June 17, 2007
Using a Theoretical Ecospace to Quantify the Ecological Diversity of Paleozoic and Modern Marine Biotas
By Novack-Gottshall, Philip M
Abstract.- The process of evolution hinders our ability to make large-scale ecological comparisons-such as those encompassing marine biotas spanning the Phanerozoic-because the compared entities are taxonomically and morphologically dissimilar. One solution is to focus instead on life habits, which are repeatedly discovered by taxa because of convergence. Such an approach is applied to a comparison of the ecological diversity of Paleozoic (Cambrian- Devonian) and modern marine biotas from deep-subtidal, soft- substrate habitats. Ecological diversity (richness and disparity) is operationalized by using a standardized ecospace framework that can be applied equally to extant and extinct organisms and is logically independent of taxonomy. Because individual states in the framework are chosen a priori and not customized for particular taxa, the framework fulfills the requirements of a universal theoretical ecospace. Unique ecological life habits can be recognized as each discrete, n-dimensional combination of character states in the framework. Although the basic unit of analysis remains the organism, the framework can be applied to other entities-species, clades, or multispecies assemblages-for the study of comparative paleoecology and ecology. Because the framework is quantifiable, it is amenable to analytical techniques used for morphological disparity. Using these methods, I demonstrate that the composite Paleozoic biota is approximately as rich in life habits as the sampled modern biota, but that the life habits in the modern biota are significantly more disparate than those in the Paleozoic; these results are robust to taphonomic standardization. Despite broadly similar distributions of life habits revealed by multivariate ordination, the modern biota is composed of life habits that are significantly enriched, among others, in mobility, infaunality, carnivory, and exploitation of other organisms (or structures) for occupation of microhabitats.
Ecological communities, however, do exist, but what are linked in them by biotic factors are not thefaunistic units, the species, but the ecological units, the life forms.
-G. Thorson (1957: p. 470)
Though the technical difficulties are very great, they could probably be solved by anyone who really wanted to compare the furry growth of diatoms on a stone in a stream with the larger-scale patches of woodland that have about the same sort of uniformity when viewed from an airplane.
-G. E. Hutchinson (1965: p. 77)
Is the modern marine biota composed of the same life habits as ancient ones? Which biotas are ecologically more diverse, in terms of both the number of life habits and the disparity (similarity) of these life habits? These are basic questions that ought to be answerable quantitatively by comparative paleoecologists. I will argue below that the answers to these and similar questions are impeded by a methodological limitation in our ability to compare communities (or other ecological entities) when they are separated by vast expanses of time and space and when they share few or no evolutionary homologies. Their solution hinges on the ability to compare quantitatively all kinds of entities directly on the basis of their ecological capabilities.
Taxonomy has remained a typical yardstick for such comparisons. It has formed the dominant basis for comparing the structure of Paleozoic and Recent communities (Bretsky 1968; Ziegler et al. 1968; Walker and Laporte 1970; Levinton and Bambach 1975; West 1976; Miller 1988; Radenbaugh and McKinney 1998). Although all of these studies considered various ecological characters (e.g., trophic guilds, abundance), their primary impetus was the presence of taxonomically similar entities. The underlying assumption when using taxonomy in this way is that the ecological characters of taxonomic groups are conserved during evolution, such that taxonomy acts as shorthand for ecology. Although this may be generally true at low taxonomic levels, and occasionally high ones (Webb et al. 2002), there are many exceptions. For example, Fauchald and Jumars (1979) noted stark population-level differences within individual species of polychaetes, and Stanley (1968,1972) and Miller (1990) noted widespread life habit convergence among bivalve orders. As a general rule, Peterson et al. (1999) demonstrated that conservatism is less likely above the familial level. Thus, although taxonomic comparisons may be suitable for documenting the ecological organization of taxonomically similar communities, such a basis is not useful when comparing taxonomically disparate communities. In short, taxonomy is an indirect, and potentially misleading, proxy for getting at ecological questions.
Morphology has been another vehicle for ecological comparisons (Van Valkenburgh 1985, 1988, 1991, 1994; Foote 1996b; Wainwright and Reilly 1994; Van Valkenburgh and Molnar 2002; Lockwood 2004). The general premise of ecomorphology is that morphology can be used as a proxy for the ecological characters of organisms. Such correspondence has been well supported (e.g., Winemiller 1991; Wainwright 1994). However, there seems little potential in using these methods for large-scale comparisons spanning phyla and long time scales because of the lack of appropriate homologous characters. The most ambitious comparisons include Paleozoic and Recent arthropods (Briggs et al. 1992; Wills et al. 1994; Stockmeyer Lofgren et al. 2003) and animal skeletons (Thomas and Reif 1993; Thomas et al. 2000). There are few homologous (and even functionally comparable) morphological characters shared throughout benthic communities composed of green algae, foraminifera, corals, trilobites, bryozoans, brachiopods, and bivalves. It is essential to focus such comparisons on ecological characters directly, instead of on their underlying morphology or their consequences for taxonomy.
It is important here to understand what I mean by the term ecological character. We can start with the understanding that each organism exhibits unique phenotypic features (sensu Bock and von Wahlert 1965) that affect environmental interactions. Collectively, these phenotypic features endow each organism with ecological capabilities or characters (faculties sensu Bock and von Wahlert 1965). For now, I will focus on those autecological characters related to feeding, use of space, mobility, dispersal, reproduction, and body size; taken together, these describe an organism's basic life habit. Ecological diversity, regarded as the overall variety of life habits within some group, can be most easily assessed by richness, the number of unique life habits in this group. It can also be assessed by ecological disparity, a measure of how different each life habit is from others in this group (modified from Foote 1993a). I propose below a common framework for such characters and formal definitions for ecological richness and disparity.
Focusing on such ecological characters directly has two benefits. First, it avoids the problems of homology associated with morphological comparisons. Because distinct phenotypes can perform identical functions in numerous ways (Bock and von Wahlert 1965; Alfaro et al. 2004, 2005; Wainwright et al. 2005; Marks and Lechowicz 2006), there exists in nature an innate tendency for ecological convergence when emergent capabilities are beneficial. In a sense, such higher-order capabilities are "screened off" (sensu Brandon 1984) from their underlying morphological and functional causes. These characters are accordingly more suitable for large- scale ecological comparisons. This may diminish, although not eliminate, the role of phylogenetic effects (Felsenstein 1985b; Harvey and Pagel 1991). Second, compared with analyses using the proxies of taxonomy or morphology alone, such a focus better aligns results with the theoretical understanding of ecological diversifications (Grant 1999; Schluter 2000; Coyne and Orr 2004).
