chapter 8 stratigraphy, phylogeny, and species sampling … · stratigraphy, phylogeny, and species...

Chapter 8

STRATIGRAPHY, PHYLOGENY, AND SPECIES SAMPLING IN TIME AND SPACE

Jonathan M. Adrain and Stephen R. Westrop

INTRODUCTION

The potential role of stratigraphic order in.phylogeny reconstruction is among the most contentious issues in contemporary paleontology (e.g., Norell, 1996; Wagner, 1996). Most workers agree that the distribution of taxa in time is essential information which should inform any evolutionary hypothesis. What is not agreed upon is whether that sampled distribution is itself evidence of'relationship, and whether time-ordering should constrain a primary phylogenetic hypothesis. The question boils down to whether relationship should be determined using intrinsic biological information alone, or by using a certain amount of biological information, countermanded to some or other extent by extrinsic temporal information.

In this chapter, we review the conceptual basis for incorporation of temporal order, the methods proposed ("strato-methods" hereafter) and their justifica- tions. Since we are non-believers, we detail the methodological objections to these approaches. In our opinion, strato-methods are damned on theoretical grounds alone. Time is not an instrinsic property of organisms or taxa, and temporal "data" can only exist in light of prior phylogenetic hypotheses-and morphologic data. The degree of compliance with the sampled order of taxa

JONATHAN M ADRAIN Department of Geoscience, University of Iowa, Iowa City Iowa 52242 STEPHEN R WESTROP - School of Geology and Geophysics, University of Oklahoma, Norman, Oklahoma 73019

Fossils. Phylogeny, and Form, Volume 19 of Topics tn Geobiology, edited by Jonathan M. Adrain et al. Kluwer Academic/Plenum Publishers, New York, 2001.

292 Fossils, Phylogeny, and Form: An Analytical Approach

required by strato-methods is arbitrary and purely subjective. And if we base phyiogenies and taxa on temporal criteria, we rob ourselves of the rich pos- sibilities of applying those phylogenetic and taxic data to any temporal problems in paleobiology, including the entire taxic paleobiology research program (Adrain and Westrop, 2000).

Beyond these basic reasons to reject strato-methods are the immense, barely explored, practical problems inherent in the implementation of any such approach. Taxa are distributed in space as well as in time, and any attempt to over-ride comparative anatomy based on this distribution must confront, in explicit detail and for all taxa considered, the quality of spatial and environmental sampling.

We compare a trilobite phylogeny derived using morphology and standard parsimony techniques with an environmental sampling survey of the study taxa. Late Cambrian Laurentian trilobites have one of the best-known fossil records of any fossil group at any time, yet the sampling obstacles remain profound and can at best be accounted for only through a mammoth effort, even for a relatively small analysis.

RECONSTRUCTING PHYLOGENY WITH AND WITHOUT TEMPORAL "DATA"

Cladistic parsimony analysis was adopted rather slowly by invertebrate paleontologists, especially as compared to vertebrate workers or systematic biologists in general. Sadly, many workers still pursue what might be termed "traditional taxonomy" - the authoritarian assertion of relationship using no explicit method, but involving subjective, ahistorical comparisons of "simi-

b

larities" and "differences" often combined with ancestor-descendant lineages read directly from the rocks. Nevertheless, the vast majority of invertebate paleontologists who use explicit numerical methods now apply some form of parsimony analysis. The pace of such phylogenetic studies has gathered momentum over the past decade, and it is now safe to say that cladistic hy- i

potheses are becoming the norm (e.g., Adrain and Chatterton, 1990; Adrain and Chatterton, 1994; Brower, 1995; Lespkrance and Desbiens, 1995; Robison and Wiley, 1995; Surnrall and Sprinkle, 1995; Westrop et al., 1996; Adrain and Edgecombe, 1997; Adrain and Ramskold, 1997; Chatterton et al., 1997; Edgecombe et al., 1997; Roopnarine, 1997; Ruta, 1997; Ruta and Theron, 1997; Scrham et al., 1997: Sundberg and McCollum, 1997; Adrain, 1998; Chatterton et al., 1998; Dean and Smith, 1998; Edgecombe et al., 1998; Johnson, 1998; Lieberman, 1998; Taylor et al., 1998; Williams et al., 1998; I

Azar e t ai., 1999: Cusack et al., 1999; Ebach and Edgecombe, 1999; Edgecombe and Ramskoid, 1999; Jeffery, 1999; Monks, 1999; Popov et al., 1999; Schram et al., 1999; Stone and Telford, 1999; Sundberg, 1999; Haasl, 2000; Lefebvre, 2000; Monks and Owen, 2000; Mooi et al., 2000; Sumrall et

Stratigraphy, Phylogeny, and Species Sampling 293

al., 2000; Tshudy and Sorhannus, 2000a, 2000b; Westrop and Ludvigsen, 2000; Adrain et al., 2001; Donoghue, 2001).

In contrast, only a few quantitative empirical studies which attempt to make use of stratigraphic order have appeared. Nevertheless, there is considerable recent interest in the use of temporal constraints, particularly in the realm of theory, centered around a handful of individuals and research groups. Fisher (1988, 1991, 1992, 1994) has developed "stratocladistics," a method used almost exclusively to date by workers with some connection to the Univer- sity of Michigan (relatively few studies have actually been published: e.g., Bodenbender, 1995; Clyde and Fisher, 1997; Polly, 1997; Fox et al., 1999; Bodenbender and Fisher, 2001; although a few more exist as abstracts: e.g.. Bloch and Fisher, 1996; Fisher, 1997). Wagner has fashioned a research program (e.g., Wagner, 1995, 1996, 1998b, 2000a, 2000b, 2000d) with the apparent rationale of voicing as many objections as possible to conventional parsimony analysis in paleontology. His alternative (Wagner, 1998a, 2000c) is a hybrid melange of cladistics, assessment of "stratigraphic debt", maximum likelihood theory, and simulation. Finally, Huelsenbeck and Rannaia (1997, 2000) have explored the incorporation of stratigraphic data using maximum likelihood approaches.

While many workers are willing to use stratigraphic congruence in a sec- ondary role to, for example, calibrate character-based cladograms, choose between equally parsimonious topologies or even develop explicit, temporal evolutionary trees (e.g., Norell, 1992, 1993; Smith, 1994; Adrain and Edgecombe, 1997), most working systematists have avoided the direct use of stratigraphy to derive phylogenies. Beyond the groups and individuals listed above, applications of strato-methods by systematists are limited to a small number of stratocladistic exercises (e.g., Haasl and Carlson, 1996; Harvey and Ausich, 1997; Haasi, 1999).

