UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

A comparative morphometric analysis of the sensory hair cells of the cochleas of echolocating mammals Girdlestone, Cassandra Dawn 2018

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
24-ubc_2018_november_girdlestone_cassandra.pdf [ 3.32MB ]
Metadata
JSON: 24-1.0372307.json
JSON-LD: 24-1.0372307-ld.json
RDF/XML (Pretty): 24-1.0372307-rdf.xml
RDF/JSON: 24-1.0372307-rdf.json
Turtle: 24-1.0372307-turtle.txt
N-Triples: 24-1.0372307-rdf-ntriples.txt
Original Record: 24-1.0372307-source.json
Full Text
24-1.0372307-fulltext.txt
Citation
24-1.0372307.ris

Full Text

A COMPARATIVE MORPHOMETRIC ANALYSIS OF THE SENSORY HAIR CELLS OF THE COCHLEAS OF ECHOLOCATING MAMMALS by  Cassandra Dawn Girdlestone  B.Sc. (Specialized Honours, Marine Biology), University of Guelph, 1997  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Zoology)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  September 2018  © Cassandra Dawn Girdlestone, 2018  ii  The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis/dissertation entitled:  A Comparative Morphometric Analysis of the Sensory Hair Cells of the Cochleas of Echolocating Mammals  submitted by Cassandra Girdlestone in partial fulfillment of the requirements for the degree of Master of Science in Zoology  Examining Committee: Dr. Robert Shadwick Supervisor  Dr. Vanessa Auld Supervisory Committee Member  Dr. William Milsom Supervisory Committee Member  Additional Examiner   Additional Supervisory Committee Members:  Supervisory Committee Member  Supervisory Committee Member iii  Abstract  Morphometric analysis of the inner ear of mammals can provide information for cochlear frequency mapping, which can determine the encoding frequency of lesions in the cochlea resulting from noise-induced hearing loss. A frequency map is a species-specific designation of the locations in the cochlea at which different sound frequencies are encoded. If the frequency map is known and there is a lesion in the cochlea due to noise exposure, the related frequencies of the anthropogenic source may be determined. Morphometric variation occurs in cells of the organ of Corti from the apex to the base of the cochlea. The base of the cochlea encodes for high frequency sounds, while low frequencies are detected in the apex. These changes in cell shape and spacing are linked to the frequencies detected at different locations, which has previously been shown in the guinea pig (Cavia porcellus). Here, we show that morphometric analysis also seems to be a viable alternative to physiological techniques when predicting the frequency as a function of location in other mammals, including those that echolocate. Parnell’s mustached bat (Pteronotus parnellii) already has a well-documented frequency map to compare morphometric measurements to. Using both traditional and geometric morphometrics to analyze scanning electron micrographs, our research shows a relationship between cochlear morphometrics in six mustached bats and their frequency map. Traditional morphometrics were also collected in a Wistar rat (Rattus norvegicus). These results from both species were further compared to traditional morphometrics measured in beluga whales (Delphinapterus leucas). Five out of eight morphometric parameters analyzed showed a strong similarity in their trends along the cochlea, including the distance between the rows of hair cells, width of outer hair cells, and gap width between hair cells. Using a multiple linear regression model revealed that five parameters are iv  responsible for 83.5% of the variation in these morphometric data. Based on this information we created the first cochlear frequency map for the beluga whale. Determining the biologically relevant measurements related to frequency detection can give us a greater understanding of how hearing works and how it is affected by anthropogenic noise.   v  Lay Summary  Hearing in bats has been studied across many species. However, further knowledge can be gained by studying echolocating bats as a proxy for other species of echolocating mammals, including toothed whales. Frequency maps link a specific location on the organ of Corti, the hearing organ of the cochlea, within the inner ear, to the frequency detected at that location. These maps can help us understand which man-made sounds are potentially causing noise-induced hearing loss or trauma in species exposed to such noise. Historically these maps were created in model animals using methods which require euthanasia of the animal specifically to analyze the cochlea. Comparing existing frequency maps to size and shape measurements of the inner ear structures, shows that measurement analyses can be used. This means frequency maps can be created using deceased animals, collected opportunistically, for species in which other methods are not possible due to ethics and availability.    vi  Preface    A version of chapter 2 has been published. Girdlestone, C.D., Piscitelli-Doshkov, M.A., Ostertag, S.K., Morell, M. and Shadwick, R.E. (2018). Description of cochlear morphology and hair cell variation in the beluga whale. Arctic Science, DOI: 10.1139/AS-2017-0031. I conducted all the measurements, the data analysis, and wrote most of the manuscript. Marina Piscitelli-Doshkov and Sonja Ostertag collected and fixed the ear samples. Marina Piscitelli-Doshkov, Maria Morell, and Robert Shadwick obtained the necessary permits for the collection, transport, and analysis of the cochlear samples. Maria Morell prepared and dissected the samples and took all of the SEM micrographs. Maria Morell and Robert Shadwick supervised the work. All the co-authors contributed in the writing and revision of the manuscript. A version of chapter 3 is currently in preparation. Girdlestone, C.D., Ng, J., Kössl, M., Shadwick, R.E., and Morell, M. (in preparation for publication). I conducted all the measurements and wrote most of the first version of the manuscript, took some of the SEM micrographs of the bats’ organ of Corti. Jodie Ng completed preliminary measurements of three parameters in the bats (A, B1, and D1, Fig. 3.2) as well as measuring the cochlear lengths for the bats. Manfred Kössl supplied the bat cochleas, as well as data from previous research. Maria Morell prepared and dissected the samples and took SEM micrographs of the organ of Corti for the belugas, bats, and rats. Adrien Caplot wrote the R code for the statistical analysis, which he also performed. Maria Morell and Adrien Caplot calculated the frequency mapping predictions. Maria Morell and Robert Shadwick supervised the work. All the co-authors will contribute in the writing and revision of the final version of the manuscript.  vii  Table of Contents  Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ........................................................................................................................ vii List of Tables ..................................................................................................................................x List of Figures ............................................................................................................................... xi List of Abbreviations ...................................................................................................................xv Acknowledgements .................................................................................................................... xvi Dedication ................................................................................................................................. xviii Chapter 1: Introduction ................................................................................................................1 1.1 Background - Hearing, frequency mapping, and morphology ....................................... 1 1.2 Mammalian inner ears..................................................................................................... 2 1.3 Hearing in echolocating bats ........................................................................................... 5 1.4 Hearing in cetaceans ....................................................................................................... 7 1.4.1 Hearing in toothed whales (Odontocetes) ................................................................... 7 1.4.1.1 Hearing in beluga whales (Delphinapterus leucas) ............................................ 9 1.5 Morphological trends in mammalian inner ears ........................................................... 10 1.6 Frequency mapping techniques..................................................................................... 11 1.7 Morphology and morphometrics................................................................................... 12 1.8 Research objectives ....................................................................................................... 13 viii  Chapter 2: Description of cochlear morphology and hair cell variation in the beluga whale........................................................................................................................................................15 2.1 Introduction ................................................................................................................... 15 2.2 Methods......................................................................................................................... 16 2.2.1 Extraction and Fixation ............................................................................................. 16 2.2.2 Decalcification .......................................................................................................... 17 2.2.3 Scanning electron microscopy – dissection and processing ..................................... 17 2.2.4 Image analysis and morphometry ............................................................................. 18 2.3 Results ........................................................................................................................... 19 2.4 Discussion ..................................................................................................................... 24 2.5 Chapter summary .......................................................................................................... 30 Chapter 3: Cochlear morphology analysis in bats and belugas, using morphometric and geometric morphometric analyses ..............................................................................................31 3.1 Introduction ................................................................................................................... 31 3.2 Methods......................................................................................................................... 33 3.2.1 Image analysis ........................................................................................................... 35 3.2.2 Morphometric analysis.............................................................................................. 35 3.2.3 Geometric morphometric analysis ............................................................................ 39 3.3 Results ........................................................................................................................... 40 3.3.1 Morphometric analysis in the mustached bat............................................................ 40 3.3.2 Results for morphometrics in the beluga whale ........................................................ 48 3.3.3 Prediction of the cochlear frequency map for belugas based on the morphometric analyses from bats and rats ................................................................................................... 55 ix  3.3.4 Geometric morphometric analysis in Parnell’s mustached bat ................................. 69 3.4 Discussion ..................................................................................................................... 75 3.4.1 Morphometric analysis.............................................................................................. 75 3.4.2 Geometric morphometric analysis ............................................................................ 80 3.5 Chapter summary .......................................................................................................... 81 Chapter 4: Conclusion .................................................................................................................83 4.1 Summary ....................................................................................................................... 83 4.2 Future directions ........................................................................................................... 84 References .....................................................................................................................................86 Appendices ..................................................................................................................................100 Appendix A Beluga cochlear sample processing.................................................................... 100 A.1 Sample treatment specifics for both the fixation and decalcification processes. Time post mortem refers to the time between the death of the animal and fixation of the ears. . 100 Appendix B Geometric Morphometrics.................................................................................. 101 B.1 Geometric morphometrics - landmarks .................................................................. 101  x  List of Tables  Table 2.1 Beluga whale mean cochlear measurements ................................................................ 23 Table 3.1 Coefficients for the multiple linear regression model - bats ......................................... 66 Table 3.2 Coefficients for the multiple linear regression model - bats and rat ............................. 67    xi  List of Figures  Figure 1.1 Schematics and image of the location of the cochlea and the organ of Corti ............... 4 Figure 2.1 Scanning electron micrographs showing fixation ....................................................... 19 Figure 2.2 Scanning electron micrographs of beluga cochleas decalcified .................................. 20 Figure 2.3  Examples of the variation in the morphology of the hair cells from the beluga whale cochlea .......................................................................................................................................... 22 Figure 2.4  Beluga whale mean hair cell width ............................................................................ 24 Figure 2.5  Beluga whale mean distance ± standard deviation from the inner hair cells (IHC) to the third row of outer hair cells (OHC3) ....................................................................................... 26 Figure 2.6  Beluga whale mean hair cell density .......................................................................... 26 Figure 3.1 Scanning electron micrograph of a bat cochlea showing the cochlear turns. .............. 34 Figure 3.2 The parameters measured using morphometrics ......................................................... 36 Figure 3.3 The landmarks used for geometric morphometrics ..................................................... 40 Figure 3.4. The mean distance between the inner hair cells (IHCs) to the third row of outer hair cells (OHC3, Parameter A) in mustached bats ............................................................................. 42 Figure 3.5. The mean distance between each row of hair cells (Parameter B1-B3) in mustached bats ................................................................................................................................................ 43 Figure 3.6. The mean width of the hair cell cuticular plate (Parameter D1-D3) in mustached bats....................................................................................................................................................... 44 Figure 3.7. The mean distance between stereocilia bundle tips (Parameter E1-E3) in mustached bats ................................................................................................................................................ 45 xii  Figure 3.8. The mean gap width between stereocilia bundles (Parameter F1-F3) in mustached bats ................................................................................................................................................ 46 Figure 3.9. The mean inner angle of the stereocilia bundles (Parameter H1-H3) in mustached bats....................................................................................................................................................... 47 Figure 3.10. The mean stereocilia lengths in a mustached bat ..................................................... 48 Figure 3.11. The mean distance between the inner hair cells (IHCs) to the third row of outer hair cells (OHC3, Parameter A) in a beluga whale. ............................................................................. 49 Figure 3.12. The mean distance between each row of hair cells (Parameter B1-B3) in a beluga whale. ............................................................................................................................................ 50 Figure 3.13. The mean width of the hair cell cuticular plate (Parameter D1-D3) in a beluga whale. ............................................................................................................................................ 51 Figure 3.14. The mean distance between stereocilia bundle tips (Parameter E1-E3) in a beluga whale. ............................................................................................................................................ 52 Figure 3.15. The mean gap width between stereocilia bundles (Parameter F1-F3) in a beluga whale. ............................................................................................................................................ 53 Figure 3.16. The mean inner angle of the stereocilia bundles (Parameter H1-H3) in a beluga whale. ............................................................................................................................................ 54 Figure 3.17. The mean stereocilia lengths in a beluga whale. ...................................................... 55 Figure 3.18. The mean distance between the inner hair cells (IHCs) to the third row of outer hair cells (OHC3, Parameter A) showing a comparison between the mustached bats and a beluga whale. ............................................................................................................................................ 56 Figure 3.19. The mean distance between each row of hair cells (Parameter B1-B3) comparing the mustached bats to a beluga whale. ................................................................................................ 56 xiii  Figure 3.20. The mean width of the hair cell cuticular plate (Parameter D1-D3) comparing the mustached bats to a beluga whale ................................................................................................. 57 Figure 3.21. The mean distance between stereocilia bundle tips (Parameter E1-E3) comparing the mustached bats to a beluga whale. ................................................................................................ 58 Figure 3.22. The mean gap width between stereocilia bundles (Parameter F1-F3) comparing the  mustached bats to a beluga whale. ................................................................................................ 59 Figure 3.23. The mean inner angle of the stereocilia bundles (Parameter H1-H3) comparing the mustached bats to a beluga whale. ................................................................................................ 59 Figure 3.24. The mean stereocilia lengths compared between the mustached bats and a beluga whale. ............................................................................................................................................ 60 Figure 3.25. The mean distance between the inner hair cells (IHCs) and the third row of outer hair cells (OHC3, Parameter A) corresponding to the percent distance from the apex comparing the mustached bats to a rat. ........................................................................................................... 61 Figure 3.26. The mean distance between the inner hair cells (IHCs) and the third row of outer hair cells (OHC3, Parameter A) corresponding to the frequencies detected (kHz) comparing the mustached bats to a rat. ................................................................................................................. 62 Figure 3.27. The mean distance between each row of hair cells (Parameter B1-B3) as a function of the frequencies detected, comparing the mustached bats to a rat ............................................. 63 Figure 3.28. The mean width of the hair cell cuticular plate (Parameter D1-D3) as a function of the frequencies detected, comparing the mustached bats to a rat ................................................. 