Environmental controls on geographic range size in marine genera Author(s): Michael Foote Source: Paleobiology, 40(3):440-458. 2014. Published By: The Paleontological Society DOI: http://dx.doi.org/10.1666/13056 URL: http://www.bioone.org/doi/full/10.1666/13056

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Environmental controls on geographic range size in marine animal genera

Michael Foote

Abstract.—Here I test the hypothesis that temporal variation in geographic range size within genera is affected by the expansion and contraction of their preferred environments. Using occurrence data from the Paleobiology Database, I identify genera that have a significant affinity for carbonate or terrigenous clastic depositional environments that transcends the Database’s representation of these environments during the stratigraphic range of each genus. These affinity assignments are not a matter of arbitrarily subdividing a continuum in preference; rather, genera form distinct, nonrandom subsets with respect to environmental preference. I tabulate the stage-by-stage transitions in range size within individual genera and the stage-by-stage changes in the extent of each environment. Comparing the two shows that genera with a preference for a given environment are more likely to increase in geographic range, and to show a larger average increase in range, when that environment increases in areal extent, and likewise for decreases in geographic range and environmental area. Similar results obtain for genera with preferences for reefal and non-reef settings. Simulations and subsampling experiments suggest that these results are not artifacts of methodology or sampling bias. Nor are they confined to particular higher taxa. Genera with roughly equal preference for carbonates and clastics do not have substantially broader geographic ranges than those with a distinct affinity, suggesting that, at this scale of analysis, spatial extent of preferred environment outweighs breadth of environmental preference in governing geographic range. These results pertain to changes over actual geologic time within individual genera, not overall average ranges. Recent work has documented a regular expansion and contraction when absolute time is ignored and genera are superimposed to form a composite average. Environmental preference may contribute to this pattern, but its role appears to be minor, limited mainly to the initial expansion and final contraction of relatively short-lived genera.

Michael Foote. Department of the Geophysical Sciences, University of Chicago, Chicago, Illinois 60637, U.S.A. E-mail: [email protected]

Accepted: 9 January 2014 Published online: 7 May 2014 Supplemental materials deposited at Dryad: doi: 10.5061/dryad.76082

What Governs Changes in Geographic graphic range reflects fluctuations in the Range Size? extent of its preferred habitat. It may seem Geographic ranges of species and genera are obvious that the answer must be affirmative. highly dynamic on both ecological and geo- There are reasons to suppose that the expec- logical time scales (Bennett 1997; Gaston 1998, tation may not be so clear, however. For 2008, 2009; Jackson and Overpeck 2000; example, barriers to dispersal (Webb 1991, Jernvall and Fortelius 2004; Jablonski et al. 2006; Holland and Patzkowsky 2007; Patz- 2006, 2013; Raia et al. 2006; Brett et al. 2007; kowsky and Holland 2007; Lessios 2008) and Foote 2007; Foote et al. 2007, 2008; Hendy and ecological incumbency (Rosenzweig and Kamp 2007; Liow and Stenseth 2007; Patz- McCord 1991; Sheehan 2008; Valentine et al. kowsky and Holland 2007; Krug et al. 2008; 2008), as well as biotic interactions more Hadly et al. 2009; Roy et al. 2009; Liow et al. generally (Jablonski 2008), may restrict taxa 2010; Willis and MacDonald 2011). Given the from areas that they would otherwise be quite evidence that species often track the locations capable of inhabiting. of their preferred environments (Bennett 1997; Using data from the Paleobiology Database, Jackson and Overpeck 2000; Holland et al. I will characterize occurrences of marine 2001; Brett et al. 2007; Hendy and Kamp 2007; animal genera as coming from carbonate Holland and Zaffos 2011; Willis and MacDon- versus terrigenous clastic environments, ald 2011), it is natural to ask whether temporal which reflect both substrate composition and variation in the magnitude of a taxon’s geo- consistency and aspects of the broader depo-

Ó 2014 The Paleontological Society. All rights reserved. 0094-8373/14/4003-00/$1.00 ENVIRONMENT AND GEOGRAPHIC RANGE 441 sitional system such as nutrient levels, turbid- genus that are assigned to carbonate and ity, and temperature (Wilson 1975; Peters 2008; clastic lithologies. These proportions were Foote and Miller 2013: Appendix 1), as well as treated as the null expectation for the frequen- reefal versus non-reef settings. I will demon- cy of occurrence of the genus in either strate that changes in the geographic range lithology. Any genus that had significantly sizes of genera correlate with changes in the more occurrences than expected in either extent of their preferred environment. Subsid- lithology, using a one-tailed binomial proba- iary analyses suggest that these results are not bility of 0.05, was considered to have an likely to be artifacts of methodology or biased affinity for the corresponding environment. sampling of environments. (This is similar to the approach of Kiessling and Aberhan [2007a] except insofar as they Materials and Methods used the overall number of fossil occurrences Occurrence data for marine animal genera, rather than number of collections to set the with associated information on stratigraphy, probabilities for the null expectation; they note lithology, paleoenvironment, and geography, [p. 417] that they obtain similar results using were downloaded from the Paleobiology collections instead.) In addition, I stipulated Database (paleobiodb.org) on 23 February an arbitrary minimum of ten occurrences for a 2012. Details of the download and vetting genus to be included in this study. Other procedures are described by Foote and Miller protocols, such as using a different critical (2013). The data are available at Dryad (doi: probability, a different minimum number of 10.5061/dryad.76082). Collections were as- occurrences, or a null expectation of equal signed to a series of stratigraphic intervals, proportions carbonate and clastic (Foote 2006; primarily international stages (Foote and Miller and Foote 2009) yield comparable Miller 2013); collections that could not be results (Appendix 1). The variety of protocols resolved to a single time interval were used to assign affinity preferentially select for ignored. Lithologies of each marine collection longer-lived and more abundant genera. Thus, were categorized as either carbonate or clastic, there is little I can say about the determinants following Foote (2006), with minor modifica- of geographic range within rare taxa. The tion, and using only the primary lithology main analyses include about 21% of all genera, field in the Database. Collections with a mixed (carbonate and clastic) or unrecorded litholo- accounting for 70% of all occurrences. gy, and those not readily assignable to either Table 1 shows a few examples of the affinity category, were ignored. Results are consistent assignments. During the stratigraphic range of if secondary lithology and mixed lithologies the trilobite Acastella, 64% of the collections are are taken into consideration (Appendix 1). The from carbonates and 36% from clastics. This presence of a genus in a collection was genus has 44 occurrences, 30 of which are counted as a single occurrence, irrespective from clastics. The probability of observing 30 of the number of species. Although all or more clastic occurrences, if the true fre- 5 resulting occurrences were used in assigning quency is 36%, is only about 10 , so this lithologic affinities of genera, the analysis of genus is assigned a clastic affinity. The changes in geographic range focuses on the gastropod Acteonella is assigned a carbonate through Pleistocene, mainly be- affinity, even though 52% of its occurrences cause of limited stratigraphic resolution in are from clastics. This is because its 48% parts of the . occurrence rate in carbonates is significantly Environmental Affinities.—A genus could greater than the null expectation of 32%. occur primarily in a given environment Finally, the cephalopod Acrioceras has 78% of simply because that environment is dominant its occurrences in carbonates; it is assigned no during its brief stay on Earth (Miller and affinity, however, because this is not signifi- Connolly 2001). To take this into consider- cantly greater than the null expectation of ation, I tabulated the proportion of all collec- 67%. Assigning affinities in this way helps tions within the stratigraphic range of each avoid a forced correlation between the size of 442 MICHAEL FOOTE

the geographic range of a genus and the extent of its preferred environment.