The rationale for constraining phylogenetic hypotheses using stratigraphy is based on the supposition that, in general, taxa are preserved in "the right order." Ancestors, by definition, must have existed in time prior to their de- scendents (even if, depending on one's ontological bent, they might also have coexisted with or even outlived any descendent). If the fossil record is adequately sampled, then, the recovered order of taxa in time must contain some substantial amount of information on the order of phylogenetic events.

Assuming there is wisdom in that position, the question of how, operationally, to admit stratigraphic data to quantitative analyses arises. Most would regard simply coding stratigraphy as an irreversable character (e.g., Kosnik, 1997; Nutzel et al., 2000), and thereby forcing a direct temporal fit, no matter how unparsimonious, as naive. Similarly, a priori temporal partitioning of taxa, with separate analyses for each time-slice (e.g., Ausich, 1998), will also obviate much of the point of character analysis and promote wildly sub-op- timal phylogenies. Clearly, if stratigraphic data are to be used, their integration

294 Fossils, Phylogeny, and Form: An Analytical Approach Stratigraphy, Phylogeny, and Species Sampling 295

must be more sophisticated than these simple, brute-force techniques. There are currently two approaches with at least some advocates: stratocladistics and stratolikelihood.

Stratocladistics

Stratocladistics was introduced and developed by Fisher (1988, 1991, 1992. 1994). The method seeks a form of compromise between conventional character-based parsimony analyses and the fit of such hypotheses to the stratigraphic distribution of taxa. In stratocladistics, the number of ad hoc assumptions of homoplasy required by character conflicts is termed the "morphologic parsimony debt." Time is atomized into discrete, countable, intervals, and for a given phylogeny, the number of instances in which the tree predicts the presence of a taxon in an interval from which it has not been recovered is summed and termed the "stratigraphic parsimony debt," since each such in- stance in effect requires an ad hoc hypothesis of sampling failure. The method claims equivalence of these "parsimony debts," and advocates the selection of a cladogram which minimizes their combined score. The appeal of stratocladistics is the application of what it would have us view as comple- mentary but independent sources of data of relevance to phylogeny. Several studies implementing some form of the methodology have appeared, and the approach was the basis for a recent claim for the superiority of temporal-based techniques (Fox et al., 1999).

The cardinal problem with stratocladistics is that time is not a discrete variable which can be treated as a property of a taxon. Time is continuous, and its subdivision into countable intervals for purposes of the method has no obvious rationale and no optimality criterion (Huelsenbeck and Rannala, 2000; Smith, 2000). How subdivided should time be? The length of the cho- sen temporal subdivisions is arbitrary, yet it directly controls the relative influence of stratigraphic constraint versus character data on the resulting cladogram. Longer arbitrary time intervals will require less stratigraphic fit and favor character-based trees. Shorter arbitrary time intervals will force increas- ing stratigraphic fit and favor non-parsimonious compliance with the sampled order of taxa. In the absence of any conceivable optimality criterion, stratocladistics amounts to little more than a procedure to force arbitrary and subjective amounts of fit to sampled stratigraphic first appearances. It should be abandoned as a serious method to reconstruct evolutionary history.

Stratolikelihood

Unlike stratocladistics, which despite its failings remains a fundamentally pattem-based method (Brochu et al., 2001), stratolikelihood approaches (Huelsenbeck and Rannala, 1997,2000; Wagner, 1998a, 2000c) depend on a

priori models of processes. Maximum likelihood estimation of phylogeny proceeds by assigning probabilities to model parameters (i.e., particular phylogenies) in light of observations under the model. In essence, the method asks how likely a particular phylogeny is given the process model and observed data. Maximum likelihood methods are widely applied to molecular sequence data (see, e.g. Hillis et al., 1996; Li, 1997; Nei and Kumar, 2000), in which the possible range of observations numbers only four and more or less explicit process assumptions can be framed. Exactly how maximum likelihood could be applied to morphological data is unclear. Thus far, only stochastic approaches, such as modelling character-change as Brownian motion (Huelsenbeck and Ranala, 1997) have been suggested (but see Lewis, 2001).

Huelsenbeck and Rannala (1997,2000) have developed a "stratolikeiihood" approach which considers stratigraphic occurrence observations in light of a model of preservational processes. Their approach was not intended to take account, however, of morphological character information (in fact, their claim [Huelsenbeck and Rannala, 1997, p. 1741 that "phylogeny can be estimated without any information on morphological or molecular characters (except those characters used to assign fossil specimens to species)" is inaccurate with respect to their own analysis - an a priori assumption of phyletic relatedness of study "species" must presumably be necessary, and this can only be based upon morphological similarity). Only Wagner (1998a) has attempted to inte- grate character and stratigraphic data in a hybrid approach involving the use of standard parsimony to generate a universe of potential trees, maximum likelihood estimation of extinction rate and sampling parameters. and simulation using datasets with the same parameters as the original and a variety of evolutionary/sampling models. Wagner's method uses the stratocladistic concept of stratigraphic debt as an estimate of sampling intensity in the analysis, and therefore suffers from the problems discussed earlier.

TIME AS "DATA"

Proponents of strato-methods portray their approaches as catholic, embrac- ing more data of relevance to evolutionary reconstruction than purely biological methods. Eaasl(1999), for example, extolls the "numerous advantagesto using all potentially relevant sources of information." Huelsenbeck and Ramala (2000, p. 165) phrase it: "...it is interesting to note that early systematists frequently incorporated additional sources of information into their phylogenetic descriptions that modem systematists now rarely consider." And Fox et al. (1999, p. 1819) claim that " ... stratocladistic hypotheses explain more features of the natural world and hence have greater explanatory power than purely cladistic hypotheses."

But is time "data"? Time in itself can't yield a phylogeny of anything; time is not an intrinsic property of organisms or taxa. Huelsenbeck and Rannala's


(1997) claim that phylogeny can be estimated with no more biological information than that necessary to assign specimens to species is meaningless without a covering assumption drawn from biology: that the species are phyl- etically related. In its absence, the method could as easily yield a "phylogeny" of arrowheads, or strangely shaped calcareous nodules, or dirt. One wouldn't attempt to infer phyletic relationship between a trilobite, a Triceratops, and a tricycle because they occurred in stratigraphic sequence. Yet strato-methods are happy to have us infer phyletic relationship of congeneric species of trilobites or Triceratops based on stratigraphic sequence. Why?

