Signs of trauma, whether accidental or deliberate (see Table 8.1) are commonly found on human remains. Fractures are the most frequent form of trauma found in assemblages recovered from urban or rural cemeteries. However, at certain times, evidence of wounding is quite common, and in later periods, signs of surgical or anatomical intervention may be apparent. Occasionally a skeleton with signs of hanging or beheading is uncovered, to the delight of all involved. Trauma may also be inflicted on the skeleton after it is buried. The weight of soil during burial will tend to flatten the skeleton so that the rib cage, the pelvic girdle and the skull may be fragmented. Further fragmentation or other damage may also occur at the hands of excavators, washers and – even dare one say – of palaeopathologists! It may be difficult to differentiate trauma that occurred at or around the time of death from that suffered after burial and there is no doubt that some peri-mortem trauma will not be recognised. Breaks to bones that occur during or after recovery should present no difficulty, however, as the broken surfaces will be of a much lighter colour than the rest of the skeleton.

In this chapter, broken and dislocated bones, wounding, some aspects of medical trauma, including trephination, and some special forms of trauma including spondylolysis and osteochondritis dissecans will be discussed.

As paleontologists, Chester Stock and Hildegard Howard were interested in the abundance of the mammals that had walked the landscape and birds that had flown in the air above the landscape at the time the faunal remains from Rancho La Brea were deposited (Chapter 1). Zooarchaeologists (known as archaeozoologists in Europe), on the other hand, are typically interested in which taxa provided the most economic resources and which taxa provided little in the way of economic resources. Thus, as zooarchaeologist Dexter Perkins (1973:369) noted, “the primary objective of faunal analysis of material from an archaeological site [or from a paleontological site] is to establish the relative frequency of each species.” This target variable sought by paleontologists and zooarchaeologists concerns taxonomic abundances. What are the frequencies of the taxa in a collection?

In any given collection of paleozoological remains, one might wish to know if carnivores are less abundant than herbivores, just as they normally are on the landscape. Given what he knew about ecological trophic structure – that herbivores should outnumber carnivores – imagine Stock's surprise to learn that the typically observed food pyramid or ecological trophic structure was upside down. The mammalian remains from Rancho La Brea represented more carnivores than herbivores − for a reason that many paleontologists thought was a taphonomic reason – because scavenging carnivores got “bogged down” or mired in the sticky tar seeping from the ground and failed to escape.

The minimum number of individuals (MNI) is typically defined as something like “the most frequently occurring skeletal part” (Table 2.4). Variation in how that definition can be operationalized – are differences in size, age, sex, or recovery context (aggregation) considered – renders MNI as a derived measure. But on a general, in some ways less discriminating scale, how the basic definition of MNI is operationalized is simply this: Given all the remains of a taxon in a collection (how the spatiotemporal boundaries of that collection are defined need not concern us initially), redundant skeletal parts are each tallied as a single MNI. Redundant skeletal parts means that specimens overlap anatomically. Two left femora of deer overlap anatomically and are redundant with one another, just as are two upper right second molars, three right distal humeri, and four left innominates. In the order listed, the MNI values are 2, 2, 3, and 4. To reiterate, redundant – that is, anatomically overlapping – skeletal parts each represent a unique individual or a tally of one MNI.

How MNI is operationalized on a general scale – by redundant skeletal parts – forces us to recognize a previously unmentioned quantitative unit. That unit was not really distinctively named until 1982, but it had played an important role in paleozoology for decades prior to that time. Today that quantitative unit is known as the minimum number of elements, or MNE.

Taphonomy is a term coined by Russian paleontologist I. A. Efremov (1940) from the Greek words taphos (burial) and nomos (law). Efremov meant for taphonomy to specify the transition, in all details, of organics from the biosphere to the lithosphere. In the context of this book (recall Figure 2.1), taphonomy concerns the agents and process(es) that influence an animal carcass from the moment of that animal's death until its remains (if any survive the vicissitudes of time) are recovered by the paleozoologist, and also the kind and magnitude of those influences. There are a plethora of taphonomic agents and processes that variously disarticulate, disperse, alter, and destroy carcass tissues, including bones and teeth (Lyman 1994c).

