Investigating Biotic Interactions in Deep Time
Authors: Danielle Fraser, Laura C. Soul, Anikó B. Tóth, Meghan A. Balk, Jussi T. Eronen, Silvia Pineda-Munoz, Alexandria B. Shupinski, Amelia Villaseñor, W. Andrew Barr, Anna K. Behrensmeyer, Andrew Du, J. Tyler Faith, Nicholas J. Gotelli, Gary R. Graves, Advait M. Jukar, Cindy V. Looy, Joshua H. Miller, Richard Potts, S. Kathleen Lyons
Journal: Trends in Ecology & Evolution (2020)

Challenging the widespread perspective that long-term diversity patterns are shaped primarily by climate is not possible without using fossil record data to understand the role of biotic interactions.Important recent development and application of models that utilize data of both living and extinct species have enabled analyses to move beyond simply excluding potential abiotic drivers to explicitly modeling biotic drivers for the first time.Analyses of paleontological data show that biotic interactions shape the temporal diversity trajectories and rates of origination and extinction for numerous taxa.Extinction of keystone species has disproportionate impacts on biotic interactions among surviving species.Recovery from extinction events can be sped up or slowed down by biotic interactions among surviving species.Historically, humans (Homo sapiens) have acted as large, generalist predators, disrupting interaction networks among non-human species. Recent renewed interest in using fossil data to understand how biotic interactions have shaped the evolution of life is challenging the widely held assumption that long-term climate changes are the primary drivers of biodiversity change. New approaches go beyond traditional richness and co-occurrence studies to explicitly model biotic interactions using data on fossil and modern biodiversity. Important developments in three primary areas of research include analysis of (i) macroevolutionary rates, (ii) the impacts of and recovery from extinction events, and (iii) how humans (Homo sapiens) affected interactions among non-human species. We present multiple lines of evidence for an important and measurable role of biotic interactions in shaping the evolution of communities and lineages on long timescales. Recent renewed interest in using fossil data to understand how biotic interactions have shaped the evolution of life is challenging the widely held assumption that long-term climate changes are the primary drivers of biodiversity change. New approaches go beyond traditional richness and co-occurrence studies to explicitly model biotic interactions using data on fossil and modern biodiversity. Important developments in three primary areas of research include analysis of (i) macroevolutionary rates, (ii) the impacts of and recovery from extinction events, and (iii) how humans (Homo sapiens) affected interactions among non-human species. We present multiple lines of evidence for an important and measurable role of biotic interactions in shaping the evolution of communities and lineages on long timescales. Biotic interactions occur when organisms living in the same community directly or indirectly influence one another. Biotic interactions can occur within or among species, be positive or negative, and cover a wide range of interactions including predation, commensalism, mutualism, resource competition, and parasitism [1.Pringle E.G. Orienting the interaction compass: resource availability as a major driver of context dependence.PLoS Biol. 2016; 14e2000891Crossref PubMed Scopus (4) Google Scholar]. Biotic interactions play an important role in structuring modern communities (e.g., [2.Rabosky D.L. Hurlbert A.H. Species richness at continental scales is dominated by ecological limits.Am. Nat. 2015; 185: 572-583Crossref PubMed Scopus (151) Google Scholar]). Understanding their importance in the past therefore has the potential to shed light on their role in shaping ancient and recent diversity patterns. Historically, however, the study of biotic interactions in the fossil record has largely focused on direct physical evidence of interactions such as bore holes in shells, plant damage by insects, patterns of bryozoan encrustation, rare occurrences of gut contents, and carnivore damage on bones (e.g., [3.Collareta A. et al.Did the giant extinct shark Carcharocles megalodon target small prey? Bite marks on marine mammal remains from the late Miocene of Peru.Palaeogeogr. Palaeoclimatol. Palaeoecol. 