Search arXivSearch

arXiv · 2309.02788

Stochastic niche-based models for the evolution of species

Abstract

There have been many studies to examine whether one trait is correlated with another trait across a group of present-day species (for example, do species with larger brains tend to have longer gestation times. Since the introduction of the phylogenetic comparative method some authors have argued that it is necessary to have a biologically realistic model to generate evolutionary trees that incorporates information about the ecological niche occupied by species. Price presented a simple model along these lines in 1997. He defined a two-dimensional niche space formed by two continuous-valued traits, in which new niches arise with trait values drawn from a bivariate normal distribution. When a new niche arises, it is occupied by a descendant species of whichever current species is closest in ecological niche space. In sequence, more species are then evolved from already-existing species to which they are ecologically closest. Here we explore ways of extending Price's adaptive radiation model. One extension is to increase the dimensionality of the niche space by considering more than two continuous traits. A second extension is to allow both extinction of species (which may leave unoccupied niches) and removal of niches (which causes species occupying them to go extinct). To model this problem, we consider a continuous-time stochastic process which implicitly defines a phylogeny. To explore if trees generated under such a model (or under different parametrizations of the model) are realistic we can compute a variety of summary statistics that can be compared to those of empirically observed phylogenies. For example, there are existing statistics that aim to measure: tree balance, the relative rate of diversification, and phylogenetic signal of traits.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Albert Ch. Soewongsono, Barbara R. Holland, Malgorzata M. O'Reilly. 2023-09-06. Stochastic niche-based models for the evolution of species. https://arxiv.org/abs/2309.02788

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Beta-coalescents when sample size is large

Sweepstakes reproduction refers to a highly skewed individual recruitment success without involving natural selection and may apply to individuals in broadcast spawning populations characterised by Type III survivorship. We consider an extension of the model of sweepstakes reproduction for a haploid panmictic population of constant size $N$; the extension also works as an alternative to the Wright-Fisher model. Our model incorporates an upper bound on the random number of potential offspring (juveniles) produced by a given individual. Depending on how the bound behaves relative to the total population size, we obtain the Kingman coalescent, an incomplete Beta-coalescent, or the (complete) Beta-coalescent. We argue that applying such an upper bound is biologically reasonable. Moreover, we estimate the error of the coalescent approximation. The error estimates reveal that convergence can be slow, and small sample size can be sufficient to invalidate convergence, for example if the stated bound is of the form $N/\log N$. We use simulations to investigate the effect of increasing sample size on the site-frequency spectrum. When the limit is a Beta-coalescent, the site frequency spectrum will be as predicted by the limiting tree even though the full coalescent tree may deviate from the limiting one. When in the domain of attraction of the Kingman coalescent the effect of increasing sample size depends on the effective population size as has been noted in the case of the Wright-Fisher model. Conditioning on the population ancestry (the random ancestral relations of the entire population at all times) may have little effect on the site-frequency spectrum for the models considered here (as evidenced by simulation results).

q-bio.PE

The role of nestedness and saturating feedback in bipartite ecological systems

Large ecosystems balance competition and cooperation, yet standard generalized Lotka--Volterra models make mutualism destabilizing by amplifying disorder and driving unbounded growth. We show that Monod-like saturation resolves this paradox: dynamical mean-field theory and random-matrix analysis reveal a broader stable phase and enhanced survival. Network architecture provides a second control mechanism, but nestedness offers no intrinsic stability advantage. Instead, it is a byproduct of degree distributions with high connectivity necessary for stability.

q-bio.PE

TreeFlow: probabilistic modelling and automatic differentiation for phylogenetics

Probabilistic modelling frameworks are powerful tools for statistical modelling and inference. They are not immediately generalizable to phylogenetic problems due to the particular computational properties of the phylogenetic tree object. TreeFlow is a software library for probabilistic modelling and automatic differentiation with phylogenetic trees. It embeds phylogenetic trees in the TensorFlow Probability framework, and implements inference algorithms for phylogenetic models given a fixed tree topology. We demonstrate how TreeFlow can be used to quickly implement and assess new models. We also show that it provides reasonable performance for gradient-based inference algorithms compared to specialized computational libraries for phylogenetics.

q-bio.PE