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Effect of altitude on wing metric variation of Aedes aegypti (Diptera: Culicidae) in a region of the Colombian Central Andes

  • Luis Míguel Leyton Ramos ,

    Contributed equally to this work with: Luis Míguel Leyton Ramos, Oscar Alexander Aguirre Obando, Víctor Hugo García-Merchán

    Roles Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

    Affiliations Grupo de Evolución, Ecología y Conservación (EECO), Universidad del Quindío, Armenia, Quindío, Colombia, Escuela de Investigación en Biomatemáticas, Universidad del Quindío, Armenia, Quindío, Colombia

  • Oscar Alexander Aguirre Obando ,

    Contributed equally to this work with: Luis Míguel Leyton Ramos, Oscar Alexander Aguirre Obando, Víctor Hugo García-Merchán

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Escuela de Investigación en Biomatemáticas, Universidad del Quindío, Armenia, Quindío, Colombia

  • Jonny Edward Duque,

    Roles Data curation, Formal analysis, Methodology, Writing – review & editing

    Affiliation Centro de Investigaciones en Enfermedades Tropicales – CINTROP, Facultad de Salud, Escuela de Medicina, Departamento de Ciencias Básicas, Universidad Industrial de Santander, Piedecuesta, Santander, Colombia

  • Víctor Hugo García-Merchán

    Contributed equally to this work with: Luis Míguel Leyton Ramos, Oscar Alexander Aguirre Obando, Víctor Hugo García-Merchán

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    victorhgarcia@uniquindio.edu.co

    Affiliation Grupo de Evolución, Ecología y Conservación (EECO), Universidad del Quindío, Armenia, Quindío, Colombia

Abstract

In mosquitoes of medical importance, wing shape and size can vary with altitude, an aspect that can influence dispersion and, consequently, their vector capacity. Using geometric morphometry analysis, Aedes aegypti wing size and shape variation of males and females was studied in four altitudes in the second-smallest department in Colombia: 1,200 m (Tebaida), 1,400 m (Armenia), 1,500 m (Calarcá), and 1,700 m (Filandia). Wing shape in males (P < 0.001) and females (P < 0.001) was significantly different through the altitudinal gradient; in turn, wing size in males followed the altitudinal gradient males (R2 = 0.04946, P = 0.0002), females (R2 = 0.0011, P = 0.46). Wing allometry for males (P < 0.001) and females (P < 0.001) was significant. Likewise, the shape and size of the wings of males (P < 0.001) and females (P < 0.001) had significant fluctuating asymmetry. It is concluded that, in a small scale with an altitudinal variation of 500 meters, it is detected that the size and shape of the wings varied in A. aegypti, main vector the agents that cause dengue, chikungunya, and Zika. The fluctuating asymmetry is present in the individuals studied and could be associated with environmental effects caused by vector control campaigns present in some sampling locations.

1. Introduction

Aedes (Stegomyia) aegypti (Linnaeus, 1762) is an urban anthropophilic mosquito from Africa, distributed in the world’s tropical and sub-tropical regions [1]. In the Americas, this mosquito is present in almost every country, considered the main vector the agents that cause dengue (DENV), Zika fever (ZIKV), and chikungunya (CHIKV) [24]. In Colombia, A. aegypti is registered in 80% of the country up to 2,300 m [5]. Nevertheless, still unknown is the epidemiological impact altitude exerts on the population dynamics of A. aegypti in areas, like the Andean region. It has been observed that the altitude in the zones where the mosquito inhabits has a direct impact on the abundance, geographic distribution, vector capacity, epidemiology, and pathogenicity of the mosquitoes [6]. Additionally, in culicids, the range of altitudinal distribution may be modified by increased global temperature [7], a phenomenon observed in the natural populations of A. aegypti of the Americas, including Colombia [5].

In A. aegypti, the size of the individuals has been associated with components of the reproductive success [8, 9]. Bigger A. aegypti individuals (per se, bigger wingspan) could be more involved in the transmission of arthropod-borne virus (arbovirus), like dengue, than smaller ones [10]. In addition, bigger individuals have been associated with a higher frequency of feeding from blood in human hosts [11], greater survival, and fertility [12]. On the contrary, smaller mosquitoes (hence, with smaller wingspan) may have a higher number of feeding events throughout their lives, which can increase infection levels and arbovirus dissemination [9, 13, 14]. Furthermore, the biological shape is an outstanding aspect of the phenotype of an organism and provides a link between the genotype and the environment [15]. The biological shape has been studied in insects, such as butterflies and fruit flies, with an emphasis on wings, which are a trait that is associated with carrying capacity and dispersal [16, 17]. In mosquitoes, wing shape is associated with dispersion capacity [18]. Additionally, wing flapping produces vibrations that generate sounds [19, 20], which are different and are related with the precopulatory behavior [21].

