Research Article  Open Access
Ecological Determinants of Forest to the Abundance of Lutzomyia longiflocosa in Tello, Colombia
Abstract
Lutzomyia longiflocosa is considered the most likely vector of cutaneous leishmaniasis in the subAndean region of the upper valley of the Magdalena River between 1,000 and 2,000 meters in the Department of Huila, Colombia. L. longiflocosa is anthropophilic, has endophagic behavior, and is especially important since its dominance in epidemics recorded in the last decade in the departments of Huila, Tolima, and the outbreak in Norte de Santander. The aim of our work is to identify ecological determinants in forest microhabitat level defining the abundance of L. longiflocosa. We use sampling; this was performed in 56 microhabitats of 28 forests with CDC traps for two consecutive nights from 18:00 to 06:00 hours. Each microhabitat (favorable and unfavorable) was located 10 m from the ecotone, with an approximate area of 10 m^{2}. Thirtyfive variables were examined as potential explanatory variables which were recorded in each microhabitat. Regression models were used to identify ecological determinants. Our results confirm that there are favorable microhabitats in the forest with specific ecological determinants that define the aggregated distribution of the species and provide the conditions necessary for survival and abundance of L. longiflocosa.
1. Introduction
Cutaneous leishmaniasis (CL) is the clinical form recorded more frequently in Colombia with more than 95% of reported cases [1, 2]. The leishmaniasis is caused by infection of parasites to the genus Leishmania and is transmitted by the bite of infected female sand flies to the genus Lutzomyia; this disease affects skin, initially comes off as a grain, and, with the passing of more days, continues to grow in a circular form until ulcers shape [3–5]. In the subAndean region of Valle Alto Magdalena River between 1,000 and 2,000 meters, Lutzomyia longiflocosa species OMOM, Psychodidae Family [6], is considered the most likely vector for its anthropophilic behavior, blood meal inside homes or endophagic behavior [7] and especially its dominance in epidemics recorded in the last decade in the departments of Huila and Tolima and the outbreak of Norte de Santander [1, 2, 7–10]. Because of its importance in public health, there have been studies that have established aggregate species distribution and abundance of regional and local ecological determinants. Knowing the dynamics of abundance of sand fly, we can partially predict the occurrence of the disease and lower the risk and the impact on humans. Among regional determinants detected, L. longiflocosa has higher abundance between 1300 and 1700 m, with temperature ranges between C and C and negative association with precipitation. Locally, L. longiflocosa is found in forests, particularly those located in relatively inclined sites within the first four arboreal strata, protected from wind and with high percentage of litter [9]. Therefore, we propose aims to identify the ecological determinants in the forest microhabitat level favoring the abundance of L. longiflocosa and start the knowledge of temporal patterns vector of cutaneous leishmaniasis in the municipality of Tello, Huila, Colombia.
2. Materials and Methods
2.1. Study Area
The study was conducted in the forests of the villages of La Urraca, La Brasilia, Alto Urraca, Medio Roblal, and Alto Roblal, which recorded high prevalence of CL during the epidemic of 1993–1996, located on the western flank of the Cordillera Oriental between the 2nd and 3rd 09′ 94′ N latitude and 74° 91′ and 75° 23′ W longitude in the municipality of Tello, Huila Department (Figure 1). Most forests have a height between 20 and 35 m; 2.5 arboreal strata now reach 93% of the soil, with litter average coverage of 87% and depth of 8.4 cm [9]. The study area is classified as Rainforest Premontano bhpM [11], with an average annual rainfall of 1346 mm and annual average temperature of C Station: El Portal, code: 2111507, PalacioVegalarga, code: 2111510, and Laureles, code: 2111514 [12]. The criteria for inclusion of forests were located between 1300 and 2100 meters, not less than 0.35 hectares area (maximum recorded area was 1.2 ha) and nonintervention antropic. In each forest, taking into account ecological determinants abundance, two microhabitats located within 10 m of ecotone that are the most productive were selected [9], each with an area of 10 m^{2} and a distance between them of not less than 40 m. One of them was designated as a favorable microhabitat and the other unfavorable; the favorable had three or more features described below and the unfavorable had only two or less:(i)Presence of trees with diameter breast height (DBH) greater than 30 cm.(ii)Trees with rough bark and roots tabloids.(iii)Thick layer of undecomposed litter more than 5 cm deep.(iv)High coverage, greater than 80% for plants larger than 5 m height.(v)Windsheltered microhabitats.
