Measuring rates of phenotypic evolution and the inseparability of tempo and mode

Paleobiology ◽  
2012 ◽  
Vol 38 (3) ◽  
pp. 351-373 ◽  
Author(s):  
Gene Hunt
Keyword(s):  
Random Walk ◽  
Evolutionary Biology ◽  
Sampling Error ◽  
Strong Dependence ◽  
Interval Length ◽  
Model Parameters ◽  
Evolutionary Divergence ◽  
Phenotypic Evolution ◽  
Interval Method ◽  
Alternative Approach

Rates of phenotypic evolution are central to many issues in paleontology, but traditional rate metrics such as darwins or haldanes are seldom used because of their strong dependence on interval length. In this paper, I argue that rates are usefully thought of as model parameters that relate magnitudes of evolutionary divergence to elapsed time. Starting with models of directional evolution, random walks, and stasis, I derive for each a reasonable rate metric. These metrics can be linked to existing approaches in evolutionary biology, and simulations show that they can be estimated accurately at any temporal resolution via maximum likelihood, but only when that metric's underlying model is true.The estimation of generational rates of a random walk under realistic paleontological conditions is compared with simulations to that of a prominent alternative approach, Gingerich's LRI (log-rate, log-interval) method. Generational rates are estimated poorly by LRI; they often reflect sampling error more than the actual pace of change. Further simulations show that under some realistic conditions, it is simply not possible to infer generational rates from coarsely sampled populations.These modeling results indicate a complex dependence between evolutionary mode and the measurement of evolutionary rates, and that there is unlikely to be a rate metric that works well for all traits and time scales. Compilations of paleontological and phylogenetic data indicate that all of the three rate metrics derived here show some relationship with interval length. Although there is no perfect rate metric, at present the most practical choices derive from the parameters of the stasis and random walk models. The latter, called the step variance, is particularly promising as a rate metric in paleontology and comparative biology.

scholarly journals Fly wing evolution explained by a neutral model with mutational pleiotropy

2020 ◽  
Author(s):  
Daohan Jiang ◽  
Jianzhi Zhang
Keyword(s):  
Linear Correlation ◽  
Evolutionary Biology ◽  
Stabilizing Selection ◽  
Evolutionary Divergence ◽  
Phenotypic Evolution ◽  
Central Question ◽  
Evolutionary Patterns ◽  
Strong Linear Correlation ◽  
Mutational Variance

ABSTRACTTo what extent the speed of mutational production of phenotypic variation determines the rate of long-term phenotypic evolution is a central question in evolutionary biology. In a recent study, Houle et al. addressed this question by studying the mutational variation, microevolution, and macroevolution of locations of vein intersections on fly wings, reporting very slow phenotypic evolution relative to the rates of mutational input, high phylogenetic signals of these traits, and a strong, linear correlation between the mutational variance of a trait and its rate of evolution. Houle et al. examined multiple models of phenotypic evolution but found none consistent with all these observations. Here we demonstrate that the purported linear correlation between mutational variance and evolutionary divergence is an artifact. More importantly, patterns of fly wing evolution are explainable by a simple model in which the wing traits are neutral or neutral within a range of phenotypic values but their evolutionary rates are reduced because most mutations affecting these traits are purged owing to their pleiotropic effects on other traits that are under stabilizing selection. We conclude that the evolutionary patterns of fly wing morphologies are explainable under the existing theoretical framework of phenotypic evolution.

Speed vs. comfort: Testing the efficacy of a single question for predicting transit users’ route choices

2019 ◽  
Author(s):  
Joseph John Pyne Simons ◽  
Ilya Farber
Keyword(s):  
Data Collection ◽  
Efficient Method ◽  
Choice Task ◽  
The Self ◽  
Self Report ◽  
Model Parameters ◽  
Single Item ◽  
Alternative Approach ◽  
Single Question ◽  
Insight Into

Not all transit users have the same preferences when making route decisions. Understanding the factors driving this heterogeneity enables better tailoring of policies, interventions, and messaging. However, existing methods for assessing these factors require extensive data collection. Here we present an alternative approach - an easily-administered single item measure of overall preference for speed versus comfort. Scores on the self-report item predict decisions in a choice task and account for a proportion of the differences in model parameters between people (n=298). This single item can easily be included on existing travel surveys, and provides an efficient method to both anticipate the choices of users and gain more general insight into their preferences.

scholarly journals Estimation of Galactic Model Parameters by Interval Method

1996 ◽  
Vol 169 ◽  
pp. 713-714
Author(s):  
S. A. Kutuzov
Keyword(s):  
Mutual Interaction ◽  
Component Model ◽  
Model Parameters ◽  
Interval Method ◽  
Two Component ◽  
The Galaxy ◽  
Galactic Model

The interval method of estimating model parameters (MPs) for the Galaxy was suggested earlier (Kutuzov 1988). Intervals are proposed to be used both for observational estimates of galactic parameters (GPs) and for the values of MPs. In this work we consider a model as a tool for studying mutual interaction of GPs. Two-component model is considered (Kutuzov, Ossipkov 1989). We have to estimate the array P of eight MPs.

