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Study of Abiotic and Biotic Parameters Affecting the Abundance of Mosquito Larvae (Diptera: Culicidae) in the Region of Fez (Morocco)

Study of Abiotic and Biotic Parameters Affecting the Abundance of Mosquito Larvae (Diptera:... Hindawi International Journal of Zoology Volume 2020, Article ID 5429472, 7 pages https://doi.org/10.1155/2020/5429472 Research Article Study of Abiotic and Biotic Parameters Affecting the Abundance of Mosquito Larvae (Diptera: Culicidae) in the Region of Fez (Morocco) 1 1,2 3 Touria Filali Mouatassem, Abdelhakim El Ouali Lalami , Chafika Faraj, 4 1 Noureddine Rais, and Raja Guemmouh Laboratory of Biotechnology and Preservation of Natural Resources, Sidi Mohamed Ben Abdellah University, Faculty of Sciences Dhar El Mahraz, Fez 30000, Morocco Higher Institute of Nursing Professions and Health Techniques of Fez, Regional Health Directorate, El Ghassani Hospital, Fez 30000, Morocco Laboratory of Medical Entomology, National Hygiene Institute, Rabat 11400, Morocco Laboratory of Computer Science, Modelling and Systems, Sidi Mohamed Ben Abdellah University, Faculty of Sciences Dhar Mahraz, Fez 30000, Morocco Correspondence should be addressed to Abdelhakim El Ouali Lalami; eloualilalami@yahoo.fr Received 25 March 2020; Revised 24 June 2020; Accepted 6 July 2020; Published 27 July 2020 Academic Editor: Joao Pedro Barreiros Copyright © 2020 Touria Filali Mouatassem et al. ,is is an open access article distributed under the Creative Commons AttributionLicense,whichpermitsunrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalworkis properly cited. Mosquitoes cause significant human health issues. However, very few studies have attempted to examine the question of how abiotic and biotic factors affect the abundance of Culicidae in the larval habitat. ,e objective of this study was to analyze the influenceofbioticandabioticfactorsontheincreaseofthemostcommonmosquitospeciesintheFezregion(CentralMorocco). Larvaemosquitoesweresampledbystandarddippingtechniqueinfourdifferenttypesofmacrohabitats,betweenNovember2015 and November 2016. Each mosquito specimen was morphologically identified by the Moroccan Culicidae key and the Brunhes key. ,e analysis was done using R analysis software. We collected a total of 772 mosquito larvae belonging to nine different species, five of which are considered of medical interest. Culex pipiens (Linnaeus, 1758), known as the major vector in the transmission of West Nile virus fever (WNV), was the most common species of all mosquito larvae collected. ,e results of Poissonregressionanalysisshowedthatfactorssuchasthepresenceofgreenfilamentousalgae,vegetationcover,anddebriswere foundtobepositivelysignificantinthedistributionofthegenus Culex.However,therewasinsufficientevidencetodeterminethe parameters that are capable of estimating the abundance of Anopheles. ,e findings have also estimated that biotic and abiotic factors can lead to significant variation in the abundance of Culex perexiguus (,eobald, 1903), Culex theileri (,eobald, 1903), and Culex pipiens(Linnaeus,1758).Identifyingthepriorityparametersgoverningtheproliferationofmosquitoesintheregionof Fez can be one of the key elements for better vector control. turbidity, algal cover and stability of the habitat [3]; these 1. Introduction factors can lead to determining the density, size and vector Mosquitoes infect humans and other vertebrates. ,eir competence [3]. Surveying biotic and abiotic factors for distribution is to a large extent influenced by climatic various mosquito fauna make it easier to monitor the po- conditions and species habits across the globe [1]. Inter- tential modifications of larval habitats affected by rains, actions between biotic and abiotic factors can conduct to global climate change, and man-made activities [4–6]. significant variation in the reproductive landscape of insects In Morocco, many species of Culicidae family have been [2]. ,ey differ in their preference for the type, size, reportedasimportantvectorsofinfectiousdiseases,includingthe 2 International Journal of Zoology presence of the major vectors of malaria (Anopheles labranchiae of longitude. It is one of the most polluted rivers in the and Anopheles sergentii (,eobald, 1907)) [7, 8], the Aedes region and contains pollutants from various sources such as albopictus, responsible for the transmission of dengue, chi- sewage, fertilizers from agricultural fields, and industrial kungunya, and Zika viruses [9], and Culex pipiens, the potential waste. vectorofbothWestNilevirus[10]andRiftValleyfevervirus[11]. Antecedent studies on larval breeding sites have been a 2.2. Larval Habitat Characterization. ,e weather and the valuable source of information regarding the larval biology characteristics of the macrohabitats were recorded, in- and ecology of different mosquito species. ,e search has cluding water use (livestock drink, industry, washing, and provided that the factors salinity, pH, and water body irrigation), average depth (measured in three various points permanence determine the occurrence and distribution