The Prediction of Locusta migratoria (Linnaeus, 1758) Outbreak under Climate Change Scenario in Indonesia
Abstract
Locusta migratoria (Linnaeus, 1758) is one of the locusts known as important pests of food crops. Outbreaks of this species can cause catastrophic damage to maize, paddy, and many other crops. A species distribution model was used to identify the probability of the locust's current and future potential distribution in the Indonesian archipelago. The study relied on the machine learning method Maximum Entropy (Maxent) Model to forecast the future spread of the species in the Indonesian archipelago and to find the climate variable that influenced the distribution of Locusta migratoria. The results showed an Area Under Curve (AUC) value of 0.956 for the Locusta migratoria model, indicating a highly reliable model. The important variable for the distribution of this species was precipitation, especially during the dry season. A low amount of rainfall increases the possibility of the species existing and being distributed. Maxent prediction models showed the potential distribution in the southern part of the Indonesian archipelago under both middle and worst-case scenarios for 2070. This model can become one of the baselines for early warning systems, targeted monitoring and surveillance, and the use of specific pesticides or biological control agents to prevent or minimize the harm of Locusta migratoria outbreak to agricultural lands in the future.
References
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27. GBIF.org. GBIF Occurrence Download. 2022, (11 July 2022) https://doi.org/10.15468/dl.f5f4jj.
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29. Anderson, R.P.; Martínez-Meyer, E. Modeling species’ geographic distributions for preliminary conservation assessments: A.; implementation with the spiny pocket mice (Heteromys) of Ecuador. Biological Conservation. 2004, 116:167–179. https://doi.org/10.1016/S0006-3207(03)00187-3.
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36. Trumper, E.V.; Cease, A.J.; Cigliano, M.M.; et al. A Review of the biology, ecology, and management of the South American Locust, Schistocerca cancellata (Serville, 1838), and future prospects. Agronomy. 2022, 12:135. https://doi.org/10.3390/agronomy12010135.
37. Lu, E.; Zeng, X. Understanding different precipitation seasonality regimes from water vapor and temperature fields: Case studies. Geophysical Research Letters. 2005, 32:. https://doi.org/10.1029/2005GL024333.
38. Zhang, H.; Cheng, H.; Spötl, C.; et al. A 200-year annually laminated stalagmite record of precipitation seasonality in southeastern China and its linkages to ENSO and PDO. Sci Rep. 2018, 8:12344. https://doi.org/10.1038/s41598-018-30112-6.
39. Fohlmeister, J.; Voarintsoa, N.R.G.; Lechleitner. F.A.; et al. Main controls on the stable carbon isotope composition of speleothems. Geochimica et Cosmochimica Acta. 2020, 279:67–87. https://doi.org/10.1016/j.gca.2020.03.042.
40. Deka, B.; Baruah, C.; Babu, A. Entomopathogenic microorganisms: their role in insect pest management. Egyptian Journal of Biological Pest Control. 2021, 31:121. https://doi.org/10.1186/s41938-021-00466-7.
41. Muhammad, J.; Fathy, Z.; Moussa, S. Entomopathogenic bacteria Photorhabdus luminescens as natural enemy against the African migratory locust, Locusta migratoria migratorioides (Reiche & Fairmaire, 1849) (Orthoptera: Acrididae). Egyptian Journal of Biological Pest Control. 2022, 32:92. https://doi.org/10.1186/s41938-022-00592-w.
42. Wu, H.; Rozlomiy, N.G. Research of Beauveria bassianao the field control of Locusta migratoria manilensis Meyen. IOP Conf Ser: Earth Environ Sci. 2021, 692:042083. https://doi.org/10.1088/1755-1315/692/4/042083.
43. Lin, C.; Hu, Z.; Luo, Y.; et al. A New Solution Based on Locust Outbreak. ASLA 2021 Student Awards. 2021, https://www.asla.org/2021studentawards/3271.html. Accessed 9 Apr 2023.
