Experimental lacustrine taphonomy:

Decompositional changes in freshwater lake

submerged Ovis aries skeletal remains within the

Pacific Coastal Western Hemlock Zone

by

Vienna Chichi Lam

B.A., Simon Fraser University, 2015

B.A., Simon Fraser University, 2011

Thesis Submitted in Partial Fulfillment of the

Requirements for the Degree of

Master of Arts

in the

School of Criminology

Faculty of Arts and Social Sciences

© Vienna Chichi Lam 2018

SIMON FRASER UNIVERSITY

Summer 2018

Copyright in this work rests with the author. Please ensure that any reproduction or re-use is done in accordance with the relevant national copyright legislation.

ii

Approval

Name: Vienna Chichi Lam

Degree: Master of Arts

Title: Experimental lacustrine taphonomy: Decompositional changes in freshwater lake submerged Ovis aries skeletal remains within the Pacific Coastal Western Hemlock Zone

Examining Committee: Chair: J. Bryan Kinney Associate Professor

Lynne S. Bell Senior Supervisor Professor

Gail S. Anderson Supervisor Burnaby Mountain Endowed Professor

Joan Bytheway External Examiner Professor College of Criminal Justice Sam Houston State University

Date Defended/Approved: August 8th, 2018

iii

Abstract

This aquatic field experiment examined the effect of freshwater submergence on

sectioned sub-adult Ovis aries (domestic sheep) femoral cortical bone discs. As a proxy

for skeletonized human remains, samples (n = 130) were deployed across ten sites at

Marion Lake, B.C., Canada. Specimens were recovered consecutively over a 16-month

period and analyzed macroscopically and microscopically for structural (artefact,

abrasion, cracking, bioerosion) and colour change. Atmospheric, lake surface, and core

temperature were also monitored, along with precipitation, water pH, cage movement,

and elemental analysis of silt composition. Bivariate analyses show a significant

relationship between taphonomic signifiers and the location of submergence, elapsed

time of submergence, and findings suggest that seasonality may impact the rate of

decomposition. The location of the cages was linked to the appearance of periosteal

abrasion and encrustation, and the loss of pre-deployment artefacts also suggests that

intentional human-induced disarticulation of bones might be obscured over time.

Keywords: Forensic Anthropology; Lacustrine; Taphonomy; Diagenesis;

Decomposition; Bone Staining

iv

Dedication

This thesis is dedicated to my late friend, Kitty.

You continue to inspire all that I do, and I am a better person for having known you.

v

Acknowledgements

I would like to begin by acknowledging that the land on which we gather on at

Simon Fraser University is the traditional territory of the Coast Salish Peoples,

specifically the shared traditional territories of the Sḵwx̱wú7mesh Úxwumixw

(Squamish), Tsleil-Waututh, and xʷməθkʷəy̓əm (Musqueam) First Nations. This

research was also conducted on the unceded traditional territory of the Katzie First

Nation. Thank you for welcoming me into your ancestral lands to pursue this research.

Huy ch q’u.

It is also with extreme gratitude that I would like to thank Mr. Ionut Aron and the

University of British Columbia Malcolm Knapp Research Forest for the use of Marion

Lake, British Columbia. Without their boat, weather station data, and access to such a

beautiful gated research facility, this project would have never been possible. There are

also many individuals that have helped me realize my dream of conducting my own

taphonomic research. Beginning with my supervising committee, I would like to thank Dr.

Lynne S. Bell for challenging the way I perceive academia, and for pushing me to strive

for the best. Her feedback throughout this process has been indispensable, and I would

not have been able to cut this thesis down to an appropriate length without her surgical

precision in finding excess. It is also with immense gratitude that I would like to thank Dr.

Gail S. Anderson for her mentorship throughout the past decade. Her encouragement

and guidance has helped me overcome many obstacles, both within and beyond

academia. From connecting me with public speaking and youth outreach organizations

to writing dozens of letters for grants and scholarships, Gail has helped given me

numerous opportunities to grow as a budding researcher. Her enthusiasm is infectious,

and I simply cannot wait to begin the next step of my academic journey under her wing!

My course supervisors and community leaders have also all helped shape my

approach to research and my appreciation for interdisciplinary work. Publishing in the

Journal of Forensic and Legal Medicine as the first author was a huge milestone for me,

and I would like to thank Mr. Randy Dalit and Dr. J. Bryan Kinney for making that

possible. It was an absolute pleasure to work as an intern at the Office of the Chief

Coroner with Randy. I also appreciate all of Bryan sharing his time, geospatial expertise,

many letters of support, and for answering my emails despite their unrelenting

vi

frequency. My course with Dr. John Whatley also changed the way I perceive forensic

sciences. I appreciate all his inspirational anecdotes, and for showing me how all

scientific endeavours come from a vantage point that remain vulnerable to subjectivity. I

would also like to thank Dr. S/Sgt. Diane Cockle for sharing her many insights and stores

about RCMP recovery work, and for being such an inspirational role model. From

leading forensic investigations with the RCMP to finding clandestine graves in war-torn

countries, this woman has really done it all! It is also with sincere gratitude that I would

like to thank Dr. Jeffrey Toward for all his support and encouragement ever since I joined

the Research Ethics Board. I have learned a tremendous amount about research design

during my time on the board, and deeply appreciate this learning opportunity. I would

also like to thank Jeff for his letters of support! I would also like to thank Dr. Richard

Frank for welcoming me into his Voices Against Extremism campaign. Taking part in this

initiative was an incredible learning experience, and I greatly appreciate all the wisdom

and Hanuta he has imparted on me these past few years.

Operating on a shoe-string budget was difficult but made incredibly easier with

the help of the generous support from faculty members, staff, and friends. I would like to

thank Dr. Karen Kavanagh for the use of her scanning electron microscope at the SFU

Nano-Imaging and Holography Laboratory, and Dr. Li Yang for her time and support in

training me on the FIB-SEM and EDAX. I would also like to thank Dr. Ronald C.

Ydenberg for supplying my field team with life jackets, Dr. Rolf Mathewes for his time

and expertise, and Suzanna Michener for helping me with my thin-sectioning and for

showing me how to mount slides. The drone photography of Marion Lake would also not

have been possible without Nelson Wu, and the SFU Archaeology department for

lending me miscellaneous field gear. Although no funding was secured for this project, I

would like to thank the Canadian Society of Forensic Science for their generous

Education Award 2016 and 2018 award that helped me pay for part of my tuition. The

awards I have received would also not have been possible without Ms. Rachel Dawson

and her incredible team at the SFU Dean of Graduate Studies Office. I would like to

thank Rachel for sharing her invaluable grant writing expertise, and for helping me turn

abstract theoretical concepts into something relatable to a wider audience.

I would like to thank my friends that I have somehow convinced to face freezing

ice storms, swarms of mosquitoes, and hours of dreadful 90’s pop music with me – you

guys are the actual best. I truly could not have asked for better bivouacking companions

vii

than Tarek Suliman and David Shaw, whom showed up without fail for every recovery

regardless of the weather conditions, and Jeffrey Yung, Kelsey Cleave, Jenny Dadswell,

and Lena Nagata for hiking up the mountain with us whenever I needed some extra

help. Tarek, your biology stories and funny commentary can always turn a miserable

snow day into one full of laughter. Your expertise offered many valuable insights that

helped shape my approach to field work and thank you for proofreading my thesis! Aside

from your technical prowess and unbounded creativity, you are also an incredible friend.

When my regulator broke and released all my air, I could not have asked for a better

dive buddy. Dave, I don’t think we would have made it up the mountain half of the time if

not for you and your trusty machete clearing the road – you are the first person I am

going to pick up in a zombie apocalypse. Thank you for taking hundreds of photos while

managing to keep the boat afloat as I recovered my samples.

Jeffrey Yung was also the best lab co-supervisor I could have asked for, and I

really appreciate you proofreading my thesis! From hundreds of tag-team-food-runs to

troubleshooting broken equipment with me, I really appreciate you being such a great

friend and lab mate. I would also like to thank Nicole Morse for the amusing laboratory

banter and for being my second set of eyes to help evaluate inter-observer error. A lot of

work was involved in producing a comparison sample that was also used to flag

discrepancies, and this process really helped me refine how I was explaining my

methods to those outside of forensic anthropology. Thanks also go to Anita Chiang and

Anna Ndegwa, for spending endless of hours with me tying thousands of fishing wire

knots, helping me with my very first deployment, and for convincing me that midnight

desserts are a real meal. And of course, I would like to thank Sonja Edwards, Maria

Nguyen, Stephanie Lau, and Daniel Reinhard for listening to me practice the same

presentation a thousand times over, and for all their emotional support. Last, but not

least, I would like to thank Reza Jooyandeh for his enduring patience during exam

season, magically making food appear when I had to work late (which was pretty much

all the time), unpaid technical support 24/7, and for reminding me to practice self-care.

viii

Table of Contents

Approval .......................................................................................................................... ii

Abstract .......................................................................................................................... iii

Dedication ...................................................................................................................... iv

Acknowledgements ......................................................................................................... v

Table of Contents ..........................................................................................................viii

List of Tables .................................................................................................................. xi

List of Figures ................................................................................................................ xii

Chapter 1. Introduction .............................................................................................. 1

Chapter 2. Relevant Literature ................................................................................... 3

2.1. Skeletal Anatomy ................................................................................................... 4

2.1.1. Human Skeleton ............................................................................................ 4

2.1.2. Mammalian Histomorphology ........................................................................ 6

2.1.3. Use of Animal Proxies ................................................................................... 7

2.2. Skeletal Taphonomy ............................................................................................ 10

2.2.1. Skeletal Abrasion ......................................................................................... 11

2.2.2. Microbial Alterations and Bioerosional Microboring (Pitting) ......................... 12

2.2.3. Encrustation, Botanic Growth, and Mineral Deposits ................................... 15

2.2.4. Aquatic Post-mortem Movement .................................................................. 17

2.3. Pacific Coastal Western Hemlock Zones ............................................................. 18

Chapter 3. Research Design .................................................................................... 21

3.1. Research Objectives ........................................................................................... 21

3.2. Research Questions ............................................................................................ 22

Chapter 4. Material and Methodology ..................................................................... 24

4.1. Logistics .............................................................................................................. 24

4.2. Materials .............................................................................................................. 27

4.2.1. Sample Selection ......................................................................................... 27

4.2.2. Preparation Methods ................................................................................... 28

4.2.3. Deployment Protocol ................................................................................... 29

4.2.4. Recovery Protocol and Sample Preparation for Analysis ............................. 30

4.2.5. Collection of Water and Silt Samples ........................................................... 31

4.3. Data Analysis ...................................................................................................... 33

4.3.1. Measurements and Research Instruments .................................................. 33

4.3.2. Macroscopic Analysis using Light Microscopy ............................................. 34

4.3.3. Microscopic Examination of Thin-Sectioned Skeletal Samples .................... 34

4.3.4. Structured Qualitative Analysis of Skeletal Change ..................................... 36

4.3.5. Silt Sample Preparation ............................................................................... 36

4.3.6. Elemental Profiling of Silt Samples .............................................................. 37

4.3.7. Temperature and Precipitation Data ............................................................ 38

4.3.8. Water pH Data ............................................................................................. 38

ix

4.3.9. Cage Depth and Movement Data................................................................. 38

4.4. Variable Operationalization .................................................................................. 41

4.4.1. Datasets ...................................................................................................... 41

4.4.2. Artefacts ...................................................................................................... 45

4.4.3. Post-mortem Decompositional Changes ...................................................... 46

4.4.4. Statistical Analysis ....................................................................................... 50

4.5. Ethics Exemption and Animal Care/Control ......................................................... 52

Chapter 5. Results .................................................................................................... 53

5.1. Results involving skeletal materials ..................................................................... 53

5.1.1. Overall Size and Weight .............................................................................. 54

5.1.2. Descriptive Statistics for Skeletal Samples .................................................. 55

5.1.3. Primer on the Environmental Impact on Skeletal Change ............................ 57

5.1.4. Primer on the Impact of Submergence Periods ............................................ 58

5.1.5. Primer on the Impact of Winter Lake Freeze on Skeletal Change ................ 59

5.1.6. Loss of Pre-deployment Bony Lipping and Saw Mark Artefacts ................... 60

5.1.7. Pitting versus Vascularity ............................................................................. 64

5.1.8. Abrasion and Cracking ................................................................................ 67

5.1.9. Evaluation of Sectioned Surface and Internal Bone Colour .......................... 73

5.1.10. Blue and Green Staining from External Agents ........................................ 76

5.1.11. Black Surface Deposit .............................................................................. 79

5.1.12. Depth of Taphonomic Surface Change .................................................... 80

5.2. Results involving non-skeletal materials .............................................................. 80

5.2.1. Elemental Profiling of Silt Samples .............................................................. 80

5.2.2. Temperature and Precipitation ..................................................................... 81

5.2.3. Water pH ..................................................................................................... 80

Chapter 6. Discussion .............................................................................................. 82

6.1. Lacustrine Skeletal Taphonomy ........................................................................... 82

6.1.1. Control Specimens ...................................................................................... 83

6.1.2. Pre-deployment Artefact Loss ...................................................................... 83

6.1.3. Post-depositional Selective Staining of Vascular Structures ........................ 84

6.1.4. Abrasion Coastal Lake Systems and Geology ............................................. 85

6.1.5. Cracking along the Periosteum and Cross-sectional Block Face ................. 87

6.1.6. Surface Bone Colour Change and Surface Staining from External Agents .. 88

6.1.7. Encrustation and External Deposits ............................................................. 89

6.2. Conducting Experimental Research – Lessons from the field .............................. 90

6.3. Monitoring Environmental Conditions .................................................................. 92

6.3.1. Lake Floor Composition ............................................................................... 92

6.3.2. Temperature and Precipitation Fluctuations ................................................. 93

6.3.3. Lake Acidity Gradient ................................................................................... 94

6.3.4. The Impact of Wildlife .................................................................................. 95

Chapter 7. Conclusion and Future Research ......................................................... 96

x

References ................................................................................................................. 100

Appendix. Munsell Colour Codes .................................................................... 109

xi

List of Tables

Table 4.1. Operationalization of environmental condition variables. ........................ 41

Table 4.2. Operationalization of Ovis aries sample variables. ................................. 42

Table 5.1. Descriptive statistics of the measurement variables of all bone discs (n = 130). ....................................................................................................... 55

Table 5.2. Coding of variables and the descriptive statistics of the experimental parameter variables (n = 129). ............................................................... 56

Table 5.3. Coding of variables and the descriptive statistics of artefact and taphonomy variables (n = 129). .............................................................. 56

Table 5.4. Bivariate associations between the location of variables (IV)1, length of submergence (IV)1, and exposure to lake freeze (IV)1 to the loss of saw marks (DV)1 and bony lipping (DV)1 artefacts (n = 129). ......................... 63

Table 5.5. Kruskal-Wallis rank scores of the total number of cutting cones by laboratory (controls) or submergence location. ....................................... 66

Table 5.6. Bivariate associations between periosteal abrasion, periosteal cracking, and transverse cross-sectional cracking (DV) and the location of the samples (IV)1 (n = 129). ......................................................................... 72

Table 5.7. Bivariate associations between bone colour changes (DV)1 and the location of the samples (IV)1 (n = 129). .................................................. 75

Table 5.8. Bivariate associations between bone staining (DV) and the location of the samples (IV)1 (n = 129). ......................................................................... 78

Table 5.9. Bivariate associations between black surface deposits (DV) and the location of the samples (IV)1 (n = 129). .................................................. 79

xii

List of Figures

Figure 4.1. Chart illustrating the calendar date of deployment and recoveries, as well as the number of days elapsed since the initial deployment and recovery of specimens. ......................................................................................... 26

Figure 4.2. Photograph of the frozen lake (right and 950 m uphill hike through the snow with field equipment (left) during the March 2017 recovery. .......... 26

Figure 4.3. Photograph of Ovis aries femur discs immediately after the sectioning and maceration process at a local butchery. ................................................. 27

Figure 4.4. Illustration (left) and photograph (right) depicting how the Ovis aries bone discs were tethered to cages, cage marking, and appearance after one month of submergence (cage and samples fully intact). ......................... 28

Figure 4.5. Photograph of Ovis aries control sample, and the cross-sectional transverse block face face 1, block face 2 and the periosteal surface. ... 30

Figure 4.6. Lam (left) and Suliman (right) diving for silt samples from the bottom of the lake. ................................................................................................. 31

Figure 4.7. Bathymetric map of the locations from which water and silt samples were collected (adapted from UBC MKRF and Efford, 1967). ......................... 32

Figure 4.8. Illustration of how a radial graph was used to map and document taphonomic change. ............................................................................... 33

Figure 4.9. Photograph of the both the Au sputtered and untreated silt samples (deep water, head water, and swamp water) on carbon tape and aluminum pins. ............................................................................................................... 37

Figure 4.10. Bathymetric map of cage deployment locations (indicated by capital letters), cage movement for the duration of the experiment (shaded regions), and the lake inflow and outflow (note that the Northeast inflow makes a minor contribution) (adapted from UBC MKRF and Efford, 1967). ............................................................................................................... 40

Figure 4.11. Image of three different types of artefacts examined on the transverse cross-sectional plane of a control bone: bone lipping, orientation lines, and saw marks (codex). ......................................................................... 45

Figure 4.12. Illustration depicting what the periosteal surface, endosteal surface, and cross-sectional transverse block face of a bone disc. ............................. 46

Figure 4.13. Image of periosteal abrasion and cracking of experimental bones, as compared to the periosteal surface of control specimen under a light microscope at x5 magnification: (A) periosteal surface (control bone), (B) cross-sectional surface (control bone), (C) periosteal cracking, (D) periosteal cracking, (E) periosteal abrasion, (F) transverse cracking (codex). .................................................................................................. 47

Figure 4.14. Image depicting pitting and black deposits (surface inclusions) identified on the cross-sectional transverse block face surface of experimental bones, using a light microscope at x5 magnification: (A) control bone, (B) black deposits, (C) pitting (codex). ......................................................... 48

Figure 4.15. Image showing different bone colours on the cross-sectional transverse block face, using a light microscope at x5 magnification: (A) white (control bone), (B) white-beige, (C) beige, (D) beige-brown, (E) brown (codex). . 49

xiii

Figure 4.16. Image of blue and green staining, using a light microscope at x5 magnification: (A) blue staining on the transverse cross-sectional block face, (B) green staining on the transverse cross-sectional block face, (C) blue staining on the periosteal surface, and (D) green staining on the periosteal surface (codex). ..................................................................... 50

Figure 5.1. A low magnification macroscopic image of localized cutting cones (originally thought to be bioerosion and/or pitting) under a light microscope. ............................................................................................ 65

Figure 5.2. Boxplot depicting the distribution of cutting cones per location (CFR Laboratory, Location A – J). Outliers within one degree of freedom is denoted by ‘o’ and any outliers beyond that distance is denoted by an ‘ * ’. ............................................................................................................... 66

Figure 5.3. Light microscope image of the periosteal surface of a submerged, experimental sample that illustrates the appearance of exposed cortical bone (right) and the periosteum (outermost layer of bone) retained (left). ............................................................................................................... 68

Figure 5.4. Light microscope image of the periosteal surface of a submerged, experimental sample’s distinctive boundary between exposed vascular structures from abrasion (left), and a surface abraded but retained (right). ............................................................................................................... 68

Figure 5.5. EDAX spectrum (elemental profle) of the swamp silt sample (ppm), as an example of typical SPC (.spc file extension) format output. .................... 81

Figure 5.6. Line chart depicting the mean (atmospheric) temperature, lake surface temperature, and lake temperature 2m below the dock in celsius (oC) between March 2016 to July 2017. ......................................................... 83

Figure 5.7. Line chart depicting the temperature trends from January 2016 to September 2017. The blue line represents the maximum atmospheric temperature, the grey line represents the mean atmospheric temperature, and the orange line represents the minimum atmospheric temperature. This analysis is based on more than 639 days worth of data (1917 data points) was collected from the Government of Canada’s Past Weather and Climate - Historical Data Centre. ..................................................... 84

Figure 5.8. Line chart depicting the total daily rain fall from March 2016 to July 2017 (duration of the experiment). .................................................................. 80

Figure 5.9. Illustrative map of the water pH by location across Marion Lake, along with silt sample extraction locations (adapted from UBC MKRF and Efford, 1967). ......................................................................................... 81

Chapter 1. Introduction

Forensic anthropology is a subfield within physical anthropology that involves the

application of human osteology (skeletal anatomy) in criminal justice matters

(Christensen et al., 2014; Pokines & Symes, 2014; Saferstein, 2018). This may include

the identification of persons, understanding pathological hardships that a person

experienced during their life, and what has happened to the body post-mortem (after

death). Discerning secondary movement and the point of origin is especially difficult in

cases where the deceased has been submerged in naturally occurring water bodies,

such as a lake, river, and/or the ocean. It has been reported that the loss of soft and

connective tissues submerged in water may cause rapid skeletonization (Anderson &

Bell, 2014; Haglund & Sorg, 2002; Hobishak & Anderson, 1999). Knowing what

environmental, temporal, and seasonal effects have on bones can help investigators

establish the post-mortem journey, develop a better understanding of when the body

may have first entered the water, and perhaps lead to the recovery of other skeletal

elements that have been lost by targeting likely points of origin (Jans, 2014, p. 25;

Pokines & Symes, 2014).

Currently, studies that have examined differential skeletal degradation between

marine, inter-tidal, transitional, and freshwater environments remain few and far between

in comparison to those conducted in terrestrial contexts. Hydrodynamic conditions can

vary dramatically in temperature, water salinity, water acidity, geological and

sedimentary composition, scavenger population, and microbial communities housed

(Donovan, 2002; Haglund & Sorg, 2002). Ecological niches may produce different types

or variations of common decompositional changes, also known as taphonomic signifiers.

Understanding the degenerative alterations in skeletal tissues can help death

investigators determine potential areas where bodies may have entered or spent time in,

prior to their recovery. To uncover and validate these environment-specific changes,

regional studies should be conducted within their respective ecological zones, such as

the Western Hemlock Zone in British Columbia.

2

To provide much needed information on the effects of lacustrine taphonomy on

skeletal remains specific to the Pacific Coastal Western Hemlock Zone, this dissertation

research involved the macroscopic examination of various changes in cortical bone

surface topography, as well as skeletal tissue surface colour change and extraneous

material deposits. Sectioned Ovis aries (domestic sheep) immature femoral shafts were

deployed and retrieved from Marion Lake, University of British Columbia Malcolm Knapp

Research Forest, British Columbia, Canada. Osteometric and morphoscopic analyses

were performed to compare the impact(s) of (1) sample submergence location, (2)

elapsed time, and (3) the sample’s exposure to natural winter conditions on the

development of decompositional alterations. Environmental conditions were closely

monitored and reported to help define the parameters of this experiment, including

temperature (atmospheric, lake surface, and lake core), precipitation (rainfall), elemental

analysis of lake floor sediment, water acidity, and cage movement.

3

Chapter 2. Relevant Literature

Physical anthropology is the study of human evolution, comparative anatomy,

and skeletal biology to better understand the human condition (Christensen et al., 2014).

Forensic anthropology is a subfield within this discipline that is concerned with the

application of physical anthropology in legal matters, including the identification of the

deceased, establishing biological profiles, identifying pathologies and trauma, as well as

establishing the post-mortem journey of remains prior to their recovery (Christensen et

al., 2014; Pokines & Symes, 2014; Saferstein, 2018). Taphonomy is the study of

fossilization, and has traditionally encompassed the field of diagenesis, the study of

changes in fossil chemistry and surrounding sediments (Donovan, 2003).

Anthropologists have since adapted this term to include biostratinomy - the study of

decompositional mechanisms that alter carcasses after death (Donovan, 2003).

Together, skeletal biologists can apply the theories and practices from physical

anthropology and taphonomy to aid in missing persons cases, identification of victims of

natural mass disasters, distinguishing trauma from post-mortem degradation, finding

evidence of war crimes, and find evidence of secondary movement of bodies (Jans,

2014, p. 25; Pokines & Symes, 2014).

Despite its utility, the use of forensic anthropology in judicial matters has also

been increasingly scrutinized over the past decade due to issues arising from the

misinterpretation of results leading to wrongful convictions. Ever since the National

Academy of Science (NAS) (2009) challenged the legitimacy of forensic sciences as

used in the United States criminal justice system, it has become more imperative for

researchers to report error rates, articulate the limits of their findings, and disclose the

theoretical basis for their interpretations. Goudge (2008) drew awareness to the misuse

of forensic data within Ontario’s courtrooms by a rogue forensic pathologist, clearly

demonstrating that Canada is facing similar issues as the ones discussed by NAS.

These two influential reports have highlighted the importance of being critical when

reviewing literary works and the legal ramifications of conducting unsubstantiated

research, falsifying results, and/or purposely misleading the scientific community by

overstating the applicability of findings. For this reason, the theoretical basis of this

4

thesis has been summarized below and includes a discussion of skeletal anatomy,

lacustrine taphonomy, and the environmental backdrop of this study.

2.1. Skeletal Anatomy

Humans rely on their skeleton for structural and mechanical support, protection of

vital organs and tissues, mineral homeostasis (regulation of calcium and phosphorus

levels), and hematopoiesis (formation of blood cells) (Burr & Akkus, 2014). Bones are

part of the musculoskeletal system and their primary function will differ from element to

element, as seen in their different shapes, sizes, muscle attachment sites, and formation

(White, 2005). Experimental studies on human bone adaptability show that skeletal

tissue is architecturally well equipped to distribute weight and can adapt to

environmental stressors through bone repair and remodelling (Oxnard, 2004). This ability

to adapt and change results in humans having considerable variability in their bone

density, size, and structure, which may impact their rate of change post-mortem. It is

also common to use animal proxies in lieu of human remains in the development of

taphonomic models, as used to discern human versus animal bones, the depositional

environment, secondary movement, elapsed time since death, amongst other important

forensic inquiries.

In general, the field of comparative anatomy involves the comparison of

locomotion, variations of the basic mammalian skeleton, and musculoskeletal

adaptations (Stein & Rowe, 2003). A comparison between human and animal bone

tissue is important to this research because this study utilizes cortical bone tissue from

the Ovis aries (domestic sheep) diaphysis (Carter & Tibbett, 2006; Griffiths & Thompson,

2017). As such, key terminology has been discussed throughout this chapter. First, a

brief examination of relevant human skeletal anatomy will be addressed, followed by a

discussion of the use of animal proxies and common approaches to taphonomic studies.

2.1.1. Human Skeleton

The average human adult skeleton has 206 bones, not including variable bones

like sesamoids (White, 2005). Diaphysis refers to the long bones in a body (Marieb et al.,

2014). Bones can be examined and described in three general levels of magnification.