2.2. Explanation for Abundance in the Forest Level Microhabitat Variables
Thirtyfive variables were examined as potential explanatory variables; four of these had been previously identified as ecological determinants abundance of L. longiflocosa: (i) tree cover, (ii) litter depth, (iii) wind barrier, and (iv) distance to the nearest housing [9]. The new variables were related to coverage of shrubs, plants, and grasses; characteristics of trees as DBH, height, roots, leaves, bark type, and presence of holes in the trunk are shown in Table 1.

2.3. Trapping for Sand Flies
Sampling was performed in each microhabitat for two consecutive nights between 18:00 and 06:00 hours, using CDC light trap [13], about 1.5 m in height from ground level.
2.4. Analysis of Information
For data analysis, the STATISTIX software (version 1.0) and MATLAB 2012 are used for this purpose initially. Excel databases (version 4.0) to be exported to the software were developed. To verify data normality test Bartlett was performed [14]. Ecological determinants to detect four types of statistical analysis described below were used:(1)To confirm whether the microhabitats designated as favorable at baseline showed higher abundance of L. longiflocosa than statistically calculated, an adverse descriptive statistical analysis was performed based on averages, standard deviation, standard error of the mean, maximum and minimum. Due to the variability of the data, a logarithmic transformation was performed to normalize the data; the statistical analysis was performed by completely random models (ANOVA and MATLAB) factorial arrangements where forests worked as a factor and the microhabitat as factor . Averages with significant differences () underwent the unplanned Tukey test.(2)To identify the ecological determinants favoring the abundance of L. longiflocosa in microhabitats, Pearson correlation coefficients were between the number of L. longiflocosa and explanatory variables. Likewise, a multiple linear regression model step in which the variables recorded greater contribution to the model , until finally the determinants that most explained the abundance of L. longiflocosa were identified. Likewise, a model of nonlinear multiple regression type of 2ndorder polynomial to detect the determinants that most contributed to the model was performed.(3)To determine differences in ecological determinants among the most abundant forests and not recording the presence of L. longiflocosa completely random analysis (ANOVA, MATLAB) and averages with significant difference the proof unplanned Tukey test averages were performed.(4)To compare the four most productive microhabitats with its counterpart in the same forest, a multiple linear regression model step in which those variables were recorded that showed a greater contribution to the model .
3. Results
3.1. Species Composition
In total, 28 forests in which 112 samples were taken and copies of Lutzomyia 3460 and 2519 were collected in the favorable and the unfavorable microhabitat 941, divided into 9 species, were sampled. L. longiflocosa was the most abundant species with 92.4% , followed by L. nuneztovari O. with 5.3% , found with less than 1% L. trinidadensis N. species , Helcocyrtomyia sp. , L. columbiana R.V. , L. atroclavata K. , L. pia F.H. , L. dubitans S. , and L. lichyi F.A. . Only four forests recorded more than six species and and five were negative. L. longiflocosa was found in 23 forests. Considering that the species L. longiflocosa is being considered and represented 92.4% of the collection, the results are shown only for this species.
3.2. Abundance and Distribution of Forest and Microhabitat
To the abundance of L. longiflocosa in the forest, 8 groups of statistically significant forests were presented; the first group was only represented by forest 14 with the highest average of 314.5 specimens, in the second group was ranked forest 1 with average of 122.8 , the third group was formed by forests 15 and 13 with averages of 84.3 and 76.3 , respectively, and in the remaining five groups were placed 24 forests with averages below 50 copies . Furthermore, significant differences in the abundance of L. longiflocosa by favorable and unfavorable microhabitat averaging 41.73 and 15.35 specimens, respectively , were found. Of the 23 forests in which L. longiflocosa was recorded in 18, abundance in the favorable microhabitat was higher than the unfavorable.
3.3. Specific Ecological Determinants in the Forest Microhabitat Level
Thirtyfive explanatory variables defined in the study and nine determinants that directly explain the abundance of L. longiflocosa in microhabitats were identified as ecologically important. Through Pearson correlations, linear regression model step by step, ANOVA, and MATLAB model nonlinear regression were detected: the trees submit holes with radius 5 cm to 20 cm, bark scaly, foliage between 11 m and 20 m and bark rough, the latter determining favored L. longiflocosa abundance in favorable with respect to microhabitats of the most abundant unfavorable forests. Determining the remaining 6 was done by a single statistical analysis [15, 16]. The linear regression model explained 68.94% of the abundance of L. longiflocosa with the 9 detected ecological determinants, while the nonlinear regression model explained 89% with two determinants: holes with radius 5 cm to 20 cm and bark with scales as in Table 2.