2017; 469: 84-91Crossref Scopus (53) Google Scholar,4.Maccracken S.A. Labandeira C.C. The Middle Permian south ash pasture assemblage of north-central Texas: coniferophyte and gigantopterid herbivory and longer-term herbivory trends.Int. J. Plant Sci. 2020; 181: 342-362Crossref Scopus (14) Google Scholar]). Analysis of unusually well-preserved fossil assemblages allows reconstruction of trophic relationships among diverse organisms (e.g., [5.Roopnarine P.D. Angielczyk K.D. Community stability and selective extinction during the Permian-Triassic mass extinction.Science. 2015; 350: 90-93Crossref PubMed Scopus (46) Google Scholar]) and earlier work documented long-term trends in ecospace (see Glossary) occupation [6.Bambach R.K. Ecospace utilization and guilds in marine communities through the Phanerozoic.in: Biotic Interactions in Recent and Fossil Benthic Communities. Springer, 1983: 719-746Crossref Scopus (219) Google Scholar]. However, temporally continuous evidence for biotic interactions (traditionally thought to structure biodiversity on only very limited spatiotemporal scales [7.Jablonski D. Biotic interactions and macroevolution: extensions and mismatches across scales and levels.Evolution. 2008; 62: 715-739Crossref PubMed Scopus (172) Google Scholar]) with appropriate temporal resolution (i.e., high-resolution stratigraphic sequences) is only rarely preserved. Consequently, paleontologists have focused primarily on the more accessible long-term trends in climate as important regulators of biodiversity and the differential success of species (e.g., [8.Fritz S.A. et al.Twenty-million-year relationship between mammalian diversity and primary productivity.Proc. Natl. Acad. Sci. U.S.A. 2016; 113: 10908-10913Crossref PubMed Scopus (29) Google Scholar]); only short-term ecological phenomena or long-term patterns that cannot be explained by climate have typically been attributed to the outcome of biotic interactions (e.g., [9.Bibi F. Kiessling W. Continuous evolutionary change in Plio-Pleistocene mammals of eastern Africa.Proc. Natl. Acad. Sci. U.S.A. 2015; 112: 10623-10628Crossref PubMed Scopus (41) Google Scholar], but see [6.Bambach R.K. Ecospace utilization and guilds in marine communities through the Phanerozoic.in: Biotic Interactions in Recent and Fossil Benthic Communities. Springer, 1983: 719-746Crossref Scopus (219) Google Scholar]). However, as the only source of sufficiently long-term data, and in light of several recent methodological advances, the fossil record is now uniquely positioned to answer many of the questions at the core of the evolutionary and ecological sciences. Herein, we address important recent advances in understanding the role of biotic interactions in shaping macroevolutionary and macroecological phenomena in the fossil record (Figure 1) and highlight areas of future research we believe will be illuminating. In this review, we exclude studies of physical evidence for interactions, except where they are used to contextualize large-scale biodiversity patterns. Interactions among individuals operate on timescales shorter than the typical temporal resolution of the fossil record (i.e., thousands to millions of years). The effects of biotic interactions do not scale up from individuals to species and clades in straightforward ways, but result from a multitude of interactions occurring among large assemblages of individuals, some of which may have opposing or multiplicative outcomes [7.Jablonski D. Biotic interactions and macroevolution: extensions and mismatches across scales and levels.Evolution. 2008; 62: 715-739Crossref PubMed Scopus (172) Google Scholar,10.Hembry D.H. Weber M.G. Ecological interactions and macroevolution: a new field with old roots.Annu. Rev. Ecol. Evol. Syst. 2020; 51 (https://doi.org/10.1146/annurev-ecolsys-011720-121505)Crossref Scopus (14) Google Scholar]. However, if interspecific and intraspecific interactions impact the ecological and reproductive success of individuals over large spatiotemporal scales, they can have effects on entire species and clades that are measurable on macroevolutionary and macroecological scales (Box 1 and Figure 1) [7.Jablonski D. Biotic interactions and macroevolution: extensions and mismatches across scales and levels.Evolution. 