Such benefits motivated the development of the guild concept. Originally focused on comparisons among taxa sharing diet and foraging habits (Root 1967), it was later modified to include other categories-microhabitat, locomotion, ecomorphology, timing of reproduction and daily activities, among others (Schoener 1974; Bambach 1983, 1985; Simberloff and Dayan 1991). Many studies have compared individual ecological characters over long time scales, including tiering (the stratification of infauna and epifauna; Thayer 1979, 1983; Ausich and Bottjer 1982; Bottjer and Ausich 1986; Droser and Bottjer 1989, 1993), insect feeding habits (Labandeira and Sepkoski 1993), energetic consumption (Vermeij 1999; Bambach 1993, 1999; Bambach et al. 2002), and body size (Smith et al. 2004), among others. Various individual characters related to escalation- chiefly carnivory, infaunality, and mobility-have been a recurrent focus (Vermeij 1977, 1987; Signor and Brett 1984; Kowalewski et al. 1998, 2006; Kosnik 2005; Madin et al. 2006; Aberhan et al. 2006).
The most ambitious multivariate guild attempt was conducted by Bambach (1983, 1985) in a series of studies comparing the ecology of Sepkoski's (1981) three evolutionary faunas. Using a three- dimensional framework defined by foraging habit, microhabitat, and mobility, he concluded that the timing of marine ecological diversification throughout the Phanerozoic was irregular and coincided with the diversification of successive evolutionary faunas, primarily resulting in increased utilization of previously vacant ecospace. These conclusions have withstood more recent analyses using broader ecological characters (Bambach et al. 2007; Bush et al. 2007). Bambach's framework has been influential (Aberhan 1994; Bottjer et al. 1996; Droser et al. 1997; Radenbaugh and McKinney 1998), but different qualitative frameworks also exist. For example, the Evolution of Terrestrial Ecosystems consortium (Behrensmeyer et al. 1992, 2003; especially Wing 1988; Wing and DiMichele 1992; Damuth et al. 1992) used a comprehensive framework for comparing terrestrial communities. Retallack (2004) also presented a framework focused on general ecological strategies. Although such approaches are well suited to identifying synoptic ecological trends, they primarily are limited to making descriptive, qualitative comparisons or statistical comparisons of isolated ecological characters. A synthetic quantitative framework, while also allowing such analyses, is preferable for several reasons. First, it facilitates more robust documentation of overall changes in ecospace utilization (Bambach 1983, 1985, 1993). This can benefit our understanding of the previously mentioned univariate trends because their causes are likely intricately related to other ecological characters that this method captures simultaneously. second, quantification makes it possible to determine the structural components of individuals occupying ecospace (Van Valen 1974). That is, it allows measurement of the central location, dispersion (disparity), and distribution of all individuals' life habits in the multidimensional space defined by the ecospace framework. Of equal importance, it allows recognition of those ecological regions that are not occupied by individuals-either currently or in the past. Finally, quantification fosters the development of mechanistic null models that can test both the robustness of observed trends and distinguish among their possible causes (McShea 1994. 1998; Foote 1996a; Ciampaglio et al. 2001; Pie and Weitz 2005). The proposed framework marks the first framework suitable for such large-scale, quantitative comparisons.
Such motivations drove the quantification of morphological disparity (Gould 1989, 1991; Briggs et al. 1992; Foote and Gould 1992; McShea 1993; Wills et al. 1994). Given the success of these approaches (Saunders and Swan 1984; Foote 1991a,b, 1992,1993a,b, 1994,1995, 1996a,b, 1999; Thomas and Reif 1993; Wagner 1995. 1997; Wills 1998, 2002; Lupia 1999; Smith and lieberman 1999; EbIe 2000; Thomas et al. 2000; Ciampaglio et al. 2001; Ciampaglio 2002; Harmon et al. 2003; Stockmeyer Lofgren et al. 2003; McClain et al. 2004; Villier and Korn 2004; Collar et al. 2005), quantification of ecological diversity seems to offer profound benefits.
In this study, I propose a general method for quantifying ecological diversity that unites an extended framework of Bambach (1983,1985) and the methodological advances of morphological disparity (see Foote 1991a; Wills 2002). The modified framework consists of 60 ecological character states that are universally applicable to extant or extinct organisms and that are logically independent of taxonomy; in this sense, the framework constitutes a theoretical ecospace. It allows quantification of ecological richness and disparity directly for any entity-individuals, lineages, or entire communities. The framework and the methods used in analyzing it are suitable for answering many questions in comparative paleoecology. Here it is used to compare the ecological diversity of Paleozoic (Cambrian through Devonian) and modern biotas from deep-subtidal, soft-substrate habitats in terms of ecological (life habit) richness, disparity, and overall distributions of life habit gradients in ordination-space.
Paleozoic and Modern Data Sets
The biotas used here represent assemblages from deep-subtidal, soft-substrate habitats. The Paleozoic biota comprises 449 samples compiled from 167 references, including nearly 80,000 individual fossils (an underestimate considering only one-quarter of samples have abundance data) and more than 3500 species ranging in age from Cambrian through Devonian (Novack-Gottshall 2004). The modern biota comprises 50 samples compiled from three references in the literature. Ten samples were selected at random from comparable habitats along the western North Atlanticfive samples from the Mid Atlantic Bight (Lynch et al. 1979) and five from the Beaufort Shelf (Day et al. 1971)-totaling more than 8000 individual organisms and 450 species from the Boreal Province on an outer continental shelf margin. Although these samples are from the same habitat as the Paleozoic samples, the temperate, oceanic shelf does not represent the same latitude as most Paleozoic samples. To account for this difference, 40 samples were also selected at random from appropriate habitats in the tropical, epeiric Gulf of Carpentaria (Australia) (Long et al. 1995), totaling more than 91,000 individuals and 400 species.
The Ecospace Framework
The life habits of the taxa in the biotas were operationalized by using the following standardized ecospace framework criteria. It is important to note that although the framework is well suited for comparing such marine biotas, it is equally well suited for characterizing the life habits of other ecological groups; the explanations that follow draw on examples from the full spectrum of life, both extinct and extant and representing most habitats.
Characters in the Framework.-The framework (Table 1; see also Appendix A online at http://dx.doi.org/10.1666/pbio06054.s1) includes 60 character states in 27 characters that describe the basic autecological capabilities of organisms. Characters include (1) resources, such as diet and microhabitat; (2) structures, behaviors, or other features related to the acquisition, maintenance, or defense of these resources, such as foraging, mobility, and substrate attachment; and (3) other important autecological characters, including body size, physiology, and reproduction. Depending on the scope of analysis, some researchers (especially macroecologists and paleobiologists) may be inclined to add geographic range, abundance, or other emergent (statistical, sensu Maurer 1999) group characters to this list (Peters 1983; Brown 1995; Gaston and Blackburn 1996; Maurer 1999). Adopting cladistic terminology, the term character refers to individual classes of ecological capabilities (faculties sensu Bock and von Wahlert 1965, whereas character state denotes the possible types of these capabilities (Swofford et al. 1996).