With the naked eye, human bones can be looked at macroscopically, which is often

5

referred to as gross-anatomical examination. Using high-powered microscopes, the

microscopic analyses of skeletal tissue can be viewed, which falls under the realm of

histological analyses. Skeletal materials can also be examined molecularly, which can

involve a plethora of methods to measure both the inorganic and organic chemical

compounds in samples (Christensen et al., 2014).

In archaeology, mass disaster recoveries, and in investigations involving

clandestine graves, macroscopic visual analyses are often used to determine the

minimum number of individuals (MNI score) (Christensen et al., 2014). By looking at

whole or fragmented bones and their characteristics, forensic anthropologists can try to

determine the number of different individuals within comingled remains, whether the

bones belong to humans or another species, and develop a biological profile

(Christensen et al., 2014). Biological profiles are the description of a person based on

their body, such as age, sex, stature, ancestry, pathologies, trauma, and the presence of

medical apparatus. At the gross anatomic level, bones can also be categorized into

either cortical bone (also referred to as compact bone), and trabecular (also known as

cancellous or spongy) bone.

Cortical bone is very dense due to the number of cylindrical osteons that are

compacted against one another (Burr & Akkus, 2014). The outer surface portion of

cortical bone is called the periosteal zone, where the outermost protective layer

(periosteum) resides. The central portion of bone is called the mesoteal zone, and the

innermost portion is called the endosteal zone (Klevezal, 1996). Osteons are cylinders

with many concentric lamellar layers that serve as individual units of the Haversian

system, a structure that house the osteocytes that are responsible for bone resorption

and replacement (Burr & Akkus, 2014). While animals are alive, the bone-forming units

(BMU) in osteons will continue to break apart old bone tissue by secreting osteoclasts

and form new bony tissue with the release of osteoblasts; to do this, nutrients must be

carried from the Haversian (central) canal that are at the center of osteons (Allen & Burr,

2014). The small canals that connect Haversian canals to each other are called

Volkmann’s canals (Christensen et al., 2014). The development of primary bone and

remodelled secondary bone can be further classified into fibrolamellar, lamellar, woven,

and/or Haversian bone tissue types based on their bone type and organizational pattern

(Bell, 2012; Hillier & Bell, 2007; Mulhern & Ubelaker, 2012).

6

Osteons can be further categorized into cutting heads, transversely cut osteons,

longitudinally cut osteons, and sealed osteons (Pazzaglia et al., 2013). In a study that

utilized scanning electron microscopy (SEM) to examine osteon frequency, bone density,

bone area, and vascular spaces in four healthy adult human trabecular bone, Pazzaglia

and colleagues (2013) found that osteon size is largely determined by the amount and

behaviour of cutting head osteoclasts. Vascularity in skeletal tissue is dynamic; in

addition, the process of bone metabolism and turnover is created by cutting cones,

which is the total area of osteoclastic tunnelling (Klein-Nulend et al., 2003; Pazzaglia et

al., 2013).

The number of osteons will increase as the animal matures, and the size of each

osteon will fluctuate between different organisms even if they are of the same age and

species. At the molecular level, bones are made from both organic and inorganic

compounds (Christensen et al., 2014). The organic components consist primarily of

collagen, which is the substance that gives your bones elasticity. The inorganic

component that makes bones rigid and strong is primarily made of calcium phosphate,

which together creates hydroxyapatite (Ca10(PO4)6(OH)2) (Christensen et al., 2014, p.

20). Cortical bone tissue is comprised of approximately 65% minerals (primarily

carbonated apatite), 25% organic material (collagen and non-collagenous proteins), and

10% water (Burr & Akkus, 2014, p. 5).

2.1.2. Mammalian Histomorphology

Bony arrangement in mammals is varied between species, and this range in

microstructural forms include compact bone, trabecular bone, and plexiform bone (Hillier

& Bell, 2007). Plexiform bone is the longitudinal arrangement of primary osteons and

vascular canals that appears like a running bond brick pattern (Brits et al., 2014;

Francillion-Vieillot et al., 1990). This feature has also been described as linearly oriented

osteonal systems, also known as osteonal banding (Mulhern & Ubelaker, 2012).

Although they recognize that plexiform bone may in rare cases be found in human bone

tissue, Mulhern and Ubelaker (2012) argue that plexiform bone in humans appear in

short segments, making plexiform bone more diagnostic of non-human animal tissue.

Recent studies suggest that plexiform microstructure can be seen in a small sample of

human bones (18%, n = 23 out of 129) using synchrotron radiation computed

tomography (SR-CT) (Andronowski et al., 2017; Ito et al., 2003). As such, contentious

7

issues commonly raised in experimental taphonomy are whether non-human mammalian

skeletal tissue can be considered a suitable proxy for Homo sapiens sapiens (modern

humans), and whether physiological differences impact the rate of decompositional

changes. There is also concern about whether the methods developed from animal-

based studies can be later extrapolated and applied to forensic cases involving humans.

This subsection will review the differences in animal versus human cortical bone, as well

as explore the use of animal proxies in taphonomic research.

2.1.3. Use of Animal Proxies

Histomorphological Variance. Histological studies of mammalian bone

structure suggest that differences in Haversian system diameter, Haversian canal

diameter, and Haversian system density can distinguish humans versus animal (rat, cat,

dog, hare, badger, racoon, dog, and deer) cortical bone (Hillier & Bell, 2007). Aside from

Haversian canal-related size differences, plexiform bone and osteon banding are

considered diagnostic of non-human microanatomy (Cattaneo et al., 1999; Dominguez &

Crowder, 2012; Hillier & Bell, 2007). Mulhern and Ubelaker (2001) believe that osteon

banding is also useful for distinguishing human versus non-human bone. Osteon shape

and circularity has also been used to distinguish humans from dogs and deer

(Dominguez & Crowder, 2012).

Plexiform arrangement may be useful to distinguish animals, but there is little

research to suggest that this difference has an impact on taphonomic decomposition

outside of age estimation. Moreover, recent studies have shown that patients with

periostitis (inflammation of periosteum) and fetuses during the early stages of

development may exhibit plexiform bone structure (Mackay-Sim & Chuah, 2000). A

medical case study also took note of plexiform arrangement, dating as far back as the

early 20th century by two surgeons (White & Thomas, 1907). Aside from pathologies that

cause bone abnormalities, Andronowski et al. (2017) found that human adult cortical

bone may also exhibit osteonal banding if examined using three-dimensional

visualization of skeletal tissue using micro-computed tomography (SR micro-CT). Brits,

Steyn, and L’Abbe (2014) compared the histomorphology of several modern and

archaeological femora to develop a classification system. In their study, they also found

that haversian bone was found in cats, dogs, horses, donkeys, and primates (including

humans).

8

Mammalian Bone Density. In a taphonomic comparison of bone density in

domestic pig (Sus scrofa), domestic cattle (Bos taurus), and domestic sheep (Ovis

aries), Ioannidou (2003) found that bone density variability exists between and within

species. In addition, Ioannidou’s (2003) results show that density models should

consider the maturity of S. scrofa, but this was less of a concern when examining O.

aries remains. Instead, male O. aries were found to be denser than females and intra-

taxonomic variability was found to be high (Ioannidou, 2003). This suggests that the

subspecies and sex of O. aries should be considered when evaluating taphonomic bone

density for age estimations. Another study of bone density in fused and unfused O. aries

(domestic sheep) bones found that taphonomic bias in age estimation may differ

depending on which element is being considered (Symmons, 2005). Interpreting

mortality profiles in archaeofaunal assemblages using fusion status of bones is also not

reliable but measuring bone density can be a good indicator of age for maturity-mediated

taphonomic research (Symmons, 2005).

Differences in skeletal robusticity between species can also impact preservation

rates. Population health in humans and animals is dynamic. Human bone tissue may

respond differently to thermal damage, ballistic trauma, and other decompositional

effects due to differences in bone density and microstructural differences (Brits et al.,

2014). In a histological comparison of mouse, hamster, rat, guinea pig, rabbit, cat and

dog cortical bone, Horner et al. (1977) found that the osteonal sizes between animal

species differed greatly, and the density of bone by maturation differed disproportionally

(in Pazzaglia et al., 2013). It has yet to be proven that cutting cone size and the different

rate of maturation in bone would impact rate of taphonomy, but this study does point to

the importance of conducting a thorough examination of all samples prior to

experimentation. If species mature at different rates and the samples used are not all

from the same population and/or of the same age, then the differences in sample bone

matrix at the start of the study may result in different onset of taphonomic change;

thereby, violating the assumption that all samples being compared are the same to begin

with.

Soft Tissue Decomposition. Taphonomic experiments often employ the use of

Ovis aries (domestic sheep) and Sus scrofa (domestic pig) in place of human bodies

because of their commercial accessibility. For decompositional studies involving soft

tissues, S. scrofa carcasses are often used because of their skin structure and gut

9

content that harbours similar microbial communities as humans (Anderson & Hobischak,

2004; Weiss et al., 2016). In contrast, Connor and colleagues (2017) from the Forensic

Investigation Research Station in Colorado recently compared the decompositional

changes in pigs (n = 17) and humans (n = 22) and found considerable differences in

decomposition rates between pigs and humans. The total number of accumulated

degree days (ADD) to reach different decompositional stages (measured using total

body score (TBS)) was higher in humans during early stages of decomposition, and then

an inverse relationship would occur, where the ADD required to reach later stages of

TBS would be greater in S. scrofa (domestic pigs) (Connor et al., 2017). Pigs also

generally showed greater variation in their rate of decomposition than humans in

terrestrial environments (Carter & Tibbett; 2006; Connor et al., 2017). Aquatic

decompositional studies using S. scrofa domesticus have been pursued, but it is unclear

whether humans would decompose similarly. Based on the Köppen-Geiger climate

classification system, Connor et al.’s (2017) research was conducted in a mid-latitude

steppe/semiarid cool environment. Terrestrial studies involve vastly different

environments than aquatic ones and pointed to how region-specific taphonomic studies

are required to properly compare human and animal proxy decomposition.

Animal Proxy Usefulness. Animal proxies can be amassed in a great quantity

for greater sample sizes, which also gives researchers the ability to be more selective

with their sampling methods. Collecting human specimens in an ethical manner depends

largely on who has donated their body for science. With animal proxies, researchers can

control for chronological age, bone maturity, sex, weight, subspecies, trauma, and other

health factors so samples used can be more homogeneous. Samples showing

pathologies such as metabolic disorders, hormonal imbalances, infections, diseases,

trauma, and developmental issues can be flagged and replaced with much greater ease

in animals than human donations. Immature bones, human or animal, are thought of as

being more susceptible to taphonomic destruction due to their more fragile structure

(Binford & Bertram, 1977; Symmons, 2005); being able to procure more samples in

experiments where sample retention is a concern makes the use of animal proxies very

appealing.

Acquiring samples can also be achieved by visiting local butchers, whereas the

collection of human skeletal materials requires extensive ethical and logistical

procedures. Many facilities are also not equipped to receive body donations or have the

10

ability to meet federal and institutional requirements for the ethical treatment of remains.

There are also mental and physical health risks to research personnel to be considered

(Bytheway et al., 2015). Overall, further studies are required to evaluate whether the

skeletal tissue types and formation in different species would impact taphonomic change

but the use of animal proxies is seen as acceptable given its close proximity to human

remains, commercial availability, and supported usage in the existing forensic

anthropology literature.

2.2. Skeletal Taphonomy

In general, any post-mortem alteration is also known as diagenesis, which

includes any physical, chemical, and structural changes (Bell, 2012). This term is often

associated with taphonomy, which is the study of the processes that alter biological

organisms upon their death (Pokines, 2014, p. 3). Within this broad field of taphonomic

research, there are many subcategories that include (but are not limited to)

saponification, mummification, microstructural taphonomy, the study of microbial

communities, biogeochemical change (Christensen et al., 2014). Some studies focus

solely on scavenger behaviour, with the most common ones being insects, carnivores,

rodents and microbes (Saferstein, 2011). Histotaphonomy is the study of microstructural

diagenesis (Bell, 2012). Common microstructural changes include bioerosion,

mechanical weathering, and fluvial erosion (Christensen et al., 2014; Griffiths &

Thompson, 2017). Several studies on aquatic taphonomy have also examined a

combination of abrasion, disarticulation, dissolution, encrustation, fragmentation, spatial

orientation, and scavenging marks from aquatic fauna (Donovan, 2002; Griffiths &

Thompson, 2017; Parsons & Brett, 1991; Sorg et al., 1997). Regarding aquatic

environmental factors, obstructions and access to the water surface, temperature,

clothing, biodiversity, sea floor substrate and geology, time of death, and water

chemistry are also commonly considered (Anderson & Hobischak, 2002; Sorg et al.,

1997).

Approaches. Methodological approaches can also be further broken into either

morphoscopic or osteometric measures. Morphoscopic approaches involve the

assessment of degrees of expression and morphological features on bones, such as the

absence or presence of features (Haglund & Sorg, 2002). This method heavily relies on

the researcher’s expertise and is subject to inter-observer bias. This being said, it plays

11

an important role in the study of forensic anthropology because of its undeniable utility.

On the other hand, osteometrics require the researcher to know how to use research

instruments and this method relies on good parent data so that statistical inferences can

be made. Many osteometric analyses also require landmarks to be present on the bone

in order for certain measurements to be made, which hinders its usefulness in cases

where the bone is fragmented or has undergone substantial structural decay

(Christensen et al., 2014; Haglund & Sorg, 2002). Approaches at the microstructural

level are often associated with histology (Bell, 2012). For instance, histomorphometrics

is the quantification of histological structures within bone tissue (Hillier & Bell, 2007).

Bone Visualization. Bone visualization techniques can also vary, depending on

the magnification desired and features being examined (Bell, 2012). For instance, digital

photodensitometry (DP) is a method of measuring radiodensity in a variety of materials,

including bone (Symmons, 2004). High-resolution x-ray imaging also enables three-

dimensional visualization of bone microarchitecture (Andronowski et al., 2017). Other

methods of bone visualization include the use of geographical information systems

(Parkinson et al., 2014; Rose et al., 2012), magnetic resonance imaging (MRI) (Chuah et

al., 2013; Loeuille & Cary-Valckenaere, 2012; Wu et al., 2011), scanning electronic

microscopy (SEM) (Bell & Jones, 1991; Bell et al., 1996; Schneider et al., 2011; Tersigni,

2007; Wierzchos et al., 2008), and computed tomography (CT) using x-rays from many

angles (Demehri et al., 2015; Klein et al., 2008; Wu et al., 2014).

2.2.1. Skeletal Abrasion

Abrasion is the process by which suspended, mobile sediments that come in

contact with bone, rocks, or other materials of interest (Cook, 1995; Griffith & Thompson,

2017; Thompson et al., 2011). It is a geological term used to describe the process of

rounding, polishing, and smoothing bone, whereby small grains make impact and

effectively sand off irregular or loose surface materials (Griffith & Thompson, 2017;

Haglund & Sorg, 2002). Potts (1988) recognized that energetic water had the ability to

carry sediments that could abrade articular ends of bone, and even obliterate muscle

attachment sites (In Haglund & Sorg, 2002). Brooks and Brooks (1997) argue that being

able to identify abrasion is important in aquatic investigations because abrasion can

greatly distort other taphonomic features and make it difficult to detect signs of trauma,

especially if these other features are superficial in depth (in Haglund and Sorg, 2002).

12

When submerged in an environment with high-energy currents with rocky bottoms,

bones were found to break, exhibit signs of blunt force trauma, and in some cases,

become fragmented, dispersed, or lost (Brooks & Brooks, 1997; Haglund & Sorg, 2002;

Nawrocki et al., 1997).

Water-based abrasion on fresh, weathered, and fossilized bone fragments were

also analyzed by Fernandez-Jalvo and Andrews (2003). They argue that information on

the type of sediment and coarseness of the grain can be extrapolated from the bones,

but they did not discuss how this causal inference was made. There could be other

taphonomic measures responsible for the changes observed. In another study involving

bone submergence, the same environmental effects that abraded soft tissues were

found to continue even after the body was skeletonized (Haglund, 1993). Findings from

this study support the idea that the effects of abrasion can be found during the early and

late stages of decomposition, and that this feature is not only recognizable in skeletal

remains.

Griffith and Thompson (2017) recently used laser scanning to visualize and

quantify the amount of sediment abrasion on water-submerged bones. Laser scanning

was used to map the surface topography of bones. They argue that their method can

provide a good approximation of surface changes and offers a non-destructive method

of calculating volumetric differences between samples. Their findings also suggest that

the natural variation between samples pre-abrasion makes it difficult to establish a linear

relationship between the amount of wear and the length of submergence (Griffith &

Thompson, 2017). Their previous studies also have showed that looser materials are

first removed before abrasion would take place, so the differences in amount of soft

tissues and other obstructions over the bone may significantly impact the amount of

abrasion (Griffith et al., 2016; Griffith & Thompson, 2017; Thompson et al., 2011). There

also appears to be a difference in abrasion patterns between archaeological versus

modern bones, which can be attributed to the level of preservation in skeletal materials

since weathered materials can be structurally weaker than that of fresh remains.

2.2.2. Microbial Alterations and Bioerosional Microboring (Pitting)

Microstructural taphonomy is largely attributed to the effects of microbial bodies

such as plants, invertebrates, and vertebrates. These include and are not limited to the

13

effects of saprotrophic bacteria and fungi, as well as carbonaceous substrates (Carter &

Tibbett, 2006; Swift et al., 1979; Weiss et al., 2016). A saprotroph is any organism,

especially fungus or bacterium that consumes dead organic material for nutrients

(Deacon, 2009). It is the organic components that entice bacteria and other

microorganisms to those areas, and the damage they inflict from absorbing the remnant

nutrients that causes taphonomic changes to the structure of osteons (Jans, 2014). This

change can take the form of pitting or expansion of existing vascular structures (Jans,

2014). Hedges et al. (1995) described three different types of distribution patterns of

bacterially induced bone alterations, those around osteons, Haversian canals, and those

that follow fractures caused from trauma. Hackett (1981) categorized microscopic focal

destruction (MFD) into linear longitudinal, lamellate and budded foci damage, and one

Wedl-type of microboring attributed to fungal attack (Hackett, 1981; Wedl, 1964 in

Pesquero et al., 2010). Depending on the aim of the study, bioerosional microboring are

either examined collectively as a microbial biomass or individually; some even go as far

as identifying the specific strain of bacteria, fungi, yeasts, algae, and protozoa (Carter &

Tibbett, 2006; Sakamoto & Oba, 1994; Savin et al., 2001).

Corrosion, pitting, and dissolution have all been used to describe the same

feature where holes appear to be made on the surface of exposed, submerged bones

(Haglund & Sorg, 2002). Parsons and Brett (1991) believe that bioerosion occurs from

organisms that bore into bone as a means of finding shelter. Grazing can also occur, but

the agent responsible for these changes has yet to be identified with confidence in the

existing literature. Studies have suggested that pitting occurs in areas with high salinity,

low temperatures, or active bioturbation, and can appear within less than a year of

submergence (Sorg et al., 1997). Enlarged osteocyte lacunae caused by microbial attack

has also been documented in studies of terrestrially exposed conditions, including buried

or exposed on the ground surface (Kontopoulos et al., 2016). This type of destruction

was found in either the periosteal, sub-periosteal, and endosteal surface, where only two

samples were destroyed across the entire section, and the rest showed small

localization of this taphonomic change (Kontopoulos et al., 2016).

The range of bacterially induced staining in marine submerged skeletal remains

has not been reported, but bacterial remodelling and microboring has been seen

appearing on existing vascular and cell networks (Bell & Elkerton, 2008). They appear

on the external surface layers of skeletal tissue that seems predominately peripheral in

14

nature. Their findings suggest that remodelled features are not limited to existing

osteonal structures, features are densely packed on the bone surface. This study does

not identify a specific microorganism as the cause of this taphonomic feature, but does

attribute them to endoliths (archaeon, bacterium, fungus, lichen, algae, and/or amoeba)

with cyanobacteria being the likeliest contributor (Bell & Elkerton, 2008). Periosteum-

penetrating micro-tunnels have also been found in fossilized remains that were once

submerged in an ancient lacustrine environment (Pesquero et al., 2010).

Microbial communities and bacteria differ between aqueous contexts than that of

dry land. Carter and Tibbot (2006) outline how microbial communities may decompose

tissues in a variety of landscapes. Barrios and Wolff (2011) found 18,832 different

microorganisms in their freshwater submerged S. scrofa domesticus (domestic pig)

carcasses. They deployed samples in a freshwater stream and lake and found that that

these microorganisms could be categorized based on their behaviours as either

shredders, collectors, predators, necrophagous (feeding on corpses),

sarcosaprophagous (feeding on dead or decaying flesh), and/or opportunists (Barrios &

Wolff, 2011). In Anderson and Hobischak’s (2004) marine taphonomy study, S. scrofa

carcasses with direct contact with sediment and sand on the ocean floor exhibited higher

rates of scavenging than those that rested on rocks and carcasses that floated. The

researchers suspect that this is due to the richness of taxa and greater number of

organisms that live in sandy sediment than those in rocky ones (Anderson & Hobischak,

2004).

Many methods also involve identifying terrestrial soil microbial communities.

Community membership can be a useful indicator of colonial succession of bacterium,

which in stable climates can also reflect seasonality specific to environmental conditions

(Damann et al., 2015). To do so, microbes are organized based on their archaeal,

bacterial (16S) and eukaryotic (18S) rRNA genes using standard DNA extraction and

PCR amplification techniques (Weiss et al., 2016, p. 253). The rate of soft tissue

decomposition is heavily impacted by the types of microbial activities that take place.

The communities themselves are influenced by soil texture, temperature, moisture,

vegetation, and by the acidity of the soil. During the earlier stages, bacteria are the most

dominant in their influence, whereas eukaryotes like nematodes and fungi increase the

decomposition rates later in the taphonomic process.

15

2.2.3. Encrustation, Botanic Growth, and Mineral Deposits

Marine organisms, like barnacles, have been seen to encrust the surface of

bone. The growth and/or deposition of external substances on bone surfaces have been

used to estimate post-mortem intervals based on growth rates of these organisms and

the location for which different types of growth can occur (Magni et al., 2015; Skinner et

al., 1988; Sorg et al., 1997). Parsons and Brett (1991) also examined other encrusting

epifauna: coralline algae, foraminifera, coelenterates, serpulid worms, bryozoans,

barnacles, and molluscs. In an example of the use of molluscs in determining

submergence periods, Dennison et al. (2004) found that barnacles’ cyprid larvae could

inhabit a skull within the first year of submersion off the eastern coast of New Zealand. In

their case study, they found that shell growth could be used to give an indication of time

but noted that barnacles can be vulnerable to death from smothering from strong

currents carrying high sediment loads.

There have also been several studies that have tested the application of diatom

analysis, the study of unicellular algae in bone marrow of femurs, as an indicator of

drowning victims (Krstic et al., 2002). Unfortunately, a standard approach to identify the

number of diatoms involves bone destruction, from sawing smaller sections to the

heating and incorporation of nitric acid (Gruspier & Pollanen, 2000, p. 5; Pollanen,

1998). There is no indication that cortical bone from these experiments are retained, as

most of them are likely to be destroyed throughout the marrow extraction process or

repatriated. If given enough time, microbial alterations to the osteons will cause enough

corrosive damage that there will be recognizable loss of bony features and the

dissociation or flaking of bone (Jans, 2014, p).

Botanic Growth. Another area of micro taphonomy is to examine the types,

growth, and alterations caused by botanical remains. The presence of foreign plant

material can indicate post-mortem body movement, and the growth and development of

flora succession has been demonstrated as a novel means of estimating post-mortem

intervals in completely skeletonized remains. Plants are considered a stable indicator

because they are largely sessile, an organism that does not possess the means to move

by themselves (Witzany & Baluska, 2012). The types of sessile substrates that grow on

bony material include green algae, mosses, lichens, and fungi (Cardoso et al., 2010).

16

In a case analysis of skeletonized forensic remains where the individual was

found six years after they had gone missing, bryophytes (mosses) and vascular plants

(shrubs) were examined to see if their developmental cycle could be a strong indicator of

time elapsed. These plants were targeted in this study because they have a strong

association to microhabitats and are extremely diverse (Cardoso et al., 2010; Mishler,

2001). This method requires the moss samples to be undisturbed, and the maximum

PMI in years is based on the number of shoot segments present in a single stem

(Cardoso et al., 2010; During, 1992; Ross et al., 1998). Results showed that the

bryophytes exhibited both typical growth forms, sympodial and monopodial, which could

give an approximate PMI estimate in years elapsed (Cardoso et al., 2010). Although this

case study was found on land, the use of this type of shrubbery still provides useful

information on the type of biological growth that can be used to date remains.

Ice encasement. Bone survivorship and preservation in frigid climates has

mostly focused on structural changes such as different forms of cracking, but ice

encasement presents a new and interested area of research. A histomorphological

analysis using scanning electron microscopes (SEM) of sixty-seven bone fragments

revealed that there was little to no structural damage to bones after being frozen in a

laboratory setting (Tersigni, 2007, p. 16). However, bone tissues that freeze outdoors

when exposed to fluctuating temperatures may experience climate induced alterations

like such as encasement of surface (periosteum) bone (Janjua & Rogers, 2008, p. 21).

Mineral deposits. There have been many studies to examine the mineral

deposits found on skeletal materials as a means of identifying what type of

environmental exposure the recovered material has been subjected to. Earlier studies

attributed mineral deposits within the cells of archaeological bones to natural biological

changes caused by living fossils (Bell et al., 2008). Other studies have since identified

mineral deposits in archaeological remains as iron-rich microspheres and have argued

that they are bacterially induced (Pesquero et al., 2015). Pesquero et al.’s (2015) is also

based on archaeological material, but of a transitionary environment between land and

what used to be lakeshore environment. Microspheres have also been detected in

marine submerged samples and have been found to be made of calcium phosphate

(Bell, 2007; Bell & Elkerton, 2008; Pesquero et al., 2017). Recognizing this type of

mineral deposit can also be useful in distinguishing burial contexts, whether this has

taken place in a terrestrial, marine, intertidal or lacustrine environment.