63 Figure 3.29. The mean distance between stereocilia bundle tips (Parameter E1-E3) as a function of the frequencies detected, comparing the mustached bats to a rat ............................................. 64 xiv  Figure 3.30. The mean gap width between stereocilia bundles (Parameter F1-F3) as a function of the frequencies detected, comparing the mustached bats to a rat ................................................. 64 Figure 3.31. The mean inner angle of the stereocilia bundles (Parameter H1-H3) as a function of the frequencies detected, comparing the mustached bats to a rat. ................................................ 65 Figure 3.32. The five variables which explained 82.17% of the variation related to frequency sensitivity in the bats, and 95% of the variation in rats. ............................................................... 68 Figure 3.33. Cochlear frequency map prediction for the beluga whale ........................................ 68 Figure 3.34. Hair cell variation from the ten locations (A through J, 5 through 95% distance from the apex) for which geometric morphometrics were analyzed in the mustached bats. ................. 70 Figure 3.35. Principal component analysis (PCA) of the inner hair cells (IHCs) and outer hair cells (OHCs) analyzed together in the mustached bats ................................................................. 71 Figure 3.36. Principal component analysis (PCA) of the inner hair cells (IHCs) separated from and compared to the outer hair cells (OHCs) in the mustached bats. ........................................... 72 Figure 3.37. Principal component analysis (PCA) of only the outer hair cells (OHCs) in the mustached bats. ............................................................................................................................. 73 Figure 3.38. Principal component one (PC1) as a function of frequency (kHz) showing locations from 5 – 95% from the apex, in the mustached bats. .................................................................... 74 Figure 3.39. Regression of shape (Procrustes) versus frequency (kHz) in the mustached bats ... 74  xv  List of Abbreviations  ms  millisecond  CP  cuticular plate IHC  inner hair cell OHC  outer hair cell OHC1  outer hair cell from the first row of hair cells OHC2  outer hair cell from the second row of hair cells OHC3  outer hair cell from the third row of hair cells SB  stereocilia bundle  df  degrees of freedom n  sample size  LM  landmark PC  principal component PCA  principal component analysis  SEM   scanning electron microscope  xvi  Acknowledgements   First and foremost, a huge thank you to my supervisor Bob Shadwick. I will be forever grateful to you for giving me the opportunity to be a member of your lab and for your guidance and support along the way. Your ongoing quest to learn and explore the world around you is an inspiration. Thank you to my committee members: Vanessa Auld for her valuable insight and perspective, and who also gains great knowledge by studying microscopically; and Bill Milsom for his feedback and support and for bringing yet another perspective to our meetings. I have been very fortunate to be supported and guided by people who have rich scientific lives, and an ongoing thirst for knowledge in all areas of science and life in general. Thank you to the following agencies, from which the required permits were obtained: ARI, DFO, and EISC. The authors would also like to thank Lisa Loseto (DFO, Canada), Stephen Raverty (British Columbia Ministry of Agriculture and Lands), and for technical help, Derrick Horne (Bioimaging Facility, University of British Columbia). We especially thank the Tuktoyaktuk community hunters and the Tuktoyaktuk Hunters and Trappers Committee, who supported and approved this sampling and research. Thank you to Christina Harvey for her invaluable help with R and geomorph and going above and beyond to teach me her ways and help me learn. Thanks also to Vikram Baliga for fielding additional R questions and for helping to pave the way with the geomorph coding that he and Christina developed. Thank you to the rest of the Altshuler Lab for their support and encouragement along the way. Thanks to Adrien Caplot for all of his work with R coding and with the machine learning and statistics used for developing the predictions of the cochlear frequency map. xvii  A HUGE “THANK YOU” to my amazing labmates in the Shadwick lab. Maria for giving me a chance to assist on one of your projects - look where it has taken me. I cannot thank you enough for giving me that initial opportunity, and for your support and encouragement since (from both near and far). Margo for asking the tough questions, making me think and keeping me on my toes, and for her appreciation of ice cream. Marina for her editing skills and support from afar. Kelsey for being a labmate, officemate, and friend – and supporting me in all those roles, and reminding me to take breaks on occasion.  In addition to Kelsey, thank you also to my other two officemates: Melissa Armstrong and Christina Harvey – the four of us have been on quite a ride, ladies and I wouldn’t have wanted to share an office with anyone else. I can’t believe how quickly the time went. I’m grateful for your support, friendship, and laughter – here’s to continued adventures in science and life! I feel so very fortunate to have been part of the UBC Zoology Department. An amazing place full of amazing people – I wish I could thank you all individually, but I hope this counts! It has been an honour, a pleasure, and definitely an experience (a great one). It has been a full two years, and I will cherish the memories and the wonderful friendships I’ve made. Thank you.  A very special thank you to my amazing mom, who has, and continues to support, encourage, and believe in me. You are an inspiration. Thank you for teaching me I can do anything I put my mind to and encouraging my love of science (even if I did go off water for a while after getting a microscope when I was young).    xviii  Dedication  Dedicated to my amazing mother. I love you a bushel and a peck. 1  Chapter 1: Introduction  1.1 Background - Hearing, frequency mapping, and morphology Ice cover in the Arctic has been declining for several decades, and as a result, new areas are becoming accessible to both animals and humans (Hauser, Laidre, & Stern, 2018). With human activity comes more widespread and elevated levels of anthropogenic or man-made sounds. As we are increasingly able to travel to newly accessible areas, which have been relatively undisturbed until now, it is important to learn more about the hearing of marine mammals. This will give us a better understanding of how increases in anthropogenic sound may be affecting not just behaviour, but also hearing function in these animals. To do this we first need to characterize what constitutes normal morphology of the hearing organ in Arctic marine mammals, so we can also recognize abnormal morphology potentially caused by acoustic trauma or hearing damage.  One tool that can help us is a frequency-place map of the cochlea. This is a species-specific map of the cochlea in which the frequencies detected correspond to a location along the cochlear length. Permanent hearing damage resulting from overexposure to sound can be indicated by a lesion or scar in place of a healthy sensory cell (Lim & Dunn, 1979; Lim & Melnick, 1971; Morell et al., 2017; Ou, Harding, & Bohne, 2000). With a frequency map in place, knowing what frequency is detected in each location, we could potentially determine the frequencies that caused the damage, and in turn the anthropogenic source of that frequency.    The survival and success of animals depends on their ability to navigate within their environment to find food, conspecifics, shelter, and avoid predators and other hazards. Some species must rely on their hearing instead of sight to do so. In some terrestrial and marine 2  mammals, echolocation has evolved as a specialized type of hearing to enable navigation in environments which are spatially, acoustically, or visually complex. Echolocating mammals use higher frequencies than are used by non-echolocating mammals and are known as high-frequency hearing specialists (Echteler, Fay, & Popper, 1994). Echolocation is present in microchiropteran bats (Simmons & Stein, 1980) and two or three species of Old World bats from the genus Rousettus (Fenton, 2013; Jones & Teeling, 2006), toothed whales (odontocetes) (Au, 1997; Ketten & Wartzok, 1990; Nachtigall & Moore, 1988), shrews (Gould, Negus, & Novick, 1964), tenrecs (Gould, 1965), swiftlets (16 species)  and oilbirds (Brinkløv, Fenton, & Ratcliffe, 2013). There is still debate around the evolution of echolocation in bats particularly whether it evolved once and was lost by megachiropterans, or if it evolved twice (Davies, Cotton, Kirwan, Teeling, & Rossiter, 2012; Fenton, 2013; Jones & Teeling, 2006; Parker et al., 2013). In birds it may have evolved three times (Brinkløv et al., 2013). It has however, been generally well accepted that high frequency echolocation has evolved convergently in bats and odontocetes (Liu et al., 2012; Madsen & Surlykke, 2013; Parker et al., 2013; Shen, Liang, Li, Murphy, & Zhang, 2012)..  Comparing the inner ear morphology between species and hearing specialists can increase our knowledge about how hearing works, including how it is affected by anthropogenic sound.  1.2 Mammalian inner ears Mammals have very different outer and middle ear morphology depending on whether they hear in air or water. At the same time, within the inner ear, species share many similarities 3  both in the cochlear organization of the sensory cells and its morphology (Echteler et al., 1994; Ketten, 2000; Von Békésy, 1960; Wartzok & Ketten, 1999). Within the inner ear is a spiral shaped structure known as the cochlea (Fig. 1.1A). The cochlea is comprised of three fluid-filled ducts, or channels. The centremost of these channels is where the organ of Corti, the hearing organ, is located (Fig. 1.1B). The surface of the organ of Corti (Fig. 1.1C) reveals an arrangement of two types of sensory cells, the inner hair cells (IHCs and the outer hair cells (OHCs). Typical for mammals, the IHCs are organized in a single row, while the OHCs form three parallel rows (Lim, 1986). OHCs play a crucial role in frequency selectivity and increasing sensitivity, while IHCs are responsible for the transduction of the mechanical stimulus into an electrical signal (for a review, see Fettiplace & Kim, 2014).  4     Figure 1.1 Schematics and image of the location of the cochlea and the organ of Corti. (A) Beluga cochlea; image taken with a dissecting microscope. Arrows indicate the maximum and minimum distances between the outer edges of the spiral ligament, used to calculate the cochlear diameter. (B) Schematic of the cochlea showing the location of the organ of Corti (OpenStax image adapted from: https://upload.wikimedia.org/wikipedia/commons/1/1c/1406_Cochlea.jpg in accordance with licensing: https://creativecommons.org/licenses/by/4.0/legalcode). (C) Scanning electron micrograph of the surface of the organ of Corti in a beluga cochlea, showing the typical arrangement of the hair cells. Visible here is the single row of inner hair cells (IHC) as well as the three parallel rows of outer hair cells (OHC1, OHC2, and OHC3). Each “U” or “W” shape represents one hair cell. Measurements shown are (i) IHC width, (ii) distance from IHC to the third row of OHCs, (iii) OHC width. Dotted lines indicate (iv) stereocilia, and (v) the borders of the cuticular plate (CP). 5   When soundwaves reach the cochlea, the stereocilia (Fig. 1.1C), which are in contact with the overlying tectorial membrane, are deflected. This initiates the process of mechanotransduction, in which ion transduction channels open causing an influx of K+ ions that depolarizes the hair cell. The depolarization of the OHC membrane results in conformational changes of the transmembrane protein prestin, an OHC motor protein that contracts and elongates the OHCs, amplifying the sensitivity and selectivity. Depolarizing contracts the OHC shortening the distance between the reticular lamina and the basilar membrane, while hyperpolarization increases this distance. This releases an electrical impulse, or acoustic information, that is carried via the spiral ganglion to the cochlear nucleus and to the brain (Dallos, 1992; Fettiplace, 2006; Gillespie & Müller, 2009). The organization of certain structures within the inner ear is well documented in terrestrial mammals, pinnipeds, and some cetaceans (Gao & Zhou, 1992; Ketten & Wartzok, 1990; Lim, 1986; Morell et al., 2015; Roth & Bruns, 1992; Wartzok & Ketten, 1999; Wever, McCormick, Palin, & Ridgway 1971a, 1971b, 1972). This organization and the structures of the inner ear are conserved among species of terrestrial mammals and those marine mammals studied thus far. Therefore, it is reasonable to expect that additional species of marine mammals will also be comparable to terrestrial mammals, especially to other high frequency specialists.  1.3 Hearing in echolocating bats Bats are known as high frequency specialists and several species use echolocation to navigate complex environments, often consisting of dense foliage in forests during the night to capture and feed on small nocturnal insects. In contrast to humans whose hearing ranges from 20 Hz to 20 kHz, most echolocating bats use frequencies between 20 kHz and 120 kHz and can hear 6  lower frequencies at which their prey are audible (Altringham, 2011), and some bats use frequencies as low as 5 - 12 kHz (Kössl & Vater, 1995; Neuweiler, 1989). The ultrastructure of the organ of Corti, to our knowledge, has only been described for four species of bats: the horseshoe bat (Rhinolophus rouxi, Temminck, 1835) (Vater & Lenoir, 1992; Vater, Lenoir, & Pujol, 1992), Parnell’s mustached bat (Pteronotus parnellii, Gray, 1843) (Kössl & Vater, 1990b, 1996; Vater & Kössl, 1996), Bicolored Leaf-nosed Bat or Bicolored Roundleaf Bat (Hipposideros bicolor, Temminck, 1834) (Dannhof & Bruns, 1991), and the Mexican free tailed bat (Tadarida brasiliensis mexicana, Saussure, 1860) (Vater & Siefer, 1995).  Echolocation is produced either in the larynx or using tongue clicks (Altringham, 2011; Jones & Holderied, 2007; Jones & Teeling, 2006; Nachtigall & Moore, 1988). Bats use a variety of echolocation signals depending on their habitat or if they are hunting. These signals may be broad or narrowband, long or short in duration, use a fundamental harmonic or multi-harmonics, or pure tone signals (Jones & Teeling, 2006). There are also different types of calls employed – frequency modulated (FM), or constant frequency (CF), or a combination of the two (CF-FM), as in Parnell’s Mustached Bat (Pteronotus parnellii) (Kössl & Vater, 1990a) and the greater horseshoe bat (Rhinolophus ferrumequinum, Schreber, 1774) (Bruns, 1976). FM calls are broadband signals, with variable harmonics, are short in duration, ranging from 0.5-10 ms and not affected by the velocity of the bat or its prey (Au, 1997, 2004; Kössl & Vater, 1995; Simmons, 1973; Simmons & Stein, 1980). FM frequencies are used for determining the size, shape, and localization of prey (Au, 1997; Simmons, 1973). CF calls are narrowband, of a constant harmonic, and usually longer in duration, typically ranging from 10 to 100 ms and even up to 300 ms although they can be as low as 1-10 msec. (Au, 2004). CF calls help the bat to differentiate between a moving and stationary target (Au, 1997). In CF-FM bats, a combination 7  of the two types of calls, is employed, allowing improved discrimination of prey in areas of high background clutter such as dense forest or walls. While the inner ears of non-echolocating bats are similar to other terrestrial mammals, those of echolocating bats show greater variability in the cochleas (Davies, Maryanto, & Rossiter, 2013). An example of this is the acoustic fovea, a specialized region of the cochlea which exhibits higher sensitivity and selectivity to the functional frequency in bats (Au, Popper, & Fay, 2000; Kössl & Vater, 1995). This region varies between species, and in the mustached bat this region centres around the frequency of 61.5 kHz and is located between 40-60% of the distance along the cochlear length (Kössl, 1994a). The inner ears of echolocating mammals both terrestrial and aquatic have similar function and in the species studied thus far, similarities in morphology as well.    1.4 Hearing in cetaceans Extant cetaceans are divided into odontocetes (toothed whales) and mysticetes (baleen whales). One of the many differences between these groups is the frequency range in which they hear and communicate. Odontocetes function using high frequencies (greater than 2 kHz) (Tyack & Clark, 2000) with several species possessing peak frequencies above 100 kHz. Mysticetes, however, use lower frequencies, primarily from 10 Hz to 200 Hz (Ketten, 2000) at times extending to around 2 kHz (Tyack & Clark, 2000).  1.4.1 Hearing in toothed whales (Odontocetes)  Odontocetes (toothed whales) are high frequency specialists, as are echolocating bats  (Tyack & Clark, 2000), and some species can hear up to 180 kHz (Mooney, Yamato, & 8  Branstetter, 2012). Previous research on this group of cetaceans has been done on the histology and morphological features with a strong focus on the bottlenosed dolphin (Tursiops truncatus, Montagu, 1821) (Wever et al., 1971a, 1971b) and the Pacific white sided dolphin (Lagenorhynchus obliquidens, Gill 1865) (Wever et al., 1972).  Amongst documented mammals, small cetaceans have been found to have the widest bandwidth for acoustic frequencies (Vater & Kössl, 2011). Again, as in the echolocating bats, there is a relationship between the frequencies of highest sensitivity, and the peak spectra for emitted sound, as well as with habitat. Despite the difference in the speed of sound transmission in water versus air, odontocetes have a pause between sonar pulses emitted, making their sonar emission comparable to that of echolocating bats (Madsen & Surlykke, 2013). These two groups also share an increase in the echolocation frequency as they close the distance between themselves and their prey while hunting.  One feature of the organ of Corti which has been studied in both terrestrial mammals and several marine mammals is the basilar membrane which underlies, and is attached to, the hair cells. The basilar membrane is tonotopically organized, meaning that the frequency to which the sensitivity is greatest, as well as the thickness and stiffness of this membrane, varies with location. In odontocetes, the basilar membrane exhibits a 0.01 ratio of thickness to width apically, and from 0.5 to greater than 0.8 basally (Ketten, 1997). This is consistent among high frequency specialist echolocators such as odontocetes and bats, and is a strong indicator of the frequencies received by a species (Ketten & Wartzok, 1990). The ratio of thickness to width also determines the stiffness of the basilar membrane, which is greater at the base of the cochlea in high frequency specialists (Vater & Kössl, 2011). In the basal region of the cochlea of odontocetes, the inner and outer bony lamina is more calcified and has a higher degree of 9  attachment to the basilar membrane, increasing its stiffness, thus allowing this membrane to vibrate at very high frequencies (Ketten & Wartzok, 1990). Although odontocetes were previously believed to produce sound from the larynx (Au et al., 2000), it is now understood that they produce sound using the nasal system in combination with their melon, and not the larynx (Amundin & Andersen, 1983; Au et al., 2000; Cranford & Amundin, 2004; Ridgway & Carder, 1988). Similarly, as in some species of echolocating bats, there is the possibility that an acoustic fovea exists in the organ of Corti of the harbour porpoise (Phocoena phocoena, Linnaeus, 1758) (Ketten, 1998 as cited in Ketten, 2000). These features are indicative of a strong convergence among echolocators regardless of the media through which they hear.    1.4.1.1 Hearing in beluga whales (Delphinapterus leucas)  We are especially interested in analyzing the cochleas of beluga whales because they have a similar hearing range to that of the mustached bat and also use high frequency echolocation. Belugas have a sophisticated echolocation system, possibly with higher resolution than other species of odontocetes (Au, 1988; Au, Carder, Penner, & Scronce, 1985). Belugas use a two pulse sonar emission (Lammers & Castellote, 2009), comparable to the CF-FM frequency emissions of Parnell’s mustached bat (Kössl & Vater, 1990a). We know from audiograms that the hearing range for belugas is from 125 Hz to 120-150 kHz (Awbrey, Thomas, & Kastelein, 1988; Castellote et al., 2014). The availability of audiograms or acoustic data is important for supporting the findings in an analysis of hearing and cochlear morphology. For this study we were fortunate to obtain fresh cochlear samples following subsistence harvesting, providing high quality results. More commonly, when samples are obtained opportunistically tissue degradation 10  due to decomposition can greatly affect the quality and usefulness of the results obtained. For these reasons the beluga whale is a logical species on which to conduct the research described herein.  