The characters were chosen according to four criteria. First, the characters must be ecologically important for living organisms. Habitat and dietary characters are given greater emphasis-that is, there are more characters-because of their recognized importance (Schoener 1974). Second, the characters must be logically independent of one another; that is, they refer to different components of life habits. This is a requirement of all theoretical multidimensional morphospaces (McGhee 1999) and even cladistics (Swofford et al. 1996). In reality, correlations may exist and can be investigated a posteriori, but the assumption here is that all character combinations are possible-even if never realized because of constraints (Seilacher 1970). Third, the characters must be assignable to ancient taxa, including long-extinct species with no living relatives or morphological analogues. Reliance on taxonomic information has been minimized by focusing on general-and consequently often convergent-ecological capabilities of organisms instead of on particular, often taxon-specific adaptations. Fourth, the individual states for each character must be fully subdivided. For example, a fluidic substrate (Table 1) is a valid substrate state because it represents a logical absence of a substrate, used by organisms that do not inhabit lithic or biotic substrates; see Appendix A for further examples.
TABLE 1. Twenty-seven characters (bold) and 60 states (numbered) in ecospace framework. Characters listed in parentheses are not easily determined for many fossil groups.
The ecospace framework does not include synecological characters, except when an organism's autecological characters necessarily imply some form of interaction. For example, carnivores are categorized only as meat eaters, and not with regard to their particular prey. In other words, character states referring to particular organisms- trilobite eaters, nectar eaters, and the like-were avoided because they limit comparisons to particular times when that dietary item was extant. This may limit the framework's utility for some comparisons, but it is a prerequisite if comparisons are to be made across wide taxonomical, morphological, and ecological ranges. Modifications of this framework are possible depending on the objectives of the study. A comparison spanning the history of life on Earth might find the character states carnivore, herbivore, and fungivore too restrictive; a replacement with chemoheterotroph might prove more useful.
Unlike the Skeleton Space (Thomas and Reif 1993; Thomas et al. 2000), this list is provisional and not intended to be fully inclusive. Although it is applied below to marine biotas, it is intended to characterize universally the significant autecological capabilities of all organisms in any habitat. Additional characters can be devised when such information is available or when a study requires them. Reproductive strategies, seasonality, daily cyclicity, food size, and numerous biogeochemical and physiological characters are important ecologically (Schoener 1974; Pianka 2000), but this information is not available for most fossil species, and so it is not included in the present treatment. Some possible candidates are listed here (Table 1 and Appendix A, in parentheses) with the hope they will be included in future comparisons. Similarly, it may sometimes be necessary to limit the number of characters and states if relevant information is not available. In the examples that follow, for instance, only 44 character states are used because of the current limitations of using fossilized species. Coding of Character States.-Unless noted, the term individuals in the following refers to individual ecological entities-individuals or species-whereas the term groups refers to more inclusive groups- communities and lineages. Most character states are binary, coded O for absent and 1 for present. Several characters-body size, microhabitat stratification and others-are coded as continuous, ordered, multistate characters by using integers (or fractions if de- weighting is preferred; Sneath and Sokal 1973; Van Valen 1974). Such multistate characters are used only when there is a clear ordination among their states. When a state cannot be confidently assigned or is unknown currently, it can be coded as unknown. Such codings, however, reflect only a lack of knowledge rather than nonrelevance; in principle, all states can be coded.
This method of coding, in which multistate characters are the exception, might seem to warrant further explanation. In most cladistics or morphological disparity studies, the characters are typically homologous, with each individual displaying a single phenotype. In contrast, individuals are more variable ecologically, marked by behavioral flexibility, generalism, and convergence with unrelated individuals (Peterson et al. 1999; Losos et al. 2003). This can be notably true for sexually dimorphic species (e.g., Pietsch 1976, 2005). The coding scheme used here accommodates such variability by allowing single individuals to be coded with multiple states in the same character. For example, semi-infaunal individuals, such as trees and some mussels, can be coded as living simultaneously above and within the sediment. (Other common ecological and behavioral capabilities best described by multiple character states for the same individual-hermaphroditism, parthenogenesis, substrate and microhabitat generalism, omnivory, among others-are discussed further in Appendix A.) In cases where individuals typically utilize a primary resource, even when capable of using others, only the primary resource is coded; this is the same method used to classify guilds (Root 1967). A limitation of such flexibility in coding is that every individual must exhibit at least one state for every character. In other words, no individual- while alive-lacks some diet, some microhabitat, or some body size. This has analytical consequences, namely that not every combination in the framework is possible.
Although individuals can undergo changes in their ecological characters throughout their life cycle-most notably due to metamorphosis or allometry-they are coded from the perspective of adult, sexually mature organisms, where ecological characters are usually most stable. Organisms with indeterminate growth are coded at the attainment of sexual maturity. Entire colonies are treated as individuals. Depending on the goals of a study, one could focus on each colony member individually, include individual genders or age or life stages separately, or code individuals within a population separately.
Some characters, such as absolute body size and microhabitat stratification, are scale-independent and coded according to absolute criteria. However, because the ecospace framework has an autecological focus, most characters are coded from the perspective of the individual organism (or colony). An example is an organism's immediate substrate, which may be rather different from the primary substrate of the focal habitat. Organisms that live cryptically within the cavities of coral reefs or endoparasitically within another organism may be both above substrates in a primary sense (i.e., situated above the sediment-water interface), but within substrates in an immediate sense (i.e., inhabiting a crevice or tissue). Because of this versatile perspective and the broad nature of the characters, the ecospace framework transcends the limitations of scaling: any ecological entity can be compared.
TABLE 2. Utility of ecospace for describing benthic microhabitats. If using just three characters (primary microhabitat, immediate microhabitat, and substrate) with several character states (in italics), it is possible to describe twelve unique microhabitat combinations. Although existing terminology exists for most combinations, the three characters are more succinct and more broadly applicable for describing them. Additional combinations are possible; for example, it is possible to occupy multiple states simultaneously. The same classification can be used for other focal habitats; in this example, the habitat is the benthic one with the sediment-water interface as the primary substrate. See text for further discussion. This ecospace framework allows the discovery of combinations that are unoccupied in nature, such as the microhabitat that is within the benthic sediment but above the water; although this may seem an unlikely life habit, it might be possible to imagine an organism that floats or flies in gas-filled chambers within a burrow network.
The Framework as a Theoretical Ecospace.-Ecological terms used in common classifications (e.g., Hunt 1925; Yonge 1928; Elton and Miller 1954; Turpaeva 1957; Jennings 1965; Walker 1972; Walker and Bambach 1974; West 1977; Bambach 1983; Merritt and Cummins 1996; Taylor and Wilson 2002) were used in the framework only when they were defined by a single character. For example, the common term deposit feeder was avoided because it conflates diet with feeding microhabitat, while implying aspects of mobility, resting microhabitat, foraging strategy, and sometimes even body size (Plante et al. 1990). The framework is versatile, however, in recognizing such common life habits through combinations of relevant states.