In mosquitoes, it has been noted that temperature (climatic variable inversely proportional to altitude) causes changes in the life cycle, affecting the body size and shape [22]. An inverse relationship has been observed in some cases between temperature and the duration of development [23]. Consequently, at lower temperatures, the transmission of arbovirus may—in some cases—be impeded [24]. Hence, knowing how wing shape and size vary in A. aegypti, with relation to altitude, could contribute useful information for its vector control.

The geometric morphometry permits detecting information patterns on the type, ecological relationships, and environmental factors associated to populations present in the area [2527]. In A. aegypti, morphometric analyses on wings have been widely studied to investigate heterogeneity and structuring in natural populations [2831]. However, very few prior studies have related altitude and wing metric variation in mosquitoes. Studies in northeastern Turkey on Aedes vexans between 808 and 1,620 m and on Culex theileri between 808 and 2,130 m showed variation in wing size and shape. Besides, in Culex theileri, a positive correlation was observed between wing size and altitude [18, 32]. Recently, in Aedes albopictus of Albania, the region where this Asian mosquito was first registered in Europe, it was observed between 154 and 1,559 m shape, size and sex variations among altitudinal populations of these species [33]. Nevertheless, in Colombia and the rest of the world, the metric variation of A. aegypti and its relation with the altitudinal gradient has not been studied much [34]. In Colombia, the department of Quindío is on the central mountain range of the Andes and it is the second smallest in geographic extension with altitudes in its urban area ranging from 1,200 to 1,917 m in 1,961 km2 [3537]. Due to the aforementioned, this study sought to explore the wing size and shape variation of A. aegypti males and females from an altitudinal gradient of the central mountain range of the Colombian Andes.

2. Methodology

2.1 Field work

The department of Quindío is the second smallest regarding land area in Colombia, with an extension of 1,961 km2, with an altitude range in the urban area from 1.200 (Tebaida) to 1,917 m (Filandia) [35, 36]. Here, for six months, in the rainy season, between August (2017) and February (2018), adult individuals of A. aegypti were collected in four altitudes of the urban zone [The taxonomic keys used are described at the end of this item]. The sampling sites were the following: 1,200 m (Tebaida), 1,400 m (Armenia), 1,500 m (Calarcá), and 1,700 m (Filandia). In Filandia, one of the municipalities with the highest altitude urban settlement in the department, no mosquitoes were found at altitudes above 1,700 m. Table 1 shows information regarding mosquitoes collected by altitude, locality, geographic coordinates and sex. For each altitude and for the rainy season, from historical data available in the Wolrdclim-2 library on temperature from 1970 to 2000 [38], the mean historic temperature was extracted using the geographic coordinates. This variable is recognized in the literature as one of the most influential in the life cycle of A. aegypti [39, 40]. Thereafter, the layers of each altitude were overlapped with each of the raster layers for temperature. Then, for each altitude and each raster layer of temperature, the median, minimum, and maximum historical average temperatures were extracted. The R software version 4.0.1, and raster library [41] were used for these purpose. To select the sampling sites by altitude, 10 points were randomly selected. Each point corresponded to a neighborhood and in each neighborhood, homes were visited where their dwellers permitted. Each home was visited four times per month and each visit lasted from 45 to 60 minutes. In each home sampled, an informed consent was delivered on the objectives of the research and the authorization to conduct the sampling.

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Table 1. Information regarding mosquitoes collected by altitude, locality, geographic coordinates and individual number for sex, as well as some climatic data.

https://doi.org/10.1371/journal.pone.0228975.t001

The adults were collected through mechanical aspiration through an electric aspirator. After collection, the individuals were sedated and sacrificed with acetone. All the collections were conducted under the framework permit from the Corporación Autonoma Regional del Quindío (CRQ) N° 240 issued for the department of Quindío, Colombia. Finally, the specimens were identified at species level by using the taxonomic keys of Forattini [42] and Rueda [43]. Fig 1 shows the location, as well as the total number of mosquitoes by altitude and sex used in this work.

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Fig 1. Map with sampling altitudes and total number of males and females of A. aegypti by altitude.

https://doi.org/10.1371/journal.pone.0228975.g001

2.2 Laboratory work

The left and right wings were removed from each male and female mosquito collected; removal was from the base, following the protocol described in [44] and [45]. Each wing was submerged in NaClO solution at 5% to remove scales and rinse them. Thereafter, each wing was submerged in ethanol solution at 99.5% to remove excess NaClO, to be mounted on a slide with ethanol at 70%. The photographs were taken on a stereomicroscope (Zeiss Stemi DV4) with integrated camera (Canon EOS REBEL T3i) with 32X magnification, according to specifications for taking landmarks (LM) for two dimensions (2D) [46].

Each wing was marked with 22 LM [47] type I (Fig 2A), according to the method by Rohlf & Slice [26, 48]. The photos were organized randomly with the tpsUtil software version 7.0 to reduce LM marking bias [49]. All the LM of the wings were marked twice by using the tpsDig2 program [50]. The LM were located by the same operator to reduce human error in taking points. To guarantee the reproducibility of the experiment, the marking of the LM was carried out twice. To detect atypical LM, the Morphoj program was used [51].

