986 ; Athanassiou et al. 2017 ). Thus, compared with other stored-product insect species that can exploit a wide range of commodities, P. truncatus is primarily found exploiting stored maize and is poorly adapted to the exploitation of most other stored commodities; as such, it may offer some insights into the early stages of host shifting that led to the development of stored-product pests (Quellhorst et al. 2021 ). Identifying original and alternative hosts of P. truncatus is important for preventing its establishment and spread, especially in non-native areas. Dispersal of P. truncatus adults away from stored products often occurs at food facilities, especially when food sources are depleted or population density is high (Hodges 1986 ; Fadamiro and Wyatt 1995 ; Scholz et al. 1997b ; Altwegg et al. 2013 ), during which they exploit non-grain resources while moving through the landscape. Borgemeister et al. ( 1998a ) trapped P. truncatus in a primary forest, a peri-urban area, and a region with intensive agriculture in Benin and analyzed the gut contents of beetles. They found that P. truncatus individuals captured in wooded areas had more lignin in their guts, whereas those in intensive agriculture settings had both starch and lignin, indicating that woody hosts were being utilized. Nang’ayo ( 1996 ) conducted no-choice rearing tests in the laboratory and showed that branches of many tree species found in the Kenyan savanna were acceptable for reproduction by P. truncatus , although reproductive rates were generally low and inconsistent. Similarly, Nansen et al. ( 2004 ) evaluated P. truncatus performance on a variety of tree species native to Africa and observed heavy attack on fresh branches from eleven tree species and fresh roots from four tree species. They further reported successful reproduction on branches of Delonix regia , Ceiba pentandra , Manihot esculenta , and Ficus exasperata , as well as on roots of Ficus capensis and F. exasperata . In natural environments, the documented forest hosts for P. truncatus are branches of trees in the family Anacardiaceae that have been girdled by cerambycid beetles (Ramírez-Martínez et al. 1994 ; Nang’ayo 1996 ; Borgemeister et al. 1998b ). These studies show the potential role of wooded habitats in the ecology of P. truncatus as reservoirs and breeding grounds, which may then contribute to its infestations in stored maize and cassava. Further research is needed to understand how P. truncatus selects hosts and reproduces in natural environments (Quellhorst et al. 2021 ). Importantly, P. truncatus has been found to positively respond to host-produced volatiles from starchy commodities and woody species, including maize, wheat, and wood of Commiphora africana (A. Rich.) (Scholz et al. 1997a ). Prior work has also determined that a single calling male P. truncatu s on stored maize was sufficient to initiate a large infestation (Scholz et al. 1997b ). Follow-up work demonstrated that like maize, wood of Commiphora riparia Engl. and C. africana caused arrestment of P. truncatus males (Scholz et al. 1998 ). In addition, other studies have also reported positive attraction in P. truncatus towards maize and cassava (Wright et al. 1993 ; Hodges 1994 ; Pike et al. 1994 ). Thus, it is likely that host odors can play an important role in attraction, colonization and establishment of P. truncatus populations in natural environments. Oak trees ( Quercus spp.) are widely distributed across the globe from northwestern South America, through Central America, North America, Europe, the northwestern edge of Africa, and much of eastern Asia (Steele et al. 2021 ). Particularly, oaks are a prevalent and dominant tree genus in North America (Frankel et al. 2022 ), especially in the southern United States, where P. truncatus poses a risk of establishment (Harman et al. 2024 , 2025 ). Oak acorns are a significant resource for a range of animals, including insects. More relevantly, native oak acorn species in North America can be used for survival and reproduction by the stored-product pest, the lesser grain borer Rhyzopertha dominica (F.) (Coleoptera: Bostrichidae), a close relative of P. truncatus (Jia et al. 2008 ). It is interesting to note in that study that survival and reproduction were especially prominent on damaged acorns, but not undamaged acorns. Currently, it is not known whether P. truncatu s is also attracted to volatiles produced by acorns or whether acorns can be used for survival and reproduction. Investigating whether P. truncatus can subsist on native resources in the landscape of North America will help enhance our understanding of population subsistence and risk posed by intercepted individuals. This is particularly important for predicting potential dispersal and immigration patterns in newly invaded natural environments. The objective of this study was to evaluate the potential of acorns as sources of attractive odors, as well as the suitability of damaged and undamaged acorns as feeding and breeding substrates that could support P. truncatus host-range expansion. To that end, we first conducted P. truncatus odor preference assays with acorns of black oak ( Quercus velutina ), red oak ( Quercus rubra ) and bur oak ( Quercus macrocarpa ) that are all native, common, and widely distributed oak species in North America, but not native to Mexico and likely novel to P. truncatus . We then characterized the relative profiles of volatile organic compounds (VOCs) from these acorns and explored the semiochemical-mediated behavioral response between P. truncatus and acorn species. We finally determined P. truncatus feeding, survival and reproductive fitness on damaged or undamaged acorns in the laboratory. Considering the global distribution and abundance of oak trees and the impacts wrought by climate change and globalization on the geographical distribution and introduction of invasive insect pests, this study will help better assess the risk of P. truncatus to establish in North America by utilizing hosts already present in the landscape so that effective biosecurity measures can be implemented. Materials and Methods Insects Prostephanus truncatus adults were obtained from an insect colony maintained at the United States Department of Agriculture (USDA), Agricultural Research Service, Center for Grain and Animal Health Research in Manhattan, Kansas, USA. The individuals were originally collected from Mexico, in native range of P. truncatus . Insects were reared on whole maize kernels in jars with screened lids and kept at 23°C and 45% relative humidity (RH) under continuous darkness. Acorns and Grains Acorns of black oak, red oak, and bur oak were collected from the ground beneath trees in Manhattan, Kansas, USA at two locations (39.18°N, -96.59°W and 39.20°N, -96.62°W) during the fall of 2022–2024. We removed the caps and discarded any acorns that had cracks or holes in the shells since these may already be infested with other insects. Intact acorns (without cracks or holes) from healthy oak trees were used in the experiments. Organic yellow maize ( Zea mays ) and hard red winter wheat ( Triticum aestivum ) (Heartland Mills, Marienthal, KS, USA) were also used in the experiments. Odor Preference Assays with Acorns and Grains Odor preference assays for adult P. truncatus were conducted in Petri dishes (100 × 15 mm, D × H, VWR, Radnor, PA, USA) serving as arenas, with one individual per dish. Two holes, spaced 5 cm apart and centered over each half of the dish, were carefully drilled on the bottom using a 7/64-inch (2.8-mm) drill bit. Holes were also drilled through a piece of filter paper (85 mm, Ahlstrom-Munksjö, Mt. Holly Springs, PA, USA) affixed with double-sided tape to the bottom of the arena to facilitate P. truncatus movement. The holes allowed the diffusion of host volatiles into the arena so that there were point sources emissions of volatiles but no visual cues. The diffusion of volatiles was confirmed with a smoke test. For each pairwise comparison, two plastic cups (30 × 50 mm, D × H, CrystalWare, Lakewood, NJ, USA) were placed directly beneath the two arena holes, each containing one of the following food stimuli: a single intact acorn of black oak, red oak or bur oak; 1.5 g of maize or wheat kernels; or empty (i.e., blank control). P. truncatus adults were placed individually in the center of the arena, and they were given 16 h to respond to an odor source. At the end of the trial, the number of insects choosing each treatment was recorded. There were n = 74 replicates per treatment combination. HS-SPME/GC-MS Analysis of Acorns and Grains VOCs from acorns and grains were analyzed using headspace solid phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME/GC-MS), based on previously developed methods (Buśko et al. 2016 ; De Flaviis et al. 2021 ) with some modifications, as described below. Maize, wheat, and acorns of bur oak, black oak and red oak were ground separately with a dedicated coffee grinder (Hamilton Beach, Model 80335G, Glen Allen, VA, USA) into a fine whole flour. To prevent cross-contamination between samples, the coffee grinder was thoroughly rinsed with water, followed by repeated rinsing with hexane before use. A total of 2 g of the flour from each sample (n = 5 replicates per treatment) was transferred into a 20-mL headspace vial (Gerstel, Linthicum Heights, MD, USA) and a vial with no flour served as a negative control. The vials were then completely sealed with magnetic screw caps with a Teflon septum. SPME was performed using an automated program on an MPS autosampler (Gerstel, Linthicum Heights, MD, USA). The flour samples were incubated at 60°C on a heating block for 15 min in the pre-equilibration stage, and then a 50/30 µm DVB/Carboxen/PDMS fiber (Supelco 57298-U, St Louis, MO, USA) was exposed for 30 min at 60°C to extract the VOCs. After the extraction step, the SPME fiber was desorbed in the injection port of the GC-MS for 3 min at 260°C in a pulse splitless mode of 40 psi followed by a purge flow of 15 mL/min. VOCs were separated using an Agilent 7890B GC (Agilent, Santa-Clara, CA, USA) coupled to a single quadrupole mass spectrometer (Agilent 5997B), using a Durabond HP-5 capillary column (30 m × 0.25 mm × 0.25 µm) (Agilent). The GC oven ran initially 1 min at 40°C followed by ramping from 40°C to 80°C at a rate of 7°C/min, then from 80°C to 130°C at a rate of 1°C/min, and finally from 130°C to 260°C at a rate of 10°C/min. The He flow rate was held constant at 1.5 mL/min. Spectra were acquired at 50 spectra/s within a range of 40–380 amu. The transfer line temperature was 280°C and the ion source temperature was 200°C. Compounds were tentatively identified by comparison of spectral data with those from the NIST 17 library and by GC retention index. Mobility in Close-range Food Preference Assays Following the odor preference for bur oak acorns observed in the choice assays, insect mobility in close-range food preference assays was recorded over a 60-min period using a video-tracking apparatus combined with EthoVision software (v. 16.0, Noldus Information Technology Inc., Leesburg, VA, USA). The equipment was set up to track six arenas (100 × 15 mm, D × H, VWR, Radnor, PA, USA) simultaneously, and within each arena, a single adult was observed. The arenas were placed in cutouts on white foamboard to affix position that was 80 cm below a network camera (GigE, Basler AG, Ahrenburg, Germany) and backlit with a LED light box (42 × 30 cm, W × L, LPB3, Litup, Shenzhen, China). A piece of filter paper (85 mm, Ahlstrom-Munksjö, Mt. Holly Springs, PA, USA) was taped to the bottom of the arena to facilitate mobility. Two tiny notches exactly halfway on each side of the arena marked where food was to be placed (i.e., 2.1 cm from the edge of the arena). On either side of the arena, we left it empty (i.e., blank control), or placed a single kernel of maize, a single kernel of wheat, or a piece of bur oak acorn (approximately the same mass as a maize kernel). Stimuli were affixed in place with a 3 × 3 mm square of parafilm (Parafilm M, Bemis Co., Davisburg, MI, USA). In total, there were 6 food comparisons, including: maize vs wheat, maize vs bur oak, wheat vs bur oak, maize vs blank, wheat vs blank, and bur oak vs blank. For each individual trial, a new Petri dish and filter paper were used to prevent confounding stimuli. After tracking, the program calculated the frequency of visits and time spent in each zone adjacent to the food source (e.g., within a 1.6-cm diameter circle) for each adult. There were n = 18 replicates per treatment. Prostephanus truncatus Feeding and Survival on Acorns Acorns of black oak, red oak and bur oak were tested for their ability to support adult P. truncatus feeding and survival. We determined P. truncatus feeding, survival and reproductive fitness on both damaged and undamaged acorns. To simulate damage, three evenly spaced holes were drilled on the adaxial surface of each acorn shell using a Dremel multi-tool (Model 300, Racine, WI, USA) with a 5/64-inch (2-mm) drill bit. A piece of filter paper (60 mm, Whatman, GE Healthcare Life Sciences, Buckinghamshire, UK) was taped to the bottom of a glass jar (118 mL, Ball Quilted Crystal, Atlanta, GA, USA). A total of 20 adults were placed on a single damaged or undamaged acorn (red oak, black oak, or bur oak) in the jar with a screened lid in a no-choice assay. A jar with no food served as a negative control and a jar with 2.5 g of maize kernels served as a positive control. The jars were left undisturbed for 2 and 4 weeks to allow the adults to feed on the acorns at 23°C and 45% RH under continuous darkness. Afterwards, each acorn was dissected to check for the presence of alive or dead adults, including those found inside or outside the acorn. The rates of adult survival and presence inside acorns were expressed as percentages, dividing the number of individuals that were alive or present inside acorns by the total number of adults in the original sample, respectively. At the end of each period, an X-ray imaging system (MX-20, Faxitron, Wheeling, IL, USA) was also used to examine the acorns for evidence of insect tunneling and feeding activity. Feeding damage was quantified based on the amount of fines produced, and the fines were weighed using a precision balance (B120S, Sartorius Basic, Göttingen, Germany). In total, there were 8 treatments, including: acorns (damaged or undamaged) from bur oak, black oak and red oak, maize as a positive control, and no food as a negative control. There were n = 5 replicates per treatment. Prostephanus truncatus Reproductive Fitness on Acorns Damaged and undamaged acorns of black oak, red oak and bur oak were tested for their ability to support production of P. truncatus F 1 progeny. A piece of filter paper (60 mm, Whatman, GE Healthcare Life Sciences, Buckinghamshire, UK) was taped to the bottom of a