The difference appears to be that strato-methods can only be applied if one already has knowledge of relationship. In paleontology, except in the most exceptional circumstances where genetic material is recoverable, this knowledge can only have one source: morphology. No matter what approach one takes to paleontological phylogeny reconstruction, any hypothesis must ini- tially be based on morphological data. Morphological data are intrinsic, biological properties of organisms and taxa.

This leads to a logical conundrum: there is evidently some threshold at which morphology breathes relevance into strato-methods, at which point the absurdity of the Triceratops and the tricycle becomes the plausibility of phyletic relationship. However, once this threshold is reached and strato-methods are applied, they proceed by ignoring some or other amount of the very morphological information on which they depend for their relevance.

We have been careful throughout this chapter to avoid the term "temporal data" in favor of "temporal constraint." No matter what type of strato-method is applied, stratigraphic information is not a separate source of data, independent of morphologic information. It cannot exist without reference to already- existing morphologic information. In fact, stratigraphic order can only be applied as an extrinsic constraint, used to countermand and set aside existing, intrinsic, morphological data. For Huelsenbeck and Rannala (1997) the extent of this abjuration of real phylogenetic signal is nearly total. For Fisher and Wagner, it is plastic and subjective, the amount of real data ignored left to the whim of the investigator.

What if morphology is wrong and actually misleading? As pointed out by Smith (2000), simulation-based attempts to discredit parsimony (Wagner, 1998a; Fox et al., 1999) typically depend on this assumption, and use character-state change probabilities set so high that the models are essentially homology-free. What such exercises tell us is that if comparative anatomy is misleading, parsimony methods will fail. If intrinsic biological information truly does not reveal the right answer, however, nothing will. If nature has made phylogeny unrecoverable, phylogeny is unrecoverable. This is not a problem unique to cladistics - it applies in equal measure to any comparative biological approach. We have absolutely no way, for example, of knowing just how much homoplasy is present in a dataset prior to embarking on a


phylogenetic analysis. This is an empirical reality and lies at the heart of parsimony methods - that all we can do under these circumstances is to maximize the explanatory power of the available intrinsic, biological information. We can never know whether a hypothesized phylogeny is correct, or "true." This state of affairs provides no justification for resorting to extrinsic, abiological constraints.

The same applies to arguments championing strato-methods when morphological data are sparse. If sampled stratigraphic order isn't primary phylogenetic information when there's a great deal of biological data. then it's an equally bad idea to use it to read phylogeny when for whatever reason biological data are few. If Paleozoic snail shells (e.g., Wagner. 1995) or Ceno- zoic mammal teeth (e.g., Polly. 1997) yield too few phylogenetic clues. then - sadly - we are unlikely to ever know how those particular Paleozoic snails or Cenozoic mammals evolved. We are not convinced that this is necessarily the case, but suggest that if the situation really is that dire, persons wishing to study evolutionary biology might be wise to pick different animals.

UTILITY OF STRATO-PHYLOGENIES

As we noted above, it is impossible to ever know to what extent morphological information is "correct" or "true," and homoplasy represents a major potential source of systematic error. However, it is equally impossible to ever know to what extent sampled first appearance matches true first appearance. Constraining hypotheses based on comparative anatomy to fit temporal order thus conflates two major sources of uncertainty (Smith, 2000). To what end?

The fossil record is critically important as a source of phylogenetic information in the form of extinct taxa. It represents the only possible way to tem- porally calibrate phylogenies and it is this property - access to the dimension of time (Smith, 2000) - that gives paleontology its unique insight into evolution. The fossil record is not, however, a phylogeny. Any effort to involve temporal "data" in phylogeny reconstruction simply amounts to arbitrary exclusion of some amount of genuine phylogenetic information in favour of the assumption that the preserved order of taxa is an accurate record of evolution.

In addition to basic conceptual flaws, however, strato-methods rob phylogenies of much of their paleobiological power. As long as time is used to con- struct phylogenies and define taxa, those phylogenies and taxa may never be used to address any time-based questions. To do so would be blatantly circu- lar. Strato-methods prohibit the use of phylogenies and taxa to study evolutionary rates, to derive patterns of cohort survivorship (e.g , Foote, 1988), and. especially, to analyze patterns of diversity through time (e.g.. Sepkoski, 1984). One cannot study "macroevolution" if the phylogenetic work needed to


understand it is based on the very same stratigraphy used to map out taxic diversity patterns (cf. Brochu and Norell, 2001).

STRATO-METHODS AND SAMPLING

Even if one accepts that the fossil record is well enough sampled (or that it is possible for it to be well enough sampled, given its fundamentally epi- sodic nature), there are to this point no reasonable methods for integrating temporal information into phylogenies. Strato-methods are conceptually flawed and, even on their own terms, operationally weak.

For the remainder of this chapter, however, we focus on an underexplored objection to methods which depend on stratigraphic sampling for their effi- cacy: direct empirical consideration of how well even the best-sampled fossil records conform to the necessary assumptions of strato-methods. This subject has been broached by MacLeod in a recent Nature Online Debate (http://www.nature.com/nature/debates/fossil/fossil . l3.html; http:// www.nature.com/nature/debates/fossil/fossil20.html), in which he chal- lenged the oft-repeated claims of stratophenetecists about the completeness of the deep-sea foraminifera1 record. MacLeod concluded "I seriously doubt that stratocladistics/likelihood will make much of an impression at the practical level of resolving ambiguities in real morphologically-based phylogenies using real stratigraphical data if the many problems inherent in the latter are honestly acknowledged." We explore this issue further using our own fieid- based data on Cambrian trilobites.

Any attempt to adjust character-based cladograms with stratigraphic order must confront the quality of sampling of the record. Stratocladistics and stratolikelihood (sensu Wagner) both rely on the distribution of stratigraphic gaps to assess "stratigraphic debt." However, fossils are distributed in both time and space, and any method that wishes to assess the quality of sampling and the significance of observed gaps beyond the scale of local stratigraphic sections must also evaluate the geographic and paleoenvironmental distribution of collections.

