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Species presence data, land use\/landcover, elevation, slope and 19 bioclimatic variables were used to model current and future distribution of <jats:italic>H. dromedarii<\/jats:italic> 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 \u2013 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 CO<jats:sub>2<\/jats:sub> 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.<\/jats:p>","DOI":"10.1017\/s0031182024001161","type":"journal-article","created":{"date-parts":[[2024,12,19]],"date-time":"2024-12-19T07:10:10Z","timestamp":1734592210000},"page":"1024-1034","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":8,"title":["Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling"],"prefix":"10.1017","volume":"151","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9292-8679","authenticated-orcid":false,"given":"Nighat","family":"Perveen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9195-1677","authenticated-orcid":false,"given":"Sabir 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\u00a9 The Author(s), 2024. 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