glass jar (118 mL, Ball Quilted Crystal, Atlanta, GA, USA) and 20 adults were placed in the jar with a single damaged or undamaged acorn for a no-choice test. The resulting jars were left undisturbed under the same conditions as above for 4 weeks, after which the adults were removed. Subsequently, the acorns were maintained for 6 weeks. At the end of this period, the same X-ray imaging system mentioned above was used to examine the acorns for evidence of insect reproductive success. Then, the acorn was dissected to count the total number of P. truncatus F 1 progeny, including larvae, pupae and adults produced. There were 6 treatments, consisting of damaged or undamaged acorns of black oak, red oak, and bur oak, each with n = 25 replicates per treatment. Data Analysis A Chi-squared goodness of fit test was used to determine whether there were any odor preferences by P. truncatus . Except where otherwise noted, the significance level was α = 0.05 for all analyses. Percentages of final choices for each food were calculated to describe overall trends in odor preference. To characterize the VOCs of each sample, raw peak areas were extracted from the GC and total ion chromatogram (TIC), and peaks were tentatively identified in profiles automatically using MassHunter Unknowns Analysis (Agilent Technologies, Inc., Santa Clara, CA, USA) with a minimum match factor of 70% to the NIST17 library. Peaks with a height less than 0.3% of the tallest peak were excluded from the exported peak table. Compounds were aligned across samples by pulling underlying m/z ratio data from public repositories and flexibly aligning compounds based on structural matches and retention time using the R package uafR (Stratton et al. 2024 ). Singleton compounds were deleted as they represented transient emissions that are not indicative of differences among treatments. Pairwise Bray-Curtis similarities were calculated among samples, and a non-metric multidimensional scaling (NMDS) plot was used to visualize the differences in VOC profiles among treatments. A total of n = 1000 permutations were used for the ordination procedure. Stress values for the NMDS procedure were < 0.10, indicating that good interpretation was possible. Analysis of similarities (ANOSIM) was used to determine significant differences for VOC emissions among treatments, while similarity percentage (SIMPER) was used to determine the major compounds significantly contributing to differences among the groups. Permutations for both analyses were n = 1000. Based on the SIMPER analysis, differences in the emissions of key compounds were visualized using boxplots from the ggplot2 package in R (Wickham 2016 ). For all multivariate statistics of VOCs, the R Package vegan was used (Oksanen et al. 2025 ). A table visualizing the VOC emissions of oak acorns and grains was created with the gt package in R (Iannone et al. 2025 ). To analyze mobility in close-range food preference assays, two dependent variables, frequency and duration of visits to each food zone, were tested using a generalized linear model (GLM) with a negative binomial likelihood and a log link function. The fixed, explanatory variables included the food stimuli (blank control, maize, wheat, or bur oak acorn) and the main effects of each stimuli comparison were estimated. Means of frequency and duration of visits to each food zone were calculated to describe overall trends in food preference. For P. truncatus survival and presence inside acorns, there were three factors, acorn species (black oak, red oak, or bur oak), acorn status (damaged or undamaged), and time (2 or 4 weeks). A Chi-square test of independence was used to determine whether there was a statistically significant association between the factors and the survival rates or percentages of P. truncatus inside acorns. When a significant association was found, post hoc pairwise comparisons with Bonferroni correction were then performed to examine if treatments were statistically different. To analyze P. truncatus feeding and reproduction on acorns, a linear mixed model (LMM) with Bonferroni correction was used to compare the amounts of fines production and the numbers of F 1 progeny produced on damaged and undamaged acorns of three oak species. The fixed, explanatory variables included potential food sources (black oak, red oak, bur oak, or maize) and status of acorns (damaged or undamaged). Upon a significant result from the overall model, Tukey’s HSD was used for multiple comparisons. Results Odor Preference of Prostephanus truncatus In food odor preference tests, P. truncatus was significantly more attracted to acorns of black oak and bur oak, maize, and wheat than to the blank control (Table 1 ; Fig. 1 A and B). By contrast, there was no difference between red oak and the control (Table 1 ; Fig. 1 A). Bur oak was significantly more attractive than black oak, red oak (Table 1 ; Fig. 1 A), and the maize host on which P. truncatus colony was reared (Table 1 ; Fig. 1 B). Table 1 Statistical results of Prostephanus truncates odor preference Treatment * df † χ 2 P Maize vs Blank 1 6.82 < 0.01 Wheat vs Blank 1 5.23 < 0.05 Bur oak vs Blank 1 31.04 < 0.001 Black oak vs Blank 1 3.85 < 0.05 Red oak vs Blank 1 1.40 0.237 Maize vs Wheat 1 0.31 0.579 Maize vs Bur oak 1 23.20 < 0.001 Wheat vs Bur oak 1 1.00 0.317 Black oak vs Bur oak 1 16.33 < 0.001 Red oak vs Bur oak 1 8.65 < 0.01 Black oak vs Red oak 1 1.49 0.223 *Grains and acorns were used as odors in two-choice pitfall traps. † Chi-square goodness of fit test was used in data analysis. VOCs Emitted by Acorns and Grains Out of 132 tentatively identified VOCs from oak acorns and grains through the HS-SPME/GC-MS analysis, 28 compounds were detected with a relative abundance greater than 1% in one treatment (Table 2 ). Black oak, red oak, bur oak, maize, and wheat had 22, 22, 24, 20, and 21 compounds, respectively. 2,4-dimethyl-1-heptene, 2-butyl-1-octanol, 4-methyl-decane and 2,6-dimethyl-nonane were the four most abundant compounds in each treatment. 2,4-dimethyl-1-heptene was the most abundant compound in acorns of black oak, red oak, and bur oak, whereas 2-butyl-1-octanol was the most abundant one in maize and wheat. Two compounds emitted from bur oak acorns, 3-hepten-2-one and 2-(5-methyl-furan-2-yl)-propionaldehyde, were unique compared to other treatments. There was some overlap in VOC compositions of maize and wheat grains, while there was significant differentiation among the three acorn species as well as the acorns and the grains (ANOSIM: R = 0.744, Permutations = 1000, P < 0.001, Fig. 2 ). The VOC composition of bur oak acorns was less variable than the red and black oak acorns (Fig. 2 ). Six compounds, including 2-butyl-octanol, 2,4-dimethyl-1-heptene, 2,6-dimethyl-nonane, 2,7-dimethyl-octanol, 4-methyl-decane, and heptanone, were shown to cumulatively contribute to a > 50% difference between bur oak and others including black oak, red oak, maize, and wheat, and there were significant differences among treatments in their emissions of these compounds (Fig. 3 ). Tukey’s HSD tests indicated that there were higher heptanone emissions by bur oak compared to black oak, red oak, maize, and wheat. Finally, bur oak emitted higher levels of 2,7-dimethyl-octanol than maize and wheat. Table 2 Summary of volatiles tentatively identified by headspace GC-MS from oak acorns and grains potentially used by Prostephanus truncates Close-range Food Preference by Prostephanus truncatus In the close-range food preference mobility assays, P. truncatus visited the zone with maize significantly more than the no-food zone (blank control), but no significant differences were observed in the frequencies of visits to wheat or bur oak acorns (Table 3 ; Fig. 4 A). Conspecifics spent significantly more time in the zone with either maize, wheat, or bur oak compared to the no-food zone (Table 3 ; Fig. 4 B). Moreover, bur oak elicited a greater frequency of visits (Table 3 ; Fig. 4 A) and longer visit duration (Table 3 ; Fig. 4 B) spent adjacent to the acorns than to maize kernels. Table 3 Statistical results of Prostephanus truncatus mobility in food preference Treatment* df † Frequency of visits Duration Wald χ 2 P Wald χ 2 P Maize vs Blank 1 7.58 < 0.01 13.43 < 0.001 Wheat vs Blank 1 1.35 0.245 51.16 < 0.001 Bur oak vs Blank 1 3.45 0.063 25.93 < 0.001 Maize vs Wheat 1 6.49 < 0.01 3.11 0.078 Maize vs Bur oak 1 13.84 < 0.001 20.98 < 0.001 Wheat vs Bur oak 1 0.45 0.501 0.73 0.394 *Grains and acorns were used in food preference mobility assays. † A negative binomial generalized linear model was used in data analysis. Boring Activity of Prostephanus truncatus in Acorns After 2 or 4 weeks of foraging by P. truncatus adults in the vials with host material, no individuals were found inside the undamaged acorns from any of the oak species (Fig. 5 A and B). By contrast, after foraging for 2 weeks, 72%, 76%, and 90% of the released adults were found present inside the damaged acorns of black oak, red oak, and bur oak, respectively. Despite detecting significant differences among acorns species (χ 2 = 10.90, df = 2, P < 0.01), pairwise comparisons showed that infestation rates did not differ between them (Fig. 5 A). After foraging for 4 weeks, 47%, 50%, and 60% of the adults were found inside the damaged acorns of black oak, red oak, and bur oak, respectively. Again, there were no differences among acorn species (χ 2 = 3.72, df = 2, P = 0.156, Fig. 5 B). Survival of Prostephanus truncatus on Acorns After foraging for 2 weeks, 91%, 79%, 90%, and 92% of the adults survived on the damaged acorns of black oak, red oak, bur oak, and maize, respectively, with an overall difference among treatments (χ 2 = 10.42, df = 3, P < 0.05). However, there were no differences in adult survival between acorns species (Fig. 6 A). After foraging for 4 weeks, 15%, 27%, 62%, and 85% of the adults survived on the damaged acorns of black oak, red oak, bur oak, and maize, respectively. Survival was higher on bur oak than black oak and red oak but was significantly lower than survival on maize (χ 2 = 124.09, df = 3, P < 0.001, Fig. 6 B). By contrast, after 2 or 4 weeks, there were few or no survivors found on the undamaged acorns of any of the oak species. There was also no significant difference in survival among undamaged acorn species and the blank control (χ 2 = 7.55, df = 3, P = 0.056, Fig. 6 A; no statistics were computed due to a constant variable, Fig. 6 B). Fines Production of Prostephanus truncatus on Acorns Overall, there were significant differences in fines production at 2 (F 5,12 = 21.24, P < 0.001) and 4 weeks (F 5,12 = 26.13, P < 0.001) among treatments. At 2 weeks, P. truncatus feeding on the damaged bur oak produced the highest fines, which were 2.3- and 1.9-fold greater than black oak and red oak, respectively (Fig. 7 A). At 4 weeks, P. truncatus feeding on the damaged bur oak produced 2.1-fold more fines than on black oak, but not significantly more than on red oak (Fig. 7 B). The weight of fines production was higher for damaged acorns than undamaged acorns across oak species (Fig. 7 A and B). Reproductive Fitness of Prostephanus truncatus on Acorns After 10 weeks, P. truncatus F 1 progeny were found on damaged acorns of bur oak (Fig. 8 A), but not on undamaged acorns of bur oak (Fig. 8 B) or on the acorns of any other oaks regardless of condition (damaged or undamaged). Overall, acorn species and their condition had a significant effect on P. truncatus reproductive fitness (F 5,12 = 6.49, P < 0.01). Conspecifics produced an average of 19.0 (± 2.1) F 1 offsprings on damaged acorns of bur oak, which was greater than that on undamaged acorns of bur oak and on damaged acorns of black oak and red oak (Fig. 9 ). Discussion Laboratory studies have shown that P. truncatus can reproduce on a wide range of woody plant species from its invaded range in Africa (Helbig et al. 1990 ; Nang’ayo et al. 1993 , 1996, 2002 ; Ramirez-Martinez et al. 1994; Hill et al. 2002 ; Nansen et al. 2002 , 2004 ; Sadiku et al. 2019 ; Mlambo et al. 2024 ), and a closely related species, R. dominica , has been reported to survive and reproduce on a variety of oak acorns in North America (Wright et al. 1990 ; Edde and Phillips 2006 ; Jia et al. 2008 ). Thus, natural habitats in North America landscapes, especially those including oak acorns, may function as reservoirs for the invasive P. truncatus and influence its movement into and out of grain storage, potentially facilitating its dispersal across the landscape. To assess the risk posed by North America natural habitats in spreading P. truncatus , this study determined the attractiveness of black oak, red oak, and bur oak acorns to conspecifics, compared the profiles of VOC emissions from these acorns, measured food preference with mobility assays, and investigated if P. truncatus can feed, survive, and reproduce on them. P. truncatus adults responded positively to volatiles from all three species of oak acorns and maize compared to the blank control in a short-distance choice bioassay, which suggests that they can use odor-mediated orientation at least over short distances rather than just encountering the food substrate by chance. We focused on short-range attractions in this study because P. truncatus was previously shown to arrest and exhibit attraction to two of its preferred stored product hosts (maize and cassava) at short ranges (Wright et al. 1993 ; Hodges 1994 ; Scholz et al. 1997a ), but not at long ranges (Wright et al. 1993 ; Tigar et al. 1994 ). In addition, Scholz et al. ( 1997a ) demonstrated that P. truncatus responded positively to native woody species from Africa at short ranges. Arnold et al. ( 2015 ) reported no evidence of color-mediated host selection in P. truncatus adults, suggesting that host preferences might predominantly be mediated by VOCs. Additional studies are needed to evaluate the potential use of these cues in long range orientation, which might play a role in landscape utilization. Furthermore, P. truncatus was more attracted to bur oak acorns rather than those from black oak, red oak, or its primary host, maize. This preference for bur oak acorns indicates that P. truncatus can perceive the difference in acorns among oak species, suggesting that this pest may use VOCs as chemical cues to locate its preferred food sources during the host-selection process as we effectively excluded visual and other cues during these bioassays. In a subsequent close-range assay, we allowed P. truncatus to use a combination of olfactory, visual, tactile and gustatory cues to differentiate between potential food sources. We found that P. truncatus visited bur oak acorns significantly more frequently and for longer durations than maize, indicating a stronger preference for bur oak acorns. Interestingly, this preference suggests that P. truncatus may still be in the early processes of shifting its dietary niche to include stored commodities and retains an ability to use resources from woody plants, which are thought to be its ancestral food sources (Quellhorst et al. 2021 ). It is likely that oaks constitute at least a part of the endemic vegetation in the native range of P. truncatus in Central America (Nixon 2006 ). Further research using oak species in P. truncatus native range is needed to evaluate the role of acorns and if VOCs from oak acorns within the native range are similar to those found in bur oak acorns. Because odors likely play a prominent role in host selection by P. truncatus , we analyzed and compared the volatile profiles of acorns and grains to look for qualitative and/or quantitative differences in profiles on which conspecifics could act. VOC profiles from black oak, red oak and bur oak acorns, as well as maize and wheat, share some compounds, but also exhibit distinct differences in their overall composition (Table 2 ). Interestingly, black oak, red oak, and bur oak acorns shared 2,4-dimethyl-1-heptene as the most abundant compound, whereas maize and wheat shared 2-butyl-1-octanol as the most abundant compound. 