U.S. Department of Justice 

Office of Justice Programs 

National Institute of Justice 

Project Narrative 

Research and Development in Forensic Science for Criminal Justice Purposes 

NIJ-2015-3985 - SL001149 

Project Title: Expanding on Total Body Score with Use of Geographic Information Systems 

(GIS) 

Submission date: April 8, 2015 

Lead Principal Investigator: Co-Principal Investigator: 

University of Tennessee, Knoxville The University of Tennessee, 
 

	 	

TABLE OF CONTENTS 

Table of Contents ..................................................................................................................i 

Project Narrative 

Outcomes, Evaluation, Dissemination Strategy and Future Directions 

Abstract................................................................................................................................ii 

Purpose.................................................................................................................................1 

Goals and Objectives ...........................................................................................................2 

Review of Relevant Literature .............................................................................................3 

Pilot Study............................................................................................................................4 

Research Design and Methods.............................................................................................9 

Description of Sample and Placement at ARF...................................................................10 

Objective 1. Development of Trait Lists and Observer Agreement...................................11 

Objective 2. Determine Baseline Variability in Human Decomposition Patterns .............11 

Objective 3. Model Creation to Estimate PMI with ADD .................................................11 

Objective 4. Model Validation ...........................................................................................12 

Management Plan and Organization..................................................................................12 

Implications for Criminal Justice Policy and Practice in the United States ......................12 

Capabilities and Competencies..........................................................................................13 

Outcomes and Evaluation ..................................................................................................13 

Dissemination Strategy ......................................................................................................14 

Future Directions ...............................................................................................................14 

Appendix I. References......................................................................................................16

Appendix II. Proposed Project Timeline and Expected Milestones ..................................19 

Appendix III. Curriculum Vitae.........................................................................................20

Appendix IV. Supporting Data...........................................................................................24 
	 	

ABSTRACT 

The quantification of human decomposition is a difficult issue within forensic anthropology. 

However, many attempts have been made to both standardize and score decomposition with the 

intent of estimating a post-mortem interval (PMI) with known error ranges (for example, 

Megyesi et al., 2005). Yet, the Megyesi et al. method (2005), aka the total body score (TBS), has 

several limitations. First, many regions of the body are grouped together and scored as one unit, 

which diminishes the fidelity in recording the often asymmetric and highly variable 

decomposition processes. Second, the method does not address how to handle scavenged 

remains, which greatly accelerates decomposition processes. Third, the method was developed 

from photographs with a combination of known and estimated PMIs, thus introducing 

unnecessary statistical noise. The proposed research will enhance the quantification of variability 

in decomposition by breaking down the body into 16 discrete regions, with limb antimeres 

scored separately. 

Ten individuals will be placed in the same environment at the same time at the Anthropological 

Research Facility (ARF) at the University of Tennessee. Separate trials will be conducted in 

different seasons to capture the variability of decomposition in different seasons. A modified trait 

list will be developed to record the presence or absence of discrete traits in the field that are later 

tied to a quasi-continuous weighted scoring system to minimize bias while collecting data. Two 

independent observers will score the same subjects each day. The associated scores will be input 

into a digitized homunculus into a geographic information system (GIS), ArcGIS (ESRI, 2011), 

each day for each individual in the study sample. At the end of each trial, the scores for each 

individual will be summed for each region of the body to create a heat map that will show 

individual regional variability in decomposition process. Further, the scores for each of the 

subjects in each trail will be summed upon collection and a heat map generated to show the 

overarching trends in decomposition. Hot spot analysis will then be performed on the combined 

heat maps to identify statistically significant hot (first to decompose) and cold (last to 

decompose) spots. Linear regression models will be created to estimate PMI. The created models 

will then be validated on various holdout specimens at the ARF. The proposed research will 

provide more precise PMI estimates and associated error ranges by capturing greater variability 

in the decomposition process. 
	 	

PROJECT NARRATIVE 

Purpose 

New forensic anthropology methods in postmortem interval estimation must meet 

Daubert standards (Daubert v Merrell Dow, 1993) of scientific reliability and the suggestions of 

the National Research Council’s report on strengthening forensic sciences in the United States 

(2009). Additionally, SWGANTH (2013) have released guidelines on taphonomic observations 

in the postmortem interval pointing out “the identification and correct interpretation of 

taphonomic alterations can assist with the reconstruction of postmortem events and the 

estimation of the postmortem interval” (SWGANTH 2013, p. 1). However, these 

aforementioned guidelines do not explicitly aid the investigator in recording observations or 

assigning decomposition stages and consequently offers no direction on estimating the 

postmortem interval (PMI). 

While there have been advances in attempts to quantify human decomposition (Galloway 

et al., 1989; Megyesi et al., 2005), none have taken a purely quantifiable approach from multiple 

specimens in the same conditions to document variability and hence, establish error rates. Based 

in part on previously funded research at UT and across human decomposition facilities, the goal 

of the proposed project is to simplify and standardize decomposition observations to maximize 

agreement among observers and reduce bias. The standardization of decomposition observations 

will be accomplished through the development of a list of easily identified traits that are recorded 

as present or absent and will rely primarily on the trait lists of Megyesi et al. (2005) as well as 

observations gained from a proof-of-concept pilot study. Further, heat maps will be generated for 

each donor within the sample to visualize the variation inherent in human decomposition, as well 

as to examine overarching trends in decomposition. The Megyesi et al. (2005) trait list is 

comprised of quasi-continuous observations that are assigned scores based on decomposition 

stage. Observations scores are tallied for the head/neck, trunk, and limbs and then summed 

together to provide a total body score (TBS). Through Megyesi and colleagues (2005) research, 

they have provided an equation that will allow a researcher to plug in the collected total body 

scores to estimate accumulated degree-days (ADD) and thus the post-mortem interval (PMI). 

However, the nebulous grouping of body regions limits the variability that can be observed 

throughout the complex process of decomposition. 

