The forensic entomologist uses weather station data as part of the calculation when estimating the postmortem interval (PMI). To reduce the potential inaccuracies of this method caused by the distance between the crime scene and the meteorological station, temperature correlation data from the site of the corpse may be used. This experiment simulated the impact of retrospective weather data correction using linear regression between seven stations and sites in three climatic exposure groups during three different seasons as part of the accumulated degree days calculation for three necrophagous species (Diptera: Calliphoridae). No consistent benefit in the use of correlation or the original data from the meteorological stations was observed. In nine cases out of 12, the data from the weather station network limited the risk of a deviation from reality. The forensic entomologist should be cautious when using this correlation model.
Knowledge of the postmortem interval (PMI) is of crucial importance in criminal investigations. When the limits of traditional legal medicine are reached for putrefied corpses colonized by insects, forensic entomology can provide the only means for estimating the time since death, often calculated with the thermal summation model [
When insects are used for intelligence or evidential purposes in criminal investigations [
More often than not, the crime scene is located some distance away from the nearest weather station. Therefore, the microclimates experienced at the two locations will differ from each other, and the temperature data will not be directly comparable [
One of the solutions proposed by forensic entomologists is the use of a correction factor, which is calculated by comparing the data collected from the weather station with the body deposition site for some days after the corpse has been recovered [
The following series of experiments introduce the limits of the linear regression method in its application to judiciary casework. The present paper measures the impact, expressed in insect time development, of weather data corrections in different environmental conditions and different correlation durations.
Three groups (exposed, partially protected, and protected) were defined according to their climatic exposure to the following criteria: direct radiance, precipitations, wind, and dew. Some of the characteristics of these three groups are illustrated in Figure
Characteristics of the sites and data loggers’ climatic exposure; comparison with their meteorological station associated (A, B, or C: periods of experimentation for a same spot).
Spot (s) | Period of experiment | Town/Characteristic of location (S) | Data loggers climatic exposure | Distance Meteorological station (MS)—S | Altitude MS/(Altitude MS-Altitude S) |
---|---|---|---|---|---|
S1 | 03/10/2002 to 11/11/2002 | Rosny sous Bois/On lawn | exposed | 0.03 km | 112 m/0 m |
S2 (A, B, C) | Nouzilly/Fallow field—on the ground | exposed | 15.10 km | 148 m/ | |
S3 | 03/10/2002 to 11/11/2002 | Joinville Le Pont/Under cover of vegetation | partially protected | 0.20 km | 37 m/0 m |
S4 | 03/10/2002 to 11/11/2002 | Joinville Le Pont/Banks of Marne river—Under cover of vegetation | partially protected | 0.20 km | 37 m/0 m |
S5 | 15/04/2004 to 24/05/2004 | Cairon/Stone shelter with roof in tile | protected | 6.60 km | 62 m/26 m |
S6 (A, B) | Fontenet/Breeze block shelter with roof in cement | protected | 12.20 km | 148 m/ | |
S7 (A, B, C) | Fontenet/Breeze block shelter with roof in corrugated iron roof | protected | 12.20 km | 148 m/ | |
Location and general characteristics of the sites.
Ambient temperature data were recorded with one Testo 175-T1 data logger per site (Table
Weather data were obtained from the French national meteorology office, Météo France, which has 3725 weather stations throughout the French metropolitan territory. The Météo France temperature data are recorded with international Norma (World Meteorological Organization), which means that it is recorded under sheltered conditions at 1.5 meters in height with grassland surroundings. There was no significant difference in altitude between the locations of the data loggers and the weather stations.
Three species of fly (Diptera-Calliphoridae), which are known to colonize corpses soon after death [
Thermal parameters (°C) regulating development of flies. Data are from Marchenko [
Species | ADD from egg to adult | Minimum development threshold |
---|---|---|
388 | 2.0 | |
251 | 7.8 | |
207 | 9.0 |
For each site the period of study was 40 days. At sites S2 and S7, three different times of the year were chosen and two different times of year were selected for site S6 (Table
Summation of the difference between
Spot | Linear regression curve equation; | |||||
---|---|---|---|---|---|---|
S1 | 28/10/2002 | 4.67 | ||||
S2 A | 07/06/2004 | 34.60 | 17.82 | 45.63 | 50.12 | |
S2 B | 22/10/2004 | 11.70 | 41.92 | 35.11 | 36.20 | |
S2 C | 29/03/2005 | 15.84 | ||||
S3 | 28/10/2002 | |||||
S4 | 28/10/2002 | |||||
S5 | 10/05/2004 | 1.69 | 28.47 | |||
S6 A | 15/05/2004 | 30.81 | 83.96 | 110.98 | 94.97 | |
S6 B | 16/08/2004 | 55.22 | 97.83 | 123.89 | 125.42 | |
S7 A | 22/09/2005 | 40.27 | 69.81 | 71.17 | 65.54 | |
S7 B | 22/04/2006 | 16.13 | 32.49 | 36.85 | ||
S7 C | 03/07/2006 | 36.29 | 66.15 | 61.57 | 62.03 | |
The temperatures shown in the table correspond to the following: the daily average of temperature minima and maxima from Météo France data, the daily average of the temperatures recorded every three hours by the data loggers.