Simulated annealing for airborne EM inversion

Geophysics ◽  
2007 ◽  
Vol 72 (4) ◽  
pp. F189-F195 ◽  
Author(s):  
Changchun Yin ◽  
Greg Hodges
Keyword(s):  
Simulated Annealing ◽  
Random Walk ◽  
Boltzmann Distribution ◽  
Model Parameters ◽  
Local Minima ◽  
Model Configuration ◽  
Airborne Electromagnetic ◽  
Starting Model ◽  
Airborne Em ◽  
Cooling Schedule

The traditional algorithms for airborne electromagnetic (EM) inversion, e.g., the Marquardt-Levenberg method, generally run only a downhill search. Consequently, the model solutions are strongly dependent on the starting model and are easily trapped in local minima. Simulated annealing (SA) starts from the Boltzmann distribution and runs both downhill and uphill searches, rendering the searching process to easily jump out of local minima and converge to a global minimum. In the SA process, the calculation of Jacobian derivatives can be avoided because no preferred searching direction is required as in the case of the traditional algorithms. We apply SA technology for airborne EM inversion by comparing the inversion with a thermodynamic process, and we discuss specifically the SA procedure with respect to model configuration, random walk for model updates, objective function, and annealing schedule. We demonstrate the SA flexibility for starting models by allowing the model parameters to vary in a large range (far away from the true model). Further, we choose a temperature-dependent random walk for model updates and an exponential cooling schedule for the SA searching process. The initial temperature for the SA cooling scheme is chosen differently for different model parameters according to their resolvabilities. We examine the effectiveness of the algorithm for airborne EM by inverting both theoretical and survey data and by comparing the results with those from the traditional algorithms.

Identification of ’Effective’ Linear Joints Using Coupling and Joint Identification Techniques

1998 ◽  
Vol 120 (2) ◽  
pp. 331-338 ◽  
Author(s):  
Y. Ren ◽  
C. F. Beards
Keyword(s):  
Dynamic Properties ◽  
Real Life ◽  
Model Parameters ◽  
Coupling Technique ◽  
Alternative Approach ◽  
Identification Technique ◽  
Joint Identification ◽  
Stiff Joint ◽  
Almost All ◽  
Identification Techniques

Almost all real-life structures are assembled from components connected by various types of joints. Unlike many other parts, the dynamic properties of a joint are difficult to model analytically. An alternative approach for establishing a theoretical model of a joint is to extract the model parameters from experimental data using joint identification techniques. The accuracy of the identification is significantly affected by the properties of the joints themselves. If a joint is stiff, its properties are often difficult to identify accurately. This is because the responses at both ends of the joint are linearly-dependent. To make things worse, the existence of a stiff joint can also affect the accuracy of identification of other effective joints (the term “effective joints” in this paper refers to those joints which otherwise can be identified accurately). This problem is tackled by coupling these stiff joints using a generalized coupling technique, and then the properties of the remaining joints are identified using a joint identification technique. The accuracy of the joint identification can usually be improved by using this approach. Both numerically simulated and experimental results are presented.

scholarly journals Chaos and the (un)predictability of evolution in a changing environment

2017 ◽  
Author(s):  
Artur Rego-Costa ◽  
Florence Débarre ◽  
Luis-Miguel Chevin
Keyword(s):  
Evolutionary Dynamics ◽  
Initial Conditions ◽  
Strong Dependence ◽  
Environmental Stochasticity ◽  
Phenotypic Evolution ◽  
Evolutionary System ◽  
Chaotic Oscillations ◽  
Changing Environment ◽  
Environmental Forcing ◽  
Evolutionary Trajectories

Among the factors that may reduce the predictability of evolution, chaos, characterized by a strong dependence on initial conditions, has received much less attention than randomness due to genetic drift or environmental stochasticity. It was recently shown that chaos in phenotypic evolution arises commonly under frequency-dependent selection caused by competitive interactions mediated by many traits. This result has been used to argue that chaos should often make evolutionary dynamics unpredictable. However, populations also evolve largely in response to external changing environments, and such environmental forcing is likely to influence the outcome of evolution in systems prone to chaos. We investigate how a changing environment causing oscillations of an optimal phenotype interacts with the internal dynamics of an eco-evolutionary system that would be chaotic in a constant environment. We show that strong environmental forcing can improve the predictability of evolution, by reducing the probability of chaos arising, and by dampening the magnitude of chaotic oscillations. In contrast, weak forcing can increase the probability of chaos, but it also causes evolutionary trajectories to track the environment more closely. Overall, our results indicate that, although chaos may occur in evolution, it does not necessarily undermine its predictability.

scholarly journals Efficient detection of repeating sites to accelerate phylogenetic likelihood calculations

2016 ◽  
Author(s):  
Kassian Kobert ◽  
Alexandros Stamatakis ◽  
Tomáš Flouri
Keyword(s):  
Evolutionary Biology ◽  
Likelihood Function ◽  
Simulated Data ◽  
Evolutionary Model ◽  
Identical Result ◽  
Model Parameters ◽  
Data Sets ◽  
Efficient Detection ◽  
Novel Method ◽  
Computational Bottleneck

