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Insects 2019, 10(4), 100; https://doi.org/10.3390/insects10040100

Review
Influences of Stored Product Insect Movements on Integrated Pest Management Decisions
Department of Biosystems Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada
Received: 21 December 2018 / Accepted: 4 April 2019 / Published: 7 April 2019

Abstract

:
Insect movement inside and outside grain bulks and processed products influences pest management decisions. Movement allows insects to find essential food resources, shelters (refuges), warmer and/or humid locations, mating and egg-laying sites, even when they are rare in fields, buildings, mills, warehouses, and inside grain masses. This review discussed the advantages and disadvantages of stored product insect movements, and the influence of insect mobility on some integrated pest management practices. Insect movement (1) results in clumped insect spatial distributions and thus makes large sample sizes necessary for monitoring; (2) makes trapping more efficient, but is influenced by many factors; (3) allows control methods to be effective, but requires pest management programs to be area-wide; (4) makes eradication of quarantine pests difficult and commodities are quickly re-infested; and (5) results in a diverse genetic pool and speeds the development of resistance to pesticides. Any element of an IPM approach should use the knowledge of insect movement. Reasons for the difficult interpretation of cryptic movement behaviours of insects were provided and future research areas were suggested.
Keywords:
stored grain insect pests; mobility; movement behaviour; pest control; monitoring

1. Introduction

Insects have evolved various physiological and behavioral responses to numerous environmental fluctuations in natural and human made ecosystems. These varied behaviors adapt insects to survive our efforts to manage them. Some insects can modify their preferences or move away from their location(s) in response to physical and chemical environmental changes including pesticide applications [1] and atmosphere modifications. Some stored product beetles move up through grain bulks after the disturbance due to the presence of other insects and/or movement of the grain [2]. Movement and dispersal may be beneficial for an individual but the individual who moves out of its current zone will face the challenge of finding food sources and mating partners at new sites. Under low insect densities, less movement could decrease competition (due to the decreased chance of running into each other and fighting [3]) among individuals and save energies [4]. These saved energies are available for their growths and multiplications which results in an increased fecundity. When Tribolium castaneum competes with T. confusum for food and space, the smaller dispersal of T. confusum, which has a higher carrying capacity than T. castaneum, would win in most of the cases. However, the favorable environment at new sites promotes survival, a larger gene pool, and fitness to the environment. While T. castaneum is the less successful competitor in several situations reviewed by Price [5], the better dispersal ability of this insect species will ensure colonization of new resource patches before T. confusum establishes itself in them [5]. Flight T. castaneum might explain their higher dispersal ability than T. confusum because the later cannot fly.
Insect movement behaviours are intentionally or un-intentionally used to control their infestation (Table 1). Even though insect controls are affected by macro-economics, business decisions, and policy factors, integrated pest management (IPM) has been gradually adapted to insect control decisions in most countries. The IPM is ecologically-based and the operational plan of an IPM has at least two key elements: monitoring-based decision making and applications of multiple pest control tactics [6]. If the foundation of an effective IPM program is to understand pest ecology, then understanding insect movement should be at the core of any IPM decision.
The influences of insect movement on IPM decisions of stored product insects have not been reviewed. This review discussed the movement of stored product insects and the influence of insect mobility on some IPM practices, and important advantages and disadvantages of insect movement in IPM decision making. The purpose of this review was not to extensively review studies in this research area due to the vast number of publications, but to find the weakness of our pest management decisions where insect movement behaviours and mobility should be considered, hence future researches and applications can overcome these weaknesses.

2. Movement Motivation and Mobility of Stored Product Insects

2.1. Moving to Food Sources

Even though there are many reasons for insect migrations from one location to other locations, the most important motivation is to find food sources. This food requirement results in different moving behaviours in different mediums such as across fields, in grain bulks, or inside mills. Insects use olfactory and taste receptors to find foods and check whether the food is preferred. Insects often exhibit upwind flight to track plumes of pheromones and/or odours of their food sources [7]. Plant secondary compounds are critical in stimulating or deterring feeding [8]. There are numerous examples of Lepidoptera utilizing airborne stimulants to locate their hosts [9,10,11,12]. The grain source that elicits Ephestia cautella oviposition behaviours also attracts gravid females upwind in wind-tunnels [13]. The larvae of Plodia interpunctella are found to respond positively to food odours [14]. Directional orientation and movement of newly emerged larvae in response to food volatiles may serve two purposes in infesting stored products: odours may help to guide larvae to the direction which odours produce, and to locate preferred locations once the larvae are inside food sources. Food searching behaviours may be modified under certain circumstances. If a P. interpunctella larva hatches close to an odour stream but is exposed to direct light, the larva will generally move away from the light source rather than pursue the odour to its food source [14].
Insects are attracted to favorable food sources, but also select alternate food sources at the same time. Bruchid beetles usually infest a few species of legumes [15]. Lectins, lectin-like α-amylase inhibitors, arcelin [16], and vicillins are linked to seed resistance to herbivories [17,18]. Seeds also defend themselves with an arsenal of secondary compounds [15,19]. Lots of plants and their active substances have repellent effects on insects [20]. Protein-rich pea flour is an antifeedant/repellent and toxic to some insect species [21]. When insects consume diets with imbalanced protein/carbohydrate ratios, they often over-feed to compensate this imbalance [22], and post-ingestive regulation is one of the strategies for dealing with these nutritional imbalances [23]. Immature stages of P. interpunctella have the highest survival rates on the artificial diet, and lower survival rates on raisin than that on dried fig, dried wheat germ, dried white mulberry, groundnut, and pistachio [24]. Sitophilus zeamais and Prostephanus truncatus prefer to feed on smaller maize grains with green colour [25]. Psocid populations are significantly higher on damaged kernels than on intact kernels of wheat varieties [26], and the progeny production of Liposcelis bostrychophila, L. decolor, and L. paeta is affected by wheat class [27]. Tyrophagus putrescentiae and Trogoderma granarium have significantly different development times on different diets [28]. High nutrition food generally results in a higher rate of larval growth, survival, adult fecundity and fertility. Insect preference to some food sources might relate to the nutrition of the food sources and the individuals’ reproductive fitness after consumption of the food. Dietary requirements are well reviewed by Cox and Collins [28].
It is difficult to completely explain the attractive or repellent effects of food odours because repellent or attractive effects are also influenced by other factors such as the environment or individual fitness. The preference of insects outside food sources might be different from that inside food sources. Insects fly or crawl fast to find food sources before they reach food sources and this movement behaviour is different from that inside grain bulks and between food patches [29]. Adults of lesser grain borer, Rhyzopertha dominica, a strong flier in air, move little once in grain bulks. Even though crowding, food deprivation, and diet influence flight initiation of lesser grain borers [30], it is unclear how, why, and when the insects will move out of food sources and fly. One reason might be caused by the adaptive and/or passivate behaviours of insects because it is not required to be attracted to olfactory cues after food sources are located. Hudaib et al. [31] found none of the extracts from resistant and susceptible beans resulted in complete ovipositional or developmental failure on Phaseolus vulgaris beans.

2.2. Moving to Warmer Locations

Insects detect temperatures using internal and external thermo-sensory neurons [32]. Even though locating food sources is the first requirement of insect movement, finding warmer locations is usually intertwined with food choice because thermal energy is the basic requirement for any insect activity. Stored grain insects are not able to change their body temperature by using thermoregulation, and behaviour change is the most used mechanism to respond to temperature changes. Insects must rely on acute thermo-tolerance mechanisms such as immobility at 8 to 17 °C for most stored grain insects [33], rapid cold hardiness, diapause, and heat shock response. Grain temperatures of less than 17 °C completely suppress stored-grain beetle population growth [34]. The immigration of all species is low when temperatures drop below 20 °C. When temperature is in the range 18 to 38 °C many insects use behaviours to achieve high and stable body temperatures, thus promoting food consumption, metabolic rate, growth, and multiplication [35]. Inside commercial grain elevators in Kansas, USA, densities of different insect species follow the weather temperature trend [36]. Jian et al. [4] concluded the first two main factors influencing the population dynamics were the temperature and the previous insect numbers in stored wheat bulks.
Even though the extent of variation among insect species in temperature detection is not known [37], different insects have different temperature responses. When 300 kg wheat is cooled inside barrels, Cryptolestes ferrugineus adults are found mostly in the centre of the grain bulk, while R. dominica adults are found mainly in the top 40 cm of the grain bulk, and there is little movement to the centre [38]. Adults of C. ferrugineus move most inside a grain bulk, while adults of T. castaneum mostly stay at the top of the grain bulk [39].

2.3. Moving to Humid Locations

Even though nutritional value of different foods can be quite varied, water content of stored products is usually low. Insects have a large surface area to volume ratio. Therefore, losing water when exposed to dry air is a challenge for insect survival. Hiding in a grain bulk might partially solve this problem if water inside the grain bulk is higher than that of air. Stored product insects physiologically adapt to this dry condition by using metabolic water [40] and hygrosensitive sensilla to sense water in air. Even though stored product insects have Malpighian tubules between their midgut and hindgut to absorb water from wastes, so they can survive at low moisture contents of grain, but each species has a minimum requirement of grain moisture content for their survival. Therefore, insects move inside grain bulks by following moisture gradients [41] at their preferred temperatures. More insects are caught in bins containing layered dry and wet grain than in the bins containing only dry grain, regardless of whether the bins are ventilated or not [42]. Sitophilus granarius moves to areas with high moisture contents. Relative humidity (RH) significantly influences the movement of T. castaneum and E. cautella and one percent of relative humidity increase can increase the trap catches by 3.3 and 3.0 times, respectively [43]. Mites do not move to warmer locations, but will have a clumped distribution at the location with high moisture contents [44]. Large numbers of psocids move out of grain bins when the RH in the bins drops over the day and return during the night after the RH increases [45,46].