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Fig 2. Location of LM, general analysis of procrustes, and comparison among replicas.

(A). Anatomical frameworks used. (B) Procrustes coordinates after the analysis of atypical data. (C) PC1 set of original data. (D) PC1 set of replica data.

https://doi.org/10.1371/journal.pone.0228975.g002

2.3 Data analysis

From the array of data with the coordinates of each LM, the effect of the scale, translation, and rotation was eliminated through a general Procrustes analysis [48, 52]. Thereafter, the Procrustes coordinates were obtained as representative variable of the wing shape and centroid size (CS) of the wing size, which were used in all the analyses performed. To guarantee the reproducibility of the data used, the measurement error rate (% ME) was estimated according to [53, 54], using the variables CS and individual factor to both markings (original and replica). These variables were obtained the variance components, one through one-way ANOVA. The individual factor was used as a source of variation between original and replica marking. To visualize the differences of each LM among the original data and their replica, from the principal components obtained from Procrustes coordinates, deformation grids were used [55].

Information from the right wing was used to analyze the shape and size variation in the altitudinal gradient for both sexes. The CS for each sex and altitude was evaluated by using the Kruskal-Wallis non-parametric test. When differences were significant, a pair-wise Mann–Whitney U-test was used, and it was visualized by using a box diagram and a chart to indicate the significant differences among the comparisons. To determine the relationship between size and the altitudinal gradient, a simple linear regression was performed. The allometric influence of wing size within the shape was analyzed through a multivariate regression of Procrustes coordinates [56] in function of the CS, using a permutations test with 10,000 randomizations [57].

The wing shape variation patterns for each sex were visualized through an analysis of principal components analysis (PCA). For each sex, wing shape and its variation in the altitudinal gradient, a Canonical Variable Analysis (CVA) was conducted. In addition, the PCA used deformation grids to determine in what LM did the wing shape variation originate. The shape variation in function of the altitudinal gradient for each sex was evaluated through an analysis of variance (ANOVA) with 10,000 randomizations [58].

With the mosquitoes (Males = 223 and Females = 385) that had both wings in good condition, symmetry or asymmetry were determined. For this, the study used values of the CS and the Procrustes coordinates of the original data and their replica, which were analyzed through a Procrustes ANOVA with 1,000 iterations [59, 60]. All the analyses were performed in the R programming software, version 4.0.1 [61], using the Geomorph package, version 3.3.1 [62], dplyr version 0.8.0.1 [63], rcompanion version 2.3.25 [64, 65], and multcompView 0.1–8 [66], except for the CVA, Mahalanobis distances, and the allometric regression, which were carried out in the MorphoJ program, version 2.6 [51].

3. Results

Fig 2B shows that the distribution of the LM used is located continuously. Fig 2C and 2D indicate that the set of original data and their replica had no variations by the user to mark the 22 LM (% ME = 1.92). The CS of the wings of males and females had significant differences (Df = 1, P < 0.05), being higher in females (4.19 CS ± 0.38) than in males (3.29 CS± 0.30); (Fig 3). In turn, the CS variation in function of the altitudinal gradient for wings from males (Df = 3, P < 0.05) and females (Df = 3, P < 0.05) was statistically significant, indicating the CS for males, based on the Mann–Whitney test, statistical differences between the altitudes from 1,400 to 1,500 m, 1,200–1,400 m, 1,500–1,700 m and 1,200–1,700 m. The CS of the wings for females was different between the altitudes 1,400–1,500 m and 1,200–1,400 m Table 2. Fig 4A suggests that wings of males have a slight tendency to being bigger at higher altitudes, nevertheless, other variables associated with the mosquito’s development must be analyzed to have better resolution (R2 = 0.04946, P = 0.0002), a pattern not observed for wings of females (R2 = 0.0011, P = 0.46; (Fig 4B)).

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Fig 3. Box diagram for the centroid size and altitude for wings from both sexes of A. aegypti.

https://doi.org/10.1371/journal.pone.0228975.g003

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Fig 4. Linear regression for centroid size and altitude for both sexes of A. aegypti, Males (A) and Females (B).

https://doi.org/10.1371/journal.pone.0228975.g004

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Table 2. Significant differences for size by sex in the altitudinal gradient, according to the Pairwise Mann–Whitney U-tests.

https://doi.org/10.1371/journal.pone.0228975.t002

The allometry test indicated that the contribution of CS wing shape variation was significant for both sexes (Males P < 0.001 and Females P < 0.001), where the percentage of wing shape variance explained by the size was 4.9% for males and 2.5% for females.

The PCA in total explained 53.1% of data variation (PC1 = 43.8%, PC2 = 9.3%). The PC1 separated two groupings corresponding to each sex. The wing shape of males was present in the negative part of PC1 and that of the females in the positive part. In males, wing shape variation was observed for LM from the wing contour (LM: 1–11, 21, 22) in negative sense to PC1 and internal LM (LM 12–20) in positive sense to PC1. For females, the LM from the wing contour were present in positive sense to PC1 and in contrary sense, the internal LM (Fig 5).