2008; 62: 715-739Crossref PubMed Scopus (172) Google Scholar,11.Marshall C.R. Quental T.B. The uncertain role of diversity dependence in species diversification and the need to incorporate time-varying carrying capacities.Philos. Trans. R. Soc. B. 2016; 37120150217Crossref PubMed Scopus (48) Google Scholar, 12.Sepkoski J.J.J. Competition in macroevolution: The double wedge revisited.in: Jablonski D. Evolutionary Paleobiology. The University of Chicago Press, 1996: 211-255Google Scholar, 13.Van Valen L.M. A new evolutionary law.Evol. Theor. 1973; 1: 1-30Google Scholar]. Such emergent patterns include, but are not limited to, shifts in species abundances, diversity, and spatial distributions (e.g., [14.Tomašových A. et al.Nonlinear thermal gradients shape broad-scale patterns in geographic range size and can reverse rapoport's rule.Glob. Ecol. Biogeogr. 2015; 24: 157-167Crossref Scopus (43) Google Scholar, 15.Pardi M.I. Smith F.A. Biotic responses of canids to the terminal pleistocene megafauna extinction.Ecography. 2016; 39: 141-151Crossref Scopus (16) Google Scholar, 16.Ezcurra M.D. Butler R.J. The rise of the ruling reptiles and ecosystem recovery from the Permo-Triassic mass extinction.Proc. R. Soc. B. 2018; 285: 20180361Crossref PubMed Scopus (49) Google Scholar]), partitioning of trait and phylogenetic space (e.g., [17.Fraser D. Lyons S.K. Mammal community structure through the Paleocene-Eocene thermal maximum.Am. Nat. 2020; 196: 1-20Crossref PubMed Scopus (3) Google Scholar,18.Chen M. et al.Assembly of modern mammal community structure driven by late cretaceous dental evolution, rise of flowering plants, and dinosaur demise.Proc. Natl. Acad. Sci. U.S.A. 2019; 116: 9931-9940Crossref PubMed Scopus (14) Google Scholar]), change in rates of diversification and morphological change (e.g., [19.Slater G.J. Iterative adaptive radiations of fossil canids show no evidence for diversity-dependent trait evolution.Proc. Natl. Acad. Sci. U.S.A. 2015; : 201403666Google Scholar, 20.Cantalapiedra J.L. et al.Decoupled ecomorphological evolution and diversification in neogene-quaternary horses.Science. 2017; 355: 627-630Crossref PubMed Scopus (51) Google Scholar, 21.Foote M. et al.Diversity-dependent evolutionary rates in early Palaeozoic zooplankton.Proc. R. Soc. B. 2018; 285: 20180122Crossref PubMed Scopus (15) Google Scholar, 22.Vermeij G.J. Power, competition, and the nature of history.Paleobiology. 2019; 45: 517-530Crossref Google Scholar, 23.Liow L.H. et al.Ecological interactions on macroevolutionary time scales: clams and brachiopods are more than ships that pass in the night.Ecol. Lett. 2015; 18: 1030-1039Crossref PubMed Scopus (66) Google Scholar]), and the success or failure of biological invasion (e.g., [20.Cantalapiedra J.L. et al.Decoupled ecomorphological evolution and diversification in neogene-quaternary horses.Science. 2017; 355: 627-630Crossref PubMed Scopus (51) Google Scholar,24.Pires M.M. et al.Continental faunal exchange and the asymmetrical radiation of carnivores.Proc. R. Soc. B. 2015; 282: 20151952Crossref PubMed Scopus (22) Google Scholar,25.Stigall A.L. et al.Biotic immigration events, speciation, and the accumulation of biodiversity in the fossil record.Glob. Planet. Chang. 2017; 148: 242-257Crossref Scopus (39) Google Scholar]). Although a significant body of theory has been developed to address the cumulative effects of biotic interactions (Box 1; [7.Jablonski D. Biotic interactions and macroevolution: extensions and mismatches across scales and levels.Evolution. 2008; 62: 715-739Crossref PubMed Scopus (172) Google Scholar,11.Marshall C.R. Quental T.B. The uncertain role of diversity dependence in species diversification and the need to incorporate time-varying carrying capacities.Philos. Trans. R. Soc. B. 2016; 37120150217Crossref PubMed Scopus (48) Google Scholar,12.Sepkoski J.J.J. Competition in macroevolution: The double wedge revisited.in: Jablonski D. Evolutionary Paleobiology. The University of Chicago Press, 1996: 211-255Google Scholar,26.Voje K.L. et al.The role of biotic forces in driving macroevolution: beyond the red queen.Proc. R. Soc. B. 2015; 282: 20150186Crossref PubMed Scopus (63) Google Scholar, 27.Barraclough T.G. How do species interactions affect evolutionary dynamics across whole communities?.Annu. Rev. Ecol. Evol. Syst. 2015; 46: 25-48Crossref Scopus (80) Google Scholar, 28.MacArthur R.H. Wilson E.O. An equilibrium theory of insular zoogeography.Evolution. 