Desert Locust (Schistocerca gregaria) Invasion Risk and Vegetation Damage in a Key Upsurge Area
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Date
2023-03
Authors
Mongare, Raphael
Abdel-Rahman, Elfatih M.
Mudereri, Bester Tawona
Kimathi, Emily
Onywere, Simon
Tonnang, Henri E. Z.
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Abstract
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. 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. The current (2020) and two
future climatic scenarios for the shared socioeconomic pathways SSP2-4.5 and SSP5-8.5 from the
model for interdisciplinary research on climate (MIROC6) were utilized to predict the future potential
distribution of DLs for the year 2030 (average for 2021–2040). Using Turkana County as a case, the
NDVI analysis indicated the highest vegetation damage between May and July 2020. The MaxEnt
model produced an area under the curve (AUC) value of 0.87 and a true skill statistic (TSS) of 0.61,
while temperature seasonality (Bio4), mean diurnal range (Bio2), and precipitation of the warmest
quarter (Bio18) were the most important bioclimatic variables in predicting the DL invasion suitability.
Further analysis demonstrated that currently 27% of the total area in Turkana County is highly
suitable for DL invasion, and the habitat coverage is predicted to potentially decrease to 20% in the
future using the worst-case climate change scenario (SSP5-8.5). These results have demonstrated
the potential of remotely sensed data to pinpoint the magnitude and location of vegetation damage
caused by the DLs and the potential future risk of invasion in the region due to the available
favorable vegetational and climatic conditions. This study provides a scalable approach as well as
baseline information useful for surveillanc
Description
Article
Keywords
food security, insect pest upsurge, Kenya, MaxEnt, Sentinel-2, species distribution model, vegetation index
Citation
Mongare, R., Abdel-Rahman, E. M., Mudereri, B. T., Kimathi, E., Onywere, S., & Tonnang, H. E. (2023). Desert Locust (Schistocerca gregaria) Invasion Risk and Vegetation Damage in a Key Upsurge Area. Earth, 4(2), 187-208.