Locust Distribution and Reproduction : A Part from the Book Chapter : Simulation of Favourable Habitats and Potential Spread for Non-gregarious Locust Pests for Preventive Measures in North Kazakhstan Based on Satellite Data

Meanwhile, there are differences between the SDM and ENM approaches. SDMs often associate known cases of species occurrence with certain environmental conditions characteristic of the sites where they were recorded to predict the possible places where populations could persist within the landscape; thus, only the main key parameters of environmental variables are required for simulation. According to the ENM concept, the resistance of species to certain environmental factors limits their stability in the landscape and an extensive database of environmental variables is required for simulation.

Both SDM and ENM approaches are trending in modern science. They are performed using geographical information system (GIS) technology products, such as the MAXENT software. With the help of this simulation, it becomes possible to obtain information on the potential locust distribution and reproduction sites on digital maps of the studied territory, where monitoring and protective measures should be directed first. If this provision finds its application in the practice of phytosanitary monitoring, then it can be a good alternative tool for the basic logical model of pest forecasting, which is currently used by phytosanitary diagnostics and forecast services.

Author(s) Details:

Kurmet Baibussenov
S. Seifullin Kazakh Agro Technical University, 62 Zhenis Ave., 010011, Nur-Sultan, Republic of Kazakhstan. 

Aigul Bekbayeva
S. Seifullin Kazakh Agro Technical University, 62 Zhenis Ave., 010011, Nur-Sultan, Republic of
Kazakhstan

Valery Azhbenov
Zh. Zhyembaev Kazakh Scientific Research Institute of Plant Protection and Quarantine, 1 Kultobe
Str., 050000, Almaty, Republic of Kazakhstan.


Also See : SPCSV is Transmitted by the Whitefly Especially Bemisia Tabaci: A Part from The Book Chapter: Management of Sweet Potato Virus Disease Using Prophylactic Measure Strategy


Recent Global Research Developments in Enhancing Locust Monitoring with GIS and Remote Sensing

Remote Sensing and GIS Concepts:

  • Locust Outbreaks: Locust outbreaks occur globally, affecting livelihoods and food security. Traditional ground surveys struggle to cover large areas efficiently.
  • Geospatial Technologies: Remote sensing and associated geospatial tools provide timely data for assessing locust risk.
  • Untapped Potential: While some locust species (such as Desert, Migratory, and Australian Plague locusts) have been monitored using remotely sensed data, there’s untapped potential for other locusts [1].

Applications of Remote Sensing:

  • Habitat Monitoring: Remotely sensed data help monitor locust habitats. Satellite imagery provides insights into vegetation, land cover, and environmental conditions.
  • Risk Assessment: Geospatial tools assess the risk of impending locust outbreaks. This information guides targeted preventive management actions in breeding areas [1].

Recent Research:

  • A review paper summarizes remote sensing-based studies for locust management over the past four decades. Progress has been made, but gaps remain for further research.
  • Open-access remote sensing data archives and cloud computing offer unprecedented opportunities for locust research.
  • Unmanned aerial vehicle (UAV) systems enhance faster and more effective locust control [2,3].

References

  1. Latchininsky, A.V., Sivanpillai, R. (2010). Locust Habitat Monitoring and Risk Assessment Using Remote Sensing and GIS Technologies. In: Ciancio, A., Mukerji, K. (eds) Integrated Management of Arthropod Pests and Insect Borne Diseases. Integrated Management of Plant Pests and Diseases, vol 5. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8606-8_7
  2. Klein, I., Oppelt, N., & Kuenzer, C. (2021). Application of remote sensing data for locust research and management—a review. Insects, 12(3), 233.
  3. Klein I, Oppelt N, Kuenzer C. Application of Remote Sensing Data for Locust Research and Management—A Review. Insects. 2021; 12(3):233. https://doi.org/10.3390/insects12030233

To Read the Complete Chapter See Here

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