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Fig 5. PCA and deformation grid for wing shape between both sexes of A. aegypti.

https://doi.org/10.1371/journal.pone.0228975.g005

The CVA for each sex showed differences in wing shape among mosquitoes located at different altitudes. In males, CV1 and 2 explain in total 83.2% of the wing shape variation (CV1 = 62.2%, CV2 = 21%), while in females, this explained 82.8% of the wing shape variation (CV1 = 60.4%, CV2 = 22.4%). These differences in wing shape were supported by the permutations test for distances by Mahalanobis for males (P < 0.001) and females (P < 0.001) (Fig 6). Wing shape in function of the altitudinal gradient for males (F = 3.8251; Df = 3; P = 0.0001) and females (F = 3.5457; Df = 3 P = 0.0001) were significant Table 3.

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Fig 6. CVA for wing shape in the altitudinal gradient: (A) Females. (B) Males.

https://doi.org/10.1371/journal.pone.0228975.g006

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Table 3. ANOVA of Procrustes for wing shape in function of the altitudinal gradient for males and females of A. aegypti.

https://doi.org/10.1371/journal.pone.0228975.t003

The bilateral symmetry test for wing shape indicated no significant variation between the left and right sides for males (Side P = 0.377) and females (Side P = 0.207) of A. aegypti. On the contrary, the variation among individuals, side and its interaction, was indeed significant for males (Individuals P = 0.001, Side*Individual P = 0.001; Table 4 and females (Individuals P = 0.001, Side*Individual P = 0.001; Table 5. For the CS, the bilateral symmetry test indicated variation among individuals, between sides and its interaction for males (Side P = 0.001, Individuals P = 0.001, Side*Individual P = 0.001) and females (Side P = 0.001, Individuals P = 0.001, Side*Individual P = 0.001).

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Table 4. ANOVA of Procrustes for the shape and centroid size of wings in males of A. aegypti.

https://doi.org/10.1371/journal.pone.0228975.t004

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Table 5. ANOVA of procrustes for shape and centroid size on wings of females of A. aegypti.

https://doi.org/10.1371/journal.pone.0228975.t005

4. Discussion

To our knowledge, this is the first work on an altitudinal gradient in the Andean region identifying differences for wing size and shape of A. aegypti males and females in an altitudinal gradient. This is a pattern previously observed in females from Culex theileri [18] and Aedes vexans [32], West Nile virus and Valley fever vectors, respectively. In C. theileri, it was found that wing size and altitude are correlated positively, while in A. vexans, these differences were observed for wing size and shape through the altitudinal gradient. Additionally, in C. theileri and A. vexans, these differences were noted in altitudinal gradients from 808 to 2,130 m (with a difference of 1,322 m) and 808 to 1,620 m (with a difference of 812 m), respectively. Curiously in our case, said difference was observed within an altitudinal range from 1,200 to 1,700 m with a difference of 500 m. For both species, the differences observed regarding wing shape or size could be attributed to variables, like relative humidity and temperature. In turn, in A. aegypti, the wing shape and size variation observed may be due to the influence of temperature. In this species, under laboratory conditions, it has been noted that larvae subjected to temperatures between 24 and 35 °C have generated males and females with larger wing size in temperatures from 24 to 25 °C, while at temperatures from 34 to 35 °C, males and females have been obtained with smaller wing size [67]. According to Instituto de Hidrología, Meteorología y Estudios Ambientales (IDEAM) and Unidad de Planeación Minero Energética (UPME)) [68], historical means annual temperatures between 1981 and 2010 for altitudes in our study of 1,200, 1,400, 1,500, and 1,700 m are 20–22 °C, 20–22 °C, 16–20 °C, and 20–24 °C, respectively. However, for our case, smaller wings were observed at altitudes between 1,200 and 1,500 m for males and females. Bigger wings were found females at 1,400 m and for males between 1,400 and 1,700 m, which differs from the study already mentioned. Probably, this disparity may be attributed to other variables not measured in this study, like larval density and availability of food. In A. aegypti males and females, it was experimentally observed that wing size is correlated negatively in function of the larval density, and positively in function of the availability of food, [69], hence, expecting that with a higher larval density, mosquitoes will have a smaller wing size, and with greater availability of food, there will be bigger individuals.

Previously, in A. aegypti, it was noted that females with bigger wings have higher survival and greater amount of feeding events through blood [70] and, thereby, increase the probability of transmitting some type of arbovirus [14]. This study did not measure wing length; nonetheless, it has been evidenced that CS has a linear relation with traditional wing length measurements [28], hence, higher CS values would indicate longer wings. In our case, higher CS were found at 1,400 m (Armenia), a city that has historically reported a higher number of dengue cases for the department of Quindío [71].