of of each pool), water flow, slope (zero slope, median slope, larval[12],andwaterdepthandtemperatureinfluencelarval and strong slope), color and origin of water (source, river, propagation[13].Moreover,thehumanfactorslikeland-use dam,dampipeline,andwastewaterdischarges),proximityto and land-cover changes represent the principal key factor of mosquito breeding habitat, surface debris, presence of the mosquito larvae occurrence [14]. vegetation, and filamentous algae. In addition, pH, tem- Few studies have analyzed the influence of biotic and perature, dissolved oxygen, and total dissolved solids were abiotic factors on the abundance of mosquito species in the taken using Consort Multiparameter Analyser C561. ,e Fez region (north central region of Morocco). salinity was taken at the same time as electrical conductivity ,eacquisitionofknowledgeaboutthelarvalhabitatsand using water quality instrument YSI scientific, and turbidity estimates of the biotic and abiotic factors associated with the was recorded by Lovibond turbidimeter Turbidirect. distribution of mosquitos can contribute to an efficient ® control method. 2.3. Mosquito Sampling. Larval sampling was carried out every two weeks using a dipping method for a period of one 2. Materials and Methods year from November 2015 to November 2016. ,e sampling 2.1. Study Area. ,e study was carried out in the Fez region was done in about ten ladle dives in several levels. ,e located in the northern central part of Morocco, charac- specimens were preserved in ethanol (70%). terizedbymildandsunnyMediterraneanclimateandalarge ,etypicalaquatichabitatssampledareshowninFigure2. human population (1150131 in 2014) (Figure 1). Mosquito larvae collections of each site were labeled with a ,e study area was limited to four habitat types (dam, sampling date, stored in glass flacons, and transferred to the swamp, source, and El Oued), categorized into artificial and Laboratory of Biotechnology and Preservation of Natural natural active larval habitats. ,e selection of habitats was Resources. All mosquito samples were morphologically iden- based on their permanent nature and the presence of larvae tified by microscopy at the species level, using the Moroccan identified in a preliminary survey. key of identification of Culicidae [15] and Mediterranean Africa mosquito identification software [16]. 2.1.1. Lgaada Dam. ,e dam has a height of 30m, with 3 3 2.90Mm of retention capacity and 10205.21Mm of total 2.4.StatisticalAnalysis. ,estatisticalanalysishasbeenused cumulated capacity. ,is is an artificial reservoir fed by to assess the relationships between biotic and abiotic factors runoff water which contributes to the supply of drinking and abundance of the most common species especially the water and allows for additional irrigation for crops during species of medical interest. R Software (version 3.4.3 (2017)) dry periods. It is located at 400m above mean sea level, wasusedfordataprocessing.Dataexplorationandmodeling ° ° 34 01.155′N of latitude, and 004 57.213′W of longitude. were used to detect the interactions between variables explained (number of species) and different explanatory variables (biotic and abiotic factors). ,e “number of each 2.1.2. Awinat Elhajaj. ,is natural site is a shallow swamp species” is the dependent variable, whereas “presence of tributary to channels of Lgaaˆda dam water. It is located at an vegetation,” “water used for washing and water for live- ° ° altitude of 382m, 34 01.226′N of latitude, and 004 57.105′W of stock,”“waterusedforindustry,”“waterusedforirrigation,” longitude. “debris,”“color,”“weather,”“slope,”“proximityofindustrial establishments,” “proximity of construction,” and “presence 2.1.3. Douwar Lhandiya. It is an artificial source located at of green filamentous algae” are all nominal independent ° ° 410mofaltitude,34 02.049′Noflatitude,and004 58.512′Wof variables. ,e quantitative explanatory variables were taken longitude.,estationchoicewasmadeasitisaperiurbanarea, into account according to nine physicochemical parameters close to the university campus Dhar El Mahraz of Fez, where such as water temperature ( C), pH, salinity (‰), dissolved foreign students with large numbers can be carriers of infec- oxygen(PPM),electricalconductivity(µs/cm),flowratemS/ tious diseases, typically imported from areas of endemicity. s, total dissolved solids (g/l), turbidity (NTU), and water depth (cm). ,e following models were used: 2.1.4. Jnan EL Alami Oued. It is located downstream of the main waterbody crossing the city of Fez (Sebou Oued)at an (1) the logistic regression for low number species like ° ° altitude of 242m, 34 04.421N of latitude, and 004 57.710′W Anopheles maculipennis s.l., Anopheles sergentii International Journal of Zoology 3 535000 544000 553000 MOULAY YACOUB Jnan EL Alami Douwar Lhandiya Awinat Elhajaj Morocco Lgaâda dam FEZ km 0 400 800 e regoin of Fez-Meknes SEFROU km Larval breeding sites km 05 10 0 80 160 535000 544000 553000 Figure 1: Location of the study area in Fez region (Morocco). Figure 2: Typical aquatic habitats sampled. 