The proposed research breaks the observations into 16 regions of the body, with each side 

scored separately. The 16 regions include the head/neck, chest, abdomen, genitals, and the left 

and right sides of the upper arms, lower arms, hands, upper legs, lower legs, and feet. Each 

region is scored independently to better capture intra-individual decomposition variation. Basic 

observation lists of discrete traits will be available for each region of the body, which are then 

assigned quasi-continuous ordinal scores, in accordance with Megyesi et al. (2005) and with 

observations gained through a pilot study described below. Individual region scores are summed 

to create a modified total body score to compare the variation in decomposition processes across 

individuals, as well as summed to establish the overarching trends in decomposition. Further, 

additional observations will be included to more holistically capture decomposition such as 

scavenging and the relative locations of color change. Lastly, the daily-modified TBS scores will 

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be input into ArcGIS (ESRI, 2011) for each individual and body region. This way, at the end of 

the trial periods, heat maps can be created to visualize the pattern and variation among individual 

donors, as well as summed to visualize overarching decomposition patterns. Furthermore, the 

heat maps, both individual and combined will be subjected to a hot spot analysis within ArcGIS 

to identify statistically significant hot and cold spots. A main advantage of using a discrete trait 

list without the associated scores is that it limits the individual bias of the observer through 

removing any qualitative judgment concerning decomposition. Moreover, the proposed 

methodology will become more transferable and can be adopted across human decomposition 

facilities as well as for research involving nonhuman models at other institutions. 

Goals and Objectives 

The primary goal of the proposed project is to develop a modified total body score 

system that accounts for information from several regions of the body independently. 

Incorporating multiple regions of the body will create a cohesive model to more accurately 

estimate PMI with known error rates. Additionally, the individual regions scored on the body will 

allow for the creation of heat maps to visualize the specific and general trends in human 

decomposition, which can then be subjected to hot spot analysis to test the significance of the 

identified variation. One key difference in the error rates associated with the proposed research 

and those presented by Megyesi et al. (2005) is that the latter error rates were calculated by 

doubling the standard error to approximate a 95% confidence interval. Because the proposed 

research represents a closed population of individuals with known PMI, actual variability can be 

directly measured to more realistically construct error rates. The proposed project will address 

the following objectives: 1) modify and add observations to the Megyesi et al. (2005) TBS to 

create list of discrete observations for each region of the body, henceforth referred to as modified 

TBS; 2) determine baseline variability in decomposition using replicate human donors placed in 

the same environmental conditions at the same time through the heat maps and hot spot analyses 

within GIS; 3) create PMI models using ADD with the modified TBS, in accordance with the 

analytical procedures outline in Megyesi et al. (2005); and 4) validate the model on a holdout 

sample. 

The first objective will be accomplished by having multiple researchers independently 

apply the new modified decomposition scoring procedure at regular intervals. Photographs will 

be taken each day. At the end of each trial, each researcher will score the photographs without 

consulting their scores from the actual observation so that scores gleaned from actual 

observations and photographs can be compared to test if there are significant differences in 

scores based on actual observation and observation of photographs. The second objective will be 

accomplished by entering the score data for each region into ArcGIS and generating heat maps 

for each individual as well as a compilation of all individuals. These heat maps will then be 

subjected to a hot spot analysis to determine significant regions of hot (greater decomposition) 

and cold (little or no decomposition) spots through time. The third objective will be completed 

by collecting ADD and modified TBS for each day to perform a linear regression following the 

analytical procedures outline by Megyesi et al. (2005) to create a new, modified TBS system 

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with appropriate error rates. The fourth objective will be completed by applying the new 

procedures and models to a holdout sample to test the models predicted values on donors not 

included in the study area or model development. Validating the model ensures that it is 

applicable applicable to other seasons and environments. The main goal of the proposed research 

is develop the scoring infrastructure and analytical procedures that can then be applied easily in 

the field by forensic anthropologists, law enforcement, and medicolegal investigators. 

Review of Relevant Literature 

Efremov (1940) has been credited for first coining the term “taphonomy”, which he 

described as “the science of the laws of embedding” (p. 93). However, research on 

decomposition started much earlier with Weigelt (1927) observing the decay of vertebrates in 

Texas where he noted the importance of insects in the decomposition process. Taphonomic 

research was then expanded by the work of paleoecologists and paleontologists, particularly, 

Behrensmeyer (1978) who developed a system of stages for the weathering of bone. 

However, the systematic study of human decomposition rates in relation to the PMI did 

not emerge until Dr. William M. Bass established the Anthropology Research Facility (ARF) to 

study human decomposition (Bass, 1997). Since Bass founded the ARF, much research has been 

conducted on various aspects of the decomposition process. Mostly, decomposition research has 

focused on the recognition of four or five general stages of decay (Reed, 1958; Payne, 1965; 

Galloway, 1989; Anderson and Van Laerhoven, 1996; Marks et al., 2009; Bass, 1997). For 

instance, Marks et al. (2009) used human donors at the ARF to define five decomposition stages 

as: 1) fresh; 2) discoloration, or putrefaction; 3) bloat; 4) skeletonization; and 5) skeletal decay. It 

has been ubiquitously agreed upon that the localized deposition environment, specifically 

temperature and insects, are the most important variables contributing to decomposition rates 

(Mann et al., 1990; Haglund, 1997; Sorg et al., 1998; Synstelien, 2009; Reeves, 2009; Rodriguez 

and Bass, 1983, 1985; Parmenter and MacMahon, 2009; Rippley et al., 2012; Vass et al., 2002). 

Essentially, warm environments more conducive to both insect and scavenger activity will 

accelerate the rate of decomposition. Thus, incorporating both temperature and time in the form 

of ADD is necessary to estimate the PMI (Vass et al., 2002; Megyesi et al., 2005). 