2.4. Search for Mating and Egg Laying Sites

Sexual selection, hence natural selection, is one of the driving forces to guide insects’ search for mates. In air, insects fly or crawl randomly before they are attracted by pheromones, and follow the plume of pheromones to form an aggregated distribution after the pheromone lure is located [7,47,48]. Stored-product insects interact with broader landscape patterns. The whole landscape and deciduous woodlands may strongly influence R. dominica distribution patterns and this will depend on the time of year [49]. There is evidence suggesting that R. dominica can survive in the wild on other hosts such as wood twigs and acorns [50]. Wooded forested sites can harbour populations of R. dominica, with adults dispersing up to 375 m [51], while Daglish et al. [52] found R. dominica could disperse at least 1.6 km. Prostephanus truncatus is attracted, feeds and reproduces on certain types of woods, and is associated with forest habitats [53]. In a grain mass, insects move randomly when insects have no preference and become aggregated in distribution at favourable locations [54,55]. These aggregated distributions will promote the search for mating and oviposition sites because of the high chance of running into the opposite sex in a place of their mutual interests. Optimal search of food sources and preferred (warmer and humid) locations benefits mate searching [56] because nutrient food source and suitable environments are important for parent insects and their oviposition sites. The author found a common phenomenon that insects with a long life span were usually less sensitive to sex pheromones than those with a short life span because insects with a long life span might have more time to find sex partners. Therefore, adult moths, which usually have a short life span, can be more effectively trapped by using pheromone lures than beetles. Product odours draw P. interpunctella females to the general vicinity of the odour sources prior to oviposition [14]. All beetles walked significantly faster in the presence of the pheromone odour than without the pheromone odour [57]. Unmated beetles of T. castaneum respond more strongly to the aggregation pheromone than the mated beetles [57]. However, no significant difference is observed in the flight response of mated and unmated beetles towards the aggregation pheromone.

2.5. Flying of Stored Product Insects

To quickly reach their preferred locations, most insects fly under suitable conditions. There are several studies showing that many stored product insects are flying in and around storage facilities [43,52,58,59,60,61] (Table 2). Bins close to infested bins are more likely to be infested as a result of insects moving and flying between bins. Newly harvested wheat generally becomes infested after being stored in a bin due to insect migration from other infestation sources [62].
Most insects fly under certain weather conditions such as warm temperatures, low wind speeds, and usually a few hours before sunset [47,61]. Slightly more than half of the variability in R. dominica captures can be explained by the mean ambient air temperature and wind speed during 2 h before sunset [60]. Trap captures of four species (R. dominica, Trogoderma variabile, L. serricorne, and P. interpunctella) increase with an increase in temperature and can be described by a linear equation [58]. Below 17 °C there is a little flight activity occurring for all 13 species [58], suggesting that there is a lower temperature threshold for flight activity that is similar across species. However, flight activities can only partially explain trap captures and flight temperatures may differ with species (Table 2). These different flight temperatures and conditions show the cryptic movement behaviours of insects.
Environments inside grain storage structures and processing buildings usually have higher and stable temperatures and lower wind velocities than that outside structures. Inside these structures, insects can fly, crawl, and/or run into/out of empty spaces and food sources. Therefore, insects are able to quickly locate their favorable locations and have a fast population increase. The results of many studies [36,61,71] indicate that insects moving into bins or mills and flying and moving inside grain storage structures will counteract the effect of the sanitation and any effort of insect controls because newly arrived insects can start a new population after applied insecticides have no toxic effects. Grain stored in pesticide treated bins is less likely to be heavily infested than that in untreated bins in less than 3 months, but not in more than 3 months [72].

3. Advantages and Disadvantages of Dispersal in IPM Considerations

Insect movements under any stored grain condition and any insect density are the fundamental biological requirement for the development of an insect population. The F1 and F2 generations of T. castaneum have constant emigration rates after their initial colonization and the proportion of adults emigrating does not increase with the increase in insect densities [73]. Movements of insects result in dispersal of insects to escape crowding as the population increases. Studies prove that crowding results in reduced oviposition rates, increased mortalities, various insect morphologies, low productivities, and weaker responses to environmental variations [74,75,76]. Adults of E. kuehniella reared at higher larval densities have lower body mass; smaller forewings, head, and thorax; reduced individual fitness; lower eupyrene sperm; and shorter life span than that at lower larval densities. The males developed under higher larval densities have allometric relationship between body mass and relatively longer wings which enhances dispersal and assists in mate searching [77]. The response of insects under a crowding condition is usually the dispersal from the crowding location because of the increased competition for resources and living spaces. In many cases migration is the less costly solution apart from other benefits that may incur to the insect [78]. Beetles of R. dominica under crowded conditions have a significantly higher flight initiation than beetles reared on isolated kernels [30].
Insects conducting movements and dispersals can avoid unfavorable and/or toxic environments and/or predations. Adults of C. ferrugineus move to positions where CO2 concentration is lower than 37%, but move away when the concentration is higher [79]. Different insect species have different responses to different CO2 concentrations [80]. The number of stored product insects increase with enlarged hotspots, and thriving adult and larval population occurs at 17 to 38 °C [81]. Adults move away from locations with a temperature higher than 38 °C inside the hotspot. Oryzaephilus surinamensis adults increase emigration with the increase of temperatures and insect densities [82]. Emigration is also observed during the heat treatment, fumigation, and insecticide treatment [83]. Moving out of storage structures that are under chemical treatments allows psocids to avoid exposure to pesticides [84,85].
Movements allow insects to find new food sources, discover new sites for each individual and for females to lay eggs so the infested area is gradually enlarged, as new geographic regions are invaded. These movements will allow insects to migrate to more suitable environments. Most stored grain insects have a broad host range which contributes to their establishment and spread. The Khapra beetle, Trogoderma granarium, a voracious feeder of stored products is considered one of the 100 worst invasive species worldwide, and can infest more than 100 commodities with moisture contents as low as 2% [86]. The foods include almost all kinds of seeds, legumes, nuts, and any kind of dried bio-materials and products. The Khapra beetle can establish itself in new regions by breeding rapidly and disperse by moving under optimum conditions, and persists owing to its larval diapause under unfavorable conditions. The Khapra beetle cannot fly and is native to the Indian subcontinent. Therefore, over 100 countries’ records of the Khapra beetle over the past 40 years [86] demonstrate the prevailing power of insect movements and dispersals. Flying insects will have much more power of dispersal. Dispersal of flying insects may limit our choice of IPM methods.
Infestation of stored grain insects is caused by insect movement and dispersal because there is no initial insect infestation if insects are not introduced by human operations or by insect movement and dispersal. Without moving, insects will always live at their initial infestation locations. Re-infestation is a common phenomenon during grain storage which is also caused by insect movement, dispersal, and multiplication for the same reasons. The failing of any insect control effort is partially (if not all) caused by insect multiplications after their dispersal. The strategy of the most current IPM methods is to control the target insects, and this may fail to control non-target insect species and the insects with a high mobility. For example, psocid populations flourish after the permethrin or phosphine treatment due to their resistance to the pesticides and the reduction of predators and competitors [87]. This flourishing should be related to our use of pesticides and incomplete understanding of the pests’ ecology and biology especially their mobility under the treatment conditions. Increasing frequency and severity of psocid infestations in Australia is linked to the industry transitioning from broad use of contact insecticides to reliance on the continuous delivery of phosphine and the relatively long period of the egg stage of psocids [88]. Psocids are traditionally regarded as minor nuisance pests and have mostly been ignored by entomologists because beetles and moth pests are more prominent and more destructive to stored commodities. Psocids’ pest status began to change internationally in the late 1980s with increased reports of large infestations in the world [88]. Therefore, insect mobility and dispersal should be considered and effectively used when an IPM decision is made by taking advantage of insect mobility when it benefits the practice, or limiting its mobility when its movement reduces the effects of pest management practices. For example, psocids are wingless and move actively in bulks of grain and storage structures, which provides an opportunity to control their infestations by applying contact insecticides [89]. If fumigation is conducted, movement of psocids to outside structures or to locations with a low fumigant concentration should be considered.

4. Influences of Insect Movement on IPM Decisions

4.1. Movement Influences the Monitoring-Based Decision Making

4.1.1. Movement Results in Uneven Insect Distribution which Requires Large Sample Sizes

Prediction of insect distribution and densities can increase the efficiency of pest control, reduce the cost of management, and decrease the risk of killing non target insects [90,91]. Cryptic movement behaviours of individuals, random movement, clumped distribution, and complexity of storage grain ecosystems make the prediction of insect distribution difficult [91]. This difficulty results in an unreliable prediction of insect densities by using sampling methods especially when sample sizes are less than the theoretical sampling sizes. The reason for the small sample sizes is that sampling with a theoretical sampling size is usually time-consuming and not economically feasible [90,91]. To increase the reliability of prediction, non-uniform insect distribution makes stratified sampling necessary, which is also time consuming and not economically feasible. Lower than theoretical sampling rates and sizes result in subjective evaluations and inconsistent penalties for insect-related quality factors. For example, there is no significant relationship among mean numbers of mites on ham or racks, or in vacuum samples or in traps [92]. Spear samples underestimate the population densities at actual insect densities of 0.25, 0.4, 2, and 10 insects per kilogram of grain [93]. Published researches conclude that (1) estimation of population densities at or below 1 insect/kg by using conventional sample sizes might be impossible [90,91,93]; (2) sampling methods might influence the characterized insect distribution patterns [94,95]; (3) using different sampling methods might result in different insect densities; and 4) using manual sampling methods to estimate insect densities with less than 60% relative variances might not be practical when insect densities are lower than 1.0 insect/kg [90,91].
Variations of population growth over time also require to conduct sampling sequentially, which is time consuming and not economically feasible in most cases. Individual insects might have different movement behaviours when individuals have different ages, sexes, previous feeding and acclimation conditions [96,97]. These complex movement behaviours and variations of growth rates result in unreliable prediction of insect densities and locations when sampling is conducted at different times.
In mills, “stored-product pests occupy spatially and temporally fragmented landscapes that can have profound impacts not only on their population dynamics [98], but also on our ability to monitor populations and effectively target pest management”. The spatial patchy distribution of T. castaneum population changes over time [98]. The “tendency for beetles to crawl along the edge of their environments may require a different approach to determining how easily pests move about, especially when presented with different numbers of food patches along their routes”.
To overcome these difficulties, some managers regularly monitor grain temperatures, detect insects outside elevators and bins when floors and equipment are cleaned, and sample grain during grain loading and unloading. Currently, there are no better recommendation than (1) developed sampling plans [99,100,101]; (2) monitoring insect activities using electronic traps [102]; and (3) sampling at any time when it is possible.