Some workers have suggested that disagreements over the role of stratigraphy in phylogeny reconstuction are at least in part a reflection of the differ- ing qualities of the records of invertebrate and vertebrate fossils. However, while most paleontologists would agree that the record of invertebrate fossils is far richer than the vertebrate record, it is still incomplete and open to a variety of potential sample biases. For example, all fossils are distributed in time and space, and failure to sample appropriate lithofacies or geographic regions could lead to apparent gaps in the temporal occurrence of taxa. Sam- pling efficiency is commonly estimated from the distribution of collections, but the number of fossils recovered from those collections will also be important. Systematic variation in collection size could influence the stratigraphic


record of taxa. In an effort to gauge the extent of bias in the invertebrate record, we compiled all published data for the stratigraphic distribution of trilobite collections in the Late Cambrian Sunwaptan Stage of Laurentian North America, including the geographic and environmental occurrences of sample horizons. Cambrian trilobites have an excellent fossil record (Raup [I9761 has estimated that 75% of described species of Cambrian skeletonized metazoans are trilobites), and the Sunwaptan Stage is the best sampled interval of the Laurentian Cambrian. The underlying Steptoean Stage is largely incomplete over much of the craton because of a major low sea level stand (Sauk I1 regression of Palmer, 1981), and most of the earlier Cambrian history also involved lower sea level stands than during the Sunwaptan (Lochman-Balk, 1970). Consequently, well-studied sequences of pre- Sunwaptan faunas are restricted to a few regions such as the Great Basin (e.g. Robison, 1964; Palmer, 1965; Palmer and Halley, 1979; Sundberg, 1994). We would argue that the record of Sunwaptan trilobites rivals that of any other invertebrate group or time interval in Laurentia, and yet it contains major biases with respect to the stratigraphic, geographic and environmental distribution of sample horizons.

Against this framework of sampling intensity, we developed a phylogenetic hypothesis for one of the most common and abundant of Sunwaptan trilobite clades, the ptychaspidids. Comparison of the phylogenetic hypothesis with the environmental distribution of its ingroup species should permit an evaluation of the assumption that species-level distributions of trilobite clades are, in generai, adequately sampled, a basic prerequisite for the application of strato- methods.

TRILOBITE SPECIES SAMPLING IN THE LAURENTIAN SUNWAPTAN

Data

Knowledge of the composition and stratigraphic distribution of Sunwaptan trilobite faunas of Laurentia is a product of the last 50 years, largely through the efforts of research groups founded by W. Charles Bell in the United States (e.g. Bell et al., 1952; Bell and Ellinwood, 1962; Grant, 1965; Longacre, 1970; Stitt, 1971, 1977), and later by Rolf Ludvigsen in Canada (Ludvigsen, 1982; Ludvigsen et al., 1989; Westrop, 1986a, 1995). We made an exhaustive search of the literature and complied data on the number of sample horizons documented as well as their stratigraphic, geographic and environmental distribution. We included only those horizons with accompanying taxonomic treatment; faunal lists that lacked information necessary to corroborate iden- tifications (e.g., Hintze et al., 1988) were excluded. We also excluded fourteen small collections from the Hales Limestone of central Nevada (Taylor,


1976) because of uncertainty over their correct correlation within the Sunwaptan. Where abundance data were available, we tallied the total number of trilobite sclerites recovered from each horizon. The data set comprised 1,901 sample horizons from sixteen regions in Canada and the United States and included six broad facies types (nearshore siliciclastics; shallow subtidal carbonates; shallow subtidal shales and carbonates; shelf buildups; shelf- margin carbonates, including buildups, and deep subtidal carbonates [below mean storm wave base]). For the purposes of analysis, we partitioned the Sunwaptan into 4 biostratigraphically divided units (Figure 1).

Results

The stratigraphic distribution of sample horizons is significantly different (G-test, p < .001) from that which would be expected if honzons were evenly distributed through the Sunwaptan (Figure l ) . ~ o r e o v e r , the geographic oc-- currence of sampling horizons is also strikingly uneven. Two of the sixteen regions from which Sunwaptan trilobites have been described, central Texas and central Oklahoma, account for half (48%) of the data (Figure 2); eleven of the remaining fourteen regions contributed less than one-fifth (19%) of the sample horizons. It might be argued that the skewed distribution reflects the abundance of fossils: paleontologists tend to collect in regions in which they meet with most success. However, data on specimens collected per sample in Oklahoma (Figure 3) suggests that the Cambrian sequence in that region is

0 200 400 600 800

NUMBER O F SAMPLE HORIZONS

Stenopilus glaber Zone

2 l-u Proricephalus wilcoxensis Zone a I 5 1 v ~ a e n u r u s z o n e I

; l $ y l Taenicephalus Zone

1 1 Irvinuella major Zone 1

Figure 1 Right Trilobite zones for the Sunwaptan of Laurentian North Amenca (Westrop, 1986) Left Straugraphic distribution of published tnlobite sample honzons for the Sunwaptan of Laurentian North Amenca Samples intervals (Im-T Irvingella major-Taenicephalus zones, So- E, Stigmacephalus oweni-Ellipsocepkaloides zones, /, lllaenurus Zone, Pw-Sg, Proricephalus wilcoxensis-Stenopilus glaber zones) have been scaled according to their thicknesses at Chandler Creek, Oklahoma (Stitt, 1977), a well-documented, complete and essentially monofacial sequence through the Sunwaptan


rather poorly fossiliferous compared to others, and the over-representation of Texas and Oklahoma most likely reflects the movement of W.C. Bell and his research group from the University of Minnesota to the University of Texas in the 1950s.

