Hubbry Logo
Tree modelTree modelMain
Open search
Tree model
Community hub
Tree model
logo
8 pages, 0 posts
0 subscribers
Be the first to start a discussion here.
Be the first to start a discussion here.
Tree model
Tree model
from Wikipedia
Cladistic representation of the Mayan linguistic family, going back 4000 years. (The numbers represent proposed historical dates in the Common Era).

In historical linguistics, the tree model (also Stammbaum, genetic, or cladistic model) is a model of the evolution of languages analogous to the concept of a family tree, particularly a phylogenetic tree in the biological evolution of species. As with species, each language is assumed to have evolved from a single parent or "mother" language, with languages that share a common ancestor belonging to the same language family.

Popularized by the German linguist August Schleicher in 1853,[1][2] the tree model has been a common method of describing genetic relationships between languages since the first attempts to do so. It is central to the field of comparative linguistics, which involves using evidence from known languages and observed rules of language feature evolution to identify and describe the hypothetical proto-languages ancestral to each language family, such as Proto-Indo-European and the Indo-European languages. However, this is largely a theoretical, qualitative pursuit, and linguists have always emphasized the inherent limitations of the tree model due to the large role played by horizontal transmission in language evolution, ranging from loanwords to creole languages that have multiple mother languages.[1] The wave model was developed in 1872 by Schleicher's student Johannes Schmidt as an alternative to the tree model that incorporates horizontal transmission.[3]

The tree model also has the same limitations as biological taxonomy with respect to the species problem of quantizing a continuous phenomenon that includes exceptions like ring species in biology and dialect continua in language. The concept of a linkage was developed in response and refers to a group of languages that evolved from a dialect continuum rather than from linguistically isolated child languages of a single language.[2]

History

[edit]
Family tree of Biblical tribes

Old Testament and St. Augustine

[edit]

Augustine of Hippo supposed that each of the descendants of Noah founded a nation and that each nation was given its own language: Assyrian for Assur, Hebrew for Heber, and so on.[4] In all he identified 72 nations, tribal founders and languages. The confusion and dispersion occurred in the time of Peleg, son of Heber, son of Shem, son of Noah.[5][6] Augustine made a hypothesis not unlike those of later historical linguists, that the family of Heber "preserved that language not unreasonably believed to have been the common language of the race ... thenceforth named Hebrew." Most of the 72 languages, however, date to many generations after Heber. St. Augustine solves this first problem by supposing that Heber, who lived 430 years, was still alive when God assigned the 72.[7]: 123 

Ursprache, the language of paradise

[edit]

St. Augustine's hypothesis stood without major question for over a thousand years. Then, in a series of tracts, published in 1684, expressing skepticism concerning various beliefs, especially Biblical, Sir Thomas Browne wrote:[8]

"Though the earth were widely peopled before the flood ... yet whether, after a large dispersion, and the space of sixteen hundred years, men maintained so uniform a language in all parts, ... may very well be doubted."

Garden of Eden, home of the Ursprache

By then, discovery of the New World and exploration of the Far East had brought knowledge of numbers of new languages far beyond the 72 calculated by St. Augustine. Citing the Native American languages, Browne suggests the "confusion of tongues at first fell only upon those present in Sinaar at the work of Babel ...." For those "about the foot of the hills, whereabout the ark rested ... their primitive language might in time branch out into several parts of Europe and Asia ...."[9] This is an inkling of a tree. In Browne's view, simplification from a larger aboriginal language than Hebrew could account for the differences in language. He suggests ancient Chinese, from which the others descended by "confusion, admixtion and corruption".[10] Later he invokes "commixture and alteration." [11]

Browne reports a number of reconstructive activities by the scholars of the times: [12]

"The learned Casaubon conceiveth that a dialogue might be composed in Saxon, only of such words as are derivable from the Greek ... Verstegan made no doubt that he could contrive a letter that might be understood by the English, Dutch, and East Frislander ... And if, as the learned Buxhornius contendeth, the Scythian language as the mother tongue runs throughout the nations of Europe, and even as far as Persia, the community on many words, between so many nations, hath more reasonable traduction and were rather derivable from the common tongue diffused through them all, than from any particular nation, which hath also borrowed and holdeth but at second hand."