364000 373000 382000 364000 373000 382000 4 International Journal of Zoology 538000 544000 Culex perexiguus Culex pipiens Anopheles cinereius Culex theileri Culex perexiguus Anopheles sergentii Culex pipiens Anopheles cinereius Culiseta longiareolata Culex theileri Uranotaenia unguiculata Culex perexiguus Anopheles sergentii Culex pipiens Culex hortensis Anopheles maculipennis s. I. Breeding site Elevation (m) Culex theileri 219–365 Culex perexiguus 365–474 Anopheles maculipennis s. I. 474–614 km 02 4 614–934 538000 544000 Figure 3: Map showing the distribution of species according to localities and altitudes. (,eobald, 1907), Culiseta longiareolata (Macquart, abundant populations were collected in Lgaada ˆ dam with 1838) and Uranotaenia unguiculata(Edwards,1913), 448 specimens and Jnan El Alami Oued with 28 specimens. ,e species common at all four sites was Cx. perexiguus (2) the Poisson regression for more abundant mosquito (,eobald, 1903) (Figure 3). species, especially Culex theileri (,eobald, 1903), ,eresultsofthelogisticregressionshowedthatthespecies Culex perexiguus(,eobald,1903),and Culex pipiens Anopheles maculipennis s.l., Anopheles sergentii (,eobald, (Linnaeus, 1758). 1907), Culiseta longiareolata (Macquart, 1838), and Urano- ,e “vif” function in the car package was used to select taenia unguiculata(Edwards,1913),whicharelessabundantin independentexplanatoryvariablesandtestingcollinearity,while the present study, had no statistically significant relationship “glm” and “step” functions are used to select the best models. between their abundance and the biotic and abiotic factors. ,e results of Poisson regression analysis (Table 1) showed that the species Cx. perexiguus (,eobald, 1903) has 3. Results been positively correlated with site proximity to industrial A total of 772 specimens belonging to nine species were establishments and the presence of debris and green fila- mentous algae and significantly increased with increasing collected. Among these species three species of anophelines were identified, including An. maculipennis s.l., An. sergentii depth and conductivity but negatively correlated with water flow and dissolved oxygen. Cx. theileri (,eobald, 1903) (,eobald, 1907) and An. Cinereus. ,e Culex was more prevalent, wherein Culex pipiens (Linnaeus, 1758) was more larval density was observed to negatively correlate with the total dissolved solids and proximity of the sites to building common than Culex perexiguus (,eobald, 1903) and Culex theileri (,eobald, 1903), and Culex hortensis was repre- construction and positively correlate with dissolved oxygen, pH, and salinity, ,e most important observation was that, sented by single species. ,e genera of Culiseta and Ura- notaenia were represented by one species (Culiseta in relation to the presence of green filamentous algae and vegetationcover,theywerestatisticallypositivelysignificant. longiareolata (Macquart, 1838) and Uranotaenia unguicu- lata (Edwards, 1913)). ,e highest species richness (seven ,e result shows negative, highly significant associations species) was observed in Douwar Lhandiya source and between the distributionof Cx. pipiens (Linnaeus, 1758)and the water used for washing and watering livestock, con- Awinat Elhajaj. ,e most abundant populations were col- lected, respectively, in Douwar Lhandiya source (448 ductivity, and dissolved oxygen and slightly significant as- sociations with pH, total dissolved solids, and water flow. specimens) and Awinat Elhajaj (217 specimens). ,e low 380000 385000 380000 385000 International Journal of Zoology 5 Table 1: Significant results of the abiotic and biotic factors affecting the distribution of species. Species Parameter Estimate Std. error z value Pr(>|z|) ∗∗∗,‡ (Intercept) 1.04e+00 1.83e −01 5.69 1.2e −08 ,‡ ∗∗∗ WUIr −1.68e+00 4.49e −01 −3.74 0.00018 ,‡ ∗∗∗ Debris1 2.13e+00 1.73e −01 12.30 <2e −16 ,‡ ∗∗∗ Indu1 8.50e −01 1.83e −01 4.66 3.2e −06 ,‡ ∗∗∗ Build1 −8.26e −01 1.89e −01 −4.38 1.2e −05 Culex perexiguus (,eobald, 1903) ,‡ ∗∗∗ GFilAlg1 7.06e −01 2.02e −01 3.49 0.00047 ,‡ ∗∗∗ DOxy −4.57e −01 4.97e −02 −9.21 <2e −16 ∗∗,‡ ECond 1.99e −04 7.14e −05 2.79 0.00522 ,‡ ∗∗∗ Debris1 −2.24e+01 5.38e+00 −4.17 3.0e −05 ∗∗∗,‡ WDep 2.26e −02 3.88e −03 5.82 5.8e −09 ,‡ ∗∗∗ (Intercept) −11.9430 2.1022 −5.68 1.3e −08 ,‡ ∗∗∗ PVeg 1.7545 0.3954 4.44 9.1e −06 ,‡ ∗∗∗ Build1 −2.1231 0.2939 −7.22 5.0e −13 ,‡ ∗∗∗ GFilAlg1 1.7961 0.3441 5.22 1.8e −07 Culex theileri (,eobald, 1903)> ,‡ ∗∗∗ pH 1.2679 0.2295 5.53 3.3e −08 ∗∗∗,‡ Sal 1.3591 0.2140 6.35 2.1e −10 ,‡ DOxy 0.1367 0.0644 2.12 0.03377 ∗∗∗,‡ TDS −1.0132 0.2868 −3.53 0.00041 (Intercept) 1.59e+00 8.73e −01 1.83 0.06771 ,‡ ∗∗∗ WUIn −9.94e −01 2.62e −01 −3.79 0.00015 ,‡ ∗∗∗ WUIr 2.95e+00 2.63e −01 11.22 <2e −16 ∗,‡ Debris1 3.86e −01 1.82e −01 2.12 0.03438 ,‡ ∗∗ GW 1.26e+00 4.41e −01 2.85 0.00441 ∗∗∗,‡ IW 2.35e+00 4.26e −01 5.51 3.7e −08 YW −1.45e+01 6.81e+02 −0.02 0.98304 ∗,‡ Culex pipiens (linnaeus, 1758) ZSlope 5.57e −01 2.41e −01 2.31 0.02068 pH −1.80e −01 9.39e −02 −1.92 0.05540 ,‡ ∗∗ Sal 6.94e −01 2.20e −01 3.15 0.00164 ,‡ ∗∗∗ DOxy −4.49e −01 4.76e −02 −9.42 <2e −16 ,‡ ∗∗∗ ECond −7.10e −04 1.69e −04 −4.21 2.6e −05 ,‡ ∗∗∗ WF −1.64e+01 2.17e+00 −7.54 4.7e −14 ,‡ ∗∗∗ TDS −1.53e+00 2.30e −01 −6.64 3.1e −11 ,‡ ∗∗∗ WDep 5.29e −02 4.80e −03 11.01 <2e −16 † ‡ ∗∗∗ ∗∗ ∗ Std.Error:standarderror; zvalue:estimate/std.error;Pr(>|z|) �Pr(N(0,1)>|z-value|);significancecodes: 0.001, 0.01, 0.05, 0.1, 1;Build1:proximityof buildings construction; Indu1: proximity of industrial establishments; GW:green water; IW:incolor water; YW: yellow water; ECond:electrical con- ductivity; WF: water flow; Debris1: presence of debris; DOxy:dissolved oxygen; GFilAlg1:presence of green filamentous algae; WUIr:water used for irrigation;pH:potentialofhydrogen;WDep:waterdepth;Sal:salinity;ZSlope:zeroslope;TDS:totaldissolvedsolids;WUIn:waterusedforindustry;PVeg: presence of vegetation. However, the presence of emergent plants, the green and Our study showed that the abundance of Cx. pipiens incolor water, and the water used for irrigation were slightly (Linnaeus, 1758) larvae within the breeding site was not positively associated. In addition, a highly positively and correlated with water pH which is in agreement with Rydzanicz et al. (2016) [17]. ,ese authors suggest a significant relationship was found in terms of zero slope, salinity, and water depth. strong correlation between Cx. pipiens (Linnaeus, 1758) ,e results of the rare observations of An. maculipennis larval abundance and the physical and hydrological s.l., An. sergentii (,eobald, 1907), Cs. longiareolata (Mac- characteristics of the aquatic systems, like electrical quart, 1838), Ur. unguiculata (Edwards, 1913), An. Cinereus conductivity. By contrast, this finding was not positively (,eobald, 1901), and Cx. hortensis (Ficalbi, 1889) were not correlated in our data. Other recent studies by Amara explained because we do not have an explicit form of the Korba et al. (2016) showed that pH, temperature, and relationship between variables explained and a set of ex- dissolved oxygen exhibited comparable values without planatory variables. any relation with larval densities of Cx. pipiens (Lin- naeus, 1758) [18], and there were no marked differences in the presence of this species and water flow, distance to 4. Discussion the nearest house, artificial or natural larval breeding sites, soluble solid, and vegetation [19]. ,ese results As shown in the statistical analyses, both abiotic and biotic were not in complete agreement with our result. How- parameters such as component environments and physi- ever, other results from another country were in cochemical parameters strongly affected the abundance of agreement with our study’s findings [20]. It was Culicidae, which is already mentioned in literature [3]. 6 International Journal of Zoology confirmed that members of Cx. pipiens (Linnaeus, 1758) ,e most important factors that greatly affect the were potentially affected by water flow, water depth, abundanceof Cx. pipiens(Linnaeus,1758)intheregionwere salinity, soluble solid, and vegetation in artificial or zero slope, salinity, and water depth. natural larval breeding sites [20]. Overall, our findings provide some results about the Larvae of Cx. pipiens (Linnaeus, 1758) are able to breed influenceofbioticandabioticparametersonthedistribution in a great variety of habitats. However, a highly polluted of mosquito species. ,eresults of this study could be useful breedingsitecaninhibittheirdevelopment[18].Overall,our fortheauthoritiesinentomologicalsurveillancetoefficiently findings confirm that polluted water characterized by a develop important vector controls. yellow color affected the abundance of this species in larval Further work must be done in order to better charac- habitat. terize the dynamics of these mosquitoes in this region. Other important factors were strongly associated with the presence of Cx. perexiguus (,eobald, 1903) larvae and Data Availability Cx. theileri (,eobald, 1903). Both of them were increasing ,e data used in this study are included within the article. in the presence of algae [3]. Our results confirmed that species of mosquitoes (Cx. perexiguus (,eobald, 1903), Cx. Conflicts of Interest theileri (,eobald, 1903)) are positively affected by green filamentous algae [3]. In the literature, it is confirmed that ,e authors declare that they have no conflicts of interest. mosquito species were generally more present in natural areas than in urban and rural landscapes [21–23]. In our Acknowledgments work, the data obtained demonstrate that these two species were less common in the sites near to residential buildings. ,eauthorsaregratefultothemembersoftheLaboratoryof Distribution and abundance of Cx. perexiguus (,eo- Medical Entomology, National Hygiene Institute, Rabat. bald,1903)wererecognizedtoshowacloserelationshipwith industrial activities and correlate with slow-running water References environments, debris, electrical conductivity, and water depth. ,e last parameter was confirmed to be correlated [1] B. Emidi, W. N. Kisinza, B. P. 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Study of Abiotic and Biotic Parameters Affecting the Abundance of Mosquito Larvae (Diptera: Culicidae) in the Region of Fez (Morocco)