Affinity By assigning genera to an affinity class, I am ignoring the possibility of variation in affinity within the history of individual genera (cf. Miller and Connolly 2001, who

0.000010.996 Clastic 0.92 Carbonate None looked at the evolution of affinity within ~ ~ ~ higher taxa). However, there is reason to

-value think that genera do not generally change p their affinities. I took those genera that have 0.999 0.01 0.16 a defined affinity in aggregate and that have ~ . , a range of two or more stages, i.e., those that logically could shift affinities. For each genus, I tabulated the number of stages in which it was sampled at least once; the total over all genera and stages is 25,260. Next, I calculated the affinity of each genus within each stage in which it is sampled, using the same protocol described above. Of the 25,260 tabulations, 18,397 (72.8%) have too few occurrences to assign an affinity; 1851 (7.3%) have the required minimum number of occurrences but do not yield a clear affinity; 4806 (11.1%) yield the same affinity as the aggregate tabulation over the life of Occurrences of this genus Proportion the genus; and only 206 (0.8%) yield the opposite affinity as the aggregate value. Thus, one could make a case that genera fluctuate between having a clear affinity and being ambivalent, but there is little reason to think that they shift affinities substantially over time (Foote 2006; Holland and Zaffos 2011; Hopkins et al. 2013). Figure 1 shows the difference between expected and observed proportion of car- bonate occurrences for genera having car- bonate and clastic affinities, as well as those having the minimum number of occurrences but no significant tendency toward either

No. of lithology. (The tabulations for clastic occur- rences would simply be the mirror images of collections within stratigraphic range Proportion

Carbonate Clastic Carbonate Clastic Carbonate Clastic Carbonatethese.) Clastic Carbonate The Clastic three groups of genera seem to form distinct populations, and the combined distribution of all genera is bimodal, but there is always the possibility that the assignment of affinities simply reflects an arbitrary cutoff in a continuum. Although (Cephalopoda) 599 296 0.669 0.331 21 6 0.78 0.22 () 1978 4246that 0.318 may 0.682 be true 26 for some 28 genera, 0.48 Figure 0.52 2 (Trilobita) 1101 623 0.639 0.361 14 30 0.32 0.68

1. Examples of affinity assignment. suggests that there really are populations of genera with distinct carbonate and clastic ABLE Acastella Acteonella Acrioceras T Genus affinities. This figure tabulates the binomial ENVIRONMENT AND GEOGRAPHIC RANGE 443

probabilities of having a certain number of occurrences in either lithology. Under the null hypothesis that genera occur with the same frequency as the lithologies present during their lifetimes, these p-values should be uniformly distributed. Instead, there are pro- nounced spikes at p , 0.05 for genera of both carbonate and clastic affinities. The clarity of these affinity groups helps account for the fact that results do not depend critically on the details of the protocol used to assign affinities (Appendix 1). Geographic Range.—For each stratigraphic interval, the globe was divided into 10,000 equal-area cells by using paleolatitude and paleolongitude (Foote and Miller 2013), and the total number of these cells containing at least one collection was tabulated. The range of each genus in each stage was defined as the proportion of these occupied cells in which it occurs. Thus, observed geographic range was expressed relative to the maximum it could be, given the distribution of available outcrop and how it is sampled. Because cells tend to be within single plates, this measure of range is relatively insensitive to the accuracy of paleo- geographic coordinates, and results are barely distinguishable if we use modern coordinates instead (Appendix 1). Results are also consis- tent if we use absolute geographic range rather than scaling it relative to the maximum possible range (Table A1). ArealExtentofEnvironment.—Using the same equal-area cells, the areal extent of each environment in each stage was defined as the proportion of cells containing at least one collection of the corresponding lithology.

FIGURE 1. Frequency of occurrence in carbonate collec- tions for genera having at least ten occurrences, sorted into genera with carbonate affinity (A), clastic affinity (B), and no clear affinity (C), as well as all genera combined (D). Depicted here is the difference between the observed proportion of carbonate occurrences and the expected proportion based on the frequency of carbonate collections within the stratigraphic range of each genus. The genera with carbonate and clastic affinities form distinct modes. (Because only collections that can be assigned to carbonate or clastic lithologies are included, the proportion of clastic occurrences is simply the complement of the proportion of carbonate occurrences, and the corresponding figures for clastic occurrences would be the mirror images of these.) 444 MICHAEL FOOTE

the other). This allows more freedom in the results. For example, if the geographic ranges of carbonate-loving taxa are positively corre- lated with the areal extent of carbonates, they need not be negatively correlated with the areal extent of clastics. If, by contrast, we measured environmental extent based on number of collections, which are assigned only to carbonate or clastic categories, the two correlations, as measured herein (see below), would necessarily be equal in magni- tude and opposite in sign. Temporal Changes in Geographic Range Size and Areal Extent of Environment.—For each pair of successive stages and for each genus sampled from both stages, I noted the change in geographic range size from one stage to the next, and calculated the mean change for all such genera in the pair of stages. Note that genera present in only one stage or the other were not tabulated. Thus, the focus here is not on the change in mean geographic range, but on the mean change in geographic range. For each pair of stages, I calculated the change in the areal extent of carbonate and clastic environments. The Spearman rank-order correlation coeffi- cient was used to assess the direction and strength of relationship between the change in areal extent of a given environment and the mean change in geographic range size of genera with an affinity for that environment. Genera and species differ from one another in their characteristic ranges (Jablonski 1987; Jablonski and Hunt 2006; Foote 2007; Hadly et al. 2009); moreover, ranges of individual FIGURE 2. Probability of genera having observed number of carbonate (A) and clastic (B) occurrences, under the null genera tend to be smaller near their first and hypothesis that the expected frequency is equal to the last appearances than in between (Foote 2007). proportion of collections within the stratigraphic range of For these reasons, it is arguably more appro- each genus having the corresponding lithology. Only genera with at least ten occurrences are shown. Probabil- priate simply to record whether a genus ities are not uniformly distributed, indicating that genera increased or decreased in geographic range. with significant carbonate affinity (hatched) and signifi- Therefore, in addition to measuring the mean cant clastic affinity (black) form distinct populations, rather than being merely chance outliers in a continuum. of what could be a very heterogeneous mix of changes in range, I simply scored whether each genus increased or decreased in range Because a given area can contain both from one stage to the next, and whether each lithologies, the carbonate proportion and environment increased or decreased in areal clastic proportion need not sum to unity (i.e., extent. From these data, I tabulated 2 3 2 the alternatives for each proportion are not contingency tables and calculated the odds carbonate versus clastic, but rather presence ratio expressing the strength of association versus absence of carbonate for one propor- between changes in environmental extent and tion, and presence versus absence of clastic for changes in individual geographic range; I ENVIRONMENT AND GEOGRAPHIC RANGE 445

used the Fisher exact test to assess the statistical significance of this association. All analyses were carried out in R, version 2.14.1 (R Development Core Team 2011).