The confusion at the Tower of Babel was thus removed as an obstacle by setting it aside. Attempts to find similarities in all languages were resulting in the gradual uncovering of an ancient master language from which all the other languages derive. Browne undoubtedly did his writing and thinking well before 1684. In that same revolutionary century in Britain James Howell published Volume II of Epistolae Ho-Elianae, quasi-fictional letters to various important persons in the realm containing valid historical information. In Letter LVIII the metaphor of a tree of languages appears fully developed short of being a professional linguist's view:[13]

"I will now hoist sail for the Netherlands, whose language is the same dialect with the English, and was so from the beginning, being both of them derived from the high Dutch [Howell is wrong here]: The Danish also is but a branch of the same tree ... Now the High Dutch or Teutonick Tongue, is one of the prime and most spacious Maternal Languages of Europe ... it was the language of the Goths and Vandals, and continueth yet of the greatest part of Poland and Hungary, who have a Dialect of hers for their vulgar tongue ... Some of her writers would make this world believe that she was the language spoken in paradise."

The search for "the language of paradise" was on among all the linguists of Europe. Those who wrote in Latin called it the lingua prima, the lingua primaeva or the lingua primigenia. In English it was the Adamic language; in German, the Ursprache or the hebräische Ursprache if one believed it was Hebrew. This mysterious language had the aura of purity and incorruption about it, and those qualities were the standards used to select candidates. This concept of Ursprache came into use well before the neo-grammarians adopted it for their proto-languages. The gap between the widely divergent families of languages remained unclosed.[citation needed]

Indo-European model

[edit]

On February 2, 1786, Sir William Jones delivered his Third Anniversary Discourse to the Asiatic Society as its president on the topic of the Hindus. In it he applied the logic of the tree model to three languages, Greek, Latin and Sanskrit, but for the first time in history on purely linguistic grounds, noting "a stronger affinity, both in the roots of the verbs and in the forms of grammar, than could possibly have been produced by accident; ...." He went on to postulate that they sprang from "some common source, which, perhaps, no longer exists." To them he added Gothic, Celtic and Persian as "to the same family."[14]

Jones did not name his "common source" nor develop the idea further, but it was taken up by the linguists of the times. In the (London) Quarterly Review of late 1813–1814, Thomas Young published a review of Johann Christoph Adelung's Mithridates, oder allgemeine Sprachenkunde ("Mithridates, or a General History of Languages"), Volume I of which had come out in 1806, and Volumes II and III, 1809–1812, continued by Johann Severin Vater. Adelung's work described some 500 "languages and dialects" and hypothesized a universal descent from the language of paradise, located in Kashmir central to the total range of the 500. Young begins by pointing out Adelung's indebtedness to Conrad Gesner's Mithridates, de Differentiis Linguarum of 1555 and other subsequent catalogues of languages and alphabets.[15]

Kashmir (red), Adelung's location of Eden

Young undertakes to present Adelung's classification. The monosyllabic type is most ancient and primitive, spoken in Asia, to the east of Eden, in the direction of Adam's exit from Eden. Then follows Jones' group, still without a name, but attributed to Jones: "Another ancient and extensive class of languages united by a greater number of resemblances than can well be altogether accidental." For this class he offers a name,[16] "Indoeuropean," the first known linguistic use of the word, but not its first known use. The British East India Company was using "Indo-European commerce" to mean the trade of commodities between India and Europe.[17] All the evidence Young cites for the ancestral group are the most similar words: mother, father, etc.