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Copyright © 2020 Touria Filali Mouatassem et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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1687-8477
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1687-8485
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10.1155/2020/5429472
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Abstract

Hindawi International Journal of Zoology Volume 2020, Article ID 5429472, 7 pages https://doi.org/10.1155/2020/5429472 Research Article Study of Abiotic and Biotic Parameters Affecting the Abundance of Mosquito Larvae (Diptera: Culicidae) in the Region of Fez (Morocco) 1 1,2 3 Touria Filali Mouatassem, Abdelhakim El Ouali Lalami , Chafika Faraj, 4 1 Noureddine Rais, and Raja Guemmouh Laboratory of Biotechnology and Preservation of Natural Resources, Sidi Mohamed Ben Abdellah University, Faculty of Sciences Dhar El Mahraz, Fez 30000, Morocco Higher Institute of Nursing Professions and Health Techniques of Fez, Regional Health Directorate, El Ghassani Hospital, Fez 30000, Morocco Laboratory of Medical Entomology, National Hygiene Institute, Rabat 11400, Morocco Laboratory of Computer Science, Modelling and Systems, Sidi Mohamed Ben Abdellah University, Faculty of Sciences Dhar Mahraz, Fez 30000, Morocco Correspondence should be addressed to Abdelhakim El Ouali Lalami; eloualilalami@yahoo.fr Received 25 March 2020; Revised 24 June 2020; Accepted 6 July 2020; Published 27 July 2020 Academic Editor: Joao Pedro Barreiros Copyright © 2020 Touria Filali Mouatassem et al. ,is is an open access article distributed under the Creative Commons AttributionLicense,whichpermitsunrestricteduse,distribution,andreproductioninanymedium,providedtheoriginalworkis properly cited. Mosquitoes cause significant human health issues. However, very few studies have attempted to examine the question of how abiotic and biotic factors affect the abundance of Culicidae in the larval habitat. ,e objective of this study was to analyze the influenceofbioticandabioticfactorsontheincreaseofthemostcommonmosquitospeciesintheFezregion(CentralMorocco). Larvaemosquitoesweresampledbystandarddippingtechniqueinfourdifferenttypesofmacrohabitats,betweenNovember2015 and November 2016. Each mosquito specimen was morphologically identified by the Moroccan Culicidae key and the Brunhes key. ,e analysis was done using R analysis software. We collected a total of 772 mosquito larvae belonging to nine different species, five of which are considered of medical interest. Culex pipiens (Linnaeus, 1758), known as the major vector in the transmission of West Nile virus fever (WNV), was the most common species of all mosquito larvae collected. ,e results of Poissonregressionanalysisshowedthatfactorssuchasthepresenceofgreenfilamentousalgae,vegetationcover,anddebriswere foundtobepositivelysignificantinthedistributionofthegenus Culex.However,therewasinsufficientevidencetodeterminethe parameters that are capable of estimating the abundance of Anopheles. ,e findings have also estimated that biotic and abiotic factors can lead to significant variation in the abundance of Culex perexiguus (,eobald, 1903), Culex theileri (,eobald, 1903), and Culex pipiens(Linnaeus,1758).Identifyingthepriorityparametersgoverningtheproliferationofmosquitoesintheregionof Fez can be one of the key elements for better vector control. turbidity, algal cover and stability of the habitat [3]; these 1. Introduction factors can lead to determining the density, size and vector Mosquitoes infect humans and other vertebrates. ,eir competence [3]. Surveying biotic and abiotic factors for distribution is to a large extent influenced by climatic various mosquito fauna make it easier to monitor the po- conditions and species habits across the globe [1]. Inter- tential modifications of larval habitats affected by rains, actions between biotic and abiotic factors can conduct to global climate change, and man-made activities [4–6]. significant variation in the reproductive landscape of insects In Morocco, many species of Culicidae family have been [2]. ,ey differ in their preference for the type, size, reportedasimportantvectorsofinfectiousdiseases,includingthe 2 International Journal of Zoology presence of the major vectors of malaria (Anopheles labranchiae of longitude. It is one of the most polluted rivers in the and Anopheles sergentii (,eobald, 1907)) [7, 8], the Aedes region and contains pollutants from various sources such as albopictus, responsible for the transmission of dengue, chi- sewage, fertilizers from agricultural fields, and industrial kungunya, and Zika viruses [9], and Culex pipiens, the potential waste. vectorofbothWestNilevirus[10]andRiftValleyfevervirus[11]. Antecedent studies on larval breeding sites have been a 2.2. Larval Habitat Characterization. ,e weather and the valuable source of information regarding the larval biology characteristics of the macrohabitats were recorded, in- and ecology of different mosquito species. ,e search has cluding water use (livestock drink, industry, washing, and provided that the factors