4-methyl-decane and 2,6-dimethyl-nonane were also abundant in each treatment of acorns and grains. The initial attraction of P. truncatus to black oak, red oak and bur oak, maize and wheat may be due to these shared volatile cues emitted by acorns and grains. Compounds uniquely emitted by or emitted in higher ratios by bur oak acorns in comparison to other treatments (Table 2 ) may be important for the odor preference by P. truncatus . For example, both 3-hepten-2-one and 2-(5-methyl-furan-2-yl)-propionaldehyde were only present in bur oak acorns and not in any other treatment. There were also higher emissions of heptanone and 2,7-dimethyl-octanol from bur oak acorns compared to other treatments. It has been reported that the compound 2,4-dimethyl-1-heptene is emitted by Gentiana asclepiadea leaves (Georgieva et al. 2005 ), Citrus grandis fruits (Chung et al. 2012 ), Anoplophora glabripennis infested Acer trees (Makarow et al. 2020 ), Aspergillus flavus or Fusarium verticillioides inoculated/uninoculated wheats (Van Winkle et al. 2022 ; Ponce et al. 2022 , 2023 ), Amorphophallus titanium flowers (Kang et al. 2023 ), spruce trees ( Picea abies ) under drought stress (Huber et al. 2024 ), and Cnaphalocrocis medinalis egg-treated rice plants (Tian et al. 2025 ). Although host plant-derived and stress-related compounds can enhance the efficiency of pheromone traps in some insect species (Birkinshaw 1998 ; Likhayo and Hodges 2000 ; Bashir et al. 2001 ; Morrison et al. 2018 ), maize volatiles did not improve P. truncatus trap captures or upwind flight responses (Hodges et al. 1998 ; Fadamiro et al. 1998 ). Our study demonstrated significant short-range attraction to bur oak acorns, exceeding that of maize. Further research is needed to determine whether the compounds associated with bur oak acorns can elicit attraction over longer ranges and synergize pheromone traps. In the final experiment, we investigated the ability of P. truncatus adults to bore into, feed on, survive, and reproduce in acorns of different oak species. The results showed that P. truncatus adults were unable to colonize undamaged acorns, indicating a preference for damaged acorns and suggesting that damage is necessary for colonization in the field. The acorn weevil Curculio glandium Marsham (Coleoptera: Curculionidae) (Reut et al. 2022 ), the acorn moth Valentinia glandulella (Riley) (Lepidoptera: Blastobasidae) (Galford and Weiss-Cottrill 1991 ), and the lesser grain borer R. dominica (Jia et al. 2008 ) also prefer damaged acorns. Surprisingly, other acorn weevils such as Curculio venosus , Curculio pellitus , and Curculio elephas do not exhibit this preference and they can infest undamaged acorns (Reut et al. 2021 , 2022 ). Natural or mechanical damage to acorns that have fallen to the ground is also common, providing another route of entry. Thus, P. truncatus may infest naturally cracked or mammal-damaged acorns or follow infestation by some acorn weevils. Together, this acorn insect community may make oaks a riskier tree in the landscape that can facilitate invasion by P. truncatus in North America. After P. truncatus adults bored into damaged black oak, red oak, and bur oak acorns, they produced dust or fines as a byproduct of their tunneling and feeding activities in all three species. However, the quantity of fines produced from bur oak was far greater than those produced from black oak and red oak. It is possible that the physical and chemical properties of bur oak acorns facilitated more tunnelling and feeding by P. truncatus compared to other oak species. According to previous studies (Von Berg and Biliwa 1990 ; Popoola et al. 2015 ), the quantity of dust produced by P. truncatus during tunneling and feeding activities is a reliable indicator of both the degree of damage and the suitability of the host. For example, P. truncatus tended to produce large amounts of dust while boring, tunneling, and feeding on maize (Quellhorst et al. 2021 ). Ramírez-Martínez and Silver ( 1983 ) reported that maize phenotypes with soft pericarp and endosperm are most vulnerable to attack by P. truncatus because conspecifics can tunnel and feed easily. Due to more extensive tunnelling and feeding activities, P. truncatus produced more dust in maize than in sorghum and larger quantities of dust were generated in the high-yielding sorghum varieties (Framida and Naga-White) compared to the local low yielding variety (Mankaraga) (Mailafiya 2003 ). As an internal feeder, P. truncatus completes its entire life cycle within its host, which provides sites for both feeding and reproduction (Sadiku et al. 2019 ). The undamaged acorns of all tested oak species were unsuitable for P. truncatus adults to feed and reproduce, presumably because it was difficult for them to gain entry. Despite being able to feed on the damaged acorns of all species, P. truncatus adults could only successfully reproduce on bur oak, suggesting that it is the only acorn species tested in this study capable of serving as a suitable host in the field. It is possible that the black and red oak acorns lack sufficient nutrients needed to support P. truncatus larval development. Alternatively, it is possible that the black and red oak acorns contain antifeedant or antinutritive compounds that make it difficult for developing beetles to sufficiently feed to complete their development. It has been reported that tannins can act as antinutritional factors and feeding deterrents for many insects by binding to proteins, reducing the efficacy of digestion and nutrient absorption, and causing midgut lesions (El‑Aswad et al. 2023). Acorns from the red oak group (e.g., red or black oak) contain two to four times more tannins than those from the white oak group (e.g., bur oak) (Wood 2005 ). Consequently, the higher tannin levels in black and red oak acorns are likely to inhibit P. truncatus feeding, development, and reproduction due to their toxic and anti-nutritional effects. The range of bur oaks begins in southern Texas, where P. truncatus has been intercepted in the past (Arthur et al. 2019 ), and the range continues northward into Southern Canada (Gucker 2011 ). As a result, this species may act in providing an invasion corridor for P. truncatus into the Great Plains where the majority of maize production occurs in the United States of America. Jia et al. ( 2008 ) found that R. dominica , a closely related bostrichid, can feed and reproduce on damaged acorns of six oak species, including chinkapin oak Quercus muehlenbergii , pin oak Quercus palustris , red oak Quercus rubra , Shumard oak Quercus shumardii , bur oak Quercus macrocarpa , and English oak Quercus robur , but not on their undamaged acorns. Earlier studies have also shown that R. dominica can reproduce on acorns of chinkapin oak Q. muehlenbergii (Wright et al. 1990 ) and post oak Quercus stellata (Edde and Phillips 2006 ). Moreover, acorn shells are naturally broken with seasonal freezing and thawing cycles or commonly damaged by other acorn predators, so damaged acorns are abundant due to both natural processes, small mammal predation, and primary insect infestation (Jia et al. 2008 ). Thus, the lacking capacity of P. truncatus to penetrate undamaged acorns may not be a real limiting factor, and bur oak acorns in natural habitats could potentially serve as temporary reservoirs to sustain P. truncatus if there was no other food available, thereby facilitating long-range dispersal. Studies have been conducted to understand the potential hosts of P. truncatus in its endemic and invaded range. For example, of the 81 local tree species tested in Kenya, 23 were found favorable to P. truncatus for reproduction (Nang’ayo et al. 1993 ). P. truncatus adults and larvae were found in branches of Spondias purpurea L. (Anacardiaceae), Lannea nigritana (Scott Elliot) Keay (Anacardiaceae), Bursera fagaroides (Kunth) Engl. (Burseraceae), Commiphora riparia Engl. (Burseraceae), and Commiphora africana Engl. (Burseraceae) that have been girdled by other insects, especially cerambycids, suggesting that natural populations of P. truncatus may target already damaged woody plants as part of its realized niche to feed and reproduce (Nang’ayo et al. 1993 ; Ramírez-Martínez et al. 1994 ; Borgemeister et al. 1998b ). Nansen et al. ( 2004 ) examined the performance of P. truncatus on a variety of tree species native to Africa and found that it can reproduce on the branches from four species of trees or shrubs ( Delonix regia , Ceiba pentandra , Manihot esculenta , and Ficus exasperata ) and on the roots from two species ( Ficus capensis , and F. exasperata ). They also demonstrated that P. truncatus can reproduce on the seeds of teak Tectona grandis (L.), highlighting an interaction between this pest and tree seeds. However, there has been no assessment of the seeds or flora of North America for use as a potential host by P. truncatus , which is of interest given its invasion potential. While we have confirmed the acorns of one oak species that can be used by P. truncatus , more studies are needed to fully understand the extent to which tree seeds in natural environments serve as a crucial food source and breeding substrate for this invasive species. In conclusion, this study demonstrates that P. truncatus prefers bur oak acorns and volatiles emitted by bur oak acorns are more attractive to this beetle than maize, its main common host commodity. P. truncatus can feed and reproduce on damaged bur oak acorns. Bur oak acorns provide a potential food source and natural habitat where P. truncatus may be attracted to survive and spread across the landscape, alluding to a heightened risk for this invasive pest in North America. Declarations Acknowledgements We would like to thank Hannah Quellhorst (KSU), Jennifer Abshire (USDA), Kathy Leonard (USDA) and the rest of the Morrison and Scully labs (USDA) for their excellent technical assistance. This manuscript is contribution No. 25-238-J from the Kansas Agricultural Experiment Station, Kansas State University, Manhattan, Kansas, USA. The use of trade names is for the purposes of providing scientific information only and does not constitute endorsement by the United States Department of Agriculture (USDA) or Kansas State University (KSU). The USDA and KSU are equal opportunity employers. Author Contributions QLM, WRM, JFC, KYZ and EDS conceived the ideas and designed the experiments; QLM, BM and MKM performed the experiments and collected the data. MH, WRM, MKM, BM and QLM performed GC-MS analyses. QLM, WRM, MH, MKM and BM analyzed the data. QLM, WRM, JFC, KYZ and EDS led the writing of the manuscript. MH, MKM, BM, MT and DHW edited the first draft of the manuscript. All authors reviewed and approved the final manuscript. Funding Open access funding provided by Kansas State University. This project was supported by the Agriculture and Food Research Initiative (AFRI) Competitive Grant #2024-67013-42400 from the USDA National Institute of Food and Agriculture’s Foundational and Applied Program. Data Availability Datasets can be accessed through the Ag Data Commons (DOI will be inserted upon approval). Competing Interests The authors declare no competing interests. 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17:00:59","extension":"html","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":214836,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7545462/v1/da39659e0017863a2dc90872.html"},{"id":92018068,"identity":"73b764fb-44e8-4d93-a6b2-b53e776715c5","added_by":"auto","created_at":"2025-09-23 17:00:59","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":146616,"visible":true,"origin":"","legend":"\u003cp\u003eResponse of adult \u003cem\u003eProstephanus truncatus\u003c/em\u003e in two-choice pitfall bioassay to odors from A) different oak acorns and B) grains and bur oak acorns. Each treatment included n = 74 replicates, with one adult individual per replicate. For each paired treatment, symbols *, **, and *** represent a significant difference between treatments at the \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, 0.01, and 0.001 levels in a chi-square goodness of fit test, respectively, and ns denotes a non-significant difference.\u003c/p\u003e","description":"","filename":"image2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7545462/v1/5e7caf47050cc563955a9283.jpeg"},{"id":92018729,"identity":"49dfe12b-c139-4fdf-8a4b-e93eee11cb8f","added_by":"auto","created_at":"2025-09-23 17:08:59","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":96498,"visible":true,"origin":"","legend":"\u003cp\u003eNon-metric multidimensional scaling (NMDS) ordination plot of volatile compound profiles from acorns and grains. Each treatment included n = 5 replicates. NMDS analysis was conducted based on the pairwise Bray–Curtis similarity between samples. Polygons represent convex hulls drawn between samples and are color coded similarly to treatments. There were a total of n = 1000 permutations, and stress was \u0026lt; 0.10, enabling adequate interpretation.\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7545462/v1/428994227a040ccef880468f.jpeg"},{"id":92018066,"identity":"20a6e41f-b904-45ad-ab7d-2388ea94cf7a","added_by":"auto","created_at":"2025-09-23 17:00:59","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":217596,"visible":true,"origin":"","legend":"\u003cp\u003eNormalized emissions rate of volatile compounds from oak acorns and grains. Within a graph, different letters represent a significant difference between treatments (Tukey HSD, \u003cem\u003eα\u003c/em\u003e = 0.05). In the box plots, the whiskers represent the range of data points from the 25th quartile to the minimum value and from the 75th quartile to the maximum value, and the horizontal line and symbol × within the box indicates the median and mean, respectively. There were n = 5 replicates per treatment.