The phylogenetic likelihood function is the major computational bottleneck in several applications of evolutionary biology such as phylogenetic inference, species delimitation, model selection and divergence times estimation. Given the alignment, a tree and the evolutionary model parameters, the likelihood function computes the conditional likelihood vectors for every node of the tree. Vector entries for which all input data are identical result in redundant likelihood operations which, in turn, yield identical conditional values. Such operations can be omitted for improving run-time and, using appropriate data structures, reducing memory usage. We present a fast, novel method for identifying and omitting such redundant operations in phylogenetic likelihood calculations, and assess the performance improvement and memory saving attained by our method. Using empirical and simulated data sets, we show that a prototype implementation of our method yields up to 10-fold speedups and uses up to 78% less memory than one of the fastest and most highly tuned implementations of the phylogenetic likelihood function currently available. Our method is generic and can seamlessly be integrated into any phylogenetic likelihood implementation.

The Intellectual Challenge of Morphological Evolution: A Case for Variational Structuralism

2014 ◽  
Author(s):  
Günter P. Wagner
Keyword(s):  
Developmental Biology ◽  
Evolutionary Biology ◽  
Morphological Evolution ◽  
Evolutionary Developmental Biology ◽  
Phenotypic Evolution ◽  
Developmental Variation ◽  
Core Idea ◽  
Intellectual Challenge

This chapter explores variational structuralism, whose core idea is that organisms and their parts play causal roles in shaping the patterns of phenotypic evolution. Drawing on the work of pioneers such as Ron Amundson, it discusses the conceptual incompatibilities between two styles of thinking in evolutionary biology: functionalism and structuralism. It proceeds by explaining the meaning of developmental types and structuralist concepts arising from macromolecular studies. It also examines facts and ideas about bodies, Rupert Riedl's theory of the “immitatory epigenotype,” and Neil Shubin and Pere Alberch's developmental interpretation of tetrapod limbs. Finally, it looks at the emergence of molecular structuralism and the enigma of developmental variation. The chapter argues that typology naturally emerged from the facts of evolutionary developmental biology and that it would be seriously problematic to try to avoid it.

scholarly journals Impact of transition to a subterranean lifestyle on morphological disparity and integration in talpid moles (Mammalia, Talpidae)

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Gabriele Sansalone ◽  
Paolo Colangelo ◽  
Anna Loy ◽  
Pasquale Raia ◽  
Stephen Wroe ◽  
...  
Keyword(s):  
Evolutionary Biology ◽  
Morphological Variability ◽  
Phenotypic Integration ◽  
Phenotypic Traits ◽  
Phenotypic Evolution ◽  
Morphological Disparity ◽  
Morphological Diversification ◽  
Phylogenetic Conservatism ◽  
Selective Forces ◽  
Subterranean Species

Abstract Background Understanding the mechanisms promoting or constraining morphological diversification within clades is a central topic in evolutionary biology. Ecological transitions are of particular interest because of their influence upon the selective forces and factors involved in phenotypic evolution. Here we focused on the humerus and mandibles of talpid moles to test whether the transition to the subterranean lifestyle impacted morphological disparity and phenotypic traits covariation between these two structures. Results Our results indicate non-subterranean species occupy a significantly larger portion of the talpid moles morphospace. However, there is no difference between subterranean and non-subterranean moles in terms of the strength and direction of phenotypic integration. Conclusions Our study shows that the transition to a subterranean lifestyle significantly reduced morphological variability in talpid moles. However, this reduced disparity was not accompanied by changes in the pattern of traits covariation between the humerus and the mandible, suggesting the presence of strong phylogenetic conservatism within this pattern.

scholarly journals Effects of spatial discretization in ice-sheet modelling using the shallow-ice approximation

2006 ◽  
Vol 52 (176) ◽  
pp. 89-98 ◽  
Author(s):  
J. Van Den Berg ◽  
R.S.W. Van De Wal ◽  
J. Oerlemans
Keyword(s):  
Initial Conditions ◽  
Strong Dependence ◽  
Ice Sheet ◽  
Model Parameters ◽  
Time Step ◽  
Numerical Errors ◽  
Surface Gradient ◽  
Dimension Analysis ◽  
Sloping Bed ◽  
Ice Model

AbstractThis paper assesses a two-dimensional, vertically integrated ice model for its numerical properties in the calculation of ice-sheet evolution on a sloping bed using the shallow-ice approximation. We discuss the influence of initial conditions and individual model parameters on the model’s numerical behaviour, with emphasis on varying spatial discretizations. The modelling results suffer badly from numerical problems. They show a strong dependence on gridcell size and we conclude that the widely used gridcell spacing of 20 km is too coarse. The numerical errors are small in each single time-step, but increase non-linearly over time and with volume change, as a result of feedback of the mass balance with height. We propose a new method for the calculation of the surface gradient near the margin, which improves the results significantly. Furthermore, we show that we may use dimension analysis as a tool to explain in which situations numerical problems are to be expected.

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