Megyesi et al. (2005) have developed a point-based system of observations on five 

regions of the body to assess the decomposition process. The points are then summed to provide 

a total body score, or TBS. The TBS is then related to accumulated degree-days to create a model 

for predicting the PMI. In fact, Megyesi and colleagues (2005) found that ADD accounts for 

80% of variability in TBS. Presumably, scoring each body region independently will aid in 

accounting for the remaining variability in human decomposition rates. However, there are 

problems with this method. First, the method developed by Megyesi et al. (2005) was 

constructed from scene photographs where exact PMI was not always known and was sometimes 

estimated by an entomologist. Second, the original TBS model does not account for scavenging 

activity, which can greatly affect decomposition patterns (Klippel and Synstelien, 2007; 

Synstelien, 2009). Third, the error rates associated with the Megyesi et al. (2005) method are 

based on doubling the standard deviation from the observed study sample, which is not 

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statistically ideal. Finally, the “regional” body scoring technique was likely too minimalistic in 

that it did not capture differential variation between arms and legs or right and left sides. 

This study improves on the deficiencies of the Megyesi TBS method in that it uses 

empirical longitudinal data from donors with known PMI rather than photographs that had no 

temporal or contextual control. By placing multiple donors at the same time in the same 

environment, direct observation of variation within and among individuals will provide a more 

realistic and nuanced error rate. In addition, field and photographic observations will be 

compared to examine if scoring decomposition from photographs offers the same fidelity as 

scoring in the field. Moreover, the inclusion of a discrete list to score each of the 16 regions of 

the body will minimize bias in scoring inherent in the bilateral asymmetry in normal 

decomposition processes. In the Megyesi et al. (2005) scoring procedure, multiple traits are 

often listed under each observation. For example, in the limb scoring procedure, one of the 

observations scored consists of, “Discoloration and/or brownish shades particularly at edges, 

drying of fingers, toes, and other projecting extremities”. This example shows multiple 

observations within a single trait, which may lead to confusion among observers and thus low 

agreement. Compiling a list of discrete traits that can be scored in the field as either a presence or 

absence of that trait can then be converted to an associated weighted score that will ideally 

reduce bias and increase observer agreement. Further, Megyesi et al. (2005) do not address the 

issues of scavenging as it relates to decomposition. The addition of a scavenging observation will 

allow for the variation in decomposition to be more critically evaluated. Finally, the inclusion of 

GIS techniques will allow for both the visualization and quantification of decomposition patterns 

through time with the use of heat maps and hot spot analysis. 

Pilot Study 

As a proof-of-concept, the PI ( ) carried out a pilot study in 2014-15 of five 

donors that were being used as part of a currently funded NIJ project on decomposition 

(Steadman et al., 2013-DN-BX-K037). Four researchers scored decomposition using a list of 

observations derived from Megyesi et al. (2005) without their associated scores and noted which 

stage of decomposition they believed the body to have been in (fresh, early decomposition, 

advanced decomposition, and skeletonization, ala Megyesi et al., 2005) and mark the 

observations that led them to that categorization. Additional observations that influenced each 

observer’s classification were also noted. The initial research revealed that a larger number of 

variables are more useful at quantifying decomposition than that provided by Megyesi et al. 

2005. In addition to a greater number of variables, converting the Megyesi et al. (2005) 

observations, which are mostly composites of multiple traits, into a list of discrete traits reduced 

inter-observer error. From this research, a list of 37 discrete observations has been developed to 

use for the proposed research (Table 1). The expanded trait list broke down the composite 

observations used by Megyesi et al. (2005) into discrete traits that can be marked as either 

presence or absence in practice instead of combining multiple traits into one observation. 

Further, observations concerning the relative quantity and activity of maggots and scavenging 

were shown to influence the original observer’s classification. In the modified scoring procedure, 

each question is phrased in a way to warrant a binary response to a discrete observation. In the 

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field, these traits would all be judged for their presence or absence and the associated scores 

would be tabulated after data collection as to not bias the observer. The associated observation 

scores in Table 1 reflect the progression of decomposition through time based on when the 

observations were noted from each researcher. In this sense, the associated scores were 

heuristically assigned based on the progression of decomposition as judged by the initial four 

observers. For comparative purposes, the scoring procedures of Megyesi et al. (2005) are shown 

in Table 2. 

The pilot study period lasted 46 days between December 2, 2014 and January 14, 2015 

and included nine observation events, all scored by PI . The observations were 

recorded in the field on forms that only provided the list of discrete traits and a box to mark if 

these traits were present or absent. The data was then transcribed into the spreadsheet that 

converted the binary responses to their corresponding score (shown as “Associated Score” in 

Table 1), which were the heuristically assigned weights for each observation. The assigned 

weights for each score were based on deconstructed composite observations from Megyesi et al. 

(2005) and the sequence in which they were noted in the initial research. The regions were then 

summed to create a modified TBS. A homunculus was created in ArcGIS with each region being 

treated separately. Each region was assigned a value that corresponded to the modified TBS 

score for that observation period. This was completed upon each day data was collected. The 

individual homunculi were then added together for each donor independently to create a visual 

heat map that showed the different rates of decomposition for different regions (Figure 1). All 

homunculi for the study period were then summed to produce a more general heat map showing 

overarching trends in decomposition in this study sample (Figure 2). For the pilot study, hot spot 

analysis was not conducted given the small sample sizes. However, the general trends do show 

patterns relevant to decomposition progression in East Tennessee. 

Table 1. Example of observation trait list with associated scores. Scores are deliberately placed in 

non-sequential order to minimize bias. The same observations were used for each of the 16 

regions of the body with the addition of two extra observations for the head/neck (hair on scalp 

has slipped revealing a hair mat= 4 and Insects around mouth and/or ears = 2). 

