{
  "id": "AIBD-0194",
  "title": "icipe MaxEnt model maps desert locust breeding regions in East Africa with mean AUC up to 0.887",
  "summary": "Peer-reviewed MaxEnt model trained on 5,406 FAO breeding records (1985–2020) projected breeding suitability for Kenya, Uganda, South Sudan and Sudan; no operational outcome reported.",
  "date_observed": "2020-07-20",
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  "account": "Researchers at the International Center of Insect Physiology and Ecology (icipe) used MaxEnt to predict desert locust breeding regions. The paper describes MaxEnt as a machine learning algorithm. Co-authors came from the Desert Locust Control Organization for Eastern Africa, Kenya's Plant Protection Services and FAO (Keith Cressman). Of 9,134 records accessed from FAO and the Moroccan anti-locust center, 5,406 breeding sites from Morocco (367), Mauritania (2,661) and Saudi Arabia (1,703) were used. They date from 1985–2020, with a 70/30 training-test split. The Mauritania model had the highest mean AUC (0.887), followed by Saudi Arabia (0.884) and Morocco (0.820). The models were projected to potential oviposition and breeding areas in Kenya, Uganda, South Sudan and Sudan. The authors thank DLCO-EA and Kenya's Ministry of Agriculture for field data. The paper does not report use of the predictions in control operations.",
  "category": "general benefit",
  "unexpected": false,
  "purpose": "Predict regions suitable for desert locust breeding so that preventive control can be targeted before hoppers cause damage.",
  "system": "MaxEnt ecological-niche model of desert locust breeding (Kimathi et al.)",
  "model_version": "Maxent software, Version 3.4.1 (printed in the reference list as 'Version 3.4. 1')",
  "developer": "International Center of Insect Physiology and Ecology (icipe) with DLCO-EA, Kenya Plant Protection Services and FAO co-authors",
  "deployer": "None documented (research model)",
  "location": null,
  "domain": "Agriculture / pest forecasting",
  "segment": "Desert locust early warning",
  "benefit_type": "Improved Knowledge Discovery",
  "taxonomy_note": null,
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    {
      "kind": "peer-reviewed study",
      "citation": "Kimathi E, Tonnang HEZ, Subramanian S, Cressman K, Abdel-Rahman EM, Tesfayohannes M, Niassy S, Torto B, Dubois T, Tanga CM, Kassie M, Ekesi S, Mwangi D, Kelemu S. Prediction of breeding regions for the desert locust Schistocerca gregaria in East Africa. Scientific Reports 10:11937 (2020). doi:10.1038/s41598-020-68895-2",
      "title": "Prediction of breeding regions for the desert locust Schistocerca gregaria in East Africa",
      "url": "https://doi.org/10.1038/s41598-020-68895-2",
      "date": "2020-07-20",
      "written_by": "makers",
      "quote": "The model generated from Mauritania had the highest mean AUC value (0.887), followed by the models from Saudi Arabia (0.884), and Morocco (0.820)."
    }
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  "replication": {
    "produced_by": [
      "FAO and Moroccan breeding-site time series 1985–2020",
      "Bioclimatic covariates and NOAA CPC soil moisture data",
      "A 70/30 cross-validation split"
    ],
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      "Environmental drivers in the East African projection area comparable to the training countries"
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  "developer_country": "Kenya",
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      "date": "2026-10-21",
      "change": "Added the model version from the cited sources.",
      "source": "https://www.nature.com/articles/s41598-020-68895-2",
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      "change": "Country of the developer added from the organization's own site or a registry.",
      "source": "https://en.wikipedia.org/wiki/International_Centre_of_Insect_Physiology_and_Ecology",
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