GEOGRAPHIC REGION

Figure 2 Geographic distributionof sample honzons Histogram shows the number of samples for each geographic region TX, Llano Uplift area, central Texas, OK, Arbuckle and Wichita Mountains, south-central Oklahoma, M-W, south-west Montana and north-west Wyommg, UMV, Upper Mississippi Valley of western Wisconsin and eastern Minnesota, A, southern Alberta, N, Cow Head region, western Newfoundland, SD, Black Hills region, South Dakota, MO, southeast Missouri, MM, Mackenzie Mountains, northern Canada, AK, Alaska-Yukon border region, Other, pooled data for seven areas m Quebec, Vermont, New York State, Pennsylvania-Virginia, Arkansas. eastern Montana and southern Idaho


The sample horizons are far from uniformly distributed among the six lithofacies (Figure 4), with shallow subtidal carbonates yielding half (48%) of collections, and three of the facies types (on-shelf buildups, shelf margin carbonates, and deep subtidal) contributing only slighly more than one-tenth (13%) of the collections. This is a particularly problematic bias because analysis of Cambrian trilobite alpha (within-habitat) diversity (Westrop and Adrain, 1998; see also Ludvigsen and Westrop, 1983a) demonstrates that species richness in the latter three settings was at least equivalent to that recorded in shallow subtidal carbonates; shelf-margin buildups have yielded some of the most speciose trilobite collections known from the Cambrian. Moreover, the pro- portion of horizons contributed by each facies fluctuates substantially between substages of the Sunwaptan, and is even more variable at the zonal level (Fig- ure 4). In all cases, distributions of samples among facies between substages and between all pairs of zones are significantly different (p < .0001) using a G-test. At all levels of stratigraphic resolution shown in Figure 4, distributions of samples are significantly different from those expected if the numbers of samples were unrelated to facies type (G-tests, p < ,0001 in all cases).

Number of sample horizons provides an index of sampling intensity, but diversity of fossils is also influenced by sample size: the number of specimens recovered per sample horizon. Unfortunately, there is no guarantee that sampling intensity as measured by number of collections in each stratigraphic interval will be correlated with actual numbers of fossils recovered. This is demonstrated by a comparison of sample distribution and sample size for two well-studied regions, south-central Oklahoma and south-westem Alberta (Fig- ure 3). Although Oklahoma is represented by three times as many samples. it yielded only 60% of the total number of sclerites recovered from Alberta, and this reflected in a smaller mean sample size per horizon (1 1 versus 56). For three of the four sample intervals, samples sizes are significantly greater in Alberta (Mann-Whitney 3-tests, p < .0001 in all cases). The only interval (Irvingella major-Taenicephalus zones) in which samples size distributions are comparable between the two regions (Mann-Whitney U-test, p = .68) is also by far the thinnest stratigraphically. Thus, although Oklahoma is likely to have a better record of the stratigraphic ranges of the more common species, Alberta may well have a better sample of the total diversity of species present. Unfortunately, such comparisons between numbers of samples versus quantity of specimens recovered are difficult to make because specimen abundance data are not routinely reported. Abundance data were available for less than half (45%) of the sample horizons included in this analysis (Figure 5).

Not only is the available rock record unevenly sampled, but species also differ profoundly in their occurrences in that record. Most Sunwaptan trilobites species are known from fewer than five records, and few are known from more than ten (Figure 6). Thus, even when a group has been studied

Stratigraphy, Phylogeny, and Species Sampling

OKLAHOMA ALBERTA Proricephalus wilcoxensis-Stenopilus glaber zones

Sample horizons: 174 Sample horizons: 13 Sclerites: 1575 Sclerites: 1148

Illaenurus Zone

0 Sample horizons: 115 Sample horizons: 38 r 40 Sclerltes: 803 40 7 Sclerltes: 1048

Stigmacephalus oweni-Ellipsocephaloides zones z W Â¡ 1 LU Sample horizons: 99 Sample horizons: 60

Sclerites: 978 Sclerites: 4081

Irvingella major-Taenicephalus zones

Sample horizons: 36 Sample horizons: 25 Sclerltes: 1284

0 80 160 240 0 80 160 240

SAMPLE SIZE (number of sclerites)

Figure 3 Comparison between Oklahoma (Stitt, 1971, 1977) and Alberta (Westrop, unpublished data) of frequency distributions of sample sizes at sample horizons in four biostratigraptucally- defined intervals of the Sunwaptan

Fossils, Phylogeny, and Form: An Analytical Approach

- ' N ' S S 1 S S ~ 01 ' 02 ' D ' 03 1 lllaenurus Zone

0 N 400-1 UPPER SUNWAPTAN

ec W LOWER SUNWAPTAN

Stigmacephalus oweni- 300 -I Elli~soceohaloia8s Zones

Figure 4 Distribution of sample horizons through six facies types: S. nearshore s~lic!clastscs: SS1. shallow subudal carbonates; SS2. shall^^. subtidal shales andcarbonatcs. B I . shelf buildups. B2, shelf-margin carbonates, including buildups, and D, deep subudal carbonates. Left colu& top, pooled data for the entire Sunwaptan Stage, center, bottom, Upper Sunwaptan and Lower Sunwaptan samples. Right column: samples m four biostratigraphically-defined intervals of the Sunwaptan.


intensively for biostratigraphic purposes, distributions of the majority of species are poorly known. In this present state of knowledge, stratigraphic data cannot offer a robust test of morphologically-derived phylogenetic hypotheses.

PHYLOGENY OF THE EUPTYCHASPIDINAE AND MACRONODINAE

As a further investigation of the influence of sampling on patterns of faunal distribution, we examine a major clade of trilobites in the context of the Sunwaptan sampling data described above. The family Ptychaspididae and its sister group in the Dikelocephalacea, the Dikelocephalidae, are represented by numerous species in the Sunwaptan rocks of Laurentian North America, and the former family was selected by Longacre (1970) as the eponymous taxon for her "Ptychaspidid Biomere". The Ptychaspididae are currently divided into three subfamilies (Westrop, 1986a, 1986b), two of which, the Euptychaspidinae Hup6 and Macronodinae Westrop, were selected for

SAMPLE QUALITY Figure 5. Frequency distribution of sample quality categories. Category 1, detailed stratigraphic data and sclente abundance data available for sample; 2, detailed stratigraphic data only, 3, sciente abundance data only; 4, detailed straugrapiuc and sclente abundance data lacking.


analysis. A sister group relationship between these two subfamilies is suggested by their distinctive knob- to flap-like palpebral lobes (e.g., Ludvigsen, 1982, Fig. 58K-M, V-W, fig. 59A-F; Westrop, 1986b, fig. 4C-D) that contrast with the flat, arcuate palpebral lobes of the Ptychaspidinae (e.g., Westrop, 1986b, pi. 7, fig. 1) and the Dikelocepnalidae (e.g. Ludvigsen, 1982, fig. 58A- B; Westrop, 1986b, pi. 3, fig. 1). We included Larifigula Ludvigsen in the analysis, a genus that has been regarded as a member of the Kingstoniidae Kobayashi (Ludvigsen, 1982; Westrop, 1986b. 1995). Similarities between L. triangulata Ludvigsen, the type species of Lari fugula, and the euptychaspidine Kathleenella subula Ludvigsen, suggest that the genus is