4.1.2. Movement Makes Trapping More Efficient, but Is Influenced by Many Factors

Trapping is the most used and might be the only method at some times to monitor insect activities inside grain bulks, buildings, mills, or warehouses. Different traps with or without pheromones or baits have been widely used [60,103]. However, interpreting the relationship among the trapping captures (number of captured insects), insect densities, and insect locations is still a study topic and there is no published model which can be used to correctly predict insect densities. The captures are highly influenced by many parameters such as species, insect stage, trap shape, size, and location; hence, in many cases captures are not directly correlated with actual population densities [104,105] (Table 3). After all of the major factors influencing captures are considered or controlled, the captures might/should theoretically correlate with insect activities (Table 3). Trapping data cannot be correlated well with grain sampling data if each sample is less than 15 kg [71,90,91,106] because less than the recommended sampling size also cannot correctly predict insect distribution and densities.
Different insect stages have different mobility. The mobile stage of storage product insects is usually the adult. Larvae usually do not move further than adults. Therefore, there are different captures for different stages. Insecticide application results in a large number of dead adults and reduction in adult captures, but no detectable difference in quantity of larvae, pupae, or adults in food patch samples and within hidden refuges [116]. Larval captures correspond with the increasing larval population, but are more pronounced in traps located closer to food patches and sources of infestation in a warehouse [116].
Even though adding pheromones or food lures might increase captures, this makes the explanation of the captures more difficult. Captures decrease when lures are not changed weekly [60]. There are some examples of interspecific cross-attraction or repellent effects among stored product beetles inside traps [28,117] or nearby traps. The pheromone of T. variabile does not impact adversely on the captures of T. castaneum, but the opposite is not true [103]. Traps containing alive and dead individuals of the same and other species can seriously affect the response and captures of additional insects [117,118]. Filter papers previously exposed to live S. oryzae are attractive to other adults of the same species [119]. The application of pyrethrins has little influence on the distribution of E. cautella or male moth captures [48]. However, uneven distribution of insecticides affects insect distribution and movement [116], which builds cryptic infestation patterns.
Due to the limitations mentioned above, trapping is mostly used to monitor insect infestation and not to predict insect densities. “Integrated management strategy relying on pheromone trapping to monitor adult E. cautella plus improved sanitation practices is likely to provide superior control of E. cautella than the blanket application of pyrethrins” [48]. Campbell et al. [120] suggested that trapping data should be used by comparing relative levels of capture among locations and over times.

4.2. Movement Allows Control Methods to Be Effective and Influences the Use of Pest Control Tactics

4.2.1. Movement Allows Control Methods to be Effective

Insect movement behaviours have been widely used to control insects when contact pesticides are used (Table 1). The main mechanism of contact pesticide is that mobile insects contact and intake pesticides which are applied on the surface of treated materials (such as surface of grain kernels). It is recommended to top-dress the stored grain in bins by treating all the surface grain with pyrethrin, Diatomaceous Earth (DE), and other grain protectants. The “top-dressing” acts as a barrier preventing insects from entering the grain mass and feeding on the surface grain, and killing insects moving through the top-dressing layer. It is a common practice to apply a band of pesticide around a warehouse, storage bin, processing building to prevent insects migrating into/out of the facility. Based on the recommended dosage of most contact pesticides, not all of the grain kernels have the same amount of applied pesticide. Studies prove that partial treatment of a stored grain bulk has a full or partial effect on insect control, and the efficacy is species dependent (Table 4). Variations of pesticide distribution in grain bulks or different movement behaviours cause different pesticide intakes by insects, which results in different efficacies.
More or less uniform distributions of aerosol particles throughout processing facilities influence the effect of insect control [127,128,129,130]. The presence of flour as a food source seems to influence the effect of aerosol treatments because the presence of flour either during or after aerosol application increases survival of T. confusum and T. castaneum [127,130]. Sanitation will cause insects hiding in refuge to come out and increases their chances of exposure to aerosol particles, which results in a higher mortality. The blanket application of synergized pyrethrins is unnecessary in most areas because E. cautella distributes throughout a confectionery factory in an aggregated pattern [48].

4.2.2. Movement Restricts the Use of Some Pest Control Tactics

Insect movement makes some techniques impossible to be used to control insects inside a grain mass. For example, insects run to cool locations during microwave heating [131]. Therefore, the uneven distribution of temperatures inside a grain mass during microwave treatment is the major limitation for the industrial application of this technology [131]. Non-uniform distribution of temperature or dose during heat treatment, irradiation, fumigant, and biological agent application also influences results of the insect management program. Mating-disruption “does not prevent mated female immigration from adjacent areas, thus oviposition and subsequent infestation are likely to still occur” [132]. Biological control cannot be used under most grain storage conditions due to customers’ low tolerance to any insect inside processed foods, and insects can migrate to areas with no or less biological agents.
Insect movement usually results in the failure of some pest control tactics. Insect penetrators can pierce most flexible polymer films as well as foil, paper, and laminate [133,134,135]. In the United States, the incidence of package infestation increases as the packages are shipped to the southern states due to the longer, warmer, more humid summer providing a longer favorable growth period for insects. The same trend is found in Australia [14]. Sealing to make an airtight environment is a common practice during fumigation but not fogging. One of the main reasons to seal materials is to prevent the fumigant leaking and insects moving/escaping and surviving [136]. It is required to treat all materials even though only parts of the materials are infested. For example, all grain in a bin should be fumigated and transportation equipment should also be treated to avoid a cross infestation. All facilities should be cleaned to keep an acceptable sanitation condition [137].
Some insect control methods require the movement of insects but these methods also have disadvantages. Effect of repellents and attractants needs insect movement, but the repelled insects may infest other materials. Contact pesticides or DE requires insect movement to kill the mobile insects, so the treatment needs time. To decrease the treatment time and/or dosage, DE + different additives (abamectin, bitterbarkomycin), + pesticies (pyrethins and thiamethoxam) [138,139], + fungal metabolites, + insect pathogenic fungi (Beauveria bassiana) [140], + bacterial metabolites (sponosad), + neonicotinoid insecticide (imidacloprid), + insect growth regulators (methoprene) [141], or + plant extracts have been tested and varying degrees of success have been achieved because the combination counters the negative effects of each material when applied alone, combines and/or synergizes the different modes of action, and takes the advantage of the insect movement. For example, desiccated insects may become physiologically stressed and prone to toxic effects of pesticides (such as deltamethrin, thiamethoxam, and spinosad) [139]. Heat treatment + DE also increase insect mortality [142]. The attract-and-kill technique kills mobile insects by using pheromone to lure them to the insecticide surfaces. Movement on insecticide-treated surfaces in 2 s can suppress P. interpunctella males over 80% for up to 8 weeks [143]. Under hermetic storage conditions, the non-mobile developmental stages generally took more exposure time to reach a 100% mortality than the mobile stages because of their lower O2 consumption and metabolic rate [144].

4.3. Movement Makes Eradication of Pests More Difficult and Insect Control Needs to Be Area-Wide

4.3.1. Movement Makes Eradication of Quarantine Pests More Difficult

Insect movement makes eradication of quarantine pests more difficult because they readily move to new locations and nearby insects can re-infest after eradication at a location. Khapra beetles have established in many Mediterranean, Middle Eastern, Asian, African, and North America countries due to their cryptic movement behaviours, high survival rates under dry conditions, and wide diets. Therefore, it is important to prevent the Khapra beetle’s introduction into uninfested areas [145] and eradicate it at the introduced area before it spreads. The critical and effective method to prevent the Khapra beetle from establishing in a region is to monitor/trap and fumigate all infested areas before a population is well established [86]. The USA customs agents have intercepted the beetle more than 15 times each year and discovered it in isolated infestations on the East and West coast of the United States [146]. However, the Khapra beetle has been successfully eradicated in USA. In 1980, T. granarium was eradicated after it was detected in rice silos in central areas of Taiwan. Yao et al. [147] in 2016 reported T. granarium was no longer present in Taiwan after a 3-year monitoring survey in paddy silos, imported rice bins, and rice mills.
The case of warehouse beetle (T. variabile) in Australia is an example of the spread of quarantine insect species which can fly. Warehouse beetle was first discovered in Western Australia on a farm in 1979. Even though eradication was attempted, the warehouse beetle was found at the farm and 150 km away in 1991. The wide spread of the beetle forced government and industry representatives to give up the eradication in favor of containment [148,149]. Khapra beetle (T. granarium) was detected and eradicated at several locations in Australia between 1977 and 1993 [150]. One of the reasons of the successful eradication of Khapra beetle is that it is easier to eradicate T. granarium than T. variabile because Khapra beetle does not fly and warehouse beetle flies. Insect flight greatly increases spreading and makes eradiation of the invasive species more difficult.

4.3.2. Mobility Makes Area-Wide Pest Management Programs Necessary

Because of insects’ mobility, infested areas may change over time, and pest management or resistance management programs need to be area-wide to cover all possible infested areas. Tribolium castaneum and R. dominica beetles readily fly from storages in which abundant resources remain [151]. This flying activity sufficiently renders their distribution over at least 40,000 km2 [152]. The geographic distribution of insect infestation on processed products is usually temperature dependent, and stocks mixed with old stored products are more likely to be infested and area-wide in a small town or factory [14].
Area-wide IPM programs are important for the control of stored grain pests because insects multiply along with the transported grain from farm bins to country elevators, flour mills, export terminal elevators, and other countries. The current practice of insect management is usually to control target insects at target places such as an infested grain bin and areas inside mills. This management program will reduce the insect number in the treated areas, but not the entire chain of the grain transportation system.

4.4. Movement Results in a Diverse Genetic Pool

Insect movement and grain trade result in a cosmopolitan distribution of insects, rich diversity of insect species, and diverse gene pool of any species. Mobility enables insects to infest every new ecosystem, such as a new loaded grain bin. The grain bin is a manmade ecosystem and renewed every time after the grain is unloaded and reloaded. After new harvested grain is loaded into a bin, diversity and abundance will increase with the increase of storage time due to insect immigration and movement. This cycle is repeated for every grain loading and unloading, and diversity and abundance inside the ecosystem is driven by insect mobility. Insects in this ecosystem must possess adaptions (such as efficiency of food utilization or rate of development) and then promote its survival in every new ecosystem.
There are extensive gene flows within each species across the entire Western Australia, and flight dispersal clearly contributes to this [65,152]. Insect migration will influence the dispersal of pesticide resistance genes [151]. Phosphine resistance of T. castaneum increases slowly when the insects have a low migration [153]. Dispersal of susceptible insects slows the onset of resistance, and immigration of resistant insects speeds the resistance development. Phosphine resistance status of individual beetles affects their resource localization abilities and their flight activities negatively [153]. These negative effects will reduce the fitness of these resistant beetles when they seek patchily distributed resources.