1.5 Morphological trends in mammalian inner ears There are multiple ways to analyze the organ of Corti, including in cross-section or by examining its surface. To understand more about the inner ear and how the morphology is changing along the cochlear length it is necessary to describe what structures are visible in the SEM micrographs which we used for our analyses. In a vestibular view (i.e. looking down on the surface of the organ of Corti, Fig. 1.1C) the lamina reticularis (the apical portion of the cells of the organ of Corti) can be seen. Visible around each hair cell is the cuticular plate (CP) (Fig. 1.1C) acting to support the stereocilia and delineated from the surrounding area by its smooth appearance (Kössl & Vater, 1995; Pollock & Mcdermott Jr., 2015). The borders of the cuticular plate indicate the edges of an individual hair cell and can be used as a landmark for morphometric measurements. There are various properties and structures of the inner ear, such as the thickness, width and stiffness of the basilar membrane, as well as the length of the hair cells and stereocilia, which vary with frequency and their location along the cochlear length (Dallos, 1992; Dong & Olson, 2009; Lim, 1986; Raphael & Altschuler, 2003; Von Békésy, 1960). It would logically follow that the arrangement of these cells and perhaps their shape would also vary depending on the location and frequencies detected by the hair cells. Work by Yarin et al. (2014) showed exactly this in the guinea pig, the only species for which a morphometric map has been created to date. Seventy-four parameters were measured at ten locations along the cochlear length, showing 11  variation that corresponds to the tonotopic organization of the hair cells. The micromechanics of the hair cells in the inner ear, as well as the fluid dynamics, vary with hair cell structure and the arrangement of the stereocilia (Ciganović, Wolde-Kidan, & Reichenbach, 2017; Lim, 1986; Lim, 1980).    1.6 Frequency mapping techniques  In 1961, Georg von Békésy won the Nobel Prize for his work on the mechanics of the inner ear and introduced the concept of tonotopic organization or frequency-place coding. This refers to the fact that the hair cells at particular locations in the cochlea are coded for or most sensitive to detecting certain frequencies (Von Békésy, 1960). Frequency-place maps commonly known as (cochlear) frequency maps are traditionally termed either anatomical maps or physiological maps (Müller, Hoidis, & Smolders, 2010). Anatomical maps typically involve exposing an animal to sound and then matching the frequencies with the resultant lesions that are indicative of hearing damage from overexposure to sound (Müller & Smolders, 2005; Ou et al., 2000). Physiological maps are commonly created by injecting horseradish peroxidase (HRP), a retrograde marker, into specific nerve fibers of known frequency coding at the level of the cochlear nucleus of the brain stem. By observing the innervation that it is labelled at the level of the cochlea, it is known which region encodes for each frequencies (Müller et al., 2010; Nachtigall & Moore, 1988; Vater, Feng, & Betz, 1985). The creation of both types of maps, involves euthanizing the animal to determine the location of the frequencies detected within the cochlea. These techniques cannot be used in all species, including marine mammals, for ethical reasons. As a result, we must study other echolocating species and use the information from their frequency maps to extrapolate these data to create frequency maps for marine mammals, and 12  other species of echolocating mammals. Given that frequency maps are important for understanding more about hearing, as well as the effects of anthropogenic sound, it is necessary to consider an alternate method such as morphometric analyses (Yarin et al., 2014).   1.7 Morphology and morphometrics First developed by Donald Greenwood in 1961, the Greenwood function (Greenwood, 1961, 1974, 1990), is a  formula that calculates the location at which frequencies are detected based on basilar length. This formula has been updated and is currently based on information from several species of mammals including humans, chinchilla, and guinea pigs, among others. Unfortunately, this function does not hold true for high or low frequency specialists (Ketten, 1997). However, the sensory cells of the organ of Corti in mammals are tonotopically organized (Dong & Olson, 2009; Pollack & Casseday, 1989; Von Békésy, 1960). The apex of the cochlea is sensitive to low frequencies, while the base is sensitive to high frequencies. The change in the frequencies along the cochlear length, although linked to specific locations, is not a linear relationship. Since we know that there is relationship between location and frequency it would make sense that the morphometrics and hair cell shape would also change with frequency. Morphometric measurements refer to either traditional morphometrics or geometric morphometrics (GMs) (Parsons, Robinson, & Hrbek, 2003; Rohlf & Marcus, 1993; Webster & Sheets, 2010). Traditional morphometrics use linear measurements including angles, to quantify the morphology of structures and organisms. Traditional morphometrics have been used in the analysis of the cuticular plate of the sensory hair cells in the cochlea of the guinea pig (Yarin et al., 2014). GMs use landmark (LM) coordinates to analyze the geometry or shape of an organism or its structures. This method gives us more information about the relationships between LMs 13  rather than strictly the linear measurements and may be easier to visualize. Additionally, GM analyses remove the variation in the data due to scale, orientation, or position, leaving only the shape data to analyze. From here on in this thesis, traditional morphometrics will be referred to simply as morphometrics, and GMs will indicate geometric morphometrics.  Both types of morphometrics give us different information, and may be used in conjunction to complement each other, not necessarily to replace one method with the other.   1.8 Research objectives The research done for this thesis addresses the following objectives: 1) To characterize the cochlear morphology and hair cell variation in the beluga whale (D. leucas). 2) To characterize the morphology of the cuticular plate (CP) of the beluga whale (D. leucas) cochlea using morphometrics.  3) To characterize the morphology of the cuticular plate (CP) of the sensory hair cells of Parnell’s mustached bats (P. parnellii) by taking measurements along the cochlear spiral and correlating these measurements with the encoding frequency of each location. 4) To produce the first frequency mapping predictions for the beluga whale (D. leucas) using morphometric measurements from Parnell’s mustached bats (P. parnellii) and Wistar rats (Rattus norvegicus).  In Chapter 2, we define the cochlear morphology and the variation in the hair cells in the beluga whale. We explain how the hair cells are arranged along the cochlear spiral of the beluga whale and compare it to that of terrestrial mammals. We describe the variation in the width, spacing, and density of the hair cells, from apex to base on the organ of Corti. Since this has not 14  been done previously, it is an important step in determining the normal morphology of the beluga whale cochlea.  Following the initial description of the cochlear morphology of the beluga, we build on this knowledge in Chapter 3, using morphometric and GM analyses, and incorporating data from two terrestrial species. First, we utilized morphometrics to analyze the variation in eight parameters of the sensory hair cells (n = 22 total parameters, (n = 7 x 3 rows + 1), eight parameters from the IHCs and OHCs, one of which was a single measurement) (Fig. 3.2) in cochleas from Parnell’s mustached bat. The results from the GM analysis in the bats are also reported. We then describe a similar analysis of the eight morphometric parameters in the beluga whale cochlea. Next, we compared these two species. However, to cover the full hearing range of the beluga whale, we also analyzed the morphometrics of a rat cochlea up to a frequency of 25 kHz. We then used these results from the two terrestrial species to create the first prediction of a cochlear frequency map for the beluga whale.    15  Chapter 2: Description of cochlear morphology and hair cell variation in the beluga whale1  2.1  Introduction Ice cover in the Arctic is decreasing (Lei et al., 2015) and, as a result, additional areas of the ocean, previously difficult to reach, are becoming more accessible to both humans and animals. This opening up of seaways is expected to result in increased shipping traffic, seismic oil exploration, and other anthropogenic activities, which will in turn result in alterations in the Arctic soundscape. Decreased ice cover can also factor into these changes, as the presence of ice can act as a barrier, preventing sounds transmitted in the air from entering the ocean (Roth, 2008). It is important to consider how this is affecting populations of marine life, including marine mammals such as beluga whales (Delphinapterus leucas Pallas, 1776). To understand future impacts, we need to understand the current health status of these animals. Regarding the beluga whale, a species that is completely dependent on its hearing for all aspects of daily life, we need to understand the morphology of their inner ear in order to recognize hearing damage or acoustic trauma if, or when, we find it.  Some of the features already described for various odontocetes, or toothed whales, include the length, thickness, and width of the basilar membrane, density of cells in the cochlea, and information about the ganglion cells and nerves. However, concerning beluga whales, there is an absence of any general description of the morphology of the organ of Corti. Much of the                                                  1 Girdlestone, C. D., Piscitelli-Doshkov, M. A., Ostertag, S. K., Morell, M., & Shadwick, R. E. (2018). Description of cochlear morphology and hair cell variation in the beluga whale. Arctic Science, DOI: 10.1139/AS-2017-0031. 16  currently ongoing work reflects the importance of understanding beluga hearing – their hearing range and acuity, behavioural effects of anthropogenic sound, and the mechanisms involved in sound production and reception used for echolocation (Castellote et al., 2014; Wartzok, Popper, Gordon, & Merrill, 2003). We are particularly interested in the reception of sound and how the hair cells and their morphometrics relate to their hearing ability. However, it is also important to understand what normal baselines and their basic morphology consist of to further understand other aspects of beluga hearing. Here we describe morphological features of the beluga whale inner ear, specifically the hair cells of the organ of Corti. In addition to this, recommended methods of fixation and decalcification are addressed to further enable the successful analysis of cochlear samples for this and other species of marine mammals.  2.2 Methods 2.2.1 Extraction and Fixation Beluga whale ear samples (right and left) were collected from four individuals (n=8), harvested in 2014 at Hendrickson Island, Northwest Territories, Canada, as part of subsistence harvesting. Prior to the start of the sampling season, all required permits were obtained as follows: Aurora Research Institute (ARI) licence No. 15467, Department of Fisheries and Oceans (DFO) fishing licence No. S-14/15-3019-YK, Marine Mammal Transport licence #18843, and Environmental Impact Screening Committee (EISC) #03-14-03. Ear samples were extracted in the field and fixed within one and a half to five hours post-mortem for each individual (Appendix A.1). The shorter the window of time post-mortem, in which the samples are fixed, the better, to minimize deterioration. Fresh samples such as these can in turn yield more reliable results than samples collected opportunistically and in varying, 17  unknown stages of decomposition. Samples were extracted and subsequently fixed using one of three solutions: 10% neutral buffered formalin (NBF) or 2.5% glutaraldehyde in 0.1 mol/L phosphate buffer (pH 7.4) or alternatively 2.5% glutaraldehyde in 0.1 mol/L cacodylate buffer (pH 7.3) according to the protocol by Morell and André (2009). Once the ear samples were fixed, they were shipped for further laboratory analysis to the University of British Columbia, Vancouver, British Columbia, Canada. 2.2.2 Decalcification Following fixation of the samples, the periotic bone that surrounds the cochlea was decalcified. Decalcification was only required to the point at which the vestibular scala and the stria vascularis were visible. This was done using one of two treatment options (Appendix A.1). The first solution used was 14% ethylenediaminetetraacetic acid (EDTA) tetrasodium salt, (pH 7.4) as described by Morell and colleagues (Morell et al., 2015, 2017). A second solution that was used on some of the samples was RDO® (Apex Engineering Products, Aurora, Illinois, USA), a rapid decalcifier. Decalcification was achieved by initially placing the sample in 50% RDO® (diluted with distilled water) for 24 hours, at which point the sample was moved to 25% RDO® (diluted with distilled water) as described in Morell et al. (2009). 2.2.3 Scanning electron microscopy – dissection and processing Once the cochlear samples were suitably decalcified, they were dissected with the vestibular scala and the stria vascularis sectioned, and both Reissner’s membrane and the tectorial membrane removed. Samples were then dehydrated using ethanol, gradually increasing the concentration until reaching 100 percent. Once dehydrated, the cochlear samples were critical point dried using CO2 and sputter coated with either gold-palladium or platinum-palladium in 18  preparation for imaging in a Hitachi S-4700 scanning electron microscope (SEM) at the University of British Columbia Bioimaging Facility, Vancouver, British Columbia, Canada. 2.2.4 Image analysis and morphometry  SEM micrographs were adjusted for brightness and contrast using Adobe Photoshop® CS3. Measurements of the cochlear structures were made using ImageJ® software. Since the shape of the entire cochlea is more ovoid than round, there is both a minimum and a maximum diameter (i.e. minimum and maximum distance between the outer margins of the spiral ligament) (Fig. 1.1A). The cochlear diameter was calculated by taking the mean of these two measurements for each cochlea. Cochlear length was measured at the level of the limit between the first row of OHCs and inner pillar cells using an average of 85 flat SEM micrographs per each ear. The length to be measured in each image was delineated prior to measuring to ensure an accurate length with no overlap or gaps.  The average number of hair cells per 100 µm was calculated for each of the apex, middle, and base regions of the cochlear samples. For the purposes of this paper, the apex region was defined as the first 33% of the cochlear length (closest to the inner point of the cochlea). The middle region refers to the next 33% to 66% and the base region to the last 34% of the cochlear length. These averages were then used to extrapolate the total number of hair cells (both outer and inner) per cochlea.   Both the area and cell width measurements were calculated using ImageJ® (Fig. 1.1C). The distance between the IHCs and third row of OHCs was also measured and compared among all three regions. 19   Mean cell width, distance from IHC to OHC3, and cell density were statistically analyzed using a one-way ANOVA, followed by a Tukey HSD post-hoc test.  2.3 Results  Several methods of fixation and decalcification were examined to further enable the successful analysis of cochlear samples for this and other species of marine mammals. During the fixation process, when 10% NBF was used, the end quality of the samples was comparable with those fixed with 2.5% glutaraldehyde (Fig. 2.1). In the one beluga in our study, for which one ear was treated with EDTA and the other with RDO®, we found that the cochlea that was decalcified with EDTA was slightly better preserved (Fig. 2.2).  Figure 2.1 Scanning electron micrographs showing fixation using (A) 10% neutral buffered formalin and (B) 2.5% glutaraldehyde in 0.1 mol/L cacodylate buffer, pH 7.3.  Cochlear samples of both ears from four adult beluga whales (n = 8) were analyzed to determine the cochlear diameter, cochlear turns, total cochlear length, and hair cell count as well as to compare any variation in the width of the hair cells between the apex, middle, and base 20  regions of each cochlea. The comparisons measured the density of the OHCs, cell width for both the IHCs and OHCs, and the distance between the IHCs and third row of OHCs.   Figure 2.2 Scanning electron micrographs of beluga cochleas decalcified using (A) EDTA and (B) RDO®. The average cochlear diameter was determined to be 14.6 mm. The samples in this study all had two cochlear turns. The mean cochlear length (measured along the limit between the first row of OHCs and the inner pillar cells) for these samples was calculated to be 41.3 mm, with a range of 39.5 mm to 42.6 mm. In addition to examining the whole cochlea, we compared the hair cells of the apex, or centremost point of the cochlea, with those in the middle section and the base, or outermost area of the cochlea, closest to the stapes. The cells sampled were from these three regions, each of which covered a distance of 33% of the cochlear length. There was some degree of variation in the cells of the three regions (Fig. 2.3) as well as variation even within the apex region (Fig. 2.3A and 2.3B). In the apex, the mean cell width of IHCs was found to be 8.0 µm, while the mean width of the OHCs was 5.8 µm (Table 2.1). With statistical analysis both the IHCs and OHCs were 21  found to be significantly different from those in the middle and base regions (P<0.01), However, in each region, the IHCs and OHCs were not significantly different from each other.  The mean cell widths were similar among the three rows of OHCs, ranging from 5.3 – 6.0 µm (Fig. 2.4). In comparison, the IHCs had a mean width of 9.7 µm in the middle region of the cochlea. The mean of the OHCs in this region was 8.6 µm, with the mean ranging from 8.4 – 8.7 µm. Similarly, to the middle region, the IHCs of the base region had a mean width of 9.7 µm. While again comparable with the cells in the middle region, but in contrast with the cells in the apex region, the mean width of the OHCs in the base was 8.4 µm, the mean ranging from 8.2 – 8.5 µm. The distance between the IHCs and third row of OHCs showed a decrease of 19 µm moving from the apex to the base (Fig. 2.5). This distance was found to be significantly different among each of the three regions (P<0.01). 22   Figure 2.3  Examples of the variation in the morphology of the hair cells from the beluga whale cochlea showing (A and B) hair cells from two locations within the apex region (33% distance from the apex), (C) hair cells in the middle region (located in the range of 33% - 66% of the cochlear length from the apex), and (D) the base region (the last 34% of the cochlea).  Hair cell density between the apex and base was also examined for all four rows (Fig. 2.6). The mean of the measurements for the OHCs in the apex showed a cell density of 148 cells/mm, while in the middle and base regions, the cell density was the same at 117 cells/mm. 23  Statistical analysis showed significant differences (P < 0.01) between the apex and both the middle and base regions for OHC1, OHC2 and the IHCs (P < 0.05 apex vs middle; P < 0.01 apex vs base). For OHC3 there was a significant difference (P < 0.05) between the hair cells of the apex and base. Further analysis showed that in the apex and middle regions, the IHCs were significantly different from each row of OHCs (P < 0.01). The total number of hair cells per cochlea, averaged among samples, was calculated as a range of 2384 – 5494 IHCs and 7151 – 21 695 OHCs (or approximately 2384 – 7232 OHCs in each of the three rows). These wide ranges were calculated using the absolute minimum and maximum cell counts per millimetre of cochlear length in all three regions combined. This was due to the fact that the cell density is not equal among regions or throughout the length of the cochlea.  Table 2.1 Beluga whale mean cochlear measurements (± standard deviation) comparing the inner hair cells (IHCs) and outer hair cells (OHCs) from the apex, middle, and base regions using scanning electron microscopy.      