In this way, the framework reduces the number of ecological terms needed to describe different life habits. Consider, for example, the number of words describing microhabitats (Elton and Miller 1954; West 1977; Taylor and Wilson 2002). If the substrate of the focal habitat is the sediment-water interface, three independent characters alone-primary microhabitat, immediate microhabitat, and immediate substrate-describe a dozen microhabitats (Table 2). Epibenthic organisms live on lithic sediment above the sediment- water interface in both a primary and an immediate (i.e., at the scale of the organism) sense. Cryptobionts and some miners live above the primary substrate, but within a lithic immediate substrate. The various parasites, epibionts, borers, and nestlers have similar relationships to a biotic substrate. Additional character states can further partition each broad microhabitat, with other combinations also possible; for example, semi-infaunal bivalves live above and within the primary sediment simultaneously (Stanley 1970). The same framework accommodates terrestrial and oceanic microhabitats by changing the primary substrate of the focal habitat from sediment-water interface to ground or water's surface, respectively (see discussion of microhabitat characters in Appendix A).
TABLE 3. Example of ecospace framework coding. Taxa 1-5 are modern species and taxa 6-10 are Paleozoic species. Only 44 characters and states for which reliable information is available are used. The numbers and order of the character states follows that in Table 1 and Appendix A. For binary characters, a value of 1 designates the presence of an ecological character state. See Tables A1-6 for designation of multistate character states in characters 51- 55; when measuring disparity in the text, such states have been deweighted to range from 0 to 1.
TABLE 3. Example of ecospace framework coding. Taxa 1-5 are modern species and taxa 6-10 are Paleozoic species. Only 44 characters and states for which reliable information is available are used. The numbers and order of the character states follows that in Table 1 and Appendix A. For binary characters, a value of 1 designates the presence of an ecological character state. See Tables A1-6 for designation of multistate character states in characters 51- 55; when measuring disparity in the text, such states have been deweighted to range from 0 to 1.
This example demonstrates an additional feature of the framework: both realized and unrealized ecological combinations are noted a priori. For example, a microhabitat exists in Table 2 within the benthic sediment in a primary sense, but above water in an immediate sense. Although this may seem a logically impossible life habit, it is not. Imagine some organism that floats on the surface of-or perhaps flies in-gas-filled chambers in a submerged burrow network. Similarly unusual ecological habits and microhabitats are common in nature (Darwin 1875; Norell et al. 2001; Rubinoff and Haines 2005; Seilacher 2005).
The framework thus constitutes a theoretical ecospace, in the sense of a theoretical statespace defined by its character- dimensions. This is analogous to the term morphospace used by theoretical morphologists (Raup and Michelson 1965; Hickman 1993; Thomas and Reif 1993; Chapman et al. 1996; McGhee 1999; Thomas et al. 2000), with which they share similar methodological approaches and goals. The framework delineates, a priori, the domain of logically possible life habits that could be occupied by all organisms, and that is independent of the actual life habits occupied by organisms. When used in a comparative context, existing life habit complexes-such as deposit feeding-can emerge as outcomes of analyses comparing ecological entities (see below). With the exception noted above, the framework can be fully occupied, at least in theory. By being unconstrained by the life habits occupied by actual organisms, it also points toward life habits that have yet to evolve, that are biomechanically nonfunctional or evolutionarily unfit, or that are developmentally impossible (Raup and Michelson 1965; Seilacher 1970; McGhee 1999). Coding of Individual Organisms and Species.-The framework is equally suitable for coding extant and extinct individuals. For living species (such as those in the modern biota), inferences of basic autecological characters are straightforward, but not without some obstacles (Ricklefs and Miles 1994). Performance studies (e.g., Arnold 1983; Garland and Losos 1994; Wainwright 1994; Irschick 2002, 2003) have been used to great effect in determining how individual morphologies perform functionally. One important consequence of such studies is that the same function can be performed by multiple morphological designs (Alfaro et al. 2004, 2005; Wainwright et al. 2005); such convergence has been identified by using more general ecological characters as well (Marks and Lechowicz 2006). However, such formalized analyses are not usually necessary here because the framework characters are straightforward and often readily inferable (in much the same way as done by Marks and Lechowicz ).
For fossils (such as those in the Paleozoic biota), direct observation of ecological characters is rare but not impossible (Boucot 1990; see obrution deposits in Brett 1984,1990; Brett and Baird 1986). Barring direct evidence, ecological characters in fossils are inferred by biomechanical studies, analysis of environmental distribution, and comparison with relatives or living morphological analogues (Rudwick 1964; Stanley 1970; Alexander 1983, 1990; Hickman 1988; Plotnick and Baumiller 2000; Vogel 2003). Despite these varied sources, such inferences remain less powerful than those made with living individuals. Although specific procedures are not developed here, it is possible to test the sensitivity of results to such coding decisions (see Felsenstein 1985a; Foote 1993a). In cases where characters are unknown currently, states can be coded as unknown.
The life habits of all taxa in the databases were coded to the lowest taxonomic level-usually family or genus-for which reliable information was available. Coding decisions have been informed currently by 197 published references. Detailed examples of how two species-one extant and one extinct-were coded with the ecospace framework are found in Appendix B in the supplementary material (http://dx.doi.org/10.1666/pbio O6054.sl). Representative codings for ten arbitrarily selected extant and extinct species from the Paleozoic and modern biotas are reported in Table 3: the five extant species are the Ungulate brachiopod Glottidia pyramidata, bryozoan Bugula neritina, crab Cancer irroratus, isopod Cirolana polita, and snail Mitrella marquesa; the five extinct, Paleozoic species are the trilobite Isotelus tnaximus, putative trilobite Naraoia compacta, crinoid Calceocrinus chrysalis, mussel Modiolopsis versaillesensis, and rhynchonellate brachiopod Zygospim modesta.
The Quantification of Ecological Diversity
Ecological Diversity of Organisms and Species.-Because the character states in the ecospace framework are all theoretically independent, the entire ecospace contains more than 106 quintillion unique combinations (1.069 x 10^sup 19^) that are theoretically possible (given the previous exception that all individuals occupy some state in each character). Using just the 44 character states that are currently practical with fossils still yields nearly 300 trillion possible combinations (2.993 x 10^sup 14^).
Once coded, these unique combinations serve as a basic unit of ecological (life habit) diversity that is theoretically independent of taxonomy and morphology. Because they are coded quantitatively, they furthermore offer a rich arsenal for comparative paleoecology. As one example, it is possible to compare the life habits of species from Table 3 as a dendrogram (Fig. 1). Prior to calculating distances, multistate characters were deweighted so each maximum state was equal to 1 and the distances were divided by the square root of 44 character states so that pairwise distances could range from a value of 1 (when two species share no character states in common) to 0 (when the species occupy the same life habit).