Upper Arm Associated Score 

Bloating 

Observation 

Active bloating (full bloat) 4 

Partial deflation of bloat 5 

Beginning Bloat 3 

No bloating 1 

Visible partial bloating 2

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6 

Skin Coloration 

Observation 

Mottling (Pinkish, bluish, greenish) on most of limb 3 

Mottling (Pinkish, bluish, greenish) Veins coloring on proximal third of 

limb 1 

Mottling (Pinkish, bluish, greenish) Veins coloring on distal third of 

limb 1 

Darkened skin (deep green or black) on proximal third of limb 4 

Darkened skin (deep green or black) on distal third of limb 4 

Darkened skin (deep green or black) on most of limb 9 

Skin Appearance 

Observation 

Only dry skin, bones, cartilage remain 20 

Skin is taut 1 

Skin appears glossy 2 

Skin sloughing off in a few areas 2 

Evidence of scavenging (unnatural openings, missing elements) 3 

Skin is dry 7 

Most soft tissues are gone, but some flesh remains 8 

Skin sloughing off in large areas 4 

Adipocere formation 5 

Some bone is showing 6 

Skin has collapsed around bones and outline of bones is visible 6 

Skin appears dark and moist 6 

Purge 

Observation 

Liquefaction beginning - purge fluids seeping into soils 2

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Deflation of bloat
	 	

Element sitting in pool of purge fluid (soil saturated) 4 

Liquefaction apparent - purge fluids leaking out 3 

Insect Activity 

Observation 

Little foam at insect feeding sites 2 

A lot of foam at insect feeding sites 3 

Maggots very active (lots of movement) 4 

Beetles present 7 

Ants and flies dominate 3 

Large number of maggots (~ >50% of region covered) 5 

Maggots sluggish/lethargic (present but not much movement) 6 

Some maggots present (~10-50% of region covered) 4 

Eggs present? 1 

Few or no maggots (~ < 10% of region covered) 2 

Table 2. Observations and associated scores from Megyesi et al. (2005). 

Observation Score 

Limbs 

Fresh, no discoloration. 1 

Pink-white appearance with skin slippage of hands and/or feet. 2 

Gray to green discoloration; marbling; some flesh still relatively fresh. 3 

Discoloration and/or brownish shades particularly at edges, drying of 

fingers, toes, and other projecting extremities. 4 

Brown to black discoloration, skin having a leathery appearance. 5 

Moist decomposition with bone exposure less than one half that of the 

area being scored. 6 

Mummification with bone exposure of less than one half that of the area 

being scored 7 

Bone exposure over one half the area being scored, some decomposed 

tissue and body fluids remaining. 8

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Bones largely dry, but retaining some grease. 9 

Dry bone. 10 

Head and Neck 

Fresh, no discoloration 1 

Pink-white appearance with skin slippage and some hair loss 2 

Gray to green discoloration: some flesh still relatively fresh 3 

Discoloration and/or brownish shades particularly at edges, drying of

nose, ears and lips 4 

Purging of decompositional fluids out of eyes, ears, nose, mouth, some 

bloating of neck and face may be present 5 

Brown to black discoloration of flesh 6 

Caving in of the flesh and tissues of eyes and throat 7 

Moist decomposition with some bone exposure less than one half that

of the area being scored 8 

Mummification with bone exposure less than one half that of the area 

being scored 9 

Bone exposure of more than half of the area being scored with greasy

substances and decomposed tissue 10 

Bone exposure of more than half of the area being scored with

desiccated or mummified tissue 11 

Bones largely dry, but retaining some grease 12 

Dry bone 13 

Trunk

Fresh, no discoloration 1 

Pink-white appearance with skin slippage and marbling present 2 

Gray to green discoloration: some flesh relatively fresh 3 

Bloating with green discoloration and purging of decompositional fluids 4 

Postbloating following release of the abdominal gases, with 

discoloration changing from green to black 5 

Decomposition of tissue producing sagging of flesh; caving in of the 

abdominal cavity 6

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Moist decomposition with bone exposure less than one half that of the 

area being scored 7 

Mummification with bone exposure of less than one half that of the area 

being scored 8 

Bones with decomposed tissue, sometimes with body fluids and grease 

still present 9 

Bones with desiccated or mummified tissue covering less than one half 

of the area being scored 10 

Bones largely dry, but retaining some grease 11 

Dry bone 12

The individual heat maps (Figure 1) and the combined heat map (Figure 2) show both the 

variability in the progression of decomposition in different anatomical regions and also general 

trends. In East Tennessee, the head/neck and genitals region decompose faster than the rest of the 

body. Conversely, the limb regions are highly variable in their decomposition rate. Over the 

course of the study period it was noted that once scavengers had exposed muscle tissue on a 

limb, that particular region was continually exploited by both scavengers and insects while 

regions still protected by skin were ignored. This observation is especially problematic in 

applying the Megyesi et al. (2005) scoring procedures. If one of the limbs is completely 

skeletonized and the others are in various stages of decay, how should they be scored? Also, 

Megyesi et al. (2005) have stated that bloating is not present in the limbs, however, in our 

experience, bloating is observed in the limbs. The bloating in the limbs was noted due to the way 

in which donors are tracked in the field – ID tags are affixed to a donor’s arm and leg before 

placement with a zip tie. The zip tie is firmly affixed compressing a region of the arm and leg 

and bloating can be noted. 

A plot of modified TBS through time is shown in Figure 3. The preliminary results 

indicate that there is a semi-linear relationship through time with the modified TBS score. 

However, the model created by this data suffers from a small sample size and about a two-week 

span when data was not recorded. While it is possible to create a formula to estimate ADD from 

the data, the error ranges would be too large to make any meaningful conclusions and as such 

have not been included. Still, the concept is viable with the inclusion of larger sample sizes and 

further considerations on trait scoring gleaned through the pilot study. 

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Figure 1. Heat maps for individual donors based on 46 days of decomposition. Hot spots in 

warmer colors (gradients towards red) decompose quicker than cooler spots (gradients towards 

blue). 

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Figure 2. Heat map showing decomposition in one individual over the pilot study duration. 