17

2.2.4. Aquatic Post-mortem Movement

The secondary movement of bodies can hinder the police’s ability to find

evidence of crimes, which is magnified when dealing with aquatic deaths because it can

often be difficult to estimate how the deceased will move in natural bodies of water

(Mateus et al., 2013). Aside from challenges in the interpretation of taphonomic

changes, many remains that are recovered have been found unintentionally by people

engaging in water-based activities that are not involved in a forensic investigation (Boyle

et al. 1997; Haglund & Sorg, 2002; Sorg et al., 1995; Sorg et al., 1997). Compared to the

location of where a body is recovered, knowing if it has moved from the original crime

scene or location of body disposal can help investigators determine the post-mortem

journey of remains (Evans, 2014, p. 155). This knowledge can also help save time and

resources during the search for clandestine graves. For instance, if a human leg bone

was found on an ocean-side beach and it shows changes that are caused only by fresh

water bacteria, investigators can look upstream or in nearby lakes to find associative

remains. It is from using similar taphonomic signifiers that the Office of the Chief Coroner

in British Columbia has been able to find dismembered feet from two different sites that

match to the same individual, and has solved many other similar cases (Carrigg, 2008,

p. 3).

In a case study of two individuals that had drowned and been displaced along the

Portuguese marine coastline where the post-mortem submergence interval (PMSI) is

known, Mateus and colleagues (2013) found that the bodies drifted 2.8 km away from

their point of submergence over 8.6 days for the 8-year old girl, and 0.7 km over 5.6

days for the 17-year old boy. This distance was measured linearly between when they

were reported missing and where they were ultimately recovered. In these two

instances, the distance of displacement was relatively low compared with other studies

of aquatic post-mortem movement.

Microbial succession based on relative abundance of specific bacterial phyla

appears to be a promising new method of identifying the location of the body

decomposition and has the potential to be used as an estimation of post-mortem interval

(PMI) (Carter & Tibbett, 2006; Damann et al., 2015). The current succession of the most

dominant bacteria in a community composition within decaying bones include firmicutes

(PMI of 27 - 284 days since death) to bacteroidetes (292 – 369 days since death) to

18

actinobacteria and acidobacteria (554 – 1692 days since death) (Damann et al., 2015).

More studies must be conducted to validate these promising findings, but their consistent

rate of change despite variances in mass is compelling given their ability to identify

species succession. Richness of phylotypes in recovered bones increases with time,

which is dependent on the soil community and existing bacterial communities in human

bodies (Costello et al., 2009; Demann et al., 2015; Wilson, 2008).

2.3. Pacific Coastal Western Hemlock Zones

Lakes are living systems, they may also undergo change which may affect the

level of generalizability that this study will have on subsequent studies within the same

zone that stretches across British Columbia’s coastal region down past the border into

the United States of America. In an examination of temperate forests within British

Columbia, researchers found that species composition, biogeoclimatic zones, and

ecology can be used to distinguish Western Hemlock Zones from other geological zones

(Gerzon et al., 2011). As a means of outlining the environmental backdrop, the following

sections will discuss Marion Lake’s (also known as Jacob’s Lake) ecology and geological

formation.

Marion Lake. One of the most comprehensive ecological studies conducted of

Marion Lake, University of British Columbia’s Malcolm Knapp Research Forest (UBC

MKRF) was headed by zoologist, Ian E. Efford (1967). His research involved more than

twelve years of meticulous data collection from 1963 to 1975, covering both Marion Lake

and its surrounding areas. The type of data collected includes the examination of

geographic landforms, bathymetric data, catalogue of fish and fauna, and a lengthy

study of phytoplankton productivity. Since then, other users at UBC MKRF have added

to this existing literature and many others have examined similar ecosystems within this

zone (Leach & Moore, 2014). As with many lakes created from the glacial recession

during the Pleistocene, Marion Lake is situated between two deep valleys at

approximately 300 meters above sea level (Armstrong, 1957; in Efford, 1967). Like many

lakes in mountainous coastal regions, there is no marine deposit in or around this lake at

present day. Marion Lake is roughly 800 meters long and 200 meters wide at its longest

and widest points, and the water depth at the deepest point fluctuates between 5.5 and 6

meters, with a mean depth of 2.4 meters.

19

The Lower Mainland and Sea-to-sky Corridor is comprised predominately of

granite, intermixed with granodiorite, tonalite, and diorite (Cannings et al., 2011). This

geological feature extends all the way to Alaska and was created from the Pacific Ocean

Floor being pushed up and westwards from the tectonic uplift caused by the Juan de

Fuca plate subducting beneath the North American Plate. This mineral composition has

led to most alpine lakes along the western North American coast having granite floors

(Cannings et al., 2011). Marion Lake is largely comprised of igneous and granite rocks

with low concentrations of nutrients like most lakes along the coastal mountains. It is

representative of other coastal mountains of British Columbia, particularly those that are

within the Western Hemlock Zone (WHZ) (Orloci, 1964, in Efford, 1967).

Western Hemlock Zones. The name for the Western Hemlock Zone is based on

where certain species of trees grow optimally. Western hemlock (Tsuga heterophylla

(Raf.) Sarg.) is the most abundant along the western coast, followed by Western

Redcedar, Amabilis Fir, and Douglas-fir trees (Gerzon et al., 2011). In an examination of

temperate forests within British Columbia, researchers found that species composition,

biogeoclimatic zones, and ecology can be used to distinguish Western Hemlock Zones

from other geological zones (Gerzon et al., 2011). The WHZ has a “mean annual

precipitation of 3120 mm, total mean annual snowfall [of] 450 mm, and mean annual

temperature is 9.1 oC” (Gerzon et al., 2011, p. 1535), and its forest floor soil composition

is mostly comprised of Humo-Ferric or Ferro-Humic Podzols. Another term commonly

used to describe the region along the North American Pacific Ocean shoreline (0 – 200

meters above sea level) is the Coastal Western Hemlock Zone (CWHZ) (Gerzon et al.,

2011; Gord, 2010). It appears that this distinction between WHZ and CWHZ in

nomenclature is reflective of the disciplines that study these areas, rather than geological

or ecological in nature.

Temperature and Climate. In a study of winter stream temperature at UBC

Malcolm Knapp Research Forest from 2011 to 2013 (UBC MKRF), Leach and Moore

(2014) found that increased winter air temperatures are causing higher winter stream

temperatures that impact the developmental cycle of fish and invertebrate growth. The

implication of their results points to the issue of global warming, and how the higher

winter temperatures will impact a variety of biological, chemical, and physical processes

in streams that will make them different than in years passed. This is of forensic

importance, because the warmer the waters, the more invertebrate and microbial

20

productivity will take place (Arismendi et al., 2013; Brown et al., 2011; Efford, 1967;

Leach & Moore, 2014).

Changing temperatures may also result in changes in the types and number of

organisms that make up the community in water because some may survive better or

worse, which can ultimately disrupt the existing food chain. Greater productivity may

then result in faster and higher rates of bioerosional diagenesis in recovered material,

thus posing a risk for remains appearing older or more decomposed than they are. Other

aquatic microorganisms of higher orders feed on phytoplankton (Efford, 1967, p. 2292;

Pal & Choudhury, 2014, p. 1). In a study of phytoplankton in Marion Lake, their rate of

growth was found to be closely tied to the ambient temperature of the water, and it

appears that their primary productivity occurs between June and October (Efford, 1967).

This will impact the population of the more complex microorganisms that remodel bone,

since there will be dramatically lower nutrients in the lake during winter and spring.

21

Chapter 3. Research Design

3.1. Research Objectives

Purpose of the study. The goal of this research was to determine the effects of

exposure to lacustrine environments on skeletal material. This study examines the

macroscopic surface and microstructural changes in cortical bone tissue of sectioned,

subadult Ovis aries (domestic sheep) femur diaphysis that have been submerged at ten

different sites across Marion Lake (also known as Jacob’s Lake) at the University of

British Columbia’s Malcolm Knapp Research Forest. Control samples were bone discs

taken from each O. aries diaphyses (one per experimental site and cage). Controls were

stored in a freezer at Simon Fraser University’s Centre for Forensic Research to be used

to compare with experimental bone discs from the same diaphysis. Aside from a time-

series comparison of samples at a monthly interval for a sixteen-month retrieval period

(longitudinal observational study design), environmental conditions were monitored to

see if the location of submergence within a single lake system would impact taphonomic

change. Lastly, the impact of being exposed to winter conditions and lake freeze were

also evaluated.

Hypothesis. Based on the existing forensic anthropology literature, it was

hypothesized that skeletal tissue would undergo decompositional changes that are

typically related to hydrodynamic conditions. Freshwater submergence in an active lake

system was suspected of altering bone materials differently than that of marine and

terrestrial environments. The length of the submergence was also suspected to have an

impact on the rate, frequency, and extent of bone remodelling, with lacustrine bacteria,

fungus, and microbial communities being the primary sources of bioerosion. Marion Lake

is not stagnant, so the water energy was expected to cause an uplift of sediment that

may cause abrasion. Aside from structural changes to cortical bone, chemical-physical

mechanisms may alter bone density and structural integrity, discolouring of bone due to

soil staining, and biological growth on the bone is expected to occur. The null hypothesis

would be that no change is observed, and that the environmental context, submergence

periods, and seasonality have no effect on taphonomic change.

22

Possible Applications & Significance. The goal of this research is to aid in

death investigations by studying the effects of change in submerged skeletonized

remains. In an study of coroner cases in British Columbia from 1995 to 1996, Hobischak

and Anderson (1999) found that 68% of aquatic deaths took place in freshwater. The

Life Saving Society’s (2016) British Columbia drowning report found that 34% of

drowning fatalities have occurred in lakes and 30% in rivers from 2009 to 2013. By

contributing to the understanding of what decompositional effects may take place in

lacustrine submerged bones, the results of this study may help identify whether

recovered bodies have spent any time in freshwater lake prior to their recovery. Should a

body be recovered in an intertidal or marine location, knowing its point of origin can be

very useful for understanding the body’s post-mortem journey. The rate of change

observed may also help suggest the amount of time elapsed in submerged bones, and

perhaps point to whether the bones have been exposed to the winter elements.

Many social justice advocacy groups, such as the Missing Aboriginal Women in

Canada movement, have highlighted the importance of being able to link missing person

cases with found remains. This ability would provide much needed closure for families,

and victim identification is paramount to the justice system’s ability to prosecute

offenders, exonerate the innocent, repatriate remains, and pursue various areas of

litigation. If the rate of change is shown to be a stable indicator of post-mortem

submergence periods between death and discovery, there is potential application for this

information to aid in identifying missing individuals that have gone missing within the

same period as the submergence interval.

3.2. Research Questions

The primary research question that this project aims to address is i) whether

there is discernable taphonomic remodelling of cortical bone tissue when submerged in

lacustrine environments. Secondary research questions include: ii) whether the types of

remodelling observed is different or similar to lacustrine submerged samples within or

outside of the Pacific Coastal Western Hemlock Zone; iii) whether the types of

remodelling observed is different or similar to marine submerged and terrestrially

exposed samples; iv) whether the remodelling observed is consistent amongst several

submerged samples at different locations within the same lake (i.e. whether cage depth,

water pH, water current, microbial communities, vegetation, etc., have a significant

23

impact); and v) whether the amount or presence of change can be attributed to the

amount of time elapsed or seasonality.

24

Chapter 4. Material and Methodology

Subadult Ovis aries (domestic sheep) femora shafts were used as human proxies

for this study on the surface decompositional effects of submersion on bone tissue.

Mammalian skeletal material is similar in terms of its mineral and chemical composition,

making animal remains an appropriate sample. The microstructural arrangement

between humans and other mammals does differ, but the focus of this study was on the

destructive change at a macroscopic level so this is discrepancy is not of concern. This

chapter will outline the (4.1) overall research design, (4.2) materials and protocols used,

(4.3) data analysis tools and instrumentation, (4.4) variable operationalization, and (4.5)

disclosures regarding ethics exemptions and the animal care and control protocols.

4.1. Logistics

This experimental research involved deploying ten cages with sectioned Ovis

aries (domestic sheep) bones in a freshwater lake, retrieving them at monthly intervals

for sixteen months, and further analysis of macroscopic surface changes in a controlled

laboratory setting. Following a time-series model, the taphonomic changes in skeletal

material were compared both temporally between samples retrieved from the same

cage, as well as against other samples retrieved during the same recovery. Taphonomic

changes were documented and presented in a descriptive manner, then quantified

through the development of a classification codex and measurements were made using

radial graphs, macroscopes, and statistical software. Like many taphonomic experiments

that consist of both macroscopic and microscopic analyses, this type of analysis involves

assessing the absence and presence of skeletal changes, degree of expression in such

changes, and overall morphological structure of such features - also referred to as

morphoscopic traits (Christensen et al., 2014; Ousley & Hefner, 2005).

A total of 130 samples were used for this research, ten of which are control

samples from different femurs and 120 experimental samples (twelve samples for each

of the ten cages), whereby each cage was deployed and submerged at different

locations across Marion Lake. Samples from the same diaphyses were placed in the

25

same cage. Twelve additional specimens were submerged in various cages and not

used for the statistical analysis because they were dedicated samples used to test

various methodological approaches, such as the destructive process of calibrating thin-

sectioning machinery for histological analyses. These twelve samples were submerged

for the full duration of the experiment (16 months).

This research was conducted at the University of British Columbia’s Malcolm

Knapp Research Forest’s (UBC MKRF) Marion Lake, British Columbia, Canada.

Permission to use Marion Lake for taphonomic research was granted by Mr. Ionut Aron,

the research director at UBC MKRF. Marion Lake was chosen because it is a secure site

with locked boat access and serves as an appropriate proxy for freshwater lakes found

within the Pacific Coastal Western Hemlock Zone. All roads leading to UBCMKRF are

gated with restricted access, which makes the area ideal because it is improbable that

there will be human induced tampering, and both aquatic and terrestrial wildlife are

undisturbed, similar to most lakes beyond the city centers of British Columbia. There are

no industrial, agricultural, or structural developments near the lake or its headwaters.

The decision to conduct a two-year study was made because of the availability of

the site for this research project, and monthly retrieval was decided in part due to the site

accessibility and the availability. The planning phase included the completion of animal

protocol forms, ethics application and ethics exemption letter, research approval from

UBC and SFU, establishing relationship with specimen distributors, laboratory training,

equipment training, safety and health training and certification, and securing the

exclusive use of Marion Lake. The preparation phase included cage preparation,

securing bone specimens to cages, creation of buoys, creation and securement of cage

identifiers, and the transportation of materials to Marion Lake. The planning and

preparation phase were pursued concurrently and took eight months, the experimental

phase took a total of sixteen months (Figure 4.1), and data analyses were performed

intermittently throughout the span of twenty-six months. During the period of December

2016 to March 2017, the lake was completely frozen, and the field team was unable to

successfully reach and recover any remains (Figure 4.2). By analyzing changes on a

monthly interval, this study aims to help distinguish which months exemplify higher rates

of microbial activity for the purpose of offering direction for future studies.

26

Figure 4.1. Chart illustrating the calendar date of deployment and recoveries, as well as the number of days elapsed since the initial deployment and recovery of specimens.

Figure 4.2. Photograph of the frozen lake (right and 950 m uphill hike through the snow with field equipment (left) during the March 2017 recovery.

0

0

34

66

94

127

155

189

219

250

405

432

460

491

0 100 200 300 400 500 600

Control Specimens (no exposure)

Deployment: 03-Mar-16

Recovery 1: 2016-04-07

Recovery 2: 2016-05-05

Recovery 3: 2016-06-04

Recovery 4: 2016-07-07

Recovery 5: 2016-08-04

Recovery 6: 2016-09-07

Recovery 7: 2016-10-07

Recovery 8: 2016-11-07

Lake Frozen/Recovery Delayed

Recovery 9: 2017-04-11

Recovery 10: 2017-05-08

Recovery 11: 2017-06-05

Recovery 12: 2017-07-05

DAYS ELAPSED

REC

OV

ERY

PER

IOD

S

27

4.2. Materials

4.2.1. Sample Selection

Two local distributers were used to acquire the ten sub-adult (immature) Ovis

aries femora shafts. These defleshed bones were purchased from butchers and were

sectioned into several bone discs using a stationary mechanical bone saw by butchers

on staff. All animal bones were frozen upon slaughter at the farm, delivery, and storage

at the store. These bones were butchered onsite upon purchase, so all materials were

still frozen when sectioned by the mechanical blade. The butchers removed the femora’s

medial and distal ends, then cut the shaft into a minimum of thirteen (13) 3.10 – 6.50 mm

thickness each (Figure 4.3). There was variance in thickness because the author could

not measure each bone between cuts, and there was no funding available to repurchase

these shafts. All bone discs from a single shaft were then bagged together and kept

separate from other shafts. These bones were then placed in a cooler full of ice and

immediately transported and secured in a locked freezer (-20 oC) in Dr. Bell’s Forensic

Anthropology Laboratory in the Centre for Forensic Research.

Figure 4.3. Photograph of Ovis aries femur discs immediately after the sectioning and maceration process at a local butchery.

28

4.2.2. Preparation Methods

Every shaft was assigned to a single cage. Twelve bone discs were then tethered

individually to their respective cage, so they could be removed individually during the

monthly recoveries. For every bone disc, four pieces of 30 cm extra-strength fishing wire

were pushed through the bone marrow (the centre for the shaft that houses organic

tissues) and tethered to the cage. Every wire was then secured using two double figure-

eight knots and both ends were closed off using an E-Star Stopper knot. The wire ends

were then glue-gunned together. The ten cages were purchased from a local hardware

store, of identical shape and size, and made from vinyl coated steel wire. Their

dimensions were 20.32 cm x 15.24 cm x 10.16 cm (8 x 6 x 4 inches), each consisting of

2.54 cm (1 inch) grid holes that slightly varied from the top to the bottom of the cage

(Figure 4.4). While the wires were being tethered, the cages and bones were periodically

returned to the freezer to ensure that the bones remained frozen and that there were no

changes due to thawing. A bone from each shaft (representing a single cage) were

retained in the lab and used as control specimens. Epiphyses and spongy bone discs

were retained but not used for this experiment.

Figure 4.4. Illustration (left) and photograph (right) depicting how the Ovis aries bone discs were tethered to cages, cage marking, and appearance after one month of submergence (cage and samples fully intact).

29

Plastic four litre milk containers were collected, washed, and their lids were

sealed using a glue gun to be utilized as buoys. A permanent ink pen was used to mark

each milk jug, and two to three buoys were assigned to each cage. These buoys were

tethered to the cages by threading twisted polypropylene (corded) yellow and red rope

through the handles, tying with figure eight knots, which were closed off using an E-Star

Stopper knot. The cages had a removable clasp that was locked, and four zip ties were

used to secure the door of the cages to ensure that they would remain closed throughout

the duration of this research project. No large scavengers were able to access the

cages, no knots were unravelled, and the doors remained closed throughout the

experiment. A plastic cut-out of a letter (A to J) and a toy vegetable was placed into each

cage to ensure that each cage would be labelled and differentiated. Numbers were also

carved into the plastic buoys.

To prepare for the deployment process, a survey of Marion Lake was conducted

both during the Fall and Spring months prior. Although a lush forest surrounded the lake,

the trees are relatively short, erect and did not obstruct direct sunlight on the lake (Figure

4.6, 4.7). Other preparation tasks included preparing and repairing the row boat, clearing

the path to the dock, creating a long shaft with a hook to collect cages, and securing

cameras and GoPro camera latches on the boat and equipment.

4.2.3. Deployment Protocol

All the bones were tethered to cages, placed into large plastic bags, and stored in

a freezer until the day of the deployment. On March 3rd, 2016, all cages and bones were

transported in a large cooler box with packaged ice. Ten locations around the lake were

chosen as experimental sites to capture the potential variations between microorganism

communities that inhabit different areas and depths within individual lake systems. Each

site had a single cage with several sections of the same bone shaft enclosed. Bones

from the same shaft were not distributed across different cages as to enable comparison

of the same bone tissue structure throughout time. One cage was deployed near the

dock, two cages were deployed north of the dock in the deepest areas of the lake, and

seven cages were dispersed along a horizontal transect along the southern half of the

lake. The cages were weighted and the gridholes were large enough for discs to pass,

so samples were suspended above the lake floor but the amount is uncertain, as a video

feed and echo sounder of the bones was not possible.

30

4.2.4. Recovery Protocol and Sample Preparation for Analysis

A small field team of three to five members assisted with each recovery and

redeployment. Once at the site, a rowboat would be carried to the dock, as one member

would take the surface temperature of the water as well as the temperature below the

dock at two meters depth. Once all the recovery equipment was loaded into the boat,

two to three people would row to each cage site (as marked with two to three buoys),

pull the cage onto the surface of the water, and a bone disc would be freed from the

cage. Lam retrieved every sample and was on the boat for every recovery. Bone discs

would be placed in separate marked plastic containers, which would sit in a cooler bag

with a bag of ice inside. This method helped ensure sample integrity by limiting the

chance of samples cross-contaminating one another.

Once all the bones were retrieved, the entire cooling bag was placed in a cooler

box and transported immediately back into the CFR secured laboratory’s freezer. The

Ovis aries bone discs would then be lightly rinsed under tap water and placed under a

fume hood vent to dry. After a week of drying, each sample would then be photographed

under a Zeiss Stemi Macroscope both before and after an orientation artefact was made

using a scalpel. This line was used to orient the bone to 90o and to determine which

bone surface was considered the cross-sectional transverse block face 1 (surface with

orientation artefact), cross-sectional transverse block face 2 (surface without orientation

artefact), and the right or left side of the periosteal surface (Figure 4.5). The bones were

then stored at room temperature in plastic boxes in the secured CFR lab. Small pin-

holes were drilled into the box prior to bones being stored, using a portable Dremel hand

drill. These holes allowed moisture to escape to avoid mold and mildew from growing.

Figure 4.5. Photograph of Ovis aries control sample, and the cross-sectional transverse block face face 1, block face 2 and the periosteal surface.

31

4.2.5. Collection of Water and Silt Samples

Water and silt samples were collected during the months of April and May 2017

using new and sterile plastic sample containers to determine water acidity and soil

composition. These months were chosen because of the high amount of water visibility,

as needed for silt sampling and for reasons pertaining to water safety. Water samples

were taken from the surface of the water. Lam and a field volunteer scuba dived to

retrieve silt samples from the bottom of the lake, which caused some silt disturbance

(Figure 4.6). To account for this uplift of lighter sediments, the samples were taken by

dipping the containment capsules 10 +/- 2 cm deep into the soil. The location of water

and silt samples sites is illustrated in Figure 4.7. Three samples were collected: a) one

from the northern area of the lake where the river meets the lake, b) one from the

shallow, western marshland/swamp-like region with freshwater molluscs, and c) another

sample from the central, southern region of the lake where the current is strong, and the

lake bottom is relatively deep.

Figure 4.6. Lam (left) and Suliman (right) diving for silt samples from the bottom of the lake.

32

Figure 4.7. Bathymetric map of the locations from which water and silt samples were collected (adapted from UBC MKRF and Efford, 1967).

33

4.3. Data Analysis

4.3.1. Measurements and Research Instruments

FisherScientific Vernier sliding calipers were used to measure the size of the

Ovis aries bone discs. The height, width, and thickness of the bone discs were taken

from the longest and widest section of the cross-sectional transverse block face. To

measure the depth of the disc, height was also taken from the periosteal surface. These

measurements were all taken using the same sliding caliper, and two personnel

measured all the bones twice to evaluate inter-observer error. To quantify taphonomic

changes to bone samples, a radial graph on a projector sheet was placed below the

sterile petri dish that held the bone discs. Using the orientation artefact on the bones, the

marker was set to 90o so all discs would be viewed the same way. The graph was

broken into twelve quadrants (Figure 4.8). With each quadrant, the types of taphonomic

change would be identified, described, and quantified. Refer to section 4.3.8. for a

complete codex of how variables were operationalized.

Figure 4.8. Illustration of how a radial graph was used to map and document taphonomic change.

34

4.3.2. Macroscopic Analysis using Light Microscopy

A Zeiss Stemi Macroscope was used in combination with Lumenera

Corporation’s Infinity Capture Application Version 5.0.0 to document taphonomic

changes to skeletal material at a low magnification (x3 – x5). Using a radial graph,

changes were documented and recorded onto a paper catalogue, which was later

transcribed into a statistical database using IBM SPSS Statistics Version 24.

Photographs of all specimens were taken using this aforementioned macroscope, both

before and after orientation lines (section 4.2.4) were installed. A complete list of what

changes were documented and how variables were operationalized is listed in section

4.4.

4.3.3. Microscopic Examination of Thin-Sectioned Skeletal Samples

An AxioScope.A1 Modular Microscope was used in combination with a Leica

SP1600 Saw Microtome Diamond blade for the microscopic analysis of skeletal discs.

Because of the size of the bones, none of the existing mounts and adapters could

securely house the sample during the thin-sectioning process. For this reason, samples

were mounted onto resin blocks to securely grip the sample in place for the sectioning

process. The goal of this process was to examine (1) the depth to which taphonomic

change can be seen in a disc based on how deep into the bone structural changes can

still be observable, (2) whether pitting in samples are naturally occurring or caused by

external agents, and (3) whether abrasion to the periosteal surface is simply exposing

existing vascular channels or creating cracks on the transverse cross-sectional plane.

This process was only performed on one experimental bone to help inform decisions

regarding future studies. Because this is a highly destructive process, the sectioning of

bones took place after the other analyses were completed.

The first step was to create clear resin blocks using a Struers SpeciFix-20 Kit, a

room temperature curing epoxy system. This was achieved by combining SpeciFix Resin

(UN-no: 3082 and SpeciFix-20 Curing Agent (UN-no: 2735) at a ratio of 1:8 by weight (g)

(as opposed to volume). The solution was poured into Buehler Disposable cold mounting

cups (1" (25mm)) that had been lubricated with Wynn's Slick 'n Shine Multi-use silicone

lubricant. After a week of drying at room temperature inside a hood vent, the resin blocks

were levelled. The Leica SP1600 Saw Microtome Diamond Blade was used to level the

35

resin blocks. A preliminary experiment involving four batches of 20 resin blocks (n = 5 /

series) involving different mixing methods, amount of time mixing, and the use of

different lubricants was completed to determine the most optimal protocol.

The experimental bone (submerged for the full duration of the 16-month study)

disc was then secured onto the sectioned resin block using Gorilla® Super Glue Gel.

Once the sample was fully adhered to the resin block, it was thin-sectioned and mounted

onto glass slides for further analysis. The speed of the blade upon contact was

maintained at speed 4 until the section was complete. To retain the surface of the disc,

the section typically made to calibrate the sample for thickness was made as thin as

possible and kept for future analyses. The subsequent sections were cut to a variety of

thicknesses to determine the most optimal settings for future thin-sectioning work. The

same Mitutoyo Coolant Proof Micrometer (0 - 25 mm, 0.001 mm) was used to determine

the thin-sectioned bone’s thickness, by measuring the difference between the slide and

cover with and without the sample mounted. Slide images were taken with a Zeiss

Axiocam (105 color) and processed using Zen 2 lite software. Data were saved as both

Carl Zeiss Image (.czi) and Tagged Image Files (.tiff).