General Location   Apex  Middle  Base Measurement n Range Mean  Range Mean  Range Mean IHC count 36 87 - 136 111 ± 14  85 - 104 93 ± 7  59 - 118 88 ± 21 Total number of IHCs (whole cochlea) 36 2384 - 5494 OHC1 count 41 114 - 179 151 ± 21  104 - 132 117 ± 9  71 - 156 117 ± 31 OHC2 count 41 118 - 179 150 ± 20  104 - 132 117 ± 9  71 - 156 117 ± 31 OHC3 count 41   59 - 179 143 ± 27  102 - 132   116 ± 10  71 - 156 117 ± 31 Total number of OHCs (per row) 41 2384 - 7232 Total number of OHCs (whole cochlea) 41 7151 – 21 695 IHC width (µm) 175 6.0 - 9.8 8.0 ± 0.9  8.0 - 11.8 9.7 ± 1.0     7.1 - 12.0 9.7 ± 1.3 OHC1 width (µm) 241 4.0 - 7.6 6.0 ± 0.7  7.4 - 10.5 8.7 ± 0.7  6.5 - 10.4 8.5 ± 1.1 OHC2 width (µm) 227 4.1 - 8.5 5.9 ± 0.9  7.1 - 10.1 8.6 ± 0.7  6.1 - 10.2 8.3 ± 1.2 OHC3 width (µm) 200 3.7 - 7.2 5.3 ± 0.8  6.3 - 10.8 8.4 ± 1.0  6.5 - 9.2 8.2 ± 0.8 Mean OHC width (µm) 668 - 5.8 ± 0.8  -   8.6 ± 0.8  - 8.4 ± 1.1 IHC-OHC3 distance (µm) 131 21.8 - 41.8 34.7 ± 3.9  15.0 - 27.7  22.9 ± 4.3  15.2 - 16.4 15.7 ± 0.6    Note: Cell counts are measured in (cells/mm); mean cochlear length was 41.3 mm 24  2.4 Discussion  The goal of this research was twofold: to determine how to best process cochlear samples to preserve their quality, especially in field conditions, and to examine the morphology of the inner ear of the beluga whale.   High quality samples are essential to analyze cochlear samples and obtain reliable results about the morphometry and structures present. For sample fixation, since we obtained similar results with all fixative solutions, the use of 10% NBF is recommended, as it is widely available and effective for fixing samples (Fig. 2.1). The benefits of 10% NBF for stranding networks worldwide are its easy accessibility, it is already in use for the fixation of all other organs, and it has a lower toxicity than glutaraldehyde.  Figure 2.4  Beluga whale mean hair cell width ± standard deviation of the inner hair cells (IHC) and outer hair cells (OHC) in each of the corresponding regions (apex, middle, and base) within the cochlea (* P<0.01).  * * 25   The dehydration process, using 90 - 100% ethanol, required for viewing samples in the SEM can result in tissue shrinkage of the sample compared to a sample in a fresh state (Edge et al., 1998). The amount of shrinkage that occurs when using formaldehyde has been documented as not being statistically significant (Edge et al., 1998). Since we expect the shrinkage of the organ of Corti and potential distortion of the structures due to fixation to be homogeneous throughout the spiral (Yarin et al., 2014), the shape of its cells would be largely preserved.  We recommend EDTA as our preferred solution for decalcifying samples, recognizing that the process is longer yet yields slightly higher quality results (Fig. 2.2). It also preserves the quality of the soft tissue in the cochlea, which is crucial when examining fine structures and cell morphology. Our sample size was too small to say definitively if there was a difference in the beluga ear samples, as only one individual had decalcification done using different solutions on each ear. However, this result was confirmed in previous studies on other species of cetaceans, where there was either no difference or EDTA was slightly better (M. Morell, unpublished data). When the results from analyzing a particular sample are required in a timelier manner, we recommend the use of RDO®, which is a rapid decalcifying agent. If lesions, indicative of noise-induced hearing loss (or hearing impairment due to other etiologies), are present, they can still be detected when either EDTA or RDO® is used. Maintaining sample quality is essential for determining more accurately the importance and the function of both cochlear structures and morphometrics.  26   Figure 2.5  Beluga whale mean distance ± standard deviation from the inner hair cells (IHC) to the third row of outer hair cells (OHC3) in each of the corresponding regions (apex, middle, and base) within the cochlea (* P<0.01).   Figure 2.6  Beluga whale mean hair cell density ± standard deviation of the inner hair cells (IHC) and outer hair cells (OHC) in each of the corresponding regions (apex, middle, and base) within the cochlea  (a, b, c, d, ¤, * P<0.01; ¥, § P<0.05). * * * 27  We examined the basic structural organization to identify normal baselines and to help us understand how anthropogenic activities and the changing environment might impact beluga whales. Understanding the morphology of normal ears in beluga whales is essential for recognizing pathology or damage if or when it is detected.   As in other terrestrial and marine mammals, the standard cellular arrangement of a single row of IHCs and three parallel rows of OHCs was present in each cochlea. The mean length of the beluga cochleas that we examined (41 mm) was comparable with the basilar membrane length (42 mm) of beluga cochleas described by Ketten (2000). The length of the cochlea, but not the width, typically exhibits a positive correlation with body size, although this relationship is not as strong in the beluga as it is in other mammals (Ketten, 1992a).   The number of cochlear turns varies among species of odontocetes and can range from 1.5 up to 2.5 turns (Ketten, 1992a; Ketten & Wartzok, 1990; Solntseva, 2010). The number of turns found in our samples was two, which corresponds to previous work by Sensor et al. (2015) in which they found 1.75 - 2 turns in the ears of beluga whales. Ketten and Wartzok (1990) categorized marine species as specialists with two distinct cochlear morphologies, separated into Type I (high frequency) and Type II (low frequency) (reviewed in Ketten, 1992a, 1992b). Under this distinction, beluga whales are classified as Type I odontocetes.  Hair cell density and counts have not been previously discussed for beluga whales. Instead, earlier work describes the density and counts of the spiral ganglion cells or afferent neuron cell body counts(Gao & Zhou, 1992; Ketten, 2000; Sensor et al., 2015). In our study, the total number of hair cells (inner and outer combined) was conservatively calculated to be 9535 – 28927 based on absolute minimum and maximum counts. The average number of IHCs calculated in our beluga samples was 3939 ± 1555, while the average for the OHCs was 14 423 ± 28  7272. The range of these measurements are large due to the variability in cochlear length among individuals as well as sensory cell density in the apex, middle, and base (Table 2.1). These counts are similar to the hair cell counts for the bottlenose dolphin (Tursiops truncatus Montagu, 1821) by Wever et al. (1971b) in which they found 3451 IHCs and 13 923 OHCs in cochleas of similar length (38.5 mm). In addition to interspecies variation, it is also important to consider intraspecies or interindividual variation. Our range is conservative since it was calculated based on minimum versus the maximum potential total number of hair cells, both inner and outer. It is difficult to calculate the inter individual variation of hair cell counts for beluga based on our sample size. However, this research provides a first estimate based on differential hair cell density along the cochlear spiral.  While we did not examine spiral ganglion cell counts, they have been calculated for many species of cetaceans and show a wide range across species, from 68,000 to more than 168,000 (Ketten, 1997). Spiral ganglion cells in cetaceans are much greater in number than in land mammals of comparable cochlear length, which is likely correlated with a greater complexity of information processed by the neurons during echolocation (Ketten & Wartzok, 1990).   The OHC width in the apex, measured by Morell et al. (2015) in other odontocete species, was found to range from 5.04 - 5.6 µm in the striped dolphin (Stenella coeruleoalba Meyen, 1833) and from 5.47 - 6.2 µm in the harbour porpoise (Phocoena phocoena Linnaeus, 1758) and were of the same magnitude as in the beluga. This morphological variation shows that there is indeed some individual variation within a species but also that there are similarities among related species.  In our study, we also show a greater width of the organ of Corti at the apex compared to the base of the cochlea. In addition, there was also a measurable decrease in 29  hair cell density towards the base of the cochlea, as a direct result of the increased cell width. There is a tonotopic distribution of the organ of Corti along the cochlear spiral in mammals. The apex of the cochlea is where lower frequencies are encoded, while the base of the cochlea is where high frequencies are encoded. The frequencies that are encoded in a particular region depend on the stiffness of the basilar membrane (Dong & Olson, 2009; Von Békésy, 1960). However, other studies from terrestrial mammals show a relationship between the coding frequency and other structures such as the length of the OHC body (Dannhof, Roth, & Bruns, 1991; Pujol, Lenoir, Ladrech, Tribillac, & Rebillard, 1992), cross-sectional area of the organ of Corti cells (Schweitzer, Lutz, Hobbs, & Weaver, 1996), ultrastructure of supporting cells (Spicer & Schulte, 1994), or morphometrics of the reticular lamina (Yarin et al., 2014). The morphometrics measured here for sensory cells and the distance between the IHCs and third row of OHCs in the apex of the beluga (Table 2.1, Fig. 2.4 and 2.5) are consistent with those of guinea pig measured from SEM micrographs (Yarin et al., 2014). In the case of the guinea pig, it is well described how several morphometrics of the reticular lamina of the organ of Corti change through the cochlear spiral and how this relates to their frequency map. Our measurements of the apex are of the same magnitude as those found by Yarin and colleagues (2014). This can be explained by the fact that the hearing range of guinea pig extends up to 30 kHz (Tsuji & Liberman, 1997), while beluga whales can hear up to 150 kHz (Castellote et al., 2014). Thus, having information on hair cell morphometrics is necessary for understanding how morphology relates to hearing function specific to each species. Mechanics of the organ of Corti are relatively well described (Chen et al., 2011; Ni, Elliott, & Baumgart, 2016; Lee et al., 2016; Liu, Gracewski, & Nam, 2015; Soons, Ricci, Steele, & Puria, 2015). However, if the morphometrics 30  of the reticular lamina are consistent among species, this may have some biomechanical implications.  2.5 Chapter summary  The study of the morphology and structural changes in cetacean inner ears, specifically beluga whales, lacks description and is of increasing importance given the changes occurring in the arctic both environmentally and due to increased human activity. To our knowledge, this study is the first to describe the morphological variation of the organ of Corti between the apex, middle, and base of the cochlea in the inner ear of the beluga whale. There is a significant decrease in overall hair cell density and increase in hair cell width as we move from the apex to the base. This indicates, as in other mammalian species, that there are trends in the morphology and morphometrics associated with various locations in the cochlea.  Gaining knowledge of the basic morphology can provide us with an understanding of normal baselines, which can further aid us in determining potential impacts and effects of human-made noise on marine mammals such as beluga whales.  31  Chapter 3: Cochlear morphology analysis in bats and belugas, using morphometric and geometric morphometric analyses 3.1 Introduction Many morphological and biomechanical features of the inner ear have been conserved across different species of terrestrial mammals (Echteler et al., 1994; Vater & Kössl, 2011) but there is still a great deal of variation in types of hearing (i.e. generalists versus high frequency specialists) and hearing ranges to investigate. To further our basic understanding of hearing and how anthropogenic sounds may affect animals in various environments it is necessary to use a comparative approach. In particular, a focus on the specific structures contributing to sound reception and processing within the inner ear would be beneficial. Analyzing variations in the morphology of the sensory hair cells across species, as a function of the frequencies which are encoded for along the cochlear length, will provide novel and critically important information. The study of inner ear physiology has given us a wealth of information about many characteristics of the organ of Corti including biomechanics of the basilar membrane and hair cells (Dallos, 1992; Von Békésy, 1960), and the innervation of the hair cells (Raphael & Altschuler, 2003). Morphometric analysis of the reticular lamina of the guinea pig (Yarin et al., 2014) shows variation in the microstructures of the hair cells with respect to location and the frequency encoded for by these cells. Among species, the width of the organ of Corti is comparable, although there is variation in the length. Other frequency related features include the length of the OHC bodies (Dannhof et al., 1991; Pujol et al., 1992), and the length of the supporting cells (Spicer & Schulte, 1994). We want to investigate if this relationship exists between the morphometrics of the cuticular plate and the encoding frequency, across species. 32  Further linking frequency with the morphological variation in the sensory hair cells is of increasing importance, given our need to understand how anthropogenic noise is impacting mammals in both terrestrial and aquatic environments. As discussed in Chapter 1, mammals have many hearing differences yet they share many similarities across species, both in cochlear organization and morphology (Echteler et al., 1994). Mammals that echolocate emit and receive higher frequencies than non-echolocating mammals. For these reasons we have compared the cochlear morphology of Parnell’s mustached bat with that of the beluga whale. Both species use echolocation and high frequencies. Parnell’s mustached bat has a hearing range from 10 kHz to 112 kHz (Kössl, 1994b; Kössl & Vater, 1996) and the beluga whale from 125 Hz to 120-150 kHz (Awbrey et al., 1988, Castellote et al., 2014). In addition to this, Parnell’s mustached bat has a cochlear frequency map already in place (Kössl & Vater, 1985). This area of the cochlea, with regards to the sensory hair cells, is under studied and is of increasing importance due to the global increase of man-made underwater noise including newly accessible areas such as the Arctic. Further knowledge on the normal baselines of cochlear morphology, as well as creating frequency maps for various species, will help us to better understand both hearing and the impact of anthropogenic sound on mammals. Analyzing the morphology of the hair cells of the organ of Corti using both morphometrics and GMs will give a greater understanding of the cochlear mechanics and the cellular organization. Using acoustic data from marine mammals as well as from mammals currently with frequency maps can support new findings and help us to make accurate determinations of which morphometrics are biologically relevant and connected to the 33  frequencies detected. These techniques will also be useful in exploring the highly specialized modes of echolocation found among mammals.  The knowledge gained by comparing morphometric measurements to existing frequency maps, is further strengthened by the availability of acoustic data from living animals. Comparing morphometrics between species can further support and give us greater insight to the details of how hearing functions and the differences and similarities between specialists and generalists as well as between terrestrial and marine species.  3.2 Methods Cochlear samples (Fig. 3.1) from the inner ears of Parnell’s mustached bat (Pteronotus parnellii), were collected from six adult individuals (from the Cuban population). Only one cochlea per bat was analyzed, except for one individual (Bat05) in which both cochleas were measured. Three of these cochleas were from left ears, while four were from right ears (n=7). After extraction, these cochlear samples were perfused intracardially at a rate of 4 ml/minute for five minutes with 0.9% NaCl, and for thirty minutes with 4% paraformaldehyde in 0.1 mol/L phosphate buffer. The Institute of Cell Biology and Neuroscience, Goethe University, Germany provided these samples. All experiments described herein were carried out in accordance with current laws for animal experimentation in Germany (Regierungspräsidium Darmstadt) and according to the Declaration of Helsinki. 34   Figure 3.1 Scanning electron micrograph of a bat cochlea showing the cochlear turns. The processing was similar to the methods described in sub-section 2.2.2, with decalcification taking place over a period of 13 hours, using 14% EDTA tetrasodium salt (pH 7.4 for the bat cochleas) followed by dissection, as described in sub-section 2.2.3. Dehydration was carried out by increasing concentrations of ethanol up to 100%. These samples were also critical point dried and were then sputter coated with gold in preparation for imaging in an Hitachi S-4700 (UBC Bioimaging Facility) and Hitachi S-4000 (COMET, Montpellier Ressources Imagerie) SEM.  Cochlear samples from two Wistar rats (Rattus norvegicus) were fixed with 3.5% glutaraldehyde in 0.1 mol/L phosphate buffer (pH 7.3) at room temperature. Cochleas were first perfused with the fixative through the round and oval windows and then immersed in the fixative for at least one hour. Cochlear samples were dissected and prepared for imaging in the SEM as described in Chapter 2, sub-sections 2.2.2 and 2.2.3. Marc Lenoir from the Institute for 35  Neurosciences of Montpellier provided the rat cochleas. Experiments were carried out in accordance with the animal welfare guidelines of the Institut National de la Santé et de la Recherche Médicale and approved by the French Ministère de l’Agriculture et de la Forêt.   3.2.1 Image analysis As in sub-section 2.2.4, the brightness and contrast of the SEM micrographs were adjusted using Adobe Photoshop® CS3.  Morphometric measurements of the cochlear structures were made using ImageJ© software (Rasband, 1997), while geometric morphometric measurements were acquired using tpsUtil, tpsDig2 (Rohlf, 2004b, 2004a), and MorphoJ© (Klingenberg, 2011) software. Additional analyses of the geometric morphometric measurements were performed in R 3.5.0. using the geomorph package (Adams, Collyer, & Kaliontzopoulou, 2018).  3.2.2 Morphometric analysis Morphometric measurements were obtained from the cochleas of a beluga whale (n = 1 for all parameters, n = 6 for the five parameters described in sub-section 3.3.3), mustached bats (n = 6) and a rat (n = 1). These measurements were taken using the same procedure in all three species.  Cochlear lengths were calculated for the mustached bats (n=7) and rats (n=2) along the limit between the first row of OHCs and the inner pillar cells, using the same methods described for the beluga whale cochleas in sub-section 2.2.4. An average of 43 flat SEM micrographs were measured per bat cochlea, and an average of 24 flat SEM micrographs per rat cochlea. The cochleas were tilted under the microscope to obtain a flat micrograph from a spiral structure. 36   Figure 3.2 The parameters measured using morphometrics. (A) The distance from IHC to OHC3, (B) the distance between the rows of hair cells (IHC - OHC1, as well as among rows of OHCs), (C) cuticular plate length of the OHCs, (D) cuticular plate width of the OHCs, (E) the distance between the stereocilia bundle tips of the OHCs, (F) gap width between stereocilia bundles of the OHCs, (G) the length of the side of the stereocilia bundles in the OHCs, and (H) the inner angle of the stereocilia bundles of the OHCs.  Following the methods used in recent work by Yarin et al. (2014), analyzing morphometrics, we measured eight parameters of the IHCs and the OHCs, as well as the length of the stereocilia of the OHCs (n = 25 total parameters, (n = 8x3 +1), as one parameter was a single measurement). Depending on which row the cells are measured in each parameter has three designations, for example parameter F – mean gap width, is comprised of F1, F2, and F3.  The parameters measured (Fig. 3.2) were the distance from IHC to OHC3 (A), the distance between the rows of hair cells, (IHC - OHC1, as well as among rows of OHCs) (B), the cuticular 37  plate (CP) (i.e. apical portion of the cell) length of the OHCs (C), the CP width of the OHCs (D), the distance between the stereocilia bundle (SB) tips of the OHCs (E), the width of the gap between SBs of the OHCs (F), the length of the side of the SBs in the OHCs (G), and the inner angle of the SBs of the OHCs (H). Except for the distance from the IHCs to the row of OHC3s (A) (the width of the organ of Corti), and the distances between each row of cells (IHC-OHC1, OHC1-OHC2, and OHC2-OHC3) (B), all measurements were taken in each of the three rows of OHCs. The exact locations at which these parameters were measured varied within our cochlear samples. This variation resulted from the condition of the organ of Corti samples and the ability to take images at each location due to the angle of the region because of the curvature of the cochlea. In the analyses and graphing of these data, points covering a small range of locations were grouped to obtain average values. From 0% up to 10% of the distance along the cochlear length, data were grouped by a single percent (i.e. 0-1%, 1-2%, and so on) since this is the region of the cochlea where the highest morphological variation is observed. From the distance of 10% to 100%, data points were averaged in a range of five percent (i.e. 10-15%, 15-20%, etc.). In the beluga whale cochleas, while images were taken from 21 different locations, morphometric measurements were taken from between 5 – 14 locations per cochlea. The region analyzed ranged from 3.3% to 99.7% distance from the apex.  