Although separated by at least 500 Myr, the modern predatory gastropod Mitrella marquesa and the Cambrian putative trilobite Naraoia compacta can be seen to share the same life habit, defined by the ecospace framework (Table 3, Fig. 1). Such correspondence across 44 states is an important feature of this framework, allowing recognition of meaningful ecological similarities, even when the taxa share no such overarching similarities in body plan, morphology, skeleton, taxonomy, or temporal occurrence. This similarity, however, does not preclude other important distinctions in their specific niches. Speed of locomotion, size of prey, specific foraging strategies, and the like could all be different, but it is not possible to determine such distinctions for most fossil taxa. A virtue of this comparative approach is that it may point toward unanticipated ecological similarities or interactions among very distantly related taxa (see Brown and Davidson 1977; Janzen 1977; Reichman 1979) that can be tested with additional research.
FIGURE 1. Dendrogram of ecological distances between marine taxa in Table 3. Cluster analysis used function hclustO in R 2.3.1 (R Development Core Team 2006) with the UPGMA method and Euclidean distance. Distances were standardized to range from O to 1 by deweighting of multistate characters and by dividing distance by square root of number of character states.
Figure 1 reveals several other potentially unanticipated results. There are four life habits-represented by the Mitrella/'Naraoia pair, Cancer, Cirolana, and lsotelus-that are similar to each other in being habitually mobile, epifaunal predators. Glottidia and Modiolopsis represent two similar life habits, sharing facultatively mobile, infaunal, filter-feeding abilities; M. versaillensis is known also to nestle in arborescent bryozoans (Pojeta 1971). The three remaining habits-represented by Zygaspira, Bugula, and Calceocrinus-are also similar, sharing sedentary, epifaunal, filter- feeding abilities. Each of these three basic life habit groupings includes modern and Paleozoic taxa, a similarity that would be unlikely if comparisons were based on evolutionary distances, or on their proxies in taxonomy and morphology. The ecospace framework allows analyses to focus solely on ecological characters, and it allows recurrently evolved and complex suites of life habits- raptorial predators, sedentary filter feeders, and the like-to emerge as results of the analysis, rather than assuming such life habit complexes exist a priori. Similar methods can be extended to compare entire biotas, such as the Paleozoic and modern.
Ecological Diversity of Multispecies Assemblages and Clades.-The simplest measure of ecological diversity for comparing groups of taxa is ecological richness, defined here as the number of occupied combinations (life habits) in the framework. This is more direct than species richness (Magurran 1988) because it measures actual ecological variation instead of using the proxy of taxonomy (Tilman et al. 1997; Diz and Cabido 2001; Reich et al. 2004).
Another important component of ecological diversity is disparity, a measure of how different the life habits within a group are from one another. The ecospace framework can be used to measure the disparity of individuals within clades or multispecies assemblages (communities). Distance metrics-mean Euclidean distance, range, total variance, and the like (Sneath and Sokal 1973; Van Valen 1974; Foote 1991a; Ciampaglio et al. 2001; Wills 2002)-are most commonly used in the study of morphological disparity and can also be used here. For example, using mean Euclidean distance, the disparity of the modern "assemblage" (0.443, Table 3) is approximately the same as that of the Paleozoic "assemblage" (0.492). This method is used below for comparing entire biotas in the Paleozoic and modern.
At even larger scales, it is possible to use the ecospace framework to understand the macroevolutionary history and evolutionary paleoecology of entire lineages. An example is not provided here, but such an approach might allow novel ways to measure ecological diversity, and especially disparity, during evolutionary radiations (Stanley 1968; Valentine 1969, 1995) mass extinctions (Jablonski 1986a; Valentine and Jablonski 1986; Jablonski and Raup 1995), and post-extinction recoveries (Hansen 1988; Jablonski 1998), as well as address the impact of ecological diversity on genus-level longevity (Kammer et al. 1998; Miller and Foote 2003; Liow 2004), onshoreoffshore diversification (Jablonski et al. 1983; Sepkoski and Miller 1985; Westrop and Adrain 1998) and other macroevolutionary phenomena (Stanley 1979).
Comparative Paleoecology of the Marine Biosphere: Do Paleozoic and Modern Biotas Exhibit Different Levels of Ecological Diversity?
It is a long-held impression that modern communities are more diverse ecologically than those of the distant past (Hutchinson 1959: pp. 155-156; Valentine 1969; 1973; Vermeij 1977, 1987; Bambach 1983, 1985). The goal here is to use the quantitative ecospace framework proposed above to assess the overall similarity in ecospace occupation in two large biotic groups from a single, deep- subtidal, soft-substrate habitat. This was done by pooling individual genera (using a randomly selected species for each genus) in the Paleozoic (Cambrian-Devonian) database and comparing it to the pooled genera in the modern database.portant differences exist between the fossil and modern samples. For example, the modern ones are not fossilized and they were collected with benthic trawls and dredges. There are also many more Paleozoic samples, covering a much wider temporal duration. Although such differences limit absolute comparisons in ecological diversity (Foote 1992), standardizations used below provide a means to estimate the relative magnitude of ecological differences between Paleozoic and modern biotas. The impact of non-fossilizable organisms was evaluated by comparing the Paleozoic biota to untreated and taphonomically treated modern databases. All-Modern is the entire modern data set-including soft- bodied, fragile, and rarely fossilized taxa. The Taph-Modern treatment includes those genera-primarily mollusks, crustaceans, tubicolous and jawed polychaetes, echinoderms, and bryozoans-nearly always or only occasionally expected to yield fossil representatives (Schopf 1978; Sepkoski 1982, 2002; Kidwell 2001, 2002). First, the ecological diversity of groups is compared by using their ecological (life habit) richness: genus richness relationship based on 2000 bootstrapped iterations for each aggregate group sample. This rarefaction method (Sanders 1968; Hurlbert 1971; Bambach 1983; Foote 1992; Miller and Foote 1996; Gotelli and Colwell 2001) standardizes for differences in sample size both within samples-because all samples in each biota are combined-and between biotas, at least when observing differences between the shape of each resulting ecological richness/genus richness relationship. Error bars were calculated as the standard deviation of the distribution of means (Foote 1993b; Efron and Tibshirani 1993). Ecological disparity within each group was calculated as mean Euclidean distance after deweighting multistate characters and standardizing for number of character states. Significance of differences in richness and disparity was tested with 2000 bootstrap replicates (Efron and Tibshirani 1993). All tests are one-sided unless noted. All statistics and quantitative analyses used R 2.3.1 for Windows (R Development Core Team 2006).
