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On March 28, 2023 at 9:26:40 AM UTC, kennedysenagi:
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Uploaded a new file to resource Scripts in Desert Locust (Schistocerca gregaria) Invasion Risk and Vegetation Damage in a Key Upsurge Area
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f | 1 | { | f | 1 | { |
2 | "acknowledgement": "The authors gratefully acknowledge the financial | 2 | "acknowledgement": "The authors gratefully acknowledge the financial | ||
3 | support for this research by the following organizations and agencies: | 3 | support for this research by the following organizations and agencies: | ||
4 | the Swedish International Development Cooperation Agency (Sida); the | 4 | the Swedish International Development Cooperation Agency (Sida); the | ||
5 | Swiss Agency for Development and Cooperation (SDC); the Australian | 5 | Swiss Agency for Development and Cooperation (SDC); the Australian | ||
6 | Centre for International Agricultural Research (ACIAR); the Federal | 6 | Centre for International Agricultural Research (ACIAR); the Federal | ||
7 | Democratic Republic of Ethiopia; and the Government of the Republic of | 7 | Democratic Republic of Ethiopia; and the Government of the Republic of | ||
8 | Kenya. The views expressed herein do not necessarily reflect the | 8 | Kenya. The views expressed herein do not necessarily reflect the | ||
9 | official opinion of the donors.\u00a0\u00a0", | 9 | official opinion of the donors.\u00a0\u00a0", | ||
10 | "administrative_areas": "Turkana county", | 10 | "administrative_areas": "Turkana county", | ||
11 | "author": null, | 11 | "author": null, | ||
12 | "author_email": null, | 12 | "author_email": null, | ||
13 | "citation_narrative": "Mongare, R.; Abdel-Rahman, E.M.; Mudereri, | 13 | "citation_narrative": "Mongare, R.; Abdel-Rahman, E.M.; Mudereri, | ||
14 | B.T.; Kimathi, E.; Onywere, S.; Tonnang, H.E.Z. Desert Locust | 14 | B.T.; Kimathi, E.; Onywere, S.; Tonnang, H.E.Z. Desert Locust | ||
15 | (Schistocerca gregaria) Invasion Risk and Vegetation Damage in a Key | 15 | (Schistocerca gregaria) Invasion Risk and Vegetation Damage in a Key | ||
16 | Upsurge Area. Earth 2023", | 16 | Upsurge Area. Earth 2023", | ||
17 | "collaborators": "[{\"collaborator\": \"Raphael Mongare\"}, | 17 | "collaborators": "[{\"collaborator\": \"Raphael Mongare\"}, | ||
18 | {\"collaborator\": \"Elfatih M. Abdel-Rahman\"}, {\"collaborator\": | 18 | {\"collaborator\": \"Elfatih M. Abdel-Rahman\"}, {\"collaborator\": | ||
19 | \"Bester Tawona Mudereri\"}, {\"collaborator\": \"Emily Kimathi\"}, | 19 | \"Bester Tawona Mudereri\"}, {\"collaborator\": \"Emily Kimathi\"}, | ||
20 | {\"collaborator\": \"Simon Onywere\"}, {\"collaborator\": \"Henri E. | 20 | {\"collaborator\": \"Simon Onywere\"}, {\"collaborator\": \"Henri E. | ||
21 | Z. Tonnang\"}]", | 21 | Z. Tonnang\"}]", | ||
22 | "contact_person": "Elfatih Abdel-Rahman", | 22 | "contact_person": "Elfatih Abdel-Rahman", | ||
23 | "contact_person_email": "eabdel-rahman@icipe.org", | 23 | "contact_person_email": "eabdel-rahman@icipe.org", | ||
24 | "country": "[{\"country\": \"KE\"}]", | 24 | "country": "[{\"country\": \"KE\"}]", | ||
25 | "creator_user_id": "f09ec764-fe3c-4069-850b-f968ff0c20bb", | 25 | "creator_user_id": "f09ec764-fe3c-4069-850b-f968ff0c20bb", | ||
26 | "date_uploaded": "2023-03-28", | 26 | "date_uploaded": "2023-03-28", | ||
27 | "donor": "icipe", | 27 | "donor": "icipe", | ||
28 | "end_date": "2021-08-31", | 28 | "end_date": "2021-08-31", | ||
29 | "groups": [ | 29 | "groups": [ | ||
30 | { | 30 | { | ||
31 | "description": "", | 31 | "description": "", | ||
32 | "display_name": "Data Management, Modelling and | 32 | "display_name": "Data Management, Modelling and | ||
33 | Geo-Information", | 33 | Geo-Information", | ||
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35 | "image_display_url": | 35 | "image_display_url": | ||
36 | .icipe.org/dataportal/uploads/group/2022-05-17-140047.712089dmmg.jpg", | 36 | .icipe.org/dataportal/uploads/group/2022-05-17-140047.712089dmmg.jpg", | ||
37 | "name": "data-management-modelling-and-geo-information", | 37 | "name": "data-management-modelling-and-geo-information", | ||
