Phylogenetic signal is an evolutionary and ecological term, that describes the tendency or the pattern of related biological species to resemble each other more than any other species that is randomly picked from the same phylogenetic tree. [1] [2]
Phylogenetic signal is an evolutionary and ecological term, that describes the tendency or the pattern of related biological species to resemble each other more than any other species that is randomly picked from the same phylogenetic tree. [1] [2]
Phylogenetic signal is usually described as the tendency of related biological species to resemble each other more than any other species that is randomly picked from the same phylogenetic tree. [1] [2] In other words, phylogenetic signal can be defined as the statistical dependence among species' trait values that is a consequence of their phylogenetic relationships. [3] The traits (e.g. morphological, ecological, life-history or behavioural traits) are inherited characteristics [4] – meaning the trait values are usually alike within closely related species, while trait values of distantly related biological species do not resemble each other to a such great degree. [5] It is often said that traits that are more similar in closely related taxa than in distant relatives exhibit greater phylogenetic signal. On the other hand, some traits are a consequence of convergent evolution and appear more similar in distantly related taxa than in relatives. Such traits show lower phylogenetic signal. [4]
Phylogenetic signal is a measure, closely related with an evolutionary process and development of taxa. It is thought that high rate of evolution leads to low phylogenetic signal and vice versa (hence, high phylogenetic signal is usually a consequence of either low rate of evolution either stabilizing type of selection). [3] Similarly high value of phylogenetic signal results in an existence of similar traits between closely related biological species, while increasing evolutionary distance between related species leads to decrease in similarity. [4] With a help of phylogenetic signal we can quantify to what degree closely related biological taxa share similar traits. [6]
On the other hand, some authors advise against such interpretations (the ones based on estimates of phylogenetic signal) of evolutionary rate and process. While studying simple models for quantitative trait evolution, such as the homogeneous rate genetic drift, it appears to be no relation between phylogenetic signal and rate of evolution. Within other models (e.g. functional constraint, fluctuating selection, phylogenetic niche conservatism, evolutionary heterogeneity etc.) relations between evolutionary rate, evolutionary process and phylogenetic signal are more complex, and can not be easily generalized using mentioned perception of the relation between two phenomenons. [3] Some authors argue that phylogenetic signal is not always strong in each clade and for each trait. It is also not clear if all of the possible traits do exhibit phylogenetic signal and if it is measurable. [4]
Phylogenetic signal is a concept widely used in different ecological and evolutionary studies. [7]
Among many questions that can be answered using a concept of phylogenetic signal, the most common ones are: [1]
Quantifying phylogenetic signal can be done using a range of various methods that are used for researching biodiversity in an aspect of evolutionary relatedness. With a help of measuring phylogenetic signal one can determine exactly how studied traits are correlated with phylogenetic relationship between species. [4]
Some of the earliest ways of quantifying phylogenetic signal were based on the use of various statistical methods (such as phylogenetic autocorrelation coefficients, phylogenetic correlograms, as well as autoregressive models). With a help of the mentioned methods one is able to quantify the value of phylogenetic autocorrelation for a studied trait throughout the phylogeny. [13] Another method commonly used in studying phylogenetic signal is so-called Brownian diffusion model of trait evolution that is based on the Brownian motion (BM) principle. [7] [14] Using Brownian diffusion model, one can not only study values but also compare those measures between various phylogenies. [1] Phylogenetic signal in continuous traits can be quantified and measured using K-statistic. [3] [15] Within this technique values from zero to infinity are used and higher value also means greater level of phylogenetic signal. [15]
The table below shows the most common indices and associated tests used for analyzing phylogenetic signal. [1]
| Type of statistics | Approach | Based on the model? | Statistical framework/applied test | Data | Reference |
|---|---|---|---|---|---|
| Abouheif's C mean | Autocorrelation | X | Permutation | Continuous | [16] |
| Blomberg's K | Evolutionary | ✓ | Permutation | Continuous | [2] |
| D statistic | Evolutionary | ✓ | Permutation | Categorical | [17] |
| Moran's I | Autocorrelation | X | Permutation | Continuous | [18] |
| Pagel's λ | Evolutionary | ✓ | Maximum likelihood | Continuous | [19] |
| δstatistic | Evolutionary | ✓ | Bayesian | Categorical | [9] |
In biology, phylogenetics is the study of the evolutionary history and relationships among or within groups of organisms. These relationships are determined by phylogenetic inference methods that focus on observed heritable traits, such as DNA sequences, protein amino acid sequences, or morphology. The result of such an analysis is a phylogenetic tree—a diagram containing a hypothesis of relationships that reflects the evolutionary history of a group of organisms.