Although the All-Modern biota has not been taphonomically treated, its ecological richness/genus richness relationship is only moderately above that for the Paleozoic biota (Fig. 2). This difference is not statistically significant at a standard richness of 400 genera (Fig. 3A; diff.^sub obs.^ = 13.40, diff.^sub crit.^ = 18.00, p = 1.005). This overall similarity is surprising because the fossil record filters out some life habits, differentially preserving ecologically similar taxa (Schopf 1978); this might greatly underestimate the richness of the original Paleozoic biota. The magnitude of such differences might be approximated by the reduced trend using the Taph-Modern treatment (Fig. 2), although the difference here is only marginally significant at a standard richness of 240 genera (diff.^sub obs^ = 13.47, diff.^sub crit^ = 14.00, p = 0.054). Measurement of ecological disparity offers a different result. Both when untreated and when taphonomically treated, the modern biota is significantly more disparate than the Paleozoic biota after standardizing for differences in genus richness (Fig. 3B; All-Modern at 400 genera: diff.^sub obs^ = 0.065, diff.^sub crit^ = 0.014, p
FIGURE 2. Ecological richness/genus richness relationship for modern and Paleozoic (Cambrian-Devonian) deep-subtidal, soft- substrate biotas. Ecological richness is defined as number of life habits. Each curve is a rarefaction (2000 bootstrap iterations) for all samples in the database, pooled by time and taphonomic treatment. Paleozoic includes all Cambrian-Devonian fossil taxa; AllModern includes all modern taxa, including unfossilizable ones; Taph-Modern includes modern taxa expected to leave a fossil record; see text for further explanation. Error bars are one standard deviation from the distribution of 2000 bootstrapped means. Inset graph highlights relationship where error bars overlap; error bars are removed to clarify relationships. see text for statistical tests.
It is increasingly well established (Vermeij 1977, 1987; Bambach 1983, 1985; Bambach et al. 2002; Aberhan et al. 2006; Kowalewski et al. 2006; Madin et al. 2006; Wagner et al. 2006) that the ecospace of modern biotas is rather different from those of Paleozoic biotas. This can also be examined here by using ordination to compare visually the distribution of genus life habits in these biotas. As a nonparametric ordination method, nonmetric multidimensional scaling (NMDS) is appropriate because the ecospace character states are categorical. Furthermore, NMDS is a robust and well-substantiated ordination method (Kenkel and Orloci 1986; Faith et al. 1987; Minchin 1987), especially when resulting gradients are short, as is the case here because all ecospace states have a maximum distance of one unit, after deweighting. Metric ordination techniques resulted in nearly identical patterns despite vast algorithmic differences in methodology; the Procrustes sum of squares difference using principal components analysis was just 0.0000015 (p
FIGURE 3. Ecological richness and disparity of modern and Paleozoic (Cambrian-Devonian) deep-subtidal, softsubstrate biotas. Modern communities include all taxa, including soft-bodied ones unlikely to be fossilized. Distributions produced from 2000 bootstrap iterations at constant genus richness of 400 genera. A, Ecological richness (life habit richness). Although modern communities contain slightly more numbers of life habits, the difference is not significant (diff.^sub obs^, = 13.40, diff.^sub crit^ = 18.000, p = 1.005), based on 2000 bootstrap iterations. B, Ecological disparity (mean Euclidean distance). Modern communities are significantly more disparate than Paleozoic ones (diff.^sub obs^ = 0.065, diff.^sub crit^ = 0.014, p
FIGURE 4. Graphical ordination ecospace for genus life habits in modern and Paleozoic (Cambrian-Devonian) deep-subtidal, soft- substrate biotas. Figure shows two axes from ordination of life habits coded with the ecospace framework. Nonmetric multidimensional scaling was conducted using function isoMDSQ in R 2.3.1 (R Development Core Team 2006) with Euclidean distance. To avoid computational errors associated with species with identical life habits, the distance between such species pairs was made equal to one-half of the minimum observed distance between any other species pairs (see function metaMDS() in the vegan library; Oksanen 2006). There are 1376 Paleozoic taxa and 423 modern ones. Many points overlap-that is, taxa share identical life habits-but this overlapping does not obscure the graphical comparison because of the few life habits shared between the Paleozoic and modern biotas
The overall distribution of Paleozoic and All-Modern life habits is broadly similar in multivariate space (Fig. 4). Many points overlap in this ordination-that is, the taxa share identical life habits-but this overlapping does not obscure the graphical comparison because, as noted below, there are few life habits shared in common between the Paleozoic and modern biotas. To aid interpretation of axes using widely known taxa, Figure 5 demonstrates just the molluscan fraction of these biotas at the class level. In this two-dimensional, graphical ecospace, both axes represent gradients in suites of life habit combinations broadly interpretable as foraging strategies. High values along axis 1 are associated with taxa with sedentary, particle-feeding, filter- feeding strategies living attached to hard substrates, whereas those with low values are associated with free-living, habitually mobile, carnivorous, bulk-feeding raptors (see Appendix A for definition and discussion of ecospace states). High values along axis 2 are associated with intermittently mobile, microbivorous, particle- feeding mass feeders whose food source is located within primary and immediate substrates; low values are associated with carnivorous, bulk-feeding raptors with epibenthic food sources.
FIGURE 5. Graphical ordination ecospace for modern and Paleozoic (Cambrian-Devonian) mollusks only. Ordination is same as for Figure 4. Labels identify the major bivalve, cephalopod, and gastropod classes by first initial. Other classes are represented by symbols in Figure 4. There are 172 Paleozoic taxa and 114 modern ones, and the same circumstances for overlapping points apply as in Figure 4.
Taken together, these gradients delineate a rich variety of unique life habits. The broadly triangular distributions in Figures 4 and 5 provide end-members for each of the archetypal life habit complexes: sedentary, epifaunal filter feeders are found in the lower-right corner; intermittently mobile, infaunal, deposit feeders in the central apex; and mobile, epifaunal and swimming predators in the lower left. However, the gradients also accommodate those life habits that are intermediate between these extremes. For example, corals-those chimerically flower-like microcarnivores that have confounded categorization since Aristotle (Holland 2004)-cluster at the bottom center of the distribution (Fig. 4) because of their bulk- feeding carnivory, their filter-feeding foraging habit, and their sedentary, attached, epifaunal microhabitat.