salinity, pH, and water body irrigation), average depth (measured in three various points permanence determine the occurrence and distribution of of each pool), water flow, slope (zero slope, median slope, larval[12],andwaterdepthandtemperatureinfluencelarval and strong slope), color and origin of water (source, river, propagation[13].Moreover,thehumanfactorslikeland-use dam,dampipeline,andwastewaterdischarges),proximityto and land-cover changes represent the principal key factor of mosquito breeding habitat, surface debris, presence of the mosquito larvae occurrence [14]. vegetation, and filamentous algae. In addition, pH, tem- Few studies have analyzed the influence of biotic and perature, dissolved oxygen, and total dissolved solids were abiotic factors on the abundance of mosquito species in the taken using Consort Multiparameter Analyser C561. ,e Fez region (north central region of Morocco). salinity was taken at the same time as electrical conductivity ,eacquisitionofknowledgeaboutthelarvalhabitatsand using water quality instrument YSI scientific, and turbidity estimates of the biotic and abiotic factors associated with the was recorded by Lovibond turbidimeter Turbidirect. distribution of mosquitos can contribute to an efficient ® control method. 2.3. Mosquito Sampling. Larval sampling was carried out every two weeks using a dipping method for a period of one 2. Materials and Methods year from November 2015 to November 2016. ,e sampling 2.1. Study Area. ,e study was carried out in the Fez region was done in about ten ladle dives in several levels. ,e located in the northern central part of Morocco, charac- specimens were preserved in ethanol (70%). terizedbymildandsunnyMediterraneanclimateandalarge ,etypicalaquatichabitatssampledareshowninFigure2. human population (1150131 in 2014) (Figure 1). Mosquito larvae collections of each site were labeled with a ,e study area was limited to four habitat types (dam, sampling date, stored in glass flacons, and transferred to the swamp, source, and El Oued), categorized into artificial and Laboratory of Biotechnology and Preservation of Natural natural active larval habitats. ,e selection of habitats was Resources. All mosquito samples were morphologically iden- based on their permanent nature and the presence of larvae tified by microscopy at the species level, using the Moroccan identified in a preliminary survey. key of identification of Culicidae [15] and Mediterranean Africa mosquito identification software [16]. 2.1.1. Lgaada Dam. ,e dam has a height of 30m, with 3 3 2.90Mm of retention capacity and 10205.21Mm of total 2.4.StatisticalAnalysis. ,estatisticalanalysishasbeenused cumulated capacity. ,is is an artificial reservoir fed by to assess the relationships between biotic and abiotic factors runoff water which contributes to the supply of drinking and abundance of the most common species especially the water and allows for additional irrigation for crops during species of medical interest. R Software (version 3.4.3 (2017)) dry periods. It is located at 400m above mean sea level, wasusedfordataprocessing.Dataexplorationandmodeling ° ° 34 01.155′N of latitude, and 004 57.213′W of longitude. were used to detect the interactions between variables explained (number of species) and different explanatory variables (biotic and abiotic factors). ,e “number of each 2.1.2. Awinat Elhajaj. ,is natural site is a shallow swamp species” is the dependent variable, whereas “presence of tributary to channels of Lgaaˆda dam water. It is located at an vegetation,” “water used for washing and water for live- ° ° altitude of 382m, 34 01.226′N of latitude, and 004 57.105′W of stock,”“waterusedforindustry,”“waterusedforirrigation,” longitude. “debris,”“color,”“weather,”“slope,”“proximityofindustrial establishments,” “proximity of construction,” and “presence 2.1.3. Douwar Lhandiya. It is an artificial source located at of green filamentous algae” are all nominal independent ° ° 410mofaltitude,34 02.049′Noflatitude,and004 58.512′Wof variables. ,e quantitative explanatory variables were taken longitude.,estationchoicewasmadeasitisaperiurbanarea, into account according to nine physicochemical parameters close to the university campus Dhar El Mahraz of Fez, where such as water temperature ( C), pH, salinity (‰), dissolved foreign students with large numbers can be carriers of infec- oxygen(PPM),electricalconductivity(µs/cm),flowratemS/ tious diseases, typically imported from areas of endemicity. s, total dissolved solids (g/l), turbidity (NTU), and water depth (cm). ,e following models were used: 2.1.4. Jnan EL Alami Oued. It is located downstream of the main waterbody crossing the city of Fez (Sebou Oued)at an (1) the logistic regression for low number species like ° ° altitude of 242m, 34 04.421N of latitude, and 004 57.710′W Anopheles maculipennis s.l., Anopheles sergentii International Journal of Zoology 3 535000 544000 553000 MOULAY YACOUB Jnan EL Alami Douwar Lhandiya Awinat Elhajaj Morocco Lgaâda dam FEZ km 0 400 800 e regoin of Fez-Meknes SEFROU km Larval breeding sites km 05 10 0 80 160 535000 544000 553000 Figure 1: Location of the study area in Fez region (Morocco). Figure 2: Typical aquatic habitats sampled. 