Results Figure 3 shows the time series of areal extent for each environment. Although a given area can contain both environments, there is obviously an inverse correlation between the areal extent of carbonates and clastics. Chang- es in geographic range for the two affinity classes are shown in Figure 4. The data from Figures 3 and 4 are presented as scatter plots in Figure 5. Evidently, fluctuations in geo- graphic range of carbonate-loving genera follow changes in the areal extent of carbon- ates, and likewise for clastic-lovers and clastic lithologies. In addition, the correlation be- tween geographic range and areal extent is substantially stronger for carbonates than for clastics. The correlations reported in Figure 5 are consistent with those obtained if we look at proportional change in environmental extent, measured as the logarithm of the ratio between successive values rather than the simple difference between them (for carbon- ates, rs ¼ 0.59, one-tailed p 0.001; for clastics, rs ¼ 0.28, p ¼ 0.01). The odds ratios for individual changes in geographic range (Table 2) show the same direction and relative magnitude of association for genera of car- bonate and clastic affinities. It is worth asking whether these relation- ships are driven by particular clades or are more general. If we look at the few groups with a large enough roster of genera to analyze separately, we see that they differ in the strength of association between geograph- ic range size and areal extent of environment, and in the relative magnitude of the carbonate and clastic associations (Table 3). Most associ-

2 2 FIGURE 3. Areal extent of carbonate (A) and clastic (B) to interval iþ1 (C and D) estimated as =(SEi þ SEiþ1 ). lithologies, and their stage-to-stage differences (C, D). Because a given cell can have both carbonate and clastic Areal extent is defined as the proportion of equal-area grid lithologies, proportions do not sum to unity. The two cells (~5 3 104 km2 each) that have at least one collection tabulations nonetheless vary inversely to a large extent. of the given lithology, relative to the total number of cells Data in this and subsequent figures plotted at stage that have any data in the stage. Error bars are plus or midpoints (Gradstein et al. 2012), with changes between minus one binomial standard error (A and B). Standard successive stages plotted in the second of each pair of error for change in areal extent of lithology from interval i stages. 446 MICHAEL FOOTE

FIGURE 4. Mean stage-to-stage change in geographic range of genera with carbonate (A) and clastic (B) affinity. Within each stage, the geographic range of each genus is defined as the proportion of equal-area cells containing it, relative to the total number of cells that have any data in the stage. For each genus that is sampled in two successive stages, its change in range is calculated, and the mean is then calculated over all genera. Error bars show plus or minus one standard error, based on bootstrap resampling of the individual changes. ations are positive, however, even if they are not all statistically significant. There does not FIGURE 5. Relationship between change in areal extent of seem to be a clear correspondence between the carbonates and mean change in geographic range of predominant affinity of a clade and the genera with carbonate affinity (A), and for extent of clastics and range of genera with clastic affinity (B). Error relative magnitude of carbonate and clastic bars for change in geographic range as in Figure 4. associations. Brachiopods, like the data at Strength of relationship given by Spearman rank-order large, are fairly evenly split between carbon- correlation coefficient. Both groups of genera show changes in geographic range that are positively and ate- and clastic-lovers, and they also show a significantly correlated (one-tailed p 0.001 and p ’ stronger range-area association for carbonates. 0.008 for genera with carbonate and clastic affinity, respectively). Outlier in upper left of A is the transition Trilobites are also roughly evenly split, but from the NorianþRhaetian to the Hettangian. they show a stronger association for clastics. The overwhelming majority of corals prefer carbonates, and their range-area association is association is stronger for clastics. By contrast, stronger for carbonates than for clastics. many more bivalves prefer clastics than Conversely, gastropod genera are predomi- carbonates, but their association is stronger nantly clastic-loving, and their range-area for carbonates. ENVIRONMENT AND GEOGRAPHIC RANGE 447

Thus, the relative strength of carbonate 0.001 0.001

value and clastic associations is idiosyncratic, and p- which association is stronger cannot be predicted based on the predominant affinities of the group in question. Nonetheless, the ent of clastics and

error existence of such associations would appear Standard to be fairly general, not confined to certain clades. Figure 6 and Table 4 show similar analyses,

Log comparing reef and non-reef environments

odds ratio rather than carbonates and clastics. I fol- lowed Foote and Miller (2013: Appendix 1) in assigning collections to reef environments. ratio Odds Collections with missing environmental in- formation or with environmental assign- ments such as ‘‘Carbonate indet.’’ were ignored, rather than being assigned to non-

Odds of reef environments. There is one exception to

range increase this: about 0.01% of the occurrences cannot be assigned unambiguously to reef or non- reef environments by using the environment field, but they do have lithologic assign- ments, for example ‘‘bafflestone’’ and ‘‘reef rocks,’’ that allow them to be classified as Increases in reefal. The association between areal extent geographic range of reefs and geographic range size of reef- lovers is stronger than for non-reefs. Given the previous results on carbonates and clastics (Table 2, Fig. 5), and the fact that reef-loving taxa are largely a subset of

Decreases in carbonate-loving taxa (83% of reef-lovers geographic range being carbonate-lovers), this result is perhaps unsurprising. The odds ratios indicate that the associations between areal extent and geographic range are stronger for reef- and

lithology non-reef settings than for carbonates and of preferred Areal extent IncreaseIncrease 1344 1890clastics. 2061 This 2381 could 1.53 be 1.26 because 1.89 1.38 the 0.64 categories 0.32 0.049 0.043 of carbonate and especially clastic are overly generalized, even though informative enough to yield a signal, whereas the distinction between reefal and non-reef set- in tabulation No. involved of transitions tings is more specific. Discussion and Conclusions Because affinity, geographic range, and areal extent of environment are all based on different treatments of the same data, it is worth asking whether the results of this study are somehow forced by methodology. 2. Association between changes in areal extent of carbonates and geographic range of genera with carbonate affinity, and between changes in areal ext There are several reasons to suppose that this ABLE geographic range of genera with clastic affinity. AffinityCarbonate No. of genera Clastic 2141 2278 1868 Decrease 1964 Decrease 1966 2258 1592 2064 0.81 0.91 T is not the case. First, affinities are based on 448 MICHAEL FOOTE

TABLE 3. Association between changes in habitat extent and geographic range for selected higher taxa.

Areal Decreases Increases Odds No. involved extent of in in of Log Higher taxon No. of in tabulation preferred geographic geographic range Odds odds Standard and affinity genera of transitions lithology range range increase ratio ratio error p-value* Anthozoa Carbonate 463 437 Decrease 531 382 0.72 Increase 284 577 2.03 2.82 1.04 0.099 0.001 Clastic 20 18 Decrease 22 20 0.91 Increase 10 20 2.0 2.18 0.78 0.50 0.15 Bivalvia Carbonate 138 128 Decrease 207 170 0.82 Increase 113 179 1.58 1.93 0.66 0.16 0.001 Clastic 650 606 Decrease 891 889 0.998 Increase 817 966 1.18 1.19 0.17 0.067 0.012 Brachiopoda Carbonate 467 409 Decrease 408 351 0.86 Increase 256 417 1.63 1.89 0.64 0.11 0.001 Clastic 346 302 Decrease 291 273 0.94 Increase 259 296 1.14 1.22 0.20 0.12 0.11 Gastropoda Carbonate 205 194 Decrease 216 192 0.89 Increase 195 233 1.19 1.34 0.30 0.14 0.038 Clastic 613 555 Decrease 711 595 0.84 Increase 432 642 1.49 1.78 0.57 0.083 0.001 Trilobita Carbonate 111 93 Decrease 53 52 0.98 Increase 56 51 0.91 0.93 0.074 0.27 0.89 Clastic 141 126 Decrease 56 49 0.88 Increase 91 106 1.16 1.33 0.29 0.24 0.28 * Values of 0.012 and smaller are significant at the 0.05 level when adjusted for multiple comparisons using the false discovery rate (Curran-Everett 2000: p. R7), whether only the results of this table are considered or the results of Tables 2 and 4 are included as well. frequency of occurrence whereas geographic that not all subsets of the data show signifi- range is based on areal extent, so the cant associations (Table 3). If associations were assignment of affinities and the analysis of a necessary outcome, we would expect car- geographic ranges and environmental extent bonate-loving trilobites to track carbonates, are somewhat decoupled. Second, genera for example, but they do not. need to deviate significantly from the ob- A tacit assumption of this study is that the served frequency of a given lithology in order relative extent of different environments as to be assigned an affinity; a pulse of carbon- represented in the data agrees with what it ates in a given stage, for example, will not was in the geologic past. There are two perforce lead to a number of genera with potential distortions here: the preservation of carbonate affinities. Third, it is not difficult to environments in the stratigraphic record, and construct a model in which genera have how they are sampled. Systematic biases, for strong lithologic affinities and the areal extent example if carbonates are always underrepre- of each lithology varies considerably over sented, should have little effect on the results. time, but in which geographic ranges of We would need to be concerned, however, if genera nonetheless do not track lithologic there were spurious, short-term variation in extent. When data are simulated with such a the representation of a given environment. If, model and then subjected to the analytical for example, carbonates consistently repre- protocols used here, we do not end up with sented a relatively fixed proportion of the results like those seen in the empirical data areal extent in the past, but our data showed (Appendix 2). But perhaps the most obvious that they fluctuated abruptly and significantly argument that the methods used here do not on stage-to-stage time scales because of biased force strong relationships between environ- representation, then both the observed areal mental extent and geographic range size is extent of carbonates and the observed geo- ENVIRONMENT AND GEOGRAPHIC RANGE 449