\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7545462/v1/36f356c7c5c48388a1d67bf5.jpeg"},{"id":92018070,"identity":"2cbeff5a-84be-4c21-af6c-34d9bb19d085","added_by":"auto","created_at":"2025-09-23 17:00:59","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":219102,"visible":true,"origin":"","legend":"\u003cp\u003eVisitation A) frequency and B) duration of adult \u003cem\u003eProstephanus truncatus\u003c/em\u003ein food zones containing grains and bur oak acorns. Each treatment included n =18 individual adult replicates. For each paired treatment, symbols *, **, and *** represent a significant difference between treatments at the \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, 0.01, and 0.001 levels in a negative binomial GLM test, respectively, and ns denotes a non-significant difference. In the box plots, the whiskers represent the range of data points from the 25th quartile to the minimum value and from the 75th quartile to the maximum value, outliers noted beyond the whiskers, and the horizontal line and symbol × within the box indicates the median and mean, respectively.\u003c/p\u003e","description":"","filename":"image5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7545462/v1/8c3f50cab5ec40328ecc4925.jpeg"},{"id":92018735,"identity":"b1e00d43-13e2-4ecb-a384-dd9f00f30501","added_by":"auto","created_at":"2025-09-23 17:08:59","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":191653,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of adult \u003cem\u003eProstephanus truncatus\u003c/em\u003e present inside undamaged and damaged acorns of different oak species at A) 2 and B) 4 weeks. Undamaged acorns consisted of a whole intact acorn, whereas damaged acorns had three 2 mm holes drilled in the adaxial surface of the shell of each acorn. Each treatment included n = 5 replicates, with 20 adults per replicate. Within a graph, different letters represent a significant difference between treatments (chi-square test of independence with Bonferroni correction, \u003cem\u003eα\u003c/em\u003e = 0.05). In the box plots, the whiskers represent the range of data points from the 25th quartile to the minimum value and from the 75th quartile to the maximum value, and the horizontal line and symbol × within the box indicates the median and mean, respectively.\u003c/p\u003e","description":"","filename":"image6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7545462/v1/c9f6b5c9d548050480434a8b.jpeg"},{"id":92019816,"identity":"ebb5ad44-f070-4a68-8592-c1388106e1ea","added_by":"auto","created_at":"2025-09-23 17:24:59","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":172305,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival of adult \u003cem\u003eProstephanus truncatus\u003c/em\u003e on undamaged and damaged acorns of different oak species at A) 2 and B) 4 weeks. Undamaged acorns consisted of a whole intact acorn, whereas damaged acorns had three 2 mm holes drilled in the adaxial surface of the shell of each acorn. Each treatment included n = 5 replicates, with 20 adults per replicate. Within a graph, different letters represent a significant difference between treatments (chi-square test of independence with Bonferroni correction, \u003cem\u003eα\u003c/em\u003e = 0.05). In the box plots, the whiskers represent the range of data points from the 25th quartile to the minimum value and from the 75th quartile to the maximum value, and the horizontal line and symbol × within the box indicates the median and mean, respectively.\u003c/p\u003e","description":"","filename":"image7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7545462/v1/578257de5d11bc8119d3dc0e.jpeg"},{"id":92018076,"identity":"f81dbb77-acc2-451c-bb48-752992de2af0","added_by":"auto","created_at":"2025-09-23 17:00:59","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":205655,"visible":true,"origin":"","legend":"\u003cp\u003eFines produced by adult \u003cem\u003eProstephanus truncatus\u003c/em\u003e on undamaged and damaged acorns of different oak species at A) 2 and B) 4 weeks. Undamaged acorns consisted of a whole intact acorn, whereas damaged acorns had three 2 mm holes drilled in the adaxial surface of the shell of each acorn. Each treatment included n = 5 replicates, with 20 adults per replicate. Within a graph, different letters represent a significant difference between treatments (linear mixed model test with Bonferroni correction, \u003cem\u003eα\u003c/em\u003e = 0.05). In the box plots, the whiskers represent the range of data points from the 25th quartile to the minimum value and from the 75th quartile to the maximum value, and the horizontal line and symbol × within the box indicates the median and mean, respectively.\u003c/p\u003e","description":"","filename":"image8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7545462/v1/508c4356e75715a1ffc2e312.jpeg"},{"id":92018072,"identity":"5dd5b953-077c-4845-a44a-8583c112b2b9","added_by":"auto","created_at":"2025-09-23 17:00:59","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":184028,"visible":true,"origin":"","legend":"\u003cp\u003eX-ray images of A) infested acorns and B) non-infested of bur oak caused by adult \u003cem\u003eProstephanus truncatus\u003c/em\u003e. Arrows indicate the presence of \u003cem\u003eProstephanus\u003c/em\u003e F\u003csub\u003e1\u003c/sub\u003e progeny in tunnels.\u003c/p\u003e","description":"","filename":"image9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7545462/v1/c1ed93890d1fba13fd055bd4.jpeg"},{"id":92018073,"identity":"2dedc030-df97-443e-91ac-7678648f66b9","added_by":"auto","created_at":"2025-09-23 17:00:59","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":126219,"visible":true,"origin":"","legend":"\u003cp\u003eTotal number of F\u003csub\u003e1\u003c/sub\u003e progeny produced by adult \u003cem\u003eProstephanus truncatus\u003c/em\u003e on undamaged and damaged acorns at 10 weeks. Undamaged acorns consisted of a whole intact acorn, whereas damaged acorns had three 2 mm holes drilled in the adaxial surface of the shell of each acorn. Each treatment included n = 25 replicates, with 20 parent adults per replicate. Within a graph, different letters represent a significant difference between treatments (linear mixed model test with Bonferroni correction, \u003cem\u003eα\u003c/em\u003e = 0.05). In the box plots, whiskers represent the range of data points from the 25th quartile to the minimum value and from the 75th quartile to the maximum value, with one outlier beyond the whiskers, and the median and mean are represented by horizontal line and × within the box, respectively.\u003c/p\u003e","description":"","filename":"image10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7545462/v1/c87702822d99784324eac564.jpeg"},{"id":97179390,"identity":"16d20139-4f86-402c-bcf8-3d453f936c8b","added_by":"auto","created_at":"2025-12-01 16:15:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2943336,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7545462/v1/a29f28d4-50be-449e-8cac-d51aa882bc56.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Odor Preference, Feeding, Survival, and Reproductive Fitness of the Invasive Larger Grain Borer Prostephanus truncatus on Acorns of Three Native North America Oak Species","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe larger grain borer, \u003cem\u003eProstephanus truncatus\u003c/em\u003e (Horn) (Coleoptera: Bostrichidae), is an invasive stored-product insect pest that is native to Mexico and Central America (Hodges \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). The species was accidentally introduced into Tanzania in the late 1970s (Hodges et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1983\u003c/span\u003e) and subsequently spread across much of sub-Saharan Africa (Holst and Meikle \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). It has also occasionally been intercepted in the southern USA, Asia, and Europe (Quellhorst et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and interceptions are expected to increase moving forward (Harman et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Although it is not established outside of Mexico, Central America, or Africa, Arthur et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) used species distribution models (SDMs) based on current climate data from locations with documented populations to predict that large areas of the tropics in Asia and the Western Hemisphere could support \u003cem\u003eP. truncatus\u003c/em\u003e populations if the species was introduced. Moreover, Harman et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) demonstrated that the threat of range expansion by \u003cem\u003eP. truncatus\u003c/em\u003e was most likely to worsen in the coming decades, and that future changes in environmental conditions could result in a higher risk to temperate regions. In a two-year study involving trapping at 19 locations along a latitudinal gradient across North America, Quellhorst et al. (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) only found \u003cem\u003eP. truncatus\u003c/em\u003e in Mexico. However, the continued range expansion of \u003cem\u003eP. truncatus\u003c/em\u003e is a global concern due to climate change and globalization.\u003c/p\u003e\u003cp\u003e\u003cem\u003eP. truncatus\u003c/em\u003e is hypothesized to have originally been a wood-boring insect and still retains this capability (Nang\u0026rsquo;ayo et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Ram\u0026iacute;rez-Mart\u0026iacute;nez et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Scholz et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1997a\u003c/span\u003e), but it has expanded its host range to include maize and cassava (Hodges et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Sadiku et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Maize can become infested with \u003cem\u003eP. truncatus\u003c/em\u003e while still on the cob in the field, and infestations continue at storage facilities (Golob and Hanks \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1990\u003c/span\u003e). The ability of \u003cem\u003eP. truncatus\u003c/em\u003e to infest root and tuber crops such as cassava, yam, and sweet potato has also been documented (Nyakunga \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Osipitan et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Ejiro et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sadiku et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Interestingly, a variety of other commodities, including wheat, barley, oats, rice, and beans, are considered inferior food sources for \u003cem\u003eP. truncatus\u003c/em\u003e and all fail to serve as reproductive hosts (Hodges \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Athanassiou et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Thus, compared with other stored-product insect species that can exploit a wide range of commodities, \u003cem\u003eP. truncatus\u003c/em\u003e is primarily found exploiting stored maize and is poorly adapted to the exploitation of most other stored commodities; as such, it may offer some insights into the early stages of host shifting that led to the development of stored-product pests (Quellhorst et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Identifying original and alternative hosts of \u003cem\u003eP. truncatus\u003c/em\u003e is important for preventing its establishment and spread, especially in non-native areas.\u003c/p\u003e\u003cp\u003eDispersal of \u003cem\u003eP. truncatus\u003c/em\u003e adults away from stored products often occurs at food facilities, especially when food sources are depleted or population density is high (Hodges \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Fadamiro and Wyatt \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Scholz et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1997b\u003c/span\u003e; Altwegg et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), during which they exploit non-grain resources while moving through the landscape. Borgemeister et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1998a\u003c/span\u003e) trapped \u003cem\u003eP. truncatus\u003c/em\u003e in a primary forest, a peri-urban area, and a region with intensive agriculture in Benin and analyzed the gut contents of beetles. They found that \u003cem\u003eP. truncatus\u003c/em\u003e individuals captured in wooded areas had more lignin in their guts, whereas those in intensive agriculture settings had both starch and lignin, indicating that woody hosts were being utilized. Nang\u0026rsquo;ayo (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) conducted no-choice rearing tests in the laboratory and showed that branches of many tree species found in the Kenyan savanna were acceptable for reproduction by \u003cem\u003eP. truncatus\u003c/em\u003e, although reproductive rates were generally low and inconsistent. Similarly, Nansen et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) evaluated \u003cem\u003eP. truncatus\u003c/em\u003e performance on a variety of tree species native to Africa and observed heavy attack on fresh branches from eleven tree species and fresh roots from four tree species. They further reported successful reproduction on branches of \u003cem\u003eDelonix regia\u003c/em\u003e, \u003cem\u003eCeiba pentandra\u003c/em\u003e, \u003cem\u003eManihot esculenta\u003c/em\u003e, and \u003cem\u003eFicus exasperata\u003c/em\u003e, as well as on roots of \u003cem\u003eFicus capensis\u003c/em\u003e and \u003cem\u003eF. exasperata\u003c/em\u003e. In natural environments, the documented forest hosts for \u003cem\u003eP. truncatus\u003c/em\u003e are branches of trees in the family Anacardiaceae that have been girdled by cerambycid beetles (Ram\u0026iacute;rez-Mart\u0026iacute;nez et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Nang\u0026rsquo;ayo \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Borgemeister et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1998b\u003c/span\u003e). These studies show the potential role of wooded habitats in the ecology of \u003cem\u003eP. truncatus\u003c/em\u003e as reservoirs and breeding grounds, which may then contribute to its infestations in stored maize and cassava. Further research is needed to understand how \u003cem\u003eP. truncatus\u003c/em\u003e selects hosts and reproduces in natural environments (Quellhorst et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eImportantly, \u003cem\u003eP. truncatus\u003c/em\u003e has been found to positively respond to host-produced volatiles from starchy commodities and woody species, including maize, wheat, and wood of \u003cem\u003eCommiphora africana\u003c/em\u003e (A. Rich.) (Scholz et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1997a\u003c/span\u003e). Prior work has also determined that a single calling male \u003cem\u003eP. truncatu\u003c/em\u003es on stored maize was sufficient to initiate a large infestation (Scholz et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1997b\u003c/span\u003e). Follow-up work demonstrated that like maize, wood of \u003cem\u003eCommiphora riparia\u003c/em\u003e Engl. and \u003cem\u003eC. africana\u003c/em\u003e caused arrestment of \u003cem\u003eP. truncatus\u003c/em\u003e males (Scholz et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). In addition, other studies have also reported positive attraction in \u003cem\u003eP. truncatus\u003c/em\u003e towards maize and cassava (Wright et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Hodges \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Pike et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). Thus, it is likely that host odors can play an important role in attraction, colonization and establishment of \u003cem\u003eP. truncatus\u003c/em\u003e populations in natural environments.