Cumulative number of species: 460 Total number of records: 4.972 I

NUMBER OF RECORDS

Figure 6 Frequency distribution of records of 460 species (taxonomically standardized by eliminating synonyms) of Sunwaptan trilobite species in the 1901 collections of our database, where a record is an occurrence of a particular species in a particular collection. Note the strong mode in the 1-5 records class, and that few species have more than ten records


better placed in the Euptychaspidinae. For example, the pleural furrows are poorly expressed over most or all of the pygidia of both species and most of the external surface displays a sculpture of anastomosing terrace ridges (Ludvigsen, 1982, figs. 561, L, Q, 59J-K, L-M, 60G-I). Also, the anterior cranidial border of L. tr~angulata, although less prominent than that of K. subula, shares the same, prow-like morphology (Ludvigsen, 1982 figs. 56A- E, 59A-H) The ingroup consists of twelve species, and Keithiella depressa Rasetti , perhaps the best known representative of the subfamily Ptychaspidinae (e.g., see Ludvigsen and Westrop 1983b; Ludvigsen et al., 1989), was selected as the outgroup. One euptychaspidine species, Euptychaspzsfrontalis Longacre, was excluded from the analysis. The handful of cranidia illustrated from the type area in Texas (Longacre, 1970, pi. 3, figs. 2-5), Oklahoma (Stitt, 1977, pi. 3, fig. 6) and Alberta (Westrop, 1986b, pi. 10, figs. 20-22) show a considerable range of variability in glabellar outline, size and shape of the anterior border, length of the preglabellar field, and as currently conceived, this species is probably poiyphyletic. The data matrix (Fig- ure 7) includes 15 binary and 10 multistate characters (Appendix l ) , all of which were treated as unordered.

A branch-and-bound search using PAUP v.3.1.1 (Swofford, 1993) retrieved two equally parsimonous cladograms that differed only in the placement of a single species, Kathleenella hamula Ludvigsen. The strict consensus tree and an optimized character distribution (ACCTRAN) are shown in Figure 8. Bremer support indices (Bremer, 1994) were calculated using the program TreeRot (Sorensen, 1996) and are indicated for each node on the consensus

kirh lyp1cali.s lugalis subula maritima hamula tnangulota leonensis carmata bulbosa P- punctata depressa

Figure 7. Data matrix used in parsimony analysis of the Euptychaspinae and Macronodinae. See appendix for description of character states. Terminal taxa are: Euptychaspis kirki Kobayashi; E. typicalis Ulnch; E. jugalis Winston & Nicholls; Kathleenella subula Ludvigsen; K. maritima Ludvigsen & Westrop: K. hamula Ludvigsen; Larifueula triangulata Ludvigsen; Leiobienvillia leonensis Winston & Nicholls; Sunwaptia carinata Westrop; Wilcoxaspis bulbosa Westrop; Macronoda prima Lochman; M. punctata Derby (= M. cf. prima of Winston & Nicholls, 1967, and Westrop 1986b). The outgroup taxon is Keithiella depressa Rasetti.

308 Fossils, Phylogeny, and Form: An Analytical Approach gb7-\<l - ,- "- ,Â¥ c-

5

I I

1 Strict consensus (from 2 trees) Length = 47; Cl = .787; RC = .644; Rl = 385

Figure 8 Results of the parsimony analysis using PAUPv 3 1 1 (Swofford, 1993) Upper diagram is strict consensus of two equally parsimonious cladograms with lengths of 47 steps Numbers at each node indicate Bremer support indices calculatedusing TreeRot (Sorensen, 1996). total support index is 0 40 Lower diagram is an optimized character distribution (ACCTRAN) on one of the most parsimonious cladograms (the other cladogram is identical to the strict consensus above). Character numbers with states in parenthesis correspond to those in Figure 7 and Appendix 1 Solid bars indicate unambiguous synapomorphies, open bars indicate reversals and/or characters that onginate more than once in the cladogram Zero-length branches are depicted as resolved


tree. Most nodes collapsed in one to two steps beyond the most parsimonious result, and the entire consensus tree is a polytomy with the addition of 4 steps to tree length; total support index (ti) is 0.40. Current generic and subfamilial concepts (Ludvigsen, 1982; Westrop. 1986a) are generally supported by the topology of the cladograms, although Kathleenella Ludvigsen is paraphyletic. Kathleenella is part of a larger monopnyletic group that includes Lar~fugula Ludvigsen, and the latter name has page priority in Ludvigsen (1982).

A phylogenetic tree (Figure 9) was produced by calibrating the most resolved of the two most parsimonious cladograms against stratigraphic range data for each species. Species were assumed to range throughout any subzone from which they are recorded; ranges of species that are confined to the Cow

a

quadra tus

m 10 5 0 Number of

species

Figure 9 Phylogenetic tree produced by calibrating the most resolved of the two most parsimonious cladograms against the stratigraphic record of the species Solid black rectangles indicate known ranges of species, whereas solid black lines indicate ghost segments of lineages, and dashed black lines indicate potential ancestor-descendant relationships Bar chart on right shows obsened species richness in each biostratigraphic unit (shaded portion of bars) and minimum estimates of missing diversity from ghost segments (unshaded) Subdivision of Illaenurus Zone is based on a sequence of species of the eponymous genus that can be recognized in Alberta (Westrop, 1986b) and Montana (Grant, 1965) The subzones can be correlated into the Upper Mississippi Valley (Westrop, 1986b, see also Hughes and Hesselbo, !997), and the base of the Illaenurus quadratus Subzone is correlative with the base Saukiella pyrene Subzone of Texas (Longacre, 1970) and Oklahoma (Stitt, 1971), as indicated by the co-occurrence of the eponymous species of both units (see Westrop, 1986b, p 20-21 for discussion)