graphic ranges of carbonate-lovers could fluctuate in concert, creating a spurious correlation. It is difficult to think of geological processes that would create fluctuating biases on the short time scales necessary to induce such a problem. Sampling could do so, however, at least in principle. In order to investigate the possibility that the results could be biased by temporal variation in sampling, I carried out various subsampling procedures in which the stage-to-stage representation of carbonates and clastics was made more uniform than in the observed data. Here I present the results of the most draconian procedure, in which every stage was forced to have an equal number of carbonate and clastic collections. This unreal- istically assumes that none of the observed variation in the proportion of collections with a given lithology, whether short or long term, is real. Subsampling in this way diminishes but does not eliminate the association between environmental extent and geographic range size (Appendix 3). The difference between carbonates and clastics is also reduced, sug- gesting that the observed difference could be partly exaggerated by variable sampling. However, that an extremely unrealistic and pessimistic sampling scenario is needed to substantially reduce the lithology-range rela- tionship suggests that the empirical results, at least qualitatively, are unlikely to be sampling artifacts. Reconstructions of shallow-water habitat suggest that the relative extent of tropical versus extratropical habitat has declined over the course of the Phanerozoic (Walker et al. 2002). It has also been argued that superim- posed on this real decline is a biased sampling of the tropics during the Paleozoic and of the extratropics during parts of the post-Paleozoic (Allison and Briggs 1993; Jablonski 1993; Jablonski et al. 2006; Vilhena and Smith 2013). The proportion of area sampled in the

FIGURE 6. Analysis based on reefs vs. non-reef environ- range of genera with non-reef affinity. Conventions as in ments. A, Areal extent of reefs and non-reef environments. Figures 4A and 5. Genera significantly expand and B, Relationship between change in areal extent of reefs and contract their geographic range in concert with the areal mean change in geographic range of genera with reefal extent of their preferred habitat (one-tailed p 0.001 and affinity. C, Relationship between change in areal extent of p ’ 0.0001 for genera with reefal and non-reef affinity, non-reef environments and mean change in geographic respectively). 450 MICHAEL FOOTE

Paleobiology Database that is reconstructed 0.001 0.001

value as tropical is generally higher than the p- empirical estimate of Walker et al. (2002) (Fig. 7), even though paleolatitude in both cases is based on similar reconstructions

error (Scotese and Golonka 1992, cited in Walker

Standard et al. 2002; C. Scotese personal communica- tion to the Paleobiology Database 2001). To explore the effects of possible latitudinal Log ratio odds sampling bias, I subsampled data so that the proportion of equal-area cells in the tropics for each time interval matched the ratio Odds prediction of the regression line through the Walker et al. data (Fig. 7). The results are consistent with those obtained using the raw data (Appendix 1), suggesting that, to the extent that there is a tropical sampling bias, it Odds of

range increase is not responsible for the documented corre- lation between geographic range size and areal extent of preferred environment. In interpreting the difference between carbonate and clastic results, it must be borne in mind that there is a general

Increases in tendency for carbonates to occur preferen- geographic range tially in tropical latitudes and shallower water (Wilson 1975; Walker et al. 2002). Therefore, what are interpreted here as effects of preference for carbonate environ- ments could partly reflect latitudinal prefer- ences or other environmental correlates. Decreases in

geographic range Although estimates of relative depth of deposition are incomplete, we can at least measure the strength of association between paleolatitude and lithology by forming 2 3 2 tables with the number of collections that are Areal

extent of tropical versus extratropical and carbonate versus clastic. All but eight of the 71 time preferred habitat Increase 575 984 1.71 2.45 0.89 0.074 Increase 841 1267 1.51 1.98 0.69 0.059 intervals used here show a positive associa- tion between tropical latitude (308) and carbonate lithology. I therefore carried out an additional analysis to control statistically for this association. For each time interval, I in tabulation No. involved of transitions randomly omitted collections from the more common combinations of latitude and lithol- ogy—usually carbonate-tropical and clastic- No. of genera extratropical—until the association between latitude and lithology was eliminated. The

4. Association between changes in habitat extent and geographic range for genera with affinities for reefs and non-reef environments. results are at least as strong as in the raw data (Table A1), suggesting that we are not ABLE T Affinity Reef 888 830 Decrease 899 629 0.70 Non-reef 1240 1112merely Decrease seeing the 1568 effects of 1187 latitudinal 0.76 ENVIRONMENT AND GEOGRAPHIC RANGE 451

the association between whether preferred environments expanded from the stage of first appearance to the subsequent stage, and whether the genera survived to the next stage. There is a statistically significant association (combined carbonate and clastic odds ratio: 1.53; p 0.001). However, this may not be very significant biologically, because the chances of survival are so high regardless of whether preferred environment expands (pro- portion surviving is 84.4% for genera whose preferred environment shrinks and 89.2% for those whose environment expands). Any FIGURE 7. Relative areal extent of shallow-water tropics genus that occurs frequently enough to show (closed squares) and proportion of sampled area that is a distinct environmental affinity is generally tropical (open circles). Shallow tropical area was estimated by digitizing Figure 2 of Walker et al. (2002); solid line is sufficiently abundant and widespread that it is the least-squares linear regression through these points, almost certain to survive past its stage of first having equation Ptrop ¼ 0.32 þ 0.00068 TMa. Sampled appearance. Genera that meet the minimum of tropical area is the proportion of equal-area grid cells, of those containing any data, that have estimated paleolati- ten occurrences throughout their duration tudes of 308 or lower. If the estimates of Walker et al. are have odds of survival beyond their stage of taken as the expectation of how data should be distrib- first appearance that are 16.5 times higher uted, the tropics may be oversampled for much of the Phanerozoic. This gives the rationale for an additional than those of genera that fall short of this analysis in which areal sampling is forced to follow the minimum. Statistically, this effect swamps the prediction of the regression line (Appendix 1). expansion of preferred environments. For many clades, the average geographic preference masquerading as carbonate or ranges of species and genera are initially clastic preference. small, expand over time, and contract leading If the difference between carbonate and up to the time of extinction (Jernvall and clastic results is robust, it would be another Fortelius 2004; Raia et al. 2006; Foote 2007; example of major macroevolutionary and Foote et al. 2007; Liow and Stenseth 2007; macroecological differences between taxa with Tietje and Kiessling 2013), although of course these respective affinities, as well as other many other general patterns have been dis- differences in environmental preference (Mil- cussed as well (Jablonski 1987; Kiessling and ler 1988; Miller and Mao 1995; Cope and Babin Aberhan 2007b; Gaston 2008). Given the 1999; Miller and Connolly 2001; Novack- results of this study, could the rise and fall Gottshall and Miller 2003; Foote 2006; Kies- be explained by genera tracking the expansion sling and Aberhan 2007a). It seems likely that and contraction of their preferred environ- at least one reason for the different strengths ments (Holland and Zaffos 2011)? One reason of association between environmental extent to suppose a priori this is not the explanation and geographic range is that areas of carbon- is that the regular averages that have been ate deposition often represent a more specific documented are based on aggregates of subset of environmental factors compared genera with staggered first and last appear- with the more generalized environmental ances and variable durations. Also, a symmet- correlates of clastic deposition (Wilson 1975). rical average rise and fall is the expected It is tempting to ask whether the expansion outcome of a bounded random walk process of preferred environments is a factor that (Foote 2007: Appendix; Pigot et al. 2012), so it contributes to survival beyond the stage of is possible that no overriding factor is needed first appearance of a genus (Heim and Peters to drive the average expansion and contrac- 2011; Foote and Miller 2013; Nurnberg¨ and tion, even if, as shown here, areal extent of Aberhan 2013). For genera having a defined preferred environments influences range fluc- affinity, I calculated the odds ratio showing tuations of individual genera. 452 MICHAEL FOOTE