A cladogram is a diagram used in cladistics to show relations among organisms. A cladogram is not, however, an evolutionary tree because it does not show how ancestors are related to descendants, nor does it show how much they have changed, so many differing evolutionary trees can be consistent with the same cladogram. A cladogram uses lines that branch off in different directions ending at a clade, a group of organisms with a last common ancestor. There are many shapes of cladograms but they all have lines that branch off from other lines. The lines can be traced back to where they branch off. These branching off points represent a hypothetical ancestor which can be inferred to exhibit the traits shared among the terminal taxa above it. This hypothetical ancestor might then provide clues about the order of evolution of various features, adaptation, and other evolutionary narratives about ancestors. Although traditionally such cladograms were generated largely on the basis of morphological characters, DNA and RNA sequencing data and computational phylogenetics are now very commonly used in the generation of cladograms, either on their own or in combination with morphology.
Convergent evolution is the independent evolution of similar features in species of different periods or epochs in time. Convergent evolution creates analogous structures that have similar form or function but were not present in the last common ancestor of those groups. The cladistic term for the same phenomenon is homoplasy. The recurrent evolution of flight is a classic example, as flying insects, birds, pterosaurs, and bats have independently evolved the useful capacity of flight. Functionally similar features that have arisen through convergent evolution are analogous, whereas homologous structures or traits have a common origin but can have dissimilar functions. Bird, bat, and pterosaur wings are analogous structures, but their forelimbs are homologous, sharing an ancestral state despite serving different functions.
A phylogenetic tree, phylogeny or evolutionary tree is a graphical representation which shows the evolutionary history between a set of species or taxa during a specific time. In other words, it is a branching diagram or a tree showing the evolutionary relationships among various biological species or other entities based upon similarities and differences in their physical or genetic characteristics. In evolutionary biology, all life on Earth is theoretically part of a single phylogenetic tree, indicating common ancestry. Phylogenetics is the study of phylogenetic trees. The main challenge is to find a phylogenetic tree representing optimal evolutionary ancestry between a set of species or taxa. Computational phylogenetics focuses on the algorithms involved in finding optimal phylogenetic tree in the phylogenetic landscape.
The molecular clock is a figurative term for a technique that uses the mutation rate of biomolecules to deduce the time in prehistory when two or more life forms diverged. The biomolecular data used for such calculations are usually nucleotide sequences for DNA, RNA, or amino acid sequences for proteins. The benchmarks for determining the mutation rate are often fossil or archaeological dates. The molecular clock was first tested in 1962 on the hemoglobin protein variants of various animals, and is commonly used in molecular evolution to estimate times of speciation or radiation. It is sometimes called a gene clock or an evolutionary clock.
In ecology, the competitive exclusion principle, sometimes referred to as Gause's law, is a proposition that two species which compete for the same limited resource cannot coexist at constant population values. When one species has even the slightest advantage over another, the one with the advantage will dominate in the long term. This leads either to the extinction of the weaker competitor or to an evolutionary or behavioral shift toward a different ecological niche. The principle has been paraphrased in the maxim "complete competitors can not coexist".