Furthermore, sexual dimorphism, allometry, and fluctuating asymmetry were found between both sexes for wing size and shape of A. aegypti. Sexual dimorphism, is a pattern previously observed in morphometric studies for wing shape and size in other Culicidae species [7275]. Our results suggest allometry between wing size and shape of both sexes, which has been observed in A. aegypti [76], as well as in other Culicidae species [27, 77]. Results obtained of fluctuating asymmetry indicate that the wings of both sexes of A. aegypti do not have directionality. The fluctuating asymmetry in mosquitoes can be attributed to environmental pressures [78], among them, vector control in urban zones could be one of them, given that previously resistance was detected to organophosphorus compounds, a class of insecticide commonly used for larval control in some of the sampling zones evaluated herein [79].

5. Conclusion

In a small scale and in an altitudinal gradient of the Colombian Andes, we found that geometric morphometry permits identifying phenotypic variation for A. aegypti wing size and shape. Geometric morphometry studies on wing variation could be used by vector control programs as a diagnostic tool to quantify the dispersion and vector capacity of A. aegypti. Future studies must be carried out to test if wing size is related with the vector capacity in this species.

Acknowledgments

Gratitude is expressed to the Biology Program and the Center of Studies and Research on Biodiversity and Biotechnology at Universidad del Quindío (CIBUQ) for providing reagents and equipment, as well as the Health Secretary of Armenia for its support and suggestions during the sampling.

We also thank the members of the Center of Research on Tropical Diseases (CINTROP) for their help and training in identifying the mosquitoes.

This work is dedicated to the memory of the grandmother (La Plita) of Víctor Hugo, who reached the age of 100 years by the time this research ended.