5. Importance of Insect Movement in IPM Decisions and Research on Insect Movement Is Necessary

5.1. Importance of Insect Movement in an IPM Decision

A comprehensive IPM is an ecosystem approach to control insect pests that uses all available tools and combines different management strategies and practices to maintain the quality of stored products, enhance the sustainability (environmental, economic, and social) of stored product ecosystems, and minimize the use of pesticides in an effective, economical, and environmental way. There are usually six main elements in an IPM program [6] and any element of an IPM approach should use the knowledge of insect movement (Table 5). Therefore, an effective IPM decision is based on the knowledge of insect movement behaviors. An IPM decision might be wrong if the movement behaviors of pests are not known. This has been proven with the practice of insect controls. For example, several species of psocids have a widespread resistance to phosphine [88] and one of the main reasons for this resistance would be their high mobility and this high mobility is not considered in the IPM decision [84,85].

5.2. Research on Insect Movement Behaviours Is Necessary

Controlling insects with an area-wide dispersal should consider insect movement behaviours. This requires the study and interpretation of insect movement behaviours under any ecological condition. The reasons for the difficult interpretation of cryptic movement behaviours are (1) small body size and hidden infestation of stored grain insects, so checking infestation is time consuming and there is no small sensor available to track their movements inside a grain mass; (2) variations of individual behaviours and stages, so multi-studies on different insect individuals and stages should be conducted; (3) multi-factors influencing insect movement behaviours, so it is difficult to interpret insect movement directions, speeds, and turnings; (4) meager techniques and tools available to study insect movement behaviours, so the research on insect movement behaviours mostly relies on traditional methods such as determining their distribution under tested conditions; and (5) inadequate studies because studies on insect movement behaviours are usually not directly related to the results and economic feedback of insect management practices.
Movement behaviours of insects on fields, in storage facilities and grain bulks before, during, and after the application of any IPM method influence the entire grain ecosystems. This review found most insect movements and distributions could not be predicted in a certain accuracy. Conventional methods such as sampling and trapping have a low accuracy to estimate densities and distributions of infested pest insects, and this estimation is the fundamental requirement of an IPM program. Insect movement behaviors influence IPM decisions and any element of an IPM approach should use the knowledge of insect movement. Therefore, research on insect movement on the following research areas is necessary and helpful for the world grain industry and research community: (1) mathematical modelling of insect movement, (2) identification of main parameters influencing the prediction accuracy of insect density and distribution under different storage conditions; (3) effects of insect movement parameters on the efficacy of pesticides; (4) effects of insect movement on population dynamics; and (5) relationships between insect movement parameters and sampling or trapping. The core of these research areas is the mathematical modeling of insect movement.

6. Conclusions

(1)
Knowledge of insect movement and dispersal is the key for making right IPM decisions.
(2)
Insect mobility influences the result and evaluation of any IPM practice.
(3)
Insect movement and distribution influence insect population monitoring.
(4)
Insect movement behaviours influence our understanding of insect population dynamics inside stored product ecosystems when a control method is applied.
(5)
Research on insect movement behaviours is necessary. The core of this research is the mathematical modeling of insect movement.

Funding

This research was partially funded by Natural Sciences and Engineering Research Council of Canada.