Cooler colors (blues/greens) show the more slowly decomposing regions, while hotter colors 

(yellows/reds) show the regions that decompose more quickly. 

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Figure 3. Plot of modified TBS over time for each subject. 

The completion of the pilot study elucidated several important considerations for the 

proposed research. First, the addition of scoring individual, discrete traits, without any weight 

associated with it during collection allows for less bias, especially from practitioners that do not 

have much experience with decomposition. This is especially important because there are no 

instructions on which part of the composite observations in Megyesi et al. (2005) should be 

given more weight. For example, the observation “brown to black discoloration, skin having a 

leathery appearance” has an associated score of 5. Will this score still be a 5 if the skin is 

leathery without the associated color change or vice versa? Second, scavenging activity greatly 

accelerates decomposition around the scavenged region. Further, more precise observations are 

necessary. It was noted in the pilot study that the proximal and distal aspects of a particular 

region went through color changes before the rest of the region did. Adding in observations such 

as “color changes in distal aspect” or “color changes in proximal aspect” will aid in capturing 

more variability in limb decomposition, especially in earlier stages. Lastly, to gain a better 

understanding of the normal variation in decomposition rates, a larger sample is paramount. 

Further, a larger sample will allow for creating season specific models, as well as a more general 

model to predict ADD from the modified TBS scores. 

Research Design and Methods 

The proposed research will be divided into three components: 1) development of a trait 

list to examine baseline variability in decomposition using donors placed in the same 

environment over the same amount of time comparing photographic and field observations; 2) 

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create a model based on modified TBS scores and ADD; and 3) validate the model on a known 

holdout sample. The majority of Research Component 1 will focus on fleshing out a list of 

observations that have high agreement and scoring multiple donors in the same settings. 

Research Component 1 will then establish the normal range of variation inherent in human 

decomposition and also elucidate overarching trends. Research Component 2 will use the data 

collected from Research Component 1 to develop the models for estimating PMI. Lastly, 

Research Component 3 will test the models on known samples as a measure of model 

applicability. 

Description of Sample and Placement in the ARF 

This project will make use of 60 human donors over the proposed two-year period. Ten 

donors will be placed simultaneously in six trials in the same microenvironment at the 

Anthropology Research Facility. A power test for generalized linear models with a large effect 

size and an alpha of 0.05 indicated that approximately 8 donors would be needed for each trial. A 

target of 10 donors for each trial will allow for wiggle room in the research design as donor 

procurement often fluctuates. The first trial will begin in the spring following grant approval in 

Year 1, then again in summer and fall. In Y2, trials will be conducted in the winter, spring, and 

summer leading towards the completion of the final report. Each trial will continue until the 

remains are skeletonized or mummified (a minimum of 2000 accumulated degree hours, or 

ADH). 

Human donors from the Forensic Anthropology Center’s (FAC) body donation program 

will be selected based on: 1) known time of death; 2) natural cause of death with no external 

trauma; 3) donor weight between 150-250 pounds; and 4) not autopsied or embalmed. To ensure 

that the target sample size can be achieved, donors enrolled in the study will be placed in a deep 

freezer to halt the decomposition process until the target sample size has been collected. Each 

donor will have be set in deep freeze for at least 24 hours to equalize body temperatures. Before 

placement, all donors will be removed from the deep freezer and allowed to thaw to ambient 

temperature for 24 hours before each trial begins. 

All donors will be photographed and weighed upon intake at the FAC. In addition, daily 

photographs will be taken at placement at the ARF until the end of each trial period. All donors 

will be placed unclothed in the supine position at least three meters apart to ensure that 

microenvironment, topography, and exposure conditions are comparable, without risking a bias 

in insect diversity by having donors placed too closely to one another (Haskell et al., 2002; 

Shoenly et al., 2007). The ARF is encapsulated by a fence that keeps out large scavengers but 

small animals, namely raccoons, possum and mice, do scavenge donors at the ARF (Synstelien 

2009; Dautartas et al., 2015). Scavenging is a necessary consideration when evaluating 

decomposition rates so the donors will not be placed in cages. To negate loss of small bones, the 

hands and feet will be bagged in mesh. 

Temperature data will be recorded for each day from data loggers placed at each body 

and also from the National Oceanic and Atmospheric Administration’s (NOAA) National 

Climatic Data Center (NCDC). NCDC data is used as it is the type of data available to law 

enforcement and forensic practitioners in a real-world setting. However, many studies that use 

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total body score also use data loggers to examine the influence of the microenvironment 

immediately surrounding the body to get finer grained temperature information (Steadman et al., 

2013). Using both temperature data loggers and the NCDC data will allow us to examine if 

NCDC data is an appropriate analogue. Following Megyesi et al. (2005), average daily 

temperatures will be used to calculate ADD. Also in accordance with Megyesi and colleagues 

(2005), all temperatures below 0° C will be scored as 0° C because freezing and sub-freezing 

temperatures inhibit decomposition processes (Megyesi et al., 2005). Thus, data collected for 

each observation event will include modified TBS for each region of the body and average 

temperature data for that particular day for each donor. 

Objective 1. Development of Trait Lists and Observer Agreement 

The observation lists will be comprised of the traits listed by Megyesi et al. (2005) 

augmented with observations gleaned from the pilot study (discussed above). Two independent 

observers, the lead PI and the graduate research assistant (GRA), will score each of the 10 bodies 

using the complete observation list, to be tied to the associated scoring procedure post field 

observation, (Table 1) for each trial and take photographs of each body region daily. At the end 

of each trial, the same two observers will score each body again from the daily photographs to 

assess the variability in score assignment from actual field observation to those gleaned from 

photographs. The scoring procedure is presented as a presence/absence list of discrete traits that 

are then entered into a spreadsheet to generate their associated weighted scores. The scores 

represent a quasi-continuous scale, much like those of Megyesi et al. (2005). Because of this, a 

Student’s two tailed t-tests with Welch’s correction will be used to assess corroboration between 

actual observation and photographic observations. Additionally, inter-observer agreement will be 

assessed between the two observers for both photographs and actual observations using the same 

t-tests. 

