Spatial Distribution of Forensically Significant Blow Flies in Subfamily Luciliinae (Diptera: Calliphoridae), Chiang Mai Province, Northern Thailand: Observations and Modeling Using GIS - PubMed (original) (raw)

Spatial Distribution of Forensically Significant Blow Flies in Subfamily Luciliinae (Diptera: Calliphoridae), Chiang Mai Province, Northern Thailand: Observations and Modeling Using GIS

Tunwadee Klong-Klaew et al. Insects. 2018.

Abstract

Blow flies of the subfamily Luciliinae (Diptera: Calliphoridae) are one of the main forensically important subfamilies globally. In addition to being used to estimate the minimum post-mortem interval (PMImin), assuming colonization occurred after death, blow fly specimens found infesting a human corpse are used to determine if the corpse was relocated or if the individual ingested narcotics prior to death. The presence of these blow flies in a given area is strongly influenced by abiotic and biotic factors, such as temperature, elevation, and habitat. Having this information, along with geographical distributions and the characteristics of preferred habitats, is necessary to better understand the biology of this group. This study aimed to characterize the spatial distribution of Luciliinae throughout 18 sampling sites within six ecozones (disturbed mixed deciduous forest, mixed deciduous forest, mixed orchard, paddy field, lowland village, and city/town) in central Chiang Mai Province, northern Thailand over one year (May 2009⁻May 2010). The purpose of the study was to elucidate the relationship of blow fly species composition with environmental abiotic factors (e.g., temperature, relative humidity, light intensity), and to predict the distribution of the common species within this subfamily using GIS. Adult collections were performed biweekly, baited with one-day-old beef offal. A total of 2331 Luciliinae flies trapped, comprising eight species, of which the four predominant species were Hemipyrellia ligurriens (Wiedemann) (n = 1428; 61.3%), Lucilia porphyrina (Walker) (n = 381; 16.3%), Hemipyrellia pulchra (Wiedemann) (n = 293; 12.6%), and Lucilia papuensis Macquart (n = 129; 5.5%). Population density across species varied seasonally, peaking in August 2009 coinciding with the rainy season. Predicting population composition was based on a model developed with ArcGIS 9.2, which utilized environmental variables (temperature, relative humidity, and light intensity) in conjunction with abundance data. Models indicated H. ligurriens had the most widespread geographic distribution, while H. pulchra was predicted to occur largely in mixed orchards and lowland villages. Lucilia porphyrina and L. papuensis were less widespread, restricted mainly to mixed deciduous forest. This model, along with knowledge of forensic information, may be useful under certain investigations where the corpse may have been relocated.

Keywords: Hemipyrellia; Lucilia; Thailand; prediction; spatial distribution.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

Figures

Figure 1

Figure 1

Map of Thailand showing three sample districts (Mueang Chiang Mai, MU; Mae Rim, MR; and Hang Dong, HD) and 18 sample locations. Green shading indicates a mountainous zone.

Figure 2

Figure 2

Monthly fluctuations in trap catches of H. ligurriens, L. porphyrina, H. pulchra, and L. papuensis determined using a portable funnel trap baited with one-day-old beef offal in Chiang Mai Province, northern Thailand, May 2009 to May 2010 (A), and variation of temperature and relative humidity recorded during the fly survey (B).

Figure 3

Figure 3

Total number of flies captured at different temperature (A) and relative humidity ranges (B).

Figure 4

Figure 4

Predictive distribution maps of Hemipyrellia ligurriens. The color scheme reflects different fly density categories. The red areas indicate the highest fly population, while the green areas indicate the lowest population density. The scale corresponds to natural logarithm of (fly density + 1).

Figure 5

Figure 5

Predictive distribution maps of Lucilia porphyrina. The color scheme represented different fly density categories. The red areas represent the highest fly population, while the green represent the lowest population density. The scale corresponds to natural logarithm of (fly density + 1).

Figure 6

Figure 6

Predictive distribution maps of Hemipyrellia pulchra. The color scheme represented different fly density categories. The red areas represent the highest fly population, while the green represent the lowest population density. The scale corresponds to natural logarithm of (fly density + 1).

Figure 7

Figure 7

Predictive distribution maps of Lucilia papuensis. The color scheme represented different fly density categories. The red areas represent the highest fly population, while the green represent the lowest population density. The scale corresponds to natural logarithm of (fly density + 1).

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