Acknowledgments

The author thanks the Natural Sciences and Engineering Research Council of Canada for partial funding of this study. I would also like to show my gratitude to David Hagstrum, Noel D. G. White, and Paul Fields for commenting and valuable suggesting on the early version of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Guedes, N.M.P.; Guedes, R.N.C.; Ferreira, G.H.; Silva, L.B. Flight take-off and walking behavior of insecticide-susceptible and—Resistant strains of Sitophilus zeamais exposed to deltamethrin. Bull. Entomol. Res. 2009, 99, 393–400. [Google Scholar] [CrossRef] [PubMed]
  2. Cogan, P.M. Aeration, insect movement and effect of grain temperature. Asp. Appl. Biol. 1990, 25, 407–416. [Google Scholar]
  3. White, N.D.G.; Bell, R.J. Effects of mating status, sex ratio, and population density on longevity and offspring production of Cryptolestes ferrugineus (Stephens) (Coleoptera: Cucujidae). Exp. Gerontol. 1993, 28, 617–631. [Google Scholar] [CrossRef]
  4. Jian, F.; Jayas, D.S.; Fields, P.G.; White, N.D.G.; Zhang, H.; Tang, P. Demography of rusty grain beetle in stored bulk wheat: Part I, population dynamics at different temperatures and grain bulk sizes. Environ. Entomol. 2018, 47, 244–255. [Google Scholar] [CrossRef] [PubMed]
  5. Price, P.W. Intraspecific and interspecific competition. In Insect Ecology; Price, P.D., Ed.; John Wiley & Sons Inc.: Kundli, Haryana, India, 1997; pp. 587–616. [Google Scholar]
  6. FAO. Integrated Pest Management of Major Pests and Diseases in Eastern Europe and the Caucasus; Food and Agriculture Organization of the United Nations: Budapest, Hungary, 2017; p. 110. [Google Scholar]
  7. Mankin, R.W.; Vick, K.W.; Coffelt, J.A.; Weaver, B.A. Pheromone-mediated flight by male Plodia interpunctella (hubner) (lepidoptera: Pyralidae). Environ. Enlomol. 1983, 12, 1218–1222. [Google Scholar] [CrossRef]
  8. Cox, P.D.; Fleming, D.A.; Atkinson, J.E.; Bannon, K.L.; Whitfield, J.M. The effect of behaviour on the survival of Cryptolestes ferrugineus in an insecticide-treated laboratory environment. J. Stored Prodacts Res. 1997, 33, 257–269. [Google Scholar] [CrossRef]
  9. Mitchell, E.R.; Tingle, F.C.; Heath, R.R. Flight activity of Heliothis virescens (F.) females (Lepidoptera: Noctuidae) with reference to host-plant volatiles. J. Chem. Ecol. 1991, 17, 259–266. [Google Scholar] [CrossRef] [PubMed]
  10. Peterson, J.K.; Horvat, R.J.; Elsey, K.D. Squash leaf glandular trichome volatiles: Identification and influence on behaviour of the female pickleworm moth Diaphania nitidalis (Stoll.) (Lepidoptera: Pyralidae). J. Chem. Ecol. 1994, 20, 2099–2109. [Google Scholar] [CrossRef] [PubMed]
  11. Phelan, P.L.; Roelofs, C.J.; Youngman, R.R.; Baker, T.C. Characterization of chemicals mediating ovipositional host-plant finding by Amyelois transitella females. J. Chem. Ecol. 1991, 17, 599–613. [Google Scholar] [CrossRef] [PubMed]
  12. Renwick, J.A.A.; Radke, C.D. Chemical recognition of host plants for oviposition by the cabbage butterfly, Pieris rapae (Lepidoptera: Pieridae). Environ. Entomol. 1983, 12, 446–450. [Google Scholar] [CrossRef]
  13. Barrer, P.M.; Jay, E.G. Laboratory observations on the ability of Ephestia cautella (Walker) (Lepidoptera: Phycitidae) to locate, and to oviposit in response to a source of grain odour. J. Stored Products Res. 1980, 16, 1–7. [Google Scholar] [CrossRef]
  14. Bowditch, T.G. Investigation of Factors Relating to the Insect Infestation of Chocolate-Based Consumables. Ph.D. Thesis, University of Tasmania, Launceston, Australia, 1996. [Google Scholar]
  15. Janzen, D.H. How southern cowpea weevil larvae (Bruchidae: Callobruchus maculatus) die on nonhost seeds. Ecology 1977, 58, 921–927. [Google Scholar] [CrossRef]
  16. Ishimoto, M.; Kitamura, K. Growth inhibitory effects of an a-amylase inhibitor from the kidney bean, Phaseolus vulgaris (L.) on three species of bruchids (Coleoptera: Bruchidae). Appl. Entomol. Zool. 1989, 24, 281–286. [Google Scholar] [CrossRef]
  17. Oliveira, A.E.A.; Sales, M.P.; Machado, O.L.T.; Fernandes, K.V.S.; Xavier-Filho, J. The toxicity of Jack bean (Canavalia ensiformis) cotyledon and seed coat proteins to the cowpea weevil (Callosobruchus maculatus). Entomol. Exp. Appl. 1999, 92, 249–255. [Google Scholar] [CrossRef]
  18. Souza, A.; Ferreira, A.; Perales, J.; Beghini, D.; Fernandes, K.; Xavier-Filho, J.; Venancio, T.; Oliveira, A. Identification of Albizia lebbeck seed coat chitinbinding vicilins (7S globulins) with high toxicity to the larvae of the Bruchid Callosobruchus maculatus. Braz. J. Med. Biol. Res. 2012, 45, 118–124. [Google Scholar] [CrossRef] [PubMed]
  19. Odeyemi, O.O.; Masika, P.; Afolayan, A.J. A review of the use of phytochemicals for insect pest control. Afr. Plant Prot. 2008, 14, 1–7. [Google Scholar]
  20. Klys, M.; Malejky, N.; Nowak-Chmura, M. The repellent effect of plants and their active substances against the beetle storage pests. J. Stored Prod. Res. 2017, 74, 66–77. [Google Scholar] [CrossRef]
  21. Hou, X.; Taylor, W.; Fields, P. Effect of pea flour and pea flour extracts on Sitophilus oryzae. Can. Entomol. 2006, 138, 95–103. [Google Scholar] [CrossRef]
  22. Woodring, J.; Hoffmann, K.H.; Lorenz, M.W. Feeding, nutrient flow, and digestive enzyme release in the giant milkweed bug, Oncopeltus faciatus. Physiol. Entomol. 2007, 32, 328–335. [Google Scholar] [CrossRef]
  23. Mullins, D.E. Physiology of environmental adaptations and resource acquisition in cockroaches. Annu. Rev. Entomol. 2015, 60, 473–492. [Google Scholar] [CrossRef]
  24. Borzoui, E.; Bandani, A.R.; Goldansaz, S.H.; Talaei-Hassanlouei, R. Dietary protein and carbohydrate levels affect performance and digestive physiology of Plodia interpunctella (Lepidoptera: Pyralidae). J. Econ. Entomol. 2018, 111, 942–949. [Google Scholar] [CrossRef]
  25. De Groote, H.; De Groote, B.; Bruce, A.Y.; Marangu, C.; Tefera, T. Maize storage insects (Sitophilus zeamais and Prostephanus truncatus) prefer to feed on smaller maize grains and grains with color, especially green. J. Stored Prod. Res. 2017, 71, 72–80. [Google Scholar] [CrossRef]
  26. Gautam, S.G.; Opit, G.P.; Giles, K.L.; Adam, B. Weight loss and germination failure caused by psocids in different wheat varieties. J. Econ. Entomol. 2013, 106, 491–498. [Google Scholar] [CrossRef] [PubMed]
  27. Athanassiou, C.G.; Opit, G.P.; Throne, J.E. Influence of commodity type, percentage of cracked kernels, and wheat class on population growth of stored product psocids (Psocoptera: Liposcelididae). J. Econ. Entomol. 2010, 103, 985–990. [Google Scholar] [CrossRef]
  28. Cox, P.D.; Collins, L.E. Factors affecting the behaviour of beetle pests in stored grain, with particular reference to the development of lures. J. Stored Prod. Res. 2002, 38, 95–115. [Google Scholar] [CrossRef]
  29. Perez-Mendoza, J.; Campbell, J.F.; Throne, J.E. Effect of abiotic factors on initiation of red flour beetle (Coleoptera: Tenebrionidae) flight. J. Econ. Entomol. 2014, 107, 469–472. [Google Scholar] [CrossRef]
  30. Perez-Mendoza, J.; Dover, B.A.; Hagstrum, D.W.; Hopkins, T.L. Effect of crowding, food deprivation, and diet on flight initiation and lipid reserves of the lesser grain borer, Rhyzopertha dominica. Entomol. Exp. Appl. 1999, 91, 317–326. [Google Scholar] [CrossRef]
  31. Hudaib, T.; Hayes, W.; Brown, S.; Eady, P.E. Seed coat phytochemistry of both resistant and susceptible seeds affords some protection against the granivorous beetle Callosobruchus maculatus. J. Stored Prod. Res. 2017, 74, 27–32. [Google Scholar] [CrossRef]
  32. Zars, T. Two thermossensors in Drosophila have different behavioral functions. J. Comp. Physiol. 2001, 187, 235–242. [Google Scholar] [CrossRef]
  33. Jian, F.; Fields, P.G.; Hargreaves, K.; Jayas, D.S.; White, N.D.G. Chill-coma and minimum movement temperatures of stored-product beetles in stored wheat. J. Econ. Entomol. 2015, 2471–2478. [Google Scholar] [CrossRef]
  34. Fields, P.G. The control of stored-product insects and mites with extreme temperatures. J. Stored Prod. Res. 1992, 28, 89–118. [Google Scholar] [CrossRef]
  35. Harrison, J.F.; Fewell, J.H. Thermal effects on feeding behaviour and net energy intake rare in the honey bee, Apis mellifera. Comp. Biochem. Physiol. 1995, 133, 323–333. [Google Scholar] [CrossRef]
  36. Flinn, P.W.; Hagstrum, D.W.; Reed, C.; Phillips, T.W. Insect population dynamics in commercial grain elevators. J. Stored Prod. Res. 2010, 46, 43–47. [Google Scholar] [CrossRef]
  37. Harrison, J.F.; Woods, H.A.; Roberts, S.P. Ecological and Environmental Physiology of Insects; Oxford University Press: Oxford, UK, 2012. [Google Scholar]
  38. Abdelghany, A.Y.; Fields, P.G. Mortality and movement of Cryptolestes ferrugineus and Rhyzopertha dominica in response to cooling in 300-kg grain bulks. J. Stored Prod. Res. 2017, 71, 119–124. [Google Scholar] [CrossRef]
  39. Jian, F.; Larson, R.; Jayas, D.S.; White, N.D.G. Three dimensional temporal and spatial distribution of adults of Tribolium castaneum (Coleoptera: Tenebrionidae) in stored wheat under different temperatures and adult densities. Agric. Res. 2012, 1, 165–174. [Google Scholar] [CrossRef]
  40. Murdock, L.L.; Margam, V.; Baoua, I.; Balfe, S.; Shade, R.E. Death by desiccation: Effects of hermetic storage on cowpea bruchids. J. Stored Prod. Res. 2012, 49, 166–170. [Google Scholar] [CrossRef]
  41. Loschiavo, S.R. Distribution of the rusty grain beetle (Coleoptera: Cucujidae) in columns of wheat stored dry or with localized high moisture content. J. Econ. Entomol. 1983, 76, 881–884. [Google Scholar] [CrossRef]
  42. Collins, L.E.; Conyers, S.T. Moisture content gradient and ventilation in stored wheat affect movement and distribution of Oryzaephilus surinamensis and have implications for pest monitoring. J. Stored Prod. Res. 2009, 45, 32–39. [Google Scholar] [CrossRef]
  43. Muralitharan, V.; Rajan, T.S.; Chandrasekaran, S.; Mohankumar, S. Studies on spatial flight pattern and movement of three stored grain insect pests in storage godown. Madras Agric. J. 2016, 103, 154–158. [Google Scholar]
  44. Athanassiou, C.G.; Palyvos, N.E.; Eliopoulos, P.A.; Papadoulis, G.T. Distribution and migration of insects and mites in flat storage containing wheat. Phytoparasitica 2001, 29, 379–392. [Google Scholar] [CrossRef]
  45. Kleih, U.; Pike, V. Economic assessment of psocid infestations in rice storage. Trop. Sci. 1995, 35, 280–289. [Google Scholar]
  46. Rees, D. Psocoptera (psocids) as pests of bulk grain storage in Australia: A cautionary tale to industry and researchers. In Proceedings of the 8th International Working Conference on Stored-product Protection, York, UK, 22–26 July 2002; pp. 59–64. [Google Scholar]
  47. Mankin, R.W.; Hagstrum, D.W. Three-dimensional orientation of male Cadra cautella (Lepidoptera: Pyralidae) flying to calling females in a windless environment. Environ. Entomol. 1995, 24, 1616–1626. [Google Scholar] [CrossRef]