Objective 2. Determine Baseline Variability in Human Decomposition Patterns 

Each donor will be scored until only skeletonized or desiccated tissue remains. The 

scores for each region of the body will be input into a homunculus in ArcGIS (ESRI, 2011). The 

homunculus will be in a raster format (an image made of pixels) where the x and y axes of the 

homunculus detail the location of each region, and the z value will be the observed region score. 

Over the study period, individual homunculi will be created for each day and then combined to 

create a “heat map” that shows the progress of decomposition through time (Figure 1). Further, 

the individual heat maps will be compiled for each season to visualize the overarching trends in 

decomposition (Figure 2). This way, individual variation in decomposition can be visualized, as 

well as general, overarching patterns. To test the significance of the heat map, hot spot analysis 

will be employed. Hot spot analysis identifies the significant hot and cold areas in a given 

weighted feature set, which, in this instance is the weighted composite scores for each body 

region, using the Getis-Ord Gi statistic (ESRI, 2011). The output of hotspot analysis is a new 

layer showing the associated Z-scores and p-values projected on the homunculus. Using hot spot 

analysis will illustrate the statistically significant regions of decomposition, which can be 

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evaluated for each of the different seasons to examine the significance of decomposition trends 

particular to each season. 

Objective 3. Model Creation to Estimate PMI with ADD 

Two models will be created – one for each of the independent observers’ scores. The 

temperature data will be converted to ADD by adding the average temperatures each day. Next, 

the model will be created in accordance with the procedures outlined in Megyesi et al. (2005): 

the ADD and PMI will both be log-transformed and the modified TBS will be squared. The 

ADD and modified TBS will be subjected to a linear regression (direct least-squares). The nature 

of the data collected through the pilot study demonstrated a curvilinear relationship with the 

modified TBS through time so using the analytical procedures put forth by Megyesi and 

colleagues (2005) is applicable for the proposed research. In sum, two models will be created for 

each season, as well as combined to make two more general models encompassing the duration 

of the entire project period. The slopes of the two different models will be tested for 

independence with the analysis of covariance (ANCOVA). Model comparisons will add to the 

replicability of the modified procedures for estimating the PMI. 

Objective 4. Model Validation 

All created models will be tested on a holdout sample. The holdout sample will be 

comprised of a total of five donors who were not included in the study and who did not 

contribute to the model’s creation. The holdout sample will make use of donor placements for a 

particular season as they become available. The holdout sample will be comprised of donors who 

meet the current study’s criteria, but will be placed in different areas of the ARF. All holdout 

donors will be placed supine and unclothed. An R2 and RSME will be calculated from the 

trained model, as well as the fitted model with the new holdout data. Assessment of model 

validation will be based on performance of the newly fitted data through an analysis of the 

residuals. Ideally, the errors of the trained and validated models will be comparable. 

Management Plan and Organization 

The proposed research project will be conducted by the FAC at the University of Tennessee, 

Department of Anthropology. The project is headed by who will be 

responsible for data collection, data analysis, data interpretation and synthesis, as well as 

contributing to reports and data dissemination. The co-PI, 

and will oversee enrollment of the donors into the research project, contribute to the data 

analysis and interpretation, progress reports and publications. We have developed a realistic 

timetable for completion of each study phase (Appendix III). The 

has successfully completed eight NIJ grants since 2007 (and currently managing nine grants). 

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Implications for Criminal Justice Policy and Practice in the United States 

Estimating time since death and decomposition events is central to forensic science and 

the criminal justice system in the United States. Previous research (Megyesi et al., 2005) has 

taken the requisite steps towards quantifying the decomposition process, though unaccounted for 

variability still remains. Creating a more holistic observation list that examines multiple regions 

of the body independently will add fidelity to the analysis and yield more accurate results. The 

results of our study will directly impact the medicolegal community by more precisely 

estimating the PMI, accounting for more sources of error (differential decomposition of paired 

elements, for example), and produce known error rates. The legal value of the PMI is increased 

when there are associated, quantifiable error rates (Christensen and Crowder 2009, Christensen 

2004). Further, the associated error rates, which are based on scientifically-derived data, will 

allow for the modified TBS to be Daubert compliant (Daubert v Merrell Dow, 1993). 

The proposed research will provide a standardized data collection protocol that includes 

trait observations in layman’s terms. The straightforward observation list will be accessible to all 

practitioners regardless of experience or education level in evaluating decomposition. This is 

especially important because the observed changes in human decomposition are highly 

qualitative and subjective. As learned from the pilot research, it was shown that the two 

observers (one familiar with decomposition and the other not) often relied upon different stimuli 

to judge decomposition. For example, the observer who had no prior familiarity to scoring 

decomposition heavily weighted the smell to dictate stage assignment, while those with more 

experience relied upon physical characteristics, such as skin slippage. Simply scoring the 

presence or absence of discrete traits will remove any bias because the observer does not make 

any conclusion about the stage of decomposition – they simply score what is observed. The trait 

lists and associated scoring system will be made available to the law enforcement and scientific 

communities along with all of the observed longitudinal data to promote further testing in 

different geographic regions. To meet the demands of the medicolegal community, longitudinal 

studies of human decomposition in different geographic regions are paramount. 

Capabilities and Competencies 

The Forensic Anthropology Center was established with the mission to conduct innovative 

research in forensic anthropology, train students and law enforcement in forensic techniques, and 

demonstrate the science of forensic anthropology to the general public. The FAC is managed by 

a Director, an Associate Director, two Assistant Directors and 8-10 graduate student staff. The 

FAC oversees the body donation program, the ARF, the Bass Donated Skeletal Collection, and 

other skeletal collections. 

