Time and Sampling in the Fossil Record

Both paleontologists and comparative biologists tend to think about each individual fossil specimen as having an age, usually in millions of years ago—and they do, but it is rarely possible to determine the age with absolute precision. This is not only due to “measurement error,” such as that represented by confidence intervals around radiometric dates; rather, the imprecision of geologic dating is a consequence of sedimentary processes and the limitations of radiometric dating (see Patzkowsky and Holland Reference Patzkowsky and Holland2012). Radiometric dates can be obtained directly from fossil material, but only if specimens are of a certain type and not very old (fewer than 50,000 years for carbon dating of bones, teeth, or plant material, and 500,000 years for uranium–thorium dating of calcium carbonate shells). Rock units, such as volcanic tuffs, which can provide much older radiometric ages for calibrating geologic time intervals, are relatively rare, nonuniformly deposited in space and time, and typically non–fossil bearing. The sedimentary rocks that preserve fossils are lithified piles of sand and mud that accumulated over time. Thus, to estimate an age for most fossils, we have to first determine the relative order of deposition of those sediment deposits. Even though the relative age of fossils collected from successive beds at a single outcrop is obvious due to their order from oldest at the bottom to youngest at the top, the relative age of fossils sampled from different localities can be difficult to determine and depends primarily on some similarity in the fossil species preserved. Because rates of sedimentation vary and sediment deposition is locally sporadic, sedimentary strata of the same thickness may represent different amounts of time, and the boundaries between strata may represent different amounts of unpreserved time, even at the same outcrop (Holland Reference Holland2016). The global geologic record is compiled by matching beds or boundaries between beds over large spatial areas, using the fossils contained within them (biostratigraphy), stable isotope data (chemostratigraphy), and regional sedimentary features related to sea-level changes (sequence stratigraphy). An absolute age model is applied primarily by assigning radiometric dates to boundaries that represent the relative position in the sedimentary sequence of dated volcanic beds, where they can be located. A few stage boundaries have direct dates, which means that most boundary ages are estimated by interpolation (Gradstein et al. Reference Gradstein, Ogg, Schmitz and Ogg2012). The preservation of magnetic reversals in association with seafloor spreading has also been used for the last 50 years to calibrate the geologic timescale but can only be applied from the Late Jurassic to the present. Orbital tuning is selectively replacing such “magnetochron” methods, but has its greatest application to deep-sea marine sediments from the Oligocene to the present (Gradstein et al. Reference Gradstein, Ogg, Schmitz and Ogg2012). Despite these challenges, it is possible to build high-resolution global timelines of fossil occurrences scaled to absolute time, including into the Paleozoic (e.g., Sadler Reference Sadler2004; Sadler et al. Reference Sadler, Cooper and Melchin2009), but the resolution of the geological timescale—and the number of fossil occurrences that can be placed within it—varies from study to study, and high-resolution timelines exist mainly for data sets limited to specific taxonomic groups.

For most fossil specimens, what can be determined is the particular interval of geologic time from which that specimen was collected, but not its exact age. The length of this interval can vary considerably. Highly precise geologic records can have very short intervals encompassing single years, in the case of some lake deposits, to thousands of years for deep-sea sediment cores. Conversely, some records can have intervals encompassing staggeringly long amounts of time, such as tens of millions of years for some terrestrial deposits. Most fossil occurrences, however, can be assigned locally to biostratigraphic zones, which can represent tens of thousands to millions of years. Placing such fossil occurrences in a global timescale frequently requires coarsening the resolution to the level of geologic stages. Across the Phanerozoic, the global marine timescale has an average resolution of 5.5 Myr; for just the Cenozoic, this improves to an average of 3.7 Myr.

Fossil taxa are often represented by multiple specimens sampled from multiple collections spanning multiple stratigraphic intervals, giving that taxon a stratigraphic “range” that represents its temporal duration. The oldest and youngest specimens that have been sampled for a fossil taxon represent the “first occurrence” and the “last occurrence,” respectively, of that taxon (other terminology for the same concept includes “first/last appearance” and “first/last appearance datum”) and are used to infer the actual time of speciation and extinction. The same age uncertainty that exists for any fossil specimen (discussed earlier) also applies to these specimens. Specifically, the age of the first and last occurrences can be bracketed within particular intervals of time, but precise ages can only rarely be assigned (Fig. 1). How well the sampled first and last occurrences represent the time of speciation or extinction of the taxon is also an issue of accuracy and has been the subject of considerable paleobiological research (see “Stratigraphic Ranges and Stasis” section).