References

  1. 1. Khormi HM, Kumar L. Climate change and the potential global distribution of Aedes aegypti: spatial modelling using GIS and CLIMEX. Geospatial health. 2014;8(2):405–15. https://doi.org/10.4081/gh.2014.29. pmid:24893017
  2. 2. World Health Organization. Global strategy for dengue prevention and control 2012–2020. Geneva: WHO. 2012.
  3. 3. Marchette NJ, Garcia R, Rudnick A. Isolation of Zika virus from Aedes aegypti mosquitoes in Malaysia. The American journal of tropical medicine and hygiene. 1969;18(3):411–5. pmid:4976739
  4. 4. Pialoux G, Gaüzère BA, Jauréguiberry S, Strobel M. Chikungunya, an epidemic arbovirosis. The Lancet infectious diseases. 2007;7(5):319–27. https://doi.org/10.1016/S1473-3099(07)70107-X. pmid:17448935
  5. 5. Ruiz-López F, González-Mazo A, Vélez-Mira A, Gómez GF, Zuleta L, Uribe S, et al. Presencia de Aedes (Stegomyia) aegypti (Linnaeus, 1762) y su infección natural con el virus del dengue en alturas no registradas para Colombia. Biomédica. 2016;36(2):303–8. https://doi.org/10.7705/biomedica.v36i2.3301.
  6. 6. Rodríguez Diego JG, Olivares JL, Sánchez Castilleja Y, Alemán Y, Arece J. Cambios climáticos y su efecto sobre algunos grupos de parásitos. Revista de Salud Animal. 2013;35(3):145–50.
  7. 7. Hopp MJ, Foley JA. Global-scale relationships between climate and the dengue fever vector, Aedes aegypti. Climatic change. 2001;48(2–3):441–63.
  8. 8. Leisnham PT, Sala LM, Juliano SA. Geographic variation in adult survival and reproductive tactics of the mosquito Aedes albopictus. Journal of medical entomology. 2014;45(2):210–21.
  9. 9. Maciel-de-Freitas R, Codeco CT, Lourenço-de-Oliveira R. Body size-associated survival and dispersal rates of Aedes aegypti in Rio de Janeiro. Medical and Veterinary Entomology. 2007;21(3):284–92. https://doi.org/10.1111/j.1365-2915.2007.00694.x. pmid:17897370
  10. 10. Sumanochitrapon W, Strickman D, Sithiprasasna R, Kittayapong P, Innis BL. Effect of size and geographic origin of Aedes aegypti on oral infection with dengue-2 virus. The American journal of tropical medicine and hygiene. 1998;58(3):283–6. https://doi.org/10.4269/ajtmh.1998.58.283. pmid:9546404
  11. 11. Xue RD, Barnard DR, Schreck CE. Influence of body size and age of Aedes albopictus on human host attack rates and the repellency of deet. Journal of the American Mosquito Control Association. 1995;11(1):50–3. pmid:7616190
  12. 12. Briegel H, Timmermann SE. Aedes albopictus (Diptera: Culicidae): physiological aspects of development and reproduction. Journal of medical entomology. 2001;38(4):566–71. https://doi.org/10.1603/0022-2585-38.4.566. pmid:11476337
  13. 13. Alto BW, Lounibos LP, Mores CN, Reiskind MH. Larval competition alters susceptibility of adult Aedes mosquitoes to dengue infection. Proceedings of the Royal Society of London B: Biological Sciences. 2008;275(1633):463–71. http://dx.doi.org/10.1098/rspb.2007.1497.
  14. 14. Alto BW, Reiskind MH, Lounibos LP, hygiene. Size alters susceptibility of vectors to dengue virus infection and dissemination. The American journal of tropical medicine and hygiene. 2008;79(5):688–95.
  15. 15. Abul-Hab J. Larvae of culicine mosquitos in north Iraq (Diptera, Culicidae). Bulletin of entomological research. 1967;57(2):279–84. https://doi.org/10.1017/S0007485300049981. pmid:4382531
  16. 16. Hoffmann AA, Ratna E, Sgro CM, Barton M, Blacket M, Hallas R, et al. Antagonistic selection between adult thorax and wing size in field released Drosophila melanogaster independent of thermal conditions. Journal of evolutionary biology. 2007;20(6):2219–27. https://doi.org/10.1111/j.1420-9101.2007.01422.x. pmid:17887974
  17. 17. Dapporto L, Bruschini C, Baracchi D, Cini A, Gayubo SF, Gonzalez JA, et al. Phylogeography and counter-intuitive inferences in island biogeography: evidence from morphometric markers in the mobile butterfly Maniola jurtina (Linnaeus)(Lepidoptera, Nymphalidae). Biological Journal of the Linnean Society. 2009;98(3):677–92. https://doi.org/10.1111/j.1095-8312.2009.01311.x.
  18. 18. Demirci B, Lee Y, Lanzaro GC, Alten B. Altitudinal genetic and morphometric variation among populations of Culex theileri Theobald (Diptera: Culicidae) from northeastern Turkey. Journal of Vector Ecology. 2012;37(1):197–209. https://doi.org/10.1111/j.1948-7134.2012.00217.x. pmid:22548554
  19. 19. Alexander RD. Sound production and associated behavior in insects. The Ohio Journal of Science. 1957;57(2):101–13.
  20. 20. Belton P. Attractton of male mosquitoes to sound. J Am Mosq Control Assoc. 1994;10:297–301.
  21. 21. Roth LM. A study of mosquito behavior. An experimental laboratory study of the sexual behavior of Aedes aegypti (Linnaeus). J The American Midland Naturalist. 1948;40(2):265–352.
  22. 22. Mohammed A, Chadee DD. Effects of different temperature regimens on the development of Aedes aegypti (L.) (Diptera: Culicidae) mosquitoes. Acta tropica. 2011;119(1):38–43. https://doi.org/10.1016/j.actatropica.2011.04.004. pmid:21549680
  23. 23. Tun‐Lin W, Burkot T, Kay B. Effects of temperature and larval diet on development rates and survival of the dengue vector Aedes aegypti in north Queensland, Australia. Medical and veterinary entomology. 2000;14(1):31–7. https://doi.org/10.1046/j.1365-2915.2000.00207.x. pmid:10759309
