Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling
Ticks are important vectors and reservoirs of pathogens causing zoonotic diseases in camels and other livestock, rodents and other small mammals, birds and humans. Hyalomma dromedarii is the most abundant tick species in Saudi Arabia and United Arab Emirates (UAE) affecting primarily camels, and to...
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Cambridge University Press
2024-08-01
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| Series: | Parasitology |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S0031182024001161/type/journal_article |
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| author | Nighat Perveen Sabir B. Muzaffar Areej Jaradat Olivier A. Sparagano Arve L. Willingham Ala Tabor |
| author_facet | Nighat Perveen Sabir B. Muzaffar Areej Jaradat Olivier A. Sparagano Arve L. Willingham Ala Tabor |
| author_sort | Nighat Perveen |
| collection | DOAJ |
| description | Ticks are important vectors and reservoirs of pathogens causing zoonotic diseases in camels and other livestock, rodents and other small mammals, birds and humans. Hyalomma dromedarii is the most abundant tick species in Saudi Arabia and United Arab Emirates (UAE) affecting primarily camels, and to a lesser extent, other livestock. Species presence data, land use/landcover, elevation, slope and 19 bioclimatic variables were used to model current and future distribution of H. dromedarii ticks using maximum entropy species distribution modelling (MaxEnt.). The model highlighted areas in the northern, eastern and southwestern parts of the study area as highly suitable for ticks. Several variables including land use/land cover (LULC) (53.1%), precipitation of coldest quarter (Bio19) (21.8%), elevation (20.6%), isothermality (Bio3) (1.9%), mean diurnal range [mean of monthly (max temp – min temp)] (Bio2) (1.8%), slope (0.5%), precipitation, seasonality (Bio15) (0.2%) influenced habitat suitability of ticks, predicting high tick density or abundance. Middle of the road scenario (ssp2-4.5) where CO2 levels remain similar to current levels, did not indicate a major change in the tick distributions. This tick distribution model could be used for targeting surveillance efforts and increasing the efficiency and accuracy of public health investigations and vector control strategies. |
| format | Article |
| id | doaj-art-822939e20deb4e609817defa0f368080 |
| institution | Kabale University |
| issn | 0031-1820 1469-8161 |
| language | English |
| publishDate | 2024-08-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Parasitology |
| spelling | doaj-art-822939e20deb4e609817defa0f3680802025-01-23T07:11:40ZengCambridge University PressParasitology0031-18201469-81612024-08-011511024103410.1017/S0031182024001161Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modellingNighat Perveen0https://orcid.org/0000-0002-9292-8679Sabir B. Muzaffar1https://orcid.org/0000-0001-9195-1677Areej Jaradat2https://orcid.org/0000-0001-7454-5917Olivier A. Sparagano3https://orcid.org/0000-0003-3141-310XArve L. Willingham4https://orcid.org/0000-0002-4168-2779Ala TaborDepartment of Biology, College of Science, United Arab Emirates University, Al-Ain, UAE Department of Veterinary Medicine, College of Agriculture and Veterinary Medicine, United Arab Emirates University, Al-Ain, UAEDepartment of Biology, College of Science, United Arab Emirates University, Al-Ain, UAE Department of Science, The Natural History Museum, London, UKDepartment of Biology, College of Science, United Arab Emirates University, Al-Ain, UAEAgricultural Sciences and Practice, Royal Agricultural University, Cirencester, UK Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong SAR, ChinaDepartment of Veterinary Medicine, College of Agriculture and Veterinary Medicine, United Arab Emirates University, Al-Ain, UAETicks are important vectors and reservoirs of pathogens causing zoonotic diseases in camels and other livestock, rodents and other small mammals, birds and humans. Hyalomma dromedarii is the most abundant tick species in Saudi Arabia and United Arab Emirates (UAE) affecting primarily camels, and to a lesser extent, other livestock. Species presence data, land use/landcover, elevation, slope and 19 bioclimatic variables were used to model current and future distribution of H. dromedarii ticks using maximum entropy species distribution modelling (MaxEnt.). The model highlighted areas in the northern, eastern and southwestern parts of the study area as highly suitable for ticks. Several variables including land use/land cover (LULC) (53.1%), precipitation of coldest quarter (Bio19) (21.8%), elevation (20.6%), isothermality (Bio3) (1.9%), mean diurnal range [mean of monthly (max temp – min temp)] (Bio2) (1.8%), slope (0.5%), precipitation, seasonality (Bio15) (0.2%) influenced habitat suitability of ticks, predicting high tick density or abundance. Middle of the road scenario (ssp2-4.5) where CO2 levels remain similar to current levels, did not indicate a major change in the tick distributions. This tick distribution model could be used for targeting surveillance efforts and increasing the efficiency and accuracy of public health investigations and vector control strategies.https://www.cambridge.org/core/product/identifier/S0031182024001161/type/journal_articlecamel tickHyalomma dromedariiMaxEntmodellingSaudi Arabiaspecies distributionUAE |
| spellingShingle | Nighat Perveen Sabir B. Muzaffar Areej Jaradat Olivier A. Sparagano Arve L. Willingham Ala Tabor Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling Parasitology camel tick Hyalomma dromedarii MaxEnt modelling Saudi Arabia species distribution UAE |
| title | Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling |
| title_full | Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling |
| title_fullStr | Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling |
| title_full_unstemmed | Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling |
| title_short | Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling |
| title_sort | camel tick species distribution in saudi arabia and united arab emirates using maxent modelling |
| topic | camel tick Hyalomma dromedarii MaxEnt modelling Saudi Arabia species distribution UAE |
| url | https://www.cambridge.org/core/product/identifier/S0031182024001161/type/journal_article |
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