Regarding the results of the resin block experiment (n = 20), the best results

were achieved when mixing 56.0 g of resin with 7.5 g of curing agent for six 1” capsules.

Buehler Disposable cold mounting cups (capsules) were used because they have two-

digit numbers hard-pressed to their base, which allows the molds to be identified from

one another. The resin was slowly mixed until the two components could not be

distinguished from one another, which takes approximately three minutes depending on

the amount of solution being produced. To avoid air bubbles, it is important to avoid

rapid mixing, and pouring from too high a distance from the plastic molds. After drying in

a hood vent for one full week without disturbance, the plastic mold was then broken from

the resin block. Wynn's Slick 'n Shine Multi-use silicone lubricant was also the preferred

choice and allowed the plastic molds to break away from the resin blocks easier than

other brands. Excessive lubricant will cause deformities and the resin block base to be

slightly concave rather than completely flat.

36

4.3.4. Structured Qualitative Analysis of Skeletal Change

Structured qualitative analyses were used to observe, document, and classify

characteristics of taphonomic change. This primarily involved the use of researcher

observation of features that are descriptive in nature, such as the colour of bones and

the colour of stains found on bones using Munsell Soil Color Charts (1998 Revised

Washable Edition – ARC 1324, OPI-309-063). Although these charts are made to be

used for soil colour documentation, these eleven charts (n = 399 unique colours) offer a

convenient notation system that classifies bones and stains based on hue (red, yellow,

green, blue, and purple), value (brightness), and chroma (proximity to a neutral colour of

the same value). Because of studies that have pointed to concerns over subjectivity in

the way humans perceive colour spectrums, the author took a colour test at a local

optometrist to ensure that there are no issues of colour blindness that could hinder the

use of this method. Details as to how these values were quantified are explained in

section 4.4.3. Other observable taphonomic changes will be discussed in the results

section, as appropriate.

4.3.5. Silt Sample Preparation

A DualBeam 235 scanning electron microscope (SEM) with a Stage Type 50x50

T SMCB Machine (Model DB235 SEM/FIB) was used for microscopic analysis. This

SEM is equipped with a Ga focused Ion Beam (FIB). The software used for imaging was

FEIxP Version 3.80. This procedure was performed at the Electron Imaging and

Holography Facility at Simon Fraser University. To prepare for the FIB-SEM process, the

silt samples were partially gold coated using standard Au sputtering techniques. Once all

the silt samples were collected, each capsule of silt was cleaned by pouring distilled

water over the sample atop several sieves. The soil sample was then placed into a small

aluminum tray and dried in an Isotemp Oven at 40 degrees Celsius for 12 hours. The

dried silt was then transferred onto a carbon tape topped aluminum pin (14 mm

diameter). A small sheet of slide glass was used to cover half the pin sample for

standardized Au (gold) sputtering (Figure 4.9).

The images of features were taken on Ultra High Resolution (UHR) mode unless

specified; there were only a few instances when the Search (SRH) mode was used to

take images at a lower magnification. A high vacuum mode was required, so the detector

37

used was through the Lens Detector – Secondary Electron (TLD-S) at 20kV, which

allowed for a structural and morphological analysis at a magnification of 6,500x the

sample size. Images were taken from the Au sputtered side as well as the untreated side

of the sample for comparison to maintain data integrity. No analyses were performed

using these images.

Figure 4.9. Photograph of the both the Au sputtered and untreated silt samples (deep water, head water, and swamp water) on carbon tape and aluminum pins.

4.3.6. Elemental Profiling of Silt Samples

Elemental profiling of silt samples was completed using Energy Dispersive

Spectroscopy (EDS). When features were examined, several elemental profiles were

taken both of specific inclusions, as well as of the entire sample frame. The spectrum

was collected over a 50 second period, and PeakID was used to identify potential

elements. To confirm the presence of these elements, the K-, M-, and L- lines for each

candidate was examined. Improbable items were then removed, and the total amount

was quantified using EDAX Genesis - Genesis Imaging/Mapping software Version 3.61.

The readings of these elements were only to suggest presence of such minerals and

elements. The quantification tool was only to provide an estimation, as there may be

great variation within a single sample. To try to account for this, several measurements

were taken from each silt sample (both from the Au sputtered and untreated side), and a

comparison between elemental presence of these samples with existing literature was

made. The use of aluminum pins and carbon tape also will suggest higher carbon and

aluminum readings than there truly are in the sample.

38

4.3.7. Temperature and Precipitation Data

All information regarding atmospheric temperature and rainfall at Malcolm Knapp

were collected from Environment Canada’s Past Weather and Climate - Historical Data

Centre. These measurements are based on the values collected by the on-site weather

station at Malcolm Knapp, named the Haney UBC RF Admin station. The climate ID

taken from this weather station is 1103332. These data were collected in CSV format,

and then imported into an SPSS database that was created to track the experimental

parameters of this research. The surface temperature of the lake and water temperature

two meters below the dock was also added into the database, and measured using two

small, handheld thermometers. Due to limited resources and technical problems in the

field, lake temperature data are not available for the month of deployment (March 2017)

and the first recovery (April 2017).

4.3.8. Water pH Data

A VWR SB80PI SympHony pH/ISE Meter was used to measure water pH levels.

Fifteen water samples of 20 mL each were collected from five different sites (three

samples at each of the five sites) at Marion Lake on April 12th, 2017 (Figure 5.11).

These samples were collected in sterilized vials, which were then transferred and kept

frozen at the Centre for Forensic Research. The decision to take water samples during

the one month as opposed to every month was based on resource availability. On May

25th, 2017, these samples were defrosted at room temperature, while the pH Meter was

calibrated. At room temperature, the pH level of the storage solution, distilled water, and

five samples were then taken. The probe was cleaned before and after each

measurement using a KIMTECH precision wipe.

4.3.9. Cage Depth and Movement Data

Cage depth could not be measured with a high enough accuracy to be reported

in this study but can be inferred by Figure 4.10. Cage movement was documented

during the monthly retrievals. Although a handheld GPS was used in the field, the

coordinates it offered are considered unreliable because there was substantial change

while standing still on the dock, even where there was no foliage cover to cause an

interference. For this reason, the location of cages was documented on the map by

39

approximation as well as with a handheld GPS. After the first two months, there was little

change in where the buoys and cages were placed. During winter when the lake froze

over, some movement was noted but the cages remained within approximately 15

meters of where the cages were found from the third month onward (Figure 4.10). Note

that a parallel study using whole Sus scrofa domesticus (domestic pig) shafts were

deployed during this study for another experiment.

40

Figure 4.10. Bathymetric map of cage deployment locations (indicated by capital letters), cage movement for the duration of the experiment (shaded regions), and the lake inflow and outflow (note that the Northeast inflow makes a minor contribution) (adapted from UBC MKRF and Efford, 1967).

41

4.4. Variable Operationalization

4.4.1. Datasets

This section will describe how the variables within each dataset were

operationalized. The first database documents the environmental conditions during each

recovery, where each recovery and deployment was treated as an individual case (Table

1). The second database documents macroscopic taphonomic changes to Ovis aries

skeletal material (Table 2).

Table 4.1. Operationalization of environmental condition variables.

Variable Name Type of Measurement Operationalized Values

Month Categorical 0 = January 1 = February 2 = March 3 = April 4 = May 5 = June 6 = July

7 = August

8 = September

9 = October

10 = November

11 = December

Year Categorical 0 = 2016

1 = 2017

Atmospheric Temperature Continuous Numeric, Celsius

Lake Surface Temperature Continuous Numeric, Celsius

Lake Temperature (2m below lake surface)

Continuous Numeric, Celsius

Precipitation Continuous Numeric, millimeters

42

Table 4.2. Operationalization of Ovis aries sample variables.

Variable Name (LABEL) Type of Measurement Operationalized Values

Catalogue ID (CID) Continuous Numeric

Field Catalogue ID (FID) Nominal - String Cage_RecoveryNumber (Ex. A01)

Cage Location (LOC) Categorical 0 = Location A

1 = Location B

2 = Location C

3 = Location D

4 = Location E

5 = Location F

6 = Location G

7 = Location H

8 = Location I

9 = Location J

Deployment Date

(DEPLOY)

Categorical 0 = March 3rd, 2016

999 = Not Applicable

Recovery Date

(RECOVERY)

Categorical 0 = April 7th, 2016

1 = May 5th, 2016

2 = June 4th, 2016

3 = July 7th, 2016

4 = August 4th, 2016

5 = September 7th, 2016

6 = October 7th, 2016

7 = November 7th, 2016

8 = April 11th, 2017

9 = May 8th, 2017

10 = June 5th, 2017

11 = July 5th, 2017

999 = Not Applicable

43

Variable Name (LABEL) Type of Measurement Operationalized Values

Days Elapsed (DAY) Continuous Numeric, Number of Days

Sample Assignment (EXP) Categorical 0 = Control Bone

1 = Experimental Bone

Cross-Sectional

Transverse Block Face

Height (XHEIGHT)

Continuous Numeric, In Millimetres

Cross-Sectional Transverse Block Face Width (XWIDTH)

Continuous Numeric, In Millimetres

Cross-Sectional Transverse Block Face

Thickness (XTHICK)

Continuous Numeric, In Millimetres

Periosteal Face Height (PHEIGHT)

Continuous Numeric, In Millimetres

Weight (WEIGHT) Continuous Numeric, In Grams

Cross-Sectional Transverse Block Face Artefact - Saw Marks (XSAW)

Binary 0 = Absent

1 = Present

Cross-Sectional Transverse Block Face Artefact – Lipping (XLIP)

Binary 0 = Absent 1 = Present

Cross-Sectional Transverse Block Face Artefact – Orientation Line (XOL)

Binary 0 = Absent 1 = Present

Periosteal Face - Signs of Abrasion (PABRA)

Binary 0 = Absent 1 = Present

44

Variable Name (LABEL) Type of Measurement Operationalized Values

Cross-Sectional Transverse Block Face Signs of Cracking (XCRACK)

Binary 0 = Absent

1 = Present

Periosteal Face Signs of Cracking (PCRACK)

Binary 0 = Absent

1 = Present

Pitting – Per Quadrant* Continuous Numeric

Gnawing (GNAW) Binary 0 = Absent

1 = Present

Black Surface Deposits (DEPOSIT)

Binary 0 = Absent

1 = Present

Bone Colour (COL) Categorical 0 = Completely White

1 = White & Beige

2 = Completely Beige

3 = Beige & Brown

4 = Completely Brown

Stain Presence (STAIN) Binary 0 = Absent

1 = Present

Stain Colour – Blue

(BLUE)

Binary 0 = Absent

1 = Present

Stain Colour – Green

(GREEN)

Binary 0 = Absent

1 = Present

Colour Coding (HEX) Descriptive See section 4.4.3

Colour Coding (MUN) Descriptive See section 4.4.3.

Growth/Inclusions (BIO) Descriptive See section 4.4.3.

* Measured per quadrant (Q1 to Q8) for both cross-sectional faces (F1 & F2); label PITF#Q#.

45

4.4.2. Artefacts

The term artefacts has been used to describe human-made changes to bones.

The process of sectioning shafts with a bone saw can produce linear lines along the

cross-sectional faces of the bone, as well as cause bony lipping at the edges of the bone

discs (Figure 4.11). This is not to be confused with osteophytes that resemble small

spherical bone growths on the outer perimeter of bones. The orientation line mentioned

in section 4.2.4 is considered an artefact because it was created by the author to help

map changes by degrees of distance in a radial graph (Figure 4.8). This was done post-

recovery. The bone saw marks and bone lipping observed in all of the samples prior to

deployment and before being secured for storage (in the case of controls) is attributed to

the butchering process of sectioning bone shafts into medallions (bone discs). Bone saw

marks are visible to the naked eye, but a magnified image has been provided for clarity.

Changes to these artefacts were noted for the control and experimental bone.

Figure 4.11. Image of three different types of artefacts examined on the transverse cross-sectional plane of a control bone: bone lipping, orientation lines, and saw marks (codex).

46

4.4.3. Post-mortem Decompositional Changes

Aside from environmental conditions and bone artefacts, post-mortem

decompositional changes were documented for both the periosteal surface and

transverse block faces of all control and experimentally submerged samples (Figure

4.12). Signs of abrasion of the periosteal surface were documented (Figure 4.13), and

cracking of both surfaces were also examined. No distinction was made between

transverse cracks and osteonal cracks was made for this study. Pitting on the transverse

face was quantified by quadrant, as previously mentioned in section 4.3.1 (Figure 4.8).

The black deposits and pits were compared to control samples in Figure 4.14. Signs of

gnawing was looked for, but there were none to be seen.

The colour of the bones changed from a porcelain white to dark brown (Figure

4.15), and some samples exhibited staining, particularly on the periosteal surface. The

process of bones drying at ambient temperature (21oC/ 70oF) made the colours appear

less vibrant than when they were first recovered. After a month of drying, the bone colour

was measured as either completely white, white-beige, beige, beige-brown or completely

brown. The presence of blue and green staining was identified (Figure 4.16). During

secondary analysis, the hexadecimal codes of the most prominent blue and green

colours were collected from photographs, along with visual confirmation and

documentation using a Munsell color chart. In instances where there were several

prominent stains, the pigments with the highest contrast were noted. Most colours

appeared in a gradient, so colour groups were used to describe the bone colour and

stain colour overall in the results.

Figure 4.12. Illustration depicting what the periosteal surface, endosteal surface, and cross-sectional transverse block face of a bone disc.

47

Figure 4.13. Image of periosteal abrasion and cracking of experimental bones, as compared to the periosteal surface of control specimen under a light microscope at x5 magnification: (A) periosteal surface (control bone), (B) cross-sectional surface (control bone), (C) periosteal cracking, (D) periosteal cracking, (E) periosteal abrasion, (F) transverse cracking (codex).

48

Figure 4.14. Image depicting pitting and black deposits (surface inclusions) identified on the cross-sectional transverse block face surface of experimental bones, using a light microscope at x5 magnification: (A) control bone, (B) black deposits, (C) pitting (codex).

49

Figure 4.15. Image showing different bone colours on the cross-sectional transverse block face, using a light microscope at x5 magnification: (A) white (control bone), (B) white-beige, (C) beige, (D) beige-brown, (E) brown (codex).

50

Figure 4.16. Image of blue and green staining, using a light microscope at x5 magnification: (A) blue staining on the transverse cross-sectional block face, (B) green staining on the transverse cross-sectional block face, (C) blue staining on the periosteal surface, and (D) green staining on the periosteal surface (codex).

4.4.4. Statistical Analysis

For the quantitative analysis component of this research, several statistical

methods and results were utilized and reported. Firstly, descriptive statistics of group

findings were reported for each variable mentioned in the classification system. Using

boxplots and other graphics, change through time was assessed for each cage and their

respective samples. Bivariate analyses (chi-square, t-test, and correlations) were then

used to assess any statistically significant relationships. Software licencing of IBM SPSS

Statistics and other analytic software was granted by SFU Technical Services through

several standard campus licence agreements.

51

All binary variables are measured based on absence or presence when

appropriate, so bivariate findings are reported using Pearson Chi-square test or a

varying test when applicable. The orientation line was artificially incised onto samples

using a scalpel after their drying phase (post-recovery), thus no further statistics were

computed for this constant variable because all samples exhibit this feature. Cramer’s V

was used to measure the strength of association when there is statistical significance,

which will be discussed in the results for each taphonomic change variable. Rather than

using Cohen’s (1992) guidelines on measuring effect (the leading standard), an

adaptation of Chase et al.’s (1976) levels of effect size was used because it is tailored to

forensic anthropology. These levels include: very weak effect (less than 0.40), weak

(0.40 – 0.59), moderate effect (0.60 – 0.79), and strong effect (0.80 and higher) (adapted

from Chase et al., 1976).

The same sliding caliper was used to measure the samples throughout this

experiment, which means that only changes greater than 1 mm would be observed using

this method. The same stainless-steel waterproof bench scale was also used to weigh

the bones. Overall, the bones were measured, weighed, and examined prior to

deployment to ensure that all samples were of relative size, shape, and quality. Quality

was based on whether the sample exhibited signs of post-mortem changes (bacterial

remodelling, colour, disfiguration, and signs of pathology) prior to this experiment

beginning. This was also done to exclude any spongy bone samples, as there were

many discs cut that did not completely consist of cortical bone.

Any samples excluded were kept in the Centre for Forensic Research (CFR)

Forensic Anthropology Lab but were not used in this study. During this initial, pre-

deployment examination, pictures were taken and the presence of artefacts such as saw

marks and bony lipping were identified on the transverse cross-sectional plane. All

samples exhibited these features, and orientation lines were not introduced until

samples were recovered. Controls were separated and stored in the CFR Forensic

Anthropology Lab for the duration of the study, while the experimental samples bones

were submerged and analyzed upon recovery.

52

4.5. Ethics Exemption and Animal Care/Control

An ethics application was made in compliance with the provisions set forth by the

Tri-Council Policy Statement of 2014 (TCPS2-2014). This research received an

‘Exemption to Research Ethics Review’ from the Simon Fraser University Research

Ethics Board (SFU REB) under TCPS2 Article 2.1 and SFU Ethics Policy R20.01

(Research Study Number #2015s0550). An ‘Application to Use Invertebrates/Tissues for

Research or Teaching’ was made to the University Animal Care Committee because this

experiment involved the collection of deceased, non-human skeletal remains (Ovis

aries). Abiding by all the regulations required of ‘Category A: Animal Care Protocol’,

approval of sample collection and storage methods was also granted. Permission to use

Marion Lake at UBC Malcolm Knapp Research Forest, Centre for Forensic Research,

and Electron Imaging and Holography Facility was granted. The Malcolm Knapp

Research Forest project number is 2013 – 08, which outlines Lam’s dissertation.

Adhering to the requirements set forth by the TCPS2 and SFU REB, this

research has taken several measures to ensure that high standards of sample storage

and data management have been followed. The samples are strictly controlled and to

ensure sample integrity, they are secured inside the Centre for Forensic Research where

limited access is granted. All electronic data are stored on either the partitioned,

encrypted hard drive on Lam’s personal computer or on one of three secured portable

hard drives in Lam’s locked office at the CFR. Data integrity is also a key consideration,

so a log of all modifications made to the databases has been kept.

53

Chapter 5. Results

This chapter has been organized into two major components: (5.1) results

involving skeletal materials, and (5.2) results involving non-skeletal materials, such as

the elemental profiling of silt samples, temperature and precipitation data, and water

acidity. All interpretations of findings can be found in the subsequent discussion chapter,

including any incidental findings regarding the overall field portion of this experiment.

5.1. Results involving skeletal materials

This section of the results is specific to skeletal materials. The categories within

this section are based on taphonomic change (dependent variables), in relationship to

environmental conditions (location) and the length of submergence periods (time and

seasonality). The only exception to this approach would be the (5.1.1) first section

involving five variables related to overall size and weight of the samples. Before

examining these categories of taphonomic variables, this research will address whether

the overall size of samples may have an impact on skeletal diagenesis and other

decompositional changes. The reason behind this is to ensure that there is no significant

relationship between the discrepancy of sample sizes and the changes observed that

could raise generalizability issues. The second section (5.1.2) will provide the descriptive

statistics of all the variables. The third (5.1.3), fourth (5.1.4), and fifth (5.1.5) section will

consist of brief primers that discuss the logic behind key independent variables. From

section six (5.1.6 and onwards), each section will focus on an aspect of change, such as

artefacts, structural skeletal change, bone colour gradients, and accretion of both

organic and inorganic substances.

Descriptive statistics and bivariate analyses have been included in each section

for both thematic and organizational purposes, and significance is evaluated based on

two-tailed significance at a 95% confidence interval. One experimental sample (H02)

from Cage H was excluded from all secondary analysis because the sample fell into the

lake during the second recovery. For this reason, sample H02 is only used in the

measurement of sample size (n = 130) because the pre-deployment measurements are

54

available, but not in subsequent analyses (n = 129) because the sample was lost.

Encrustations, algae growth, and other biological masses that grew on the bone were

excluded because they were found to be an unreliable method of determining their

relationship with the sample, as a light rinse with distilled water removed vegetation

easily and the recovery process could have artificially introduced materials.

5.1.1. Overall Size and Weight

The bone disc measurements of both control and experimental specimens are

provided below (Table 5.1). Because the measurement variables are continuous by

nature, their range, mean, and standard deviation values have been reported. The size

of bone discs was compared to see if size differences are related to taphonomic change.

Results suggest that the size differences between samples is not statistically related to

decompositional change, as the bivariate analyses showed no statistical relationship

between size (cross sectional height, width, thickness, periosteal height, and weight) and

taphonomic signifiers.

Because all other taphonomic variables are either continuous or binary, the

correlation coefficient value was used to determine significance, based on a 95%

confidence interval where the p-value is less than 0.05. Pearson’s correlation was also

chosen over Spearman values because the variables are normally distributed. Each

sample was an independent observation, the sample size is 130, and all cell counts

were greater than 5, which supports that no statistical assumptions were violated in this

analysis.

Given the lack of statistical significance between decompositional changes and

the size of samples, the null hypothesis was accepted, and further analyses can be

pursued knowing that the surface area of the sample is not associated with the rate

and/or development of decompositional changes. No change between the samples

before and after submersion periods was detected. The control specimens also

remained the same size throughout this study. As mentioned previously, Sample H02

was not recovered, so only the pre-experiment measurements were used in these

calculations. There is nothing to suggest that H02 would be an outlier.

55

Null Hypothesis (H0) = There is no relationship between the size of bone discs and all other variables.

Hypothesis (H1) = There is a relationship between the size of bone discs and all other variables.

Table 5.1. Descriptive statistics of the measurement variables of all bone discs (n = 130).

Measurement Variables1

Min - Max �̅� M σ

xHeight (mm)

xWidth (mm)

xThickness (mm)

pHeight (mm)

Weight (g)

16.10 – 29.20

13.30 – 25.00

1.10 – 6.30

3.10 – 6.50

0.80 – 2.40

20.32

17.41

3.78

4.66

1.40

19.70

17.28

3.60

4.70

1.40

2.53

2.55

0.82

0.72

0.30

1 An ‘x’ before the measurement refers to measurements made of the transverse cross-sectional plane, and ‘p’ refers to measurements taken from the periosteal surface (refer to Figure 4.12).

5.1.2. Descriptive Statistics for Skeletal Samples

Descriptive statistics of all experiment parameters are presented in Table 5.2.

Artefacts, and taphonomic signifiers are presented in Table 5.3. Taphonomic change

was categorized as either a structural change, bone colour change, or as an

encrustation to describe substrates that deposited and/or penetrated the sample. The

values in Table 5.2 are based on the presence of these features across the entire

sample size (n = 129). Regarding the bone colour categorical variable, the first category

(0 = white) was chosen as the reference category because that is the colour of the

bones prior to deployment and the colour maintained by the control bones throughout

this experiment.

Descriptive statistic results show that 45% of samples lost their saw marks

completely (n = 58), and bone lipping was removed for 74.4% (n = 96) for all samples.

No taphonomic changes were observed on control bones. Structural changes were

observed on samples, including pitting (𝒙= 130, M = 130.7, σ = 155.44), periosteal

abrasion (68.2%, n = 88), periosteal cracking (45.0%, n = 58), cracking on the transverse

56

cross-sectional block face (53.5%, n = 69). There were no signs of gnawing on any

samples in this study, thus, no statistics were computed for this constant value and this

variable has been excluded from all further analyses.

Table 5.2. Coding of variables and the descriptive statistics of the experimental parameter variables (n = 129).

Experiment Parameter Variables % (n)

Sample Assignment (1 = experimental bone)1

Cage Location

0 = CFR Laboratory2

1 = Location A

2 = Location B

3 = Location C

4 = Location D

5 = Location E

6 = Location F

7 = Location G

8 = Location H

9 = Location I

10 = Location J

Days Elapsed

Lake Freeze (1 = exposure)3

92.2% (119)

7.8% (10)

9.3% (12)

9.3% (12)

9.3% (12)

9.3% (12)

9.3% (12)

9.3% (12)

9.3% (12)

8.5% (11)

9.3% (12)

9.3% (12)

𝒙 = 226.25, M = 189.00, σ = 163.83

31.0% (40)

1 The reference category is 0 = control sample. 2 This value is used as the reference category. 3 The reference category is 0 = no exposure.

Table 5.3. Coding of variables and the descriptive statistics of artefact and taphonomy variables (n = 129).

Variables % (n)

Artefacts

Orientation Line (1 = present)

Bone Lipping (1 = loss of artefact)1

Saw Marks (1 = loss of artefact)1

100.0% (129)

74.4% (96)

45.0% (58)

57

Variables % (n)

Structural Changes

Pitting

pAbrasion2 (1 = present)

pCracking2 (1 = present)

xCracking2 (1 = present)

Gnawing (1 = present)

Bone Colour Changes

Bone Colour

0 = White3

1 = White-beige

2 = Beige

3 = Beige-brown

4 = Brown

Encrustation

Stain Presence (1 = present)

Stain – Blue (1 = present)

Stain - Green (1 = present)

Black Surface Deposit (1 = present)

𝒙 = 130, M = 130.7, σ = 155.44

68.2% (88)

45.0% (58)

53.5% (69)

0.0% (0)

13.2% (17)

13.2% (17)

24.0% (31)

41.1% (53)

8.5% (11)

27.1% (35)

6.2% (8)

20.9% (27)

43.4% (56)

1 The reference category is 0 = artefact retained. 2 An ‘x’ before the name of variables refers to examinations made on the transverse cross-sectional plane, and ‘p’ refers to examinations made from the periosteal surface (refer to Figure 4.12). 3 This value is used as the reference category (no change).

5.1.3. Primer on the Environmental Impact on Skeletal Change

Based on this experiment’s non-skeletal findings, the silt samples from across the

lake seem to have the same chemical composition and morphological consistency, but

the water samples reveal differences in acidity that may impact the loss of pre-

deployment artefacts and the development of decompositional changes. This is not to

say that the water acidity would directly inflict mineral change to bone, but to suggest

that these differences may impact the microbial communities that may promote skeletal

change. To address whether the location of samples across Marion lake (categorical

58

variable) have an impact on artefact or taphonomic signifiers (further categorized as

either deteriorative or appearance changes), bivariate tests were used to determine

statistical significance between taphonomic variables and the ten experimental sites.

The hypothesis (H1) is that the location of submergence may be related to the

amount, frequency, or presence of decompositional changes in bone discs. Conversely,

the null hypothesis (H0) is that all skeletal material deposited into a Pacific Hemlock

freshwater lake would exhibit the same decompositional changes regardless of which

part of the lake in which it is submerged. The distribution of cage locations across

samples (n = 129) is positively skewed (0.005) and platykurtic (negative kurtosis = -

1.203), which is within reasonable limits (+/- 2) as to not require any statistical

corrections. The near perfectly normalized score for skewness (0.005) is because there

was an equal number of samples per cage, save for controls that stored one bone from

the same shaft that was used per cage location, which resulted in ten bone discs as

opposed to the twelve used for the experiment.