  24. 24. Lambrechts L, Paaijmans KP, Fansiri T, Carrington LB, Kramer LD, Thomas MB, et al. Impact of daily temperature fluctuations on dengue virus transmission by Aedes aegypti. Proceedings of the National Academy of Sciences. 2011;108(18):7460–5. https://doi.org/10.1073/pnas.1101377108.
  25. 25. Wilke ABB, de Oliveira Christe R, Multini LC, Vidal PO, Wilk-da-Silva R, de Carvalho GC, et al. Morphometric wing characters as a tool for mosquito identification. PloS one. 2016;11(8):e0161643. https://doi.org/10.1371/journal.pone.0161643. pmid:27551777
  26. 26. Bookstein FL. Morphometric tools for landmark data: geometry and biology: Cambridge University Press; 1991.
  27. 27. Vidal PO, Carvalho E, Suesdek L. Temporal variation of wing geometry in Aedes albopictus. Memórias do Instituto Oswaldo Cruz. 2012;107(8):1030–4. https://dx.doi.org/10.1590/S0074-02762012000800011. pmid:23295754
  28. 28. Vargas REM, Ya-umphan P, Phumala-Morales N, Komalamisra N, Dujardin J-P. Climate associated size and shape changes in Aedes aegypti (Diptera: Culicidae) populations from Thailand. Infection, Genetics and Evolution. 2010;10(4):580–5. https://doi.org/10.1016/j.meegid.2010.01.004. pmid:20123039
  29. 29. Carvajal JJ, Moncada Ll, Rodríguez MH, L. PdP, Olano VA. Caracterización preliminar de los sitios de cría de Aedes (Stegomyia) albopictus (Skuse, 1894)(Diptera: Culicidae) en el municipio de Leticia, Amazonas, Colombia. Biomédica. 2009;29(3). https://doi.org/10.7705/biomedica.v29i3.13.
  30. 30. Sendaydiego JP, Torres MAJ, Demayo CG. Describing wing geometry of Aedes aegypti using landmark-based geometric morphometrics. International Journal of Bioscience, Biochemistry and Bioinformatics. 2013;3(4):379.
  31. 31. Oliveira Paloma, S Lincoln. Comparison of wing geometry data and genetic data for assessing the population structure of Aedes aegypti. Infection, Genetics and Evolution. 2012;12(3):591–6. https://doi.org/10.1016/j.meegid.2011.11.013. pmid:22178147
  32. 32. Kuclu O, Aldemir A, Demirci B. Altitudinal variation in the morphometric characteristics of Aedes vexans Meigen from northeastern Turkey. Journal of Vector Ecology. 2011;36(1):30–41. https://doi.org/10.1111/j.1948-7134.2011.00138.x. pmid:21635639
  33. 33. Prudhomme J, Velo E, Bino S, Kadriaj P, Mersini K, Gunay F, et al. Altitudinal variations in wing morphology of Aedes albopictus (Diptera, Culicidae) in Albania, the region where it was first recorded in Europe. Parasite. 2019;26.
  34. 34. Cassab A, Morales V, Mattar S. Climatic factors and cases of dengue in Monteria, Colombia: 2003–2008. Revista de Salud Pública. 2011;13(1):115–28.
  35. 35. Gobernación del Quindio. Ficha basica municipal La Tebada 2017 [cited 2019 September 09]. https://www.quindio.gov.co/observatorio-departamental-del-quindio/fichas-basicas-municipales/fichas-la-tebaida.
  36. 36. Gobernación del Quindio. Ficha basica municipal Filandia, 2017 [cited 2019 September 09]. https://www.quindio.gov.co/observatorio-departamental-del-quindio/fichas-basicas-municipales/filandia.
  37. 37. Gobernación del Quindio. Análisis de la situación del departamento del Quindío 2012 [cited 2019 September 09]. https://www.minsalud.gov.co/plandecenal/mapa/Analisis-de-situacion-de-salud-del-departamento-del-Quindio.pdf.
  38. 38. Fick S HJ. Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology. International journal of climatology. 2017;37(12):4302–15.
  39. 39. Ewing A CA, Purse V, Nunn M, White S. Modelling the effect of temperature on the seasonal population dynamics of temperate mosquitoes. Journal of theoretical biology. 2016;(400):65–79. pmid:27084359
  40. 40. Huber J CM, Caldwell J, Mordecai E. Seasonal temperature variation influences climate suitability for dengue, chikungunya, and Zika transmission. Plos Negl Trop Dis. 2018;12(5). pmid:29746468
  41. 41. Hijmans RJ, Van Etten J, Cheng J, Mattiuzzi M, Sumner M, Greenberg JA, et al. Package ‘raster’. R package 2015;734.
  42. 42. Forattini OP. Culicidologia médica: identificação, biologia, epidemiologia Vol. 2: Edusp; 1996.
  43. 43. Rueda LM. Pictorial keys for the identification of mosquitoes (Diptera: Culicidae) associated with Dengue Virus Transmission. Zootaxa. 2004;589(1):1–60.
  44. 44. Lorenz C, Suesdek L. Evaluation of chemical preparation on insect wing shape for geometric morphometrics. The American journal of tropical medicine and hygiene. 2013;89(5):928–31. https://doi.org/10.4269/ajtmh.13-0359. pmid:24019438
  45. 45. Dos-Santos EB. Estrutura da comunidade de culicidae (Insecta: Diptera) em área de Mata Atlântica do Paraná [M.Sc.]: Universidade federal do Paraná; 2016.
  46. 46. Zelditch ML, Swiderski DL, Sheets HD. Geometric morphometrics for biologists: a primer: Academic Press; 2012.
  47. 47. Guedes MLP. Análise de fatores regulatórios na variação interpopulacional e na composição das comunidades de culicidae (Diptera) [PhD]: Universidade Federal do paraná; 2014.
  48. 48. Rohlf J, Slice D. Extensions of the Procrustes method for the optimal superimposition of landmarks. Systematic Biology. 1990;39(1):40–59.