\u003c/p\u003e\u003cp\u003eOak trees (\u003cem\u003eQuercus\u003c/em\u003e spp.) are widely distributed across the globe from northwestern South America, through Central America, North America, Europe, the northwestern edge of Africa, and much of eastern Asia (Steele et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Particularly, oaks are a prevalent and dominant tree genus in North America (Frankel et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), especially in the southern United States, where \u003cem\u003eP. truncatus\u003c/em\u003e poses a risk of establishment (Harman et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Oak acorns are a significant resource for a range of animals, including insects. More relevantly, native oak acorn species in North America can be used for survival and reproduction by the stored-product pest, the lesser grain borer \u003cem\u003eRhyzopertha dominica\u003c/em\u003e (F.) (Coleoptera: Bostrichidae), a close relative of \u003cem\u003eP. truncatus\u003c/em\u003e (Jia et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). It is interesting to note in that study that survival and reproduction were especially prominent on damaged acorns, but not undamaged acorns. Currently, it is not known whether \u003cem\u003eP. truncatu\u003c/em\u003es is also attracted to volatiles produced by acorns or whether acorns can be used for survival and reproduction. Investigating whether \u003cem\u003eP. truncatus\u003c/em\u003e can subsist on native resources in the landscape of North America will help enhance our understanding of population subsistence and risk posed by intercepted individuals. This is particularly important for predicting potential dispersal and immigration patterns in newly invaded natural environments.\u003c/p\u003e\u003cp\u003eThe objective of this study was to evaluate the potential of acorns as sources of attractive odors, as well as the suitability of damaged and undamaged acorns as feeding and breeding substrates that could support \u003cem\u003eP. truncatus\u003c/em\u003e host-range expansion. To that end, we first conducted \u003cem\u003eP. truncatus\u003c/em\u003e odor preference assays with acorns of black oak (\u003cem\u003eQuercus velutina\u003c/em\u003e), red oak (\u003cem\u003eQuercus rubra\u003c/em\u003e) and bur oak (\u003cem\u003eQuercus macrocarpa\u003c/em\u003e) that are all native, common, and widely distributed oak species in North America, but not native to Mexico and likely novel to \u003cem\u003eP. truncatus\u003c/em\u003e. We then characterized the relative profiles of volatile organic compounds (VOCs) from these acorns and explored the semiochemical-mediated behavioral response between \u003cem\u003eP. truncatus\u003c/em\u003e and acorn species. We finally determined \u003cem\u003eP. truncatus\u003c/em\u003e feeding, survival and reproductive fitness on damaged or undamaged acorns in the laboratory. Considering the global distribution and abundance of oak trees and the impacts wrought by climate change and globalization on the geographical distribution and introduction of invasive insect pests, this study will help better assess the risk of \u003cem\u003eP. truncatus\u003c/em\u003e to establish in North America by utilizing hosts already present in the landscape so that effective biosecurity measures can be implemented.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eInsects\u003c/h2\u003e\u003cp\u003e\u003cem\u003eProstephanus truncatus\u003c/em\u003e adults were obtained from an insect colony maintained at the United States Department of Agriculture (USDA), Agricultural Research Service, Center for Grain and Animal Health Research in Manhattan, Kansas, USA. The individuals were originally collected from Mexico, in native range of \u003cem\u003eP. truncatus\u003c/em\u003e. Insects were reared on whole maize kernels in jars with screened lids and kept at 23\u0026deg;C and 45% relative humidity (RH) under continuous darkness.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAcorns and Grains\u003c/h3\u003e\n\u003cp\u003eAcorns of black oak, red oak, and bur oak were collected from the ground beneath trees in Manhattan, Kansas, USA at two locations (39.18\u0026deg;N, -96.59\u0026deg;W and 39.20\u0026deg;N, -96.62\u0026deg;W) during the fall of 2022\u0026ndash;2024. We removed the caps and discarded any acorns that had cracks or holes in the shells since these may already be infested with other insects. Intact acorns (without cracks or holes) from healthy oak trees were used in the experiments. Organic yellow maize (\u003cem\u003eZea mays\u003c/em\u003e) and hard red winter wheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e) (Heartland Mills, Marienthal, KS, USA) were also used in the experiments.\u003c/p\u003e\n\u003ch3\u003eOdor Preference Assays with Acorns and Grains\u003c/h3\u003e\n\u003cp\u003eOdor preference assays for adult \u003cem\u003eP. truncatus\u003c/em\u003e were conducted in Petri dishes (100 \u0026times; 15 mm, D \u0026times; H, VWR, Radnor, PA, USA) serving as arenas, with one individual per dish. Two holes, spaced 5 cm apart and centered over each half of the dish, were carefully drilled on the bottom using a 7/64-inch (2.8-mm) drill bit. Holes were also drilled through a piece of filter paper (85 mm, Ahlstrom-Munksj\u0026ouml;, Mt. Holly Springs, PA, USA) affixed with double-sided tape to the bottom of the arena to facilitate \u003cem\u003eP. truncatus\u003c/em\u003e movement. The holes allowed the diffusion of host volatiles into the arena so that there were point sources emissions of volatiles but no visual cues. The diffusion of volatiles was confirmed with a smoke test. For each pairwise comparison, two plastic cups (30 \u0026times; 50 mm, D \u0026times; H, CrystalWare, Lakewood, NJ, USA) were placed directly beneath the two arena holes, each containing one of the following food stimuli: a single intact acorn of black oak, red oak or bur oak; 1.5 g of maize or wheat kernels; or empty (i.e., blank control). \u003cem\u003eP. truncatus\u003c/em\u003e adults were placed individually in the center of the arena, and they were given 16 h to respond to an odor source. At the end of the trial, the number of insects choosing each treatment was recorded. There were n\u0026thinsp;=\u0026thinsp;74 replicates per treatment combination.\u003c/p\u003e\n\u003ch3\u003eHS-SPME/GC-MS Analysis of Acorns and Grains\u003c/h3\u003e\n\u003cp\u003eVOCs from acorns and grains were analyzed using headspace solid phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME/GC-MS), based on previously developed methods (Buśko et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; De Flaviis et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) with some modifications, as described below. Maize, wheat, and acorns of bur oak, black oak and red oak were ground separately with a dedicated coffee grinder (Hamilton Beach, Model 80335G, Glen Allen, VA, USA) into a fine whole flour. To prevent cross-contamination between samples, the coffee grinder was thoroughly rinsed with water, followed by repeated rinsing with hexane before use. A total of 2 g of the flour from each sample (n\u0026thinsp;=\u0026thinsp;5 replicates per treatment) was transferred into a 20-mL headspace vial (Gerstel, Linthicum Heights, MD, USA) and a vial with no flour served as a negative control. The vials were then completely sealed with magnetic screw caps with a Teflon septum. SPME was performed using an automated program on an MPS autosampler (Gerstel, Linthicum Heights, MD, USA). The flour samples were incubated at 60\u0026deg;C on a heating block for 15 min in the pre-equilibration stage, and then a 50/30 \u0026micro;m DVB/Carboxen/PDMS fiber (Supelco 57298-U, St Louis, MO, USA) was exposed for 30 min at 60\u0026deg;C to extract the VOCs. After the extraction step, the SPME fiber was desorbed in the injection port of the GC-MS for 3 min at 260\u0026deg;C in a pulse splitless mode of 40 psi followed by a purge flow of 15 mL/min. VOCs were separated using an Agilent 7890B GC (Agilent, Santa-Clara, CA, USA) coupled to a single quadrupole mass spectrometer (Agilent 5997B), using a Durabond HP-5 capillary column (30 m \u0026times; 0.25 mm \u0026times; 0.25 \u0026micro;m) (Agilent). The GC oven ran initially 1 min at 40\u0026deg;C followed by ramping from 40\u0026deg;C to 80\u0026deg;C at a rate of 7\u0026deg;C/min, then from 80\u0026deg;C to 130\u0026deg;C at a rate of 1\u0026deg;C/min, and finally from 130\u0026deg;C to 260\u0026deg;C at a rate of 10\u0026deg;C/min. The He flow rate was held constant at 1.5 mL/min. Spectra were acquired at 50 spectra/s within a range of 40\u0026ndash;380 amu. The transfer line temperature was 280\u0026deg;C and the ion source temperature was 200\u0026deg;C. Compounds were tentatively identified by comparison of spectral data with those from the NIST 17 library and by GC retention index.\u003c/p\u003e\n\u003ch3\u003eMobility in Close-range Food Preference Assays\u003c/h3\u003e\n\u003cp\u003eFollowing the odor preference for bur oak acorns observed in the choice assays, insect mobility in close-range food preference assays was recorded over a 60-min period using a video-tracking apparatus combined with EthoVision software (v. 16.0, Noldus Information Technology Inc., Leesburg, VA, USA). The equipment was set up to track six arenas (100 \u0026times; 15 mm, D \u0026times; H, VWR, Radnor, PA, USA) simultaneously, and within each arena, a single adult was observed. The arenas were placed in cutouts on white foamboard to affix position that was 80 cm below a network camera (GigE, Basler AG, Ahrenburg, Germany) and backlit with a LED light box (42 \u0026times; 30 cm, W \u0026times; L, LPB3, Litup, Shenzhen, China). A piece of filter paper (85 mm, Ahlstrom-Munksj\u0026ouml;, Mt. Holly Springs, PA, USA) was taped to the bottom of the arena to facilitate mobility. Two tiny notches exactly halfway on each side of the arena marked where food was to be placed (i.e., 2.1 cm from the edge of the arena). On either side of the arena, we left it empty (i.e., blank control), or placed a single kernel of maize, a single kernel of wheat, or a piece of bur oak acorn (approximately the same mass as a maize kernel). Stimuli were affixed in place with a 3 \u0026times; 3 mm square of parafilm (Parafilm M, Bemis Co., Davisburg, MI, USA). In total, there were 6 food comparisons, including: maize vs wheat, maize vs bur oak, wheat vs bur oak, maize vs blank, wheat vs blank, and bur oak vs blank. For each individual trial, a new Petri dish and filter paper were used to prevent confounding stimuli. After tracking, the program calculated the frequency of visits and time spent in each zone adjacent to the food source (e.g., within a 1.6-cm diameter circle) for each adult. There were n\u0026thinsp;=\u0026thinsp;18 replicates per treatment.\u003c/p\u003e\u003cp\u003e\u003cb\u003eProstephanus truncatus\u003c/b\u003e \u003cb\u003eFeeding and Survival on Acorns\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAcorns of black oak, red oak and bur oak were tested for their ability to support adult \u003cem\u003eP. truncatus\u003c/em\u003e feeding and survival. We determined \u003cem\u003eP. truncatus\u003c/em\u003e feeding, survival and reproductive fitness on both damaged and undamaged acorns. To simulate damage, three evenly spaced holes were drilled on the adaxial surface of each acorn shell using a Dremel multi-tool (Model 300, Racine, WI, USA) with a 5/64-inch (2-mm) drill bit. A piece of filter paper (60 mm, Whatman, GE Healthcare Life Sciences, Buckinghamshire, UK) was taped to the bottom of a glass jar (118 mL, Ball Quilted Crystal, Atlanta, GA, USA). A total of 20 adults were placed on a single damaged or undamaged acorn (red oak, black oak, or bur oak) in the jar with a screened lid in a no-choice assay. A jar with no food served as a negative control and a jar with 2.5 g of maize kernels served as a positive control. The jars were left undisturbed for 2 and 4 weeks to allow the adults to feed on the acorns at 23\u0026deg;C and 45% RH under continuous darkness. Afterwards, each acorn was dissected to check for the presence of alive or dead adults, including those found inside or outside the acorn. The rates of adult survival and presence inside acorns were expressed as percentages, dividing the number of individuals that were alive or present inside acorns by the total number of adults in the original sample, respectively. At the end of each period, an X-ray imaging system (MX-20, Faxitron, Wheeling, IL, USA) was also used to examine the acorns for evidence of insect tunneling and feeding activity. Feeding damage was quantified based on the amount of fines produced, and the fines were weighed using a precision balance (B120S, Sartorius Basic, G\u0026ouml;ttingen, Germany). In total, there were 8 treatments, including: acorns (damaged or undamaged) from bur oak, black oak and red oak, maize as a positive control, and no food as a negative control. There were n\u0026thinsp;=\u0026thinsp;5 replicates per treatment.\u003c/p\u003e\u003cp\u003e\u003cb\u003eProstephanus truncatus\u003c/b\u003e \u003cb\u003eReproductive Fitness on Acorns\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDamaged and undamaged acorns of black oak, red oak and bur oak were tested for their ability to support production of \u003cem\u003eP. truncatus\u003c/em\u003e F\u003csub\u003e1\u003c/sub\u003e progeny. A piece of filter paper (60 mm, Whatman, GE Healthcare Life Sciences, Buckinghamshire, UK) was taped to the bottom of a glass jar (118 mL, Ball Quilted Crystal, Atlanta, GA, USA) and 20 adults were placed in the jar with a single damaged or undamaged acorn for a no-choice test. The resulting jars were left undisturbed under the same conditions as above for 4 weeks, after which the adults were removed. Subsequently, the acorns were maintained for 6 weeks. At the end of this period, the same X-ray imaging system mentioned above was used to examine the acorns for evidence of insect reproductive success. Then, the acorn was dissected to count the total number of \u003cem\u003eP. truncatus\u003c/em\u003e F\u003csub\u003e1\u003c/sub\u003e progeny, including larvae, pupae and adults produced. There were 6 treatments, consisting of damaged or undamaged acorns of black oak, red oak, and bur oak, each with n\u0026thinsp;=\u0026thinsp;25 replicates per treatment.