In phylogenetics and computational phylogenetics, maximum parsimony is an optimality criterion under which the phylogenetic tree that minimizes the total number of character-state changes. Under the maximum-parsimony criterion, the optimal tree will minimize the amount of homoplasy. In other words, under this criterion, the shortest possible tree that explains the data is considered best. Some of the basic ideas behind maximum parsimony were presented by James S. Farris in 1970 and Walter M. Fitch in 1971.
The Syngnathidae is a family of fish which includes seahorses, pipefishes, and seadragons. The name is derived from Ancient Greek: σύν, meaning "together", and γνάθος, meaning "jaw". The fused jaw is one of the traits that the entire family have in common.
Molecular ecology is a field of evolutionary biology that is concerned with applying molecular population genetics, molecular phylogenetics, and more recently genomics to traditional ecological questions. It is virtually synonymous with the field of "Ecological Genetics" as pioneered by Theodosius Dobzhansky, E. B. Ford, Godfrey M. Hewitt, and others. These fields are united in their attempt to study genetic-based questions "out in the field" as opposed to the laboratory. Molecular ecology is related to the field of conservation genetics.
In biology, a substitution model, also called models of DNA sequence evolution, are Markov models that describe changes over evolutionary time. These models describe evolutionary changes in macromolecules represented as sequence of symbols. Substitution models are used to calculate the likelihood of phylogenetic trees using multiple sequence alignment data. Thus, substitution models are central to maximum likelihood estimation of phylogeny as well as Bayesian inference in phylogeny. Estimates of evolutionary distances are typically calculated using substitution models. Substitution models are also central to phylogenetic invariants because they are necessary to predict site pattern frequencies given a tree topology. Substitution models are also necessary to simulate sequence data for a group of organisms related by a specific tree.
A grade is a taxon united by a level of morphological or physiological complexity. The term was coined by British biologist Julian Huxley, to contrast with clade, a strictly phylogenetic unit.
A phylogenetic network is any graph used to visualize evolutionary relationships between nucleotide sequences, genes, chromosomes, genomes, or species. They are employed when reticulation events such as hybridization, horizontal gene transfer, recombination, or gene duplication and loss are believed to be involved. They differ from phylogenetic trees by the explicit modeling of richly linked networks, by means of the addition of hybrid nodes instead of only tree nodes. Phylogenetic trees are a subset of phylogenetic networks. Phylogenetic networks can be inferred and visualised with software such as SplitsTree, the R-package, phangorn, and, more recently, Dendroscope. A standard format for representing phylogenetic networks is a variant of Newick format which is extended to support networks as well as trees.
Computational phylogenetics, phylogeny inference, or phylogenetic inference focuses on computational and optimization algorithms, heuristics, and approaches involved in phylogenetic analyses. The goal is to find a phylogenetic tree representing optimal evolutionary ancestry between a set of genes, species, or taxa. Maximum likelihood, parsimony, Bayesian, and minimum evolution are typical optimality criteria used to assess how well a phylogenetic tree topology describes the sequence data. Nearest Neighbour Interchange (NNI), Subtree Prune and Regraft (SPR), and Tree Bisection and Reconnection (TBR), known as tree rearrangements, are deterministic algorithms to search for optimal or the best phylogenetic tree. The space and the landscape of searching for the optimal phylogenetic tree is known as phylogeny search space.
Ancestral reconstruction is the extrapolation back in time from measured characteristics of individuals to their common ancestors. It is an important application of phylogenetics, the reconstruction and study of the evolutionary relationships among individuals, populations or species to their ancestors. In the context of evolutionary biology, ancestral reconstruction can be used to recover different kinds of ancestral character states of organisms that lived millions of years ago. These states include the genetic sequence, the amino acid sequence of a protein, the composition of a genome, a measurable characteristic of an organism (phenotype), and the geographic range of an ancestral population or species. This is desirable because it allows us to examine parts of phylogenetic trees corresponding to the distant past, clarifying the evolutionary history of the species in the tree. Since modern genetic sequences are essentially a variation of ancient ones, access to ancient sequences may identify other variations and organisms which could have arisen from those sequences. In addition to genetic sequences, one might attempt to track the changing of one character trait to another, such as fins turning to legs.