  48. Bowditch, T.G.; Madden, J.L. Spatial and temporal distribution of Ephestia cautella (Walker) (Lepidoptera: Pyralidae) in a confectionery factory: Causal factors and management implications. J. Stored Prod. Res. 1996, 32, 123–130. [Google Scholar] [CrossRef]
  49. Campbell, J.F.; Ching’oma, G.P.; Toews, M.D.; Ramaswamy, S.B. Spatial distribution and movement patterns of stored-product insects. In Proceedings of the 9th International Working Conference on Stored-product Protection, Campinas, Brazil, 15–18 October 2006; pp. 361–370. [Google Scholar]
  50. Wright, V.F.; Fleming, E.E.; Post, D. Survival of Rhyzopertha dominica (Coleoptera, Bostrichidae) on fruits and seeds collected from woodrat nests in Kansas. J. Kansas Entomol. Soc. 1990, 63, 344–347. [Google Scholar]
  51. Mahroof, R.M.; Edde, P.A.; Robertson, B.; Puckette, J.A.; Phillips, T.W. Dispersal of Rhyzopertha dominica (Coleoptera: Bostrichidae) in different habitats. Environ. Entomol. 2010, 39, 930–938. [Google Scholar] [CrossRef]
  52. Daglish, G.J.; Ridley, A.W.; Reid, R.; Walter, G.H. Testing the consistency of spatio-temporal patterns of flight activity in the stored grain beetles Tribolium castaneum (Herbst) and Rhyzopertha dominica (F.). J. Stored Prod. Res. 2017, 72, 68–74. [Google Scholar] [CrossRef]
  53. Hill, M.G.; Borgemesiter, C.; Nansen, C. Ecological studies on the larger grain borer, Prostephanus truncatus (Horn) (Col.: Bostrichidae) and their implications for integrated pest management. Integr. Pest Manag. Rev. 2002, 7, 201–221. [Google Scholar] [CrossRef]
  54. Jian, F.; Jayas, D.S. Detecting and responding to resource and stimulus during the movements of Cryptolestes ferrugineus adults. Food Bioprocess Technol. 2009, 2, 45–56. [Google Scholar] [CrossRef]
  55. Jian, F.; Jayas, D.S.; White, N.D.G. Optimal environmental search and scattered orientations during movement of adult rusty grain beetles, Cryptolestes ferrugineus (Stephens), in grain bulks—Suggested movement and distribution patterns. J. Stored Prod. Res. 2009, 45, 177–183. [Google Scholar] [CrossRef]
  56. Parker, G.A. Evolution of competitive mate searching. Annu. Rev. Entomol. 1978, 23, 173–196. [Google Scholar] [CrossRef]
  57. Malekpour, R.; Rafter, M.A.; Daglish, G.J.; Walter, H.W. The movement abilities and resource location behaviour of Tribolium castaneum: Phosphine resistance and its genetic influences. J. Pest Sci. 2018, 91, 739–749. [Google Scholar] [CrossRef]
  58. McKay, T.; White, A.L.; Starkus, L.A.; Arthur, F.; Campbell, A. Seasonal patterns of stored-product insects at a rice mill. J. Econ. Entomol. 2017, 110, 1366–1376. [Google Scholar] [CrossRef]
  59. Giles, P.H. Observations in Kenya on the flight activity of stored products insects, particularly Sitophilus zeamais Motsch. J. Stored Prod. Res. 1969, 4, 317–329. [Google Scholar] [CrossRef]
  60. Toews, M.D.; Campbell, J.F.; Arthur, F.H.; Ramaswamy, S.B. Outdoor flight activity and immigration of Rhyzopertha dominica into seed wheat warehouses. Entomol. Exp. Appl. 2006, 121, 73–85. [Google Scholar] [CrossRef]
  61. Rajan, T.S.; Muralitharan, V.; Daglish, G.J.; Mohankumar, S.; Rafter, M.A.; Chandrasekaran, S.; Mohan, S.; Vimal, D.; Srivastava, C.; Loganathan, M.; et al. Flight of three major insect pests of stored grain in the monsoonal tropics of India, by latitude, season and habitat. J. Stored Prod. Res. 2018, 76, 43–50. [Google Scholar] [CrossRef]
  62. Hagstrum, D.W. Immigration of insects into bins etoring newly harvested wheat on 12 Kansas farms. J. Stored Prod. Res. 2001, 37, 221–229. [Google Scholar] [CrossRef]
  63. Vásquez-castro, J.A.; Baptista, G.C.d.; Trevizan, L.R.P.; Gadanha, C.D., Jr. Flight activity of Sitophilus oryzae (L) and Sitophilus zeamais Motsch (Coleoptera: Curculionidae) and its relationship with susceptibility to Insecticides. Neotrop. Entomol. 2009, 38, 405–409. [Google Scholar] [CrossRef] [PubMed]
  64. Cox, P.D.; Wakefield, M.E.; Jacob, T.A. The effects of temperature on flight initiation in a range of moths, beetles and parasitoids associated with stored products. J. Stored Prod. Res. 2007, 43, 111–117. [Google Scholar] [CrossRef]
  65. Ridley, A.W.; Hereward, J.P.; Daglish, G.J.; Raghu, S.; McCulloch, G.A.; Walter, G.H. Flight of Rhyzopertha dominica (Coleoptera: Bostrichidae)—A spatio-temporal analysis with pheromone trapping and population genetics. J. Econ. Entomol. 2016, 109, 2561–2571. [Google Scholar] [CrossRef] [PubMed]
  66. Leos-Martinez, J.; Granovsky, T.A.; Williams, H.J.; Vinson, S.B.; Burkholder, W.E. Estimation of aerial density of the lesser grain borer (Coleoptera: Bostrichidae) in a warehouse using dominicalure traps. J. Econ. Entomol. 1986, 79, 1134–1138. [Google Scholar] [CrossRef]
  67. Dowdy, A.K. Flight initiation of lesser grain borer (Coleoptera: Bostrichidae) as influenced by temperature, humidity, and light. J. Econ. Entomol. 1994, 87, 1714–1717. [Google Scholar] [CrossRef]
  68. Sinclair, E.R.; Alder, J. Migration of stored-grain insect pests from a small wheat bulk. Aust. J. Exp. Agric. Anim. Husb. 1984, 24, 260–266. [Google Scholar] [CrossRef]
  69. Wright, E.J.; Morton, R. Daily flight activity of Trogoderma variabile (Coleoptera: Dermestidae) and Rhyzopertha dominica (Coleoptera: Bostrichidae). J. Stored Prod. Res. 1995, 31, 177–184. [Google Scholar] [CrossRef]
  70. Fardisi, M.; Mason, L.J. Influence of temperature, gender, age, and mating status on cigarette beetle (Lasioderma serricorne (F.)) (Coleoptera: Anobiidae) flight initiation. J. Stored Prod. Res. 2013, 52, 93–99. [Google Scholar] [CrossRef]
  71. Vela-Coiffier, E.L.; Fargo, W.S.; Bonjour, E.L.; Cuperus, G.W.; Warde, W.D. Immigration of insects into on-farm stored wheat and relationships among trapping methods. J. Stored Prod. Res. 1997, 33, 157–166. [Google Scholar] [CrossRef]
  72. Reed, C.; Anderson, K.; Brockschmidt, J.; Wright, V.; Pedersen, J. Cost and effectiveness of chemical insect control measures in farm-stored Kansas wheat. J. Kansas Entomol. Soc. 1990, 63, 351–360. [Google Scholar]
  73. Hagstrum, D.W.; Gilbert, E.E. Emigration rate and age structure dynamics of Tribolium castaneum populations during growth phase of a colonizing episode. Environ. Entomol. 1976, 5, 445–448. [Google Scholar] [CrossRef]
  74. Smith, L.B. Effect of crowding on oviposition, development and mortality of Cryptolestes ferrugnieus (Stephens) (Coleoptera, Cucujidae). J. Stored Prod. Res. 1966, 2, 91–96. [Google Scholar] [CrossRef]
  75. Kotaki, T.; Nakakita, H.; Kuwahara, M. Crowding inhibits pupation in Tribolium freemani (Coleoptera, Tenebrionidae)—Effects of isolation and juvenile hormone analogues on development and pupation. Appl. Entomol. Zool. 1993, 28, 43–52. [Google Scholar] [CrossRef]
  76. Cayetano, L.; Maklakov, A.A.; Brooks, R.C.; Bonduriansky, R. Evolution of male and female genitalia following release from sexual selection. Evolution 2011, 65, 2171–2183. [Google Scholar] [CrossRef]
  77. Bhavanam, S.; Trewick, S. Effects of larval crowding and nutrient limitation on male phenotype, reproductive investment and strategy in Ephestia kuehniella Zeller (Insecta: Lepidoptera). J. Stored Prod. Res. 2017, 71, 64–71. [Google Scholar] [CrossRef]
  78. Petrakis, P.V.; Legakis, A. Insect migration and dispersal with emphasis on Mediterranean ecosystems. In Migration of Organisms, Climate, Geography, Ecology; Elewa, A.M.T., Ed.; Springer: Berlin/Heidelberg, Germany; New York, NY, USA, 2005; pp. 85–126. [Google Scholar]
  79. White, N.D.G.; Sinha, R.N.; Jayas, D.S.; Muir, W.E. Movement of Cyptolestes ferrugineus (Coleoptera, cucujidae) through carbon-dioxide gradients in stored wheat. J. Econ. Entomol. 1993, 86, 1846–1851. [Google Scholar] [CrossRef]
  80. Navarro, S.; Amos, T.G.; Williams, P. The effect of oxygen and carbon dioxide gradients on the vertical dispersion of grain insects in wheat. J. Stored Prod. Res. 1981, 17, 101–107. [Google Scholar] [CrossRef]
  81. Sinha, R.N.; Wallace, H.A.H. Ecology of insect-induced hot spots in stored grain in western Canada. Res. Popul. Ecol. 1966, VIII, 107–132. [Google Scholar] [CrossRef]
  82. Kłyś, M. Emigration activity of the saw-toothed grain beetle Oryzaephilus surinamensis L. (Coleoptera: Silvanidae) in various environmental temperatures. J. Plant Prot. Res. 2012, 52, 397–400. [Google Scholar] [CrossRef]
  83. Navarro, S.; Finkelman, S.; Rindner, M.; Dias, R. Emigration and control of nitidulid beetles from dates using heat. Integr. Prot. Stored Prod. IOBC Bull. 2004, 27, 219–225. [Google Scholar]
  84. Phillips, T.W.; Throne, J.E. Biorational approaches to managing stored-product insects. Annu. Rev. Entomol. 2010, 55, 375–397. [Google Scholar] [CrossRef]
  85. Nayak, M.K.; Collins, P.J.; Pavic, H.; Kopittke, R.A. Inhibition of egg development by phosphine in the cosmopolitan pest of stored products Liposcelis bostrychophila (Psocoptera: Liposcelididae). Pest Manag. Sci. 2003, 59, 1191–1196. [Google Scholar] [CrossRef]
  86. Athanassiou, C.G.; Phillips, T.W.; Wakil, W. Biology and control of the khapra Beetle, Trogoderma granarium, a major quarantine threat to global food security. Annu. Rev. Entomol. 2019, 64, 8.1–8.18. [Google Scholar] [CrossRef]
  87. Roesli, R.; Jones, R. The use of various insect traps for studying psocid populations. In Proceedings of the 6th International Working Conference on Stored-product Protection, Canberra, Australia, 17–23 April 1994; pp. 448–450. [Google Scholar]
  88. Nayak, M.K.; Collins, P.J.; Throne, J.E.; Wang, J.J. Biology and management of psocids infesting stored products. Annu. Rev. Entomol. 2014, 59, 279–297. [Google Scholar] [CrossRef]
  89. Nayak, M.K.; Collins, P.J.; Pavic, H. Long-term effectiveness of grain protectants and structural treatments against Liposcelis decolor (Pearman) (Psocoptera: Liposcelididae), a pest of stored products. Pest Manag. Sci. 2002, 58, 1223–1228. [Google Scholar] [CrossRef] [PubMed]
  90. Jian, F.; Jayas, D.S.; White, N.D.G. How many kilograms of grain per sample unit is big enough? Part II—Simulation of sampling from grain mass with different insect densities and distribution patterns. J. Stored Prod. Res. 2014, 56, 67–80. [Google Scholar] [CrossRef]
  91. Jian, F.; Jayas, D.S.; White, N.D.G. How many kilograms of grain per sample unit is big enough? Part I—Comparison of insect detection and density estimation between manual probe sampling and Insector® system. J. Stored Prod. Res. 2014, 56, 60–66. [Google Scholar] [CrossRef]
  92. Amoah, B.; Hagstrum, D.; Subramanyam, B.; Campbell, J.F.; Schilling, M.W.; Phillips, T.W. Sampling methods to detect and estimate populations of Tyrophagus putrescentiae (Schrank) (Sarcoptiformes: Acaridae) infesting dry-cured hams. J. Stored Prod. Res. 2017, 73, 98–108. [Google Scholar] [CrossRef]