To explore the relationship between envi- ronment and the rise-and-fall pattern, I segre- gated genera into duration classes (number of stages), calculated the average geographic range of each group of genera in each stage of its duration, and compared this with the mean areal extent of the preferred environ- ment of these genera in these stages (Fig. 8). For genera with durations of three stages, the initial average expansion in range from the first to the second stage corresponds to an increase in the extent of their preferred lithology (Fig. 8A). Similarly, the contraction in average range from the second to the final stage is matched by a decrease in extent of preferred lithology. Note, however, that the change in the average extent of preferred lithology is small compared to the changes documented with respect to real geologic time (Fig. 5). When removed from the context of actual time, three-stage genera show a consid- erable expansion and contraction, but the small corresponding change in the average areal extent of carbonates and clastics suggests that these average aggregates tend to change largely irrespective of how environmental extent changes. Moreover, the relationship between envi- ronment and geographic range largely breaks down for genera with durations of more than three stages (Fig. 8B–F). Genera with longer durations expand and contract on average, but the only clear relationship to preferred environment seems to be a decline in the areal extent of clastics from the penultimate to the ultimate stage. Moreover, when genera are separated into duration classes rather than superimposed as a single aggregate, there is little systematic variation in average range

geographic range of all three-stage genera sampled in the second stage of their stratigraphic range. For consistency, mean areal extent of preferred lithology is averaged over genera actually sampled; results are similar if this average is taken over all genera extant in a given stage, whether FIGURE 8. Mean geographic range of genera and mean sampled or not. Error bars are plus or minus one standard areal extent of their preferred lithologies. Only genera error, based on bootstrap resampling. Points are plotted with an assigned affinity are included. A–G, Genera with offset for clarity. Except for three-stage genera and for the total stratigraphic range of three through nine stages, final change in range within clastic-loving genera, areal respectively. Closed symbols show the mean range of all extent of preferred lithology is not a good predictor of genera sampled within a given stage of their existence; for overall average geographic range when genera that lived example, the points at stage 2 in panel A give the mean at different times are averaged together. ENVIRONMENT AND GEOGRAPHIC RANGE 453

TABLE 5. Association between changes in areal extent of lithology and geographic range, excluding transitions that involve the stages of first and last appearance of genera.

Areal Decreases Increases extent of in in Odds of Log preferred geographic geographic range Odds odds Standard Affinity lithology range range increase ratio ratio error p-value Carbonate Decrease 1370 1062 0.78 Increase 789 1267 1.61 2.07 0.73 0.061 0.001 Clastic Decrease 1470 1364 0.93 Increase 1358 1785 1.31 1.42 0.35 0.052 0.001

other than the initial expansion and final widespread—mesh with the larger-scale ob- retreat. In light of these results, we should servation that changes in geographic range of ask whether the overall correlation between genera over millions of years are correlated geographic range and areal extent of lithology with, and presumably influenced by, the (Table 2) reflects anything other than the initial expansion and contraction of their preferred expansion and final contraction of individual habitat. These in turn mirror patterns at even genera. It does: If we ignore transitions larger taxonomic scales, in which diversifica- involving the stages of first and last appear- tion and prevalence of preferred habitat are ance, we see that the association between related (Miller and Connolly 2001). individual changes in range and changes in environmental extent is just as strong (Table 5). Acknowledgments Another factor that influences genus geo- I am grateful to the many people who have graphic range is breadth of environmental contributed to the Paleobiology Database. tolerance, whether this is because individual Major contributors for the data used herein species are broadly tolerant (Bozinovic et al. include M. Aberhan, J. Alroy, A. Miller, D. 2011; Slatyer et al. 2013) or because congeneric Bottjer, M. Clapham, F. Fursich,¨ N. Heim, A. species vary in their preferences. Against this Hendy, S. Holland, L. Ivany, W. Kiessling, B. backdrop, the results presented here agree Kroger,¨ A. McGowan, T. Olszewski, P. No- with the notion that widespread taxa do not vack-Gottshall, M. Patzkowsky, M. Uhen, L. necessarily have the broadest tolerances, but Villier, and P. Wagner. I thank D. Jablonski, A. instead track environmental factors that are I. Miller, M. F. Przeworski, S. E. Peters, and D. more broadly distributed, as Jablonski et al. B. Rowley for discussion and advice. S. (2013) recently reported for temperature pref- Finnegan, A. I. Miller, M. Powell, and an erences of living bivalve species. A rough look anonymous referee kindly reviewed the man- attheroleofenvironmentalbreadthis uscript. Supported by NASA Exobiology possible by comparing genera with distinct (NNX10AQ44G). This is Paleobiology Data- carbonate or clastic affinities to those that have base publication number 194. no clear affinity. Although the test is quite crude, given the coarse environmental catego- Literature Cited ries, it suggests that eurytopic genera, oper- Agresti, A. 2007. An introduction to categorical data analysis, 2nd ationalized as those that occur nearly as ed. Wiley, New York. frequently in carbonates as in clastics, are at Allison, P. A., and D. E. G. Briggs. 1993. Paleolatitudinal sampling bias, Phanerozoic species diversity, and the end- mass most about 10% more widely distributed on extinction. Geology 21:65–68. average than genera with clear carbonate or Bennett, K. D. 1997. Evolution and ecology: the pace of life. clastic affinities (Appendix 4). Cambridge University Press, Cambridge. Bozinovic, F., P. Calosi, and J. I. Spicer. 2011. Physiological In summary, the results presented here correlates of geographic range in . Annual Review of illustrate two ways in which the properties Ecology, Evolution, and Systematics 42:155–179. of species—their tendency to track preferred Brett, C. E., A. J. W. Hendy, A. J. Bartholomew, J. R. Bonelli Jr., and P. I. McLaughlin. 2007. Response of shallow marine biotas to environments and to be more widespread sea-level fluctuations: a review of faunal replacement and the when their preferred environments are more process of habitat tracking. Palaios 22:228–244. 454 MICHAEL FOOTE