38 | "title": "Data Management, Modelling and Geo-Information" | 38 | "title": "Data Management, Modelling and Geo-Information" | ||
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42 | "isopen": false, | 42 | "isopen": false, | ||
43 | "license_id": "cc-nc", | 43 | "license_id": "cc-nc", | ||
44 | "license_title": "Creative Commons Non-Commercial (Any)", | 44 | "license_title": "Creative Commons Non-Commercial (Any)", | ||
45 | "license_url": "http://creativecommons.org/licenses/by-nc/2.0/", | 45 | "license_url": "http://creativecommons.org/licenses/by-nc/2.0/", | ||
46 | "maintainer": "Kennedy Senagi", | 46 | "maintainer": "Kennedy Senagi", | ||
47 | "maintainer_email": "ksenagi@icipe.org", | 47 | "maintainer_email": "ksenagi@icipe.org", | ||
48 | "metadata_created": "2023-03-27T10:59:12.922326", | 48 | "metadata_created": "2023-03-27T10:59:12.922326", | ||
n | 49 | "metadata_modified": "2023-03-28T09:19:16.961389", | n | 49 | "metadata_modified": "2023-03-28T09:26:39.860025", |
50 | "name": | 50 | "name": | ||
51 | esert-locust-invasion-risk-and-vegetation-damage-in-key-upsurge-area", | 51 | esert-locust-invasion-risk-and-vegetation-damage-in-key-upsurge-area", | ||
52 | "notes": "In the recent past, the Horn of Africa witnessed an | 52 | "notes": "In the recent past, the Horn of Africa witnessed an | ||
53 | upsurge in the desert locust (Schistocerca gregaria) invasion. This | 53 | upsurge in the desert locust (Schistocerca gregaria) invasion. This | ||
54 | has raised major concerns over the massive food insecurity, | 54 | has raised major concerns over the massive food insecurity, | ||
55 | socioeconomic impacts, and livelihood losses caused by these recurring | 55 | socioeconomic impacts, and livelihood losses caused by these recurring | ||
56 | invasions. This study determined the potential vegetation damage due | 56 | invasions. This study determined the potential vegetation damage due | ||
57 | to desert locusts (DLs) and predicted the suitable habitat at high | 57 | to desert locusts (DLs) and predicted the suitable habitat at high | ||
58 | risk of invasion by the DLs using current and future climate change | 58 | risk of invasion by the DLs using current and future climate change | ||
59 | scenarios in Kenya. The normalized difference vegetation index (NDVI) | 59 | scenarios in Kenya. The normalized difference vegetation index (NDVI) | ||
60 | for the period 2018\u20132020 was computed using multi-date Sentinel-2 | 60 | for the period 2018\u20132020 was computed using multi-date Sentinel-2 | ||
61 | imagery in the Google Earth Engine platform. This was performed to | 61 | imagery in the Google Earth Engine platform. This was performed to | ||
62 | assess the vegetation changes that occurred between May and July of | 62 | assess the vegetation changes that occurred between May and July of | ||
63 | the year 2020 when northern Kenya was the hotspot of the DL upsurge. | 63 | the year 2020 when northern Kenya was the hotspot of the DL upsurge. | ||
64 | The maximum entropy (MaxEnt) algorithm was used together with 646 DL | 64 | The maximum entropy (MaxEnt) algorithm was used together with 646 DL | ||
65 | occurrence records and six bioclimatic variables to predict DL habitat | 65 | occurrence records and six bioclimatic variables to predict DL habitat | ||
66 | suitability. The current (2020) and two future climatic scenarios for | 66 | suitability. The current (2020) and two future climatic scenarios for | ||
67 | the shared socioeconomic pathways SSP2-4.5 and SSP5-8.5 from the model | 67 | the shared socioeconomic pathways SSP2-4.5 and SSP5-8.5 from the model | ||
68 | for interdisciplinary research on climate (MIROC6) were utilized to | 68 | for interdisciplinary research on climate (MIROC6) were utilized to | ||
69 | predict the future potential distribution of DLs for the year 2030 | 69 | predict the future potential distribution of DLs for the year 2030 | ||
70 | (average for 2021\u20132040). Using Turkana County as a case, the NDVI | 70 | (average for 2021\u20132040). Using Turkana County as a case, the NDVI | ||
71 | analysis indicated the highest vegetation damage between May and July | 71 | analysis indicated the highest vegetation damage between May and July | ||