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eA Chi-squared goodness of fit test was used to determine whether there were any odor preferences by \u003cem\u003eP. truncatus\u003c/em\u003e. Except where otherwise noted, the significance level was \u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05 for all analyses. Percentages of final choices for each food were calculated to describe overall trends in odor preference.\u003c/p\u003e\u003cp\u003eTo characterize the VOCs of each sample, raw peak areas were extracted from the GC and total ion chromatogram (TIC), and peaks were tentatively identified in profiles automatically using MassHunter Unknowns Analysis (Agilent Technologies, Inc., Santa Clara, CA, USA) with a minimum match factor of 70% to the NIST17 library. Peaks with a height less than 0.3% of the tallest peak were excluded from the exported peak table. Compounds were aligned across samples by pulling underlying \u003cem\u003em/z\u003c/em\u003e ratio data from public repositories and flexibly aligning compounds based on structural matches and retention time using the R package \u003cem\u003euafR\u003c/em\u003e (Stratton et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Singleton compounds were deleted as they represented transient emissions that are not indicative of differences among treatments. Pairwise Bray-Curtis similarities were calculated among samples, and a non-metric multidimensional scaling (NMDS) plot was used to visualize the differences in VOC profiles among treatments. A total of n\u0026thinsp;=\u0026thinsp;1000 permutations were used for the ordination procedure. Stress values for the NMDS procedure were \u0026lt;\u0026thinsp;0.10, indicating that good interpretation was possible. Analysis of similarities (ANOSIM) was used to determine significant differences for VOC emissions among treatments, while similarity percentage (SIMPER) was used to determine the major compounds significantly contributing to differences among the groups. Permutations for both analyses were n\u0026thinsp;=\u0026thinsp;1000. Based on the SIMPER analysis, differences in the emissions of key compounds were visualized using boxplots from the \u003cem\u003eggplot2\u003c/em\u003e package in R (Wickham \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). For all multivariate statistics of VOCs, the R Package \u003cem\u003evegan\u003c/em\u003e was used (Oksanen et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). A table visualizing the VOC emissions of oak acorns and grains was created with the \u003cem\u003egt\u003c/em\u003e package in R (Iannone et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTo analyze mobility in close-range food preference assays, two dependent variables, frequency and duration of visits to each food zone, were tested using a generalized linear model (GLM) with a negative binomial likelihood and a log link function. The fixed, explanatory variables included the food stimuli (blank control, maize, wheat, or bur oak acorn) and the main effects of each stimuli comparison were estimated. Means of frequency and duration of visits to each food zone were calculated to describe overall trends in food preference.\u003c/p\u003e\u003cp\u003eFor \u003cem\u003eP. truncatus\u003c/em\u003e survival and presence inside acorns, there were three factors, acorn species (black oak, red oak, or bur oak), acorn status (damaged or undamaged), and time (2 or 4 weeks). A Chi-square test of independence was used to determine whether there was a statistically significant association between the factors and the survival rates or percentages of \u003cem\u003eP. truncatus\u003c/em\u003e inside acorns. When a significant association was found, post hoc pairwise comparisons with Bonferroni correction were then performed to examine if treatments were statistically different.\u003c/p\u003e\u003cp\u003eTo analyze \u003cem\u003eP. truncatus\u003c/em\u003e feeding and reproduction on acorns, a linear mixed model (LMM) with Bonferroni correction was used to compare the amounts of fines production and the numbers of F\u003csub\u003e1\u003c/sub\u003e progeny produced on damaged and undamaged acorns of three oak species. The fixed, explanatory variables included potential food sources (black oak, red oak, bur oak, or maize) and status of acorns (damaged or undamaged). Upon a significant result from the overall model, Tukey\u0026rsquo;s HSD was used for multiple comparisons.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eOdor Preference of\u003c/b\u003e \u003cb\u003eProstephanus truncatus\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn food odor preference tests, \u003cem\u003eP. truncatus\u003c/em\u003e was significantly more attracted to acorns of black oak and bur oak, maize, and wheat than to the blank control (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and B). By contrast, there was no difference between red oak and the control (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Bur oak was significantly more attractive than black oak, red oak (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), and the maize host on which \u003cem\u003eP. truncatus\u003c/em\u003e colony was reared (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStatistical results of \u003cem\u003eProstephanus truncates\u003c/em\u003e odor preference\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003edf\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaize vs Blank\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWheat vs Blank\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBur oak vs Blank\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack oak vs Blank\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRed oak vs Blank\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.237\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaize vs Wheat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.579\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaize vs Bur oak\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWheat vs Bur oak\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.317\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack oak vs Bur oak\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRed oak vs Bur oak\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlack oak vs Red oak\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.223\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Grains and acorns were used as odors in two-choice pitfall traps.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u0026dagger;\u003c/sup\u003e Chi-square goodness of fit test was used in data analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eVOCs Emitted by Acorns and Grains\u003c/h3\u003e\n\u003cp\u003eOut of 132 tentatively identified VOCs from oak acorns and grains through the HS-SPME/GC-MS analysis, 28 compounds were detected with a relative abundance greater than 1% in one treatment (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Black oak, red oak, bur oak, maize, and wheat had 22, 22, 24, 20, and 21 compounds, respectively. 2,4-dimethyl-1-heptene, 2-butyl-1-octanol, 4-methyl-decane and 2,6-dimethyl-nonane were the four most abundant compounds in each treatment. 2,4-dimethyl-1-heptene was the most abundant compound in acorns of black oak, red oak, and bur oak, whereas 2-butyl-1-octanol was the most abundant one in maize and wheat. Two compounds emitted from bur oak acorns, 3-hepten-2-one and 2-(5-methyl-furan-2-yl)-propionaldehyde, were unique compared to other treatments. There was some overlap in VOC compositions of maize and wheat grains, while there was significant differentiation among the three acorn species as well as the acorns and the grains (ANOSIM: R\u0026thinsp;=\u0026thinsp;0.744, Permutations\u0026thinsp;=\u0026thinsp;1000, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The VOC composition of bur oak acorns was less variable than the red and black oak acorns (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Six compounds, including 2-butyl-octanol, 2,4-dimethyl-1-heptene, 2,6-dimethyl-nonane, 2,7-dimethyl-octanol, 4-methyl-decane, and heptanone, were shown to cumulatively contribute to a\u0026thinsp;\u0026gt;\u0026thinsp;50% difference between bur oak and others including black oak, red oak, maize, and wheat, and there were significant differences among treatments in their emissions of these compounds (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Tukey\u0026rsquo;s HSD tests indicated that there were higher heptanone emissions by bur oak compared to black oak, red oak, maize, and wheat. Finally, bur oak emitted higher levels of 2,7-dimethyl-octanol than maize and wheat.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003eSummary of volatiles tentatively identified by headspace GC-MS from oak acorns and grains potentially used by \u003cem\u003eProstephanus truncates\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cimg 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\" width=\"584\" height=\"728\"\u003e\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eClose-range Food Preference by\u003c/b\u003e \u003cb\u003eProstephanus truncatus\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn the close-range food preference mobility assays, \u003cem\u003eP. truncatus\u003c/em\u003e visited the zone with maize significantly more than the no-food zone (blank control), but no significant differences were observed in the frequencies of visits to wheat or bur oak acorns (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Conspecifics spent significantly more time in the zone with either maize, wheat, or bur oak compared to the no-food zone (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Moreover, bur oak elicited a greater frequency of visits (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA) and longer visit duration (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB) spent adjacent to the acorns than to maize kernels.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStatistical results of \u003cem\u003eProstephanus truncatus\u003c/em\u003e mobility in food preference\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTreatment*\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003edf\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eFrequency of visits\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eDuration\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWald χ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWald χ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaize vs Blank\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e13.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWheat vs Blank\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.245\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e51.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBur oak vs Blank\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.063\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e25.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaize vs Wheat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaize vs Bur oak\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e20.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWheat vs Bur oak\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.501\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.394\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Grains and acorns were used in food preference mobility assays.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e\u003cb\u003e\u0026dagger;\u003c/b\u003e\u003c/sup\u003eA negative binomial generalized linear model was used in data analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eBoring Activity of\u003c/b\u003e \u003cb\u003eProstephanus truncatus\u003c/b\u003e \u003cb\u003ein Acorns\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAfter 2 or 4 weeks of foraging by \u003cem\u003eP. truncatus\u003c/em\u003e adults in the vials with host material, no individuals were found inside the undamaged acorns from any of the oak species (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA and B). By contrast, after foraging for 2 weeks, 72%, 76%, and 90% of the released adults were found present inside the damaged acorns of black oak, red oak, and bur oak, respectively. Despite detecting significant differences among acorns species (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;10.90, df\u0026thinsp;=\u0026thinsp;2, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), pairwise comparisons showed that infestation rates did not differ between them (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). After foraging for 4 weeks, 47%, 50%, and 60% of the adults were found inside the damaged acorns of black oak, red oak, and bur oak, respectively. Again, there were no differences among acorn species (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;3.72, df\u0026thinsp;=\u0026thinsp;2, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.156, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSurvival of\u003c/b\u003e \u003cb\u003eProstephanus truncatus\u003c/b\u003e \u003cb\u003eon Acorns\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAfter foraging for 2 weeks, 91%, 79%, 90%, and 92% of the adults survived on the damaged acorns of black oak, red oak, bur oak, and maize, respectively, with an overall difference among treatments (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;10.42, df\u0026thinsp;=\u0026thinsp;3, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, there were no differences in adult survival between acorns species (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). After foraging for 4 weeks, 15%, 27%, 62%, and 85% of the adults survived on the damaged acorns of black oak, red oak, bur oak, and maize, respectively. Survival was higher on bur oak than black oak and red oak but was significantly lower than survival on maize (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;124.09, df\u0026thinsp;=\u0026thinsp;3, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). By contrast, after 2 or 4 weeks, there were few or no survivors found on the undamaged acorns of any of the oak species. There was also no significant difference in survival among undamaged acorn species and the blank control (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;7.55, df\u0026thinsp;=\u0026thinsp;3, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.056, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA; no statistics were computed due to a constant variable, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eFines Production of\u003c/b\u003e \u003cb\u003eProstephanus truncatus\u003c/b\u003e \u003cb\u003eon Acorns\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOverall, there were significant differences in fines production at 2 (F\u003csub\u003e5,12\u003c/sub\u003e = 21.24, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 4 weeks (F\u003csub\u003e5,12\u003c/sub\u003e = 26.13, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) among treatments. At 2 weeks, \u003cem\u003eP. truncatus\u003c/em\u003e feeding on the damaged bur oak produced the highest fines, which were 2.3- and 1.9-fold greater than black oak and red oak, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). At 4 weeks, \u003cem\u003eP. truncatus\u003c/em\u003e feeding on the damaged bur oak produced 2.1-fold more fines than on black oak, but not significantly more than on red oak (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). The weight of fines production was higher for damaged acorns than undamaged acorns across oak species (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA and B).