Head Group of Newfoundland and the subsurface Deadwood Formation of Montana are poorly constrained, and their upper and lower limits are indicated by question marks. Four species join nodes as zero-length branches, although all but one of these (Euptychaspis typicalis Ulrich) is poorly known. As metataxa, they can be treated as ancestors of their sister species using the methodology described by Smith (1994). Long ghost lineages lead to the Kathleenella-Larifitgula clade and to the subfamily Macronodinae. Part of the stratigraphic gap in the lineage leading to the former may eventually be closed by the problematic euptychaspidine, Euptychaspis frontalis Longacre, which is known from the 1. quadratus Subzone of the Illaenurus Zone and correla- tives. The presence of gaps in our knowledge of the history of the Macronodinae is unquestionably a consequence of the scarcity of species currently included in this subfamily. For example, the highly apomorphic species. Sunwaptia carinata Westrop and Wilcoxaspis bulbosa Westrop are currently known only from southern Alberta (Westrop, 1986a, 1986b; Loch et al., 1993), where they are represented by fewer than twenty sclerites. S i m - larly, the genus Macronoda Lochman, although more widely distributed than other macronodines (Lochman. 1964; Longacre, 1970; Westrop, 1986b; Loch et al., 1993), is also a very rare component of Upper Sunwaptan faunas.

Larifugula leonensis (Winston and Nicholls) is an immigrant that appears abruptly in a number of localities at the base of the Ibexian during an interval of shelf-wide biofacies reorganization that characterizes the extinction event at the end of the Sunwaptan Stage (Ludvigsen and Westrop, 198%; Westrop and Ludvigsen, 1987). Under these circumstances, the long ghost segment indicated by the phylogenetic tree is not unexpected.

Ghost lineages offer a means of correcting estimates of diversity at the species level, where sampling problems are likely to be most profound (Smith, 1994). This approach is followed in Figure 9, Addition of ghost lineages to the tally of species present in each unit provides a minimum estimate of unsampled diversity. Raw counts of species richness indicate a steady increase between the I. quadratus Subzone and the Stenopilus glaber Subzone. The succeeding Eurekia apopsis is marked by a dramatic reduction in the number of species, and is part of an interval of major faunal turnover that can be recognized across Laurentian North America; both subfamilies were extin- guished at the end of the E. apopsis Subzone. In this particular example, the same trends are evident in the corrected estimate of species richness. Note that the magnitude of the correction factor in the S. glaber subzone is much lower than in the older subzones, simply because there is only a single species available in the E. apopsis Subzone to provide a ghost lineage. That is, the number of ghost lineages recognized in any stratigraphic unit must be a function of the number of species in overlying units, and this means that the effective- ness of the method in correcting diversity must be reduced in the later phases


in the history of any clade. Diversity cannot be corrected for the E. apopsis Subzone because there are no younger representatives of either subfamily to generate ghost lineages.

PHYLOGENY VERSUS SAMPLING It is instructive to consider the distribution of the euptychaspidines and

macronodines in the context of the analysis of Sunwaptan sampling presented earlier. Figure 10 shows the distribution of ingroup species across the spectrum of facies used in the sampling analysis. More than half of the species are known from only one facies, and none are known from more than four (mean occurrence: 2 facies types). Thus, the uneven distribution of sample horizons between facies (Figure 10) is a potentially serious bias in the stratigraphic data. The number of species recorded from each facies type is not significantly different (G-test,p = .20) from that expected if species richness was a function

Soecies 1 N 1 SS1 1 SS2 I B1 ! B2 1 D 1 Total 1

1 Expected I ; 1 2 1 4 1 1 1 3 1 1 1 I Figure 10 Occurrences of euptychaspidine and macronodine species across the spectrum of lithofacies types used in the analysis of Sunwaptan sampling intensity The bottom row of the table (Expected) indicates the number of species expected in each facies if species richness was simply a function of the distribution of sampling horizons in the Upper Sunwaptan (Fig 4) Observed ("Total" row) and expected distributions of species are not significantly different using a G-test, although they are significant if the data are percent-transformed


of the distribution of Upper Sunwaptan sample horizons (Figure 4), although the difference is significant if the data are percent-transformed (G-test, p < 0001). The largest mismatches between actual and expected number of species are for shallow subtidal carbonate and and deep subtidal facies. In shallow subtidal carbonates, expected species richness is half of that actually recorded and, while this could record environmental or ecological factors, it may simply reflect the number of specimens recovered from each sample horizon. As noted earlier, samples from Oklahoma yielded very small numbers of sclerites (Figure 3), and these include more than half (57%) of the total number of Upper Sunwaptan sample horizons from shallow subtidal carbonates. Sclerite yield per sample horizon may also be responsible for the six-fold difference between actual and expected species richness in deep subtidal fa- c i e ~ . Much of the data come from silicified faunas of the Rabbitkettle Forma- tion (Ludvigsen, 1982), which are characterized by large numbers of sclerites per sample.

Thus, not surprisingly, the known distribution of euptychaspidine and macronodine species appears to be influenced greatly by the number of sample horizons from each facies and the number of sclerites recovered from individual horizons. Uneven sampling is the Achilles Heel of all strato-methods because there are so many different aspects that need to be considered.

If strato-methods are to be applied, it is essential to determine whether an apparent gap in a species' range is simply due to a failure to sample the appropriate facies or geographic region, or to some other sampling bias. Propo- nents of stratocladistic and stratolikelihood approaches (e.g., Wagner, 2000c) acknowledge this problem and suggest that paleoenvironmental, taphonomic and paleoecologic data permit the plausibility of apparent gaps to be evalu- ated. However, such information is seldom included in the biostratigraphic or systematic studies that are typically used to compile stratigraphic ranges. Consequently, attempts to evaluate stratigraphic gaps by this approach have been anecdotal in nature. For example, Wagner's (2000c, p. 443) analysis of lophospiroid gastropod phylogeny used murchisonioid and eotomarioid gastropods as taphonomic and paleoenvironmental controls for the occurrence of lophospiroids. However, paleoenvironmental interpretation was limited to the suggestion that the "common co-occurrences of murchisonioids, eotomanoids and lophospiroids suggest similar environmental preferences and tolerances". Without detailed information on facies occurrences, abundances, preservational data, and so on, such assertions are less than compelling. Thus, although interpretation of apparent gaps in stratigraphic ranges is possible at least in principle, obtaining adequate data is an onerous task. Stratocladistic and stratolikelihood analyses have yet to meet this challenge.