Null Hypothesis (H0) = There is no relationship between the location of the samples (laboratory and 10 field sites) and the changes found in samples.

Hypothesis (H1) = There is a relationship between the location of the samples (laboratory and 10 field sites) and the changes found in samples.

5.1.4. Primer on the Impact of Submergence Periods

The field experiment took a total of 16 months, for a total of 491 days. As

mentioned in the methods section, four recoveries could not take place because of the

hazardous weather conditions that made it physically impossible to recover samples

without endangering the recovery team. These include snow storms, freezing of the lake,

and the dangerous release of water from glacial melt that produced high energy currents

beneath the frozen lake surface. The degenerative changes in bones was hypothesized

to increase based on the number of days the sample has been submerged.

The number of days a sample was submerged was measured for all 129 bone

discs, ranging from 0 days for control specimens to 491, the maximum exposure that any

experimental sample had undergone. The mean amount of days exposed is 266.25

days, with a standard deviation of 163.834. When samples were recovered, they were

randomly selected from the cage and the cage was quickly returned back into the water

59

to limit the amount of disturbance and surface exposure. The statistical distribution of

submergence periods is considerably normalized (within +/- 2), with a positive skewness

of 0.360 and platykurtic shape with a negative kurtosis of -1.293 (n = 129). The number

of days submerged are specifically: 0 (no submergence), 34, 66, 94, 127, 155, 189, 219,

250, 405, 432, 460, and 491 days. Information on why these intervals were selected can

be found under Chapter 4.

Null Hypothesis (H0) = There is no relationship between the length of submergence periods and all other variables.

Hypothesis (H1) = There is a relationship between the length of submergence periods and all other variables.

5.1.5. Primer on the Impact of Winter Lake Freeze on Skeletal Change

There are several ways to define changes in seasons, such as temperature,

calendar dates, and earth’s distance from the sun. Some descriptions can distort how

certain weather-based phenomenon that impact taphonomic change are documented,

especially given global climate change. The cold weather normally associated with

autumn has not been apparent in the Metro Vancouver region throughout the duration of

this experiment. Based on temperature and precipitation findings, the weather at Marion

lake has been warmer late into the year and remained colder throughout most of the

Spring season. For this reason, this research will define winter based on when the lake

was no longer accessible due to weather-induced hazards such as heavy snow falls and

Marion lake freezing over. There is no way to tell if the samples or the bones were frozen

or not during this time, just that they were exposed to a very cold climate.

To evaluate whether exposure to cold climate had an impact on skeletal samples,

a dummy code variable was made for samples recovered after being exposed to winter

conditions. Because of the way the experiment was set up, all samples from recovery 9,

10, 11, and 12 were captured by this variable because the recovery dates occurred after

the lengthy winter period (December 2015 – March 2016). When evaluating whether any

statistical assumptions were broken, results show that there is no significant relationship

between exposure to lake freeze and the location of samples (𝑥2 = 4.915, df = 10, p =

0.897), but there was a significant relationship found between lake freeze and

submergence periods (𝑥2 = 129.000, df = 12, p = 0.000).

60

Concerns about multicollinearity exist, which should be kept in mind should

regression modelling be pursued in future studies using these data. The distribution of

the number of samples exposed to winter lake freeze is platykurtic (negative kurtosis = -

1.330) and positive skewed (0.831). This distribution falls within reasonable limits (+/- 2),

so no further corrections were made. A total of 40 (31%) samples were exposed to the

winter lake freeze condition (n = 129). There is no way to know whether the samples

were frozen when the lake surface was frozen, because the samples could not be

accessed. All that is known is that the temperature in the lake dropped significantly, and

the layer of snow and ice above the lake could have changed the environmental

conditions dramatically enough to elicit some kind of taphonomic change.

Null Hypothesis (H0) = There is no relationship between the impact of being exposed to winter conditions and all other variables.

Hypothesis (H1) = There is a relationship between the impact of being exposed to winter conditions and all other variables.

5.1.6. Loss of Pre-deployment Bony Lipping and Saw Mark Artefacts

The results pertaining to artefacts in this section do not include orientation lines

because they were applied post-recovery. For context, the process of sectioning skeletal

shafts with a mechanical blade causes an excess of bony material to form along the

partial exit perimeter of the blade, as well as saw marks that can be seen from the

transverse cross-sectional block face of bone discs. During macroscopic documentation

of surface changes, it soon became clear that there were no changes in artefact

prominence amongst control bones. Both bone lipping and saw marks on control bones

were seen before and after the field experiment. However, bivariate analyses revealed

that there was a loss of definition of pre-deployment artefacts in the experimental bones.

In total, macroscopic examination through light microscopy revealed that 45% of

samples (n = 58) exhibited no saw marks post-recovery where they were once present,

and a total of 74.4% (n = 96) of samples did not retain any bony lipping (Table 5.3).

When there was suspected loss of this feature, but some form of bony lipping was still

present, samples were considered to have retained this feature; only complete loss was

measured. The presence of bone lipping and saw marks were present in all bone

samples prior to their deployment but appears to be obscured over time when

61

submerged. It is the absence of this feature that is of interest, not its presence – as

opposed to the other variables of taphonomic change.

Given that both bony lipping and saw marks are binary variables, Pearson’s Chi-

Square values were used to determine significance in relation to the location of samples,

and Cramer’s V was used to measure the effect size because the location variable

exceeded two categories. A two-tailed independent t-test was used to evaluate the

correlation coefficient in relation to the length of submergence in days to artefact loss

(Hypothesis is that lipping loss and retention have endured different number of days of

submergence). Levene’s test was used in the latter two cases to determine

homoscedasticity, and Hedge’s g was used to measure effect size. Hedge’s g was

chosen because the author did not have access to the population’s standard deviation,

as required for Cohen’s d. Pearson’s Chi-Square values were used to determine whether

the sample being exposed to lake freeze would have an impact. Phi was used to

evaluate effect size due to the categorical variable being binary.

Bony Lipping. The observations of bony lipping absence are assumed to be

independent, and the distribution is marginally platykurtic (negative kurtosis = -0.729)

and negatively skewed (-1.133). Any values within +/- 2 for skewness and kurtosis was

considered acceptable distribution variance for this variable, so no statistical corrections

were sought. Bony lipping was identified macroscopically in all the control samples (n =

10) and observed in all samples retrieved from the first and second recovery (n = 19),

but by the third recovery (94 days of submergence), only the samples from sites A, B, C,

and D exhibited this feature (n = 4).

Bivariate analyses show that the loss of bony lipping has a statistically significant

relationship with all three independent variables. Firstly, the author observed a strong

association between artefact loss and the location of its submergence (𝑥2 (10) = 33.175,

p = 0.000), thus, the null hypothesis is rejected. However, 11 cells (50%) have an

expected count of less than 5 where the minimum expected is 2.56, which violates one

of the chi-square assumptions. Due to this violation, the likelihood ratio was examined

(𝑥2 (10) = 31.954, p = 0.000) to conclude that the relationship is indeed significant, and

that artefact loss is dependent on the location of its submergence, but the effect of

location is weak (Cramer’s V = 0.507, p = 0.000) (Table 5.4).

62

Secondly, the loss of bony lipping was observed as being highly related to the

number of days for which the sample was submerged, whereby the means are

significantly different. The loss of lipping is considerably higher than retained, with a

mean score of 290.04 (96) as compared to 40.67 (n = 33). Levene’s test was found to be

significant (F = 136.747, p = 0.000), so the results where equal variances are not

assumed was used to correct for heteroscedasticity. The results of the t-test for equality

of means suggests that the difference between days submerged between samples that

retained their bony lipping and those that had their bony lipping removed is statistically

significant (t (118.812) = -16.153, p = 0.000). The effect size revealed that the magnitude

of the difference between groups was very strong (-2.445), whereby the negative effect

size indicates that the second mean is larger than the first mean:

𝑆𝑝𝑜𝑜𝑙𝑒𝑑 = √𝑠1

2 + 𝑠22

2= √

32.9462 + 140.4412

2= 102.003

𝐻𝑒𝑑𝑔𝑒′𝑠 g = 𝑀1 − 𝑀2

𝑆𝑝𝑜𝑜𝑙𝑒𝑑=

40.67 − 290.04

102.003= −2.445

Lastly, exposure to lake freeze was observed to be statistically related to loss of

bony lipping (𝑥2 (1) = 19.930, p = 0.000), but the effect of this exposure is weak (Phi =

0.393, p = 0.000) (Table 5.5). In other words, being exposed to the lake freeze is indeed

related to the loss of this artefact, but the role it plays is minimal. This supports the idea

that there may be many competing reasons for why pre-deployment artefacts are lost

when submerged in lacustrine environments.

Saw Marks. The observations for saw marks are assumed to be independent.

The distribution is marginally leptokurtic (positive kurtosis = 0.205) and negatively

skewed (-1.989), which is considered acceptable enough that no additional corrections

were made. Just like bony lipping, where the sample was submerged is related to the

loss of saw marks (𝑥2 (10) = 40.709, p = 0.000), but its effect is relatively weak

(Cramer’s V = 0.562, p = 0.000). Only two cells had an expected count of less than 5, so

no further corrections were sought for this analysis. Details regarding the specific

locations of their submergence are outlined in Table 5.4.

63

Table 5.4. Bivariate associations between the location of variables (IV)1, length of submergence (IV)1, and exposure to lake freeze (IV)1 to the loss of saw marks (DV)1 and bony lipping (DV)1 artefacts (n = 129).

Saw Marks Bony Lipping

Location Variable Loss (%) Retained

(%) Loss (%) Retained

(%)

CFR Laboratory2

Site A

Site B

Site C

Site D

Site E

Site F

Site G

Site H

Site I

Site J

0 (0.0%)

8 (66.7%)

8 (66.7%)

9 (75.0%)

7 (58.3%)

6 (50.0%)

2 (16.7%)

8 (66.7%)

8 (72.7%)

1 (8.3%)

1 (8.3%)

10 (100.0%)

4 (33.3%)

4 (33.3%)

3 (25.0%)

5 (41.7%)

6 (50.0%)

10 (83.3%)

4 (33.3%)

3 (27.3%)

11 (91.7%)

11 (91.7%)

0 (0.0%)

9 (75.0%)

9 (75.0%)

9 (75.0%)

9 (75.0%)

10 (83.3%)

10 (83.3%)

10 (83.3%)

10 (90.9%)

10 (83.3%)

10 (83.3%)

10 (100.0%)

3 (25.0%)

3 (25.0%)

3 (25.0%)

3 (25.0%)

2 (16.7%)

2 (16.7%)

2 (16.7%)

1 (9.1%)

2 (16.7%)

2 (16.7%)

Total

58 (45.0%)

71 (55%) 96 (74.4%) 33 (25.6%)

Pearson Chi-Square Symmetric Value

𝑥2 = 40.709, df = 10, p = 0.000 Cramer’s V = 0.562, p = 0.000

𝑥2 = 31.954, df = 10, p = 0.000 Cramer’s V = 0.507, p = 0.000

1 IV refers to independent variables, and DV refers to the dependent variable.

2 Control specimens were stored in the Centre for Forensic Research’s Forensic Anthropology Laboratory.

Regarding days elapsed in submergence, mean score of 302.29 in samples that

lost their saw marks (n = 58) was much greater than the mean score of 164.13 for

samples that retained their marks (n = 71). Levene’s test was not significant, so equal

variances have been assumed (F = 0.050, p = 0.823). The impact of the length of

submergence was statistically significant (t (127) = -5.233, p = 0.000), and the effect was

considered strong (-0.932):

𝑆𝑝𝑜𝑜𝑙𝑒𝑑 = √𝑠1

2 + 𝑠22

2= √

156.6572 + 139.4482

2= 148.302

𝐻𝑒𝑑𝑔𝑒′𝑠 g = 𝑀1 − 𝑀2

𝑆𝑝𝑜𝑜𝑙𝑒𝑑=

164.13 − 302.29

148.302= −0.932

64

The relationship between exposure to lake freeze and the loss of saw marks was

also found to be statistically significant (𝑥2 (1) = 9.408, p = 0.0002), but the effect was so

small that it can be considered very weak (Phi = 0.270, p = 0.002). Given these findings,

it is clear that the loss of definition in pre-deployment artefacts is occurring, and this

taphonomic change is related to the location of its submergence, length of

submergence, and exposure to lake freeze but the effect of these circumstances varies

greatly.

5.1.7. Pitting versus Vascularity

To determine whether the pitting features observed was a product of bioerosion

mechanics from microbial communities or the expansion and/or alteration of existing

vascular structures, an experimental sample was thin-sectioned and examined using a

modular microscope. This secondary analysis revealed that the features first observed

under a light microscope are existing vascular structures being stained by unidentified

external agents. There are signs of crenulation around the outer perimeter of the holes,

which is a feature that is indicative of natural bone growth and remodelling and not post-

mortem bioerosion or microbial diagenesis. Thus, what was originally thought to be

structural change in experimental bone during light surface analysis was the

documentation of exaggerated natural vascular structures that have been made more

apparent through selective staining.

Given the new information provided by histological analyses, the term pitting was

replaced by the term cutting cones (CC) in the results and discussion to more accurately

reflect what change was observed. Cutting cones are the total osteonal area observed

(Klein-Nulend et al., 2003; Pazzaglia et al., 2013). When the bones were first

submerged, they were not chemically macerated prior to deployment, so the organic

tissues were still intact. Over time, these organic tissues were separated, making the

existing Haversian canals and other holes (ex. nutrient foramen and osteocytes)

observable under low magnification. This process of selective staining of vascular

structures that made cutting cones more apparent offers valuable information on organic

tissue loss that may be indicative of lacustrine submergence.

The number of cutting cones (CC) measured across all samples (n = 129) varies

from a minimum of zero, as expected from control samples, to a high of 806. The mean

65

number of CC observed in samples is 130.7, median of 66.0, and standard deviation of

155.44. The total number of CC observed is tallied instead of tallying them by quantiles

because there was little to suggest that different areas of the transverse cross-sectional

faces of the bone disc would be more susceptible to change than others. It is unclear

why the selective staining of vascular structures appears in localized regions (Figure

5.1).

Figure 5.1. A low magnification macroscopic image of localized cutting cones (originally thought to be bioerosion and/or pitting) under a light microscope.

Regarding the distribution of CC features across all samples, the distribution is

leptokurtic (Kurtosis = 2.725) and positive skewed (1.652). The author did consider log-

transformation to normalize the distribution but given the size of the sample (n = 129),

this approach did not seem appropriate, so no corrections were made for this variable. A

boxplot depicting the distribution of total number of CC observed by location is shown in

Figure 5.2. Bivariate analyses were also pursued. The first test was to evaluate the

relationship between the location of bone submergence and the total number of CC

observed. Given that this sample is not normally distributed (within +/- 2), a Kruskal-

Wallis test was used in lieu of an independent t-test. Results of the Kruskal-Wallis Test

66

rejected the null hypothesis and suggested that there is a statistically significant

relationship between location and the number of CC made visible (𝑥2 (10) = 33.232, p =

0.000). The small effect size of 0.260 suggests that 26% of the variability in rank scores

(Table 5.6) is accounted for by the location of the submergence (grouping variable):

𝐸𝑓𝑓𝑒𝑐𝑡 𝑠𝑖𝑧𝑒 = 𝑥2

𝑛 − 1=

33.232

129 − 1= 0.260

Figure 5.2. Boxplot depicting the distribution of cutting cones per location (CFR Laboratory, Location A – J). Outliers within one degree of freedom is denoted by ‘o’ and any outliers beyond that distance is denoted by an ‘ * ’.

Table 5.5. Kruskal-Wallis rank scores of the total number of cutting cones by laboratory (controls) or submergence location.

LOC1 CFR2 A B C D E F G H I J Total

N 10 12 12 12 12 12 12 12 11 12 12 129

Mean Rank

12.00 71.17 70.75 71.67 98.08 51.63 59.42 63.08 71.14 65.79 71.96

1 LOC refers to Location. 2 CFR refers to the Centre for Forensic Research Anthropology Laboratory, where the controls were held.

67

Spearman’s rho was used to test whether submergence periods and the number

of cutting cones observed are linearly related. Spearman’s was used because it removes

the effect of outliers by relying on rank instead of exact numbers. A strong linear

relationship was observed between these two variables (Spearman’s rho = 0.666, p =

0.000). These observations were independent, and the sample size was greater than 30

(n = 129) as to meet the basic assumptions of this test. When evaluating the impact of

winter lake freeze on the number of cutting cones made apparent, a Mann-Whitney U

test was used because the dependent variable is not normally distributed. Their

relationship is statistically significant (p = 0.000, Mann-Whitney U = 907.500), however,

the effect size of 0.155 is very weak:

𝐸𝑓𝑓𝑒𝑐𝑡 𝑠𝑖𝑧𝑒 = 𝑛2 = 𝑧2

𝑛 − 1=

−4.4562

129 − 1= 0.155

5.1.8. Abrasion and Cracking

Abrasion is only observed on the periosteal surface when examined

macroscopically using a light microscope, although it is possible that abrasion had taken

place on the transverse cross-section block face. Cracking, on the other hand, was

observed on both the periosteal surface as well as from the transverse cross-sectional

block face. The periosteum eventually separated from the sample, which exposed the

cortical bone (Figure 5.3). All samples did retain periosteal tissues, but of varying

amounts. The appearance of distinctive boundaries was also observed on the periosteal

surface (5.4).

Periosteal Abrasion. The distribution of periosteal abrasion across all samples

(n = 129) is platykurtic (negative kurtosis = -1.395) and negatively skewed (- 0.792), but

within a reasonable range (+/- 2) as to not require further corrections. A total of 88

(68.2%) samples exhibited this feature, and the control did now show any signs of

abrasion. Results show that there is a significant relationship between periosteal

abrasion and the location of samples (𝑥2 (10) = 28.055, p = 0.002), but the strength of

the association is weak (Cramer’s V = 0.466) (Table 5.6).

68

Figure 5.3. Light microscope image of the periosteal surface of a submerged, experimental sample that illustrates the appearance of exposed cortical bone (right) and the periosteum (outermost layer of bone) retained (left).

Figure 5.4. Light microscope image of the periosteal surface of a submerged, experimental sample’s distinctive boundary between exposed vascular structures from abrasion (left), and a surface abraded but retained (right).

69

When examining the periosteal surface abrasion based on the number of days

for which the sample was submerged, the Levene’s Test was found to be significant, so

equal variances were not assumed (F = 33.912, p = 0.000). Results of the independent

t-test suggests that there is a strong correlation between these two variables (t (127) = -

8.954, p = 0.000), and the effect size is very strong (Hedge’s g = -1.776), whereby the

negative effect size indicates that the second mean (experimental samples) is larger

than the first mean (control samples):

𝑆𝑝𝑜𝑜𝑙𝑒𝑑 = √𝑠1

2 + 𝑠22

2= √

104.7382 + 138.4362

2= 122.749

𝐻𝑒𝑑𝑔𝑒′𝑠 g = 𝑀1 − 𝑀2

𝑆𝑝𝑜𝑜𝑙𝑒𝑑=

77.51 − 295.55

122.749= −1.776

Of the 88 (68.2%) samples that showed signs of periosteal abrasion, 38 (43.2%)

have been exposed to lake freezing. Of the 41 (31.8%) samples that did not show any

periosteal abrasion, only 2 (4.9%) of samples were also exposed to winter lake freeze.

The association between periosteal abrasion and location is significant (𝑥2 (1) = 19.182,

p = 0.000), but the effect size is considered negligible based on the parameters often

found in other forensic anthropology studies. The effect is notably very close to being

weak (Phi = 0.386).

Periosteal Cracking. Due to very high inter and intra variability in measuring the

number and extent of cracking found during the analysis phase, this variable was

dummy coded from a Likert scale to a binary variable. Of the 129 samples in this

experiment, 58 (45%) showed signs of periosteal cracking. The distribution of this

variable was platykurtic (negative kurtosis = -1.989) and marginally positively skewed

(0.205), which is normal enough that no corrections were made. The relationship

between periosteal cracking and the location of the cage submergence was found to be

not significant (𝑥2 (10) = 17.688, p = 0.060) at a 95% confidence interval. Should the

confidence interval be reduced to 90%, then Cramer’s V would be assessed - at which

point, the effect would be considered negligible but close to being weak (0.370).

When evaluating the impact of elapsed time on cracking presence, the Levene’s

Test of Equality of Variances was found to be not significant (F = 2.008, p = 0.159), so

70

the sample is assumed to be homoscedastic. The relationship between these two

variables is statistically significant (t (127) = -5.151, p = 0.000), with a strong negative

effect size (-1.294). This suggests that elapsed time plays an important role in

determining whether periosteal cracking will occur in submerged samples. The sample

being exposed to lake freeze and periosteal cracking is significant (𝑥2 (1) = 11.902, p =

0.001) and the effect size was very weak (Phi = 0.304):

𝑆𝑝𝑜𝑜𝑙𝑒𝑑 = √𝑠1

2 + 𝑠22

2= √

150.0.332 + 149.0472

2= 105.392

𝐻𝑒𝑑𝑔𝑒′𝑠 g = 𝑀1 − 𝑀2

𝑆𝑝𝑜𝑜𝑙𝑒𝑑=

164.93 − 301.31

105.392= −1.294

Transverse Cross-sectional Block Face Cracking. As mentioned previously,

this variable was coded to include any cracks that can be seen from the transverse

cross-sectional block face, with the exception of periosteal cracks (i.e. cracks that

originate or stem from the periosteal layer). This variable is effectively aimed to capture

osteonal cracks and those that travel along the natural lamellar alignment of plexiform

bone. A total of 69 (53.5%) samples exhibited this feature. The distribution is platykurtic

(negative kurtosis = -2.011) and negatively skewed (-0.142). The kurtosis score was

close enough to the threshold of +/- 2 that no further corrections were made to this

variable.

The location of the sample was found to have a significant impact on cracking (𝑥2

(10) = 19.558, p = 0.034), but the effect size is very weak (Cramer’s V = 0.389). This

suggests that even though the location of the bone submergence played a role in

cracking, its impact was negligible (Table 5.6). Conversely, the length of submergence

periods is found to be significantly related to cracking (t (127) = -9.832, p = 0.000), and

this effect is strong (- 1.726). Levene’s test was found to be significant (F = 19.187, p =

0.000) so equal variances were not assumed. The impact of exposure to winter lake

freeze was found to have a weak association with cracking (Phi = -0.457), but its

relationship was nonetheless statistically significant (𝑥2 (1) = 16.958, p = 0.000):

𝑆𝑝𝑜𝑜𝑙𝑒𝑑 = √𝑠1

2 + 𝑠22

2= √

113.4982 + 133.3842

2= 123.841

71

𝐻𝑒𝑑𝑔𝑒′𝑠 g = 𝑀1 − 𝑀2

𝑆𝑝𝑜𝑜𝑙𝑒𝑑=

111.93 − 325.65

123.841= −1.726

Table 5.6. Bivariate associations between periosteal abrasion, periosteal cracking, and transverse cross-sectional cracking (DV) and the location of the samples (IV)1 (n = 129).

pAbrasion2 pCracking2 xCracking2

Location Variable Absent (%) Present (%) Absent (%) Present (%) Absent (%) Present (%)

CFR Laboratory

Site A

Site B

Site C

Site D

Site E

Site F

Site G

Site H

Site I

Site J

Total

10 (100.0%)

2 (16.7%)

3 (25.0%)

3 (25.0%)

3 (25.0%)

2 (16.7%)

4 (33.3%)

3 (25.0%)

2 (18.2%)

6 (50.0%)

3 (25.0%)

41 (31.8%)

0 (0.0%)

10 (83.3%)

9 (75.0%)

9 (75.0%)

9 (75.0%)

10 (83.3%)

8 (66.7%)

9 (75.0%)

9 (75.0%)

6 (50.0%)

9 (75.0%)

88 (68.2%)

10 (100.0%)

4 (33.3%)

7 (58.3%)

4 (33.3%)

5 (41.7%)

8 (66.7%)

9 (75.0%)

6 (50.0%)

7 (63.6%)

5 (41.7%)

6 (50.0%)

71 (55.0%)

0 (0.0%)

8 (66.7%)

5 (41.7%)

8 (66.7%)

7 (58.3%)

4 (33.3%)

3 (25.0%)

6 (50.0%)

4 (36.4%)

7 (58.3%)

6 (50.0%)

58 (45.0%)

10 (100%)

3 (25.0%)

5 (41.7%)

4 (33.3%)

3 (25.0%)

7 (58.3%)

6 (50.0%)

5 (41.7%)

6 (54.5%)

4 (33.3%)

7 (38.3%)

60 (46.5%)

0 (0.0%)

9 (75.0%)

7 (58.3%)

8 (66.7%)

9 (75.0%)

5(41.7%)

6(50.0%)

7 (58.3%)

5 (45.5%)

8 (66.7%)

5 (41.7%)

69 (53.5%)

Pearson Chi-Square Symmetric Value

𝑥2 = 28.055, df = 10, p = 0.002 Cramer’s V = 0.466, p = 0.002

𝑥2 = 17.688, df = 10, p = 0.060 Cramer’s V = 0.370, p = 0.060

𝑥2 = 19.558, df = 10, p = 0.034 Cramer’s V = 0.389, p = 0.034

1 IV refers to independent variables, and DV refers to the dependent variable. 2 pAbrasion refers to the periosteal surface abrasion, pCracking refers to the periosteal surface cracking, and xCracking refers to the transverse cross-sectional block face cracking.

5.1.9. Evaluation of Sectioned Surface and Internal Bone Colour

For the purposes of this analysis, the colour documented is based on the colour

of the bone within 3 – 14 days after it was recovered. None of the bones were examined

until a minimum of 48 hours had passed after they were dried. The specific colours of the

bone were also evaluated based on Munsell colour chart. Many of the samples exhibited

a gradient of several pale beiges. This method may yield more accurate results in

identifying true colour, but the level of detail made comparisons and generalisabilities

very difficult. These colours are reported in the appendix, and no further analyses were

pursued with this string variable.

The distribution of bone colour changes is platykurtic (negative kurtosis = -0.749)

and negatively skewed (-0.537), which falls within the range of acceptable variance (+/-

2). When looking at this colour change in relation to the location of submergence, results

suggest that there is a significant relationship (𝑥2 (40) = 113.899, p = 0.000), and the

effect size is weak (Cramer’s V = 0.470). Many of the cells shared the same value, which

suggests that the proportion of change per location does not effectively differ

significantly from each other at the 0.5 level (95% confidence interval). Details regarding

the specific colour and distribution location is outlined in Table 5.7.