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3. Pranita, E. What is migratory locust, a pest that terrorizes Sumbanese farmers in East Nusa Tenggara? KOMPAS.com. 2022, https://www.kompas.com/sains/read/2022/05/28/170000123/apa-itu-belalang-kembara-hama-yang-meneror-petani-sumba-ntt-. Accessed 8 Apr 2023.
4. Kanwil NTT. The Correctional Institution of Waingapu Participates in the Control of the Migratory Locust Pest in East Sumba. East Nusa Tenggara Regional Office, Ministry of Law and Human Rights of the Republic of Indonesia. 2023, https://ntt.kemenkumham.go.id/berita-kanwil/berita-upt/11780-lapas-waingapu-turut-ambil-bagian-pengendalian-hama-belalang-kembara-di-sumba-timur. Accessed 8 Apr 2023.
5. Lecoq M.; Sukirno. Drought and an exceptional outbreak of the Oriental Migratory Locust, Locusta migratoria manilensis (Meyen 1835) in Indonesia (Orthoptera: Acrididae). Journal of Orthoptera Research. 1999, 153–161. https://doi.org/10.2307/3503438.
6. Lassa, J. The return of locust outbreak in Sumba, Indonesia: a rapid situational analysis. Working Paper #17, Institute of Resource Governance and Social Change (IRGSC). 2017, http://dx.doi.org/10.13140/RG.2.2.26065.94563.
7. Lecoq, M.; Luong-Skovmand M.H.; Rachadi, T. General policy of locust management in Indonesia: Proposal for a long term program. Montpellier. 2020.
8. Dewantara, A.W.; Nurhayati, D.R.; Santosa, S.J. Study on the effects of different types of biological fertilizers on the intensity of locust damage on black corn plants. Innofarm: Jurnal Inovasi Pertanian. 2020, 22:29–35. https://doi.org/10.33061/innofarm.v22i1.3529.
9. Sudarsono, H.; Hasibuan, R.; Buchori. Biology and transformation of the migratory locust Locusta migratoria manilensis Meyen (orthoptera: acrididae) at several laboratory population density levels. Jurnal Hama dan Penyakit Tumbuhan Tropika. 2005, 5:24–31. https://doi.org/10.23960/j.hptt.1524-31.
10. Nik, N.; Rusae, A.; Atini, B. Identification of pests and bioinsecticide applications on locusts (Locusta migratoria L) as an integrated pest control model on sorghum. Savana Cendana. 2017, 2:46–47. https://doi.org/10.32938/sc.v2i03.165.
11. Wawo, Y.C.; Akbar, B.; Eting, M.A. The Effect of Different Volumes of Organic Insecticide from Mimba Leaves on the Mortality of Migratory Locusts. BIOS 3. 2018.
12. Tu, X.; Hu, G.; Fu, X.; et al. Mass windborne migrations extend the range of the migratory locust in East China. Agricultural and Forest Entomology. 2019, 22:41–49. https://doi.org/10.1111/afe.12359.
13. Zhao, L.; Guo, W.; Jiang, F.; et al. Phase-related differences in egg production of the migratory locust regulated by differential oosorption through microRNA-34 targeting activinβ. PLOS Genetics. 2021, 17: e1009174. https://doi.org/10.1371/journal.pgen.1009174.
14. Sudarsono, H.; Hasibuan, R.; Swibawa, I.G. Correlation between rainfall and migratory locust attack area (Locusta migratoria manilensis Meyen) in Lampung province. Jurnal Hama dan Penyakit Tumbuhan Tropika. 2011, 11:95–101. https://doi.org/10.23960/j.hptt.11195-101.
15. Sudarsono, H. Effect of dry period and rainfall intensity on emergence of the migratory locust (Locusta migratoria manilensis Meyen). Jurnal Hama dan Penyakit Tumbuhan Tropika. 2008, 8:117–122. https://doi.org/10.23960/j.hptt.28117-122.