Cope, J. C. W., and C. Babin. 1999. Diversification of bivalves in the dynamics of the marine latitudinal diversity gradient. the Ordovician. Geobios 32:175–185. Proceedings of the National Academy of Sciences USA Curran-Everett, D. 2000. Multiple comparisons: philosophies and 110:10,487–10,494. illustrations. American Journal of Physiology: Regulatory, Jackson, S. T., and J. T. Overpeck. 2000. Responses of plant Integrative and Comparative Physiology 279:R1–R8. populations and communities to environmental changes of the Foote, M. 2006. Substrate affinity and diversity dynamics of late Quaternary. In D. H. Erwin and S. L. Wing, eds. Deep time: Paleozoic marine animals. Paleobiology 32:345–366. Paleobiology’s perspective Paleobiology 26(Suppl. to No. 4):194– ———. 2007. Symmetric waxing and waning of marine inverte- 220. brate genera. Paleobiology 33:517–529. Jernvall, J., and M. Fortelius. 2004. Maintenance of trophic Foote, M., and A. I. Miller. 2013. Determinants of early survival in structure in fossil mammal communities: site occupancy and marine animal genera. Paleobiology 39:171–192. taxon resilience. American Naturalist 164:614–624. Foote, M., J. S. Crampton, A. G. Beu, B. A. Marshall, R. A. Cooper, Kiessling, W., and M. Aberhan. 2007a. Environmental determi- P. A. Maxwell, and I. Matcham. 2007. Rise and fall of species nants of marine benthic biodiversity dynamics through – occupancy in Cenozoic fossil mollusks. Science 318:1131–1134. time. Paleobiology 33:414–434. Foote, M., J. S. Crampton, A. G. Beu, and R. A. Cooper. 2008. On ———. 2007b. Geographical distribution and extinction risk: the bidirectional relationship between geographic range and lessons from Triassic–Jurassic marine benthic organisms. Journal taxonomic duration. Paleobiology 34:421–433. of Biogeography 34:1473–1489. Gaston, K. J. 1998. Species-range size distributions: products of Krug, A. Z., D. Jablonski, and J. W. Valentine. 2008. Species-genus speciation, extinction and transformation. Philosophical Trans- ratios reflect a global history of diversification and range actions of the Royal Society of London B 353:219–230. expansion in marine bivalves. Proceedings of the Royal Society ———. 2008. Biodiversity and extinction: the dynamics of of London B 275:1117–1123. geographic range size. Progress in Physical Geography 32:678– Lessios, H. A. 2008. The Great American Schism: divergence of 683. marine organisms after the rise of the Central American ———. 2009. Geographic range limits: achieving synthesis. isthmus. Annual Review of Ecology, Evolution, and Systematics Proceedings of the Royal Society of London B 276:1395–1406. 39:63–91. Gradstein, F. M., J. Ogg, M. Schmitz, and G. Ogg. 2012. The Liow, L. H., and N. C. Stenseth. 2007. The rise and fall of species: geologic time scale 2012. Elsevier, Amsterdam. implications for macroevolutionary and macroecological stud- Hadly, E. A., P. A. Spaeth, and C. Li. 2009. Niche conservatism ies. Proceedings of the Royal Society of London B 274:2745– above the species level. Proceedings of the National Academy of 2752. Sciences USA 106:19,707–19,714. Liow, L. H., H. J. Skaug, T. Ergon, and T. Schweder. 2010. Global Heim, N. A., and S. E. Peters. 2011. Regional environmental occurrence trajectories of microfossils: environmental volatility breadth predicts geographic range and longevity in fossil and the rise and fall of individual species. Paleobiology 36:224– marine genera. PLoS ONE 6:e18946. doi: 10.1371/journal.pone. 252. 0018946. Miller, A. I. 1988. Spatio-temporal transitions in Paleozoic Bivalvia: Hendy, A. J. W., and P. J. J. Kamp. 2007. Paleoecology of Late an analysis of North American fossil assemblages. Historical Miocene–Early Pliocene sixth-order glacioeustatic sequences in Biology 1:251–273. the Manutahi-1 core, Wanganui-Taranaki basin, New Zealand. Miller, A. I., and S. R. Connolly. 2001. Substrate affinities of higher Palaios 22:325–337. taxa and the Ordovician Radiation. Paleobiology 27:768–778. Holland, S. M., and M. E. Patzkowsky. 2007. Gradient ecology of a Miller, A. I., and M. Foote. 2009. Epicontinental seas versus open- biotic invasion: biofacies of the type Cincinnatian Series (Upper ocean settings: the kinetics of mass extinction and origination. Ordovician), Cincinnati, Ohio region, USA. Palaios 22:392–407. Science 326:1106–1109. Holland, S. M., and A. Zaffos. 2011. Niche conservatism along an Miller, A. I., and S. Mao. 1995. Association of orogenic activity onshore-offshore gradient. Paleobiology 37:270–286. with the Ordovician radiation of marine life. Geology 23:305– Holland, S. M., A. I. Miller, D. L. Meyer, and B. F. Datillo. 2001. The 308. detection and importance of subtle biofacies variation within a Novack-Gottshall, P. M., and A. I. Miller. 2003. Comparative single lithofacies: the Upper Ordovician Kope Formation of the geographic and environmental diversity dynamics of gastro- Cincinnati, Ohio region. Palaios 16:205–217. pods and bivalves during the Ordovician Radiation. Paleobiol- Hopkins, M. J., C. Simpson, and W. Kiessling. 2013. Differential ogy 29:576–604. niche dynamics among major marine invertebrate clades. Nurnberg,¨ S., and M. Aberhan. 2013. Habitat breadth and Ecology Letters. doi: 10.1111/ele.12232, accessed 17 December geographic range predict diversity dynamics in marine Meso- 2013. zoic bivalves. Paleobiology 39:360–372. Jablonski, D. 1987. Heritability at the species level: analysis of Patzkowsky, M. E., and S. M. Holland 2007. Diversity partitioning geographic ranges of mollusks. Science 238:360–363. of a Late Ordovician marine biotic invasion: controls on ———. 1993. The tropics as a source of evolutionary novelty diversity in regional ecosystems. Paleobiology 33:295–309. through geological time. Nature 364:142–144. Peters, S. E. 2008. Environmental determinants of extinction ———. 2008. Biotic interactions and macroevolution: extensions selectivity in the fossil record. Nature 454:626–629. and mismatches across scales and levels. Evolution 62:715–739. Pigot, A. L., I. P. F. Owens, and C. D. L. Orme. 2012. Speciation and Jablonski, D., and G. Hunt. 2006. Larval ecology, geographic extinction drive the appearance of directional range size range, and species survivorship in Cretaceous mollusks: evolution in phylogenies and the fossil record. PLoS Biology organismic versus species-level explanations. American Natu- 10:e1001260. doi: 10.1371/journal.pbio.1001260. ralist 168:556–564. R Development Core Team. 2011. R: a language and environment Jablonski, D., K. Roy, and J. W. Valentine. 2006. Out of the tropics: for statistical computing. R Foundation for Statistical Comput- evolutionary dynamics of the latitudinal diversity gradient. ing, Vienna. http://www.R-project.org/. Science 314:102–106. Raia, P., C. Meloro, A. Loy, and C. Barbera. 2006. Species Jablonski, D., C. L. Belanger, S. K. Berke, S. Huang, A. Z. Krug, K. occupancy and its course in the past: macroecological patterns Roy, A. Tomasovˇ ych,´ and J. W. Valentine. 2013. Out of the in extinct communities. Evolutionary Ecology Research 8:181– tropics, but how? Fossils, bridge species, and thermal ranges in 194. ENVIRONMENT AND GEOGRAPHIC RANGE 455