1963; 17: 373-387Crossref Google Scholar, 29.MacArthur R. Wilson E.O. The Theory of Island Biogeography. Princeton University Press, 1967Google Scholar]), empirical tests of models that account for the complexity of paleontological data have lagged behind theory.Box 1A Summary of the Basis for Attributing of Macroevolutionary and Macroecological Patterns to Biotic Interactions.Theory of Island BiogeographyThe Theory of Island Biogeography (TIB; [28.MacArthur R.H. Wilson E.O. An equilibrium theory of insular zoogeography.Evolution. 1963; 17: 373-387Crossref Google Scholar,29.MacArthur R. Wilson E.O. The Theory of Island Biogeography. Princeton University Press, 1967Google Scholar]) proposed ecological rules governing species richness and macroevolution on islands. TIB has been extended to explain continental macroecological and temporal diversity patterns in the fossil record. Much of the theory for equilibrial and unimodal patterns of diversity draw upon TIB.Species RichnessThere is a positive relationship between island size and species richness, which is attributed to elevated extinction among small populations on small islands and enhanced origination among large populations on large islands. Species–area relationships are found in both neontological and paleontological contexts (e.g., [109.Pruden M.J. Leighton L.R. Exploring the species–area relationship within a paleontological context, and the implications for modern conservation biology.in: Marine Conservation Paleobiology. Springer, 2018: 143-161Crossref Google Scholar]). TIB predicts greater richness over larger spatiotemporal scales (e.g., [53.Close R. et al.The spatial structure of Phanerozoic marine animal diversity.Science. 2020; 368: 420-424Crossref PubMed Scopus (25) Google Scholar,110.Du A. Behrensmeyer A.K. Spatial, temporal and taxonomic scaling of richness in an Eastern African large mammal community.Glob. Ecol. Biogeogr. 2018; 27: 1031-1042Crossref Scopus (5) Google Scholar]) and enhanced origination during dispersal (e.g., [20.Cantalapiedra J.L. et al.Decoupled ecomorphological evolution and diversification in neogene-quaternary horses.Science. 2017; 355: 627-630Crossref PubMed Scopus (51) Google Scholar,24.Pires M.M. et al.Continental faunal exchange and the asymmetrical radiation of carnivores.Proc. R. Soc. B. 2015; 282: 20151952Crossref PubMed Scopus (22) Google Scholar]).Equilibrial or Equilibrium DiversityAs richness nears the carrying capacity of an island, species accumulation (immigration and origination) will slow due to niche saturation and niche incumbency. This is the basis for the concept of negative diversity dependence, wherein higher diversity suppresses origination (or increases extinction) on evolutionary timescales [21.Foote M. et al.Diversity-dependent evolutionary rates in early Palaeozoic zooplankton.Proc. R. Soc. B. 2018; 285: 20180122Crossref PubMed Scopus (15) Google Scholar,55.Žliobaitė I. et al.Reconciling taxon senescence with the red queen's hypothesis.Nature. 2017; 552: 92-95Crossref PubMed Scopus (34) Google Scholar,58.Solórzano A. et al.Biotic and abiotic factors driving the diversification dynamics of crocodylia.Palaeontology. 2019; : 1-15Google Scholar,59.Condamine F.L. et al.Climate cooling and clade competition likely drove the decline of lamniform sharks.Proc. Natl. Acad. Sci. USA. 2019; 116: 20584-20590Crossref PubMed Scopus (21) Google Scholar].Red Queen HypothesisThe Red Queen Hypothesis (RQH; [13.Van Valen L.M. A new evolutionary law.Evol. Theor. 