72 | 2020. The MaxEnt model produced an area under the curve (AUC) value of | 72 | 2020. The MaxEnt model produced an area under the curve (AUC) value of | ||
73 | 0.87 and a true skill statistic (TSS) of 0.61, while temperature | 73 | 0.87 and a true skill statistic (TSS) of 0.61, while temperature | ||
74 | seasonality (Bio4), mean diurnal range (Bio2), and precipitation of | 74 | seasonality (Bio4), mean diurnal range (Bio2), and precipitation of | ||
75 | the warmest quarter (Bio18) were the most important bioclimatic | 75 | the warmest quarter (Bio18) were the most important bioclimatic | ||
76 | variables in predicting the DL invasion suitability. Further analysis | 76 | variables in predicting the DL invasion suitability. Further analysis | ||
77 | demonstrated that currently 27% of the total area in Turkana County is | 77 | demonstrated that currently 27% of the total area in Turkana County is | ||
78 | highly suitable for DL invasion, and the habitat coverage is predicted | 78 | highly suitable for DL invasion, and the habitat coverage is predicted | ||
79 | to potentially decrease to 20% in the future using the worst-case | 79 | to potentially decrease to 20% in the future using the worst-case | ||
80 | climate change scenario (SSP5-8.5). These results have demonstrated | 80 | climate change scenario (SSP5-8.5). These results have demonstrated | ||
81 | the potential of remotely sensed data to pinpoint the magnitude and | 81 | the potential of remotely sensed data to pinpoint the magnitude and | ||
82 | location of vegetation damage caused by the DLs and the potential | 82 | location of vegetation damage caused by the DLs and the potential | ||
83 | future risk of invasion in the region due to the available favorable | 83 | future risk of invasion in the region due to the available favorable | ||
84 | vegetational and climatic conditions. This study provides a scalable | 84 | vegetational and climatic conditions. This study provides a scalable | ||
85 | approach as well as baseline information useful for surveillance, | 85 | approach as well as baseline information useful for surveillance, | ||
86 | development of control programs, and monitoring of DL invasions at | 86 | development of control programs, and monitoring of DL invasions at | ||
87 | local and regional scales.", | 87 | local and regional scales.", | ||
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243 | }, | 243 | }, | ||
244 | { | 244 | { | ||
245 | "display_name": "insect pest upsurge", | 245 | "display_name": "insect pest upsurge", | ||
246 | "id": "c333f254-1978-4b99-a99f-665b69f2267d", | 246 | "id": "c333f254-1978-4b99-a99f-665b69f2267d", | ||
247 | "name": "insect pest upsurge", | 247 | "name": "insect pest upsurge", | ||
248 | "state": "active", | 248 | "state": "active", | ||
249 | "vocabulary_id": null | 249 | "vocabulary_id": null | ||
250 | }, | 250 | }, | ||
251 | { | 251 | { | ||
252 | "display_name": "species distribution model", | 252 | "display_name": "species distribution model", | ||
253 | "id": "b5ef492c-b6c6-48ab-93d1-5bf562e5b45f", | 253 | "id": "b5ef492c-b6c6-48ab-93d1-5bf562e5b45f", | ||
254 | "name": "species distribution model", | 254 | "name": "species distribution model", | ||
255 | "state": "active", | 255 | "state": "active", | ||
256 | "vocabulary_id": null | 256 | "vocabulary_id": null | ||
257 | }, | 257 | }, | ||
258 | { | 258 | { | ||
259 | "display_name": "vegetation index", | 259 | "display_name": "vegetation index", | ||
260 | "id": "d1d49155-af99-46af-8d2d-534c477aa513", | 260 | "id": "d1d49155-af99-46af-8d2d-534c477aa513", | ||
261 | "name": "vegetation index", | 261 | "name": "vegetation index", | ||
262 | "state": "active", | 262 | "state": "active", | ||
263 | "vocabulary_id": null | 263 | "vocabulary_id": null | ||
264 | } | 264 | } | ||
265 | ], | 265 | ], | ||
266 | "third_party": "yes", | 266 | "third_party": "yes", | ||
267 | "title": "Desert Locust (Schistocerca gregaria) Invasion Risk and | 267 | "title": "Desert Locust (Schistocerca gregaria) Invasion Risk and | ||
268 | Vegetation Damage in a Key Upsurge Area", | 268 | Vegetation Damage in a Key Upsurge Area", | ||
269 | "type": "dataset", | 269 | "type": "dataset", | ||
270 | "url": null, | 270 | "url": null, | ||
271 | "version": null | 271 | "version": null | ||
272 | } | 272 | } |