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Original Article Using Ecological Niche Modeling to Predict the Spatial Distribution of Anopheles Maculipennis S.L. and Culex T

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Original Article Using Ecological Niche Modeling to Predict the Spatial Distribution of Anopheles Maculipennis S.L. and Culex T J Arthropod-Borne Dis, June 2019, 13(2): 165–176 N Hesami et al.: Using Ecological Niche … Original Article Using Ecological Niche Modeling to Predict the Spatial Distribution of Anopheles maculipennis s.l. and Culex theileri (Diptera: Culicidae) in Central Iran Najmeh Hesami1; *Mohammad Reza Abai1; Hassan Vatandoost1,2; Mostafa Alizadeh3; Mahboubeh Fatemi1; Javad Ramazanpour3; *Ahmad Ali Hanafi-Bojd1,2 1Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran 2Department of Environmental Chemical Pollutants and Pesticides, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran 3Department of Communicable Diseases Control, Deputy for Health, Isfahan University of Medical Sci- ences, Isfahan, Iran (Received 30 May 2018; accepted 24 Apr 2019) Abstract Background: Mosquitoes are very important vectors of diseases to human. We aimed to establish the first spatial database on the mosquitoes of Isfahan Province, central Iran, and to predict the geographical distribution of species with medical importance. Methods: Mosquito larvae were collected from eight counties of Isfahan Province during 2014. Collected data were transferred to a database in ArcGIS and the distribution maps were created. MaxEnt model and jackknife analysis were used to predict the geographical distribution of two medical important species, and to find the effective varia- bles for each species. Results: Totally, 1143 larvae were collected including 6 species, Anopheles maculipennis s.l., An. superpictus s.l., An. marteri, Culex hortensis, Cx. theileri and Culiseta longiareolata. The area under curve in MaxEnt model was 0.951 and 0.873 rather 1 for An. maculipennis s.l. and Cx. theileri, respectively. Culex theileri had wider and more appropriate niches across the province, except for the eastern area. The environmental variable with highest gain was mean temperature of the wettest quarter for Cx. theileri and temperature seasonality for An. maculipennis. Culex theileri, An. maculipennis s.l. and An. superpictus, three important vectors of parasitic agents to humans, were collected in this study. Conclusion: The mosquito collected and mapped can be considered for transmission of malaria and filariasis in the region. Bearing in mind the results of niche modeling for vector species, more studies on vectorial capacity and re- sistance status to different insecticides of these species are recommended. Keywords: Culicidae; Spatial distribution; Culex theileri; Anopheles maculipennis s.l.; Ecological niche modeling Introduction Mosquitoes are one of the most important Phlebovirus) on the inland plateau of southern groups of medical arthropods and transmit ma- Africa (3). Dirofilariasis due to Dirofilaria im- laria, filariasis, different arboviruses and en- mitis and D. repens and setariasis have been cephalitis as well as annoyance due to their reported in current studies from some parts bites (1). A serological study in 1970s showed of Iran, while West Nile Virus is also detect- West Nile infection was relatively common ed in current studies from the birds, horse, hu- in Iran with a prevalence of 30%, while in- man and mosquitoes (4–14). This is in accord- fection with Sindbis virus was very rare (2). ance with the global trends of these diseases, Culex theileri is the principal epidemic vec- although both animal and human cases of tor of Rift Valley fever virus (Bunyaviridae: this disease are under estimated (15, 16). 165 * Corresponding authors: Dr Ahmad Ali Hanafi-Bojd, http://jad.tums.ac.ir Email: [email protected], Mr Mohammad Reza Published Online: June 24, 2019 Abai, Email: [email protected] J Arthropod-Borne Dis, June 2019, 13(2): 165–176 N Hesami et al.: Using Ecological Niche … Study on the mosquitoes of Iran has a long and Iran as well, accurate study on the ecol- history and is conducted on different aspects ogy and bionomics of mosquitoes are neces- such as fauna, distribution, parasitic infection, sary due to their important role in disease trans- resistance to insecticides and modeling distri- mission, especially arboviruses. Data collec- bution (5, 6, 17–20). Culex theileri is reported tion on their biodiversity, distribution and ecol- from 27 out of 31 provinces of Iran including ogy will provide guideline for appropriate vec- Ardabil, West Azarbaijan, East Azarbaijan, tor control. Bushehr, Charmahal and Bakhtiari, Fars, Gui- Geographic Information Systems (GIS) is lan, Hamadan, Hormozgan, Ilam, Isfahan, Ker- a rapidly growing technology that combines man, Kermanshah, South Khorassan, North graphics features with the environmental data Khorassan, Khorassan-e Razavi, Khuzestan, obtained from the vectors of disease. This Kohgiluyeh and Boyerahmad, Kordestan, ability helps us to assess the distribution and Lorestan, Markazi, Mazandaran, Qom, Sistan bioecology of vector species. In last two dec- and Baluchestan, Tehran, Yazd, and Zanjan ades using GIS in vector-borne diseases