Factors affecting quality of temperature models for the pre-appearance interval of forensically useful insects
Introduction
Postmortem interval (PMI) or more frequently minimum PMI may be estimated from development or succession of insects on cadavers [1], [2], [3]. While estimating PMI from immature insects, it is convenient to divide it into the development interval and the pre-appearance interval (PAI) [4], [5]. Most recent progress in the field refers to methods for the estimation of the development interval [6], [7], [8], [9], [10], [11], [12], [13], [14], [15]. As for the PAI, substantial progress was achieved in the area of volatile organic compounds attracting insects to carcasses [16], [17], [18], [19], [20]. Moreover, recent works demonstrated that PAI of several forensically useful insects is dependent on temperature prevailing throughout this interval [21], [22], [23], [24]. PAI was regularly found to decrease exponentially with an increase in temperature, which indicates that an exponential decrease is a general model for the association of PAI with temperature in forensically significant insects [22], [24].
A recent progress in understanding the relation between PAI and temperature resulted in the proposition to estimate PAI from temperature [4], [5], [22], [23], [24]. These estimates require regression models capturing the dependence of PAI on average preceding temperatures in particular insect species. Such models were recently elaborated for many European species of Coleoptera [22], few European species of Diptera [24] and some Australian species of Diptera or Coleoptera [23]. The temperature models for PAI may be used in casework to estimate PAI simply by using temperatures specific for a given case. Such estimates of PAI may eventually be used to formulate estimates of PMI with a succession-based or a development-based approach [4], [5].
The temperature models for PAI may be created only from results of highly replicated pig carcass studies with a PAI-oriented design. Unfortunately, such studies are costly and time-consuming, so it would be useful to know how to effectively reduce their costs. Moreover, previous results suggest that differences in methods between various PAI studies may result in differences between resultant temperature models for PAI [4], [5], [22], [23]. Accordingly, a more profound understanding of factors affecting quality of temperature models for PAI is needed. Such knowledge will help to specify best practice in the PAI field studies, similarly to other fields of forensic entomology [25], [26], [27], [28], [29], [30].
It seems that the frequency with which insects are sampled during field studies is one of the most important factors. Sampling frequency was found to have a direct influence on the accuracy of temperature models for the development of forensically useful flies [26], [31]. It may have similar effects on temperature models for PAI. We predict that the accuracy of PAI data decreases with decreasing frequency of insect sampling, which, in turn, affects the quality of temperature models for PAI. However, the extent of these effects and in particular robustness of the models to decreasing frequency needs to be investigated.
Another factor of probable high relevance is techniques of insect sampling. Several techniques were used in forensic field carrion studies, i.e. manual collections (by hand or entomological net) [32], [33], [34], [35], [36], [37], [38], [39], pitfall traps [32], [35], [36], [37], [40], sticky traps [32], [38], Malaise traps [41] or Schoenly traps [42], [43], [44]. However, very few studies compared their performance in a forensic context. Schoenly et al. [32] demonstrated that the combination of pitfall traps and hand collections has the highest efficiency in catching forensically important taxa during field carcass experiments. It was also found that Schoenly traps are more efficient in catching adult flies than traditional manual collections [42]. It is however unclear whether and to what extent sampling techniques may influence the accuracy of PAI data and resultant temperature models for PAI. We predict that these effects exist and may have adverse influence on the quality of temperature models for PAI.
The quality of temperature data used in the model for PAI is also of probable high importance. On-site hourly measurements are preferable [22], [23], [24], however weather station data were also used and after retrospective correction gave surprisingly good models [4], [5]. Consequently, it would be interesting to determine how seriously weather station data deteriorate models, and to what extent retrospective correction of temperature improves the models. It is of relevance that corrections of weather station temperatures were found to improve the accuracy with which these temperatures represent temperatures of the place where corpse has been found [45]. However some results suggest that these corrections have uncertain benefit when estimating PMI from the development of flies [46].
The last relevant factor of the current study is the number of carcasses comprising the sample used for modeling purposes. Because temperature cannot be manipulated in PAI field studies, a good design for such studies is of key importance. A reliable model for PAI should cover a broad range of temperatures, and to attain this goal researchers should address some issues concerning experimental design. In order to study PAI at different temperatures, recent experiments involved several placements of carcasses, separated in time [22], [23], [24]. For the same purpose carcasses were exposed in different habitats [22], [24]. Moreover, carcasses may be distributed over different seasons, months and years. From this point of view several interesting questions arise. Firstly, is it more efficient to separate carcasses in time or space? Secondly, how should we separate carcasses in time or space to get the best range of temperatures? One may predict that both types of separation are important, however their effectiveness in collecting PAI data at different temperatures is probably different. Thirdly, what is the minimal number of carcasses that will give acceptable models? A recent work of Archer [23] revealed that for some insects quite good models may be created from as few as 10 carcasses, although their quality was worse than models from highly replicated studies [4], [5], [22], [24]. So we predict that number of carcasses in PAI fields studies may be reduced to some extent without sacrificing the quality of resultant models.