Multiple measurements were taken of individual cell parameters from each row of OHCs, at each location. In the mustached bat cochlear samples, 5 to 13 locations were analyzed in each of the cochleas. These locations covered the area of the organ of Corti from 0.4% to 99.1% distance from the apex. The cochlear sample from the rat had morphometrics analyzed at six locations along the cochlea, reaching from the apex to a distance along the cochlear length of 65% from the apex. Statistical analysis 38  of the datasets in figures 3.4-3.10 and 3.11-3.17 was carried out using linear regression. Figures 3.6 and 3.7, were also analyzed using a one-way ANOVA, and a Tukey HSD post-hoc test. In addition to the parameters described above, the stereocilia lengths were also measured in the beluga whales and the mustached bats. Our methodology differed from that of Yarin et al. (2014) who used two images, knowing the angular difference between the two, to calculate a “true length”. In our analysis, we initially attempted to replicate this method. We found that when we compared this measurement to the length of the stereocilia imaged straight on, from a viewpoint parallel to the stereocilia, and having a flat image of the stereocilia – there was no significant difference in the lengths. Therefore, moving forward we took just one image per area for analysis. The cochlear measurements for the morphometric analyses were also analyzed using machine learning techniques. Machine learning is a type of artificial intelligence, in which the computer uses algorithms to “learn” patterns based on sample data entered and by running numerous repetitions (El Naqa & Murphy, 2015). Machine learning may be supervised (data and desired outcomes are provided) or unsupervised (only the sample data is entered, and the computer looks for patterns on its own). Repeatedly running an algorithm, “teaches” the computer, so it becomes better at achieving the desired outcome. At this point, novel data can be introduced and analyzed. Of all the algorithms we tested, we chose the one with the least error which produced the most logical prediction.  Based on an initial determination of the estimated error, which was used to discard the least applicable techniques, results were plotted from those which there was the least amount of error. These results were then compared to the morphological observations and published audiograms to determine if they were in agreement. We assessed the following types of techniques: 1) neural networks, 2) random forest, 3) support 39  vector machine (using different shapes of the regression: linear, polynomial, logarithmic, and exponential), and 4) multiple linear regression. Statistical analysis was programmed and performed with R software (version 3.4.4).  3.2.3 Geometric morphometric analysis Geometric morphometrics were used only for the mustached bats. Using the software tpsDig2 (Rohlf, 2004a) cells were digitized in blocks of 12 cells (three IHCs and nine OHCs, consisting of three OHCs in each of the three rows) (Fig. 3.3). These groups of cells were separated into individual cells during the analysis. The LMs chosen (Appendix B.1 and Fig. 3.3) were selected to capture the variation in the hair cell shapes. The IHCs were digitized using four LMs to capture their shape, while each OHC was digitized with five LMs. The fifth LM was included to mark the lower point of the SB, to test whether there was a significant change in its position along the cochlear length. However, this LM was not included in all the analyses as we wanted to focus only on the cell shape. These measurements were taken from 10 equidistant locations along the length of the cochleas, spaced apart at increments of 10% of the cochlear length from 5% to 95%. Each designated location included a range of two percent above and below the location represented. For example, the location of five percent distance represents a range of three percent to seven percent of the distance of the cochlea from the apex. As described earlier, due to the condition of the organ of Corti at the various locations and the angle of the surface with respect to the SEM lens, not all locations could be analyzed in each cochlea. 40   Figure 3.3 The landmarks used for geometric morphometrics. The landmarks denoted in green were not used during the principal component analysis.  3.3 Results 3.3.1 Morphometric analysis in the mustached bat  The cochlear length was calculated using the cochlear samples from six adult mustached bats (n=7, since both the left and right cochleas for individual Bat05 were measured). The mean cochlear length ranged from 8.90 mm to 11.68 mm with a mean of 10.53 mm. The cochlear samples we analyzed possessed two and a half cochlear turns which is in agreement with 41  previous findings (Kössl & Vater, 1985). The organ of Corti of Parnell’s mustached bat has been thoroughly described in previous research (Kössl, 1994a; Kössl & Vater, 1985, 1990a; Vater & Kössl, 1996). As in other terrestrial mammals, the hair cells are arranged in rows parallel to each other, with a single row of IHCs and three rows of OHCs. Also, as in other terrestrial mammals, there is visible variation in the hair cell spacing and morphometric parameters from the apex to the base.  We measured eight morphometric parameters of the IHCs and OHCs (n = 22 total parameters, (n = 7x3 +1), measured among the IHCs and OHCs, with one parameter being a single measurement) in the cochlear samples from six adult Parnell’s mustached bats (n=6, Fig 3.2). Not all of these parameters changed with respect to their position along the cochlear length, however the following parameters (Fig. 3.2) showed the most variation : A (the mean distance from IHC-OHC3) (Fig. 3.4); B (the mean distance between the rows of hair cells) (Fig. 3.5); D (the mean width of the cuticular plate (CP) of the OHCs) (Fig. 3.6), E (the mean distance between the SB tips of the OHCs) (Fig. 3.7), F (the mean width of the gap between SBs of the OHCs) (Fig. 3.8), and H (the mean inner angle of the SBs of the OHCs) (Fig. 3.9).  The distance from the IHC to OHC3 (Fig. 3.4) decreased by 12.23 µm from the apex to the base (measured at 97.5% distance along the cochlear length from the apex) and was statistically significant at P=<0.0001. Closest to the apex (0.4% cochlear length from the apex), the mean distance was 26.5 µm, while close to the base (between 95% and 100% of cochlear length from the apex), the mean distance was 14.26 µm. There were two peaks in these data, where the distance from the IHC to OHC3 at 10% and 42.5% increased to 28.69 µm and 27.94 µm respectively.  42   Figure 3.4. The mean distance (± standard deviation) between the inner hair cells (IHCs) to the third row of outer hair cells (OHC3, Parameter A, Figure 3.2) corresponding to the percent distance from the apex, along the cochlear length in Parnell’s mustached bat (n=6) (P=<0.0001). Closest to the apex, parameter B (distance between rows of hair cells, Fig. 3.5) was 14.23 µm (IHC-OHC1), 5.73 µm (OHC1-OHC2), and 4.01 µm (OHC2 – OHC3). Each of these distances decreased significantly from apex to base (IHC-OHC1 P=<0.0001; OHC1-OHC2 P= <0.01; OHC2-OHC3 P=<0.0001) and differed significantly from each other (P=<0.01). Closest to the base these distances had decreased, in the same order, 8.12 µm, 3.28 µm, and 1.70 µm. This shows an overall decrease of these distances, along the cochlear length, of 6.11 µm (IHC-OHC1), 2.45 µm (OHC2-OHC3), and 2.31 µm (OHC2-OHC3).   43   Figure 3.5. The mean distance (± standard deviation) between each row of hair cells (Parameter B, Fig. 3.2). Shown are the distances between the inner hair cells (IHC) and the first row of outer hair cells (OHC1) (P=<0.0001), the distance between the first and second row of outer hair cells (OHC1-OHC2, P=<0.01), and the distance between the second and third row of outer hair cells (OHC2-OHC3, P=<0.0001). These distances are shown corresponding to the percent distance from the apex, along the cochlear length in Parnell’s mustached bat (n=6). Each mean distance was significantly different from the others (P=<0.01). Alternatively, parameters D to H, were measured in each of the three rows of OHCs and showed a high degree of similarity regardless of which row the hair cells were in (Figs. 3.6, 3.7, 3.8, and 3.9). Significant differences were present between the apex and the base in each of these four parameters (P=<0.001, except for parameter E which had a P=<0.05). Parameters D (CP width), E (distance between SB tips), and H (SB inner angle) (Figs. 3.6, 3.7, and 3.9) are reduced between 35 – 70% of cochlear length. This corresponds to the known acoustic fovea of mustached bats, located between 40 and 60% of the cochlear length, which detects sound around the frequency of 61.5 kHz (Kössl, 1994a). Beyond 70% these lengths decrease toward the base.  44  Parameter D (OHC width) (Fig. 3.6) shows an overall increase from apex to base despite the fluctuations along the cochlear length. The hair cell width in OHC1 increased from 3.88 µm to 5.35 µm, in OHC2 from 4.14 µm to 5.15 µm, and in OHC3 from 4.07 µm to 5.39 µm. The change from apex to base was significant (P=<0.001). The variation in these data was also significantly different at distances of 35, 50, and 70% from the apex.   Figure 3.6. The mean width of the hair cell cuticular plate (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter D, Fig. 3.2). These distances are shown corresponding to the percent distance from the apex, along the cochlear length in Parnell’s mustached bat (n=6). P=<0.001. Parameter E (the distance between SB tips) (Fig 3.7), which is a measurement of the width of OHCs plus the distance between these cells among the same row, fluctuated along the cochlear length in a similar pattern to D and H, and was found to be significant although to a lesser degree than other parameters, as P=<0.05. The change from apex to base was significant (P=<0.001). The variation in these data for parameter E was also significantly different at 45  distances of 35, 50, and 70% from the apex. The mean distances in OHC1 ranged from 5.13 µm to 5.21 µm, in OHC2 from 5.32 µm to 5.09 µm, and in OHC3 from 5.83 µm to 5.14 µm.    Figure 3.7. The mean distance between stereocilia bundle tips (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter E, Fig. 3.2). These distances are shown corresponding to the percent distance from the apex, along the cochlear length in Parnell’s mustached bat (n=6). P=<0.05. Parameter H (inner angle of the OHC SB) (Fig. 3.9) showed some variability between the three rows of OHCs around 1% distance from the apex, but increased significantly overall from apex to base (P=<0.0005). The mean inner angle increased for OHC1 from 89.06˚ to 102.68˚, but unexpectedly decreased in the other two rows, in OHC2 from 112.0˚ to 99.12˚, and in OHC3 from 113.05˚ to 110.07˚.  Looking more closely at these data showed these values from the apex resulted from the one bat for which there were measurements made at this location. The OHC1 looked typical, however those from OHC2 and OHC3 were flatter and wider as expected of hair 46  cells closer to the base. Removing this one location, from one individual, from the dataset results in a shift in the mean inner angle near the apex to: OHC1 76.7˚, OHC2 82.9˚, and OHC3 82.6˚.   Parameter F (gap width between SBs) (Fig. 3.8) shows a significantly decreasing curve from apex to base (P=<0.0001), which changes more rapidly in the initial portion of the plot, and more gradually towards the base following the shape of a logarithmic curve. The mean gap widths near the apex were 1.95 µm (OHC1), 1.50 µm (OHC2), and 1.68 µm (OHC3). These gaps decreased towards the base where they were 0.43 µm (OHC1), 0.43 µm (OHC2), and 0.33 µm (OHC3). The OHC1 gap widths decreased the most, at a difference of 1.52 µm, OHC2 decreased by 1.06 µm and OHC3 decreased by 1.35 µm.  Figure 3.8. The mean gap width between stereocilia bundles (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter F, Fig. 3.2). These distances are shown corresponding to the percent distance from the apex, along the cochlear length in Parnell’s mustached bat (n=6). P=<0.0001.   47   Figure 3.9. The mean inner angle of the stereocilia bundles (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter H, Fig. 3.2). These distances are shown corresponding to the percent distance from the apex, along the cochlear length in Parnell’s mustached bat (n=6). P=<0.0005.  The stereocilia lengths were also measured along the cochlear length of a mustached bat (Fig. 3.10) and showed a trend similar to that seen in other echolocating bats (Yao et al., 2007). The mean stereocilia length ranged from 1.18 µm near the apex to 0.40 µm near the base, a decrease of 0.78 µm. These stereocilia length data follow a curved path, which decreases more rapidly up to a distance of 20% from the apex, after which, it changes more gradually. This was a significant decrease from apex to base (P=<0.0001).      48   Figure 3.10. The mean stereocilia lengths (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3) in an individual Parnell’s mustached bat. P=<0.0001.  3.3.2 Results for morphometrics in the beluga whale  Preliminary results for morphometrics were determined for a beluga whale (n=1) by measuring the same eight parameters as in the mustached bat (n=22 total parameters, from the IHCs and OHCs) (Fig. 3.2) along the cochlea between 3.3% and 99.65% of its length. In the beluga, as in the mustached bats, not all the parameters showed clear trends, so we chose to focus on those that did. Also, as in the mustached bats, the strongest trends were seen in parameters A (Fig. 3.11), B (Fig. 3.12), D (Fig. 3.13), E (Fig. 3.14), F (Fig. 3.15), and H (Fig. 3.16).  In the beluga the mean distance from IHC to OHC3 (parameter A) decreased by 21.03 µm from the apex to the base, measuring 38.33 µm at 3.3% of the cochlear length from the apex, decreasing to 17.30 µm near the base (85% distance from the apex) (Fig. 3.11). These data 49  decrease significantly in a relatively constant pattern, with a slight peak around 20% from the apex (P=<0.001).   Figure 3.11. The mean distance (± standard deviation) between the inner hair cells (IHCs) to the third row of outer hair cells (OHC3, Parameter A, Fig. 3.2) corresponding to the percent distance from the apex, along the cochlear length in a beluga whale (P=<0.001). The distances between rows (parameter B) (Fig. 3.12), once again decreased significantly from the apex to the base of the cochlea (IHC-OHC1 P=<0.01; OHC1-OHC2 P=<0.001; OHC2-OHC3 P=<0.0001), but to a greater degree than in the mustached bats. Closest to the apex, the mean distances were 19.77 µm (IHC-OHC1), 9.72 µm (OHC1-OHC2), and 6.94 µm (OHC2-OHC3). Closer to the base (83.73 – 99.65% distance from the apex), these distances had decreased to 8.90 µm (IHC-OHC1), 4.14 µm (OHC1-OHC2), and 2.13 µm (OHC2-OHC3). OHC1 was significantly different from either of the other two rows of OHCs (P=<0.01).   50    Figure 3.12. The mean distance (± standard deviation) between each row of hair cells (Parameter B, Fig. 3.2). Shown are the distances between the inner hair cells (IHC) and the first row of outer hair cells (OHC1) (P=<0.01), the distance between the first and second row of outer hair cells (OHC1-OHC2, P=<0.001), and the distance between the second and third row of outer hair cells (OHC2-OHC3, P=<0.0001). The mean distance for IHC-OHC1 was significantly different from the others (P=<0.01). These distances are shown corresponding to the percent distance from the apex, along the cochlear length in a beluga whale. In the remaining parameters (D, E, F, and H, Fig. 3.13 – 3.16) as in the mustached bats, the measurements for the beluga whale were similar among all three rows of hair cells. In addition, each parameter showed similar trends from apex to base, which were significant in both the beluga and the mustached bats. Although these data followed a relatively smooth path, in each of these last four parameters there was a decrease in the mean measurement for the last data point (located at 99.65% of the cochlear distance), relative to the previous point (from 95.26% of the cochlear distance). For this reason, statistical analysis did not include this data point, although the trends remained significant with or without including it. 51  The CP width (D), change significantly from apex to base (P=<0.0001) and showed a relatively steady increase in size, aside from the very last measurement (Fig. 3.13). At the apical end, the mean cell width for all three rows was 4.59 µm (ranging from 4.92 µm in OHC1 to 4.28 µm in OHC3). At the basal end of the cochlea, the mean width for all three rows had increased to 6.24 µm (ranging from 7.70 µm for OHC1 to 5.58 µm for OHC3).  Figure 3.13. The mean width of the hair cell cuticular plate (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter D, Fig. 3.2) (P=<0.0001). These distances are shown corresponding to the percent distance from the apex, along the cochlear length in a beluga whale.  The mean distance between SB tips (E) (Fig. 3.14) and mean inner angle of SBs (H) (Fig. 3.16) showed a similar trend to each other with both parameters showing an initial decrease, followed by a steady increase, except for the last data point as mentioned above. The change from apex to base for both of these parameters was significant (P=<0.01 and P=<0.0001 respectively). Parameter E showed some variation in mean distance between SB tips at the apex, in OHC1 this distance was 5.24 µm, 5.98 µm in OHC2, and 6.57 µm in OHC3. In OHC1, the 52  closest measurement to the base was at 95.26% from the apex and measured 7.80 µm. The measurements for OHC2 and OHC3 were both taken at 99.65% distance and were a similar size at 5.38 µm and 5.48 µm respectively.    Figure 3.14. The mean distance between stereocilia bundle tips (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter E, Fig. 3.2) (P=<0.01). These distances are shown corresponding to the percent distance from the apex, along the cochlear length in a beluga whale.  The mean gap width between SBs (F) (Fig. 3.15) showed a significant decreasing curve from apex to base (P=<0.0001). The difference in the gap width decreased between rows of OHC as the location of the measurements drew closer to the base of the cochlea. Near the apex the mean gap widths measured 1.10 µm (OHC1), 2.09 µm (OHC2), and 3.08 µm (OHC3). These gaps decreased approaching the base to 0.43 µm for OHC1 at an 83.73% distance, and at 99.64% distance, the gap width was 0.29 µm (OHC2) and 0.36 µm (OHC3).  53    Figure 3.15. The mean gap width between stereocilia bundles (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter F, Fig. 3.2) (P=<0.0001). These distances are shown corresponding to the percent distance from the apex, along the cochlear length in a beluga whale.  The mean inner angle of the SBs near the apex (H) (Fig. 3.16), was measured as 95.16˚ for OHC1, 87.54˚ for OHC2, and 96.87˚ for OHC3. In OHC1 the last measurement was taken from 95.26% distance from the apex and was 124.0˚, while OHC2 and OHC3 were both measured at 99.65% distance and were 110.06˚ and 114.05˚ respectively. These data decreased significantly from apex to base (P=<0.0001). 54   Figure 3.16. The mean inner angle of the stereocilia bundles (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter H, Fig. 3.2) (P=<0.0001). These distances are shown corresponding to the percent distance from the apex, along the cochlear length in a beluga whale. The stereocilia lengths of the OHCs in the beluga whale were measured along the cochlear length from the apex to the base (Fig. 3.17), and again showed a similar trend to the changing lengths of the stereocilia in the OHCs of the mustached bat. Measurements were taken between 1.92% and 97.17% of the cochlear length. The stereocilia decreased significantly in length moving from apex to base along the cochlea, in a decreasing curve (P=<0.0001). The stereocilia length for OHC1 ranged from 2.79 µm to 0.5 µm, OHC2 from 2.55 µm to 0.53 µm, and OHC3 from 1.14 µm to 0.52 µm. 55   Figure 3.17. The mean stereocilia lengths (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3) in a beluga whale (P=<0.0001).  3.3.3 Prediction of the cochlear frequency map for belugas based on the morphometric analyses from bats and rats  To predict the cochlear frequency map for belugas based on morphometric measurements, we began by comparing these measurements from the cochleas of Parnell’s mustached bats to those of the beluga. We analyzed the measurements, then compared the results for the six parameters which showed changes associated with the location (% distance from the apex) along the organ of Corti. Comparing the parameters (Fig. 3.2), A (Fig. 3.18), B (Fig. 3.19), D (Fig. 3.20), E (Fig. 3.21), F (Fig. 3.22), H (Fig. 3.23), and the mean stereocilia length (Fig. 3.24), the most similarity in the measurements from the two species occured where the mid to high frequencies were encoded. This region was found at greater than 20% distance from the apex, or at frequencies around 40 kHz and higher in the mustached bat (Kössl & Vater, 1985). Due to the separation of  56   Figure 3.18. The mean distance (± standard deviation) between the inner hair cells (IHCs) to the third row of outer hair cells (OHC3, Parameter A, Figure 3.2) corresponding to the percent distance from the apex, along the cochlear length. Showing a comparison between Parnell’s mustached bat (n=6) and a beluga whale.  