When evaluating the impact of submergence period on bone colour change, a

One-Way Anova was used to compare the means between and within groups. Results

suggest that this relationship is significant (p = 0.000). The effect size was measured

based on Eta-squared, whereby the sum of squares between groups is divided by the

total sum of squares. The effect size was found to be moderate (𝜂2 = 0.741), which is

fairly close to being strong. Using Eta-squared, 71% of the total variance between the

bone colours can be accounted by the length of submergence:

𝜂2 =𝑆𝑆 𝑏𝑒𝑡𝑤𝑒𝑒𝑛

𝑆𝑆 𝑡𝑜𝑡𝑎𝑙=

137.481

185.581= 0.741

Similar findings were found between the effect of being exposed to winter lake

freeze and the colour changes, whereby the relationship was found to be significant (𝑥2

(4) = 25.782, p = 0.000) but the effect size was considerably weak (Cramer’s V = 0.447).

Based on these findings, it appears that the amount of time a bone spends submerged

74

has the greatest impact on skeletal samples turning from a porcelain white to dark

brown.

Table 5.7. Bivariate associations between bone colour changes (DV)1 and the location of the samples (IV)1 (n = 129).

Bone Colour

Location Variable White (%) White-Beige (%) Beige (%) Beige-Brown (%) Brown (%)

CFR Laboratory

Site A

Site B

Site C

Site D

Site E

Site F

Site G

Site H

Site I

Site J

Total

100 (0.0%)

1 (8.3%)

1 (8.3%)

1 (8.3%)

1 (8.3%)

1 (8.3%)

1 (8.3%)

1 (8.3%)

0 (0.0%)

1 (8.3%)

1 (8.3%)

19 (14.7%)

0 (0.0%)

2 (16.7%)

1 (8.3%)

1 (8.3%)

2 (16.7%)

4 (33.3%)

1 (8.3%)

2 (16.7%)

1 (9.1%)

2 (16.7%)

0 (0.0%)

16 (12.4%)

0 (0.0%)

2 (16.7%)

2 (16.7%)

2 (16.7%)

4 (33.3%)

0 (0.0%)

8 (66.7%)

6 (50.0%)

2 (18.2%)

2 (16.7%)

2 (16.7%)

30 (23.3%)

0 (0.0%)

4 (33.3%)

5 (41.7%)

5 (41.7%)

5 (41.7%)

7 (58.3%)

2 (16.7%)

3 (25.0%)

8 (72.7%)

7 (58.3%)

7 (58.3%)

53 (41.1%)

0 (0.0%)

3 (25.0%)

3 (25.0%)

3 (25.0%)

0 (0.0%)

0 (0.0%)

0 (0.0%)

0 (0.0%)

0 (0.0%)

0 (0.0%)

2 (16.7%)

11 (8.5%)

Pearson Chi-Square Symmetric Value

𝑥2 = 113.899, df = 40, p = 0.000 Cramer’s V = 0.470, p = 0.000

1 IV refers to independent variables, and DV refers to the dependent variable.

5.1.10. Blue and Green Staining from External Agents

There was a total of 35 (27.1%) samples that exhibited staining from an external

agent (n = 129). The quantity of surface area stained was not measured, only the

presence or absence of such a stain post-recovery, and after the sample was lightly

rinsed and dried. The two types of stains observed were blue (n = 8) and green (n = 27).

The stains were found on both the periosteal and transverse cross-sectional block face,

and the mass often appeared to be interconnected. The stain location was also different

across all samples, some taking up greater residence on the periosteal layers, and

others only radiating from different areas on the cross-sectional surface.

The presence of stains had a platykurtic (negative kuroisis = -0.932) and

positively skewed (1.041) distribution. Given how few bones exhibited blue staining, the

distribution for this sample was grossly (positive kurtosis = 11.685) and positively

skewed (3.675). For this reason, this variable was log transformed to normalize the

distribution, with the intention of using the logged variable for subsequent analyses. Note

that this variable was dummy coded and recoded back into original operationalized

characters where 0 is the reference category (no blue stain). However, due to the very

small count, the logged variable presented the same distribution as before. The

distribution of samples exhibiting green staining was also leptokurtic (positive kurtosis =

0.092), and positively skewed (1.446).

Stain Presence. When evaluating the impact of the location of submergence on

staining presence in general, the relationship between these variables was found to be

significant (𝑥2 (10) = 21.631, p = 0.017) but the effect size was weak (Cramer’s V =

0.409). The specific distribution of samples with staining by location is outlined in Table

5.8. The results of the Levene’s Test for Equality of Variances between days elapsed

and stain presence was not significant (F = 1.228, p = 0.270), so equal variances are

assumed. This relationship was found to be statistically significant (t (127) = -4.482, p =

0.000), with a strong effect size (Hedge’s g = -0.891). The impact of winter exposure to

stain presence was found to be significant (𝑥2 (1) = 12.166, p = 0.000) but the effect was

very weak (Phi = 0.307):

77

𝑆𝑝𝑜𝑜𝑙𝑒𝑑 = √𝑠1

2 + 𝑠22

2= √

153.5142 + 150.9572

2= 152.241

𝐻𝑒𝑑𝑔𝑒′𝑠 g = 𝑀1 − 𝑀2

𝑆𝑝𝑜𝑜𝑙𝑒𝑑=

189.45 − 325.09

152.241= −0.891

Blue Stain Presence. The location of the sample had no effect on whether a

blue stain would become apparent (𝑥2 (10) = 14.523, p = 0.150) (Table 5.8). Regarding

the impact of submergence periods, Levene’s test showed that equal variances could

not be assumed in blue stain presence within this sample population (F = 14.192, p =

0.000), and that the number of days submerged had no effect on this type of stain

presence (t (127) = 0.953, p = 0.342). Due to the small count and violation of

assumptions for a typical Chi-square, the continuity correction value was used instead.

This result showed that the impact of exposure to winter lake freeze was not significant

(𝑥2 (1) = 2.444, p = 0.118).

Green Stain Presence. The location of where green-stained samples was found

(Table 5.8) to have a statistically significant impact (𝑥2 (10) = 18.450, p = 0.048), but the

effect size was very weak (Cramer’s V = 0.378). The population of green stain presence

based on the number of days it was submerged for was homoscedastic (Levene’s test: F

= 0.024, p = 0.877), so equal variances were assumed. The submergence period was

found to be statistically significant for this variable (t (127) = -5.741, p = 0.000), with a

strong effect (Hedge’s g = -1.258). The exposure to winter lake freeze was found to have

an impact on green staining presence (𝑥2 (1) = 24.732, p = 0.000), but the effect size

was weak (Phi = 0.438):

𝑆𝑝𝑜𝑜𝑙𝑒𝑑 = √𝑠1

2 + 𝑠22

2= √

147.8232 + 141.5382

2= 144.715

𝐻𝑒𝑑𝑔𝑒′𝑠 g = 𝑀1 − 𝑀2

𝑆𝑝𝑜𝑜𝑙𝑒𝑑=

188.14 − 370.22

144.715= −1.258

Table 5.8. Bivariate associations between bone staining (DV) and the location of the samples (IV)1 (n = 129).

Bone Staining Presence Stain – Blue Stain - Green

Location Variable Absent (%) Present (%) Absent (%) Present (%) Absent (%) Present (%)

CFR Laboratory

Site A

Site B

Site C

Site D

Site E

Site F

Site G

Site H

Site I

Site J

Total

10 (100.0%)

9 (75.0%)

7 (58.3%)

11 (91.7%)

11 (91.7%)

7 (58.3%)

12 (100.0%)

9 (75%)

6 (54.5%)

7 (58.3%)

11 (91.7%)

100 (77.5%)

0 (0.0%)

3 (25.0%)

5 (41.7%)

1 (8.3%)

1 (8.3%)

5 (41.7%)

0 (0.0%)

3 (25.0%)

5 (45.5%)

5 (41.7%)

1 (8.3%)

29 (22.5%)

10 (100.0%)

11 (91.7%)

11 (91.7%)

12 (100.0%)

12 (100.0%)

9 (75.0%)

12 (100.0%)

10 (83.3%)

9 (81.8%)

12 (100.0%)

11 (91.7%)

119 (92.2%)

0 (0.0%)

1 (8.3%)

1 (8.3%)

0 (0.0%)

0 (0.0%)

3 (25%)

0 (0.0%)

2 (16.7%)

2 (18.2%)

0 (0.0%)

1 (8.3%)

10 (7.8%)

10 (100.0%)

9 (75.0%)

8 (66.7%)

11 (91.7%)

10 (83.3%)

8 (66.7%)

12 (100.0%)

11 (91.7%)

6 (54.5%)

7 (58.3%)

12 (100.0%)

104 (80.6%)

0 (0.0%)

3 (25.0%)

4 (33.3%)

1 (8.3%)

2 (16.7%)

4 (33.3%)

0 (0.0%)

1 (8.3%)

5 (45.5%)

5 (41.7%)

0 (0.0%)

25 (19.4%)

Pearson Chi-Square Symmetric Value

𝑥2 = 21.631, df = 10, p = 0.017 Cramer’s V = 0.409, p = 0.017

𝑥2 = 14.523, df = 10, p = 0.150 ---

𝑥2 = 18.450, df = 10, p = 0.048 Cramer’s V = 0.378, p = 0.048

1 IV refers to independent variables, and DV refers to the dependent variable.

5.1.11. Black Surface Deposit

In total, 57 (44.2%) of the 129 samples had black surface deposits. The

distribution of these samples was fairly normal, with a platykurtic shape (negative

kurtosis = -1.975) and mild positive skewness (0.237); thus, no further corrections were

made. The black surface inclusions were found to not be associated with the location of

cage sites (𝑥2 (10) = 17.431, p = 0.065) (Table 5.9). Results of Levene’s test for equality

of variances between this variable and elapsed days was not significant, so homogeneity

of variances can be assumed (F = 3.219, p = 0.075). The Independent Samples test

revealed that days elapsed did not have an impact on mineral deposit accumulation (t

(127) = -1.817, p = 0.072). Exposure to winter was also found to not be associated with

this variable (𝑥2 (1) = 0.16, p = 0.901).

Table 5.9. Bivariate associations between black surface deposits (DV) and the location of the samples (IV)1 (n = 129).

Black Surface Deposits

Location Variable Absent (%) Present (%)

CFR Laboratory

Site A

Site B

Site C

Site D

Site E

Site F

Site G

Site H

Site I

Site J

Total

10 (100.0%)

9 (75.0%)

6 (50.0%)

7 (58.3%)

5 (41.7%)

4 (33.3%)

4 (33.3%)

7 (58.3%)

8 (72.7%)

6 (50.0%)

6 (50.0%)

73 (56.6%)

0 (0.0%)

3 (25.0%)

6 (50.0%)

5 (41.7%)

7 (58.3%)

8 (66.7%)

8 (66.7%)

5 (41.7%)

3 (27.3%)

6 (50.0%)

6 (50.0%)

56 (43.4%)

Pearson Chi-Square Symmetrical Value

𝑥2 = 17.431, df = 10, p = 0.065 ---

1 IV refers to independent variables, and DV refers to the dependent variable.

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5.1.12. Depth of Taphonomic Surface Change

During the analysis of a thin-sectioned experimental bone, it became clear that

the change in bone colour is superficial, in that it was only retained on the uppermost

layer of exposed bone. In one of the five concurrent experiments to the main surface

analysis of bone, a sample that was submerged for twelve months in Cage B, Location B

was thin-sectioned into as many slides as possible for histological examination. The

result was six slides of varying thickness, that were then mounted and observed under a

modular microscope. The surface cut that is typically used to level the sample was made

to be as thin as possible, as to retain as much information and material allowed by this

destructive process. The blade thickness (260 µ) results in material lost during the

process of sectioning.

Based on the thin-sectioning of bones, it appears that the selective staining and

the presence of green staining of existing vascular structures can reach a depth of more

than 2103.6 µ (2.103 mm) from the surface, whereas the bone colour (ranked as 4 =

Brown) was quickly lost as the subsequent sections below the surface revealed white

bone colour (0 = White). This finding renders the change in bone colour as a superficial

feature that may be easily lost. This also suggests that some taphonomic changes can

impact bone deep below the surface, but signs of this type of decomposition can only be

evaluated histologically.

5.2. Results involving non-skeletal materials

This multi-faceted research project involves the examination of secondary data

sources and the collection of non-skeletal data; these of which include the (1) elemental

profiles of silt samples, (2) temperature and precipitation data throughout the duration of

the experiment, and (3) water pH (acidity) at Marion Lake.

5.2.1. Elemental Profiling of Silt Samples

Elemental analysis of silt samples from deep water, head water, and swamp

water from bottom of the lake floor were conducted. All silt samples consisted primarily

of carbon, oxygen, and silicon (Figure 5.5). Trace amounts (ppm) of iron, sodium,

bromine, sulfur, magnesium and calcium were also detected but their amounts varied

81

dramatically between each sample and even between different areas of a single pin. The

detection of aluminum and high counts of carbon is probably due to the way the samples

were mounted, whereby aluminum pins are used as a stadium, and the carbon tape as a

means of securing the sample that can also maintain conductivity for scanning electron

microscopy. The Au sputtered side was used primarily for imaging purposes for future

analyses. Although elemental analysis of both the untreated and treated sides were

taken, the averages presented below are measured from the non-treated (natural, not

sputtered) side of the sample.

Figure 5.5. EDAX spectrum (elemental profle) of the swamp silt sample (ppm), as an example of typical SPC (.spc file extension) format output.

5.2.2. Temperature and Precipitation

The atmospheric temperature, humidity and rainfall data were collected from the

on-site Haney UBC RF Admin weather station at the University of British Columbia’s

Malcolm Knapp Research Forest (49.155210 N, -122.342340 W), which is less than 7

km from Marion Lake (49.309694 N, - 122.547984 W). These data are monitored and

provided by the Environment Canada’s Historical Data Centre. The elevation of the

weather station is 147.00 m above sea water, which is 67.7 m lower than Marion Lake’s

82

elevation of 214.7 m. To account for this difference, the surface temperature of the lake

was taken, along with temperature measurements two metres below the surface of the

floating dock.

As mentioned previously in the methods and materials chapter, lake temperature

data are not available for the month of deployment (March 2016) and the first recovery

(April 2016). No readings below zero degrees were also collected (December 2016 to

March 2017) because no ice was broken when the lake was frozen to retrieve

measurements due to the health and safety hazards that the temperature surveying

process would serve under such circumstances. The dock, platform, and surface of the

lake were completely obscured from a (conservative) estimate of more than 50 cm of

snow. It is for this reason that the field team did not access the lake. Both handheld

thermometers broke during the months of June 2017 and July 2017, which included the

new thermometers that were purchased for the last recovery.

As compared to the surface of the lake, the temperature of the water below the

dock was found to be cooler throughout the year, with more substantial differences being

seen during the summer months than during Fall, Spring, or Winter (average of 1 oC

difference with a range from 0.5 to 4 oC difference) (Figure 5.6). This is likely due to the

impact of direct sunlight that has a warming effect on the lake surface. Because the

temperatures taken during recoveries is not reflective of the year-long temperature

trends, a second line chart has been provided to show temperature changes from

January 2016 to September 2017 (when the experiment took place) (Figure 5.7).

The total rainfall throughout the experiment varied by season, expectantly lower

during the summer seasons and higher throughout the end of winter and during spring

(Figure 5.8). This analysis is based on more than 639 days’ worth of data, totaling 1917

data points (measurements) that was initially collected from the Environment Canada’s

Past Weather and Climate Historical Data Centre. The specific weather station that

collected this information is at UBC Malcolm Knapp, named the Haney UBC RF Admin

station.

Figure 5.6. Line chart depicting the mean (atmospheric) temperature, lake surface temperature, and lake temperature 2m below the dock in celsius (oC) between March 2016 to July 2017.

18

24

12

15

11

8

6

0 0 0 0

8

14.5

16

23

11

14.5

10

8

5.5

0 0 0 0

5

10.5

8.8

14.3 14.5

21.5

14

18

13.5

11.510.8

-3

-4.5

3.34

9

11.5

14.5

20.3

-10

-5

0

5

10

15

20

25

30Te

mp

erat

ure

(oC

)

Calendar Date (month/day/year)

Lake Surface (°C) 2m Below Dock (°C) Mean Temp (°C)

84

Figure 5.7. Line chart depicting the temperature trends from January 2016 to September 2017. The blue line represents the maximum atmospheric temperature, the grey line represents the mean atmospheric temperature, and the orange line represents the minimum atmospheric temperature. This analysis is based on more than 639 days worth of data (1917 data points) was collected from the Government of Canada’s Past Weather and Climate - Historical Data Centre.

80

Figure 5.8. Line chart depicting the total daily rain fall from March 2016 to July 2017 (duration of the experiment).

5.2.3. Water pH

The readings from a VWR SB80PI SympHony pH/ISE Meter of several water

samples from Marion Lake were examined for water acidity. As a control, the pH

readings of the storage solution and distilled water were also taken and the results were

within the range of what is expected. No recalibration of the instrument was deemed

necessary based on these readings. The storage solution had a pH of 6.25, distilled

water had a pH of 6.71, sample 1 (head water, near Site I) had a pH of 6.04, sample 2

(deep water, west side of the lake) had a pH of 5.39, sample 3 (deep water, centre of the

lake) had a pH of 5.21, sample 4 (shallow swamp water, near site J) had a pH of 5.15,

and sample 5 (centre of the lake, near Site G) had a pH of 4.78 (Figure 5.5). The

measurement of water acidity all took place during the same day, with the probe being

cleaned between each reading.

81

Figure 5.9. Illustrative map of the water pH by location across Marion Lake, along with silt sample extraction locations (adapted from UBC MKRF and Efford, 1967).

82

Chapter 6. Discussion

Much of the existing literature focuses on skeletal decomposition within terrestrial

environments because the study of archaeological specimens far predates that of

contemporary forensic anthropology and bioarchaeology in aquatic environments. There

are few studies that examine submergence effects on bones, particularly the

examination of structural changes in waterlogged samples at the macroscopic surface

and microscopic level. The goal of this experimental lacustrine taphonomic project was

to investigate how skeletal material may be structurally affected when submerged in a

freshwater lake within the Pacific Coastal Western Hemlock Zone (WHZ). This study was

conducted in a single lake system, chosen because existing ecological studies

supported by UBC Malcolm Knapp Research Forest have suggested that Marion Lake is

a suitable proxy due to its similarity to other lakes within the WHZ. The need for localized

studies underscore the importance of this research.

When this research began, little was known regarding what type of taphonomic

change may take place. Without an existing baseline of structural skeletal change known

for lacustrine environments within the Pacific West Coast, the coding for changes

observed had to be approached inductively. Open coding meant that the analysis of

bones had to be completed multiple times for every new variable that was introduced.

The nomenclature of such decompositional changes has also undergone changes as

new information arises. In particular, what appeared as pitting under light microscopy

was revealed to be the selective vascular staining and loss of organic tissue to reveal

naturally occurring cutting cones. The loss of organic materials in experimental samples

and not control samples suggests that this is a non-structural post-mortem change that

was mistaken for post-mortem structural change. Examples like these emphasize the

importance of pursuing histological analyses.

6.1. Lacustrine Skeletal Taphonomy

This discussion that follows centers around the changes observed in skeletal

materials. Because immature Ovis aries (domestic sheep) skeletal samples were used

83

(see section 4.2.1. Sample Selection for more information), the extracellular rigid matrix

in developing bones is very fibrous and less compact than in adult bones. This lowered

robusticity has the potential to make sub-adult skeletal remains more vulnerable to

change, and for existing vascular structures to be mistaken for bacterially induced

microboring. Regarding the effects of the study protocol decisions, the process of

sectioning the bone into discs, as opposed to submerging an entire shaft, creates more

surface area for which microbial growth may adhere. Bivariate results also suggest that

the variation in bone disc dimensions and weight is not statistically related to the

appearance of taphonomic change.

6.1.1. Control Specimens

As per the research protocol and to ensure that changes in bones are not

naturally occurring phenomenon, the documentation of taphonomic change in O. aries

samples began with a macroscopic examination of the control samples. At the beginning

of the research, all samples were examined under a light microscope. At the end of the

experiment, the control samples were re-examined to see if they had undergone any of

the changes seen in experimental samples. Results showed that there was no change

observed amongst the control samples when comparing them before the initial

deployment to when they were analyzed after all the samples were recovered. The

process of being stored in a freezer did not appear to have an effect on the bones, and

none of the taphonomic changes observed in experimental bones were seen in the

controls. An additional survey of surface topography months after the sample was

removed from the fridge and placed into room-temperature storage revealed no changes

in the bones pre- and post-deployment.

6.1.2. Pre-deployment Artefact Loss

The process of cutting long bones with a butcher’s meat band saw will invariably

create marks due to serrated blades leaving prominent lines across the cut surface of

bone – marks that can help identify the instrument that caused this change using kerf

mark analysis (Thompson & Inglis, 2009). The process of cutting bone also pushes

excess skeletal material to the side where the blade exits (finishes the cut), which

creates bony lipping. These distinct features are not naturally occurring, making them a

type of artefact that is introduced by humans. In this research, finding artefacts on bones

84

is expected, given how the bone discs were made from sectioning O. aries femoral

shafts. In criminal investigations, the appearance of artefacts in recovered bone can

suggest human interference and/or intentional severance of parts of the body. The

implications of finding artefacts becomes an important feature that can suggest foul play,

which is why the loss of pre-deployment artefact loss holds great significance.

The initial hypothesis was that submergence periods would not impact artefacts

due to the prominent structural morphological change that they have caused on the

surface of bones. The results of this study ran contrary to this belief, as the obfuscation

of artefacts was seen starting from the third recovery (94 days of submergence). The

location where the sample was submerged, the number of days the sample was

exposed to the lake, and whether the sample had been submerged when the lake froze

over were all found to have a statistically significant relationship with the loss of pre-

deployment artefacts. However, the effect of these environmental conditions were weak

indicators of change, aside from the days elapsed that showed a very strong negative

effect whereby the second mean (those without artefacts) is larger than the first.

These findings suggest that all samples will eventually lose their bony lipping and

nearly half of all the samples (n = 10 per recovery) may lose their saw marks once

submerged for 127 days or longer. This may have a significant impact on the ability of

investigators to be able to distinguish whether recovered bones had been butchered

using man-made tools prior to discovery. There are more sensitive microscopic

instruments that may be able to see finite topographical alterations to the bone from saw

marks, but it is very possible that even under higher magnification, these features may

be indistinguishable due to complete removal.

6.1.3. Post-depositional Selective Staining of Vascular Structures

Macroscopic analysis of skeletal remains has been a staple approach to

documenting skeletal change, and the application of microscopic techniques over the

past two decades has also helped better document and quantify skeletal modifications.

This research demonstrates how even with the utmost care in the surface documentation

of change, the nature of these features may be hard to detect under low magnification.

As a result of pursuing microscopic analysis by thin-sectioning the bone discs, what was

initially identified as pitting (suspected macroboring from a combination of bacterial

85

and/or fungus) was found to be the (1) loss of organic soft tissue within existing vascular

Haversian and Volkmann canals, (2) staining of the crenulated perimeter of bone

remodelling and/or growth, and (3) no exaggerated holes were found to be independent

of vascular or cell networks.

No cutting cones were observed on the control samples or samples recovered

during the first recovery (34 days of submergence). Upon the second recovery (66 days

of submergence), eight of the ten samples showed signs of cutting cones. By the fifth

recovery (155 days of submergence) and onwards, every sample exhibited this feature,

the only difference being the number of cutting cones made visible under light

microscopy. The location of where the lacustrine samples were submerged is found to

be statistically related to the appearance of cutting cone features and is found to have a

strong effect on the frequency of their appearance. The number of days the samples

were submerged and their exposure to winter lake freeze was found to be related, but

negligible due to its low effect size. Andrade et al. (2008) found that freezing would

cause cell and nuclei enlargement whereby osteocytes would become obscured, so

even if the impact of effect size was small, this change may have had a big impact on

the overall appearance of this feature.

The range of staining observed in this study have not been reported in studies for

marine environments. Compared with ancient lakeshore environments, the distribution of

selective staining at Marion Lake (Figure 5.9) and that of microboring on bone surface at

Cerro de la Garita were both not histologically-oriented and highly concentrated on the

outer surface of bone (Pasquero et al., 2010). It is unclear if selective staining was seen

in the Spanish samples, as their type of taphonomic alteration covered a vast surface

and appeared highly concentrated. The size and distribution of micro-tunneling in the

continental lake sample did show an outer rim that was not seen in marine bacterial

microboring (Bell & Elkerton, 2008; Pasquero et al., 2010).

6.1.4. Abrasion Coastal Lake Systems and Geology

Abrasion is one of the taphonomic features often associated with aquatic

environments. Haglund (1993) argued that abrasive modification of skeletal material can

be attributed to a combination of dissolution, current-drive bioerosion, and being dragged

in sediment that causes the bones to rub or strike against water-suspended debris.

86

Amongst all the samples from Marion Lake (n=129), 88 (68.2%) showed varying levels

of abrasion on the periosteal surface, and none of the controls showed any signs of

abrasion throughout the experiment. The loss of pre-deployment saw marks on the

transverse cross-sectional plane could very well be due to abrasion, but further analysis

would be required to substantiate this hypothesis.

When examining the abraded topography of the periosteal surface, it was very

clear that this process was also damaging the structural integrity of this outer bone layer.

In many cases, large sections of the periosteum had been removed entirely (Figure

5.11). When this occurred, existing vascular structures were exposed. Given that

samples are of subadult O. aries, it is also possible that the looser matrix of growing

bone in juveniles will result in quicker or easier loss of this outer layer, as compared with

that of adult bones. These findings are consistent with Delabarde et al.’s (2013) forensic

case analysis of recovered remains from a freshwater riverine environment in France. In

their study, they found that the sacrum exhibited extensive abrasion damage, resulting in

exposure of trabecular tissue. Despite extensive scavenging activity on the bones, signs

of abrasion were still identifiable.

The boundaries of this type of bone loss is also very distinctive (Figure 5.12),

where the surface appears to be abraded until the surface layer fractures, then these

loosened pieces appeared to have disarticulated from the sample. This distinctive

boundary appears similar to the taphonomic alterations expected of samples that have

been exposed terrestrially (Pokines, 2016). This distinctively darkened area resembles

the irregular soil staining of samples that have had direct contact with soil surfaces, as

documented macroscopically (Pokines, 2016).

Abrasion is likely to occur where there is an active current (Haglund, 1993).