16. Rohman, A.F.; Santosa, S.J.; Siswadi, S. Study of the types of manure fertilizers on the intensity of damage caused by the migratory locust pest (Locusta migratoria manilensis L.) on three types of corn (Zea mays ssp. mays). Innofarm: Jurnal Inovasi Pertanian. 2020, 22:73–78. https://doi.org/10.33061/innofarm.v22i2.3535.
17. Guo, J.; Zhao, L.; Huang, W; et al. Study on the forming mechanism of the high-density spot of locust coupled with habitat dynamic changes and meteorological conditions based on time-series remote sensing images. Agronomy. 2022, 12:1610. https://doi.org/10.3390/agronomy12071610.
18. Jyoti, B.; Shali, Y.; Zehua, Z.; et al. Population dynamics and life history of Locusta migratoria tibetensis Chen in Lhasa River. Pakistan Journal of Zoology. 2020, 52:927–936. https://doi.org/10.17582/journal.pjz/20181231071257.
19. Ramazi, P.; Kunegel-Lion, M.; Greiner, R.; Lewis, M.A. Predicting insect outbreaks using machine learning: A mountain pine beetle case study. Ecol Evol. 2021, 11:13014–13028. https://doi.org/10.1002/ece3.7921.
20. Elith, J.; Leathwick J.R. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time. Annual Review of Ecology, Evolution, and Systematics. 2009, 40:677–697. https://doi.org/10.1146/annurev.ecolsys.110308.120159.
21. O’Donnell, M.S.; Ignizio, D.A. Bioclimatic Predictors for Supporting Ecological Applications in the Conterminous United States. US Geological Survey Data Series. 2012, 691 10.
22. Phillips, S.J.; Anderson, R.P.; Schapire, R.E. Maximum entropy modeling of species geographic distributions. Ecological Modelling. 2006, 190:231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026.
23. Phillips, S.J.; Dudík, M. Modeling of species distribution with Maxent: new extensions and a comprehensive evalutation. Ecograpy. 2008, 31:161–175. https://doi.org/10.1111/j.2007.0906-7590.05203.x.
24. Taylor, K.E.; Stouffer, R.J.; Meehl, G.A. An Overview of CMIP5 and Experimental Design. Bulletin of the American Meteorological Society. 2012, 93:485–498. https://doi.org/10.1175/BAMS-D-11-00094.
25. Cabrera, J.S.; Lee, H.S. Flood risk assessment for Davao Oriental in the Philippines using geographic information system-based multi-criteria analysis and the maximum entropy model. Journal of Flood Risk Management. 2020, 13:1–17. https://doi.org/10.1111/jfr3.12607.
26. Saputra, M.H.; Lee, H.S. Evaluation of climate change impacts on the potential distribution of Styrax sumatrana in North Sumatra, Indonesia. Sustainability. 2021, 13:462. https://doi.org/10.3390/su13020462.
27. GBIF.org. GBIF Occurrence Download. 2022, (11 July 2022) https://doi.org/10.15468/dl.f5f4jj.
28. Lassa, J. The return of locust outbreak in Sumba, Indonesia: a rapid situational analysis. Working Paper #17, Institute of Resource Governance and Social Change (IRGSC). 2017, http://dx.doi.org/10.13140/RG.2.2.26065.94563.
29. Anderson, R.P.; Martínez-Meyer, E. Modeling species’ geographic distributions for preliminary conservation assessments: A.; implementation with the spiny pocket mice (Heteromys) of Ecuador. Biological Conservation. 2004, 116:167–179. https://doi.org/10.1016/S0006-3207(03)00187-3.
30. Miller, J. Species distribution modeling. Geography Compass. 2010, 4:490–509. https://doi.org/10.1111/j.1749-8198.2010.00351.x.