Phylogenetic comparative methods (PCMs) use information on the historical relationships of lineages (phylogenies) to test evolutionary hypotheses. The comparative method has a long history in evolutionary biology; indeed, Charles Darwin used differences and similarities between species as a major source of evidence in The Origin of Species. However, the fact that closely related lineages share many traits and trait combinations as a result of the process of descent with modification means that lineages are not independent. This realization inspired the development of explicitly phylogenetic comparative methods. Initially, these methods were primarily developed to control for phylogenetic history when testing for adaptation; however, in recent years the use of the term has broadened to include any use of phylogenies in statistical tests. Although most studies that employ PCMs focus on extant organisms, many methods can also be applied to extinct taxa and can incorporate information from the fossil record.
The term phylogenetic niche conservatism has seen increasing use in recent years in the scientific literature, though the exact definition has been a matter of some contention. Fundamentally, phylogenetic niche conservatism refers to the tendency of species to retain their ancestral traits. When defined as such, phylogenetic niche conservatism is therefore nearly synonymous with phylogenetic signal. The point of contention is whether or not "conservatism" refers simply to the tendency of species to resemble their ancestors, or implies that "closely related species are more similar than expected based on phylogenetic relationships". If the latter interpretation is employed, then phylogenetic niche conservatism can be seen as an extreme case of phylogenetic signal, and implies that the processes which prevent divergence are in operation in the lineage under consideration. Despite efforts by Jonathan Losos to end this habit, however, the former interpretation appears to frequently motivate scientific research. In this case, phylogenetic niche conservatism might best be considered a form of phylogenetic signal reserved for traits with broad-scale ecological ramifications. Thus, phylogenetic niche conservatism is usually invoked with regards to closely related species occurring in similar environments.
Catherine H. Graham is an American team leader and senior scientist working on the Biodiversity & Conservation Biology, and the Spatial Evolutionary Ecology research units at the Swiss Federal Institute for Forest, Snow and Landscape Research WSL. From 2003 to 2017 she was an Assistant, Associate, or Full Professor of Ecology and Evolution at the Stony Brook University, and since her appointment at the WSL in 2017 she has maintained adjunct status there. She received both her M.S. degree (1995) and her Ph.D. (2000) from the University of Missouri at St. Louis, and did post-doctoral training at the Jet Propulsion Laboratory and the University of California, Berkeley. She studies biogeography, conservation biology, and ecology. Catherine H. Graham is most noted for her analysis of statistical models to describe species' distributions. This work with Jane Elith is useful in determining changes in biodiversity resulting from human activities. Her paper on niche conservatism with John J. Wiens is also highly cited. They focused on how species' retention of ancestral traits may limit geographic range expansion. In many of her papers, she has sought to unite ecology and evolutionary biology to derive a better understanding of the processes driving species diversity patterns. In particular, she and Paul Fine laid out a framework for interpreting community assembly processes from a phylogenetic approach to quantifying beta diversity.
Phylogenetic inertia or phylogenetic constraint refers to the limitations on the future evolutionary pathways that have been imposed by previous adaptations.
A selection gradient describes the relationship between a character trait and a species' relative fitness. A trait may be a physical characteristic, such as height or eye color, or behavioral, such as flying or vocalizing. Changes in a trait, such as the amount of seeds a plant produces or the length of a bird's beak, may improve or reduce their relative fitness. Changes in traits may accumulate in a population under an ongoing process of natural selection. Understanding how changes in a trait affect fitness helps evolutionary biologists understand the nature of evolutionary pressures on a population.
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