A more complex gradient, apparent along the upper right side of the distributions seen in both Figures 4 and 5, describes the vast spectrum of particle-feeding microbivores. Using examples of modern molluscan genera (Fig. 5), this gradient delineates infaunal deposit feeders (such as nuculoid Ennucula and gastropod Turritella) at the apex through a region of siphonate deposit feeders (such as TelUna), mobile infaunal filter feeders (Cyclocardia and Cultellus), attached infaunal filter feeders (Cucullaea), and ends on the lower-right side with attached epifaunal filter feeders (such as semi-infaunal pterioid Pinna, adhesive gastropod Crucibulum, and ending with attached pterioid Anomia). Similarly, the gradient along the left side of this triangle delineates a mobility and predation spectrum dominated by gastropods, with intermittently mobile microbivores Strombus and Xenophora intersecting the particle-feeding gradient, continuing through facultatively mobile, attachment-feeding (and sometimes solution-feeding) carnivores and ectoparasites (Volva, Eulimella, and Epitonium), and ending at the lower-right corner with archetypal habitually mobile predators (such as Murex and cuttlefish Sepia). The predatory bivalve Cuspidaria also plots in this region. Similar gradient interpretations and the recognition of taxonomic overlap in life habits can also be observed in Figure 4. The same interpretations result when restricting analysis to the Taph-Modern treatment. Such categorically subtle but biologically real distinctions among life habits are not captured in most traditional ecospace frameworks (cf. Bambach 1983, 1985; Bambach et al. 2007; Bush et al. 2007). An important property of this ecospace framework is that it can make such rich and sometimes subtle life habit distinctions while still permitting the recognition of life habit convergence in unrelated taxa. Despite the broad overlap in the distributions of Paleozoic and modern life habits, important differences remain. For example, although the entire modern biota is composed of 230 distinct life habits and the Paleozoic of 287, only 17 are shared, and seven result from taxa whose life habits could not be coded completely, such as "sponge indet." Such differences are expected given that modern biotas are enriched in predatory, mobile, and infaunal life habits compared to Paleozoic biotas (Vermeij 1977, 1987; Thayer 1979, 1983; Barnbach 1983,1985; Bambach et al. 2002; NovackGottshall and McShea 2003; Aberhan et al. 2006; Kowalewski et al. 2006; Madin et al. 2006; Wagner et al. 2006; Bambach et al. 2007; Bush et al. 2007). This can be substantiated by comparing the distributions of occupied states. The two biotas are significantly different in the occupation of half of the 44 character states (Table 4; Mann-Whitney two-sided tests, total alpha = 0.05 after Bonferroni correction; but see warnings of reduced power [Underwood 1997]); this reduces to 15 significant differences when the Taph-Modern biota is used.
Compared with the Paleozoic biota, TaphModern is enriched in taxa whose life habits are mobile (although there is no difference among habitually mobile habits), are infaunal (in terms of both primary and immediate microhabitat), exploit other organisms (or structures) to occupy their specific microhabitat, live and feed on food that is further away from the sediment-water interface (either infaunalIy or epifaunally), are carnivorous, are feeding on dissolved food (frequently as parasites) or intact food, and forage by attaching to or taking in large quantities of food sources. Of these significant differences, only solutionand attachment-feeding should be viewed with caution because parasitism is sometimes difficult to identify in the fossil record. Because the comparisons are made among inhabitants of the same deep-subtidal, soft-substrate habitat, perhaps it is not surprising that characters related to substrate relationships (states 16-21) and the sources of food (states 30-33) are generally similar. Particulate, microbial diets (states 35 and 41) are the most common manner in which food is eaten in both biotas, but the manner in which this food is acquired is distinct, with Paleozoic taxa using filters and modern ones feeding en masse. Most of these differences are maintained with the All-Modern biota (Table 4), although several additional ones emerge.
Because these differences relate to many of the same general foraging characters defining the gradients in Figure 4, it should be expected that the distributions, despite much overlap, are distinct. Indeed, the Paleozoic biota has significantly greater values along the first axis than both All-Modern and Taph-Modern, marking a general shift from sedentary, epifaunal filter feeders to mobile predators (Mann-Whitney one-sided test, All-Modern: p
TABLE 4. Comparison of ecospace character-state occupation among Paleozoic and modern biotas. Mann-Whitney U-test used for comparing state distributions. Statistically significant differences after Bonferroni correction (p
Such differences between the Paleozoic and modem biotas can be due to several causes that the current analysis does not yet resolve. For example, it might be that such differences are the result of the combined accumulation of Paleozoic and modern samples spanning large geographic and temporal ranges. Finer geographic and temporal comparisons might reveal greater similarities (or differences) between modern and Paleozoic assemblages when restricted to certain regions or time intervals. Such temporal variation has been reported (Novack-Gottshall 2004; Madin et al. 2006; Bambach et al. 2007) during the Paleozoic interval considered here, especially from the Cambrian through Ordovician when many carnivorous habits were replaced by filter-feeding ones. The current method facilitates such finer-scale comparisons to be made quantitatively, even when there are no genera and but one family- the ubiquitous inarticulated brachiopod Lingulidae-shared in common among the ecological entities being compared.
Conclusions and Prospects
The composition of life has changed dramatically during its history (Valentine 1969, 1973; Bambach 1983, 1985; Vermeij 1987), and documenting this change and its ecological and evolutionary consequences remains an important goal. However, traditional methods to investigate these changes have been hindered by their focus on taxonomical or morphological comparisons alone. By focusing on ecological characters directly, the theoretical ecospace framework presented above serves as an important complement to these approaches.
When applied to deep-subtidal, soft-substrate Paleozoic (Cambrian- Devonian) and modern biotas, the framework describes a wide spectrum of important life habits observed in modern and ancient marine biotas. It does so in a standardized and taxon-free (sensu Wing 1988; Damuth et al. 1992) manner that is amenable to comparative analyses of ecological diversity using techniques previously used for morphological disparity. Although the comparison is a broad one, it suggests that the life habits in modern biotas are more ecologically disparate from one another, on average, than were those in the Paleozoic, although both biotas shared generally similar numbers of life habits per genus. The distribution of these life habits overlaps broadly in ordination space, although the modern biota is enriched in carnivorous, actively mobile, and infaunal life habits, among others.
Because the ecospace framework ultimately is coded from the perspective of the individual organism, the framework is suitable for comparing ecological entities existing at extraordinarily different scales or living in different focal habitats. For example, it would be a simple task to compare the biota of the Southern Appalachian ecosystem (Hackney et al. 1992; Martin et al. 1993a,b) to that of a single lake or stream (Hutchinson 1965; Merritt and Cummings 1996; Benz and Collins 1998), interstitial benthic community (i.e., those living between grains of sand; Fenchel 1978), or even the gut fauna of a single individual (Hungate 1975; Plante et al. 1990). Despite major differences in spatial resolution and habitat diversity between these scales, there might be important similarities in terms of their structural organization.
But one might predict major differences between constituent organisms as well, primarily because of the influence of size on an individual's ecological capabilities (Peters 1983; Schmidt-Nielsen 1984; Bonner 2006). For example, to a first approximation, size determines whether the basic functions of life are governed by viscous or inertial forces (Vogel 1994, 2003). For many small organisms-such as agnostid trilobites (Muller and Walossek 1987) and copepods-their spinose or filamentous appendages function more like paddles than rakes (Koehl 1981; Koehl and Strickler 1981), making them bona fide raptors (sensu Appendix A) for their sizes (Vogel 1994). When found in much larger organisms, the same structures function very differently. Size should provide a dominant influence on the ecological constraints of organisms and the manner in which different organisms occupy ecospace.