31. Austin, M. Species distribution models and ecological theory: A critical assessment and some possible new approaches. Ecological Modelling. 2007, 200:1–19. https://doi.org/10.1016/j.ecolmodel.2006.07.005.
32. Elith, J, Phillips, S.J.; Hastie, T.; et al. A statistical explanation of MaxEnt for ecologists: online appendices. Diversity and Distributions. 2011, 17:1–18.
33. Lecoq, M. Locusta migratoria (migratory locust). CABI Compendium CABI Compendium. 2023, https://doi.org/10.1079/cabicompendium.31151.
34. Sudarsono, H.; Hasibuan, R.; et al. (2005) Biology and transformation of the migratory locust Locusta migratoria manilensis Meyen (orthoptera: acrididae) at several laboratory population density levels. Jurnal Hama dan Penyakit Tumbuhan Tropika 5:24–31. https://doi.org/10.23960/j.hptt.1524-31.
35. Susanti, E.; Surmaini, E.; Estiningtyas, W. Climate Parameters as Indicators of Early Warning Attack on Pest and Diseases of Plant. Jurnal Sumberdaya Lahan. 2018, 12:59. https://doi.org/10.21082/jsdl.v12n1.2018.59-70.
36. Trumper, E.V.; Cease, A.J.; Cigliano, M.M.; et al. A Review of the biology, ecology, and management of the South American Locust, Schistocerca cancellata (Serville, 1838), and future prospects. Agronomy. 2022, 12:135. https://doi.org/10.3390/agronomy12010135.
37. Lu, E.; Zeng, X. Understanding different precipitation seasonality regimes from water vapor and temperature fields: Case studies. Geophysical Research Letters. 2005, 32:. https://doi.org/10.1029/2005GL024333.
38. Zhang, H.; Cheng, H.; Spötl, C.; et al. A 200-year annually laminated stalagmite record of precipitation seasonality in southeastern China and its linkages to ENSO and PDO. Sci Rep. 2018, 8:12344. https://doi.org/10.1038/s41598-018-30112-6.
39. Fohlmeister, J.; Voarintsoa, N.R.G.; Lechleitner. F.A.; et al. Main controls on the stable carbon isotope composition of speleothems. Geochimica et Cosmochimica Acta. 2020, 279:67–87. https://doi.org/10.1016/j.gca.2020.03.042.
40. Deka, B.; Baruah, C.; Babu, A. Entomopathogenic microorganisms: their role in insect pest management. Egyptian Journal of Biological Pest Control. 2021, 31:121. https://doi.org/10.1186/s41938-021-00466-7.
41. Muhammad, J.; Fathy, Z.; Moussa, S. Entomopathogenic bacteria Photorhabdus luminescens as natural enemy against the African migratory locust, Locusta migratoria migratorioides (Reiche & Fairmaire, 1849) (Orthoptera: Acrididae). Egyptian Journal of Biological Pest Control. 2022, 32:92. https://doi.org/10.1186/s41938-022-00592-w.
42. Wu, H.; Rozlomiy, N.G. Research of Beauveria bassianao the field control of Locusta migratoria manilensis Meyen. IOP Conf Ser: Earth Environ Sci. 2021, 692:042083. https://doi.org/10.1088/1755-1315/692/4/042083.
43. Lin, C.; Hu, Z.; Luo, Y.; et al. A New Solution Based on Locust Outbreak. ASLA 2021 Student Awards. 2021, https://www.asla.org/2021studentawards/3271.html. Accessed 9 Apr 2023.
Authors
[1]
SaputraM.H., Sutomo, PujionoE., Indra JanuarH., HadiyanY., HaniA., Erna Wati HadiE., KuswandiR., KurniawanH. and HumaidaN. 2024. The Prediction of Locusta migratoria (Linnaeus, 1758) Outbreak under Climate Change Scenario in Indonesia. Media Konservasi. 29, 4 (Nov. 2024), 583. DOI:https://doi.org/10.29244/medkon.29.4.583.
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