Although this may be true, recent studies have found that grain size and angularity of

sediments are better predictors of micro-abrasion rates than the frequency at which O.

aries femoral shafts are bombarded by sediments when submerged in a flume (Griffith et

al., 2016). Results of their regressions also show that the abrasive capabilities of coarser

grains can cause pitting and cracking on the periosteal surface, and that the

quantification of abrasion can be used to determine submersion periods and transport

pathways based on silt or other sedimentary composition in aquatic contexts (Griffith et

al., 2016).

87

The location of submergence at Marion Lake was found to be related to the

presence of abrasion, but this association was found to be weak. Should a detailed

analysis be conducted of sediment morphology at each location, perhaps the rate of

abrasion and amount of surface abraded can be delineated from environmental

contexts. When considering the movement of cages, sites near the dock (B, C, D, E) and

in the marshland area (J) exhibited short distances travelled but this did not impact the

onset of abrasion.

The length of the submergence period was found to be highly related to the

presence of abrasion. Exposure to winter lake freeze was also related but the effect it

had on the appearance of abrasion is negligible. Controlled experiments have also

examined the conditions of maximum wear and abrasion. Although these studies do not

represent changes that occur in natural settings, the data generated can help develop a

better understanding of rate of diagenetic change to bone based on the hydrodynamic

and morphological properties of sediment grains (Griffith & Thompson, 2017). Their

classification of abrasive wear on skeletal tissue is consistent with what has been seen

in this study, and by examining the morphological structure of the silt samples, perhaps

submergence periods may be able to be predicted based on the gross amount of

material changes seen on bone surface.

6.1.5. Cracking along the Periosteum and Transverse Cross-sectional Block Face

Regarding cracking seen on the periosteum, bivariate analyses showed that the

location of where the sample was submerged is not related to cracking. Conversely,

location was found to be related to cracking observed on the transverse cross-sectional

block face, but its effect is so small that it is negligible. For the presence of cracks on all

surfaces, a strong association is found between the presence of cracking and the days

the sample spent submerged. Surprisingly, there was also no relationship found

between the presence of cracking on either surface and the exposure to lake freeze.

This is likely due to how many samples had exhibited cracking by that point.

No distinction between the types of cracking observed was made due to low

magnification examination, but a thin-section of experimental bone was explored to

develop a better understanding of the structural changes happening microscopically.

88

This secondary microscopic analysis revealed that many of the cracks observed from the

transverse plane include osteonal cracks, cracks that follow along lamellar alignment,

cracks that protrude from the periosteal surface towards the center of the bone, as well

as cracks that follow the boundary between periosteal bone and cortical bone.

The appearance of microcracks resemble ones that have been found in other

studies, both within a controlled freshwater submergence and marine submergence

context. Multiple longitudinal cracks along the periosteum were found in an experiment in

which 93 deer metapodials (long bones and feet) were submerged in distilled water, then

exposed to freeze-thaw conditions (Pokines et al., 2016). They found that freeze-thaw

cycles may be inhibited by vegetation or snowfall that can serve to insulate skeletal

materials, but osteonal and transverse cracks like those from Marion Lake were

observed when bone was observed under higher magnification. Another study found that

there were no differences in the number of cracks observed between samples exposed

to dry/freeze-thaw cycles, freshwater, or salt water (Turpin, 2017).

Osteonal cracks were not observed in Turpin’s (2017) aqueous submergence

experiments, where as samples from Marion Lake did show signs of this type of

cracking. Similar microcracking and fissures have been observed in several studies of

marine taphonomic alterations to bone, including osteonal and transverse cracks similar

to those found in this dissertation research (Bell & Elkerton, 2008; Pelkier et al., 1984;

Tersigni, 2007). Based on these findings, the presence of cracking appears to only

suggest aqueous submergence, and not the aquatic context from which it is found. The

types of cracking in combination with other taphonomic features may, however, be able

to indicate where samples have been submerged.

6.1.6. Surface Bone Colour Change and Surface Staining from External Agents

Upon first glance, the bones sustained colour changes when recovered from the

water. After lightly rinsing the sample of mud and debris (completed within a couple of

hours of the recovery), the samples would lighten in colour from being dried under a

hood vent. The darker colour of the bone was thought to lighten with time, but even

months after being stored in a cool (room temperature) and dry environment, their

original colour was maintained. The exceptions to this are the samples that exhibited a

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lot of blue and green staining, in which case, the bones turned a score darker than those

that did not (ex. from beige to beige-brown).

Results show that there is a weak relationship between the observed bone colour

changes (from beige to brown) based on the location of submergence and whether or

not the bones have been exposed to winter lake freeze. Submergence periods have a

moderate effect, which suggests that time plays a minimal role in determining whether

the surface of the bone will change in colour. Although not examined directly in this

research, soil formation has been found to be a good indicator of skeletal colour change

based on mineral absorption (Dent et al. 2004). Marine-submerged samples have

appeared blackened, but this colour is lost within a week of oxidation in room

temperature (Bell, 2016). Cockle and Bell (2017), Estevez et al. (2014), Janjua and

Rogers (2008) and Parker et al. (2010), have all observed similar changes in bone

colour, but these studies (like many others) were conducted terrestrially.

Similar to the selective dark brown staining observed around existing vascular

structures, the endosteal border of the bone discs were darkened when sectioned.

Macroscopic analysis did not show this feature because there was often a white chalky

substance (suspected to be the saponification of fatty tissues) or biological growth (plant

material) obscuring the view. This staining may suggest bacterial invasion, as seen in

marine-submerged samples (Bell & Elkerton, 2008).

6.1.7. Encrustation and External Deposits

Three types of encrustation were found on the surface of the bone during

macroscopic examination: blue staining, green staining, and black surface deposits.

Because the nature of the blue and green staining differs morphologically from that of

black surface deposits, they will be addressed separately. Regarding the presence of

blue and green staining, it was found that the impact of location was significant but weak

in general. In contrast, submergence periods were found to be a strong indicator of

staining presence and green staining, but not blue staining. Exposure to lake freeze was

found to have very little to do with the presence of staining overall.

Two qualitative findings were made during an examination of samples six months

after the samples were first recovered and analyzed. Firstly, the vibrant colours seen

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when the sample was dried had turned brown. This suggests that the external staining

may be due to organic agents that died in the laboratory, where the samples were

stored. This is consistent with the hypothesis that staining presence may be due to living

organisms, whether it be algae, complex microbial communities, or other naturally

occurring agents in freshwater lakes. Without further analysis and use of microbiological

tools and DNA sequencing, no identification of these stains can be made with certainty.

Secondly, the thin-sectioned samples show that the presence of green stains were

pervasive enough to travel through existing vascular structures deep into the bone,

suggesting there was colour absorption by intact paternal systems. This taphonomic

feature only occupied existing Haversian canals, Volkmann’s canals and osteocytes. No

sample with blue stain presence was thin-sectioned to explore whether the same

phenomenon can be seen in both types of staining.

The black surface deposits were found on bone samples and remained on the

surface of the bone, even after the sample was lightly rinsed post-recovery. The deposits

exhibited lustre and reflected light, which suggests that it may have been a crystalline

structure that is geological in nature. Future analyses of bone samples may include

elemental classification of these black deposits. Although these deposits adhered to the

bone post-recovery, they were found to move if agitated with forceps. The petri-dish

used to house samples during surface analysis were cleaned between each sample

during every stage of the analysis as a means to control for contamination. The

presence of these deposits was not found to be associated with the location of cage

sites, submergence periods, or with winter lake freeze. Their appearance may be tied to

other geological features that have not been captured by the environmental monitoring

pursued in this research. In a study of bioerosion in lakeshore environments from 1997

to 2003, Pesquero et al. (2010) detected the microspheres deposited deep inside

microtunnels using scanning electron microscopy (SEM). Mineral redeposits were found,

and it is possible that these iron-rich microspheres may be similar to that which is being

detected as black deposits in this study.

6.2. Conducting Experimental Research – Lessons from the field

The recovery protocol used for this experiment served its purpose, but there were

a couple of areas that could be improved. Of the three cage markers used, the letters (A

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to J) cut out of plastic were the most effective because the letter was not obscured or

stained from biological growth. The plastic vegetable toys retained their colour and

shape, but silt, mud, and plant growth made them difficult to identify. The letter written on

buoys also faded and were hard to read. All three methods proved useful in varying

amounts, and overall, there were no issues regarding the proper identification of cages.

The milk jug buoys also worked well, and the glue gun seal remained intact throughout

the entire experiment. The double figure eight knot on the fishing wire that tethered the

bone discs to the cage loosened over time, but the e-stopper knot kept the loose ends

from unravelling.

The rocks used to ensure that the cage would not float did not seem to have any

effect on the amount of movement of the cage. They were used to weigh the cages, as

to simulate the weight of severed long bones enough to allow for the natural drift and

subsurface movements expected but not so much as to bury the sample. The goal of

using a row boat instead of a motorized boat was to cause as little disturbance to wildlife

and the lake floor sediment deposits as possible. This appeared to have worked

because small fish, salamanders, and other small creatures were not scared off as the

boat skimmed above them. An issue encountered in the field was when the lake’s water

levels were so low that the boat could not reach the swamp bank without touching the

lake floor. Upon discovering this problem, a large pole was fashioned into an extendable

hook to enable the retrieval of cages from the boat without disturbing the freshwater

clam garden at Marion Lake’s swampy area.

A single cage would not be disturbed for more than two minutes each month, but

each recovery did require the cage to be lifted from the soil and shellfish midden it was

situated in. The cages were on the lake bed, but the samples themselves were likely

suspended. On recovery days where the water was clear enough that the cage was

visible from the boat, the samples appeared to be suspended above the cage. Starting

from the fourth recovery, cages were often found completely covered by silt, and it is

unknown whether the sample was buried in the silt or not. Without the buoy tether, the

cages were almost always unrecognizable to the naked eye. An average of three and a

half hours per recovery was spent on the water in ideal weather conditions, which

tended to double when there was heavy rain, wind, or snow. Because the energy of the

water was observably high during ice melt and throughout the summer, the cages were

likely pulled by the current of the water to areas with less energy. It is also suspected

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that the buoys may have acted as sails and have caused the cages to move; it is the

author’s belief that this movement was marginal, because the buoys remained in the

same area for the remainder of the study after the first month’s migration.

6.3. Monitoring Environmental Conditions

Several concurrent processes were conducted to monitor the environmental

conditions of Marion Lake, along with the collection of pertinent climate data from the

University of British Columbia’s weather station (Haney UBC RF Admin Station; climate

ID #1103332) and Environment Canada’s Past Weather and Climate’s Historical Data

Centre. By monitoring and disclosing the environmental conditions at Marion Lake and

its surrounding area, this research can uphold standards of transparency regarding the

level of generalizability of results. Not all lakes may exhibit the same differences in soil

composition, water acidity, or climate, so readers may draw their own inferences and

decide what variability is of an acceptable range when comparing these findings to their

own taphonomic experiments. As mentioned in the literature review, many remote lakes

within temperate rainforests exhibit several similarities in the type of flora, fauna, and

lake bed mineral composition, which allows for some cautious generalizations to be

made for studies that take place in these types of lacustrine environments.

6.3.1. Lake Floor Composition

Ian E. Efford (1967) spent decades documenting the wildlife at University of

British Columbia’s Malcolm Knapp Research Forest, along with the geological and

ecological characteristics of Marion Lake. Elemental analysis findings show a consistent

primary composition of carbon, oxygen, and silicon, with trace amounts of iron, sodium,

bromine, sulfur, magnesium, and calcium (ppm). This silt composition is consistent with

Efford’s findings (1967), as well as earlier works from Roddick and Armstrong (1959) on

the geography of coast mountains near Vancouver, British Columbia. More recent

geochemical surveys of lakes in coastal British Columbia (2008 – 2015) have found that

mainland lakes within this coastal region exhibit less sedimentary and volcanic rocks and

more intrusive and metamorphic rocks (Gibson et al., 2018, p. 61 – 62).

Researchers estimated that 85% of the entire mountainous area is underlain with

plutonic rocks (hornblende diorite) to more common intermediate igneous rock types like

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biotite granite (Roddick & Armstrong, 1959, p.603). Given that hornblende is rich in

different combinations of calcium-iron-magnesium silicates, aluminum-iron-magnesium

silicate, and an iron-magnesium silicate, the lake floor is the most likely contributor to

these trace elements found in the silt sample. The silt collected from the bottom of the

lake were surface samples that are effectively suspended in water, and the collection

period took place in April and May, when microbial productivity and reproduction is made

possible due to warming temperatures in the lake (Efford, 1967; Kirchman, 2011a;

Kirchman, 2011b).

6.3.2. Temperature and Precipitation Fluctuations

In Efford’s (1967) observations of the productivity of macrophytes in Marion Lake

and surrounding lake systems, he discovered that there is a relationship between

microbial productivity and the lake temperature, but not between productivity and the

availability of sunlight (p. 2283). Based on a comparison between historical and

contemporary maps of Marion Lake, it appears that little has changed the geological

formation and treelines within the experiment field site. Marion Lake still does not have

foliage cover, which means that there is an abundance of direct sunlight exposed to the

lake. This direct sunlight may not impact the level of microbial activity in the lake but may

have an indirect effect because of the role it plays in raising the water temperature.

When comparing the highest and lowest daily atmospheric temperature (Figure

5.3), clear extremes can be seen within weather data, which is expected of coastal

mountain lakes. The mean atmospheric temperature was approximately two degrees

lower than the lake temperature (both surface and 2m below the dock) throughout

spring, but approximately three degrees higher from August to November. The

temperature on the lake core and surface could not be measured safely during the four

months when the lake froze over, which is why the lake temperature plateaus at zero

during those four months. This documented lake temperature is within the conservative

range of -60 oC and 100 oC that microbes require to survive (Kirchman, 2011a).

The frequency of rainfall along British Columbia’s coast is consistent throughout

the year, with higher amounts of precipitation from October to April, and extreme lows

(less than 10 mm) during June, July, and August (Figure 5.4). The amount of rainfall

during May and September has been very different over the past three years and will

94

probably continue to fluctuate due to changes in global warming, similar to other lakes

within the Western Hemlock Zone (Rayne & Forest, 2016; Smith, 2016). Rainfall is an

important consideration because it will impact the lake volume, temperature, and current

energy.

Precipitation has also been considered in terrestrial studies. Cockle and Bell

(2017) found that precipitation did not have a significant impact on the rate of

decomposition, based on a systematic review of homicide cases (n = 7328). Should

remains be exposed in a transitional environment, the effects of terrestrial weathering

may still be found on submerged remains. No sequencing of microbial communities was

pursued, but one can infer that microbial activity did occur in the lake either nearby or on

the samples. Without pursuing further examinations of the bacterial cultures found on

bones, little can be said regarding the impact that temperature and precipitation has

played on the observed taphonomic changes.

6.3.3. Lake Acidity Gradient

In Kirchman’s (2011a) study, he found that the Western Hemlock Zone lakes

tend to be neutral pH or mildly acidic. Results of Marion Lake’s water pH test suggests

that a gradient of acidity exists, where the northernmost region of Marion Lake has the

most alkaline signature and the level of acidity rises the more south the water travels

(Figure 5.5). The northern most sample had a signature of 6.04 pH, which is expected of

freshwater lakes. In a geochemical survey of 560 lakes in British Columbia, including

Marion Lake, researchers found that hydrological processes that impact water balance,

physical and chemical properties have a direct impact on the level of acidity within a lake

(Gibson et al., 2018).

Knowing the lake water acidity is important because it has as much of an impact

on the health and growth of microbes as temperature (Kirchman, 2011a). Because the

water column does not have the same solids as soil, the distance between bacteria can

be quite far (60 µm, as opposed to 10 µm) (p. 46). This physical distance between

bacteria was found to hinder their ability to communicate with each other, and thus,

lower concentrations mean less activity and less acidity produced by bacteria (Kirchman,

2011a, p. 46; Yooseph et al., 2010). Less bacterial productivity may impact the onset of

taphonomic changes in skeletal material. Microbial activity was not directly assessed in

95

this dissertation study, but it is suspected of being the cause of selective vascular

staining.

6.3.4. The Impact of Wildlife

None of the wildlife encountered during this experiment were unexpected. The

only surprise was the number of fish and frog eggs deposited in the cage (some of which

appeared to make direct contact with the bones), and how the deer were bold enough to

walk directly into the research site at Marion Lake. None of the equipment or gear were

taken by scavengers, and the research team were not endangered during this

experiment. On two occasions, a bear was seen in the distance, but walked into the

forest before the author could take photographs. There have also been wolf sightings

from other research teams, but this research team never encountered any. It is unclear

how the presence of eggs laid within the cages can impact taphonomic changes, but this

is certainly an area of interest and DNA testing may be pursued in the future.

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Chapter 7. Conclusion and Future Research

The findings from this dissertation’s six concurrent analyses of bone taphonomy

and complimentary studies of Marion Lake ecology provide insight into what

decompositional changes can be expected from lacustrine submergence, specific to

freshwater lakes within the Pacific Coastal region of the Western Hemlock Zone. The

goal of this research was to develop a baseline of taphonomic signifiers that can help

delineate submergence location, elapsed time since water entry, seasonality from

exposure effects, and to be used in future comparisons with other submergence

contexts. Instead of accepting what is known about these hydrodynamic systems based

on existing biogeoclimatic ecosystem classifications, this study also monitored Marion

Lake because it is necessary to recognize that climate change is reshaping the

distinctions and boundaries between zones (Haeussler, 2011). This interdisciplinary

research involved the construction of a satellite research camp site at University of

British Columbia’s Malcolm Knapp Research Forest (UBC MKRF) for sixteen months of

data collection. Macroscopic and microscopic analyses of sectioned Ovis aries (domestic

sheep) femoral diaphyses were performed at Simon Fraser University’s (SFU) Centre for

Forensic Research, and elemental analysis of silt composition was conducted at the

SFU Nano-imaging and Holography Laboratory.

The primary research question sought to discern whether any taphonomic

changes would occur to lacustrine submerged cortical bone tissue. Results of this study

reject the null hypothesis and make it clear that decompositional changes have

occurred, some of which appearing after as little as two months of submergence.

Secondary questions about generalizability, consistency of remodelling appearance, and

the relationship of taphonomic signifiers to environmental conditions were also answered

in this study. The taphonomic signifiers observed can be summarized as a combination

of artefact loss (bony lipping and saw marks), structural damage (abrasion and

cracking), vascular network exposure (loss of organic tissue and selective staining of

cutting cones), bone colour change, and encrustation (black deposits and green/blue

staining).

97

Results suggest that after four months of submergence or longer, bone lipping

and saw marks on the cut surface of bone become undetectable under macroscopic

examination. This was an unexpected incidental finding, as no previous literature on the

loss of artefacts in lacustrine submerged remains was encountered during the literature

review. The loss of pre-deployment artefacts is of great criminal justice importance

because it suggests that the common signs used to determine intentional human-

induced dismemberment using a mechanical blade may be indistinguishable after a

certain period of submergence. This feature is only visible on cut surfaces, so

exploration of non-destructive methods of microtopographic visualization will be pursued

to further support this finding.

Periosteal abrasion was documented in many samples and was found to be

highly related to the length of the submergence period. This suggests that the longer the

sample stayed underwater, the more abrasive wear took place due to the natural

hydrodynamic characteristics of a mountainous coastal lake. Sediment would

theoretically strike the bone indiscriminately, so although no signs of abrasion were seen

on the transverse cross-sectional block face, it is also possible that this form of

weathering and smoothing of surfaces has contributed to the loss of pre-deployment

artefacts. Trauma to the periosteal surface has caused parts of the periosteum to

separate from the mesosteal zone of the cortical bone disc. The appearance of abrasion

in these samples support other intertidal and lacustrine studies in suggesting that

abrasion may be a diagnostic feature of aquatic submergence, as opposed to

terrestrially exposed remains. In the future, better methods for the quantification of the

percentage and extent of periosteum damage may help signify lake characteristics, such

as the energy of the water run-off, sediment class, and seasonality. Inspired by Griffith

and Thompson’s (2017), another possible avenue for the visualization and quantification

of abrasion in these samples could involve laser scanning. It would also be beneficial to

capture underwater videography of the samples to see if they had any interaction with

the cages to which they were tethered.

Where samples were placed across Marion Lake had no effect on whether

cracking would occur. Instead, the length of time a sample was submerged was yet

again the most important factor in determining whether cracking on both the periosteum

and transverse block face would take place. It was hypothesized that cracking would

follow weaker boundaries of existing lamellar alignment, but findings show that cracks

98

were protruding from the periosteal surface inwards, as well as radiating outwards from

cutting cones. These forms of cracking have been documented in previous studies

involving marine submerged samples, but the type of periosteal cracking observed in this

research has not been seen in other aquatic studies. Without closer examination through

microscopic videography as these effects take place, no causal effects can be

delineated.

Based on the existing literature on bioerosional effects like microboring (pitting),

similar effects were hypothesized to occur. Using light microscopy, the macrostructural

examination of the cross-sectional transverse block face showed large, scattered

groupings of holes that resembled pitting. They were not seen in the control samples

and appeared highly irregular, especially given the large dark rings that outlined their

borders. Histological analyses revealed that these holes were not created by external

agents, but instead, was a combination of effects and conditions that made naturally

occurring cutting cones visible under low magnification; these changes include irregular

and selective staining around the areas where loss of organic tissue took place. The

likelihood that the use of subadult bone may have also resulted in larger and less dense

osteons in samples that contributed towards this form of decompositional change being

misclassified.

These findings on vascularity are of great importance to the field of freshwater

taphonomy because it calls other macroscopic findings into question. Sectioning the

bone did result in a loss of surface material where the most taphonomic change is likely

to have occurred, but this method did provide insights as to the true nature of how these

holes are exaggeration of naturally occurring cutting cones rather than bacterially

induced microboring. Other experimental samples will be sectioned in later studies to

quantify these changes, and perhaps other methods may be pursued to identify

decompositional changes on the outer most surfaces of these bone discs.

The surface of the bone had also changed colours, but sectioning of samples

revealed that this colour change is largely superficial. From white to brown, the gradient

of colours observed was found to have a weak relationship with submergence location

and submergence period had only a moderate effect. The appearance of bone colour

change would appear like a gradient in some samples, but there were a select number

of samples that had very sharp boundaries between the colours. It is unclear as to what

99

could have caused this difference. Other studies have pointed to mineral absorption as

the likeliest cause of bone colour change, so the examination of soil staining of

submerged bones is another area that can be further explored. It would be interesting to

compare the colour changes based on time and the chemical constituency of the

sediment the sample would be suspended in. These findings hold great significance

because they may be able to suggest the geolocation of their deployment. The same

can be said about the unidentified black deposits, and the blue and green staining

observed on bone.

Overall, the changes in microarchitecture of cortical bone tissue provided an

exciting new look into lacustrine taphonomy, and the many diagenetic changes observed

have prompted several new potential research avenues. Moreover, there were many

significant findings made during this research process. From a methodological

standpoint, macroscopic observations are necessary to observe surface changes that

may be lost with the sectioning of bone, but they should be pursued in tandem with

histological analyses because of their important role in discerning the true nature of

microscopic change. The validation of these findings through repeated studies should be

pursued so this baseline of distinguishable features may be used to aid death

investigators in determining the post-mortem journey of lacustrine submerged skeletal

remains.

100

References

Adams, B. J., & Crabtree, P. J. (2008). Comparative Skeletal Anatomy: A Photographic Atlas for Medical Examiners, Coroners, Forensic Anthropologists, and Archaeologists. USA: Humana Press.

Allen, M. R., & Burr, D. B. (2014). Bone Modelling and Remodelling. In D. B. Burr & M. R. Allen (Eds.), Basic and Applied Bone Biology, p. 75 - 90.

Anderson, G. S., Hobischak, N. R. (2002). Determination of time of death for humans discovered in saltwater using aquatic organism succession and decomposition rates. Canadian Police Research Centre, Technical Report, Ottawa, Ontario.

Anderson, G. S., & Bell, L. S. (2014). Deep coastal marine taphonomy: Investigation into carcass decomposition in the Saanich Inlet, British Columbia using a baited camera. PlosOne, 9(10), p. 1 – 25.

Anderson, G. S., VanLaerhoven, S. L. (1996). Initial studies on insect succession on carrion in southwestern British Columbia. Journal of Forensic Science, 41, p. 617 – 625.

Andronowski, J. M., Pratt, I. V., & Cooper, D. M. L. (2017). Occurrence of osteon banding in adult human cortical bone. American Journal of Physical Anthropology, 164(3), p. 635 – 642.

Arismendi, I., Johnson, S. L., Dunham, J. B., & Haggerty, R. (2013). Decriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America. Journal of Freshwater Biology, 58, p. 880 – 894.

Barros, M., & Wolff, M. (2011). Initial study of arthropods succession and pig carrion decomposition in two freshwater ecosystems in the Colombian Andes. Forensic Science International Journal, 212, p. 164 – 172.

Bell, L. S. (2007). Unique Marine Taphonomy in Human Skeletal Material Recovered from the Medieval Warship Mary Rose. International Journal of Osteoarchaeology, Published online in Wiley InterScience. DOI: 10.1002/oa.952.

Bell, L. S. (2012). Histotaphonomy. In Crowder, C., Staut, S. (editors) Bone histology. An anthropological perspective. CRC Press: Boca Raton, p. 241 – 251.

Bell, L. S. (2012). Forensic microscopy for skeletal tissues: Methods and protocols (edited by L. S. Bell). New York: Humana Press, Springer.

Bell, L. S. (2018). Personal Communications.

101

Bell, L. S. & Anderson G. S. (2016). The skeletal histotaphonomy of deep coastal marine submersion and exposure. Presented at the American Academy of Forensic Science’s annual conference at Las Vegas, United States of America.

Bell, L. S., & Elkerton, A. (2008). Unique marine taphonomy in human skeletal material recovered from the Medieval warship Mary Rose. International Journal of Osteoarchaeology, 18(5), p. 523 – 535.

Bell, L. S., & Jones, S. J. (1991). Macroscopic and microscopic evaluation of archaeological pathological bone: Backscattered electron imaging of putative pagetic bone. International Journal of Osteoarchaeology, 1(3-4), p. 179 – 184.

Bell, L. S., Kayser, M., & Jones, C. (2008). The mineralized osteocyte: A living fossil. American Journal of Physical Anthropology, 137, p. 449 – 456.

Bell, L. S., Skinner, M. F., Jones, S. J. (1996). The speed of post mortem change to the human skeleton and its taphonomic significance. Forensic Science International Journal, 82, p. 129 – 140.

Binford, L. R., & Bertram, J. B. (1977). Bone frequencies and attritional processes. For Theory Building in Archaeology, 1, p. 77 – 153.