Figure 3.19. The mean distance (± standard deviation) between each row of hair cells (Parameter B, Figure 3.2). Shown are the distances between the inner hair cells (IHC) and the first row of outer hair cells (OHC1), the distance between the first and second row of outer hair cells (OHC1-OHC2), and the distance between the second and third row of outer hair cells (OHC2-OHC3). These distances are shown corresponding to the percent distance from the apex, along the cochlear length, comparing Parnell’s mustached bat (n=6) to a beluga whale. 57  the measurements between the two species, from the apex to 20% distance from the apex, and the fact that we have information from the frequency map from 25 kHz onwards for the mustached bat, we decided to look at another species to cover the lower frequency range. We wanted to determine if there would be greater comparability in the low frequency area near the apex. We selected the rat, in part because it has a well-documented frequency map (Müller, 1991). The rat hearing range should include the same low frequency area closest to the apex and there would also be an overlap with the area greater than 20% distance from the apex. These data from the rat, for the same seven parameters that were measured in the bats and the beluga, showed changes in the measurements related to their location along the cochlear length (Figs. 3.25-3.31). Although, in parameter F (mean gap width between OHCs), the relationship was not as consistent as the other parameters among the three rows of OHCs (Fig. 3.30). This   Figure 3.20. The mean width of the hair cell cuticular plate (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter D, Figure 3.2). These distances are shown corresponding to the percent distance from the apex, along the cochlear length, comparing Parnell’s mustached bat (n=6) to a beluga whale. 58  relationship, shows greater variability in the hair cell morphology and arrangement in this region.  As in both the bat and beluga, the similarity between three rows of OHCs was comparable for all parameters, except parameter B, which again showed a separation of the distances between each row of hair cells (Fig. 3.27), although little difference was visible between the second two distances (OHC1-OHC2 and OHC2-OHC3).  Figure 3.21. The mean distance between stereocilia bundle tips (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter E, Figure 3.2). These distances are shown corresponding to the percent distance from the apex, along the cochlear length, comparing Parnell’s mustached bat (n=6) to a beluga whale.  59   Figure 3.22. The mean gap width between stereocilia bundles (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter F, Figure 3.2). These distances are shown corresponding to the percent distance from the apex, along the cochlear length, comparing Parnell’s mustached bat (n=6) to a beluga whale.  Figure 3.23. The mean inner angle of the stereocilia bundles (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter H, Figure 3.2). These distances are shown corresponding to the percent distance from the apex, along the cochlear length, comparing Parnell’s mustached bat (n=6) to a beluga whale. 60   Figure 3.24. The mean stereocilia lengths (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3) compared between Parnell’s mustached bat (n=6) and a beluga whale.  The mean cochlear length for two adult male rats was calculated to be 7.89 mm. The measurements taken from the rat cochleas, were taken from at a distance from the apex of 5% to 65% which corresponds to a frequency range of 3 to 24 kHz. These measurements were then compared to those from the mustached bats, but needed to be plotted differently than when comparing the bats and the beluga whale. Since the frequency maps for the rats and bats are known, we can plot these data as a function of the frequency. This shows a continuous representation of the morphological changes with frequency. In the beluga and bat comparison this was not possible as we do not have a frequency map in place for the belugas and can only plot versus the distance from the apex. However, this is still representative, as the hearing range of the bat and beluga are comparable, unlike that of the bat and the rat. Analyzing parameter A 61  (the mean distance from IHC to OHC3), a comparison of the results from the bats and the rats (Fig. 3.25) plotted as a function of distance from the apex (%), again showed there is a comparable change with location.   Figure 3.25. The mean distance (± standard deviation) between the inner hair cells (IHCs) and the third row of outer hair cells (OHC3, Parameter A, Figure 3.2) corresponding to the percent distance from the apex, along the cochlear length. Showing the comparison between Parnell’s mustached bat (n=6) and a rat.  However due to the difference in hearing ranges, if these measurements are plotted as a function of frequency (kHz) (Fig. 3.26) we obtain a different visual representation of the information showing these data in continuity, not in parallel, and it becomes clear that the rat is a good species to use to fill in some of the gaps in the lower frequencies. This also shows that the variation in morphology associated with location is not just related to the physical location along the cochlear length, but also to the frequencies encoded for by these hair cells. Comparing the  62   Figure 3.26. The mean distance (± standard deviation) between the inner hair cells (IHCs) and the third row of outer hair cells (OHC3, Parameter A, Figure 3.2) corresponding to the frequencies detected (kHz). Showing the comparison between Parnell’s mustached bat (n=6) and a rat.   morphometrics from the mustached bats and rats as a function of frequency was possible because cochlear frequency maps are already available for both species (Kössl & Vater, 1985; Müller, 1991). The bats and belugas could not be analyzed this way as the belugas do not have a frequency map, but since they share a similar hearing range, including high frequencies, and both use echolocation, it is reasonable to use the distance from the apex (%) to compare them. The measurements for the rats and bats align reasonably well, except for parameter F (mean gap width between SBs of the OHCs, Fig. 3.30). In all figures (Fig. 3.26 to 3.31) frequencies of 15 kHz for the bat, which correspond to the distances from 0 – 7% from the apex, are based on a second frequency map from Kössl and Vater (1996).  63   Figure 3.27. The mean distance (± standard deviation) between each row of hair cells (Parameter B, Figure 3.2). Shown are the distances between the inner hair cells (IHC) and the first row of outer hair cells (OHC1), the distance between the first and second row of outer hair cells (OHC1-OHC2), and the distance between the second and third row of outer hair cells (OHC2-OHC3). These distances are represented as a function of the frequencies detected (kHz), comparing Parnell’s mustached bat (n=6) to a rat.   Figure 3.28. The mean width of the hair cell cuticular plate (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter D, Figure 3.2). These distances are represented as a function of the frequencies detected (kHz), comparing Parnell’s mustached bat (n=6) to a rat.  64   Figure 3.29. The mean distance between stereocilia bundle tips (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter E, Figure 3.2). These distances are represented as a function of the frequencies detected (kHz), comparing Parnell’s mustached bat (n=6) to a rat.  Figure 3.30. The mean gap width between stereocilia bundles (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter F, Figure 3.2). These distances are represented as a function of the frequencies detected (kHz), comparing Parnell’s mustached bat (n=6) to a rat.  65   Figure 3.31. The mean inner angle of the stereocilia bundles (± standard deviation) in each row of outer hair cells (OHC1, OHC2, and OHC3, Parameter H, Figure 3.2). These distances are represented as a function of the frequencies detected (kHz), comparing Parnell’s mustached bat (n=6) to a rat.   All the measurements from the morphometrics for the bats and rats were further analyzed to determine which morphological measurements were the most relevant to the frequency sensitivity and detection of specific frequencies. Since each parameter was measured in each of the three rows of hair cells, there is variation in the morphology even within each of the parameters. For example, parameter D - mean CP width, consists of D1, D2, and D3 depending on which of the three rows the cell measured was in. Looking first at the morphometrics of the bats, according to the Akaik Information Criterium (AIC criteria), and R2 values (multiple R-squared = 0.8217, Adjusted R-squared = 0.7983), five variables explained 82.17% of the variance in frequency detection (Table 3.1). In the bats, these variables were as follows: (B2) the mean distance from OHC1-OHC2, (C1) mean CP length of OHC1, (C3) mean CP length of OHC3, (D3) mean CP width OHC3, and (E1) mean distance between SB tips (Fig. 3.32). 66    Estimate Std. Error t value Pr(>|t|) (Intercept)            118.341 14.711   8.044 9.96e-10 *** Mean distance OHC1-OHC2 (B2)   -10.505   1.510 -6.958 2.80e-08 *** Mean CP length OHC1 (C1)    24.147   5.884   4.104  0.000207 *** Mean CP length OHC3 (C3)  -25.161   5.722 -4.397 8.54e-05 *** Mean CP width OHC3 (D3)   19.548   3.345  5.845 9.30e-07 *** Mean distance between SB tips OHC1 (E1)  -18.582   3.199 -5.809 1.04e-06 *** Number of stars indicates the weight of each variable in explaining the frequency.  Significance codes:  0 '***' / 0.001 '**' / 0.01 '*' / 0.05 '.' / 0.1 ' ' / 1  Table 3.1 Coefficients for the multiple linear regression model of the variables with the most weight calculated from the morphometrics of Parnell’s mustached bat (n=6).  The test of Shapiro, (p-value = 0.4473) indicates that the small prediction errors generated from this model follow a normal distribution. This is important, as it allows us to apply a linear “least square” regression for our data, to minimize the sum of squared prediction errors.  The results from the morphometric measurements of the rat, taking into account the five variables found to be the most significant in the bats, explain 95% of the variation related to frequency sensitivity (multiple R-squared = 0.9507, adjusted R-squared = 0.9444, F-statistic = 150.4 on 5 and 39 degrees of freedom (df), p-value <2.2 e-16, and Shapiro test W = 0.9526, p-value = 0.06376 with errors following a normal distribution). Combining the results from the morphometric measurements from the rats for the frequencies from 1 – 25 kHz with those from bats for 25 – 120 kHz, the multiple linear regression model gives us the best result (Table 3.2). This model has a residual standard error of 12.94 on 61 df, multiple R-squared = 0.8349, adjusted R-squared = 0.8213, F-statistic = 61.68 on 5 and 61 df, and a p-value < 2.2e-16.     67   Estimate Std. Error t value Pr(>|t|) (Intercept)             127.9220 17.8298   7.175 1.16e-09 *** Mean distance OHC1-OHC2 (B2)    -8.3725   1.3643 -6.137 6.87e-08 *** Mean CP length OHC1 (C1)     -0.9672   4.5158 -0.214    0.831 Mean CP length OHC3 (C3)    -6.7932   4.6496 -1.461    0.149 Mean CP width OHC3 (D3)    19.6985   3.2164   6.124 7.22e-08 *** Mean distance between SB tips OHC1 (E1)   -18.4969   2.5264 -7.321 6.49e-10 *** Number of stars indicates the weight of each variable in explaining the frequency.  Significance codes:  0 '***' / 0.001 '**' / 0.01 '*' / 0.05 '.' / 0.1 ' ' / 1  Table 3.2 Coefficients for the multiple linear regression model of the variables with the most weight calculated from the morphometrics of Parnell’s mustached bat (n=6) and a rat (n=1).  We could calculate the predicted frequencies along the cochlear spiral for the beluga whale (n=6) based on the results of the multiple linear regression model (Fig. 3.32), based on the morphometrics from the bats and rat, determined from the following equation: 𝐸𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝐹𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦 (𝑘𝐻𝑧)=  127.92 − (𝐵2 × 8.37) −  (𝐶1 × 0.97) − (𝐶3 × 6.79) + (𝐷3 × 19.70)− (𝐸1 × 18.50) For the 5 parameters that explained the maximum variability of the dataset (Fig. 3.32), we used data from 6 beluga whales to have a better estimate of the inter-individual variability (Fig. 3.33). 68   Figure 3.32. The five variables which explained 82.17% of the variation related to frequency sensitivity in Parnell’s mustached bat (n = 6), and 95% of the variation in rats (n = 1).    Figure 3.33. Cochlear frequency map prediction for the beluga whale (n=6), using morphometrics measured in Parnell’s mustached bat (n=6) and the rat (n=1). 69   3.3.4 Geometric morphometric analysis in Parnell’s mustached bat      As seen by the placement of the LMs in Fig. 3.3, there is variation in the hair cell shape, particularly in the OHCs from apex to base along the organ of Corti. This variation does not change linearly along the entire cochlear length, although it does change overall from apex to base (Fig. 3.34).  Having selected and digitized 57 LMs (Fig. 3.3, and Appendix B1) for at least three replicates in each of the 10 locations of % distance, we then performed a Procrustes fit using MorphoJ©. This process removes the variation attributed to factors other than shape, such as orientation, scale, and position, from these LM data, while also aligning and averaging the shapes.  Next, we analyzed the results using a principal component analysis (PCA) to determine which principal component (PC) is responsible for the greatest amount of variation in the hair cell shape. We performed a PCA on the blocks of 12 cells (IHCs and OHCs) as a single unit (Fig. 3.35). The results show in this case that PC1 is responsible for 59.5% of the variation (eigenvalue of 0.01196996), and PC2 is responsible for 21% of the variation (eigenvalue of 0.00429978). It is difficult to see a clear pattern in these data points relating the changes in the cell shapes to location along the organ of Corti.   70   Figure 3.34. The variation in SEM micrographs from the ten locations (A through J showing 5 through 95% distance from the apex) for which geometric morphometrics were analyzed along the organ of Corti of Parnell’s mustached bat. Scale bars = 5 µm. 71   Figure 3.35. Principal component analysis (PCA) of the blocks of inner hair cells (IHCs) and outer hair cells (OHCs) analyzed together as a block of twelve cells in total (3 IHC and 9 OHC) of Parnell’s mustached bat (n=6).  Then, to better understand the differences between the IHCs and the OHCs, we separated the blocks of cells into individual cells, grouped by IHCs and OHCs (Fig. 3.36). This showed that the variation which occurs in the cell shape as a function of location along the cochlear length, differs between the IHCs and OHCs. However, the variation is again primarily due to PC1, which was responsible for 74% of the variation, with only 20% attributed to PC2. In this case there is a more distinct relationship between the variation in cell shape related to location along the cochlear length, which is more prominent in the OHCs, represented on the right-hand side of Fig. 3.36.   72    Figure 3.36. Principal component analysis (PCA) of the inner hair cells (IHCs) separated from and compared to the outer hair cells (OHCs) of Parnell’s mustached bat (n=6).  Lastly, we separated the individual OHCs and performed a PCA only on these hair cells, separated into single cells (Fig. 3.37). This allowed us to see that PC1 is responsible for 56% of the variation, and PC2 for 29% of the variation, which shows that the total variation here is spread between these two components to a greater degree. The relationship between the change in hair cell shape due to both PC1 and PC2, and location along the organ of Corti, is clearly visible in this analysis of the OHCs. This also reflects the morphological changes in the hair cells independently from their relationship to other hair cells, either in the same or neighbouring rows. In both the analysis of IHCs vs OHCs, as well as for only OHCs, the first four PCs were responsible for a total of 100% of the hair cell shape variation. When comparing the first PC with 73  the coding frequency, we observed a clear trend along the spiral (Fig. 3.38). Next, we did a regression between shape (Procrustes) and frequency, (Fig. 3.39), which showed variation in shape related to frequency and location.  This geometric morphometric analysis of the hair cells in the bat cochlea gives us information about the variation in morphology, specifically hair cell shape, as a function of the location along the cochlear length.    Figure 3.37. Principal component analysis (PCA) of only the outer hair cells (OHCs) of Parnell’s mustached bat (n=6).  74   Figure 3.38. Principal component one (PC1) as a function of frequency (kHz) showing locations from 5 – 95% from the apex, for Parnell’s mustached bat (n=6).   Figure 3.39. Regression of shape (Procrustes) versus frequency (kHz) results, averaged by individual and location (% distance from the apex), for Parnell’s mustached bat (n=6). 75  3.4 Discussion   3.4.1 Morphometric analysis We were able to take morphometric measurements at 10 equidistant locations along the cochlear length of the bat, giving more details of morphological changes than we were able to obtain for the beluga at this time. The results for parameter A (distance of IHC-OHC3) (Fig. 3.2, Fig. 3.18) and parameter B (distance between rows of hair cells, Fig. 3.19), show a decrease from apex to base in the bat, as in the beluga. These two parameters change together as expected and as reported previously in other mammals (Dallos, 1992; Lim, 1986). In the mustached bat, the parameters (Fig. 3.2): D (Fig. 3.6), E (Fig. 3.7), F (Fig. 3.8), and H (Fig. 3.9) show similar overall changes as seen for the beluga (Fig. 3.20 – 3.23 for comparison of these data). The biggest difference is a notable decrease in these values between 35 – 70% of the distance from the apex. As mentioned earlier, this corresponds to the acoustic fovea of mustached bats, which is located between 40 and 60% of the cochlear length and detects frequencies of around 61.5 kHz (Kössl, 1994a). This is a region of the organ of Corti which has an increased amount of innervation, and therefore greater selectivity and sensitivity to this frequency, which is biologically important for the echolocation of the mustached bats (Kössl & Vater, 1985). In the beluga whale, although there is a significant basal increase in CP width, there seems to be a plateau between distances of around 30% and 65% along the cochlear length. This could correspond to an acoustic or auditory fovea, which has also been described for the greater horseshoe bat (Rhinolophus ferrumequinum) (Bruns & Schmieszek, 1980). This dramatic change in the morphology of this area further indicates that the morphometrics of these hair cells is directly linked to the frequencies encoded for by the hair cells at this and other locations. 76  Parameter H (inner angle of the OHC SB) (Fig. 3.9) showed some variability between the three rows of OHCs around 1% distance from the apex, but increased overall from apex to base.  As expected from previous studies (Vater & Lenoir, 1992; Vater & Siefer, 1995) and our measurements in the beluga, the mean inner angle increased for OHC1 from apex to base. Surprisingly, these angles decreased in OHC2 and OHC3, as the apical values were from a single bat. The OHC1 looked typical for cells close to the apex, however those from OHC2 and OHC3 were flatter and wider similar to hair cells closer to the base, possibly due to an inclination of the picture. Removing this single location from the one individual out of the dataset, results in a shift in which the mean inner angle increases from apex to base as in other mammals. This speaks to a couple of sources of variation possible in an analysis such as this. One source of variation in any study involving biological samples, is of course individual variation, of which there is a certain amount in any species, or group of living organisms (Hayes & Jenkins, 1997). In addition, the most apical region is the most variable morphologically in several mammalian species (Echteler et al., 1994; Wever et al., 1971a, 1972). Another source of variation in this case is due to the processing of the cochlear samples in preparation for SEM imaging. The fixation and critical point drying required do result in some shrinkage of the tissue, which is unavoidable but fairly consistent among samples processed using the same methodology (Edge et al., 1998; Yarin et al., 2014).  