The challenges to inferring the regulators of biodiversity in deep time

Abstract

Attempts to infer the ecological drivers of macroevolution in deep time have long drawn inspiration from work on extant systems, but long-term evolutionary and geological changes complicate the simple extrapolation of such theory. Recent efforts to incorporate a more informed ecology into macroevolution have moved beyond the descriptive, seeking to isolate generating mechanisms and produce testable hypotheses of how groups of organisms usurp each other or coexist over vast timespans. This theme issue aims to exemplify this progress, providing a series of case studies of how novel modelling approaches are helping infer the regulators of biodiversity in deep time. In this Introduction, we explore the challenges of these new approaches. First, we discuss how our choices of taxonomic units have implications for the conclusions drawn. Second, we emphasize the need to embrace the interdependence of biotic and abiotic changes, because no living organism ignores its environment. Third, in the light of parts 1 and 2, we discuss the set of dynamic signatures that we might expect to observe in the fossil record. Finally, we ask whether these dynamics represent the most ecologically informative foci for research efforts aimed at inferring the regulators of biodiversity in deep time. The papers in this theme issue contribute in each of these areas.

Estimating Age-Dependent Extinction: Contrasting Evidence from Fossils and Phylogenies

“…Of particular interest is the potential effect that taxonomic resolution might have on our inferences regarding the generality of ADE models. Ezard et al (2016) and Crampton et al (2016) have shown that the choice of taxonomic level in foraminifera and graptolites, respectively, affects extinction rate inferences, with evidence of age dependence at the species level but not at the genus level. This suggests that Van Valen’s law of constant extinction may be taxonomy dependent.…”

Assessing the causes of diversification slowdowns: temperature‐dependent and diversity‐dependent models receive equivalent support

“…Most studies have only done so relying on visual inspections of phylogenies in parallel to paleoenvironmental curves or with simple birth–death models (Winkler et al ; Condamine et al ). As a result, we still know little about the role of abiotic factors in driving macroevolutionary dynamics, in particular for groups lacking a comprehensive fossil record (Benton ; Ezard et al , ). This is a major gap, given that paleontological studies have suggested a prominent effect of environmental changes on diversification, for example, by generating bursts of speciation (Jaramillo et al ; Peters ; Erwin ; Hannisdal & Peters ; Mayhew et al ).…”

Towards a morphological metric of assemblage dynamics in the fossil record: a test case using planktonic foraminifera

“…In full recognition of the ultimate need for precision, we set out to develop a high-throughput approach (semi-3D morphometrics). We reasoned that image processing and machine learning will ultimately allow us to extract the ecological and evolutionary signals from the noise and that rapid approaches are critically needed to address questions of assemblage dynamics (see call for population studies in [ 109 , 121 ]). Towards this end, we have developed and tested a method for the extraction of 3D hulls from light microscopic and photogrammetric images, examined the potential of morphology as a tracer of assemblage dynamics in planktonic foraminifera, compared rapid and refined 3D morphometric approaches (e.g.…”