The Species-Area Relationship in the Late Ordovician: A Test Using Neutral Theory

Abstract

Abstract:The fundamental biodiversity number, θ, as proposed by Hubbell, should be positively correlated with province area. Because θ can be calculated from preserved relative abundance distributions, this correlation can be tested in the fossil record for regions with known provinces. Late Ordovician (443-458 Ma) strata of Laurentia are divided into four geochemically and biologically distinct regions that reflect provinces in the epicontinental sea. We use existing and newly obtained bed-level census data to test whether Hubbell's θ is positively correlated with the area of these four regions, corresponding roughly to the Appalachian Basin, Cincinnati Arch, Upper Mississippi Valley, and western United States and Canada. Results indicate a positive relationship between province area and θ that suggests the influence of provincial area, among other factors, on diversity. This correlation highlights the inherent link between diversity and abundance structure at local and regional scales, such that changes at one scale will necessarily affect the other. Since diversity at these smaller spatial scales is an important component of global biodiversity, determining the nature of this relationship in the fossil record has implications for understanding how diversity is assembled globally throughout the Phanerozoic.

Controlling for the species-area effect supports constrained long-term Mesozoic terrestrial vertebrate diversification

“…Our equal-spread subsampled diversity estimates demonstrate that correcting for spatial biases can yield flatter diversity trajectories relative to uncorrected data. However, we anticipate that studies of diversity in deep time will increasingly focus on quantifying species-area relationships 32 36 37 38 39 67 —which encode information about patterns of alpha, beta and gamma diversity—and how they vary through time and space. This approach will provide rich new insights about the history of biodiversity on our planet.…”

“…Relationships between the apparent richness of fossil taxa and the palaeogeographic spread over which fossils have been collected could result from either of two non-mutually-exclusive models: (1) ‘record bias', in which species richness covaries with sampled area purely due to the confounding effect of uneven spatial sampling and species-area relationships; or (2) ‘common cause', in which Earth system processes (for example, sea-level change, tectonic activity) ultimately determine both the sizes of individual regions available for sampling and their corresponding species richness. Previous attempts to correct for variation in palaeogeographic spread 8 32 33 34 36 37 38 39 would not allow the roles of these two alternative models to be distinguished, making it difficult to determine whether the corrections were appropriate (under a record bias model) or not (under a common cause model). Nevertheless, the issue can be circumvented by drawing fossil occurrences from geographic regions of equal size through time and space before the application of richness-estimation methods.…”

Spatial, temporal and taxonomic scaling of richness in an eastern African large mammal community

“…The implications for palaeoecological research are important, as most studies are done at the genus level or higher, including studies that look at SARs and STRs in the fossil record (e.g., Sclafani & Holland, ). Palaeoecologists need to understand how richness scales with taxonomic level and how this interacts with space and time.…”

Understanding ecological change across large spatial, temporal and taxonomic scales: integrating data and methods in light of theory

“…dispersal) among individuals of different species (Hubbell 2001, Rosindell et al 2011) represent a starting point for more complex models of assemblage dynamics (Chave 2004, Rosindell et al 2012. In rare cases, predictions from neutral IBMs have also been evaluated against paleoecological data at millennial scales (McGill et al 2005, Sclafani and Holland 2013, Correa-Metrio et al 2014, Holland 2018. The relationship between processes, data types and methodological advances in the study of ecological community dynamics in space and time.…”

“…Fuller et al 2005, McGill et al 2006a, Horvát et al 2010, Rosindell et al 2011. In rare cases, predictions from neutral IBMs have also been evaluated against paleoecological data at millennial scales (McGill et al 2005, Sclafani and Holland 2013, Correa-Metrio et al 2014, Holland 2018. We are unaware of studies evaluating predictions from neutral IBMs against integrated datasets of paleo and historic or contemporary communities; however, such a study could enable assessing the importance of ecological drift at both large temporal extents and fine temporal resolutions.…”