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eReproductive Fitness of\u003c/b\u003e \u003cb\u003eProstephanus truncatus\u003c/b\u003e \u003cb\u003eon Acorns\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAfter 10 weeks, \u003cem\u003eP. truncatus\u003c/em\u003e F\u003csub\u003e1\u003c/sub\u003e progeny were found on damaged acorns of bur oak (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA), but not on undamaged acorns of bur oak (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB) or on the acorns of any other oaks regardless of condition (damaged or undamaged). Overall, acorn species and their condition had a significant effect on \u003cem\u003eP. truncatus\u003c/em\u003e reproductive fitness (F\u003csub\u003e5,12\u003c/sub\u003e = 6.49, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Conspecifics produced an average of 19.0 (\u0026plusmn;\u0026thinsp;2.1) F\u003csub\u003e1\u003c/sub\u003e offsprings on damaged acorns of bur oak, which was greater than that on undamaged acorns of bur oak and on damaged acorns of black oak and red oak (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eLaboratory studies have shown that \u003cem\u003eP. truncatus\u003c/em\u003e can reproduce on a wide range of woody plant species from its invaded range in Africa (Helbig et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Nang\u0026rsquo;ayo et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1993\u003c/span\u003e, 1996, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Ramirez-Martinez et al. 1994; Hill et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Nansen et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2002\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Sadiku et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mlambo et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and a closely related species, \u003cem\u003eR. dominica\u003c/em\u003e, has been reported to survive and reproduce on a variety of oak acorns in North America (Wright et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Edde and Phillips \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Jia et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Thus, natural habitats in North America landscapes, especially those including oak acorns, may function as reservoirs for the invasive \u003cem\u003eP. truncatus\u003c/em\u003e and influence its movement into and out of grain storage, potentially facilitating its dispersal across the landscape. To assess the risk posed by North America natural habitats in spreading \u003cem\u003eP. truncatus\u003c/em\u003e, this study determined the attractiveness of black oak, red oak, and bur oak acorns to conspecifics, compared the profiles of VOC emissions from these acorns, measured food preference with mobility assays, and investigated if \u003cem\u003eP. truncatus\u003c/em\u003e can feed, survive, and reproduce on them.\u003c/p\u003e\u003cp\u003e\u003cem\u003eP. truncatus\u003c/em\u003e adults responded positively to volatiles from all three species of oak acorns and maize compared to the blank control in a short-distance choice bioassay, which suggests that they can use odor-mediated orientation at least over short distances rather than just encountering the food substrate by chance. We focused on short-range attractions in this study because \u003cem\u003eP. truncatus\u003c/em\u003e was previously shown to arrest and exhibit attraction to two of its preferred stored product hosts (maize and cassava) at short ranges (Wright et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Hodges \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Scholz et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1997a\u003c/span\u003e), but not at long ranges (Wright et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Tigar et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). In addition, Scholz et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1997a\u003c/span\u003e) demonstrated that \u003cem\u003eP. truncatus\u003c/em\u003e responded positively to native woody species from Africa at short ranges. Arnold et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) reported no evidence of color-mediated host selection in \u003cem\u003eP. truncatus\u003c/em\u003e adults, suggesting that host preferences might predominantly be mediated by VOCs. Additional studies are needed to evaluate the potential use of these cues in long range orientation, which might play a role in landscape utilization. Furthermore, \u003cem\u003eP. truncatus\u003c/em\u003e was more attracted to bur oak acorns rather than those from black oak, red oak, or its primary host, maize. This preference for bur oak acorns indicates that \u003cem\u003eP. truncatus\u003c/em\u003e can perceive the difference in acorns among oak species, suggesting that this pest may use VOCs as chemical cues to locate its preferred food sources during the host-selection process as we effectively excluded visual and other cues during these bioassays. In a subsequent close-range assay, we allowed \u003cem\u003eP. truncatus\u003c/em\u003e to use a combination of olfactory, visual, tactile and gustatory cues to differentiate between potential food sources. We found that \u003cem\u003eP. truncatus\u003c/em\u003e visited bur oak acorns significantly more frequently and for longer durations than maize, indicating a stronger preference for bur oak acorns. Interestingly, this preference suggests that \u003cem\u003eP. truncatus\u003c/em\u003e may still be in the early processes of shifting its dietary niche to include stored commodities and retains an ability to use resources from woody plants, which are thought to be its ancestral food sources (Quellhorst et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It is likely that oaks constitute at least a part of the endemic vegetation in the native range of \u003cem\u003eP. truncatus\u003c/em\u003e in Central America (Nixon \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Further research using oak species in \u003cem\u003eP. truncatus\u003c/em\u003e native range is needed to evaluate the role of acorns and if VOCs from oak acorns within the native range are similar to those found in bur oak acorns.\u003c/p\u003e\u003cp\u003eBecause odors likely play a prominent role in host selection by \u003cem\u003eP. truncatus\u003c/em\u003e, we analyzed and compared the volatile profiles of acorns and grains to look for qualitative and/or quantitative differences in profiles on which conspecifics could act. VOC profiles from black oak, red oak and bur oak acorns, as well as maize and wheat, share some compounds, but also exhibit distinct differences in their overall composition (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Interestingly, black oak, red oak, and bur oak acorns shared 2,4-dimethyl-1-heptene as the most abundant compound, whereas maize and wheat shared 2-butyl-1-octanol as the most abundant compound. 4-methyl-decane and 2,6-dimethyl-nonane were also abundant in each treatment of acorns and grains. The initial attraction of \u003cem\u003eP. truncatus\u003c/em\u003e to black oak, red oak and bur oak, maize and wheat may be due to these shared volatile cues emitted by acorns and grains. Compounds uniquely emitted by or emitted in higher ratios by bur oak acorns in comparison to other treatments (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) may be important for the odor preference by \u003cem\u003eP. truncatus\u003c/em\u003e. For example, both 3-hepten-2-one and 2-(5-methyl-furan-2-yl)-propionaldehyde were only present in bur oak acorns and not in any other treatment. There were also higher emissions of heptanone and 2,7-dimethyl-octanol from bur oak acorns compared to other treatments. It has been reported that the compound 2,4-dimethyl-1-heptene is emitted by \u003cem\u003eGentiana asclepiadea\u003c/em\u003e leaves (Georgieva et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), \u003cem\u003eCitrus grandis\u003c/em\u003e fruits (Chung et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), \u003cem\u003eAnoplophora glabripennis\u003c/em\u003e infested \u003cem\u003eAcer\u003c/em\u003e trees (Makarow et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), \u003cem\u003eAspergillus flavus\u003c/em\u003e or \u003cem\u003eFusarium verticillioides\u003c/em\u003e inoculated/uninoculated wheats (Van Winkle et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ponce et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), \u003cem\u003eAmorphophallus titanium\u003c/em\u003e flowers (Kang et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), spruce trees (\u003cem\u003ePicea abies\u003c/em\u003e) under drought stress (Huber et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and \u003cem\u003eCnaphalocrocis medinalis\u003c/em\u003e egg-treated rice plants (Tian et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Although host plant-derived and stress-related compounds can enhance the efficiency of pheromone traps in some insect species (Birkinshaw \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Likhayo and Hodges \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Bashir et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Morrison et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), maize volatiles did not improve \u003cem\u003eP. truncatus\u003c/em\u003e trap captures or upwind flight responses (Hodges et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Fadamiro et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Our study demonstrated significant short-range attraction to bur oak acorns, exceeding that of maize. Further research is needed to determine whether the compounds associated with bur oak acorns can elicit attraction over longer ranges and synergize pheromone traps.\u003c/p\u003e\u003cp\u003eIn the final experiment, we investigated the ability of \u003cem\u003eP. truncatus\u003c/em\u003e adults to bore into, feed on, survive, and reproduce in acorns of different oak species. The results showed that \u003cem\u003eP. truncatus\u003c/em\u003e adults were unable to colonize undamaged acorns, indicating a preference for damaged acorns and suggesting that damage is necessary for colonization in the field. The acorn weevil \u003cem\u003eCurculio glandium\u003c/em\u003e Marsham (Coleoptera: Curculionidae) (Reut et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the acorn moth \u003cem\u003eValentinia glandulella\u003c/em\u003e (Riley) (Lepidoptera: Blastobasidae) (Galford and Weiss-Cottrill \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), and the lesser grain borer \u003cem\u003eR. dominica\u003c/em\u003e (Jia et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) also prefer damaged acorns. Surprisingly, other acorn weevils such as \u003cem\u003eCurculio venosus\u003c/em\u003e, \u003cem\u003eCurculio pellitus\u003c/em\u003e, and \u003cem\u003eCurculio elephas\u003c/em\u003e do not exhibit this preference and they can infest undamaged acorns (Reut et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Natural or mechanical damage to acorns that have fallen to the ground is also common, providing another route of entry. Thus, \u003cem\u003eP. truncatus\u003c/em\u003e may infest naturally cracked or mammal-damaged acorns or follow infestation by some acorn weevils. Together, this acorn insect community may make oaks a riskier tree in the landscape that can facilitate invasion by \u003cem\u003eP. truncatus\u003c/em\u003e in North America.\u003c/p\u003e\u003cp\u003eAfter \u003cem\u003eP. truncatus\u003c/em\u003e adults bored into damaged black oak, red oak, and bur oak acorns, they produced dust or fines as a byproduct of their tunneling and feeding activities in all three species. However, the quantity of fines produced from bur oak was far greater than those produced from black oak and red oak. It is possible that the physical and chemical properties of bur oak acorns facilitated more tunnelling and feeding by \u003cem\u003eP. truncatus\u003c/em\u003e compared to other oak species. According to previous studies (Von Berg and Biliwa \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Popoola et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), the quantity of dust produced by \u003cem\u003eP. truncatus\u003c/em\u003e during tunneling and feeding activities is a reliable indicator of both the degree of damage and the suitability of the host. For example, \u003cem\u003eP. truncatus\u003c/em\u003e tended to produce large amounts of dust while boring, tunneling, and feeding on maize (Quellhorst et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Ram\u0026iacute;rez-Mart\u0026iacute;nez and Silver (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1983\u003c/span\u003e) reported that maize phenotypes with soft pericarp and endosperm are most vulnerable to attack by \u003cem\u003eP. truncatus\u003c/em\u003e because conspecifics can tunnel and feed easily. Due to more extensive tunnelling and feeding activities, \u003cem\u003eP. truncatus\u003c/em\u003e produced more dust in maize than in sorghum and larger quantities of dust were generated in the high-yielding sorghum varieties (Framida and Naga-White) compared to the local low yielding variety (Mankaraga) (Mailafiya \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAs an internal feeder, \u003cem\u003eP. truncatus\u003c/em\u003e completes its entire life cycle within its host, which provides sites for both feeding and reproduction (Sadiku et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The undamaged acorns of all tested oak species were unsuitable for \u003cem\u003eP. truncatus\u003c/em\u003e adults to feed and reproduce, presumably because it was difficult for them to gain entry. Despite being able to feed on the damaged acorns of all species, \u003cem\u003eP. truncatus\u003c/em\u003e adults could only successfully reproduce on bur oak, suggesting that it is the only acorn species tested in this study capable of serving as a suitable host in the field. It is possible that the black and red oak acorns lack sufficient nutrients needed to support \u003cem\u003eP. truncatus\u003c/em\u003e larval development. Alternatively, it is possible that the black and red oak acorns contain antifeedant or antinutritive compounds that make it difficult for developing beetles to sufficiently feed to complete their development. It has been reported that tannins can act as antinutritional factors and feeding deterrents for many insects by binding to proteins, reducing the efficacy of digestion and nutrient absorption, and causing midgut lesions (El‑Aswad et al. 2023). Acorns from the red oak group (e.g., red or black oak) contain two to four times more tannins than those from the white oak group (e.g., bur oak) (Wood \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Consequently, the higher tannin levels in black and red oak acorns are likely to inhibit \u003cem\u003eP. truncatus\u003c/em\u003e feeding, development, and reproduction due to their toxic and anti-nutritional effects.