 Located on approximately 2.5 acres of land along a bluff overlooking the Tennessee River, the 

ARF is the first outdoor natural laboratory dedicated to the study of human decomposition and 

related subjects. Scores of researchers have conducted scientific studies at the ARF and it serves 

as a training site of more than 200 students and law enforcement personnel per year. Over 3000 

individuals have pre-registered to donate their body to the program, and the William M. Bass 

Donated Skeletal Collection now contains more than 1300 donated skeletons. 

– NIJ-2015-3985 – Narrative: Expanding on Total Body Score with GIS - 16
 

 

	 	

The FAC PIs are well qualified to accomplish the objectives of this project. 

. has worked 

extensively in GIS and taken both basic and advanced GIS modeling courses. Further, he has 

used GIS as part of his Master’s thesis and has taught an advanced modeling course using GIS to 

graduate students at 

at the 

and is scheduled to teach an archaeology GIS course 

. Additionally, he will direct the research design, conduct all 

statistical analyses, and develop the protocols for scoring decomposition, analyzing the data, and 

preparing the decomposition heat maps. is the 

 and will facilitate and oversee the research at the ARF. She is a Diplomate 

of the American Board of Forensic Anthropology and has served as an expert witness in U.S. 

state and federal courts and is an international consultant. She will be responsible for data 

management, data analysis, and writing and submitting semi-annual reports to OJP. 

 has previously been a PI for National Science Foundation (NSF) and Wenner-Gren 

Foundation grants and is currently a PI or co-PI on two NIJ grants. 

Outcomes, Evaluation, Dissemination Strategy and Future Directions 

Outcomes and Evaluation 

This study will have a significant impact on the field in that it will provide a simple scoring 

system to adequately encapsulate the decomposition process in multiple regions of the body, 

examine the normal variation in decomposition, and provide PMI estimates with associated error 

rates. The result of the study will provide comprehensive and validated PMI estimates for 

criminal justice purposes. Further, this study will include additional quantitative measures of 

decomposition to provide more objective approaches to PMI research. The broader impact of our 

project contributes to the efforts to quantify forensic data that have historically been subjective in 

nature. Our principal outcome will be a quantitative expansion of the commonly used TBS 

system developed by Megyesi and colleagues (2005). This will include visualizations of the 

normal variation inherent in decomposition. 

Dissemination Strategy 

The target audience for the proposed research includes forensic science researchers and 

practitioners, law enforcement, and anthropologists who conduct or apply time since death 

research and testify in court. Law enforcement agencies, forensic pathologists and criminal 

attorneys will be directly impacted by this research as time since death estimations are essential 

for identification and investigative purposes. 

Given the far-reaching significance of this research, the results will be disseminated in 

journals representing forensic science and anthropology. Specifically, abstracts will be prepared 

for the 2017 annual American Academy of Forensic Science meetings. Further, manuscripts will 

– NIJ-2015-3985 – Narrative: Expanding on Total Body Score with GIS - 17
 

	 	

be prepared for submission to the Journal of Forensic Sciences, Forensic Science International, 

and the International Journal of Legal Medicine. 

Forensic professionals, including federal, state, and local law enforcement agents and 

medicolegal investigators nationwide frequently attend the forensic short courses offered by the 

FAC. Each summer we offer a minimum of five courses that serve over 100 professionals and 

pre-professionals in the medicolegal community. Course participants come from agencies and 

universities throughout the United States and internationally. The PI and co-PI are 

faculty members able to disseminate these results through the short course curriculum. Further, 

we provide agency-specific training (e.g. to FBI Emergency Response Teams) in which our 

research figures prominently in their training. In the event of funding, the FAC will offer a 

condensed short course (2-3 days) for law enforcement to teach the protocols and analytical 

procedures for using the revised method. In addition to adult education, the PIs are committed to 

youth outreach. The FAC employs our research as a means to teach STEM to youth as we 

provide an average of 30 presentations on forensic anthropology and forensic science per year to 

school age children around the country. 

Future Directions 

This project will provide the necessary baseline data and infrastructure for standardizing 

decomposition observations in an easy-to-use format. This research can then be applied to other 

facilities capable of human decomposition research to examine the variability in different 

geographic locales. The provided infrastructure will thus allow for further researchers to create 

regional specific PMI estimation equations for broader applicability. Additionally, broadening 

the geographic breadth will aid in the identification of observations that are location specific due 

to differing environmental conditions. Lastly, additional geospatial analyses could be 

incorporated easily through GIS. For example, space-time cluster analysis could be used to 

examine the influence of decomposition patterns given the temporal differences. This way, the 

differences in decomposition processes can be analyzed seasonally to investigate significant 

differences among temporal units. Alternatively, ADD could be used as the unit in the space-time 

cluster analysis to examine the differences in ADD units through time. 

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APPENDIX I. REFERENCES 

Anderson GS, Van Laerhoven SL. 1996. Initial studies on insect succession on carrion in 

southwestern British Columbia. Journal of Forensic Sciences 41:617-625. 

Bass WM. 1997. Outdoor decomposition rates in Tennessee. In: Haglund WD and Sorg MH, eds. 

Forensic Taphonomy: The Postmortem Fate of Human Remains. Boca Raton, FL: CRC Press. 

181-186. 

Behrensmeyer AK (1978). Taphonomic and ecologic information from bone weathering. 

Paleobiology 4:150-162. 

Daubert v. Merrell Dow Pharmaceuticals, Inc. 509 U.S. 579 (1993). 

Efremov JA. 1940. Taphonomy: a new branch of paleontology. Pan-American Geologist 

74:81-93. 

ESRI 2011. ArcGIS Desktop: Release 10. Redlands, CA: Environmental Systems Research 

Institute. 

Galloway A, Birkby WH, Jones AM, Henry TE, Barks BO. 1989. Decay rates of human remains 

in an arid environment. Journal of Forensic Sciences 34(3):607-616. 