has (21). increased and a new field of investigation has Anopheles maculipennis s.l. is one of the been opened. Creating databases, mapping, main malaria vectors in its distribution areas spatial and statistical analysis of vector-borne including Iran (22). It is reported from 20 diseases are results of this new branch of sci- provinces of Iran including Ardabil, West ence (25). Azarbaijan, East Azarbaijan, Charmahal and This study aimed to establish the first Bakhtiari, Guilan, Golestan, Hamadan, Isfa- spatial database on the mosquitoes of Isfa- han, Kermanshah, Khorassan-e Razavi, North han Province and to predict the geographical Khorassan, Kohgiluyeh and Boyerahmad, Kor- distribution of medically important species. destan, Qazvin, Lorestan, Markazi, Mazanda- ran, Semnan, Tehran, and Zanjan (22). Materials and Methods Despite activities regarding mosquito con- trol in Iran, there is still the problem of pain- Study Area ful bites of these insects, especially in cen- The Isfahan Province covers an area of tral areas like Isfahan, Arak, Semnan, and approximately 107,027km2 and is situated in Tehran provinces. Due to the vital role of the center of Iran (Fig. 1). The province ex- health in development programs, and be- periences a moderate and dry climate, on the cause the study on ecology and bionomics of whole, ranging between 40.6 °C and 10.6 °C mosquitoes is one of the important indices on a cold day in the winter season. The av- that have a fundamental role in development erage annual temperature has been recorded of ecotourism industry, proper knowledge as 16.7 °C and the annual rainfall on an av- from behavioral characteristics and bionom- erage has been reported as 116.9mm. More ics of mosquitoes in different ecological con- than 5 million peoples are living in 24 coun- ditions is one of the main factors in planning ties of this province. Isfahan is destination of the strategy to combat the mosquitoes. Isfa- millions of tourists from different parts of han Province is one of the main poles for Iran and other countries. industry and tourism in Iran. Although rare studies have been done in past (23, 24), but Entomological Survey still there is no comprehensive survey on vec- Sampling was conducted two times dur- tor(s) bioecology in different climates, seasons, ing summer 2015 from 8 counties (Khomein- temperatures, and so on. With due attention ishahr, Golpayegan, Faridan, Khansar, Mo- to the extensive climate change in the world barakeh, Fereidoonshahr, Najafabad, Samirom) 166 http://jad.tums.ac.ir Published Online: June 24, 2019 J Arthropod-Borne Dis, June 2019, 13(2): 165–176 N Hesami et al.: Using Ecological Niche … in three main topographic areas of Isfahan Bio16 (Precipitation of wettest quarter (mm)), Province. Mosquito larvae were collected by Bio17 (Precipitation of driest quarter (mm)), the standard dipping method. Coordinates of Bio18 (Precipitation of warmest quarter (mm)) the collections sites were recorded using a and Bio19 (Precipitation of coldest quarter GPS device. Species were transferred to the (mm)). Two environmental variables were al- laboratory, mounted and identified morpho- so used for modeling i.e. altitude (m) and Nor- logically (26). malized Difference Vegetation Index (NDVI). All the mounted slides were deposited in The first variable was derived from the Digi- the Medical Entomology Museum, School tal Elevation Model (DEM) of Iran with the of Public Health, Tehran University of Med- same resolution, while NDVI was acquired ical Sciences under code of GC22ST11-94. from Aug 2014 image of MODIS satellite. Creating Database and Mapping Results All collected data obtained from this en- tomological survey were transferred to a rel- Species Composition evant database in ArcGIS and then the dis- Overall, 1143 mosquito larvae were col- tribution maps were created. lected including 6 species: Anopheles macu- Modeling lipennis s.l. (24), An. superpictus s.l. (4), An. MaxEnt model and bioclimatic variables marteri (10), Culex hortensis (454), Cx. theileri were used to predict and to map the geo- (429) and Culiseta longiareolata (222). The graphical distribution of medically important most and the least density was due to Cx. species which had enough occurrence data hortensis (39.72%) and An. superpictus s.l points (27). Jackknife test in MaxEnt model (0.35%), respectively (Table 1). Anopheles was used to find the effective variables for maculipennis s.l. was collected from both each species. The bioclimatic data were plain and foothill areas, but we could not downloaded from the worldclim database in find this malaria vectors in mountainous ar- 1km2 spatial resolution (version1.4, eas of Isfahan Province. Culex theileri and http://www.worldclim.org/past). They were in- Cx. hortensis were the most aboundant spe- cluded Bio1 (Annual mean temperature (oC), cies. Regardless of the topography of the area, Bio 2 (Mean diurnal range: mean of monthly they were caught in all the studied areas. (max temp–min temp) (°C)), Bio3 (Isother- mality: (Bio2/Bio7)× 100), Bio4 (Tempera- MaxEnt Modeling ture seasonality (SD× 100)), Bio5 (Maximum This method was used to find the appro- temperature of warmest month (°C)), Bio6 priate niches for Cx.
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