Bristow, J., Simms, Z., & Randolph-Quinney, P. (2011). Chapter 9: Taphonomy. In S. Black & E. Ferguson (Eds.), Forensic Anthropology: 2000 to 2010, p. 279 – 317.

Brits, D., Steyn, M., & L’Abbe, E. N. (2014). A histomorphological analysis of human and non-human femora. International Journal of Legal Medicine, 128 (2), p. 369 – 377.

Brown, R. S., Hubert, W. A., & Daly, S. F. (2011). A primer on winter, ice, and fish: What fisheries biologists should know about winter ice processes and stream-dwelling fish. Journal of Fisheries, 36, p. 8 – 26.

Burr, D. B., & Akkus, O. (2014). Basic Bone Biology and Physiology. In D. B. Burr & M. R. Allen (Eds.), Basic and Applied Bone Biology, p. 3 – 25.

Bytheway, J. A., Connor, M., Dabbs, G. R., Johnston, C. A., & Sunkel, M. (2015). The ethics and best practices of human decomposition facilities in the United States. Journal of Forensic Science Policy and Management, 6(3-4), p. 59 – 68.

Cannings, S., Nelson, J., & Cannings, R. (2011). Geology of British Columbia: A Journey Through Time. Greystone Books Ltd.

Cardoso, H. F. V., Santos, A., Dias, R., Garcia, C., Pino, M., Sergio, C., & Magalhaes, T. (2010). Establishing a minimum post-mortem interval of human remains in an advanced state of skeletonization using the growth rate of bryophytes and plant roots. International Journal of Legal Medicine, 124, p. 451 – 456.

102

Carter, D. O., & Tibbett, M. (2006). Microbial decomposition of skeletal muscle tissue (Ovis aries) in a sandy loam soil at different temperatures. Journal of Soil Biology and Biochemistry, 38, p. 1139 – 1145.

Carrigg, D. (2008, June 17). Fifth human foot – with shoe – found floating: Two Most Recent Finds in Fraser Delta, Other Three Off Gulf Islands. Vancouver Province, p. A3.

Cattaneo, C., DiMartino, S., Scali, S., Craig, O. E., Grandi, M., & Sokol, R. J. (1999). Determining the human origin of fragments of burnt bone: A comparative study of histological, immunological, and DNA techniques. Journal of Forensic Science International, 102, p. 181 – 191.

Christensen, A. M., Passalacqua, N. V., & Bartelink, E. J. (2014). Forensic Anthropology: Current Methods and Practice. Oxford, UK: Elsevier Inc.

Chuah, T. K., Van Reeth, E., Sheah, K., & Poh, C. L. (2013). Texture analysis of bone marrow in knee MRI for classification of subjects with bone marrow lesion: Data from the Osteoarthritis Initiative. Journal of Magnetic Resonance Imaging, 31(6), p. 930 – 938.

Cockle, D. L., & Bell, L. S. (2017). The environmental variables that impact human decomposition in terrestrially exposed contexts within Canada. Science & Justice, 57(2), p. 107 – 117.

Connor, M., Baigent, C., Hansen, E. S. (2017). Testing the use of pigs as human proxies in decompositional studies. Journal of Forensic Science, e. 1 – 6.

Damann, F. E., Tanittaisong, A., & Carter, D. O. (2012). Potential carcass enrichment of the University of Tennessee Anthropology Research Facility: A baseline survey of edaphic features. Journal of Forensic Science International, 222, p. 4 – 10.

Damann, F. E., Williams, D. E., & Layton, A. C. (2015). Potential use of bacterial community succession in decaying human bone for estimating post-mortem interval. Journal of Forensic Sciences, 60(4), p. 844 – 850.

De Donno, A., Campobasso, C. P., Santoro, V., Leonardi, S., Tafuri, S., & Introna, F. (2014). Bodies in sequestered and non-sequestered aquatic environments: A comparative taphonomic study using decompositional scoring system. Journal of Science and Justice, 54(4), p. 439 – 446.

De La Grandmaison, G. L., Leterrux, M., Lasseuguette, K., Alvarez, J-C., De Mazancourt, P., & Durigon, M. (2006). Study of the diagnostic value of iron in fresh water drowning. Journal of Forensic Science International, 157, p. 117 – 120.

Delabarde, T., Keyser, C., Tracqui, A., & Charabidze, D. (2013). The potential of forensic analysis on human bones found in riverine environment. Journal of Forensic Science International, 228, e. 1 – 5.

103

Demehri, S., Muhit, A., Zbijewski, W., Stayman, J., Yorkston, J., Packard, N., Senn, R., Yang, D., Foos, D., Thawait, G., Fayad, L., Chhabra, A., Carrino, J., Siewerdsen, J. (2015). Assessment of image quality in soft tissue and bone visualization tasks for a dedicated extremity cone-beam CT system. Journal of European Radiology, 25(6), p. 1742 – 1751.

Dennison, K. J., Kieser, J. A., Buckeridge, J. S., Bishop, P. J. (2004). Post mortem cohabitation - shell growth as a measure of elapsed time: A case report. Journal of Forensic Science International, 139, p. 249 – 254.

Dickson, G. C., Poulter, R. T. M., Maas, E. W., Probert, P. K., & Kieser, J. A. (2011). Marine bacterial succession as a potential indicator of postmortem submersion interval. Journal of Forensic Science International, p. 1 – 10.

Dominquez, V. M., & Crowder, C. M. (2012). The utility of osteon shape and circularity for differentiating human and non-human Haversian bone. American Journal of Physical Anthropology, 149(1), p. 84 – 91.

Donovan, S. K. (2002). Fossils explained 41: Taphonomy. Journal of Geology Today, 18(6), p. 226 – 231.

Efford, I. E. (1967). Temporal and Spatial Differences in Phytoplankton Productivity in Marion Lake, British Columbia. Journal of the Fisheries Research Board of Canada, 24 (11), p. 2283 – 2309.

Estevez, J., Villagran, X. S., Balbo, A. L., Hardy, K. (2014). Microtaphonomy in archaeological sites: The use of soil micromorphology to better understand bone taphonomy in archaeological contexts. Quaternary international, 330, p. 3 – 9.

Evans, T. (2014). Fluvial Taphonomy. In J. T. Pokines & C. Atchison (Eds.), Manual of Forensic Taphonomy, p. 115 – 142.

Fernandez-Jalvo, Y., & Andrews, P. (2003). Experimental Effects of Water Abrasion on Bone Fragments. Journal of Taphonomy, 1(3), p. 145 – 161.

Gibson, J. J., Birks, S. J., Yi, Y., Shaw, P., & Moncur, M. C. (2018). Isotopic and geochemical surveys of lakes in coastal B.C.: Insights into regional water balance and water quality controls. Journal of Hydrology: Regional Studies, 17, p. 47 – 63.

Gord, N. (2010). A closer look at site index - biogeoclimatic site series correlations: Douglas-fir in the Coastal Western Hemlock Zone, xm2 variant, 01 site series. The Forestry Chronicle, 86(4), p. 477 – 483.

Goudge, S. T. (2008). Inquiry into Pediatric Forensic Pathology in Ontario: Report. Ontario Ministry of the Attorney General. Queen’s printer for Ontario 2008.

104

Government of Canada’s Past Weather and Climate’s Historical Data Centre. Data retrieved from 2015 to 2018.

Government of Canada’s National Centre for Missing Persons and Unidentified Remains. (2017). Background – 2017 Fast Fact Sheet. Retrieved from the Government of Canada’s National Centre for Missing Persons and Unidentified Remains Canada’s Missing website: http://www.canadasmissing.ca/pubs/2017/index-eng.htm

Griffith, S. J., & Thompson, C. E. L. (2017). The use of laser scanning for visualization and quantification of abrasion on water-submerged bone. In David Errickson and Tim Thompson (Eds) Human remains: Another dimension: The application of Imaging to the study of human remains. Academic Press: UK.

Griffith, S. J., Thompson, C. E. L., Thompson, T. J. U., Gowland R. L. (2016). Experimental abrasion of water submerged bone: The influence of bombardment by different sediment classes on microabrasion rate. Journal of Archaeological Science: Reports, 10, p. 15 – 29.

Gruspier, K. L. & Pollanen, M. S. (2000). Limbs found in water: Investigation using anthropological analysis and the diatom test. Journal of Forensic Science International, 112, p. 1 – 9.

Hackett C. J. (1981). Microscopical focal destruction (tunnels) in exhumed human bones. Journal of Medicine, Science, and the Law, 21, p. 243 – 265.

Haglund, W. D. (1993). Disappearance of soft tissue and the disarticulation of human remains from aqueous environments, Journal of Forensic Science, 38(4), p. 806 – 815.

Haglund, W. D. & Sorg, M. H. (2002). Human remains in water environments. In W. D. Haglund and M. H. Sorg (Eds.), Advances in Forensic Taphonomy. CRC Press, Boca Raton, p. 559 – 565.

Haeussler, S. (2011). Rethinking biogeoclimatic ecosystem classification for a changing world. Environmental Reviews, 19, p. 254 – 277.

Heaton, V., Lagden, A., Moffatt, C., Simons, T. (2010). Predicting the postmortem submersion interval for human remains recovered from U.K. Waterways. Journal of Forensic Sciences, 55(2), p. 302 – 307.

Hillier, M. L., & Bell, L. S. (2007). Differentiating human bone from animal bone: A review of histological methods. Journal of Forensic Science, 52(2), p. 249 – 263.

Hobishak, N. R., & Anderson, G. S. (1999). Freshwater-related death investigations in British Columbia in 1995 – 1996. A Review of Coroners Cases. Canadian Society of Forensic Science Journal, 32(2-3), p. 97 – 106.

105

Horner, K., Loeffler, K., & Holtzmann, M. (1997). Comparison of the histological structure of the compact bone of the long hallow bones of mouse, hamster, rat, guinea pig, rabbit, cat, and dog during development. Journal of Anatomia, histologia, embryologia, (26), p. 289-295.

Layton, A., McKay, L., Williams, D., Garrett, V., Gentry, R., & Sayler, G. (2006). Development of bacteroides 16S rRNA gene TaqMan-based real-time PCR assays for estimation of total, human, and bovine fecal pollution in water. Journal of Applied Environmental Microbiology, 72, p. 4214 – 4224.

Leach, J. A., & Moore, R. D. (2014). Winter stream temperature in the rain-on-snow zone of the Pacific Northwest: Influences of hillslope runoff and transient snow cover. Journal of Hydrology and Earth Systems Science, 18, p. 819 – 838.

Loeuille, D., & Chary-Valckenaere, I. (2012). MRI in OA: From cartilage to bone marrow lesion. Journal of Osteoporosis International, 23(8), p. 867 – 869.

Ito, M., Ejiri, S., Jinnai, H., Kono, J., Ikeda, S., Nishida, A., Uesugi, K., Yaga, N., Tanaka, M., & Hayashi, K. (2003). Bone structure and mineralization demonstrated using synchrotron radiation computed tomography (SR-CT) in animal models: Preliminary findings. Journal of Bone and Mineral Metabolism, 21(5), p. 287 – 93.

Janjua, M. A., & Rogers, T. (2008). Bone weathering patterns of metatarsals versus femur and the post-mortem interval in Southern Ontario. Forensic Science International, 178, p. 16 – 23.

Jans, M. E. (2014). Microscopic Destruction of Bone. In J. T. Pokines & C. Atchison (Eds.), Manual of Forensic Taphonomy, p. 19 – 35.

Kirchman, D. L. (2011a). Physical-chemical environment of microbes. In Processes in Microbial Ecology (Processes in Microbial Ecology, Chapter 9). Oxford University Press.

Kirchman, D. L. (2011b). Community structure of microbes in natural environments. In Processes in Microbial Ecology (p. Processes in Microbial Ecology, Chapter 9). Oxford University Press.

Klein, M., Goetz, H., Pazen, S., Al-Nawas, B., Wagner, W., Duschner, H. (2008). Pore characteristics of bone substitute materials assessed by microcomputed tomography. Journal of Clinical Oral Implants Research, 20(1), p. 67 – 74.

Klein-Nulend, J., Nijweide, P. J., & Burger, E. H. (2003). Osteocyte and Bone Structure. Journal of Current Osteoporosis Reports, 1, p. 5 – 10.

Klevezal, G. A. (1996). Recording structures of mammals: Determination of age and reconstruction of life history (English version). A. A. Balkema, Rotterdrdam, Brookfield.

106

Kontopoulos, I., Nystrom, P., & White, L. (2016). Experimental taphonomy: Post-mortem microstructural modificiations in Sus scrofa domestricus bone.

Life Saving Society Canada (2016). British Columbia Drowning Report. Retrieved from: http://www.lifesaving.bc.ca/sites/default/files/98DrowningReport2016_BC_Web.pdf

Mackay-Sim, A., & Chuah, M. I. (2000). Neurotrophic factors in the primary olfactory pathway. Progress in Neurobiology, 62, p. 527 – 559.

Marieb, E., Wilhelm, P., & Mallatt, J. (2014). Human anatomy (7th ed.). Boston, MA: Pearson.

Mulhern, D. M., & Ubelaker, D. H. (2001). Differences in osteon banding between human and nonhuman bone. Journal of Forensic Science, 46, p. 220 – 222.

Nawrocki, S. P., Pless, J. E., Hawley, D. A., & Wagner, S. A. (1997). Fluvial transport of human crania, in W. D. Haglund and M. H. Sorg (Eds) The postmortem fate of human remains. CRC Press LCC: Boca Raton Fl.

National Research Council Committee on Identifying the Needs of the Forensic Science Community. (2009). Strengthening forensic science in the United States: A path forward. Washington, D. C.: National Academy Press.

Oxnard, C. E. (2004). Thoughts on bone biomechanics. Journal of Folio Primatologica, 75, p. 189 – 201.

Rayne, S., & Forest, K. (2016). Rapidly changing climatic conditions for wine grape growing in the Okanagan Valley Region of British Columbia, Canada. Science of the Total Environment, 556(15), p. 169 – 178.

Roddick, J. A., & Armstrong J. E. (1959). Relict dikes in the coast mountains near Vancouver, B.C. Journal of Geology, 67(6), p. 603 – 613.

Rose, D. C., Agnew, A. M., Gocha, T. P., Stout, S. D., & Fields, J. S. (2012). Technical note: The use of geographical information systems software for the spatial analysis of bone microstructure. American Journal of Physical Anthropology, 148(4), p. 648 – 654.

Palys, T., & Atchison, C. (2014). Research Decisions: Quantitative, Qualitative, and Mixed Methods Approaches (5th Ed.), Nelson Education.

Parker, R., Ruffell, A., Hughes, D., & Pringle, J. (2010). Geophysics and the search of freshwater bodies: A review. Science and Justice, 50, p. 141 – 149.

Parkinson, J. A., Plummer, T. W., & Bose, R. (2014). A GIS-based approach to documenting large canid damage to bones. Palaeography, Palaeoclimatology, Palaeoecology, 409, p. 57 – 71.

107

Parsons & Brett (1991). Taphonomic processes and biases in modern marine environments: An actualistic perspective of possil assemblage preservation, in S. K. Donovan (Eds) The Process of Fossilization. Columbia University Press: New York.

Pasquero, M. D., Alcala, L., Bell, L. S., and Fernadez-Jalvo, Y. (2015). Bacterial origin of iron-rich microspheres in Miocene mammilian fossils. Paleogeography, Paleoclimatology, Paleoecology, 420, p.27-34.

Pasquero, M. D., Ascaso, C., Alcala, L., Fernandex-Jalvo, Y. (2010). A new taphonomic bioerosion in a Miocene lakeshore environment. Palaeogeography, paleoclimatology, paleoecology, 295, p. 192 – 198.

Pasquero, M. D., Bell, L. S., Fernadez-Jalvo, Y. (2017). Skeletal modification by microorganism and their environments. Journal of Historical Biology, e. 1 – 12.

Pazzaglia, U. E., Congiu, T., Pienazza, A., Zakaria, M., Gnecchi, M., and Dell’Orbo, C. (2013). Morphometric analysis of osteonal architecture in bones from healthy young human male subjects using scanning electron microscopy. Journal Anatomy, 223, p. 242 – 254.

Pokines, J. T. (2013). Manual of Forensic Taphonomy. USA: CRC Press.

Pokines, J. T. (2016). Taphonomic alterations to terrestrial surface-deposited human osseous remains in a New England Environment. Journal of Forensic Identification, 66(1), p. 59 – 79.

Pokines, J. T. & Symes, S. A. (2014). Manual of Forensic Taphonomy. USA: CRC Press.

Pollanen, M. S. (1998). Diatoms and Homicide. Journal of Forensic Science International, 91, p. 29 – 34.

Saferstein, R. (2018). Criminalistics: An introduction to forensic science (Twelfth Edition). Boston, MA: Pearson Press.

Schneider, P., Meier, M., Wepf, R., Muller, R. (2011). Serial FIB/SEM imaging for quantitative 3D assessment of the osteocyte lacuna-canalicular network. Journal of Bone, 49(2), p. 304 – 311.

Smith, J. H. (2016). Variations in lake temperature trends. Journal of Science, 351(6271), p. 351-352.

Sorg, M. H., Dearborn, J. H., Monahan. E. I., Ryan, H. F., Sweeney, K. G., & David, E. (1997). Forensic taphonomy in marine contexts, in Haglund, W. D., & Sorg, M. H. (editors) Forensic taphonomy. The post-mortem fate of human remains. CRC Press, Boca Raton, p. 567 – 604.

108

Symmons, R. (2004). Digital photodensitometry: A reliable and accessible method for measuring bone density. Journal of Archaeological Science, 31, p. 711 – 719.

Symmons, R. (2005). New density data for unfused and fused sheep bones, and a preliminary discussion on the modelling of taphonomic bias in archaeofaunal age profiles. Journal of Archaeological Science, 32(11), p. 1691 – 1698.

Thompson, C. E. L., Ball, S., Thompson, T. J. U., & Gowland, R. (2011). The abrasion of modern and archaeological bones by mobile sediments: The importance of transport modes. Journal of Archaeological Science, 38(4), p. 784 – 793.

Thompson, T. J. U., & Inglis, J. (2009). Differentiation of serrated and non-serrated blades from stab marks in bone. International Journal of Legal Medicine, 123, p. 129 – 135.

Toward, J. (2014). Simon Fraser University’s Office of Research Ethics: Human Research Ethics.

Vanin, S., & Zancaner, S. (2011). Post-mortal lesions in freshwater environment. Journal of Forensic Science International, e18 – 20.

White, J. W., & Thomas, T. T. (1907). The surgical treatment of prostatic hypertrophy. American Journal of the Medical Sciences, 133(5), p. 788.

Wierzchos, J., Falcioni, T., Kiciak, A., Wolinski, J., Koczorowski, R., Chomicki, P., Porembska, M., & Ascaso, C. (2008). Advances in the ultrastructural study of the implant: Bone interface by backscattered electron imaging. Journal of Micron, 39(8), p. 1363 – 1370.

Wu, J., Belle, A., Hargraves, R. H., Cockrell, C., Tang, Y., & Najarian, K. (2014). Bone segmentation and 3D visualization of CT images for traumatic pelvic injuries. International Journal of Imaging Systems and Technology, 24(1), p. 29 – 38.

Wu, Y., Reese, T. G., Cao, H., Horvat, M. I., Toddes, S. P., Lemdiasov, R. A., & Ackerman, J. L. (2011). Bone mineral images in vivo by 31P solid state MRI of human wrists. Journal of Magnetic Resonance Imaging, 34(3), p. 623 – 633.

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Appendix. Munsell Colour Codes

This appendix details the primary Munsell colour code of bone disc’s cut surface

(transverse block face). Majority of bone discs exhibited a gradient of colours, so this

colour code is based on what appeared to be the most representative of each sample.

SAMPLE MUNSELL Colour Code

A00 Hue 2.5Y 8/1 white

B00 Hue 2.5Y 8/2 pale yellow

C00 Hue 2.5Y 8/2pale yellow

D00 Hue 2.5Y 8/2 pale yellow

E00 Hue 2.5Y 8/3 pale yellow

F00 Hue 2.5Y 8/3 pale yellow

G00 Hue 2.5Y 8/2 pale yellow

H00 Hue 2.5Y 7/4 pale yellow

I00 Hue 2.5Y 8/3 very pale brown

J00 Hue 2.5Y 8/2 very pale brown

A01 Hue 10Y 8/1 white

B01 Hue 10Y 8/1 white

C01 Hue 10Y 8/3 pale yellow

D01 Hue 2.5Y 8/2 pale yellow

E01 Hue 2.5Y 8/2 pale yellow

F01 Hue 2.5Y 8/2 pale yellow

G01 Hue 2.5Y 8/2 pale yellow

I01 Hue 2.5Y 8/2 pale yellow

J01 Hue 2.5Y 8/2 pale yellow

A02 Hue 2.5Y 7/5 yellow

B02 Hue 2.5Y 7/3 pale yellow

C02 Hue 2.5Y 6/8 reddish yellow

D02 Hue 10Y 6/8 brownish yellow

E02 Hue 2.5Y 8/4 pale yellow

F02 Hue 10Y 6/8 brownish yellow

G02 Hue 10Y 7/8 yellow

H02 Hue 10Y 7/8 yellow

I02 Hue 2.5Y 8/6 yellow

J02 Hue 2.5Y 8/6 yellow

A03 Hue 10Y 6/8 brownish yellow

B03 Hue 10Y 7/8 yellow

SAMPLE MUNSELL Colour Code

C03 Hue 10Y 7/8 yellow

D03 Hue 10Y 6/6 brownish yellow

E03 Hue 2.5Y 8/3 pale yellow

F03 Hue 10Y 7/6 yellow

G03 Hue 2.5Y 8/4 pale yellow

H03 Hue 10Y 7/6 yellow

I03 Hue 10Y 6/6 brownish yellow

J03 Hue 10Y 7/8 yellow

A04 Hue 10Y 8/6 yellow

B04 Hue 10Y 7/6 yellow

C04 Hue 7.5Y 3/4 dark brown

D04 Hue 10Y 6/6 brownish yellow

E04 Hue 10Y 7/6 yellow

F04 Hue 10Y 6/6 brownish yellow

G04 Hue 10Y 7/4 yellow

H04 Hue 10Y 6/8 brownish yellow

I04 Hue 10Y 6/8 brownish yellow

J04 Hue 10Y 6/8 brownish yellow

A05 Hue 10Y 5/4 yellowish brown

B05 Hue 10Y 5/4 yellowish brown

C05 hue 7.5Y 4/4 brown

D05 Hue 10Y 7/4 very pale brown

E05 Hue 10Y 6/6 brownish yellow

F05 Hue 10Y 6/6 brownish yellow

G05 Hue 10Y 7/4 very pale brown

H05 Hue 10Y 6/6 brownish yellow

I05 Hue 10Y 6/6 brownish yellow

J05 Hue 10Y 6/6 brownish yellow

A06 Hue 10Y 4/4 dark yellowish brown

B06 Hue 10Y 2/2 very dark brown

C06 Hue 10Y 3/2 very dark grayish brown

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SAMPLE MUNSELL Colour Code

D06 Hue 10Y 6/4 light yellowish brown

E06 hue 2.5Y 8/2 pale yellow

F06 Hue 10Y 4/6 dark yellowish brown

G06 Hue 10Y 7/4 very pale brown

H06 Hue 10Y 6/4 light yellowish brown

I06 Hue 10Y 6/4 light yellowish brown

J06 Hue 10Y 5/6 yellowish brown

A07 Hue 10Y 3/4 dark yellowish brown

B07 Hue 10Y 3/4 dark yellowish brown

C07 Hue 10Y 6/6 brownish yellow

D07 Hue 10Y 4/4 dark yellowish brown

E07 Hue 10Y 8/2 very pale brown

F07 Hue 10Y 4/4 dark yellowish brown

G07 Hue 10Y 7/3 very pale brown

H07 Hue 10Y 5/4 yellowish brown

I07 Hue 10Y 4/6 dark yellowish brown

J07 Hue 10Y 4/3 brown

A08 Hue 10Y 3/6 dark yellowish brown

B08 Hue 10Y 7/6 yellow

C08 Hue 10Y 3/6 dark yellowish brown

D08 Hue 10Y 4/6 dark yellowish brown

E08 Hue 10Y 4/4 dark yellowish brown

F08 Hue 10Y 4/4 dark yellowish brown

G08 Hue 10Y 3/3 dark brown

H08 Hue 10Y 4/4 dark yellowish brown

I08 Hue 10Y 5/6 yellowish brown

J08 Hue 10Y 4/4 dark yellowish brown

A09 Hue 10Y 4/3 brown

B09 Hue 10Y 2/2 very dark brown

C09 Hue 10Y 3/6 dark yellowish brown

D09 Hue 10Y 4/6 dark yellowish brown

E09 Hue 10Y 3/6 dark yellowish brown

F09 Hue 10Y 5/6 yellowish brown

SAMPLE MUNSELL Colour Code

G09 Hue 10Y 4/6 dark yellowish brown

H09 Hue 10Y 5/4 yellowish brown

I09 Hue 10Y 3/3 dark brown

J09 Hue 10Y 3/3 dark brown

A10 Hue 10Y 6/4 light yellowish brown

B10 Hue 10Y 5/6 yellowish brown

C10 Hue 10Y 4/6 dark yellowish brown

D10 Hue 10Y 6/4 light yellowish brown

E10 Hue 10Y 5/6 yellowish brown

F10 Hue 10Y 5/6 yellowish brown

G10 Hue 10Y 4/4 dark yellowish brown

H10 Hue 10Y 3/4 dark yellowish brown

I10 Hue 10Y 4/4 dark yellowish brown

J10 Hue 10Y 6/4 light yellowish brown

A11 Hue 10Y 4/4 dark yellowish brown

B11 Hue 10Y 6/4 light yellowish brown

C11 Hue 10Y 5/4 yellowish brown

D11 Hue 10Y 4/4 dark yellowish brown

E11 Hue 10Y 4/6 dark yellowish brown

F11 Hue 10Y 5/6 yellowish brown

G11 Hue 10Y 4/4 dark yellowish brown

H11 Hue 10Y 5/4 yellowish brown

I11 Hue 10Y 3/6 dark yellowish brown

J11 Hue 10Y 4/4 dark yellowish brown

A12 Hue 10Y 5/4 yellowish brown

B12 Hue 10Y 5/8 yellowish brown

C12 Hue 10Y 4/6 dark yellowish brown

D12 Hue 10Y 7/8 yellow

E12 Hue 10Y 6/4 light yellowish brown

F12 Hue 10Y 5/6 yellowish brown

G12 Hue 10Y 4/3 brown

H12 Hue 10Y 5/3 light olive brown

I12 Hue 10Y 4/3 brown

J12 Hue 10Y 6/4 light yellowish brown