Figure 1 Schematic showing local sampling of fossil specimens of a hypothetical species (A) compared with the uncertainty around first and last occurrences in a global timescale (B). The species was sampled locally from multiple strata, represented by the black bars in A. Strata with the oldest specimens are known to be Coniacian in age based on biostratigraphically useful fossils also sampled from the same strata (indicated by the biozone boundaries). Strata with the youngest specimens are known to be early Maastrichtian in age. If occurrences of this species at other localities also fall within this range, then the global stratigraphic range of this species is considered to be Coniacian to Maastrichtian. At the typical resolution of the global timescale for marine sediments, the lengths of these two stages represent the uncertainty around the global first and last occurrences (about 3 million years and 6.1 million years, respectively). Note that although the Santonian is about as long in temporal duration as the Coniacian (B), each stage is represented locally by different thicknesses of rock (A). The stratigraphic section in A is modeled after the Guru Section in south Tibet (Wendler et al. Reference Wendler, Willems, Gräfe, Ding and Luo2011). Timescale in B based on Gradstein et al. Reference Gradstein, Ogg, Schmitz and Ogg2012.

Time and Sampling in the Molecular Record

In comparison to the fossil record, the relationship between sampling and time is straightforward for living taxa: almost all individuals sampled have a timestamp of sometime in the past 150 years, with very rare exceptions (Leonardi et al. Reference Leonardi, Librado, Der Sarkissian, Schubert, Alfarhan, Alquraishi, Al-Rasheid, Gamba, Willerslev and Orlando2017). At the scale of the evolutionary histories of clades, these individuals are effectively the same age, and we denote this by saying that they were sampled from the Recent.

Assigning Times of Observation

Sampling–time relationships influence how dates are assigned to different biological units. In dated molecular phylogenies, branch tips are inherently linked to observational data sampled from contemporaneous populations. Many comparative approaches assume that the ages of tip taxa are single-point estimates, even if noncontemporaneous data are allowed. This concept of branch tips as instantaneous populations is incongruous with the paleontological concept of species, because morphologically indistinct specimens sampled across millions of years of geologic time are often treated as a single contiguous taxonomic unit (e.g., a “morphospecies”) with a stratigraphic range. Paleontological data thus complicate any analysis in which a taxon needs to be assigned a single precise age, requiring some treatment to deal with persistent morphotaxa and leading to the so-called times of observation problem (Fig. 2; Bapst Reference Bapst2013). Previous studies have assigned fixed ages by sampling from a uniform distribution bounded by the taxon’s stratigraphic range (e.g., Heath et al. Reference Heath, Huelsenbeck and Stadler2014), but the stratigraphic range is distinct from stratigraphic uncertainty in the age of a specimen or the first occurrence of the taxon (see “Time and Sampling in the Fossil Record” section), and the two should not be confounded.

Figure 2 Schematic showing potential variation in “points of observation” for different types of data. Thin black line shows complete evolutionary history of a clade. Thick gray lines represent known stratigraphic range based on the fossil record. Dashed black lines represent range extension of living taxa into the future (it is currently unknown when the last occurrence will be). Blue vertical lines mark points of observation for discrete character data describing a species. Because all individuals of the species share these characters, they must be expressed by the time of the first occurrence of the species. Red vertical lines mark points of observation for molecular data; these are tied to the age of the sampled specimen, almost always at the present, except for rare samples from ancient DNA. Black vertical lines mark additional points in the stratigraphic range where species have been sampled. Stars mark points of observation for continuous morphological data, which are tied to the age of the measured specimen sampled from that part of the stratigraphic range. There may be more than one such specimen within the stratigraphic range of the species, and the age of the measured specimen(s) may not be coincident with the first or last occurrence of the species. Although vertical lines and stars are represented as “points” in time, each has an uncertainty associated with it based on the resolution of the fossil record and age model (see Fig. 1).