Section snippets
Data used in the analyses
All models were made by using PAI data from a large scale, PAI oriented pig carcass study. Details on the experimental design and protocols for handling of carcasses, sampling of insects and temperature measurements were specified by Matuszewski and Szafałowicz [22] and Matuszewski et al. [24]. Below there is just a brief description of the most important points. Thirty pig carcasses were separated in time: 18 April (four pigs), 15 June (six pigs), 4 July (six pigs), 21 July (four pigs), 16
Sampling frequency
There were significant differences between models in the fit, the c parameter and the accuracy of estimates (Table 2 and Fig. 1). Models at lower frequencies displayed poorer fit, a systematic increase in the c parameter and a substantial increase in the error of estimates (Fig. 1). Models at very low frequency lacked the inherent variability in PAI (Fig. 2 and for further comparison see models published by Matuszewski and Szafałowicz [22]).
Sampling techniques
Models significantly differed according to the fit and
Sampling frequency and techniques
As expected, reduction of sampling frequency resulted in evident deterioration of models; however the size of this effect was a surprise. These results suggest that sampling frequency is one of the most important factors affecting quality of temperature models for PAI in carrion insects. Richards and Villet [31] demonstrated that low frequency of sampling reduced the accuracy of K and D0 calculations in a temperature model for the development of forensically important blowflies. Reduction of
Acknowledgements
Thanks are extended to K. Frątczak (Poznań, Poland), M. Jarmusz (Poznań, Poland), S. Konwerski (Poznań, Poland) and M. Szafałowicz (Warsaw, Poland) for help in field or laboratory work during 2011 or 2012 field studies, to K. Szpila (Toruń, Poland) for identification of adult and larval Stearibia nigriceps and to D. Bajerlein (Poznań, Poland) for identification of adult Saprinus semistriatus from 2012 experiment. We are also grateful to anonymous reviewers for their comments and suggestions,
References (47)
Estimating the pre-appearance interval from temperature in Necrodes littoralis L. (Coleoptera: Silphidae)
Forensic Sci. Int.
(2011)- et al.
Preliminary studies of the influence of fluctuating temperatures on the development of various forensically relevant flies
Forensic Sci. Int.
(2010) - et al.
Larval-mass effect: characterisation of heat emission by necrophageous blowflies (Diptera: Calliphoridae) larval aggregates
Forensic Sci. Int.
(2011) - et al.
Effect of different post-feeding intervals on the total time of development of the blowfly Lucilia sericata (Diptera: Calliphoridae)
Forensic Sci. Int.
(2012) - et al.
Virtual forensic entomology: improving estimates of minimum post-mortem interval with 3D micro-computed tomography
Forensic Sci. Int.
(2012) - et al.
Life history data on the fly parasitoids Aleochara nigra Kraatz and A. asiatica Kraatz (Coleoptera: Staphylinidae), and their potential application in forensic entomology
Forensic Sci. Int.
(2013) - et al.
Predicting the visitation of carcasses by carrion-related insects under different rates of degree-day accumulation
Forensic Sci. Int.
(2009) - et al.
Temperature-dependent appearance of forensically useful beetles on carcasses
Forensic Sci. Int.
(2013) - et al.
Annual and seasonal patterns of insect succession on decomposing remains at two locations in Western Australia
Forensic Sci. Int.
(2009) - et al.
Insect succession and carrion decomposition in selected forests of Central Europe. Part 3: succession of carrion fauna
Forensic Sci. Int.
(2011)
Insects colonising carcasses in open and forest habitats of Central Europe: search for indicators of corpse relocation
Forensic Sci. Int.
How promptly do blowflies colonise fresh carcasses? A study comparing indoor with outdoor locations
Forensic Sci. Int.
Coleoptera of forensic interest: a study of seasonal community composition and succession in Lisbon, Portugal
Forensic Sci. Int.
Seasonal structure and dynamics of sarcosaprophagous fauna on pig carrion in a rural area of Cordoba (Argentina): their importance in forensic science
Forensic Sci. Int.