At the largest scale, the ecospace framework offers a means to study the extent to which life-in its enormity-has occupied ecospace (cf. Thomas and Reif 1993). Little attention has been paid to assessing the prodigious ecological varieties exhibited by organisms in this general, theoretical sense (McGhee 1999). Elementary-and essentially unanswered-questions abound. How extensively occupied is ecospace currently, and what degree of lability (sensu Losos et al. 2003) has it exhibited through time (Bambach et al. 2007)? To what degree is this occupation governed by convergent adaptation (Van Valen 1978; Moore and Willmer 1997; Losos et al. 1998; Vermeij and Lindberg 2000; Stayton 2006) and constraints of various kinds (Seilacher 1970; McPeek 2000)? How quickly and to what extent was ecospace filled during the Cambrian radiation and following the Late Permian mass extinction (Valentine 1969, 1995; Erwin et al. 1987; Droser et al. 1997)? Do mechanical constraints of anatomical design result in reduced levels of ecospace filling within terrestrial communities compared to marine ones (Thomas and Reif 1993)? Do equivalent taxonomic ranks-kingdoms, phyla, and classes-occupy similar levels of ecological diversity (Valentine 1969, 1980; Van Valen 1973; Valentine et al. 1991)? Such ideas deserve greater attention because they can point toward important, unrecognized explanations of evolutionary history. Acknowledgments
I thank D. W. McShea, A. I. Miller, S. E. Novack-Gottshall, R. E. Chapman, C. N. Ciampaglio, D. H. Erwin, M. A. Kosnik, J. D. Marcot, D. L. Meyer, V. L. Roth, W. Wilson, G. A. Wray, and S. Vogel for valuable discussion, support, and inspiration at various stages of development, some long-ago. I. R. Poiner and M. Haywood of the Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) Marine and Atmospheric Research graciously offered unpublished data on the benthos of the Gulf of Carpentaria, Australia. This paper was strengthened by reviews from M. E. Alfaro, T. K. Baumiller, A. M. Bush, D. H. Erwin, M. Foote, J. B. Losos, and four anonymous reviewers. This study is based, in part, on a portion of my Ph.D. dissertation at Duke University.
Aberhan, M. 1994. Guild-structure and evolution of Mesozoic benthic shelf communities. Palaios 9:516-545.
Aberhan, M., W. Kiessling, and E T. Fursich. 2006. Testing the role of biological interactions in the evolution of mid-Mesozoic marine benthic ecosystems. Paleobiology 32:259-277.
Alexander, R. M. 1983. Animal mechanics. Blackwell Scientific, Boston.
_____. 1990. Dynamics of dinosaurs. Columbia University Press, New York.
Alfaro, M. E., D. I. Bolnick, and P. C. Wainwright. 2004. Evolutionary dynamics of complex biomechanical systems: an example using the four-bar mechanism. Evolution 58:495-503.
_____. 2005. Evolutionary consequences of many-to-one mapping of jaw morphology to mechanics in labrid fishes. American Naturalist 165:E140-E154.
Arnold, S. J. 1983. Morphology, performance and fitness. American Zoologist 23:347-361.
Ausich, W. I., and D. J. Bottjer. 1982. Tiering in suspension feeding communities on soft substrata throughout the Phanerozoic. Science 216:173-174.
Bambach, R. K. 1983. Ecospace utilization and guilds in marine communities through the Phanerozoic. Pp. 719-746 in M. J. S. Tevesz and P. L. McCaIl, eds. Biotic interactions in recent and fossil benthic communities. Plenum, New York.
_____. 1985. Classes and adaptive variety: the ecology of diversification in marine faunas through the Phanerozoic. Pp. 191- 253 in J. W. Valentine, ed. Phanerozoic diversity patterns: profiles in macroevolution. Princeton University Press, Princeton, N.J.
_____. 1993. Seafood through time: changes in biomass, energetics, and productivity in the marine ecosystem. Paleobiology 19:372-397.
_____. 1999. Energetics in the global marine fauna: a connection between terrestrial diversification and change in the marine biosphere. Geobios 32:131-144.
Bambach R. K., A. H. Knoll, and J. J. Sepkoski Jr. 2002. Anatomical and ecological constraints on Phanerozoic animal diversity in the marine realm. Proceedings of the National Academy of Sciences USA 99:6854-6859.
Bambach R. K., A. M. Bush, and D. H. Erwin. 2007. Autecology and the filling of ecospace: key metazoan radiations. Palaeontology 50:1- 22.
Behrensmeyer, A. K., J. D. Damuth, W. A. DiMichele, R. Potts, H.- D. Sues, and S. L. Wing, eds. 1992. Terrestrial ecosystems through time: evolutionary paleoecology of terrestrial plants and animals. University of Chicago Press, Chicago.
Behrensmeyer, A. K., C. T. Stayton, and R. E. Chapman. 2003. Taphonomy and ecology of modern avifaunal remains from Amboseli Park, Kenya. Paleobiology 29:52-70.
Benz, G. W., and D. E. Collins, eds. 1998. Aquatic fauna in peril: the southeastern perspective. Southeast Aquatic Research Institute Special Publication 1. Lenz Design and Communications, Decatur, Ga.
Bock, W. J. and G. von Wahlert. 1965. Adaptation and the formfunction complex. Evolution 19:269-299.
Bonner, J. T. 2006. Why size matters: from bacteria to blue whales. Princeton University Press, Princeton, N.J.
Bottjer, D. J., and W. I. Ausich. 1986. Phanerozoic development of tiering in soft substrata suspension-feeding communities. Paleobiology 12:400-420.
Bottjer, D. J., J. K. Schubert, and M. L. Droser. 1996. Comparative evolutionary ecology: assessing the changing ecology of the past, in M. B. Hart, ed. Biotic recovery from mass extinction events. Geological Society of London Special Publication 102: 1-13.
Boucot, A. J. 1990. Evolutionary paleobiology of behavior and coevolution. Elsevier, New York.
Brandon, R. 1984. The levels of selection. Pp. 133-141 in R. Brandon and R. Burian, eds. Genes, organisms, populations: controversies over the units of selection. MIT Press, Cambridge.
Bretsky, P. W. 1968. Evolution of Paleozoic marine invertebrate communities. Science 159:1231-1233.
Brett, C. E. 1984. Autecology of Silurian pelmatozoan echinoderms. In M. G. Bassett and J. D. Lawson, eds. Autecology of Silurian organisms. Special Papers in Palaeontology 32:87-120.
_____. 1990. Obrution deposits. Pp. 239-243 in D. E. G. Briggs and P. R. Crowther, eds. Palaeobiology: a synthesis. Blackwell Scientific, London.
Brett, C. E., and G. C. Baird. 1986. Comparative taphonomy: a key to paleoenvironmental interpretation based on fossil preservation. Palaios 1:207-227.
Briggs, D. E. G., R. A. Fortey, and M. A. Wills. 1992. Morphological disparity in the Cambrian. Science 256:1670-1673.
Brown, J. H. 1995. Macroecology. University of Chicago Press, Chicago.
Brown, J. H., and D. W. Davidson. 1977. Competition between seed- eating rodents and ants in desert ecosystems. Science 196:880-882.
Bush, A. M., R. K. Bambach, and G. M. Daley. 2007. Changes in theoretical ecospace utilization in m