1973; 1: 1-30Google Scholar]) is based on the observation that species are equally likely to go extinct at any time, given an unvarying environment (age-independent extinction) [111.Marshall C.R. Five palaeobiological laws needed to understand the evolution of the living biota.Nat. Ecol. Evol. 2017; 1: 0165Crossref PubMed Scopus (85) Google Scholar]. RQH forms the basis for understanding how biotic interactions shape patterns of species coexistence and diversification in the fossil record. RQH remains controversial due to its focus on abiotic factors as the primary drivers of long-term biodiversity patterns [26.Voje K.L. et al.The role of biotic forces in driving macroevolution: beyond the red queen.Proc. R. Soc. B. 2015; 282: 20150186Crossref PubMed Scopus (63) Google Scholar].Ecosystem EnergyCompetition for available ecosystem energy is mediated by biotic interactions that structure the division of niche space and set limits to diversity (i.e., equilibrium diversity; e.g., [50.Close R.A. et al.Diversity dynamics of Phanerozoic terrestrial tetrapods at the local-community scale.Nat. Ecol. Evol. 2019; 3: 590Crossref PubMed Scopus (26) Google Scholar,53.Close R. et al.The spatial structure of Phanerozoic marine animal diversity.Science. 2020; 368: 420-424Crossref PubMed Scopus (25) Google Scholar]). As a community reaches equilibrium, speciation and invasion decrease (or extinction increases), as the number of ways to divide the niche space decrease. RQH predicts richness be greater in environments or during periods of higher ecosystem energy (e.g., [8.Fritz S.A. et al.Twenty-million-year relationship between mammalian diversity and primary productivity.Proc. Natl. Acad. Sci. U.S.A. 2016; 113: 10908-10913Crossref PubMed Scopus (29) Google Scholar]) as well as negative diversity dependence and unimodal diversity-through-time patterns (e.g., [21.Foote M. et al.Diversity-dependent evolutionary rates in early Palaeozoic zooplankton.Proc. R. Soc. B. 2018; 285: 20180122Crossref PubMed Scopus (15) Google Scholar,55.Žliobaitė I. et al.Reconciling taxon senescence with the red queen's hypothesis.Nature. 2017; 552: 92-95Crossref PubMed Scopus (34) Google Scholar]).Zero-Sum GameEvolutionary change in one species that improves the overall fitness of its members results in a negative effect of equal magnitude among coexisting species. An increase in abundance or diversity of one species also results in an energetically equivalent decrease in the abundance or diversity of other species (e.g., [42.Pires M.M. et al.Interactions within and between clades shaped the diversification of terrestrial carnivores.Evolution. 2017; 71: 1855-1864Crossref PubMed Scopus (18) Google Scholar]). Without environmental change, equilibrium diversity is stable, despite fluctuations in the relative abundances and taxonomic identity of constituent species (e.g., [50.Close R.A. et al.Diversity dynamics of Phanerozoic terrestrial tetrapods at the local-community scale.Nat. Ecol. Evol. 2019; 3: 590Crossref PubMed Scopus (26) Google Scholar]). Theory of Island Biogeography The Theory of Island Biogeography (TIB; [28.MacArthur R.H. Wilson E.O. An equilibrium theory of insular zoogeography.Evolution. 1963; 17: 373-387Crossref Google Scholar,29.MacArthur R. Wilson E.O. The Theory of Island Biogeography. Princeton University Press, 1967Google Scholar]) proposed ecological rules governing species richness and macroevolution on islands. TIB has been extended to explain continental macroecological and temporal diversity patterns in the fossil record. Much of the theory for equilibrial and unimodal patterns of diversity draw upon TIB. Species Richness There is a positive relationship between island size and species richness, which is attributed to elevated extinction among small populations on small islands and enhanced origination among large populations on large islands. Species–area relationships are found in both neontological and paleontological contexts (e.g., [109.Pruden M.J. Leighton L.R. Exploring the species–area relationship within a paleontological context, and the implications for modern conservation biology.in: Marine Conservation Paleobiology. Springer, 2018: 143-161Crossref Google Scholar]). TIB predicts greater richness over larger spatiotemporal scales (e.g., [53.Close R. et al.The spatial structure of Phanerozoic marine animal diversity.Science. 2020; 368: 420-424Crossref PubMed Scopus (25) Google Scholar,110.Du A. Behrensmeyer A.K. Spatial, temporal and taxonomic scaling of richness in an Eastern African large mammal community.Glob. Ecol. Biogeogr. 2018; 27: 1031-1042Crossref Scopus (5) Google Scholar]) and enhanced origination during dispersal (e.g., [20.Cantalapiedra J.L. et al.Decoupled ecomorphological evolution and diversification in neogene-quaternary horses.Science. 