  49. 49. Rohlf FJ. tpsUtil, file utility program, version 1.7. Department of Ecology and Evolution, State University of New York at Stony Brook. 2016.
  50. 50. Rohlf F. TPSDig2: a program for landmark development and analysis. Department of Ecology and Evolution, State University of New York, Stony Brook. 2001.
  51. 51. Klingenberg CP. MorphoJ: an integrated software package for geometric morphometrics. Molecular ecology resources. 2011;11(2):353–7. pmid:21429143
  52. 52. Gower JC. Generalized procrustes analysis. Psychometrika. 1975;40(1):33–51.
  53. 53. Yezerinac SM, Lougheed SC, Handford P. Measurement error and morphometric studies: statistical power and observer experience. Systematic Biology. 1992;41(4):471–82. https://doi.org/10.1093/sysbio/41.4.471.
  54. 54. Claude J. Morphometrics with R: Springer Science & Business Media; 2008. 317 p.
  55. 55. Fruciano C. Measurement error in geometric morphometrics. Development genes and evolution. 2016;226(3):139–58. pmid:27038025
  56. 56. Drake AG, Klingenberg CP. The pace of morphological change: historical transformation of skull shape in St Bernard dogs. Proceedings of the Royal Society B: Biological Sciences. 2007;275(1630):71–6. https://doi.org/10.1098/rspb.2007.1169.
  57. 57. Good P. Permutation tests: a practical guide to resampling methods for testing hypotheses: Springer Science & Business Media; 2013.
  58. 58. Goodall C. Procrustes methods in the statistical analysis of shape. Journal of the Royal Statistical Society Series B (Methodological). 1991:285–339. https://doi.org/10.1111/j.2517-6161.1991.tb01825.x.
  59. 59. Klingenberg CP, Leamy LJ. Quantitative genetics of geometric shape in the mouse mandible. Evolution. 2001;55(11):2342–52. pmid:11794792
  60. 60. Mardia KV, Bookstein FL, Moreton IJJB. Statistical assessment of bilateral symmetry of shapes. Biometrika. 2000;87(2):285–300.
  61. 61. R Development CoreTeam. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2018.
  62. 62. Adams DC, Otárola-Castillo E. geomorph: an R package for the collection and analysis of geometric morphometric shape data. Methods in Ecology and Evolution. 2013;4(4):393–9. https://doi.org/10.1111/2041-210X.12035.
  63. 63. Wickham H, François R, Henry L, Müller K. dplyr: A Grammar of Data Manipulation. R package version 0.8. 0.1. ed; 2019.
  64. 64. Mangiafico S, Mangiafico MS. Package ‘rcompanion’. CRAN package repository. 2017:1–71.
  65. 65. Mangiafico SS. An R companion for the handbook of biological statistics. rcompanion org/documents/RCompanionBioStatistics pdf. 2015.
  66. 66. Graves S, Piepho H-P, Selzer L, Dorai-Raj S. multcompView: visualizations of paired comparisons. R package version 01–7. 2015.
  67. 67. Mohammed A, Chadee D. Effects of different temperature regimens on the development of Aedes aegypti (L.) (Diptera: Culicidae) mosquitoes. Acta tropica. 2011;119(1):38–43. pmid:21549680
  68. 68. Instituto de Hidrología MyEAIUdPMEU. Atlas Climatológico de Colombia 2020 [cited 2020 May 22]. http://atlas.ideam.gov.co/visorAtlasClimatologico.html.
  69. 69. Jirakanjanakit N, Leemingsawat S, Thongrungkiat S, Apiwathnasorn C, Singhaniyom S, Bellec C, et al. Influence of larval density or food variation on the geometry of the wing of Aedes (Stegomyia) aegypti. Tropical Medicine & International Health. 2007;12(11):1354–60.
  70. 70. Nasci RS. The size of emerging and host-seeking Aedes aegypti and the relation of size to blood-feeding success in the field. J Am Mosq Control Assoc. 1986;2(1):61–2. pmid:3507471
  71. 71. Muñoz LGD. Incidencia del Dengue en el departamento del Quindio 1999–2010. Hospitium. 2015;2.
  72. 72. Virginio F, Vidal PO, Suesdek L. Wing sexual dimorphism of pathogen-vector culicids. Parasites & Vectors. 2015;8(1):159.
  73. 73. Sanchez E, Castillo D, Liria J. Pupal shape and size dimorphism in Aedes albopictus (Skuse, 1894) (Diptera: Culicidae). Journal of Threatened Taxa. 2017;9(6):10314–9.
  74. 74. Oliveira Christe R, Wilke ABB, Vidal PO, Marrelli MT. Wing sexual dimorphism in Aedes fluviatilis (Diptera: Culicidae). Infection, Genetics and Evolution. 2016;45:434–6. https://doi.org/10.1016/j.meegid.2016.10.007. pmid:27746293
  75. 75. Devicari M, Lopes AR, Suesdek L. Wing sexual dimorphism in Aedes scapularis (Diptera: Culicidae). Biota Neotropica. 2011;11(2):165–9.
  76. 76. Jirakanjanakit N, Leemingsawat S, Dujardin JP. The geometry of the wing of Aedes (Stegomyia) aegypti in isofemale lines through successive generations. Infection, Genetics Evolution. 2008;8(4):414–21. pmid:17600773
  77. 77. Garzón MJ, Schweigmann N. Morphometric Variation of the Aedes albifasciatus (Diptera: Culicidae) Wings in Three Populations From Different Ecoregions of Argentina. Journal of medical entomology. 2018;55(6):1602–6. pmid:29939291
  78. 78. Galbo KR, Tabugo SRM. Fluctuating asymmetry in the wings of Culex quinquefasciatus (Say) (Diptera: Culicidae) from selected barangays in Iligan City, Philippines. Aquaculture, Aquarium, ConservationLegislation. 2014;7(5):357–64.
  79. 79. Aguirre-Obando OA, Bona ACD, Duque L, Jonny E, Navarro-Silva MA. Insecticide resistance and genetic variability in natural populations of Aedes (Stegomyia) aegypti (Diptera: Culicidae) from Colombia. Zoologia. 2015;32(1):14–22.