Rosenzweig, M. L., and R. D. McCord. 1991. Incumbent with a geographic range of zero during a stage in which it is extant replacement: evidence for long-term evolutionary progress. but not sampled (Table A1). Paleobiology 17:202–213. Accounting for Cases in Which Absolute Geographic Range Does Not Roy, K., G. Hunt, D. Jablonski, A. Z. Krug, and J. W. Valentine. Change.—Geographic range is measured as the ratio between the 2009. A macroevolutionary perspective on species range limits. number of equal-area cells occupied and the maximum that could Proceedings of the Royal Society of London B 276:1485–1493. be occupied given the spatial extent of data. It is therefore possible Scotese, C. R., and J. Golonka. 1992. PALEOMAP paleogeographic for geographic range to change from one stage to the next because atlas. PALEOMAP Progress Report No. 20. Department of of changes in the spatial extent of data rather than the number of Geology, University of Texas, Arlington. cells occupied. I therefore carried out a separate analysis in which Sheehan, P. M. 2008. Did incumbency play a role in maintaining changes in proportional cell occupancy were included only if boundaries between Late Ordovician brachiopod realms? absolute cell occupancy also changed. In this analysis, the Lethaia 41:147–153. correlation between environmental extent and geographic range Slatyer, R. A., M. Hirst, and J. P. Sexton. 2013. Niche breadth is still stronger for carbonate-lovers, but the difference between predicts geographical range size: a general ecological pattern. carbonate- and clastic-lovers in the strength of association for Ecology Letters 16:1104–1114. individual changes vanishes (Table A1). Tietje, M., and W. Kiessling. 2013. Predicting extinction from fossil Taxa Included.—The main analysis included all marine animal trajectories of geographic ranges in benthic marine molluscs. genera, including those that are planktonic and nektonic. The Journal of Biogeography 40:790–799. rationale is that lithology reflects not just substrate but also the Valentine, J. W., D. Jablonski, A. Z. Krug, and K. Roy. 2008. overall depositional system, which is relevant to pelagic organ- Incumbency, diversity, and latitudinal gradients. Paleobiology isms. I performed a separate analysis (Table A1) including only the 34:169–178. major, principally benthic, classes with at least 1000 occurrences Vilhena, D. A., and A. B. Smith. 2013. Spatial bias in the marine (Anthozoa, Bivalvia, Crinoidea, Demospongea, Echinoidea, Gas- fossil record. PLoS ONE 8:e74470. doi: 10.1371/journal.pone. tropoda, Gymnolaemata, Hexactinellida, Lingulata, Ostracoda, 0074470. Polychaeta, Rhynchonellata, Scaphopoda, Stenolaemata, Stroma- Walker, L. J., B. H. Wilkinson, and L. C. Ivany. 2002. Continental toporoidea, Strophomenata, and Trilobita). These collectively drift and Phanerozoic carbonate accumulation in shallow-shelf account for about 84% of all occurrences. and deep-marine settings. Journal of Geology 110:75–87. Protocol for Assigning Affinity.—Three alternative protocols were Webb, S. D. 1991. Ecogeography of the Great American Inter- used (Table A1): (1) a stricter one requiring a minimum of 20 rather change. Paleobiology 17:266–280. than ten occurrences and a deviation from expected frequency of ———. 2006. The Great American Biotic Interchange: patterns and occurrence of a given lithology at a probability of 0.01 rather than processes. Annals of the Missouri Botanical Garden 93:245–257. 0.05; (2) a weaker one with a minimum of five occurrences and a Willis, K. J., and G. M. MacDonald. 2011. Long-term ecological probability of 0.1; (3) an alternative null hypothesis that all genera records and their relevance to climate change predictions for a are expected to have equal numbers of carbonate and clastic warmer world. Annual Review of Ecology, Evolution, and occurrences (Foote 2006; Miller and Foote 2009). Systematics 42:267–287. Geographic Coordinates.—Locations of collections were assigned Wilson, J. L. 1975. Carbonate facies in geologic history. Springer, in the main analysis by using estimated paleocoordinates (C. New York. Scotese personal communication to the Paleobiology Database 2001). As stated above, this should make little difference when Appendix 1 geographic range and areal extent of lithology are measured with equal-area cells, because most cells will fall within a single plate. Alternative Analyses As expected, there is little quantitative difference in the results if I explored several alternative protocols to assess the robustness locations are assigned to modern coordinates (Table A1). of results, in addition to those briefly mentioned in the main text. Adjusting Sampled Area of Tropical and Extratropical Latitudes.— In all cases, the alternative results show a positive association Assuming that the regression line of Figure 7 approximates the between changes in areal extent of a given environment and areal extent of tropical sampling in the absence of bias, data were changes in the geographic ranges of genera with an affinity for subsampled so that the proportion of equal-area cells in each stage that environment (Table A1). In most cases the measures of would fall on this line. P is the desired proportion of sampled association are also quantitatively rather close to the baseline trop cells falling in the tropics, N is the observed number of cells in analysis. trop the tropics, and N is the total number of cells. If the observed Coding of Lithology.—Secondary lithology was ignored in the tot proportion N /N is greater than P , then the tropics must be standard analysis, and occurrences with a mixed carbonate-clastic trop tot trop downsampled, and the number of tropical cells retained is given lithology were omitted. In an alternative analysis, collections from by mixed settings were retained and the secondary lithology was included in assigning a collection. A collection is considered to Mtrop ¼ PtropðNtot NtropÞ=ð1 PtropÞ come from a mixed setting if the primary and/or secondary lithology field indicates mixed carbonate-clastic lithology, or if the In practice this is truncated to an integer. For example, there are primary lithology is carbonate and the secondary lithology clastic 131 cells sampled in the Tremadocian, 100 (76%) of which are (or vice versa) (Foote 2006: Table 3). Such collections, which tropical. The expected proportion according to the regression line account for 14% of the total, were randomly and equiprobably is 65%. Substituting into the foregoing equation, we find that assigned to the carbonate and clastic categories. The association keeping 57 tropical cells and all 31 extratropical cells yields the between environmental extent and geographic range weakens desired proportion of 65% tropical coverage. Thus 57 tropical cells, somewhat for carbonates, but the results are consistent with the and all the collections contained therein, are randomly chosen and baseline analysis (Table A1). retained, while the remaining 43 tropical cells and all their Convention for Stratigraphic Gaps.—In the analyses presented in collections are omitted. If extratropical latitudes are oversampled, the main text, a change in geographic range was recorded only if a they are similarly downsampled so the expected proportion of genus is sampled in two successive stages. Stages in which a genus tropical coverage is attained. This procedure is repeated for every is known to be extant but is not sampled were ignored. As an stage. The analysis of the resulting data set yields results alternative, I conducted an analysis in which I credited a genus compatible with the analysis of the raw data (Table A1). 456

TABLE A1. Results of alternative analyses.