2017; 355: 627-630Crossref PubMed Scopus (51) Google Scholar,24.Pires M.M. et al.Continental faunal exchange and the asymmetrical radiation of carnivores.Proc. R. Soc. B. 2015; 282: 20151952Crossref PubMed Scopus (22) Google Scholar]). Equilibrial or Equilibrium Diversity As richness nears the carrying capacity of an island, species accumulation (immigration and origination) will slow due to niche saturation and niche incumbency. This is the basis for the concept of negative diversity dependence, wherein higher diversity suppresses origination (or increases extinction) on evolutionary timescales [21.Foote M. et al.Diversity-dependent evolutionary rates in early Palaeozoic zooplankton.Proc. R. Soc. B. 2018; 285: 20180122Crossref PubMed Scopus (15) Google Scholar,55.Žliobaitė I. et al.Reconciling taxon senescence with the red queen's hypothesis.Nature. 2017; 552: 92-95Crossref PubMed Scopus (34) Google Scholar,58.Solórzano A. et al.Biotic and abiotic factors driving the diversification dynamics of crocodylia.Palaeontology. 2019; : 1-15Google Scholar,59.Condamine F.L. et al.Climate cooling and clade competition likely drove the decline of lamniform sharks.Proc. Natl. Acad. Sci. USA. 2019; 116: 20584-20590Crossref PubMed Scopus (21) Google Scholar]. Red Queen Hypothesis The Red Queen Hypothesis (RQH; [13.Van Valen L.M. A new evolutionary law.Evol. Theor. 1973; 1: 1-30Google Scholar]) is based on the observation that species are equally likely to go extinct at any time, given an unvarying environment (age-independent extinction) [111.Marshall C.R. Five palaeobiological laws needed to understand the evolution of the living biota.Nat. Ecol. Evol. 2017; 1: 0165Crossref PubMed Scopus (85) Google Scholar]. RQH forms the basis for understanding how biotic interactions shape patterns of species coexistence and diversification in the fossil record. RQH remains controversial due to its focus on abiotic factors as the primary drivers of long-term biodiversity patterns [26.Voje K.L. et al.The role of biotic forces in driving macroevolution: beyond the red queen.Proc. R. Soc. B. 2015; 282: 20150186Crossref PubMed Scopus (63) Google Scholar]. Ecosystem Energy Competition for available ecosystem energy is mediated by biotic interactions that structure the division of niche space and set limits to diversity (i.e., equilibrium diversity; e.g., [50.Close R.A. et al.Diversity dynamics of Phanerozoic terrestrial tetrapods at the local-community scale.Nat. Ecol. Evol. 2019; 3: 590Crossref PubMed Scopus (26) Google Scholar,53.Close R. et al.The spatial structure of Phanerozoic marine animal diversity.Science. 2020; 368: 420-424Crossref PubMed Scopus (25) Google Scholar]). As a community reaches equilibrium, speciation and invasion decrease (or extinction increases), as the number of ways to divide the niche space decrease. RQH predicts richness be greater in environments or during periods of higher ecosystem energy (e.g., [8.Fritz S.A. et al.Twenty-million-year relationship between mammalian diversity and primary productivity.Proc. Natl. Acad. Sci. U.S.A. 2016; 113: 10908-10913Crossref PubMed Scopus (29) Google Scholar]) as well as negative diversity dependence and unimodal diversity-through-time patterns (e.g., [21.Foote M. et al.Diversity-dependent evolutionary rates in early Palaeozoic zooplankton.Proc. R. Soc. B. 2018; 285: 20180122Crossref PubMed Scopus (15) Google Scholar,55.Žliobaitė I. et al.Reconciling taxon senescence with the red queen's hypothesis.Nature. 2017; 552: 92-95Crossref PubMed Scopus (34) Google Scholar]). Zero-Sum Game Evolutionary change in one species that improves the overall fitness of its members results in a negative effect of equal magnitude among coexisting species. An increase in abundance or diversity of one species also results in an energetically equivalent decrease in the abundance or diversity of other species (e.g., [42.Pires M.M. et al.Interactions within and between clades shaped the diversification of terrestrial carnivores.Evolution. 2017; 71: 1855-1864Crossref PubMed Scopus (18) Google Scholar]). Without environmental change, equilibrium diversity is stable, despite fluctuations in the relative abundances and taxonomic identity of constituent species (e.g., [50.Close R.A. et al.Diversity dynamics of Phanerozoic terrestrial tetrapods at the local-community scale.Nat. Ecol. Evol. 2019; 3: 590Crossref PubMed Scopus (26) Google Scholar]). The development of comprehensive phylogenetic and occurrence-based data sets that include extant and extinct species (Table 1) (e.g., [30.Faurby S. Svenning J.