  93. Wilkin, D.R.; Fleurat-Lessard, F. The detection of insects in grain using conventional sampling spears. In Proceedings of the 5th International Working Conference Stored-product Protection, Bordeaux, France, 9–14 September 1990; pp. 1445–1454. [Google Scholar]
  94. Stejskal, V.; Aulicky, R.; Kucerova, Z.; Lukas, J. Method of sampling and laboratory extraction affects interpretation of grain infestation by storage pests. J. Plant Dis. Prot. 2008, 115, 129–133. [Google Scholar] [CrossRef]
  95. Lukas, J.; Kučerová, Z.; Aulický, R.; Stejskal, V. How methodical approaches affects results of pest sampling in stores and counting in laboratory. In Proceedings of the 10th International Working Conference on Stored-product Protection, Estoril, Portugal, 27 June–2 July 2010; p. 150. [Google Scholar]
  96. Jian, F.; Jayas, D.S.; White, N.D.G. Effects of temperature acclimation and age on movement of Cryptolestes ferrugineus (Coleoptera: Laemophloeidae) adults in response to temperature gradients. Can. Entomol. 2005, 137, 71–82. [Google Scholar] [CrossRef]
  97. Cordeiro, E.M.G.; Campbell, J.F.; Phillips, T.W. Movement and orientation decision modeling of Rhyzopertha dominica (Coleoptera: Bostrichidae) in the grain mass. Environ. Entomol. 2016, 45, 410–419. [Google Scholar] [CrossRef]
  98. Semeao, A.A.; Campbell, J.F.; Whitworth, R.J.; Sloderbeck, P.E. Influence of Environmental and Physical Factors on Capture of Tribolium castaneum (Coleoptera: Tenebrionidae) in a Flour Mill. J. Econ. Entomol. 2012, 105, 686–702. [Google Scholar] [CrossRef] [PubMed]
  99. Jian, F.; Larson, R.; Jayas, D.S.; White, N.D.G. Evaluation of sampling units and sampling plans for adults of Cryptolestes ferrugineus (Coleoptea: Laemophloeidae) in stored wheat under different temperatures, moisture contents, and adult densities. J. Stored Prod. Res. 2011, 47, 334–340. [Google Scholar] [CrossRef]
  100. Green, R.H. On fixed precision level sequential sampling. Res. Popul. Ecol. 1970, 12, 249–251. [Google Scholar] [CrossRef]
  101. Subramanyam, B.; Hagstrum, D.W. Sampling. In Integrated Management of Insects in Stored Products; Subramanyam, B., Hagstrum, D.W., Eds.; Marcel Dekker, Inc.: New York, NY, USA, 1995; pp. 135–194. [Google Scholar]
  102. Jian, F.; Jayas, D.S.; White, N.D.G.; Fields, P.G. Insect detection and density estimation in stored grain bins: Is it a needle in a haystack or an elephant in a room? In Proceedings of the 11th International Working Conference on Stored-Product Protection, Chiang Mai, Thailand, 24–28 November 2014; pp. 230–245. [Google Scholar]
  103. Dowdy, A.K.; Mullen, M.A. Multiple stored-product insect pheromone use in pitfall traps. J. Stored Prod. Res. 1998, 34, 75–80. [Google Scholar] [CrossRef]
  104. Toews, M.D.; Phillips, T.W.; Payton, M.E. Estimating populations of grain beetles using probe traps in wheat-filled concrete silos. Environ. Entomol. 2005, 34, 712–718. [Google Scholar] [CrossRef]
  105. Hagstrum, D.W.; Flinn, P.W.; Subramanyam, B. Predicting Insect Density From Probe Trap Catch in Farm-Stored Wheat. J. Stored Prod. Res. 1998, 34, 251–262. [Google Scholar] [CrossRef]
  106. Athanassiou, C.G.; Buchelos, C.T. Detection of stored-wheat beetle species and estimation of population density using unbaited probe traps and grain trier samples. Entomol. Exp. Appl. 2001, 98, 67–78. [Google Scholar] [CrossRef]
  107. Jian, F.; Larson, R. Relationship between density of adult rusty grain beetle, Cryptolestes ferrugineus (Coleoptera: Laemophloeidae) and insector counts in stored wheat at uniform moisture contect and small temperature fluctuations. In Proceedings of the 9th International Working Conference on Stored-Product Protection, Campinas, Brazil, 15–18 October 2006; pp. 456–462. [Google Scholar]
  108. Flinn, P.W.; Opit, G.P.; Throne, J.E. Predicting stored grain insect population densities using an electronic probe trap. J. Econ. Entomol. 2009, 102, 1696–1704. [Google Scholar] [CrossRef] [PubMed]
  109. Wakefield, M.E.; Cogan, P.M. The use of a managed bulk of grain for the evaluation of PC, pitfall beaker, insect probe and WBII probe traps for monitoring Sitophilus granarius during the winter and summer in the UK. J. Stored Prod. Res. 1999, 35, 329–338. [Google Scholar] [CrossRef]
  110. Stejskal, V. The influence of food and shelter on the efficacy of a commercial sticky trap in Tribolium castaneum (Coleoptera: Tenebrionidae). J. Stored Prod. Res. 1995, 31, 229–233. [Google Scholar] [CrossRef]
  111. Hawkin, K.J.; Stanbridge, D.M.; Fields, P.G. Sampling Tribolium castaneum and Tribolium confusum in flour mill rollstands. J. Stored Prod. Res. 2013, 52, 7–11. [Google Scholar] [CrossRef]
  112. Buckman, K.A.; Campbell, J.F. How varying pest and trap densities affect Tribolium castaneum capture in pheromone traps. Entomol. Exp. Appl. 2013, 146, 404–412. [Google Scholar] [CrossRef]
  113. Campbell, J.F.; Hagstrum, D.W. Patch exploitation by Tribolium Castaneum: Movement patterns, distribution, and oviposition. J. Stored Prod. Res. 2002, 38, 55–68. [Google Scholar] [CrossRef]
  114. Hawkin, K.; Stanbridge, D.; Fields, P. Sampling Tribolium confusum and Tribolium castaneum in mill and laboratory settings: Differences between strains and species. Can. Entomol. 2011, 143, 504–517. [Google Scholar] [CrossRef]
  115. Campbell, J.F. Attraction of walking Tribolium castaneum adults to traps. J. Stored Prod. Res. 2012, 51, 11–22. [Google Scholar] [CrossRef]
  116. Toews, M.D.; Arthur, F.H.; Campbell, J.F. Monitoring Tribolium castaneum (Herbst) in pilot-scale warehouses treated with β-cyfluthrin: Are residual insecticides and trapping compatible? Bull. Entomol. Res. 2009, 99, 121–129. [Google Scholar] [CrossRef]
  117. Athanassiou, C.G.; Kavallieratos, N.G.; Campbell, J.F. Capture of Tribolium castaneum and Tribolium confusum (Coleoptera: Tenebrionidae) in floor traps: The effect of previous captures. J. Econ. Entomol. 2016, 109, 461–466. [Google Scholar] [CrossRef]
  118. Athanassiou, C.G.; Kavallieratos, N.G.; Campbell, J.F. Effect of the presence of live or dead insects on subsequent captures of six stored-product beetle species: The relative species matters. J. Econ. Entomol. 2017, 110, 770–775. [Google Scholar] [CrossRef]
  119. Athanassiou, C.G.; Kavallieratos, N.G.; Trematerra, P. Responses of Sitophilus oryzae (Coleoptera: Curculionidae) and Tribolium confusum (Coleoptera: Tenebrionidae) to traps baited with pheromones and food volatiles. Eur. J. Entomol. 2006, 103, 371–378. [Google Scholar] [CrossRef]
  120. Campbell, J.F.; Mullen, M.A.; Dowdy, A.K. Monitoring Stored-Product Pests in Food Processing Plants with Pheromone Trapping, Contour Mapping, and Mark-Recapture. J. Econ. Entomol. 2002, 95, 1089–1101. [Google Scholar] [CrossRef][Green Version]
  121. Arthur, F.H. Efficacy of chlorpyrifos-methyl for control of maize weevils (Coleoptera, Curculionidae) and red flour beetles (Tenebrionidae) in mixtures of treated and untreated corn. J. Econ. Entomol. 1992, 85, 554–560. [Google Scholar] [CrossRef]
  122. Kavallieratos, N.G.; Athanassiou, C.G.; Arthur, F.H. Efficacy of deltamethrin against stored-product beetles at short exposure intervals or on a partially treated rice mass. J. Econ. Entomol. 2015, 108, 1416–1421. [Google Scholar] [CrossRef]
  123. Daglish, G.J.; Nayak, M.K. Uneven application can influence the efficacy of s-methoprene against Rhyzopertha dominica (F.) in wheat. J. Stored Prod. Res. 2010, 46, 250–253. [Google Scholar] [CrossRef]
  124. Athanassiou, C.G.; Arthur, F.H.; Throne, J.E. Efficacy of spinosad in layer-treated wheat against five stored-product insect species. J. Stored Prod. Res. 2009, 45, 236–240. [Google Scholar] [CrossRef]
  125. Fields, P.; Korunic, Z. The effect of grain moisture content and temperature on the efficacy of diatomaceous earths from different geographical locations against stored-product beetles. J. Stored Prod. Res. 2000, 36, 1–13. [Google Scholar] [CrossRef]
  126. Wijayaratne, L.K.W.; Fields, P.G.; Arthur, F.H. Effect of methoprene on the progeny production of Tribolium castaneum (Coleoptera: Tenebrionidae). Pest Manag. Sci. 2012, 68, 217–224. [Google Scholar] [CrossRef]
  127. Arthur, F.H. Aerosol distribution and efficacy in a commercial food warehouse. Insect Sci. 2008, 15, 133–140. [Google Scholar] [CrossRef]
  128. Jenson, E.A.; Arthur, F.H.; Nechols, J.R. Efficacy of methoprene applied at different temperatures and rates on surface substrates to control eggs and fifth instars of Plodia interpunctella. J. Econ. Entomol. 2009, 102, 1992–2002. [Google Scholar] [CrossRef] [PubMed]
  129. Jenson, E.A.; Arthur, F.H.; Nechols, J.R. Methoprene and synergized pyrethrins as aerosol treatments to control Plodia interpunctella (Hübner), the Indian meal moth (Lepidoptera: Pyralidae). J. Stored Prod. Res. 2010, 46, 103–110. [Google Scholar] [CrossRef]
  130. Arthur, F.H.; Campbell, J.F. Distribution and efficacy of pyrethrin aerosol to control Tribolium confusum (Coleoptera: Tenebrionidae) in food storage facilities. J. Stored Prod. Res. 2008, 44, 58–64. [Google Scholar] [CrossRef]
  131. Jian, F.; Jayas, D.S.; White, N.D.G.; Fields, P.G.; Howe, N. An evaluation of insect expulsion from wheat samples by microwave treatment for disinfestation. Biosyst. Eng. 2015, 130, 1–12. [Google Scholar] [CrossRef]
  132. Savoldelli, S.; Trematerra, P. Mass-trapping, mating-disruption and attracticide methods for managing stored-product insects: Success stories and research needs. Stewart Postharvest Rev. 2011, 7, 1–8. [Google Scholar] [CrossRef]
  133. Cline, L.D. Penetration of seven common flexible packaging materials by larvae and adults of eleven species of stored-product insects. J. Econ. Entomol. 1978, 71, 726–729. [Google Scholar] [CrossRef]
  134. Highland, H.A.; Wilson, R. Resistance of polymer films to penetration by lesser grain borer and description of a device for measuring resistance. J. Econ. Entomol. 1981, 74, 67–70. [Google Scholar] [CrossRef]
  135. Yerington, A.P. Insects and package seal quality. Modern Package 1978, 51, 41–42. [Google Scholar]
  136. Jian, F.; Jayas, D.S. Engineering considerations for creating uniform distribution of applied gas during controlled atmospheres and fumigation. In Proceedings of the 10th International Conference on Controlled Atmosphere and Fumigation in Stored Products (CAF2016), New Dehli, India, 1–11 November 2016; pp. 377–381. [Google Scholar]
  137. Williams, S.B.; Alexander, C.E.; Mason, L.J. Sanitation’s impact on the effectiveness of the pest management programs of food processing facilities. J. Stored Prod. Res. 2015, 60, 48–53. [Google Scholar] [CrossRef]
  138. Machekano, H.; Mvumi, B.M.; Chinwada, P.; Richardson-Kageler, S.J.; Rwafa, R. Efficacy of diatomaceous earths and their low-dose combinations with spinosad or deltamethrin against three beetle pests of stored-maize. J. Stored Prod. Res. 2017, 72, 128–137. [Google Scholar] [CrossRef]