Association between areal extent of carbonates Association between areal extent and range of genera with carbonate affinity of clastics and range of genera with clastic affinity Odds ratio Correlation Correlation with for individual with mean Odds ratio Analysis mean change in range p-value changes p-value change in range p-value for individual changes p-value Baseline 0.60 0.001 1.89 0.001 0.29 0.008 1.38 0.001 Absolute geographic range* 0.66 (0.48) 0.001 1.88 (1.55) 0.001 0.25 (0.22) 0.021 (0.061) 1.73 (2.02) 0.001 Tropical/extratropical area

subsampled to match empirical FOOTE MICHAEL proportion 0.52 0.001 1.53 0.001 0.33 0.003 1.16 0.002 Tropical-carbonate association eliminated by subsampling 0.60 0.001 2.62 0.001 0.41 0.0003 1.82 0.001 Include collections with mixed lithology 0.52 0.001 1.59 0.001 0.31 0.005 1.51 0.001 Include stratigraphic gaps as zero ranges 0.71 0.001 1.65 0.001 0.33 0.003 1.42 0.001 Include only non-zero changes in absolute cell occupancy 0.61 0.001 1.69 0.001 0.32 0.004 1.79 0.001 Major benthic groups only 0.60 0.001 1.95 0.001 0.25 0.017 1.37 0.001 Stricter affinity protocol 0.57 0.001 1.90 0.001 0.27 0.012 1.40 0.001 Weaker affinity protocol 0.61 0.001 1.81 0.001 0.28 0.009 1.33 0.001 Null hypothesis of even carbonate-clastic split 0.58 0.001 1.78 0.001 0.31 0.005 1.29 0.001 Modern geographic coordinates 0.58 0.001 1.85 0.001 0.30 0.006 1.51 0.001 * Because absolute geographic range potentially depends strongly on the amount of data within a stage, partial correlations with number of collections per stage are reported here; raw correlations are given in parentheses. Odds ratios are estimated from a log-linear model incorporating two-way associations between change in areal extent of environment, change in geographic range, and change in total number of collections in the stage (Agresti 2007: eq. 7.5). Odds ratios ignoring number of collections are reported in parentheses. ENVIRONMENT AND GEOGRAPHIC RANGE 457

Appendix 2

A Model of Decoupled Lithologic Extent and Geographic Range The purpose of describing this model is not to claim that it is realistic, but rather to show that it is possible to simulate data with genera that have strong lithologic preferences, and with substan- tial temporal variation in lithologic extent, but in which the methods used herein do not force a correlation between lithologic extent and geographic range. For each of N stages, M genera originate and subsequently show exponential survivorship with extinction rate q. Half of the genera are randomly assigned a carbonate preference and half a clastic preference, with the probability, Ppref, of occurring in the preferred lithology set to a uniform random number between 0.7 and 0.9. The landscape is divided into Ncell equal-area cells. In each stage, the proportion of collections that are carbonates, Pcarb,isa uniform random number between 0.3 and 0.7. (This range of values is similar to the empirical range.) The proportion of clastic collections, Pclast, is equal to 1Pcarb. In each stage, Ncoll collections are randomly assigned a lithology, with probabilities equal to Pcarb and Pclast for the corresponding stage, and each collection is randomly assigned to one of the cells. Finally, for each genus that is extant in the stage, the number of cells it occupies and the number of collections in which it occurs are drawn at random from Poisson distributions with parameter k1 and k2 (equal to the mean number of cells per genus and the mean number of collections per genus), with the conditions that the specific collections drawn for the genus must be contained within the cells that have been drawn, and that the probability of drawing a collection with a genus’s preferred lithology is equal to its particular value of Ppref. Note that the geographic range of a genus is drawn independently of the areal extent of its preferred lithology. The simulated data are then processed exactly as the empirical data. (Results are essentially the same if genera are classified by their initially assigned affinities rather than affinities determined from the frequency of occurrence in the respective

FIGURE A2. Results of subsampling procedure designed to reduce temporal variation in the representation of carbonate and clastic lithologies. See text for explanation of procedure. A, Distribution of correlations (cf. Fig. 5) between areal extent of lithology and geographic range of genera with affinity for that lithology (solid, carbonate; dashed, clastic), resulting from 1000 replicates of the subsampling procedure. Arrows show values in raw data. Normal curves are fitted to the distribution of subsampling results. B, The same, for the log odds ratio for individual genus changes (cf. Table 2). By making the proportion of carbonate and clastic collections uniform, the lithology-range relationship is diminished but not eliminated; only 0.4% of simulations yield negative correlations for clastics, and 3% yield log odds ratios less than or equal to zero. See text for further discussion.

FIGURE A1. Results of model designed to simulate range histories in which genera do not expand and contract with their preferred lithologies.) For the simulations presented here, Ncell ¼ 1000, Ncoll ¼ habitats. See text for details. Each point shows the pair of 1000, N ¼ 20, M ¼ 50, q ¼ 0.1, k1 ¼10, and k2 ¼ 20, but other values associations for a single simulation. Error bars in upper right are yield compatible results. plus or minus two standard errors (Agresti 2007: p. 30) for the Figure A1 shows the lithology-range associations for 1000 median of the simulations. It is possible for the methods used here simulations. About 10% of the associations are significantly to create a spurious positive association for one habitat, but this is positive at p , 0.05, more than the 5% we would expect by generally coupled with a spurious negative association for the chance. However, the carbonate and clastic associations are other. None of the simulations yield spurious positive associations negatively correlated, a feature not seen in empirical data, so that (at p , 0.05) for both. It therefore seems unlikely that the observed none of the simulations yield significantly positive associations for data would yield positive associations for both carbonates and both lithologies. It therefore seems unlikely that the methods used clastics if genera did not in fact covary in range with the areal here are forced to detect range-lithology associations where none extent of their preferred lithology. exist. 458 MICHAEL FOOTE

Appendix 3

Imposing Uniform Representation of Carbonates and Clastics There are several ways to reduce temporal variation in the representation of lithologies. One reasonable approach would be to focus on large changes between successive stages. For example, if there is a large jump in the proportion of clastic collections from one stage to the next, one could sample fewer clastic collections from the second stage. How many fewer, however? One possibility is to down-sample until the proportions in successive stages do not differ significantly in the statistical sense. In analyses not presented here, I have used this approach and found it to have rather minor effects on the results. Instead, I will present results of a more draconian sampling scheme. In the observed data, there are Ncarb carbonate collections and Nclast clastic collections in each stage; let Nmin be the minimum of these two. Then, for each stage, Nmin collections of the more common lithology are sampled at random, and all of the collections of the less common lithology are retained, so that the two lithologies are equally represented. The analysis then proceeds as for the original empirical data. This subsampling procedure was repeated 1000 times. The results (Fig. A2) show that the lithology-range relationship is diminished but not eliminated. FIGURE A3. Mean per-stage geographic range of eurytopes versus genera with clear affinities. Open and closed circles show the Appendix 4 weaker and stricter operational definition of eurytopes, respec- tively. Dotted line is the 1:1 line, solid line is the regression through the open circles, and dashed line is the regression through the Geographic Range of Eurytopes versus Genera with Clear closed circles. Using a stringent criterion for eurytopy yields Affinities genera having slightly larger average ranges than those with a The genera that have no clear affinity overlap with the distinct lithologic affinity. carbonate and clastic groups in terms of their distribution of lithologic occurrences (Fig. 1), and in many cases it is not possible to assign them an affinity simply because they have relatively few genera with distinct affinities (28). I also made a second, stricter occurrences. In fact, the median number of occurrences of these designation corresponding to those genera with deviations of less genera collectively is 18, compared with 28 for the genera having than or equal to 0.05; these genera have a median of 28 clear affinities. Thus, all else being equal, we would expect them to occurrences. For every stage, I tabulated the mean geographic have smaller sampled geographic ranges. Therefore, I operation- range of genera with distinct affinities (carbonate and clastic ally designated as eurytopes the subset of no-affinity genera that have deviations between expected and observed frequency of combined) and the mean range of eurytopes. The results are carbonate (or clastic) occurrence of less than or equal to 0.1, i.e., the shown in Figure A3. The two designations of eurytopes show inner part of the distribution of Figure 1C. These have nearly the either slightly smaller or slightly larger geographic ranges on same median total number of occurrences per genus (26) as do the average compared with the genera having distinct affinities.