Spatial distribution of forensically significant blow flies in subfamily luciliinae (Diptera: Calliphoridae), Chiang Mai province, northern Thailand: Observations and modeling using GIS

Abstract

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. 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 (PMI min ), 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.