 
CP: Pearson correlation. : Pearson correlation coefficient (: 0.31 and 0.6 correlation accepted, : 0.61 and 0.8 [good correlation]). MLRMF: Multiple Linear Regression Model Footsteps. : determination coefficient. ANOVAMATLAB: Analysis of Variance. : value. NRML: Nonlinear Regression Model. : determination coefficient. : probability value; and ; and . Ni: not identified by the statistical analysis. 
4. Discussion
The strengths of this study were as follows: (i) sampling the inclusion of the 28 existing relict forests between 1300 and 2100 asl in the villages of the municipality of Tello affected by the epidemic CL, (ii) the prior identification of regional and local ecological determinants favoring the definition of the criteria for selection of favorable and unfavorable sites, (iii) CDC light trap confirming as an appropriate technique that collects abundance of L. longiflocosa in subAndean of Colombian region, (iv) the previous definition of the height at 1.5 m ground level, (v) prior definition of the location of the CDC light trap in the ecotone forest to greater abundance, and (vi) negative association with precipitation which defined the sampling month [9].
Species richness was low as was expected by the altitudinal range selected in this study and the sampling method because it is aimed at the sand fly attracted to light. However, other collection methods, such as human bait, were not used to avoid a possible transmission of the disease. CDC light tramp was used by the representative in the collection of L. longiflocosa in this region [9], which was demonstrated in this study, a dominance of 92.4%; L. nuneztovari, L. columbiana, and L. pia and five other species of other subgenres plus three more species of verrucarum group were captured.
The 9 specific ecological determinants in the forest microhabitat level identified for abundance of L. longiflocosa partially explain the aggregated distribution of this species. It was assumed that those determinants, together with regional and local ecological factors identified previously [9], generate microclimate forests which are suitable places for survival and abundance of the species, specifically (i) resting sites and places for reproduction and (ii) potential breeding sites where the life cycle develops. According to Cabanillas and Castellón [17], morphological characteristics of the bark can influence Lutzomyia species in the choice of resting places, as in the case of L. umbratilis W.F. found in bark with grooves [18]; this situation is according to Memmott who suggests that aggregate Lutzomyia species in forest trees distribution is not random but is due to a shortlist of trees used as daytime resting site [19].
In this study, for the rest of the L. longiflocosa activities it was considered that the determinants’ scaly bark trees and trees with rough bark had a significant contribution as in Table 2. In like manner, possibly presenting gaps trees radio 5 cm to 20 cm contributed significantly to rest sites because studies indicate Lutzomyia species using this microhabitat as resting place, L. vespertilionis F.H. [18, 19], L. trapidoi F.H. captured in tree hollows below 2 m high [20], L. shannoni D. [18, 20–23] in holes with diameters between 40 cm and 80 cm [24], L. spinicrassa M.O.O.H. and L. gomezi N. [23] and L. isovespertilionis F.H. [25]. Determining the ecological determinants’ roots with lower correlation tabloids possibly also provided resting sites, since according to Memmott in certain areas the Lutzomyia roots are aggregated in tabloids root and also have vertical zoning. The remaining determinants, number of trees, DBH greater than 41 cm, foliage between 11 m and 20 m, and trees with height between 3 m and 40 m, together with the determinants of higher correlation, were considered which remained within the microhabitat favorable microclimatic conditions [19]. Breeding sites have not been found in this study, but the obtained data suggests that they might be identical to the bedding locations for adults or very close to them as it also was reported for other Lutzomyia species [19]. In this study, between detected ecological determinants, the tabloids roots and holes with radius 5 cm to 20 cm provide a stableaspossible breeding site where the immature forms are kept in microenvironment. Hanson collected Lutzomyia larvae in the bases (tabloids roots) of big trees [26] and Thatcher using floating collection method larvae collected L. micropyga M. and L. disponeta F.H. in hollow shaft [27].
This study is the first to identify determinants in forest ecological level microhabitat for abundance of L. longiflocosa complementing the findings of regional and local ecological determinants for this species, allowing microhabitats as producers to focus areas of sand fly, in synergy with parasites which favors the transmission cycle of leishmaniasis. In conclusion, there are favorable microhabitats in the forest with specific ecological determinants such as holes with radius of 5 cm to 20 cm, scaly bark, rough bark, DBH greater than 41 cm, foliage between 11 m and 20 m, height between 21 m and 40 m, tree numbers, tabloids roots, and height between 11 and 21 m, which partially explain the aggregated distribution of Lutzomyia longiflocosa and provide the conditions necessary for survival and abundance of this species.
Conflict of Interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
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Copyright
Copyright © 2015 Ruthber Rodríguez Serrezuela and Luis Alexander Carvajal Pinilla. 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.