Desert Locust (Schistocerca gregaria) Invasion Risk and Vegetation Damage in a Key Upsurge Area

Occurrence
Latest version published by International Centre for Insect Physiology and Ecology on Oct 9, 2023 International Centre for Insect Physiology and Ecology
Home:
https://dmmg.icipe.org/dataportal/dataset/desert-locust-invasion-risk-and-vegetation-damage-in-key-upsurge-area
Publication date:
9 October 2023
License:
CC-BY 4.0

Download the latest version of this resource data as a Darwin Core Archive (DwC-A) or the resource metadata as EML or RTF:

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Description

In the recent past, the Horn of Africa witnessed an upsurge in the desert locust (Schistocerca gregaria) invasion. This has raised major concerns over the massive food insecurity, socioeconomic impacts, and livelihood losses caused by these recurring invasions. This study determined the potential vegetation damage due to desert locusts (DLs) and predicted the suitable habitat at high risk of invasion by the DLs using current and future climate change scenarios in Kenya.

Data Records

The data in this occurrence resource has been published as a Darwin Core Archive (DwC-A), which is a standardized format for sharing biodiversity data as a set of one or more data tables. The core data table contains 646 records.

This IPT archives the data and thus serves as the data repository. The data and resource metadata are available for download in the downloads section. The versions table lists other versions of the resource that have been made publicly available and allows tracking changes made to the resource over time.

Versions

The table below shows only published versions of the resource that are publicly accessible.

How to cite

Researchers should cite this work as follows:

Senagi K (2023). Desert Locust (Schistocerca gregaria) Invasion Risk and Vegetation Damage in a Key Upsurge Area. Version 2.0. International Centre for Insect Physiology and Ecology. Occurrence dataset. https://doi.org/10.60798/yebfgo

Rights

Researchers should respect the following rights statement:

The publisher and rights holder of this work is International Centre for Insect Physiology and Ecology. This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.

GBIF Registration

This resource has been registered with GBIF, and assigned the following GBIF UUID: 6ac75bd0-8d64-4bc2-b4a6-a1b289a7294d.  International Centre for Insect Physiology and Ecology publishes this resource, and is itself registered in GBIF as a data publisher endorsed by International Centre for Insect Physiology and Ecology.

Keywords

food security; insect pest upsurge; Kenya; MaxEnt; Sentinel-2; species distribution model; vegetation index

Contacts

Kennedy Senagi
  • Metadata Provider ●
  • Originator ●
  • Point Of Contact
  • Data Manager
icipe
KE

Geographic Coverage

Turkana County, northwestern Kenya

Bounding Coordinates South West [-4.215, 7.031], North East [63.549, 60.469]

Taxonomic Coverage

Desert locust

Species Schistocerca gregaria (desert locus)

Temporal Coverage

Start Date / End Date 2020-02-01 / 2020-08-31

Project Data

No Description available

Title Desert Locust (Schistocerca gregaria) Invasion Risk and Vegetation Damage in a Key Upsurge Area
Identifier https://doi.org/10.3390/earth4020010

Sampling Methods

Freely available data on DL occurrence were acquired from the FAO DL hub (https://locust-hub-hqfao.hub.arcgis.com, accessed on 10 June 2021). The DL occurrence data that were collected between 1 February and 31 August 2020 were used.

Study Extent This study was conducted in Turkana County (Figure 1), a semi-arid region in northwestern Kenya covering approximately 68,232.9 km2 with a population of 926,976 people and an annual population growth rate of 0.81% [32]. Turkana lies between latitudes of 1°30′00″ N and 5°30′00″ N and longitudes of 34°30′00″ E and 36°40′00″ E.

Method step description:

  1. The normalized difference vegetation index (NDVI) for the period 2018–2020 was computed using multi-date Sentinel-2 imagery in the Google Earth Engine platform. This was performed to assess the vegetation changes that occurred between May and July of the year 2020 when northern Kenya was the hotspot of the DL upsurge. The maximum entropy (MaxEnt) algorithm was used together with 646 DL occurrence records and six bioclimatic variables to predict DL habitat suitability.

Bibliographic Citations

  1. Mongare R, Abdel-Rahman EM, Mudereri BT, Kimathi E, Onywere S, Tonnang HEZ. Desert Locust (Schistocerca gregaria) Invasion Risk and Vegetation Damage in a Key Upsurge Area. Earth. 2023; 4(2):187-208. https://doi.org/10.3390/earth4020010 https://doi.org/10.3390/earth4020010