In this chapter, techniques for tallying what are sometimes referred to as taphonomic signatures, features, or attributes evident on faunal remains are introduced. Identifying the taphonomic agents and processes that influenced an assemblage of faunal remains assists interpretation of the remains. (If the agent is biological, then the taphonomic feature is a trace fossil [Gautier 1993; Kowalewski 2002].) Do, for example, those remains reflect what human hunters ate or do they represent a fluvially winnowed set of skeletons of animals that died during a seasonal crossing of a river at flood stage? Determination of the taphonomic history of a collection of faunal remains may reveal aspects of paleoecology not otherwise evident among the collection of remains, such as evidence of carnivore gnawing on ungulate bones when no carnivore remains are recovered.

It is commonsensical to note that what is recovered – the amount recovered of each kind, and the number of kinds – will influence quantitative analyses (Cannon 1999). As we have seen in earlier chapters, sample size influences many measures and estimates of taxonomic abundances. The size of a sample of faunal remains measured as the number of specimens recovered is in turn influenced by the sampling design chosen (how much is excavated) and the recovery techniques (passing sediment through fine- or coarse-mesh sieves) used to implement that sampling design. This chapter focuses on how one generates a collection of faunal remains (sampling and recovery), properties of the resultant sample, and ways to examine the influences of sample size on selected target variables.

Paleozoologists have long worried about how methods of recovery might produce collections that are not representative of a target variable (e.g., Hibbard 1949; Kuehne 1971; McKenna 1962; Payne 1972; Thomas 1969). Exacerbating this worry is the fact that paleozoologists collect samples of faunal remains from geological contexts (Krumbein 1965; Ward 1984). This is true on at least two levels. First, paleozoologists never (or at least very seldom) collect all of the faunal remains from a deposit, paleontological location, or archaeological site. Second, the target variable usually resides in an entity other than the “identified assemblage” (Figure 2.1).

In Chapter 2, the two methods of measuring taxonomic abundances – NISP and MNI – most commonly used in paleozoology were discussed. In this chapter other methods that have been used to quantify taxonomic abundances or what is sometimes loosely referred to as taxonomic importance are described. In so doing, perhaps methods that work better than NISP and MNI in some situations can be identified. And, we can explore how and why some of these methods are less accurate, valid, or reliable than NISP, MNI, or each other, and whether or not they should be used at all. This last point is critical because virtually all of the alternative methods discussed here have occasionally been advocated as better than NISP or MNI as measures of taxonomic abundances within a biocoenose. Because most of them were proposed 20 or more years ago, it seems appropriate to evaluate them in light of the new knowledge that has been gained over the past two decades.

The problems that attend NISP and MNI suggest that counting units different than MNI and NISP should be designed and used. And the literature contains arguments that counting units other than NISP and MNI should be used to determine taxonomic abundances. Clason (1972:141), for example, argues that MNI should be termed the “estimated minimum number of individuals,” and he uses the word estimated “intentionally because a real calculation of the minimum number of individuals is not possible.”

Early in the twentieth century, paleontologist Chester Stock (1929) was, as he put it, faced with “recording a census” of large mammals from the late Pleistocene as evidenced by their remains recovered “from the asphalt deposits of Rancho La Brea,” in Los Angeles, California. Paleontologist Hildegarde Howard (1930) was faced with a similar challenge with respect to the bird remains from Rancho La Brea. Stock and Howard could have merely listed the species of mammals and the species of birds, respectively, that were represented by the faunal remains they had – they could have constructed an inventory of taxa – but they chose to do something more informative and more analytically powerful. They tallied up how many individuals of each species were represented by the remains – they each produced a census. The quantitative unit they chose became known as the minimum number of individuals, or MNI, a unit that was quickly (within 25 years) adopted by many paleozoologists. We will consider this unit in some detail in Chapter 2, but here it is more important to outline how Stock and Howard defined it and why they decided to provide a census rather than an inventory of mammals and an inventory of birds.

Stock (1929:282) stated that the tally or “count” of each taxon was “determined by the number of similar parts of the internal skeleton as for example the skull, right ramus of mandible, left tibia, right scaphoid. In many cases the total number of individuals for any single group [read taxon] is probably a minimum estimate.”