In our analysis of Sunwaptan trilobites, we have documented biases in the stratigraphic, geographic and paleoenvironmental distribution of samples, as well as pervasive differences in the number of specimens recovered from


samples in different geographic regions. It might be possible at some stage to incorporate these uncertainties into a probabilistic model but, given the effort that will be involved in the acquisition of adequate data, one has to ask "Why bother?" Setting aside philosophical issues, the current state of knowledge of the stratigraphic distribution of species does not permit routine application of strato-methods. We doubt that it ever will.

CONCLUSIONS

In addition to containing major, non-random biases in preservation (e.g. Smith, 1994; Holland, 1995), the preserved fossil record has been unevenly sampled. These biases do not appear to have significantly distorted the record of Phanerozoic taxonomic diversity at global scales (e.g. Bambach, 1977; Sepkoski et al., 1981; Signor, 1985), but at smaller temporal and spatial scales, they will inevitably have a major impact on species-level analyses of phylogeny. The data assembled here indicate that several facies, geographic regions and time intervals of the Sunwaptan record have been undersampled. Spatial and environmental variations in sampling intensity have yet to be incorporated in stratocladistic and stratolikelihood methods in a realistic manner, and this represents a major challenge. If the record of Sunwaptan trilobites is any in- dication, conflicts between cladograms based on parsimony analysis of morphology and the current stratigraphic database will identify species that are poorly sampled. but we see little reason to believe that adjusting cladograms to fit existing stratigraphic ranges represents a significant step forward in phylogenetic analysis.

The extent of congruence between sampled stratigraphic first appearances and phylogenetic hypotheses may be a rich source of paleontological insight (e.g., Benton and Storrs, 1994; Benton et al., 1999), indicating potential problems with either paleontological sampling or phylogenetic analysis. Con- straining phylogenies to fit the sampled order of the fossil record discards such insight. In addition, strata-methods render phylogenies and taxa unavailable to address any temporal problems. Not least, this includes the entire research program termed taxic paleobiology (Adrain and Westrop, 2000). Strato-methods are conceptually flawed, needlessly conflate the potential for systematic error, and greatly devalue the enormous and barely tapped paleobiological potential of systematics.

ACKNOWLEDGMENTS

This is a joint work and the order of our names is alphabetical. We are grate- ful to C. A. Brochu and C. D. Sumrall for discussion and comments on an earlier version of this chapter. Our work on Cambrian trilobite systematics and phylogeny is supported by NSF grant EAR 9973065.


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APPENDIX 1. CHARACTER LIST FOR ANALYSIS OF EUPTYCHASPIDINAE AND MACRONODINAE 1. Glabellar outline

0 subrectangular to anteriorly tapered 1 suboval in front of 1s 2 suboval in front of 2s 3 gently expanded and rounded anteriorly

2. I s glabellar furrows 0 connected across glabella by firmly impressed furrow 1 lateral furrows or connected across glabella by shallow furrow

3. 2s glabellar furrows 0 lateral furrow or connected across glabella by shallow furrow 1 connected across glabella by firmly impressed furrow 2 absent

4. 3s glabellar furrows 0 present 1 absent

5. 4s glabellar furrows 0 present 1 absent

6. Median anterior glabellar furrow 0 absent 1 present on at least exfoliated surfaces

7. Anterior margin of glabella 0 well-defined 1 merges with frontal area

8. Occipital spine 0 absent 1 present

9. Posterior border wrapped around occipital spine 0 absent 1 present

10. "Buttress" 0 absent 1 present

11. Palpebral lobe 0 arcuate band 1 short flap or knob 2 absent

12. Palpebral lobe position (or location of inflexion in sutures) 0 behind 2s furrow 1 opposite 2s furrow 2 in front of 2s furrow

13. Palpebral ridge 0 absent 1 present

14. Anterior cranidial border 0 broad, convex 1 narrow, subtriangular prow 2 minute or absent

15. Anterior border furrow 0 forwardly convex 1 backwardly concave 2 absent

16. Preglabellar field 0 absent 1 present

17. Anterior cranidial arch 0 absent 1 present

18. Interoccular cheek width 0 ~ 2 5 % glabellar width 1 = or < 25% of glabellar width

19. Carina on fixigena 0 absent 1 present


20. Posterior border furrow 0 reaches lateral cranidial margin 1 isolated from lateral cranidial margin

21. Pygidium 0 transversely semielliptical in outline, with broad pleural field 1 subelliptical to subtriangular in outline; pleural field, if expressed, well-

defined only near axis 2 elongate, subtriangular in outline with flat, pitted border

22. Ridge at edge of pleural field 0 absent 1 present

23. Pygidial axial rings 0 four 1 three 2 seven 3 >seven

24. Sculpture 0 tubercles or granules 1 anastomosing ridges 2 smooth

25. Sutures 0 opisthoparian 1 submarginal

Chapter 9

ANALYZING SPECIATION RATES IN MACROEVOLUTIONARY STUDIES

Bruce S. Lieberman

INTRODUCTION

Paleobiologists working in the area of macroevolutionary theory have made important contributions to our understanding of evolution by emphasizing how research programs that study evolutionary patterns of speciation and extinction within and among clades can be used to infer evolutionary processes (reviewed in Eldredge and Cracraft, 1980; Vrba, 1983, 1989; Lieberman, 1995; and refs. therein). It is partly ontological and epistemological advances that have made it possible to utilize such pattern-based approaches to study evolutionary processes. Among the ontoiogical advances is the recognition that species are fundamental units in nature that are characterized by distinct birth and death points (Ghiselin, 1974; Hull, 1980), and they are also stable and cohesive throughout their existence (Eldredge, 1985, 1989; Vrba, 1989, 1995). Another advance that arises from this is the recognition that differences in rates of speciation and extinction within clades, due to extrinsic or intrinsic factors, play an important role in generating the large scale pattern of life (Eldredge and Gould, 1972; Stanley, 1979, 1990; Eldredge, 1979, 1982, 1989, 1999; Vrba, 1980, 1984, 1996).

BRUCE S. LIEBERMAN Department of Geology and Department of Ecology and Evolutionary Biology, University of Kansas. Lawrence. Kansas 66045.

Fossils, Phylogeny, and Form, Volume 19 of Topics in Geobioiogy, edited by Jonathan M. Aarain el al. Kluwer AcademdPlenum Publishers, New York. 2001.

chapter 8 stratigraphy, phylogeny, and species sampling … · stratigraphy, phylogeny, and species...

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