The time of observation that should be used in a given analysis will depend on the parameters of interest. For example, if one is interested in the morphological evolution of a continuous trait, the appropriate time of observation may be the estimated age of the particular specimen from which the morphological data were measured. But if one is interested in discrete character change along branches, then the appropriate time of observation may be the first occurrence of the taxon, because all of the discrete characteristics that describe that taxon must be present by that point (e.g., Hopkins and Smith Reference Hopkins and Smith2015). For living taxa with a fossil record, this complicates efforts to combine morphological and molecular data in single analyses, as the morphological data might be more appropriately tied to the first occurrence of a species, while the molecular data are tied to the present day. The confounding effect of different times of observation is largely unexplored in the literature, but choices about times of observation should not be ignored, as these decisions can impact phylogenetic comparative analyses with fossil data (Bapst Reference Bapst2014; Cuff et al. Reference Cuff, Randau, Head, Hutchinson, Pierce and Goswami2015). A similar issue arises with calculations of phylogenetic diversity and the loss of evolutionary history, the measurement of which makes implicit assumptions about how we conceptualize the persistence of taxonomic units over geologic time (Huang et al. Reference Huang, Goldberg and Roy2015).

Stratigraphic Ranges and Stasis

Paleontologists have long worried about how well the age of the oldest (or youngest) sampled specimens of a species represent the time of speciation or extinction of that species (e.g., Strauss and Sadler Reference Strauss and Sadler1989; Marshall Reference Marshall1990, Reference Marshall1997; Weiss and Marshall Reference Weiss and Marshall1999; Holland Reference Holland2003; see Wang and Marshall [Reference Wang and Marshall2016] for a review). The gap between speciation and the first sampled occurrence of a species (the range offset; see Holland and Patzkowsky Reference Holland and Patzkowsky2002) is due at least in part to the evolutionary history of a species or clade, rather than simply a general failing of the fossil record. This is because most species start and end with small geographic ranges and low abundance (Foote et al. Reference Foote, Crampton, Beu, Marshall, Cooper, Maxwell and Matcham2007, Reference Foote, Crampton, Beu and Cooper2008; Liow and Stenseth Reference Liow and Stenseth2007), reducing the probability that member individuals will be sampled, even if they are preserved somewhere in the rock record (e.g., CoBabe and Allmon Reference CoBabe and Allmon1994). High-resolution sampling of the fossil record can only occasionally provide information about the process of speciation, or at least about the pattern of morphological divergence among putative descendant populations from an ancestral stock (e.g., Geary Reference Geary1992; Hunt et al. Reference Hunt, Bell and Travis2008).Paleontologists tend not to consider where in the process of reproductive isolation that morphological distinctiveness occurs, and thus what stage of speciation is reflected by first occurrences, as the geologic record often involves coarse timescales. However, there is considerable variation in how quickly speciation occurs (regardless of how it is defined; Marie Curie Speciation Network 2012), with some estimates as long as millions of years (e.g., to complete reproductive isolation; Dufresnes et al. Reference Dufresnes, Brelsford, Crnobrnja-Isailović, Tzankov, Lymberakis and Perrin2015). The appearance across clades of morphologically distinct units, as recognized in paleontology, may be entirely uncoupled from when lineages diverge (e.g., relative to divergences reconstructed on a dated molecular phylogeny; Huang et al. Reference Huang, Goldberg and Roy2015). The question of whether most morphological differentiation occurs during speciation is still under active investigation (Pennell et al. Reference Pennell, Harmon and Uyeda2014) but has implications for estimating evolutionary rates and divergence times, as we lack phylogenetic models that incorporate this possibility.

There will always be an interval of time over which a taxon existed, regardless of how well the first and last occurrences of a taxon are known to approximate the time of speciation and extinction both accurately and precisely. The observation that morphospecies are consistently found within sedimentary rocks spanning multiple intervals, and thus appear to persist for sometimes millions of years, underlies the concept of morphological stasis (Eldredge and Gould Reference Eldredge and Gould1972). Over many years, there has been discussion about how stasis should be modeled, how sampling and species concepts influence the documented patterns, and what processes might be driving it (see Lidgard and Hopkins [Reference Lidgard and Hopkins2015] for an annotated bibliography). Such considerations influence how stasis has been defined, with definitions ranging from the more general and oft-used pattern-based “little net morphological (or evolutionary) change within a lineage” (Eldredge et al. Reference Eldredge, Thompson, Brakefield, Gavrilets, Jablonski, Jackson, Lenski, Lieberman, McPeek and Miller2005; Pennell et al. Reference Pennell, Harmon and Uyeda2014), to the highly specific, process-based “no evolution within any of the coexisting species due to their interactions with their biotic or abiotic environment, but with occasional minimal evolution due to genetic drift” (Nordbotten and Stenseth Reference Nordbotten and Stenseth2016: p. 1849). Despite this debate on quantifying stasis, the existence of long-lived morphospecies has been widely documented (see Erwin and Anstey Reference Erwin and Anstey1995; Hallam Reference Hallam1998; Jackson and Cheetham Reference Jackson and Cheetham1999; Jablonski Reference Jablonski2000; Eldredge et al. Reference Eldredge, Thompson, Brakefield, Gavrilets, Jablonski, Jackson, Lenski, Lieberman, McPeek and Miller2005; Hunt Reference Hunt2007; Hopkins and Lidgard Reference Hopkins and Lidgard2012; Hunt et al. Reference Hunt, Hopkins and Lidgard2015), indicating a need to consider this aspect of the evolutionary process in phylogenetic analyses incorporating fossils.