One of the most common analytical procedures in paleozoology is to compare faunas from different time periods, from different geographic locales, or both (e.g., Barnosky et al. 2005 and references therein). Comparisons may be geared toward answering any number of questions. Does the taxonomic composition of the compared faunas differ (and why), and if so, by how much (and why)? Does the number of taxa represented (NTAXA) differ between faunas (and why), and if so, by how much (and why)? Do the abundances of taxa vary (and why)? Ignoring the “and why's,” these and similar queries are what can be considered proximal questions. The why questions are the ultimate questions of interest; they constitute a reason(s) to identify and quantify the faunal remains in the first place. Was hominid or human dietary change over time the cause of the change in taxonomic composition, abundance, and so on? Did the environment (particularly the climate) change such that different ecologies prompted a change in the taxa present, the number of taxa present, or the abundances of various taxa? It is beyond the scope of this volume to consider these ultimate why questions other than as examples. The purpose of this chapter is to explore how quantitative faunal data can be analytically manipulated in order to produce answers to these kinds of proximal questions.

Several years ago I had the opportunity to have a relaxed discussion with my doctoral advisor, Dr. Donald K. Grayson. In the course of that discussion, I asked him if he would ever revise his then 20-year-old book titled Quantitative Zooarchaeology, which had been out of print for at least a decade. He said “No” and explained that the topic had been resolved to his satisfaction such that he could do the kinds of analyses he wanted to do. A spur-of-the-moment thought prompted me to ask, “What if I write a revision?” by which I meant not literally a revised edition but instead a new book that covered some of the same ground but from a 20-years-later perspective. Don said that he thought that was a fine idea.

After the conversation with Grayson, I began to mentally outline what I would do in the book. I realized that it would be a good thing for me to write such a book because, although I thought I understood many of the arguments Grayson had made regarding the counting of animal remains when I was a graduate student, there were other arguments made by other investigators subsequent to the publication of Grayson's book that I didn't know (or if I knew of those arguments, I wasn't sure I understood them very well).

In this volume, some of the most basic issues of quantifying different kinds of paleozoological data have been explored. A bit more than two decades ago, Grayson (1984) published a book-length treatment on the same general topic, and that seemed to resolve many of the debates over how to quantify taxonomic abundances. Arguments over whether NISP or MNI was the better measure nearly ceased to appear in the literature. Yet, some individuals continue to report MNI values, either as the unit of choice for quantifying taxonomic abundances (e.g., Avery 1991, 1992; Landon 1996), or apparently for the sake of complete descriptive reporting (e.g., Plug 2004; Stahl and Athens 2001). A few continue to develop innovative ways of tallying MNI (e.g., Vasileiadou et al. 2007). The usual reason given for use of MNI is that NISP is subject to intertaxonomic variation in fragmentation and so gives potentially biased estimates of taxonomic abundances. Although it is true that NISP can influence estimates of taxonomic abundance, those who use the differential fragmentation argument as a warrant to determine MNI values neither empirically evaluate the truthfulness of this warrant in their particular instances nor fail to present NISP data. Why do they present what they take to be biased data? Why do they not determine if in fact fragmentation varies intertaxonomically rather than simply assert that it does? Perhaps they do not because of a lack of mathematical and statistical sophistication. That lack of sophistication is a major reason for this book.

Foreword

An epidemiological study of schistosomiasis at the University of Manchester in the United Kingdom (see Chapter 1) indicated a need for diagnostic tools that could be applied to large numbers of ancient Egyptian tissues. This chapter discusses the successful application of immunocytochemistry to both modern and ancient tissues. This was acheved in an initial investigation in which tissue samples from fifty Egyptian mummies were studied with a view to establishing protocols that are now being applied to a larger epidemiology research project.

Using an indirect fluorescence staining protocol with antisera directed against Schistosoma mansoni and Schistosoma haematobium antigens, positive staining to S. mansoni and S. haematobium antigens in modern tissues, a fifty-year-old tissue sample from an Egyptian cadaver, and ancient Egyptian tissues has been achieved. Immunocytochemistry has proven to be cost effective and easy to perform, and is now a preliminary to other tests.

Although the enzyme-linked immunosorbent assay (ELISA) and other tests such as histology, enzyme immunotransfer blots (EITB), and DNA analysis have also been explored to reinforce the initial immunostaining results, this chapter will focus on the use of immunocytochemistry to diagnose ancient disease. The definition of an immunoassay and the principles of immunocytochemistry are briefly outlined, followed by details of the development of immunocytochemistry as a diagnostic tool for schistosomiasis in ancient tissues. This chapter highlights how experimental principles have been adapted when working with ancient dehydrated samples.