Spatial processes and evolutionary models: a critical review

Abstract

Evolution is a fundamentally population level process in which variation, drift and selection produce both temporal and spatial patterns of change. Statistical model fitting is now commonly used to estimate which kind of evolutionary process best explains patterns of change through time using models like Brownian motion, stabilizing selection (Ornstein–Uhlenbeck) and directional selection on traits measured from stratigraphic sequences or on phylogenetic trees. But these models assume that the traits possessed by a species are homogeneous. Spatial processes such as dispersal, gene flow and geographical range changes can produce patterns of trait evolution that do not fit the expectations of standard models, even when evolution at the local‐population level is governed by drift or a typical OU model of selection. The basic properties of population level processes (variation, drift, selection and population size) are reviewed and the relationship between their spatial and temporal dynamics is discussed. Typical evolutionary models used in palaeontology incorporate the temporal component of these dynamics, but not the spatial. Range expansions and contractions introduce rate variability into drift processes, range expansion under a drift model can drive directional change in trait evolution, and spatial selection gradients can create spatial variation in traits that can produce long‐term directional trends and punctuation events depending on the balance between selection strength, gene flow, extirpation probability and model of speciation. Using computational modelling that spatial processes can create evolutionary outcomes that depart from basic population‐level notions from these standard macroevolutionary models.

On the Effect of Asymmetrical Trait Inheritance on Models of Trait Evolution

“…For instance, such a simulator can help answer longstanding questions about the impact and fate of microevolutionary processes on a macroevolutionary scale ( Hansen and Martins 1996 ; Arnold et al 2001 ; Reznick and Ricklefs 2009 ; Kostikova et al 2016 ; Rolland et al 2018 ; Duchen et al 2020 ). Currently, our community is in need of individual-based simulators of phenotypic traits, although some research in this direction has been done in the past ( Neuenschwander et al 2008 ; Boucher et al 2014 ; Aguilée et al 2018 ; Polly 2019 ). For instance, ( Neuenschwander et al, 2008 ) have developed a simulator of quantitative traits, but they focus more on the genetic basis and works only at the population level.…”

“…Additionally, ( Boucher et al, 2014 ) have also developed a simulator of phenotypes allowing for different modes of speciation, but limited to a small number of generations. ( Polly, 2019 ), on the other hand, developed computational models that take spatial processes into account and applied them to paleontological data. His results also support the fact that overlooking such processes results in incorrect interpretations of traditional model fitting in Evolutionary Biology ( Polly, 2019 ).…”

“…( Polly, 2019 ), on the other hand, developed computational models that take spatial processes into account and applied them to paleontological data. His results also support the fact that overlooking such processes results in incorrect interpretations of traditional model fitting in Evolutionary Biology ( Polly, 2019 ). Our simulator is unique in that it simulates populations of individuals for thousands of generations, and it allows for different types of speciation events to happen, under different adaptive peaks, thus generating complete phylogenies.…”

Phylogenetic Comparative Methods: A User's Guide for Paleontologists

“…There are a variety of reasons that simple models of trait evolution applied across a whole clade might not be good models for the underlying dynamics (see e.g. Polly 2019). Furthermore, it may be the case that there is simply not enough information in your dataset to allow you to identify an adequate model, especially if the model you are interested in assessing produces similar patterns of trait evolution to other candidate models (Boettiger et al 2012;Slater and Pennell 2014).…”

New Avenues for Old Travellers: Phenotypic Evolutionary Trends Meet Morphodynamics, and Both Enter the Global Change Biology Era

“…Leaving aside the uncertainties relative to the underlying evolutionary mechanisms, the focus on geographical and ecological information in a theoretical model of directional evolutionary patterns recently became a central topic in macroevolution. For instance, Polly (2018) highlighted that existing statistical models used to study evolutionary patterns rely on a Fisherian view of evolution, whereby species are considered single panmictic populations (i.e., populations in which all individuals are potential partners) whose traits are the same regardless of spatial and environmental influences (Fisher, 1930). According to this vision, evolutionary outcomes disregard drift and habitat-specific selection (and are likely to be affected by a misjudgement of the impact of sexual selection).…”