– NIJ-2015-3985 – Narrative: Expanding on Total Body Score with GIS - 19
	 	

Haglund WD. 1997. Dogs and coyotes: postmortem involvement with human remains In: 

Haglund WD and Sorg MH, eds. Forensic Taphonomy: The Postmortem Fate of Human 

Remains. Boca Raton, FL: CRC Press. 367-379. 

Haskell N, Schoenly KG, Hall RD. 2002. Testing the reliability of animal models in research and 

training program in forensic entomology, Part II, Final Report. NIJ192281. January 31, 2002, 

Award 97-IJ-CX-0046. 

Kippel WE, Synstelien JA. 2007. Rodents as taphonomic agents: bone gnawing by brown rats 

and gray squirrels. Journal of Forensic Sciences 52(4):765-773. 

Mann RW, Bass WM, Meadows L. 1990. Time since death and decomposition of the human 

body: variables and observations in cause and experimental field studies. Journal of Forensic 

Sciences 35(1):103–11. 

Marks MK, Love JC, Dadour IR. 2009. Taphonomy and time: estimating the postmortem 

interval. In: Steadman DW, ed. Hard Evidence: Case Studies in Forensic Anthropology, 2nd 

Edition. Upper Saddle River, NJ: Prentice Hall. 165-178. 

Megyesi MS, Nawrocki SP, Haskell NH. 2005. Using accumulated degree days to estimate the 

postmortem interval from decomposed human remains. Journal of Forensic Sciences 50(3):618– 

26. 

Parmenter RR, MacMahon JA. 2009. Carrion decomposition and nutrient cycling in a semiarid 

shrub–steppe ecosystem. Ecological Monographs 79(4):637-661. 

Payne JA. 1965. A summer carrion study of the baby pig Sus scrofa. Ecology 46:592-602. 

Reed J. 1958. A study of dog carcass communities in Tennessee, with special reference to the 

insects. American Midland Nature 59:213-245. 

Reeves N. 2009. Taphonomic effects of vulture scavenging. Journal of Forensic Sciences 

54(3):523-528. 

Rippley A, Larison NC, Moss KE, Kelly JD, Bytheway JA. 2012. Scavenging Behavior of Lynx 

rufus on human remains during the winter months in southeast Texas. Journal of Forensic 

Sciences (available online, onlinelibrary.wiley.com). 

Rodriguez WC, Bass WM. 1983. Insect activity and its relationship to decay rates of human 

cadavers in east Tennessee. Journal of Forensic Sciences 28(2):423–32. 

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Rodriguez WC, Bass WM. 1985. Decomposition of buried bodies and methods that may aid in 

their location. Journal of Forensic Sciences 30:836-852. 

Schoenly KG, Haskell NH, Hall RD, Gbur JR. 2007. Comparative performance and 

complementarity of four sampling methods and arthropod preference tests from human and 

porcine remains at the Forensic Anthropology Center in Knoxville, Tennessee. Journal of 

Medical Entomology 44:881-894. 

Sorg MH, David E, Rebmann AJ. 1998. Cadaver dogs, taphonomy, and postmortem interval in 

the Northeast. In: Reichs KJ, ed. Forensic Osteology: Advances in the Identification of Human 

Remains, 2nd Edition. Springfield, IL: Charles C. Thomas. pp. 120-144. 

Steadman DW, Vidoli G, Jantz LM, Williams R, DeBruyn J, Schaeffer SM. 2013. A 

multidisciplinary validation study of nonhuman animal models for forensic decomposition 

research. National Institute of Justice Grant NIJ-2013-3362. 

SWGANTH. 2013. Scientific Working Group for Forensic Anthropology Taphonomic 

Observations in the Postmortem Interval. http://swganth.startlogic.com/ 

Taphonomic%20Observations%20Rev0.pdf. Last accessed 16 March 2015. 

Synstelien J. 2009. Raccoon (Prodyon lotor) soft tissue modification of human remains. 

Proceedings from the American Academy of Forensic Sciences 15:359. 

Vass AA, Barshick SA, Sega G, Caton J, Skeen JT, Love JC, Synstelien JA. 2002. 

Decomposition chemistry of human remains: A new methodology for determining the 

postmortem interval. Journal of Forensic Sciences 47:542-553. 

Weigelt J. 1987. Recent vertebrate carcasses and their paleobiological implications (English 

translation of Weigelt 1927, by J. Schaefer). Chicago, IL. University of Chicago Press. 

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July 1 

to 

Dec. 31 

• Submit semi-annual progress repo1t to NIJ OJB - July • Place first round of 10 fall trial donors ( estimated September 20) • Analyze data from Yl trials • Submit abstract to the AAFS to present preliminruy results at 2017 Annual

Meetings August 1 • Submit quarterly financial repo1t to NIJ OJP - September 30 & December 31

Year 2 (January 1- December 31, 2017) 

Month Grant Activity 

Janmuy 1 

to 

June 30 

• Place second round of 10 winter tiial donors ( estimated Januruy 8) • Place second round of 10 spring trial donors (estimated Mru-d120) • Place second round of 10 summer trial donors (estimated June 20) • Submit quruterly financial repo1t to NIJ OJP March 30 and June 30 • Submit semi-annual progress repo1t to NIJ OJP June 30

July 1 

to

September 

30 

• Submit semi-annual progress repo1t to NIJ OJP July • Place second round of 10 fall tlfal donors (estimated September 20) • Complete all analyses • Submit absti·act to AAFS to present preliminruy results at 2018 Annual Meetings

August 1 • Submit quruterly financial repo1t to NIJ OJP - September 30 • Submit final technical repo1t - September 30

October 1 

to

Dec. 31 

• Compile all data and complete final analyses • Prepru·e mrumscripts for submission to vruious journals • Upload collected data to the National.Archive of Criminal Justice Data (NACJD) • Submit quruterly financial repo1t, semi-annual progress repo1t, and final draft of

Final Technical Repo1t to NIJ OJP

- NIJ-2015-3985 NaiTative: Expanding on Total Body Score with GIS - 23