Influences of Stored Product Insect Movements on Integrated Pest Management Decisions
Abstract
:1. Introduction
2. Movement Motivation and Mobility of Stored Product Insects
2.1. Moving to Food Sources
2.2. Moving to Warmer Locations
2.3. Moving to Humid Locations
2.4. Search for Mating and Egg Laying Sites
2.5. Flying of Stored Product Insects
3. Advantages and Disadvantages of Dispersal in IPM Considerations
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
4.1.2. Movement Makes Trapping More Efficient, but Is Influenced by Many Factors
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
4.2.2. Movement Restricts the Use of Some Pest Control Tactics
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
4.3.2. Mobility Makes Area-Wide Pest Management Programs Necessary
4.4. Movement Results in a Diverse Genetic Pool
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
5.2. Research on Insect Movement Behaviours Is Necessary
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
Acknowledgments
Conflicts of Interest
References
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Control Methods | Mechanisms | Examples |
---|---|---|
Monitoring | ||
Trapping at outside of grain bulks | Insects fly or move into traps with or without bait or pheromone | Use striped funnel trap, dome pitfall trap, flight trap |
Trapping inside grain bulks | Insects move into traps without bait or pheromone | Use pitfall trap |
Sampling grain bulks | Sample grains with moving or non-moving insects | Use probe, vacuum-probe, grain trier, sampler |
Physical | ||
Pheromone trap | Lure flying insects into traps and kill | Suppress moth population by using traps |
Heat treatment, controlled atmosphere, microwave heating | Elevated temperature of the medium kills insects regardless of insect mobility. Insects might escape to cooler locations | Heat building to 60 °C, apply CO2, N2 and airtight the stored grain |
Chemical | ||
Contact pesticide or growth regulator | Insects moving through the grain mass contact/intake of the applied pesticides | Apply DE, methoprene cyfluthrin, pyrethrin, or malathion |
Fumigation | Insects inhale toxic chemicals regardless of insect mobility | Use Aerotech with NyGuard or phosphine |
Biological | ||
Predator or parasitoid | Predators or parasitoids moving through grain mass prey or lives on/in insects | Wasp control insect pests as a predator or parasite |
Biological agents | Moving insects contact/intake entomopathogenic fungi, bacteria, and/or the chemicals produced by the biological agent | Apply spinosad to the stored grain |
Insects a | Reported Different Flying Conditions | Sources |
---|---|---|
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 °C | Vasquez-castro et al. [63], Giles [59] | |
T. castaneum | Year 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 °C | Cox et al. [64], Perez-Mendoza et al. [29] | |
R. dominica | On India fields at 4.8 to 9.3 °C | Rajan et al. [61] |
Year round on Australia fields at mean minimum temperature 6.6 °C | Ridley 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. serricorne | In lab at 10 to 15 °C | McKay et al. [58] |
In lab at 22.5 °C | Fardisi and Mason 127 [70] |
Insects a | Relationship | Sources |
---|---|---|
C. ferrugineus | Only 25 to 34% of variation of insect population can be explained by a liner regression equation | Vela-Coiffier et al. [71] |
An electronic trap can predict densities of the introduced insects inside grain bins | Jian et al. [107], Flinn et al. [108] | |
S. granarius | Captures are different at different temperatures and seasons | Wakefield and Cogan [109] |
T. castaneum | Relationship is not strong | Toews et al. [60] |
Lower captures when food and shelter are present elsewhere | Vela-Coiffier et al. [71], Stejskal [110] | |
Few beetles are caught inside a milling machine | Hawkin et al. [111] | |
There is a strong correlation between insect density and actual trap captures | Buckman and Campbell [112] | |
Beetles are more likely to be trapped along walls than next to poles in a warehouse | Campbell and Hagstrum [113] | |
Trap locations, temperature, and flour dust accumulation significantly influence trap captures | Semeao et al. [98] | |
Field strains are caught 24% less than the laboratory strains | Hawkin et al. [114] | |
Mating status has a significant effect on the captures in aggregation pheromone traps | Malekpour et al. [57] | |
Response to pheromone/kairomone traps is strong when there is air movement, but not in still air | Campbell [115] | |
Mites | Only about 37% of the variation of insect population can be explained | Amoah et al. [92] |
Pesticide | Insects | Treatment Method | Efficacy | Sources |
---|---|---|---|---|
Chlorpyriphos-methyl | S. zeamais, T. castaneum | Treated:untreated corn = 2:3 | Similar with 100% treated corn for the long-term control | Arthur [121] |
Deltamethrin | T. castaneum, R. Dominica S. granarius | Mixing treated and untreated brown rice | Mortality of adults < 7%, progeny is reduced | Kavallieratos et al. [122] |
S-methoprene | R. dominica | Mixing treated and untreated wheat | Progeny depends on both the average dose and evenness of application | Daglish and Nayak [123] |
Spinosad | R. dominica, S. oryzae, L. paeta, L. bostrychophila, L. reticulatus | Layer, top, or portion treatment of wheat | Species dependent, mortality is high if insects moved through the treated wheat | Athanassiou et al. [124] |
Diatomaceous earth | C. ferrugineus; S. oryzae, O. surinamensis, R. dominica, T. castaneum | Different doses and different temperatures of wheat | Insect mobility and species dependent | Fields and Korunic [125] |
Methoprene | T.castaneum | Wheat treated at 0.001 to 0.0165 ppm | Progeny is reduced at 1600–5000 times lower than the label dosage | Wijayaratne [126] |
Elements of An IPM Approach | Required Knowledge of Insect Movement |
---|---|
(1) planning and managing storage ecosystems to prevent insect infestation | Movement ability of insects infesting the storage ecosystem |
(2) identifying pests and understanding their biology and ecology | Their mobility related to their population dynamics |
(3) monitoring populations of pests and storage environment | Relationship between mobility and the prediction of insect density and distribution |
(4) making control decisions based on the information collected | Unknown movement might result in a wrong decision or the decision cannot be made |
(5) reducing pest populations to acceptable levels | Movement will result in re-infestation and population fluctuation |
(6) evaluating effect and efficacy of IPM decisions | Unknown movement might result in a wrong evaluation or the evaluation cannot be made |
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Jian, F. Influences of Stored Product Insect Movements on Integrated Pest Management Decisions. Insects 2019, 10, 100. https://doi.org/10.3390/insects10040100
Jian F. Influences of Stored Product Insect Movements on Integrated Pest Management Decisions. Insects. 2019; 10(4):100. https://doi.org/10.3390/insects10040100
Chicago/Turabian StyleJian, Fuji. 2019. "Influences of Stored Product Insect Movements on Integrated Pest Management Decisions" Insects 10, no. 4: 100. https://doi.org/10.3390/insects10040100
APA StyleJian, F. (2019). Influences of Stored Product Insect Movements on Integrated Pest Management Decisions. Insects, 10(4), 100. https://doi.org/10.3390/insects10040100