-C. A species-level phylogeny of all extant and late quaternary extinct mammals using a novel heuristic-hierarchical Bayesian approach.Mol. Phylogenet. Evol. 2015; 84: 14-26Crossref PubMed Scopus (84) Google Scholar]) have begun to close this gap by enabling empirical testing of hypotheses relating biotic interactions to emergent biodiversity patterns (Figure 1). Models of evolutionary processes have increased in sophistication to allow explicit inclusion of interactions among clades (Table 1) [31.Drury J.P. et al.An assessment of phylogenetic tools for analyzing the interplay between interspecific interactions and phenotypic evolution.Syst. Biol. 2018; 67: 413-427Crossref PubMed Scopus (15) Google Scholar, 32.Manceau M. et al.A unifying comparative phylogenetic framework including traits coevolving across interacting lineages.Syst. Biol. 2017; 66: 551-568PubMed Google Scholar, 33.Silvestro D. et al.Bayesian estimation of multiple clade competition from fossil data.Evol. Ecol. Res. 2017; 18: 41-59Google Scholar]. There have been concurrent advances in analyses for understanding the role of biotic interactions in shaping macroecological patterns (e.g., [34.Tóth A.B. et al.Reorganization of surviving mammal communities after the end-pleistocene megafaunal extinction.Science. 2019; 365: 1305-1308Crossref PubMed Scopus (19) Google Scholar]) and trophic networks (e.g., [5.Roopnarine P.D. Angielczyk K.D. Community stability and selective extinction during the Permian-Triassic mass extinction.Science. 2015; 350: 90-93Crossref PubMed Scopus (46) Google Scholar]; Figure 1).Table 1Approaches Recently Used to Quantify or Model the Macroevolutionary Effects of Biotic Interactions Using Fossil Occurrence or Trait Data (Some Are Novel, While Others Are Extensions of Previously Applied Methods)aRelevant methods papers are included in 'Example applications', even if they do not contain an empirical application of the method they propose. Where there is an empirical application, the focal taxa are in parentheses. Papers that include an explicit test of or model the effect of biotic interactions (rather than inferring their effect by eliminating other factors) are bolded and starred.MethodApproachHow it is used to detect biotic interactions from fossil evidenceAdvantagesLimitationsExample applicationsBirth–death process with fossil occurrencesA birth–death-sampling (BDS) model is one that describes a phylogenetic tree of living taxa and fossil occurrences, parameterized with rates of character change, origination, extinction, and fossil sampling. Bayesian Markov Chain Monte Carlo algorithms are used to estimate the probability density of possible phylogenies based on the data.Interclade and intraclade diversity dependence and abiotic factors can be explicitly included in the modeling framework to estimate their relative contribution. If the inclusion of diversity dependence or interaction between the diversity trajectories of two clades in the model leads to more probable phylogenies, then biotic effects can be inferred to be important.The process of biotic interactions contributing to evolution is directly modeled, which eliminates the ambiguity inherent in modeling the resulting pattern of evolution (rather than the process) common in other approaches, where one pattern can be generated by a number of different possible processes.Models are often highly complex and in combination with a paucity of data they can be difficult to fit reliably. The behavior of estimation algorithms has not yet been well characterized in a breadth of macroevolutionary scenarios to understand possible biases. Some BDS models assume complete species sampling. The method does not inherently consider whether specific taxa could reasonably be expected to be interacting with one another.[46.Silvestro D. et al.The role of clade competition in the diversification of North American canids.Proc. Natl. Acad. Sci. U.S.A. 2015; 112: 8684-8689Crossref PubMed Scopus (93) Google Scholar]* (canids), [24.Pires M.M. et al.Continental faunal exchange and the asymmetrical radiation of carnivores.Proc. R. Soc. B. 2015; 282: 20151952Crossref PubMed Scopus (22) Google Scholar] (carnivor