  139. Wakil, W.; Riasat, T.; Lord, J.C. Effects of combined thiamethoxam and diatomaceous earth on mortality and progeny production of four Pakistani populations of Rhyzopertha dominica (Coleoptera: Bostrichidae) on wheat, rice and maize. J. Stored Prod. Res. 2013, 52, 28–35. [Google Scholar] [CrossRef]
  140. Wakil, W.; Schmitt, T. Field trials on the efficacy of Beauveria bassiana, diatomaceous earth and Imidacloprid for the protection of wheat grains from four major stored grain insect pests. J. Stored Prod. Res. 2015, 64 Pt B, 160–167. [Google Scholar] [CrossRef]
  141. Chanbang, Y.; Arthur, F.H.; Wilde, G.E.; Throne, J.E. Efficacy of diatomaceous earth and methoprene, alone and in combination, against Rhyzopertha dominica (F.) (Coleoptera: Bostrichidae) in rough rice. J. Stored Prod. Res. 2007, 43, 396–401. [Google Scholar] [CrossRef]
  142. Dowdy, A.K.; Fields, P.G. Heat Combined With Diatomaceous Earth to Control the Confused Flour Beetle (Coleoptera: Tenebrionidae) in a Flour Mill. J. Stored Prod. Res. 2002, 38, 11–22. [Google Scholar] [CrossRef]
  143. Campos, M.; Phillips, T.W. Contact toxicity of insecticides for attract-and-kill applications against adult Plodia interpunctella (Hübner) (Lepidoptera: Pyralidae). Pest Manag. Sci. 2010, 66, 752–761. [Google Scholar] [CrossRef]
  144. Riudavets, J.; Castañé, C.; Alomar, O.; Pons, M.J.; Gabarra, R. Modified atmosphere packaging (MAP) as an alternative measure for controlling ten pests that attack processed food products. J. Stored Prod. Res. 2009, 45, 91–96. [Google Scholar] [CrossRef]
  145. Lindgren, D.a.L.; Vincent, L.l.E.; Krohne, H.E. The khapra beetle, Trogoderma granarium Everts. Hilgardia 1955, 24, 1–36. [Google Scholar] [CrossRef]
  146. Harris, A. Khapra Beetle, Trogoderma Granarium Everts; University of Florida, Institute of Food and Agricultural Sciences Extension: Gainesville, FL, USA, 2015. [Google Scholar]
  147. Yao, M.C.; Chang, S.C.; Tseng, J.C.; Lee, C.Y. Investigating the current occurrence status of Trogoderma granarium (Coleoptera: Dermestidae) in Taiwan. Formos. Entomol. 2016, 36, 33–43. [Google Scholar]
  148. Butcher, M.J. Decision making in regulatory entomology: The case of Trogoderma variabile in Western Australia. In Proceedings of the 6th International Working Conference on Stored-product Protection, Canberra, Australia, 17–23 April 1994; pp. 1169–1172. [Google Scholar]
  149. Castalanelli, M.A.; Mikac, K.M.; Baker, A.M.; Munyard, K.; Grimm, M.; Groth, D.M. Multiple incursions and putative species revealed using a mitochondrial and nuclear phylogenetic approach to the Trogoderma variabile (Coleoptera: Dermestidae) trapping program in Australia. Bull. Entomol. Res. 2011, 101, 333–343. [Google Scholar] [CrossRef] [PubMed]
  150. Day, C.; White, B. Khapra Beetle, Trogoderma granarium Interceptions and Eradications in Australia and Around the World. School of Agricultural and Resource Economics; University of Western Australia: Crawley, Australia, 2016; p. 29. [Google Scholar]
  151. Walter, G.H.; Rafter, M.A.; McCulloch, G.A.; Daglish, G.J. To what extent does dispersal by insect flight influence the spatio-temporal dynamics of phosphine resistance? In Proceedings of the 11th International Working Conference on Stored Product Protection, Changmai, Thailand, 24–28 November 2014; pp. 99–103. [Google Scholar]
  152. Ridley, A.W.; Hereward, J.P.; Daglish, G.J.; Raghu, S.; Collins, P.J.; Walter, G.H. The spatiotemporal dynamics of Tribolium castaneum (Herbst): Adult flight and gene flow. Mol. Ecol. 2011, 20, 1635–1646. [Google Scholar] [CrossRef] [PubMed]
  153. Rafter, M.A.; McCulloch, G.A.; Daglish, G.J.; Walter, G.H. Progression of phosphine resistance in susceptible Tribolium castaneum (Herbst) populations under different immigration regimes and selection pressures. Evolut. Appl. 2017, 10, 907–918. [Google Scholar] [CrossRef]
Table 1. Mechanisms of insect control methods in respect of insect movement behaviours.
Table 1. Mechanisms of insect control methods in respect of insect movement behaviours.
Control MethodsMechanismsExamples
Monitoring
 Trapping at outside of grain bulksInsects fly or move into traps with or without bait or pheromoneUse striped funnel trap, dome pitfall trap, flight trap
 Trapping inside grain bulksInsects move into traps without bait or pheromoneUse pitfall trap
 Sampling grain bulksSample grains with moving or non-moving insectsUse probe, vacuum-probe, grain trier, sampler
Physical
 Pheromone trapLure flying insects into traps and killSuppress moth population by using traps
 Heat treatment, controlled atmosphere, microwave heatingElevated temperature of the medium kills insects regardless of insect mobility. Insects might escape to cooler locationsHeat building to 60 °C, apply CO2, N2 and airtight the stored grain
Chemical
 Contact pesticide or growth regulatorInsects moving through the grain mass contact/intake of the applied pesticidesApply DE, methoprene cyfluthrin, pyrethrin, or malathion
 FumigationInsects inhale toxic chemicals regardless of insect mobilityUse Aerotech with NyGuard or phosphine
Biological
 Predator or parasitoidPredators or parasitoids moving through grain mass prey or lives on/in insectsWasp control insect pests as a predator or parasite
 Biological agentsMoving insects contact/intake entomopathogenic fungi, bacteria, and/or the chemicals produced by the biological agent Apply spinosad to the stored grain
Table 2. Different weather conditions reported when flying insects are captured.
Table 2. Different weather conditions reported when flying insects are captured.
Insects aReported Different Flying ConditionsSources
S. zeamais,
S. oryzae
Peak flight from 15:00 to 17:00 pm at 5 to 45 °C on India fields Rajan et al. [61]
In lab at 22 °CVasquez-castro et al. [63], Giles [59]
T. castaneumYear round on Australia fields at 6.6 °C mean minimum to 22.5 °C mean maximum temperatures Daglish et al. [52]
In lab at ≥ 22.5 °C and ≤ 45 °CCox et al. [64], Perez-Mendoza et al. [29]
R. dominicaOn India fields at 4.8 to 9.3 °C Rajan et al. [61]
Year round on Australia fields at mean minimum temperature 6.6 °CRidley et a. [65], Daglish et al. [52]
Year round on Arkansas fields at ≥ −6.7 °C.McKay et al. [58]
On Kansas fields at ≥ 17.5 °C and ≤ 6 m/s wind speed
In a warehouse, small peak of flight activity around sunrise, and large one at sunset
Toews et al. [60]
Leos-Martinez et al. [66]
In lab at 19.9 to 41.6 °C Dowdy 1994 [67]
In lab at 21.5 °C Sinclair and Alder [68]
In lab at 16 °C Wright and Morton [69]
L. serricorneIn lab at 10 to 15 °CMcKay et al. [58]
In lab at 22.5 °CFardisi and Mason 127 [70]
a More than 20 species of flying insects are captured on fields. Only the most studied insects are listed.
Table 3. Relationship between trap capture and actual population density.
Table 3. Relationship between trap capture and actual population density.
Insects aRelationshipSources
C. ferrugineusOnly 25 to 34% of variation of insect population can be explained by a liner regression equationVela-Coiffier et al. [71]
An electronic trap can predict densities of the introduced insects inside grain binsJian et al. [107], Flinn et al. [108]
S. granariusCaptures are different at different temperatures and seasonsWakefield and Cogan [109]
T. castaneumRelationship is not strongToews et al. [60]
Lower captures when food and shelter are present elsewhereVela-Coiffier et al. [71], Stejskal [110]
Few beetles are caught inside a milling machineHawkin et al. [111]
There is a strong correlation between insect density and actual trap capturesBuckman and Campbell [112]
Beetles are more likely to be trapped along walls than next to poles in a warehouseCampbell and Hagstrum [113]
Trap locations, temperature, and flour dust accumulation significantly influence trap capturesSemeao et al. [98]
Field strains are caught 24% less than the laboratory strainsHawkin et al. [114]
Mating status has a significant effect on the captures in aggregation pheromone trapsMalekpour et al. [57]
Response to pheromone/kairomone traps is strong when there is air movement, but not in still airCampbell [115]
MitesOnly about 37% of the variation of insect population can be explainedAmoah et al. [92]
a Only a few species are listed.
Table 4. Effect of short exposure intervals, low doses, mixing treatments, or partial treatments on efficacy.
Table 4. Effect of short exposure intervals, low doses, mixing treatments, or partial treatments on efficacy.
PesticideInsectsTreatment MethodEfficacySources
Chlorpyriphos-methylS. zeamais,
T. castaneum
Treated:untreated corn = 2:3Similar with 100% treated corn for the long-term controlArthur [121]
DeltamethrinT. castaneum,
R. Dominica
S. granarius
Mixing treated and untreated brown riceMortality of adults < 7%, progeny is reducedKavallieratos et al. [122]
S-methopreneR. dominicaMixing treated and untreated wheatProgeny depends on both the average dose and evenness of applicationDaglish and Nayak [123]
SpinosadR. dominica,
S. oryzae,
L. paeta,
L. bostrychophila,
L. reticulatus
Layer, top, or portion treatment of wheatSpecies dependent, mortality is high if insects moved through the treated wheatAthanassiou et al. [124]
Diatomaceous earthC. ferrugineus;
S. oryzae,
O. surinamensis,
R. dominica,
T. castaneum
Different doses and different temperatures of wheatInsect mobility and species dependentFields and Korunic [125]
MethopreneT.castaneumWheat treated at 0.001 to 0.0165 ppmProgeny is reduced at 1600–5000 times lower than the label dosageWijayaratne [126]
Table 5. Relationship between elements of an integrated pest management (IPM) approach and required knowledge of insect movement.
Table 5. Relationship between elements of an integrated pest management (IPM) approach and required knowledge of insect movement.
Elements of An IPM ApproachRequired Knowledge of Insect Movement
(1) planning and managing storage ecosystems to prevent insect infestationMovement ability of insects infesting the storage ecosystem
(2) identifying pests and understanding their biology and ecologyTheir mobility related to their population dynamics
(3) monitoring populations of pests and storage environmentRelationship between mobility and the prediction of insect density and distribution
(4) making control decisions based on the information collectedUnknown movement might result in a wrong decision or the decision cannot be made
(5) reducing pest populations to acceptable levelsMovement will result in re-infestation and population fluctuation
(6) evaluating effect and efficacy of IPM decisionsUnknown movement might result in a wrong evaluation or the evaluation cannot be made

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