Shifting Vantage Points

In some ways, molecular data might seem much more powerful than fossil data, in that they can be treated as precisely known points of observation. Unfortunately, the simple relationship between sampling of Recent specimens and time does not provide a universal framework for comparative analyses based on molecular phylogenies. A relatively well-known example of this comes from recent exploration of the performance of the gamma statistic. The gamma statistic assesses how internode distances vary through time relative to what would be expected under a pure birth process (Pybus and Harvey Reference Pybus and Harvey2000). Negative gamma values indicate that nodes are concentrated near the root of the tree, which in turn indicates that the diversification rate has decreased over time, as might be expected if diversification is diversity dependent (Phillimore and Price Reference Phillimore and Price2008). However, phylogenies driven by diversity-dependent diversification will only yield negative gamma values if the tree is sampled around the time that equilibrium diversities were first reached (Liow et al. Reference Liow, Quental and Marshall2010), and thus carries poor test power when the present marks a different point in a clade’s diversification history.

Although molecular phylogenies typically consist of taxa sampled from the same time, that particular time—the Recent—likely represents different points in the diversification history of different clades, contingent on both the age of the group and its specific diversification trajectory. This phenomenon is similar to the “shifting baselines” phenomenon recognized in ecology and conservation biology. The shifting baselines concept originated in fisheries research to describe the tendency for each new generation to consider the depauperate fish communities they grew up with as pristine (Pauly Reference Pauly1995). Thus the “baseline” for judging the health of current populations is frequently based on personal experience, as if no relevant change had occurred before, and thus shifts generation by generation. In the case of molecular phylogenies, the present represents many different baselines, depending on the clade of interest. If all diversification histories could be somehow standardized to the equivalent starting point, it would become clear that the present represents snapshots of many different evolutionary points. This is effectively what is done to apply the gamma statistic, but ironically, the suite of snapshots represented by the present makes clade histories much harder to compare within the same framework, as is apparent from the shortcomings of the gamma statistic. With the shifting baselines concept in mind, we have dubbed this the “shifting vantage points” phenomenon.

The shifting vantage points phenomenon extends to other common analyses in evolutionary biology, notably the application of early burst models of trait evolution to phylogenetic data sets, which tests whether trait evolution was higher early in a clade’s history rather than later (Harmon et al. Reference Harmon, Losos, Davies, Gillespie, Gittleman, Jennings, Kozak, McPeek, Moreno-Roark, Near, Purvis, Ricklefs, Schluter, Jr, Seehausen, Sidlauskas, Torres-Carvajal, Weir and Mooers2010; Slater and Pennell Reference Slater and Pennell2014). Like gamma, early burst models are time-dependent, with constant exponential rate change, and thus the initiation point is not arbitrary. Unfortunately, application of early burst models often assess the entire data set (i.e., all taxa on a given phylogeny) rather than a specific point chosen a priori. This means the initiation of the early burst is often at the divergence between a major clade and a small outgroup, which may have little relationship to where some prior expectation of an early burst may have been placed. For molecular phylogenies, this often means the initiation of a crown clade, even though the onset of an increase in the rate of trait change and the subsequent slowdown might be earlier, in an unseen stem portion of the clade (Slater and Pennell Reference Slater and Pennell2014). Even for paleontological phylogenies, the tested initiation point is likely at the origin of some major named group, which may be a poor choice if clades originate long before they enter a phase of intense diversification and trait change (e.g., Cooper and Fortey Reference Cooper and Fortey1998; Hopkins and Smith Reference Hopkins and Smith2015). Fortunately, very recent work extends these models to allow for early bursts within subclades rather than across the entire tree (Puttick Reference Puttick2018).