Experimental and casework validation of ambient temperature corrections in forensic entomology
J. Forensic Sci.
Estimating the postmortem interval
Forensic entomology: applications and limitations
Forensic Sci. Med. Pathol.
Advances in entomological methods for death time estimation
Estimating the pre-appearance interval from temperature in Creophilus maxillosus L. (Coleoptera: Staphylinidae)
J. Forensic Sci.
Variation in developmental time for geographically distinct populations of the common green bottle fly, Lucilia sericata (Meigen)
J. Forensic Sci.
Diapause-specific gene expression in Calliphora vicina (Diptera: Calliphoridae) – a useful diagnostic tool for forensic entomology
Int. J. Leg. Med.
Strengthen forensic entomology in court-the need for data exploration and the validation of a generalised additive mixed model
Int. J. Leg. Med.
The analysis of temporal gene expression to estimate the age of forensically important blow fly pupae: results from three blind studies
Int. J. Leg. Med.
Cited by (15)
Estimating crime scene temperatures from nearby meteorological station data
2020, Forensic Science InternationalCitation Excerpt :Insects are poikilothermic and, therefore, the role of temperature in forensic entomology applications, particularly its effects on rates of development, have been well emphasised [e.g. 1,7–9]. Temperature is a fundamental influencing factor in body decomposition as well as for estimations of the pre-appearance interval (PAI) in insect succession patterns [7,10,11]. Seasonal temperature variations can influence body decomposition rates, as reported by a study in 2004, which found that decomposition rates increased in higher temperatures and with greater rainfall [9].
Post-mortem interval estimation based on insect evidence in a quasi-indoor habitat
2019, Science and JusticeCitation Excerpt :Accordingly, we used the regression equation to retrospectively correct temperatures from the station to be used in PMI estimation. In general, insect age was estimated using thermal summation method [20–22], and supplemented with the PAI estimated using temperature methods [23, 24]. Because larval PAI may be estimated with the average error of about 20% [23] and because there is no contemporary data on the error rate of insect age estimates (it is probably lower than 20%), we decided to include a conservative 20% error rate for both age and PAI estimates.
Estimation of postmortem interval (PMI) based on empty puparia of Phormia regina (Meigen) (Diptera: Calliphoridae) and third larval stage of Necrodes littoralis (L.) (Coleoptera: Silphidae) – Advantages of using different PMI indicators
2018, Journal of Forensic and Legal MedicineCitation Excerpt :Various tools were recently developed in forensic entomology to estimate the age of insects sampled on a cadaver.3–8 Moreover, methods of PAI estimation from temperature data were developed for different species of forensically-useful insects.9,10 Much attention is also paid to studies on insect succession on carrion in relation to various cadaver treatments, body mass, geographical region, season and habitat of decomposition.11–17
The importance of Saprinus semistriatus (Coleoptera: Histeridae) for estimating the minimum post-mortem interval
2018, Legal MedicineCitation Excerpt :This is not in accordance with our study where the PAI increased with increasing temperature, ranging from 3 to 14 days at temperatures from 13.7 to 16.6 °C (Fig. 3), although the number of data points measured within this small temperature range between the two studies is almost the same (this study n = 10, n = 12 [5]). The discrepancy between the two studies may be due to the fact that our study did not meet all the criteria suggested by Matuszewski and Madra [24] to assure the quality of the temperature model for PAI. Although the frequency of insect sampling and the combination of pitfall traps and hand collections was carried out, one of the most important factors, i.e. the broad range of temperature data that should be covered [24], was not realized in our study.
Optimising crime scene temperature collection for forensic entomology casework
2017, Forensic Science InternationalHeat accumulation and development rate of massed maggots of the sheep blowfly, Lucilia cuprina (Diptera: Calliphoridae)
2016, Journal of Insect PhysiologyCitation Excerpt :Blowflies (Diptera: Calliphoridae) are useful indicators of the time that has elapsed since a carcass or corpse was exposed to colonization by insects (Higley and Haskell, 2010; Villet et al., 2010; Rivers and Dahlem, 2014). Gravid females may arrive at carrion within minutes of death, and will lay eggs promptly under optimal conditions (Matuszewski and Madra, 2015). Larvae can hatch from 6 h onwards, depending on ambient temperatures and precocial fertilisation (Erzinçlioğlu, 1990; Wells and King, 2001), and then feed on the carcass until they reach the post-feeding stage in preparation for pupation (Villet et al., 2010; Rivers and Dahlem, 2014).