\u003c/p\u003e\u003cp\u003eThe range of bur oaks begins in southern Texas, where \u003cem\u003eP. truncatus\u003c/em\u003e has been intercepted in the past (Arthur et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and the range continues northward into Southern Canada (Gucker \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). As a result, this species may act in providing an invasion corridor for \u003cem\u003eP. truncatus\u003c/em\u003e into the Great Plains where the majority of maize production occurs in the United States of America. Jia et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) found that \u003cem\u003eR. dominica\u003c/em\u003e, a closely related bostrichid, can feed and reproduce on damaged acorns of six oak species, including chinkapin oak \u003cem\u003eQuercus muehlenbergii\u003c/em\u003e, pin oak \u003cem\u003eQuercus palustris\u003c/em\u003e, red oak \u003cem\u003eQuercus rubra\u003c/em\u003e, Shumard oak \u003cem\u003eQuercus shumardii\u003c/em\u003e, bur oak \u003cem\u003eQuercus macrocarpa\u003c/em\u003e, and English oak \u003cem\u003eQuercus robur\u003c/em\u003e, but not on their undamaged acorns. Earlier studies have also shown that \u003cem\u003eR. dominica\u003c/em\u003e can reproduce on acorns of chinkapin oak \u003cem\u003eQ. muehlenbergii\u003c/em\u003e (Wright et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e1990\u003c/span\u003e) and post oak \u003cem\u003eQuercus stellata\u003c/em\u003e (Edde and Phillips \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Moreover, acorn shells are naturally broken with seasonal freezing and thawing cycles or commonly damaged by other acorn predators, so damaged acorns are abundant due to both natural processes, small mammal predation, and primary insect infestation (Jia et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Thus, the lacking capacity of \u003cem\u003eP. truncatus\u003c/em\u003e to penetrate undamaged acorns may not be a real limiting factor, and bur oak acorns in natural habitats could potentially serve as temporary reservoirs to sustain \u003cem\u003eP. truncatus\u003c/em\u003e if there was no other food available, thereby facilitating long-range dispersal.\u003c/p\u003e\u003cp\u003eStudies have been conducted to understand the potential hosts of \u003cem\u003eP. truncatus\u003c/em\u003e in its endemic and invaded range. For example, of the 81 local tree species tested in Kenya, 23 were found favorable to \u003cem\u003eP. truncatus\u003c/em\u003e for reproduction (Nang\u0026rsquo;ayo et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). \u003cem\u003eP. truncatus\u003c/em\u003e adults and larvae were found in branches of \u003cem\u003eSpondias purpurea\u003c/em\u003e L. (Anacardiaceae), \u003cem\u003eLannea nigritana\u003c/em\u003e (Scott Elliot) Keay (Anacardiaceae), \u003cem\u003eBursera fagaroides\u003c/em\u003e (Kunth) Engl. (Burseraceae), \u003cem\u003eCommiphora riparia\u003c/em\u003e Engl. (Burseraceae), and \u003cem\u003eCommiphora africana\u003c/em\u003e Engl. (Burseraceae) that have been girdled by other insects, especially cerambycids, suggesting that natural populations of \u003cem\u003eP. truncatus\u003c/em\u003e may target already damaged woody plants as part of its realized niche to feed and reproduce (Nang\u0026rsquo;ayo et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Ram\u0026iacute;rez-Mart\u0026iacute;nez et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Borgemeister et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1998b\u003c/span\u003e). Nansen et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) examined the performance of \u003cem\u003eP. truncatus\u003c/em\u003e on a variety of tree species native to Africa and found that it can reproduce on the branches from four species of trees or shrubs (\u003cem\u003eDelonix regia\u003c/em\u003e, \u003cem\u003eCeiba pentandra\u003c/em\u003e, \u003cem\u003eManihot esculenta\u003c/em\u003e, and \u003cem\u003eFicus exasperata\u003c/em\u003e) and on the roots from two species (\u003cem\u003eFicus capensis\u003c/em\u003e, and \u003cem\u003eF. exasperata\u003c/em\u003e). They also demonstrated that \u003cem\u003eP. truncatus\u003c/em\u003e can reproduce on the seeds of teak \u003cem\u003eTectona grandis\u003c/em\u003e (L.), highlighting an interaction between this pest and tree seeds. However, there has been no assessment of the seeds or flora of North America for use as a potential host by \u003cem\u003eP. truncatus\u003c/em\u003e, which is of interest given its invasion potential. While we have confirmed the acorns of one oak species that can be used by \u003cem\u003eP. truncatus\u003c/em\u003e, more studies are needed to fully understand the extent to which tree seeds in natural environments serve as a crucial food source and breeding substrate for this invasive species.\u003c/p\u003e\u003cp\u003eIn conclusion, this study demonstrates that \u003cem\u003eP. truncatus\u003c/em\u003e prefers bur oak acorns and volatiles emitted by bur oak acorns are more attractive to this beetle than maize, its main common host commodity. \u003cem\u003eP. truncatus\u003c/em\u003e can feed and reproduce on damaged bur oak acorns. Bur oak acorns provide a potential food source and natural habitat where \u003cem\u003eP. truncatus\u003c/em\u003e may be attracted to survive and spread across the landscape, alluding to a heightened risk for this invasive pest in North America.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eWe would like to thank Hannah Quellhorst (KSU), Jennifer Abshire (USDA), Kathy Leonard (USDA) and the rest of the Morrison and Scully labs (USDA) for their excellent technical assistance. This manuscript is contribution No. 25-238-J from the Kansas Agricultural Experiment Station, Kansas State University, Manhattan, Kansas, USA. The use of trade names is for the purposes of providing scientific information only and does not constitute endorsement by the United States Department of Agriculture (USDA) or Kansas State University (KSU). The USDA and KSU are equal opportunity employers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eQLM, WRM, JFC, KYZ and EDS conceived the ideas and designed the experiments; QLM, BM and MKM performed the experiments and collected the data. MH, WRM, MKM, BM and QLM performed GC-MS analyses. QLM, WRM, MH, MKM and BM analyzed the data. QLM, WRM, JFC, KYZ and EDS led the writing of the manuscript. MH, MKM, BM, MT and DHW edited the first draft of the manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eOpen access funding provided by Kansas State University. This project was supported by the Agriculture and Food Research Initiative (AFRI) Competitive Grant #2024-67013-42400 from the USDA National Institute of Food and Agriculture\u0026rsquo;s Foundational and Applied Program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eDatasets can be accessed through the Ag Data Commons (DOI will be inserted upon approval). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOpen Access\u003c/strong\u003e This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article\u0026rsquo;s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article\u0026rsquo;s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAltwegg R, Collingham YC, Erni B, Huntley B (2013) Density-dependent dispersal and the speed of range expansions. Divers Distrib 19(1):60\u0026ndash;68. https://doi.org/10.1111/j.1472-4642.2012.00943.x\u003c/li\u003e\n\u003cli\u003eArnold SEJ, Stevenson PC, Belmain SR (2015) Responses to colour and host odour cues in three cereal pest species, in the context of ecology and control. 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Springer-Verlag, NY, USA. https://ggplot2.tidyverse.org\u003c/li\u003e\n\u003cli\u003eWood MD (2005) Tannin and lipid content of acorns in Scatterhoards and Larderhoards. Northeast Nat 12(4):463\u0026ndash;472. https://doi.org/10.1656/1092-6194(2005)012[0463:TALCOA]2.0.CO;2\u003c/li\u003e\n\u003cli\u003eWright M, Akou-Edi D, Stabrawa A (1993) Infestation of dried cassava and maize by \u003cem\u003eProstephanus truncatus\u003c/em\u003e: entomological and socio-economic assessments for the development of loss reduction strategies. Larger Grain Borer Project, Togo. Natural Resources Institute Report 1941, Chatham, United Kingdom, pp 1\u0026ndash;141.\u003c/li\u003e\n\u003cli\u003eWright VF, Fleming EE, Post D (1990) Survival of \u003cem\u003eRhyzopertha dominica\u003c/em\u003e (Coleoptera, Bostrichidae) on fruits and seeds collected from woodrat nests in Kansas. J Kans Entomol Soc 63:344\u0026ndash;347. https://www.jstor.org/stable/25085185\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-chemical-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joce","sideBox":"Learn more about [Journal of Chemical Ecology](https://www.springer.com/journal/10886)","snPcode":"10886","submissionUrl":"https://submission.nature.com/new-submission/10886/3","title":"Journal of Chemical Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Invasive insect species, Larger grain borer, Oak acorns, Odor preference, Volatile organic compound, Host suitability","lastPublishedDoi":"10.21203/rs.3.rs-7545462/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7545462/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe larger grain borer, \u003cem\u003eProstephanus truncatus\u003c/em\u003e (Horn), is an invasive pest on stored grains but can also exploit non-grain food sources. Currently, this species has a limited distribution in North America but possesses the potential to further expand across the continent. Alternative non-grain foods could play a role in range expansion and previous research has shown that acorns can be a suitable food for the lesser grain borer \u003cem\u003eRhyzopertha dominica\u003c/em\u003e (F.), a closely related grain pest. Here, we assessed the odor preference of \u003cem\u003eP. truncatus\u003c/em\u003e for acorns from black oak (\u003cem\u003eQuercus velutina\u003c/em\u003e), red oak (\u003cem\u003eQuercus rubra\u003c/em\u003e), and bur oak (\u003cem\u003eQuercus macrocarpa\u003c/em\u003e) compared to maize and wheat, and analyzed their volatile organic compound (VOC) profiles. Further, we measured \u003cem\u003eP. truncatus\u003c/em\u003e feeding and reproduction on these acorns. Results demonstrated that \u003cem\u003eP. truncatus\u003c/em\u003e responded to volatiles of each acorn species but responded most positively to bur oak acorns. Interestingly, bur oak acorns were also more attractive than maize, its main host grain. VOC profiles showed that two compounds emitted from bur oak acorns, 3-hepten-2-one and 2-(5-methyl-furan-2-yl)-propionaldehyde, were unique compared to other treatments, which may be important for odor preference. \u003cem\u003eP. truncatus\u003c/em\u003e also preferred to feed on bur oak acorns over other oak species. Bur oak was the only acorn species tested in which F\u003csub\u003e1\u003c/sub\u003e progeny were detected. These results suggest that \u003cem\u003eP. truncatus\u003c/em\u003e exhibits evolutionary plasticity that enables it to survive on acorns in the absence of grains, highlighting an elevated risk of landscape-level invasion by this pest in North America.\u003c/p\u003e","manuscriptTitle":"Odor Preference, Feeding, Survival, and Reproductive Fitness of the Invasive Larger Grain Borer Prostephanus truncatus on Acorns of Three Native North America Oak Species","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 17:00:54","doi":"10.21203/rs.3.rs-7545462/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-01T07:44:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-28T19:29:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"200847471448875412151121711693345350477","date":"2025-10-09T20:14:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-01T22:42:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107124356495881461122122652336247508390","date":"2025-09-18T13:07:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-15T12:51:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-15T12:50:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-10T00:32:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Chemical Ecology","date":"2025-09-05T14:55:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-chemical-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joce","sideBox":"Learn more about [Journal of Chemical Ecology](https://www.springer.com/journal/10886)","snPcode":"10886","submissionUrl":"https://submission.nature.com/new-submission/10886/3","title":"Journal of Chemical Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"24db0143-6c0c-431c-8037-a9d3a7cb4e41","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T16:09:49+00:00","versionOfRecord":{"articleIdentity":"rs-7545462","link":"https://doi.org/10.1007/s10886-025-01671-6","journal":{"identity":"journal-of-chemical-ecology","isVorOnly":false,"title":"Journal of Chemical Ecology"},"publishedOn":"2025-11-27 15:57:53","publishedOnDateReadable":"November 27th, 2025"},"versionCreatedAt":"2025-09-23 17:00:54","video":"","vorDoi":"10.1007/s10886-025-01671-6","vorDoiUrl":"https://doi.org/10.1007/s10886-025-01671-6","workflowStages":[]},"version":"v1","identity":"rs-7545462","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7545462","identity":"rs-7545462","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}