The day of cadaver discovery was termed
Calculation and application of linear regression.
For 25 days before
In forensic entomology, the PMI estimation is based on the study of the duration of insect development. There is a direct relationship between time of development and the ambient temperatures experienced by the insect. Marchenko [
To determine an estimate of the date of oviposition, the IRCGN Entomology department mainly utilises ADD model. Other published insect developmental data recorded under constant temperature conditions, as Kamal's work [
In this study, we used the ADD model for all of the data from the three species of Diptera. Zero was used to replace all of the temperature values recorded below the developmental threshold.
When the total temperature summation needed to complete development (with When the total temperature summation needed to complete development (with
Comparisons between ADD
Differences between ADD
Differences between ADD
Differences between ADD
Results are shown in Table
For the sites under different climatic exposures, the best fitting temperature data originated from different sources. For S1, the most suitable temperature data was obtained with
In partially protected conditions (S3, S4), the
In protected conditions,
For S7, none of linear regressions could be applied for the three periods of study;
Finally, for all the species and temperatures considered, the higher the developmental threshold is, the greater the deviation became. Therefore, for a species with a low developmental threshold, for example,
In forensic entomology technique, one solution to obtaining an estimate of the temperature data that the body might have been exposed to would be the use of a mathematical tool to obtain an estimate based on temperatures recorded at the site post body discovery and weather station temperature data. However, neither temperatures from linear correlations nor weather station data could provide a truly accurate representation of temperatures experienced at a crime scene.
If we compare all of the results obtained for the three different time intervals (5, 10, and 15 days) for the linear regressions used in the 12 “cases”, none of these were more suitable than the others for describing the situation recorded by data loggers. Moreover, consequences on the time duration were not standardized and could increase the deviation significantly. For example, for S2B and
Furthermore, in ADD calculation, insect time developments could be affected when ambient temperature is closed to their theoretical development threshold [
Within the same site, it was difficult to estimate the impact of the time of year on the method to use. For example, for S2, three times of year were selected and the linear regression for 5 days was more representative in June whereas
Additionally, neither the correlation data nor the data from Météo France were linked to the distance between the site and the weather station locations. At site S1, the distance from the station was 30 meters and the best result was obtained using
Regarding the three different types of location (Figure
The forensic entomologist has to use the most reliable data to provide an accurate PMI. At first glance, a statistical model based on correlations would appear to be a logical and useful method. However, the situation is more complex and depends on many external factors which are difficult to quantify. Regression (i.e., linear), sometime used in casework, is useful but there is risk of obtaining a significant deviation from the temperatures actually experienced at the crime scene. Correlations are obtained with data recorded after the body has been discovered and insect development has already occurred. Rain, direct sun exposure on the corpse and the state of the vegetation in the vicinity are some parameters which may directly affect the local temperature experienced by the necrophagous insects [
Regarding this study and the extent of the meteorological station network available in France, the department of forensic entomology from IRCGN will continue to use data from Météo France directly in its forensic casework. Despite the fact that weather station data are likely to be different from conditions experienced at the crime scene, they should be considered, by default, as the most ideal data to use for PMI estimations, bearing in mind the possibility of any deviations. The risk of any deviations is considered to be acceptable for the purposes of forensic entomology as long as they are taken into account when providing PMI estimations and an appropriate range is given.
At least, it is necessary to realize that this study was performed with Marchenko data (ADD model). However, numerous authors displayed disparities in the threshold value for a same species depending, for example, on protocols of the study or the geographical strain origin [
Thus, a deeper understanding of insect development rates, their physiological activity close to the developmental threshold, and the succession mechanisms of necrophagous insects may be a better way of improving the accuracy of PMI estimates in forensic entomology.
The authors are very grateful to Bernard Chauvet, Fabrice Lefèbvre, and Jean-Bernard Myskowiak for their great help to carry out these experiments. They thanks also Gérard Mayençon from Météo France for his availability and his technical advises. Special thanks to Andrew Hart for his precious help.