The decrease in OHC stereocilia lengths in the mustached bat from apex to base follow a descending curve, which changes most rapidly from 0 to 20% distance from the apex (Fig. 3.10). This pattern of change was also seen in four other species of echolocating bats with OHC stereocilia lengths similar to the mustached bats analyzed here (Yao et al., 2007). The OHC stereocilia of echolocating bats have also been found to be shorter than those of non-echolocating 77  mammals and varies tonotopically along the cochlear length (Dannhof & Bruns, 1991; Vater & Kössl, 1996; Vater & Lenoir, 1992; Vater & Siefer, 1995). Again, this change in OHC stereocilia length, follows the pattern seen in this study for the beluga whale (Fig. 3.24). Unfortunately, we were only able to obtain consistent measurements from a few locations in the beluga whale cochlea, but more samples, and measuring additional locations would increase the level of detail, as well as quantify inter-individual variability. There were several parameters (D, E, F, and H) (Fig. 3.2) which had lower values for the basal-most data point (at 99.65% distance), relative to the previous data points in each set. It is not clear why this is the case, but our results are consistent with previous work where other researchers have found the same contrary tendency in the basilar membrane within the first micrometers of the base, known as the hook (for its shape), in echolocating whales and bats (Bruns, 1976; Dannhof & Bruns, 1991; Kössl & Vater, 1985; Morell et al., 2015). In addition, it is difficult to image the hook effectively for analysis using morphometric measurements, as well as for other types of studies (Rhode, & Recio, 2000). The decrease in OHC stereocilia length from apex to base along the organ of Corti of the beluga whale (Fig. 3.17), is supported by earlier research. A similar change in OHC stereocilia length has also been reported in other species of odontocetes, such as the striped dolphin (Stenella coeruleoalba, Meyen, 1833) and the harbour porpoise (Phocoena phocoena, Linnaeus, 1758) (Morell et al., 2015). What is particularly promising with respect to the beluga whale and the prediction of its cochlear frequency map, is that regardless of how much a parameter changed with location from the apex to the base, the measurements closely followed those for the bats. The morphometric measurements corresponding to the lower frequencies were not as well aligned when comparing 78  the mustached bat and the beluga as they were for the higher frequencies. This could be due to the fact that belugas can hear down to 125 Hz (Awbrey et al., 1988) while mustached bats hear down to only 10 kHz (Kössl, 1994b). To fill in the gaps and cover the frequency range lower than that heard by the mustached bat, we also included a rat cochlea. The rat was selected because it has a hearing range (1.2 – 54 kHz) (Müller, 1991) which encompasses the lower frequencies not heard by the mustached bat, as well as overlapping with the lower end of the hearing range for the bat.  We plotted the morphometric measurements for the bats and rat together (Figs. 3.26 - 3.31), as a function of frequency, rather than distance from the apex, as with the beluga. Since both the mustached bat and the rat already have a known frequency map, plotting this way shows that the measurements align overall, giving a complete range of morphometric measurements linked to the frequencies encoded by these hair cells.    The morphometric measurements for the bats and rat required further analysis to determine which of the parameters, and from which OHC row were the most relevant for predicting the cochlear frequency map. Each parameter consists of measurements from all three rows of OHC and may therefore contain variations. Using machine learning techniques to first analyze the morphometrics from the bats, there were five parameters which were determined to be responsible for explaining 82.2% of the variance (Table 3.1). The variables in the bats were: (B2) the mean distance from OHC1-OHC2, (C1) mean CP length of OHC1, (C3) mean CP length of OHC3, (D3) mean CP width OHC3, and (E1) mean distance between SB tips (Fig. 3.32). Since the prediction errors follow a normal distribution, a linear “least square” regression was applicable for our data. When considering the same five parameters that were significant in the bats to analyze the morphometric measurements 79  from the rat, we found that they are responsible for 95% of the variance related to frequency sensitivity. Using the morphometric results from the rat for the frequency range of 1 – 25 kHz along with those from the bat, covering 25 – 120 kHz, a multiple linear regression model produces the best result (Table 3.2).  Using the morphometrics from the bats and rat (Fig. 3.32), and based on the results of the multiple linear regression model as determined from the following equation: 𝐸𝑠𝑡𝑖𝑚𝑎𝑡𝑒𝑑 𝐹𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦 (𝑘𝐻𝑧)=  127.92 − (𝐵2 × 8.37) −  (𝐶1 × 0.97) − (𝐶3 × 6.79) + (𝐷3 × 19.70)− (𝐸1 × 18.50)  we were able to calculate the predicted frequencies and their locations along the cochlear spiral, resulting in the first ever, prediction of the cochlear frequency map for the beluga whale (Fig. 3.33). This frequency map is preliminary and requires further research as it is based on a relatively small sample size (n=6). Individual variation must be accounted for, although this frequency map does not extend to the maximum possible hearing range recorded for beluga whales. A more typical or average hearing range would be from 1 – 2 kHz up to 128 – 130 kHz (Mooney et al., 2012), which is closer to what we have calculated. We chose this type of graph as it allowed us to show the distribution of these data as well as the trend line, and the error of prediction (shown in grey). The ability to use morphological measurements supported by auditory information is essential in creating cochlear frequency maps from morphometric measurements and morphological structures common among mammalian species.  80  3.4.2 Geometric morphometric analysis Morphometric measurements provide a lot of information through a series of linear measurements. While this is extremely informative, we also wanted to use GMs to determine what we could learn about the overall hair cell shape as a function of its location along the cochlear length. GM analysis looks at the interactions between all the selected LM coordinates and removes the variation other than that related to the shape. This can improve our understanding of how the individual parameters are working together to change the overall shape of the hair cells. The LMs selected were chosen to best capture the variation in the hair cell shape throughout the cochlea in both the IHC and OHC (Fig. 3.3). Principal components (PCs) each contribute to the overall variation in the shape of the hair cells. While analyzing all the data together did not show any clear pattern with respect to the first PCs (Fig 3.35), the OHCs were separated from IHCs (Fig. 3.36) and the OHC shape was clearly defined among locations (Fig 3.37) when data was separated in 2 blocks: IHCs and OHCs. This analysis indicated that the variation in the OHCs is linked to location, and potentially to the frequency. Our results also show that both PC1 and PC2 are responsible for most of the variation in the shape of these cells. Clear grouping was shown when plotting PC1 (responsible for the variation from apex to base) as a function of frequency (Fig. 3.38) and coloured according to location. These results show variation which corresponds to frequency and location. A regression for the hair cells in the bats also showed a relationship between hair cell shape and frequency (Fig. 3.39). 81  The tonotopic organization of the organ of Corti has been well documented (Müller, Von Hünerbein, Hoidis, & Smolders, 2005; Dallos, 1992; Kössl & Vater, 1990a, 1990b). Our results from both morphometric and GM analyses are indicative of the relationship between the frequencies detected and the location along the cochlear length at which they are detected. The comparison of two species of echolocating mammals, supplemented with measurements from the rat, has given us a better understanding of some of the morphological features of the cuticular plate of the organ of Corti, related to their frequency sensitivity.  3.5 Chapter summary We need to understand more about hearing across species, different types of hearing, and how anthropogenic sounds may be affecting animals regardless of their environment. To do so, it is necessary to compare species to learn more about the specific morphology of the sensory hair cells, contributing to sound reception and processing within the inner ear. To our knowledge, this study is only the second to describe the morphological variation of the cuticular plate of hair cells along the cochlear length of the organ of Corti using morphometrics. Previously this has only been done in the guinea pig (Yarin et al., 2014). Also to our knowledge, this is the first study to examine the variation in hair cell cuticular plate shape along the cochlear length using geometric morphometric analysis. Morphometrics give us insight about the individual parameters of the sensory hair cells which contribute to the overall hair cell shape. These parameters may have differing degrees of importance related to the biomechanics and frequency sensitivity associated with hair cell location along the organ of Corti. Of all the parameters measured, five have been determined to explain more than 82% of the variability of the data and can be used to predict a cochlear frequency map for the beluga whale. GM analysis 82  gave us additional information about the overall hair cell shape, which varies with the frequency detected by the hair cell, and its location along the cochlear length. The overall shape of the hair cells varies more among the OHCs than the IHCs, and noticeably between the apex, middle, and base of the cochlea. These results further indicate that, as in other mammalian species, there are changes in the morphology and morphometrics linked to the frequencies detected at various locations in the cochlea. In our research thus far, the morphometric analysis has given us the most information required for us to develop the first predictions of a cochlear frequency map for the beluga whale. The use of morphometric measurements to develop frequency maps gives us an excellent opportunity to apply this analysis to other species. Once the cochlear frequency map for a species is determined, it will be possible to estimate the acoustic characteristics of a source of sound that may have caused damage by acoustic overstimulation. As a result, our study can ultimately help determine potential impacts and effects of human-made noise on mammals, both terrestrial and aquatic.   83  Chapter 4: Conclusion  4.1 Summary The research presented here is novel and crucial to furthering our understanding of the impacts on mammals due to anthropogenic noise. We are in a critical time to gather this information as the Arctic and other areas are becoming more accessible. In a changing acoustic environment, collecting baselines of normal morphology, and creating frequency maps for marine species are essential tools. This knowledge can help us to determine proper protocols and regulations for producing anthropogenic noise.  The hair cells in the beluga whale (D. leucas) cochlea are arranged in a single row of IHCs parallel to three rows of OHCs, as is also typical of terrestrial mammals. There are changes in the hair cell width, spacing, and density, from the apex to the base along the organ of Corti (objective 1). This establishes a baseline for normal morphology in the beluga cochlea, so pathology or damage can be recognized and documented if found in future investigations.  Five of the measurements of the cuticular plate in the beluga (B2 – mean distance from the rows OHC1 – OHC2, C1 and C3– mean length of OHC1 and OHC3, D3 – mean CP width of OHC3, and E1 – distance between the base of the SBs of OHC1), change from the apex to the base along the cochlear length. The stereocilia length was also found to decrease from the apex to the base of the cochlea (objective 2).  Morphometric analysis of Parnell’s mustached bat (P. parnellii) showed a sharp reduction in these measurements in the region of the acoustic fovea, in addition to changes from the apex to the base. These morphometric changes were related to the frequencies detected at ten locations along the cochlear length. 84   In addition to the morphometric analysis, we also analyzed GMs from the bats. Most of the variation in the dataset was due to the first two PCs. These results showed a change in the overall hair cell shape associated with frequency and location along the cochlear spiral (objective 3). Using machine learning techniques, we determined that five of the morphometric measurements were responsible for 83.5% of the variance of the data.  Using these five measurements we created the first frequency mapping predictions for the beluga whale from Parnell’s mustached bats and rats (objective 4).  4.2 Future directions Every study has its limitations and challenges, but also opportunities for future improvements and to propose future research directions. The possibility for future studies are very exciting and there are many aspects to investigate further. An area of personal interest, would be to examine the possibility of using different techniques for preservation and imaging of the cochlear samples. Using the SEM gives us an extremely high level of detail, but one drawback is the tissue distortion which results from the processing required for use in the SEM. Sample size was an issue in this study, as is often the case with marine mammals, and other animals, depending on constraints on availability which varies for different reasons and with species. Being able to take measurements from a greater number of cochlear samples could help strengthen these results and increase our understanding of individual variation.  Based on the research described here, it would seem that the use of morphometrics is a viable alternative to physiological frequency mapping techniques. These results are very promising and this approach has been used previously only in the guinea pig (Yarin et al., 2014). 85  Further investigation across species could help us further understand how anthropogenic noise is affecting not just marine mammals, but also terrestrial animals. The methods described here will also be used in ongoing research of other species of terrestrial mammals including other rodents to learn more about their hearing and to make the machine learning models stronger.  There is also potential for these techniques to be used to investigate hearing in other species of marine mammals. The success of this would depend largely on the availability and quality of the samples obtained. The greatest challenge could be in finding enough cochlear samples to analyze, however connections to stranding networks could aid in this endeavor. Although a large undertaking, it would be very beneficial to examine additional species of marine mammals to gain a greater understanding of what sounds are impacting which species and to what degree. Expanding comparative studies to include cochlear morphology of mysticetes (baleen whales), which communicate with much lower frequency calls, could be a valuable approach to understanding the hearing capabilities of the largest animals on Earth. Ultimately, if frequency maps for such species could be created, we would have a tool to help determine how they are being affected by anthropogenic noise which is an ever-increasing problem in the oceans.  86  References  Adams, D. C., Collyer, M. L., & Kaliontzopoulou, A. (2018). Geomorph: Software for geometric morphometric analyses. R package version 3.0.6. Retrieved from https://cran.r.project.org/package=geomorph. Altringham, J. D. (2011). Bats: From evolution to conservation (2nd ed.). New York; Oxford: Oxford University Press. Amundin, M., & Andersen, S. H. (1983). Bony nares air pressure and nasal plug muscle activity during click production in the harbour porpoise, Phocoena phocoena, and the bottlenosed dolphin, Tursiops truncatus. J. Exp. Biol., 105, 275–282. Au, W. W. L. (1988). Sonar Target Detection and Recognition by Odontocetes. In P. E. Nachtigall & P. W. B. Moore (Eds.), Animal Sonar: Processes and Performance (pp. 451–465). Boston, MA: Springer US. https://doi.org/10.1007/978-1-4684-7493-0_44 Au, W. W. L. (1997). Echolocation in dolphins with a dolphin bat comparison, 8, 137–162. Au, W. W. L. (2004). A comparison of the sonar capabilities of bats and dolphins. In J. A. Thomas, C. F. Moss, & M. Vater (Eds.), Echolocation in Bats and Dolphins (pp. xiii–xxvii). Chicago and London: University of Chicago Press. Au, W. W. L., Carder, D. A., Penner, R. H., & Scronce, B. L. (1985). Demonstration of adaptation in beluga whale echolocation signals. J. Acoust. Soc. Am., 77(2), 726–730. https://doi.org/10.1121/1.392341 Au, W. W. L., Popper, A. N., & Fay, R. R. (Eds.). (2000). Hearing by whales and dolphins. New York: Springer-Verlag.  87  Awbrey, F. T., Thomas, J. A., & Kastelein, R. A. (1988). Low-frequency underwater hearing sensitivity in belugas, Delphinapterus leucas. J. Acoust. Soc. Am., 84(6), 2273–2275. https://doi.org/10.1121/1.397022 Brinkløv, S., Fenton, M. B., & Ratcliffe, J. M. (2013). Echolocation in Oilbirds and swiftlets. Front. Physiol., 4, 1–12. https://doi.org/10.3389/fphys.2013.00123 Bruns, V. (1976). Peripheral auditory tuning for fine frequency analysis by the CF-FM bat, Rhinolophus ferrumequinum - I. Mechanical specializations of the cochlea. J. Comp. Physiol. A, 106, 77–86. https://doi.org/10.1007/BF00606573 Bruns, V., & Schmieszek, E. (1980). Cochlear innervation in the greater horseshoe bat: Demonstration of an acoustic fovea. Hear. Res., 3, 27–43. Castellote, M., Mooney, T. A., Quakenbush, L., Hobbs, R., Goertz, C., & Gaglione, E. (2014). Baseline hearing abilities and variability in wild beluga whales (Delphinapterus leucas). J. Exp. Biol., 217(10), 1682–1691. https://doi.org/10.1242/jeb.093252 Chen, F., Zha, D., Fridberger, A., Zheng, J., Choudhury, N., Jacques, S. L., … Nuttall, A. L. (2011). A differentially amplified motion in the ear for near-threshold sound detection. Nat. Neurosci., 14(6), 770–774. https://doi.org/10.1038/nn.2827 Ciganović, N., Wolde-Kidan, A., & Reichenbach, T. (2017). Hair bundles of cochlear outer hair cells are shaped to minimize their fluid-dynamic resistance. Sci. Rep., 7(1), 1–9. https://doi.org/10.1038/s41598-017-03773-y Cranford, T. W., & Amundin, M. (2004). Biosonar pulse production in odontocetes: the state of our knowledge. In Echolocation in Bats and Dolphins (ed. JA Thomas, CF Moss and M. Vater) (pp. 27–35).  88  Dallos, P. (1992). The active cochlea. J. Neurosci., 12(12), 4575–4585. Dannhof, B. J., & Bruns, V. (1991). The Organ of Corti in the Bat Hipposideros-Bicolor. Hear. Res., 53, 253–268. Dannhof, B. J., Roth, B., & Bruns, V. (1991). Length of hair cells as a measure of frequency representation in the mammalian inner ear? Naturwissenschaften, 78(12), 570–573. https://doi.org/10.1007/BF01134454 Davies, K. T. J., Cotton, J. A., Kirwan, J. D., Teeling, E. C., & Rossiter, S. J. (2012). Parallel signatures of sequence evolution among hearing genes in echolocating mammals: An emerging model of genetic convergence. Heredity (Edinb)., 108(5), 480–489. https://doi.org/10.1038/hdy.2011.119 Davies, K. T. J., Maryanto, I., & Rossiter, S. J. (2013). Evolutionary origins of ultrasonic hearing and laryngeal echolocation in bats inferred from morphological analyses of the inner ear. Front. Zool., 10(1), 1–15. https://doi.org/10.1186/1742-9994-10-2 Dong, W., & Olson, E. S. (2009). In vivo impedance of the gerbil cochlear partition at auditory frequencies. Biophys. J., 97(5), 1233–1243. https://doi.org/10.1016/j.bpj.2009.05.057 Echteler, S. M., Fay, R. R., & Popper, A. N. (1994). Structure of the Mammalian Cochlea. In R. R. Fay & A. N. Popper (Eds.), Comparative Hearing: Mammals (pp. 134–171). Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2700-7_5 Edge, R. M., Evans, B. N., Pearce, M., Richter, C., Hu, X., & Dallos, P. Y. (1998). Morphology of the unfixed cochlea. Hear. Res., 124, 1–16. El Naqa, I., & Murphy, M. J. (2015). What Is Machine Learning? In I. El Naqa, R. Li, & M. J. Murphy (Eds.), Machine Learning in Radiation Oncology: Theory and Applications (pp. 3–11). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-18305-3_1 89  Fenton, M. B. (2013). Questions, ideas and tools: Lessons from bat echolocation. Anim. Behav., 85(5), 869–879. https://doi.org/10.1016/j.anbehav.2013.02.024 Fettiplace, R. (2006). Active hair bundle movements in auditory hair cells. J. Physiol., 576(1), 29–36. https://doi.org/10.1113/jphysiol.2006.115949 Fettiplace, R., & Kim, K. X. (2014). The Physiology of Mechanoelectrical Transduction Channels in Hearing. Physiol. Rev., 94(3), 951–986. https://doi.org/10.1152/physrev.00038.2013 Gao, G., & Zhou, K. (1992). Fiber analysis of the optic and cochlear nerves of small cetaceans. In J. A. Thomas, R. A. Kastelein, & A. Y. Supin (Eds.), Marine Mammal Sensory Systems (pp. 39–52). Boston, MA: Springer. Gillespie, P. G., & Müller, U. (2009). Mechanotransduction by Hair Cells: Models, Molecules, and Mechanisms. Cell, 139(1), 33–44. https://doi.org/10.1016/j.cell.2009.09.010 Gould, E. (1965). Evidence for Echolocation in the Tenrecidae of Madagascar. Proc. Am. Phiolosophical Soc., 109(6), 352–360. Gould, E., Negus, N. C., & Novick, A. (1964). Evidence for Echolocation in Shrews. J. Exp. Biol., 156(1), 19–37. Greenwood, D. D. (1961). Critical Bandwidth and the Frequency Coordinates of the Basilar Membrane. J. Acoust. Soc. Am., 33(10), 1344–1356. https://doi.org/10.1121/1.1908437 Greenwood, D. D. (1974). Critical bandwidth in man and some other species in relation to the travelling wave envelope. In H. R. Moskowitz, B. Scharf, & J. C. Stevens (Eds.), Sensation and Measurement (pp. 231–239). Dordrecht: Springer. Greenwood, D. D. (1990). A cochlear frequency‐position function for several species—29 years later. J. Acoust. Soc. Am., 87(6), 2592–2605. https://doi.org/10.1121/1.399052 90  Hauser, D. D. W., Laidre, K. L., & Stern, H. L. (2018). Vulnerability of Arctic marine mammals to vessel traffic in the increasingly ice-free Northwest Passage and Northern Sea Route, 1–6. https://doi.org/10.1073/pnas.1803543115 Hayes, J. P., & Jenkins, S. H. (1997). Individual Variation in Mammals. J. Mammal., 78(2), 274–293. https://doi.org/10.2307/1382882 Jones, G., & Holderied, M. W. (2007). Bat echolocation calls: adaptation and convergent evolution. Proc. R. Soc. B Biol. Sci., 274(1612), 905–912. https://doi.org/10.1098/rspb.2006.0200 Jones, G., & Teeling, E. C. (2006). The Evolution of Echolocation in Bats. Trends Ecol. Evol., 21(3), 1–8. https://doi.org/10.1016/j.tree.2006.01.001 Ketten, D. R. (1992a). The Cetacean Ear: Form, Frequency, and Evolution. In J. A. Thomas, R. A. Kastelein, & A. Y. Supin (Eds.), Marine Mammal Sensory Systems (pp. 53–75). Boston, MA: Springer. Ketten, D. R. (1992b). The marine mammal ear: Specializations for aquatic audition and echolocation. Evol. Biol. Hear., 717–750. https://doi.org/10.1007/978-1-4612-2784-7_44 Ketten, D. R. (1997). Structure and function in whale ears, 8(1–2), 103–135. https://doi.org/10.1080/09524622.1997.9753356 Ketten, D. R. (2000). Cetacean Ears. In W. W. L. Au, A. N. Popper, & R. R. Fay (Eds.), Hearing by Whales and Dolphins. Springer Handbook of Auditory Research (pp. 43–108). New York, NY: Springer. https://doi.org/10.1007/978-1-4612-1150-1_2 Ketten, D. R., & Wartzok, D. (1990). Three-dimendional reconstruction of the dolphin ear. Sens. Abil. Cetaceans Lab. F. Evid., 81–105.  91  Klingenberg, C. P. (2011). MorphoJ: An integrated software package for geometric morphometrics. Mol. Ecol. Resour., 11(2), 353–357. https://doi.org/10.1111/j.1755-0998.2010.02924.x Kössl, M. (1994a). Evidence for a mechanical filter in the cochlea of the “constant frequency” bats, Rhinolophus rouxi and Pteronotus parnellii. Hear. Res., 72(1–2), 73–80. https://doi.org/10.1016/0378-5955(94)90207-0 Kössl, M. (1994b). Otoacoustic emissions from the cochlea of the ‘constant frequency’ bats, Pteronotus parnellii and Rhinolophus rouxi. Hear. Res., 72(1–2), 59–72. https://doi.org/10.1016/0378-5955(94)90206-2 Kössl, M., & Vater, M. (1985). The cochlear frequency map of the mustache bat, Pteronotus parnellii. J. Comp. Physiol. A, 157(5), 687–697. https://doi.org/10.1007/BF01351362 Kössl, M., & Vater, M. (1990a). Resonance phenomena in the cochlea of the mustache bat and their contribution to neuronal response characteristics in the cochlear nucleus. J. Comp. Physiol. A, 166, 711–720. https://doi.org/10.1007/BF00240020 Kössl, M., & Vater, M. (1990b). Tonotopic organization of the cochlear nucleus of the mustache bat, Pteronotus parnellii. J. Comp. Physiol. A, 166(5), 695–709. https://doi.org/10.1007/BF00240019 Kössl, M., & Vater, M. (1995). Cochlear Structure and Function in Bats. In A. N. Popper & R. R. Fay (Eds.), Hearing by Bats (pp. 191–234). Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2556-0_5 Kössl, M., & Vater, M. (1996). Further studies on the mechanics of the cochlear partition in the mustached bat. II. A second cochlear frequency map derived from acoustic distortion products. Hear. Res., 94, 78–86. https://doi.org/10.1016/0378-5955(96)00006-8 92  Lammers, M. O., & Castellote, M. (2009). The beluga whale produces two pulses to form its sonar signal. Biol. Lett., 5(3), 297–301. https://doi.org/10.1098/rsbl.2008.0782 Lee, H. Y., Raphael, P. D., Xia, A., Kim, J., Grillet, N., Applegate, B. E., … Oghalai, J. S. (2016). Two-Dimensional Cochlear Micromechanics Measured In Vivo Demonstrate Radial Tuning within the Mouse Organ of Corti. J. Neurosci., 36(31), 8160–8173. https://doi.org/10.1523/JNEUROSCI.1157-16.2016 Lei, R., Xie, H., Wang, J., Leppäranta, M., Jónsdóttir, I., & Zhang, Z. (2015). Changes in sea ice conditions along the Arctic Northeast Passage from 1979 to 2012. Cold Reg. Sci. Technol., 119, 132–144. https://doi.org/10.1016/j.coldregions.2015.08.004 Lim, D. J. (1980). Cochlear anatomy related to cochlear micromechanics. A review. J. Acoust. Soc. Am., 67(5), 1686–1695. Lim, D. J. (1986). Functional structure of the organ of Corti: a review. Hear. Res., 22(1–3), 117–146. https://doi.org/10.1016/0378-5955(86)90089-4 Lim, D. J., & Dunn, D. E. (1979). Anatomic correlates of noise induced hearing loss. Otolaryngol. Clin. North Am., 12(3), 493–513. Lim, D. J., & Melnick, W. (1971). Acoustic Damage of the Cochlea. Arch. Otolaryngol., 94, 294–305. Liu, Y., Gracewski, S. M., & Nam, J. (2015). Consequences of Location-Dependent Organ of Corti Micro-Mechanics. PLoS One, 10(8), 1–25. https://doi.org/10.1371/journal.pone.0133284    93  Liu, Y., Han, N., Franchini, L. F., Xu, H., Pisciottano, F., Elgoyhen, A. B., … Zhang, S. (2012). The voltage-gated potassium channel subfamily KQT member 4 (KCNQ4) displays parallel evolution in echolocating bats. Mol. Biol. Evol., 29(5), 1441–1450. https://doi.org/10.1093/molbev/msr310 Madsen, P. T., & Surlykke, A. (2013). Functional Convergence in Bat and Toothed Whale Biosonars, 28(5), 276–283. https://doi.org/10.1152/physiol.00008.2013 Mooney, T. A., Yamato, M., & Branstetter, B. K. (2012). Hearing in Cetaceans : From Natural History to Experimental Biology. In Advances in Marine Biology (1st ed., Vol. 63, pp. 197–246). Elsevier Ltd. https://doi.org/10.1016/B978-0-12-394282-1.00004-1 Morell, M., & André, M. (2009). Cetacean Ear Extraction and Fixation Protocol. Inst. Neurosci. Montpellier, (Figure 2), 2–7. Morell, M., Brownlow, A., McGovern, B., Raverty, S. A., Shadwick, R. E., & André, M. (2017). Implementation of a method to visualize noise-induced hearing loss in mass stranded cetaceans. Sci. Rep., 7, 41848. https://doi.org/10.1038/srep41848 Morell, M., Degollada, E., Alonso, J. M., Jauniaux, T., & André, M. (2009). Decalcifying odontocete ears following a routine protocol with RDO®. J. Exp. Mar. Bio. Ecol., 376(2), 55–58. https://doi.org/10.1016/j.jembe.2009.05.005 Morell, M., Lenoir, M., Shadwick, R. E., Jauniaux, T., Dabin, W., Begeman, L., … André, M. (2015). Ultrastructure of the Odontocete Organ of Corti: Scanning and transmission electron microscopy. J. Comp. Neurol., 523(3), 431–448. https://doi.org/10.1002/cne.23688 Müller, M. (1991). Frequency representation in the rat cochlea. Hear. Res., 51, 247–254.   94  Müller, M., Hoidis, S., & Smolders, J. W. T. (2010). A physiological frequency-position map of the chinchilla cochlea. Hear. Res., 268(1–2), 184–193. https://doi.org/10.1016/j.heares.2010.05.021 Müller, M., & Smolders, J. W. T. (2005). Shift in the cochlear place-frequency map after noise damage in the mouse. Neuroreport, 16(11), 1183–1187. https://doi.org/10.1097/00001756-200508010-00010 Müller, M., Von Hünerbein, K., Hoidis, S., & Smolders, J. W. T. (2005). A physiological place-frequency map of the cochlea in the CBA/J mouse. Hear. Res., 202(1–2), 63–73. https://doi.org/10.1016/j.heares.2004.08.011 Nachtigall, P. E., & Moore, P. W. B. (Eds.). (1988). A and Processes -nimal Sonar  st ed.). New York: Plenum Publishing Corporation1( Performance.  Neuweiler, G. (1989). Foraging Ecology and Audition in Echolocating Bats. Trends Ecol. Evol., 4(6), 160–166. Ni, G., Elliott, S. J., & Baumgart, J. (2016). Finite-element model of the active organ of Corti. J. R. Soc. Interface, 13(20150913), 1–12. https://doi.org/10.1098/rsif.2015.0913 Ou, H. C., Harding, G. W., & Bohne, B. A. (2000). An anatomically based frequency-place map for the mouse cochlea. Hear. Res., 145(1–2), 123–129. https://doi.org/10.1016/S0378-5955(00)00082-4 Parker, J., Tsagkogeorga, G., Cotton, J. A., Liu, Y., Provero, P., Stupka, E., & Rossiter, S. J. (2013). Genome-wide signatures of convergent evolution in echolocating mammals. Nature, 502, 228–231. https://doi.org/10.1038/nature12511   95  Parsons, K. J., Robinson, B. W., & Hrbek, T. (2003). Getting into shape : An empirical comparison of traditional truss-based morphometric methods with a newer geometric method applied to New World cichlids. Environ. Biol. Fishes, 67, 417–431. Pollack, G. D., & Casseday, J. H. (1989). Tonotopic Organization. In The neural basis of echolocation in bats (pp. 25–39). Berlin Heidelberg: Springer Berlin Heidelberg. https://doi.org/https://doi-org.ezproxy.library.ubc.ca/10.1007/978-3-642-83662-6_2 Pollock, L. M., & Mcdermott Jr., B. M. (2015). The Cuticular Plate : A Riddle , Wrapped in a Mystery , Inside a Hair Cell. Birth Defects Res. (Part C), 105, 126–139. https://doi.org/10.1002/bdrc.21098 Pujol, R., Lenoir, M., Ladrech, S., Tribillac, F., & Rebillard, G. (1992). Correlation Between the Length of Outer Hair Cells and the Frequency Coding of the Cochlea. In Y. CAZALS, K. HORNER, & L. DEMANY (Eds.), Auditory Physiology and Perception (pp. 45–52). Pergamon. https://doi.org/https://doi.org/10.1016/B978-0-08-041847-6.50011-3 Raphael, Y., & Altschuler, R. A. (2003). Structure and innervation of the cochlea. Brain Res. Bull., 60(5–6), 397–422. https://doi.org/10.1016/S0361-9230(03)00047-9 Rasband, W. S. (1997). ImageJ. Bethsada, Maryland: U.S. National Institutes of Health. Retrieved from https://imagej.nih.gov/ij/ Rhode, W. S., & Recio, A. (2000). Study of mechanical motions in the basal region of the chinchilla cochlea. J. Acoust. Soc. Am., 107(6), 3317–3332. https://doi.org/10.1121/1.429404    96  Ridgway, S. H., & Carder, D. A. (1988). Nasal pressure and sound production in an echolocating white whale, Delphinapterus leucas. In P. E. Nachtigall & P. Moore (Eds.), A New York: Plenum60). –53(1st ed., pp.  Processes and Performance -nimal Sonar  ishing CorporationPubl.  Rohlf, F. J. (2004a). TPSDig2, Version 2.26. Stony Brook, New York: Department of Ecology and Evolution, State University of New York (SUNY). Retrieved from http://life.bio.sunysb.edu/morph Rohlf, F. J. (2004b). TPSUtil, Version 1.70. Stony Brook, New York: Department of Ecology and Evolution, State University of New York (SUNY). Retrieved from http://life.bio.sunysb.edu/morph/ Rohlf, F. J., & Marcus, L. F. (1993). A Revolution in Morphometrics. Trends Ecol. Evol., 8(4), 129–132. https://doi.org/https://doi.org/10.1016/0169-5347(93)90024-J Roth, B., & Bruns, V. (1992). Postnatal development of the rat organ of Corti II. Hair cell receptors and their supporting elements. Anat. Embryol. (Berl)., 185, 571–581. Roth, E. H. (2008). Arctic Ocean Long-Term Acoustic Monitoring: Ambient Noise, Environmental Correlates, and Transients North of Barrow, Alaska. Schweitzer, L., Lutz, C., Hobbs, M., & Weaver, S. P. (1996). Anatomical correlates of the passive properties underlying the developmental shift in the frequency map of the mammalian cochlea. Hear. Res., 97, 84–94. Sensor, J. D., Suydam, R., George, J. C., Liberman, M. C., Lovano, D., Rhaganti, M. A., … Thewissen, J. G. M. (2015). The spiral ganglion and Rosenthal’s canal in beluga whales. J. Morphol., 276(12), 1455–1466. https://doi.org/10.1002/jmor.20434  97  Shen, Y. Y., Liang, L., Li, G. S., Murphy, R. W., & Zhang, Y. P. (2012). Parallel evolution of auditory genes for echolocation in bats and toothed whales. PLoS Genet., 8(6), e1002788. https://doi.org/10.1371/journal.pgen.1002788 Simmons, J. A. (1973). The resolution of target range by echolocating bats. J. Acoust. Soc. Am., 54(1), 157–173. https://doi.org/10.1121/1.1913559 Simmons, J. A., & Stein, R. A. (1980). Acoustic Imaging in Bat Sonar : Echolocation Signals and the Evolution of Echolocation. J. Comp. Physiol. A, 135, 61–84. Solntseva, G. (2010). Morphology of the inner ear in mammals with different ecological peculiarities in ontogeny. Vestn. Zool., 44(3), 1–18. https://doi.org/10.2478/v10058-010-0013-y Soons, J. A. M., Ricci, A. J., Steele, C. R., & Puria, S. (2015). Cytoarchitecture of the Mouse Organ of Corti from Base to Apex, Determined Using In Situ Two-Photon Imaging. JARO - J. Assoc. Res. Otolaryngol., 16(1), 47–66. https://doi.org/10.1007/s10162-014-0497-1 Spicer, S. S., & Schulte, B. A. (1994). Differences along the place-frequency map in the structure of supporting cells in the gerbil cochlea. Hear. Res., 79, 161–177. Tsuji, J., & Liberman, M. C. (1997). Intracellular labeling of auditory nerve fibers in guinea pig: Central and peripheral projections. J. Comp. Neurol., 381(2), 188–202. https://doi.org/10.1002/(SICI)1096-9861(19970505)381:2<188::AID-CNE6>3.0.CO;2-# Tyack, P. L., & Clark, C. W. (2000). Communication and Acoustic Behavior of Dolphins and Whales. In W. W. L. Au, A. N. Popper, & R. R. Fay (Eds.), Hearing by Whales and Dolphins (pp. 156–224). New York: Springer-Verlag.   98  Vater, M., Feng, A. S., & Betz, M. (1985). An HRP-study of the frequency-place map of the horseshoe bat cochlea: Morphological correlates of the sharp tuning to a narrow frequency band. J. Comp. Physiol. A, 157, 671–686. Vater, M., & Kössl, M. (1996). Further studies on the mechanics of the cochlear partition in the mustached bat. I. Ultrastructural observations on the tectorial membrane and its attachments. Hear. Res., 94, 63–77. https://doi.org/10.1016/0378-5955(96)00005-6 Vater, M., & Kössl, M. (2011). Comparative aspects of cochlear functional organization in mammals. Hear. Res., 273(1–2), 89–99. https://doi.org/10.1016/j.heares.2010.05.018 Vater, M., & Lenoir, M. (1992). Ultrastructure of the Horseshoe Bat’s Organ of Corti. I. Scanning Electron Microscopy. J. Comp. Neurol., 318, 367–379. Vater, M., Lenoir, M., & Pujol, R. (1992). Ultrastructure of the Horseshoe Bat’s Organ of Corti. II. Transmission Electron Microscopy. J. Comp. Neurol., 318, 380–391. Vater, M., & Siefer, W. (1995). The cochlea of Tadarida brasiliensis: specialized functional organization in a generalized bat. Hear. Res. https://doi.org/10.1016/0378-5955(95)00188-3 Von Békésy, G. (1960). Experiments in Hearing. (E. G. Wever, Ed.). McGraw-Hill. Wartzok, D., & Ketten, D. R. (1999). Marine Mammal Sensory Systems. In J. Reynolds & S. Rommel (Eds.), Biology of Marine Mammals (pp. 117–175). Washington, D.C.: Smithsonian Institution Press. https://doi.org/10.1007/978-1-4615-3406-8 Wartzok, D., Popper, A. N., Gordon, J., & Merrill, J. (2003). Factors Affecting the Responses of Marine Mammals to Acoustic Disturbance. Mar. Technol. Soc. J., 37(4), 6–15. https://doi.org/10.4031/002533203787537041   99  Webster, M., & Sheets, H. D. (2010). A PRACTICAL INTRODUCTION TO LANDMARK-BASED GEOMETRIC MORPHOMETRICS. Paleontol. Soc. Pap., 16, 163–188. https://doi.org/doi:10.1017/S1089332600001868 Wever, E. . G., McCormick, J. G., Palin, J., & Ridgway, S. H. (1972). Cochlear structure in the dolphin, Lagenorhynchus obliquidens. Proc. Natl. Acad. Sci. U. S. A., 69(3), 657–661. https://doi.org/10.1073/pnas.69.3.657 Wever, E. G., McCormick, J. G., Palin, J., & Ridgway, S. H. (1971a). The cochlea of the dolphin, Tursiops truncatus: General morphology. Proc. Natl. Acad. Sci. U. S. A., 68(10), 2381–2385. https://doi.org/10.1073/pnas.68.10.2381 Wever, E. G., McCormick, J. G., Palin, J., & Ridgway, S. H. (1971b). The cochlea of the dolphin, Tursiops truncatus: General morphology. Proc. Natl. Acad. Sci. U. S. A., 68(10), 2381–2385. https://doi.org/10.1073/pnas.68.10.2381 Wever, E. G., McCormick, J. G., Palin, J., & Ridgway, S. H. (1971). The cochlea of the dolphin, Tursiops truncatus: hair cells and ganglion cells. Proc. Natl. Acad. Sci. U. S. A., 68(12), 2908–2912. Yao, Q., Zeng, J. Y., Zheng, Y. M., Latham, J., Liang, B., Jiang, L., & Zhang, S. Y. (2007). Characteristics of echolocating bats’ auditory stereocilia length, compared with other mammals. Sci. China, Ser. C Life Sci., 50(4), 492–496. https://doi.org/10.1007/s11427-007-0055-8 Yarin, Y. M., Lukashkin, A. N., Poznyakovskiy, A. A., Meißner, H., Fleischer, M., Baumgart, J., … Zahnert, T. (2014). Tonotopic morphometry of the lamina reticularis of the guinea pig cochlea with associated microstructures and related mechanical implications. JARO - J. Assoc. Res. Otolaryngol., 15(1), 1–11. https://doi.org/10.1007/s10162-013-0420-1 100  Appendices  Appendix A   Beluga cochlear sample processing    A.1 Sample treatment specifics for both the fixation and decalcification processes. Time post mortem refers to the time between the death of the animal and fixation of the ears.        Beluga ID Ear (Right/Left) Perfusion Time Post Mortem (hours) Fixation Solution Decalcification Solution  1 Right yes 3.25 2.5% glutaraldehyde in PB RDO®    Left yes 3 2.5% glutaraldehyde in PB RDO®  2 Right yes 4.75 2.5% glutaraldehyde in CB RDO®    Left no 5 2.5% glutaraldehyde in CB RDO®  3 Right yes 2 - 3 10% neutral buffered formalin RDO®    Left no 1.5 - 2.5 10% neutral buffered formalin RDO®  4 Right yes 2.25 - 3.25 2.5% glutaraldehyde in CB EDTA   Left yes 2.5 - 3.75 2.5% glutaraldehyde in CB RDO®  Note: Buffers used with glutaraldehyde: CB = 0.1 M cacodylate buffer, pH 7.3; PB = 0.1 M phosphate buffer, pH 7.4             101  Appendix B  Geometric Morphometrics  B.1 Geometric morphometrics - landmarks   Landmark number Description IHC 1 leftmost middle point of the first IHC 2 rightmost middle point of the first IHC 3 upper middle point of the first IHC 4 lower middle point of the first IHC 5 leftmost middle point of the second IHC 6 rightmost middle point of the second IHC 7 upper middle point of the second IHC 8 lower middle point of the second IHC 9 leftmost middle point of the third IHC 10 rightmost middle point of the third IHC 11 upper middle point of the third IHC 12 lower middle point of the third IHC OHC1 13 leftmost point of the first OHC1 in line with the end of the stereocilia 14 rightmost point of the first OHC1 in line with the end of the stereocilia 15 upper middle point of the first OHC1 in line with the W 16 lower middle point of the first OHC1 in line with the W 17 projection of the middle point between the 2 lower edges of the W 18 leftmost point of the second OHC1 in line with the end of the stereocilia 19 rightmost point of the second OHC1 in line with the end of the stereocilia 20 upper middle point of the second OHC1 in line with the W 21 lower middle point of the second OHC1 in line with the W 22 projection of the middle point between the 2 lower edges of the W 23 leftmost point of the third OHC1 in line with the end of the stereocilia 24 rightmost point of the third OHC1 in line with the end of the stereocilia 25 upper middle point of the third OHC1 in line with the W 26 lower middle point of the third OHC1 in line with the W 27 projection of the middle point between the 2 lower edges of the W     102      Landmark number Description OHC2 28 leftmost point of the first OHC2 in line with the end of the stereocilia 29 rightmost point of the first OHC2 in line with the end of the stereocilia 30 upper middle point of the first OHC2 in line with the W 31 lower middle point of the first OHC2 in line with the W 32 projection of the middle point between the 2 lower edges of the W 33 leftmost point of the second OHC2 in line with the end of the stereocilia 34 rightmost point of the second OHC2 in line with the end of the stereocilia 35 upper middle point of the second OHC2 in line with the W 36 lower middle point of the second OHC2 in line with the W 37 projection of the middle point between the 2 lower edges of the W 38 leftmost point of the third OHC2 in line with the end of the stereocilia 39 rightmost point of the third OHC2 in line with the end of the stereocilia 40 upper middle point of the third OHC2 in line with the W 41 lower middle point of the third OHC2 in line with the W 42 projection of the middle point between the 2 lower edges of the W OHC3 43 leftmost point of the first OHC3 in line with the end of the stereocilia 44 rightmost point of the first OHC3 in line with the end of the stereocilia 45 upper middle point of the first OHC3 in line with the W 46 lower middle point of the first OHC3 in line with the W 47 projection of the middle point between the 2 lower edges of the W 48 leftmost point of the second OHC3 in line with the end of the stereocilia 49 rightmost point of the second OHC3 in line with the end of the stereocilia 50 upper middle point of the second OHC3 in line with the W 51 lower middle point of the second OHC3 in line with the W 52 projection of the middle point between the 2 lower edges of the W 53 leftmost point of the third OHC3 in line with the end of the stereocilia 54 rightmost point of the third OHC3 in line with the end of the stereocilia 55 upper middle point of the third OHC3 in line with the W 56 lower middle point of the third OHC3 in line with the W 57 projection of the middle point between the 2 lower edges of the W  

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
https://iiif.library.ubc.ca/presentation/dsp.24.1-0372307/manifest

Comment

Related Items