364000 373000 382000 364000 373000 382000 4 International Journal of Zoology 538000 544000 Culex perexiguus Culex pipiens Anopheles cinereius Culex theileri Culex perexiguus Anopheles sergentii Culex pipiens Anopheles cinereius Culiseta longiareolata Culex theileri Uranotaenia unguiculata Culex perexiguus Anopheles sergentii Culex pipiens Culex hortensis Anopheles maculipennis s. I. Breeding site Elevation (m) Culex theileri 219–365 Culex perexiguus 365–474 Anopheles maculipennis s. I. 474–614 km 02 4 614–934 538000 544000 Figure 3: Map showing the distribution of species according to localities and altitudes. (,eobald, 1907), Culiseta longiareolata (Macquart, abundant populations were collected in Lgaada ˆ dam with 1838) and Uranotaenia unguiculata(Edwards,1913), 448 specimens and Jnan El Alami Oued with 28 specimens. ,e species common at all four sites was Cx. perexiguus (2) the Poisson regression for more abundant mosquito (,eobald, 1903) (Figure 3). species, especially Culex theileri (,eobald, 1903), ,eresultsofthelogisticregressionshowedthatthespecies Culex perexiguus(,eobald,1903),and Culex pipiens Anopheles maculipennis s.l., Anopheles sergentii (,eobald, (Linnaeus, 1758). 1907), Culiseta longiareolata (Macquart, 1838), and Urano- ,e “vif” function in the car package was used to select taenia unguiculata(Edwards,1913),whicharelessabundantin independentexplanatoryvariablesandtestingcollinearity,while the present study, had no statistically significant relationship “glm” and “step” functions are used to select the best models. between their abundance and the biotic and abiotic factors. ,e results of Poisson regression analysis (Table 1) showed that the species Cx. perexiguus (,eobald, 1903) has 3. Results been positively correlated with site proximity to industrial A total of 772 specimens belonging to nine species were establishments and the presence of debris and green fila- mentous algae and significantly increased with increasing collected. Among these species three species of anophelines were identified, including An. maculipennis s.l., An. sergentii depth and conductivity but negatively correlated with water flow and dissolved oxygen. Cx. theileri (,eobald, 1903) (,eobald, 1907) and An. Cinereus. ,e Culex was more prevalent, wherein Culex pipiens (Linnaeus, 1758) was more larval density was observed to negatively correlate with the total dissolved solids and proximity of the sites to building common than Culex perexiguus (,eobald, 1903) and Culex theileri (,eobald, 1903), and Culex hortensis was repre- construction and positively correlate with dissolved oxygen, pH, and salinity, ,e most important observation was that, sented by single species. ,e genera of Culiseta and Ura- notaenia were represented by one species (Culiseta in relation to the presence of green filamentous algae and vegetationcover,theywerestatisticallypositivelysignificant. longiareolata (Macquart, 1838) and Uranotaenia unguicu- lata (Edwards, 1913)). ,e highest species richness (seven ,e result shows negative, highly significant associations species) was observed in Douwar Lhandiya source and between the distributionof Cx. pipiens (Linnaeus, 1758)and the water used for washing and watering livestock, con- Awinat Elhajaj. ,e most abundant populations were col- lected, respectively, in Douwar Lhandiya source (448 ductivity, and dissolved oxygen and slightly significant as- sociations with pH, total dissolved solids, and water flow. specimens) and Awinat Elhajaj (217 specimens). ,e low 380000 385000 380000 385000 International Journal of Zoology 5 Table 1: Significant results of the abiotic and biotic factors affecting the distribution of species. Species Parameter Estimate Std. error z value Pr(>|z|) ∗∗∗,‡ (Intercept) 1.04e+00 1.83e −01 5.69 1.2e −08 ,‡ ∗∗∗ WUIr −1.68e+00 4.49e −01 −3.74 0.00018 ,‡ ∗∗∗ Debris1 2.13e+00 1.73e −01 12.30 <2e −16 ,‡ ∗∗∗ Indu1 8.50e −01 1.83e −01 4.66 3.2e −06 ,‡ ∗∗∗ Build1 −8.26e −01 1.89e −01 −4.38 1.2e −05 Culex perexiguus (,eobald, 1903) ,‡ ∗∗∗ GFilAlg1 7.06e −01 2.02e −01 3.49 0.00047 ,‡ ∗∗∗ DOxy −4.57e −01 4.97e −02 −9.21 <2e −16 ∗∗,‡ ECond 1.99e −04 7.14e −05 2.79 0.00522 ,‡ ∗∗∗ Debris1 −2.24e+01 5.38e+00 −4.17 3.0e −05 ∗∗∗,‡ WDep 2.26e −02 3.88e −03 5.82 5.8e −09 ,‡ ∗∗∗ (Intercept) −11.9430 2.1022 −5.68 1.3e −08 ,‡ ∗∗∗ PVeg 1.7545 0.3954 4.44 9.1e −06 ,‡ ∗∗∗ Build1 −2.1231 0.2939 −7.22 5.0e −13 ,‡ ∗∗∗ GFilAlg1 1.7961 0.3441 5.22 1.8e −07 Culex theileri (,eobald, 1903)> ,‡ ∗∗∗ pH 1.2679 0.2295 5.53 3.3e −08 ∗∗∗,‡ Sal 1.3591 0.2140 6.35 2.1e −10 ,‡ DOxy 0.1367 0.0644 2.12 0.03377 ∗∗∗,‡ TDS −1.0132 0.2868 −3.53 0.00041 (Intercept) 1.59e+00 8.73e −01 1.83 0.06771 ,‡ ∗∗∗ WUIn −9.94e −01 2.62e −01 −3.79 0.00015 ,‡ ∗∗∗ WUIr 2.95e+00 2.63e −01 11.22 <2e −16 ∗,‡ Debris1 3.86e −01 1.82e −01 2.12 0.03438 ,‡ ∗∗ GW 1.26e+00 4.41e −01 2.85 0.00441 ∗∗∗,‡ IW 2.35e+00 4.26e −01 5.51 3.7e −08 YW −1.45e+01 6.81e+02 −0.02 0.98304 ∗,‡ Culex pipiens (linnaeus, 1758) ZSlope 5.57e −01 2.41e −01 2.31 0.02068 pH −1.80e −01 9.39e −02 −1.92 0.05540 ,‡ ∗∗ Sal 6.94e −01 2.20e −01 3.15 0.00164 ,‡ ∗∗∗ DOxy −4.49e −01 4.76e −02 −9.42 <2e −16 ,‡ ∗∗∗ ECond −7.10e −04 1.69e −04 −4.21 2.6e −05 ,‡ ∗∗∗ WF −1.64e+01 2.17e+00 −7.54 4.7e −14 ,‡ ∗∗∗ TDS −1.53e+00 2.30e −01 −6.64 3.1e −11 ,‡ ∗∗∗ WDep 5.29e −02 4.80e −03 11.01 <2e −16 † ‡ ∗∗∗ ∗∗ ∗ Std.Error:standarderror; zvalue:estimate/std.error;Pr(>|z|) �Pr(N(0,1)>|z-value|);significancecodes: 0.001, 0.01, 0.05, 0.1, 1;Build1:proximityof buildings construction; Indu1: proximity of industrial establishments; GW:green water; IW:incolor water; YW: yellow water; ECond:electrical con- ductivity; WF: water flow; Debris1: presence of debris; DOxy:dissolved oxygen; GFilAlg1:presence of green filamentous algae; WUIr:water used for irrigation;pH:potentialofhydrogen;WDep:waterdepth;Sal:salinity;ZSlope:zeroslope;TDS:totaldissolvedsolids;WUIn:waterusedforindustry;PVeg: presence of vegetation. However, the presence of emergent plants, the green and Our study showed that the abundance of Cx. pipiens incolor water, and the water used for irrigation were slightly (Linnaeus, 1758) larvae within the breeding site was not positively associated. In addition, a highly positively and correlated with water pH which is in agreement with Rydzanicz et al. (2016) [17]. ,ese authors suggest a significant relationship was found in terms of zero slope, salinity, and water depth. strong correlation between Cx. pipiens (Linnaeus, 1758) ,e results of the rare observations of An. maculipennis larval abundance and the physical and hydrological s.l., An. sergentii (,eobald, 1907), Cs. longiareolata (Mac- characteristics of the aquatic systems, like electrical quart, 1838), Ur. unguiculata (Edwards, 1913), An. Cinereus conductivity. By contrast, this finding was not positively (,eobald, 1901), and Cx. hortensis (Ficalbi, 1889) were not correlated in our data. Other recent studies by Amara explained because we do not have an explicit form of the Korba et al. (2016) showed that pH, temperature, and relationship between variables explained and a set of ex- dissolved oxygen exhibited comparable values without planatory variables. any relation with larval densities of Cx. pipiens (Lin- naeus, 1758) [18], and there were no marked differences in the presence of this species and water flow, distance to 4. Discussion the nearest house, artificial or natural larval breeding sites, soluble solid, and vegetation [19]. ,ese results As shown in the statistical analyses, both abiotic and biotic were not in complete agreement with our result. How- parameters such as component environments and physi- ever, other results from another country were in cochemical parameters strongly affected the abundance of agreement with our study’s findings [20]. It was Culicidae, which is already mentioned in literature [3]. 6 International Journal of Zoology confirmed that members of Cx. pipiens (Linnaeus, 1758) ,e most important factors that greatly affect the were potentially affected by water flow, water depth, abundanceof Cx. pipiens(Linnaeus,1758)intheregionwere salinity, soluble solid, and vegetation in artificial or zero slope, salinity, and water depth. natural larval breeding sites [20]. Overall, our findings provide some results about the Larvae of Cx. pipiens (Linnaeus, 1758) are able to breed influenceofbioticandabioticparametersonthedistribution in a great variety of habitats. However, a highly polluted of mosquito species. ,eresults of this study could be useful breedingsitecaninhibittheirdevelopment[18].Overall,our fortheauthoritiesinentomologicalsurveillancetoefficiently findings confirm that polluted water characterized by a develop important vector controls. yellow color affected the abundance of this species in larval Further work must be done in order to better charac- habitat. terize the dynamics of these mosquitoes in this region. Other important factors were strongly associated with the presence of Cx. perexiguus (,eobald, 1903) larvae and Data Availability Cx. theileri (,eobald, 1903). Both of them were increasing ,e data used in this study are included within the article. in the presence of algae [3]. Our results confirmed that species of mosquitoes (Cx. perexiguus (,eobald, 1903), Cx. Conflicts of Interest theileri (,eobald, 1903)) are positively affected by green filamentous algae [3]. In the literature, it is confirmed that ,e authors declare that they have no conflicts of interest. mosquito species were generally more present in natural areas than in urban and rural landscapes [21–23]. In our Acknowledgments work, the data obtained demonstrate that these two species were less common in the sites near to residential buildings. ,eauthorsaregratefultothemembersoftheLaboratoryof Distribution and abundance of Cx. perexiguus (,eo- Medical Entomology, National Hygiene Institute, Rabat. bald,1903)wererecognizedtoshowacloserelationshipwith industrial activities and correlate with slow-running water References environments, debris, electrical conductivity, and water depth. ,e last parameter was confirmed to be correlated [1] B. Emidi, W. N. Kisinza, B. P. 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