Estimating ancient biogeographic patterns with statistical model discrimination

Abstract

The geographic ranges in which species live is a function of many factors underlying ecological and evolutionary contingencies. Observing the geographic range of an individual species provides valuable information about these historical contingencies for a lineage, determining the distribution of many distantly related species in tandem provides information about large-scale constraints on evolutionary and ecological processes generally. We present a linear regression method that allows for the discrimination of various hypothetical biogeographical models for determining which landscape distributional pattern best matches data from the fossil record. The linear regression models used in the discrimination rely on geodesic distances between sampling sites (typically geologic formations) as the independent variable and three possible dependent variables: Dice/Sorensen similarity; Euclidean distance; and phylogenetic community dissimilarity. Both the similarity and distance measures are useful for full-community analyses without evolutionary information, whereas the phylogenetic community dissimilarity requires phylogenetic data. Importantly, the discrimination method uses linear regression residual error to provide relative measures of support for each biogeographical model tested, not absolute answers or p-values. When applied to a recently published dataset of Campanian pollen, we find evidence that supports two plant communities separated by a transitional zone of unknown size. A similar case study of ceratopsid dinosaurs using phylogenetic community dissimilarity provided no evidence of a biogeographical pattern, but this case study suffers from a lack of data to accurately discriminate and/or too much temporal mixing. Future research aiming to reconstruct the distribution of organisms across a landscape has a statisticalbased method for determining what biogeographic distributional model best matches the available data.

Introduction to Dinosaurs: New Ideas from Old Bones papers honoring Peter Dodson

“…While an application of this method to a recently published dataset of Campanian pollen, supported two plant communities separated by a transitional zone of unknown size, a similar case study of ceratopsid dinosaurs using phylogenetic community dissimilarity provided no evidence of a biogeographical pattern (Gates et al, 2023). They conclude that this latter case study suffered from sufficient data to accurately discriminate and/or too much temporal mixing (Gates et al, 2023). Hedrick (2023) examines the use of morphometrics as applied to studies of dinosaurs and identifies five aspects of non-avian dinosaur paleobiology where morphometrics has been widely utilized to advance our knowledge: systematics, sexual dimorphism, locomotion, macroevolution, and trackways.…”

“…They note a decoupling of endosteal and periosteal pathological bone deposition in the metatarsal exhibiting homogenously thick endosteal pathological bone in the absence of localized periosteal reactive bone (Tsogtbaatar et al, 2023). Gates et al (2023) present a linear regression method that allows for the discrimination of various hypothetical biogeographical models in determining the landscape distributional pattern that best matches data from the fossil record. While an application of this method to a recently published dataset of Campanian pollen, supported two plant communities separated by a transitional zone of unknown size, a similar case study of ceratopsid dinosaurs using phylogenetic community dissimilarity provided no evidence of a biogeographical pattern (Gates et al, 2023).…”

“…Gates et al (2023) present a linear regression method that allows for the discrimination of various hypothetical biogeographical models in determining the landscape distributional pattern that best matches data from the fossil record. While an application of this method to a recently published dataset of Campanian pollen, supported two plant communities separated by a transitional zone of unknown size, a similar case study of ceratopsid dinosaurs using phylogenetic community dissimilarity provided no evidence of a biogeographical pattern (Gates et al, 2023). They conclude that this latter case study suffered from sufficient data to accurately discriminate and/or too much temporal mixing (Gates et al, 2023).…”

“…While an application of this method to a recently published dataset of Campanian pollen, supported two plant communities separated by a transitional zone of unknown size, a similar case study of ceratopsid dinosaurs using phylogenetic community dissimilarity provided no evidence of a biogeographical pattern (Gates et al, 2023). They conclude that this latter case study suffered from sufficient data to accurately discriminate and/or too much temporal mixing (Gates et al, 2023).…”