Adelung's additional classes were the Tataric (which would later be known as the disputed family Altaic), the African and the American, which depend on geography and a presumed descent from Eden. Young does not share Adelung's enthusiasm for the language of paradise, and brands it as mainly speculative.[citation needed]

Young's designation, successful in English, was only one of several candidates proposed between 1810 and 1867: indo-germanique (Conrad Malte-Brun, 1810), japetisk (Rasmus Christian Rask, 1815), Indo-Germanisch (Julius Klaproth, 1823), indisch-teutsch (F. Schmitthenner, 1826), sanskritisch (Wilhelm von Humboldt, 1827), indokeltisch (A. F. Pott, 1840), arioeuropeo (Graziadio Isaia Ascoli, 1854), Aryan (Max Müller, 1861) and aryaque (H. Chavée, 1867). These men were all polyglots and prodigies in languages. (Klaproth, for example, the author of the successful German-language candidate, Indo-Germanisch, who criticised Jones for his uncritical method, knew Chinese, Japanese, Tibetan and a number of other languages with their scripts.) The concept of a Biblical Ursprache appealed to their imagination. As hope of finding it gradually died they fell back on the growing concept of common Indo-European spoken by nomadic tribes on the plains of Eurasia, and although they made a good case that this language can be deduced by the methods of comparative linguistics, in fact that is not how they obtained it. It was the one case in which their efforts to find the Ursprache succeeded.[citation needed]

Neogrammarian model

[edit]

The model is due in its most strict formulation to the Neogrammarians. The model relies on earlier conceptions of William Jones, Franz Bopp and August Schleicher by adding the exceptionlessness of the sound laws and the regularity of the process. The linguist perhaps most responsible for establishing the link to Darwinism was August Schleicher.

Schleicher's tree model

That he was comparing his Stammbaum, or family tree of languages, to Darwin's presentation of evolution shortly after that presentation, is proved by the open letter he wrote in 1863 to Ernst Haeckel, published posthumously, however. In 1869, Haeckel had suggested he read Origin of Species.[citation needed]

After reading it Schleicher wrote Die Darwinische Theorie und die Sprachwissenschaft, "Darwinism tested by the Science of Language."[18] In a scenario reminiscent of that between Darwin and Wallace over the discovery of evolution (both discovered it independently), Schleicher endorsed Darwin's presentation, but criticised it for not inserting any species. He then presented a Stammbaum of languages, which, however, was not the first he had published.[citation needed]

The evolution of languages was not the source of Darwin's theory of evolution. He had based that on variation of species, such as he had observed in finches in the Galapagos Islands, who had appeared to be modifications of a common ancestor. Selection of domestic species to produce a new variety also played a role in his conclusions. The first edition of Origin of Species in 1859 discusses the language tree as though de novo under the topic of classification. Darwin criticises the synchronic method devised by Linnaeus, suggesting that it be replaced by a "natural arrangement" based on evolution.[citation needed] He says:[19]

"It may be worth while to illustrate this view of classification, by taking the case of languages. If we possessed a perfect pedigree of mankind, a genealogical arrangement of the races of man would afford the best classification of the various languages now spoken throughout the world; and if all extinct languages, and all intermediate and slowly changing dialects, had to be included, such an arrangement would, I think, be the only possible one. Yet it might be that some very ancient language had altered little, and had given rise to few new languages, whilst others (owing to the spreading and subsequent isolation and states of civilisation of the several races, descended from a common race) had altered much, and had given rise to many new languages and dialects. The various degrees of difference in the languages from the same stock, would have to be expressed by groups subordinate to groups; but the proper or even only possible arrangement would still be genealogical; and this would be strictly natural, as it would connect together all languages, extinct and modern, by the closest affinities, and would give the filiation and origin of each tongue."

Schleicher had never heard of Darwin before Haeckel brought him to Schleicher's attention. He had published his own work on the Stammbaum in an article of 1853, six years before the first edition of Origin of Species in 1859. The concept of descent of languages was by no means new. Thomas Jefferson, a devout linguist himself, had proposed that the continual necessity for neologisms implies that languages must "progress" or "advance."[20] These ideas foreshadow evolution of either biological species or languages, but after the contact of Schleicher with Darwin's ideas, and perhaps Darwin's contact with the historical linguists, Evolution and language change were inextricably linked, and would become the basis for classification. Now, as then, the main problems would be to prove specific lines of descent, and to identify the branch points.[citation needed]

Phylogenetic tree

[edit]

The old metaphor was given an entirely new meaning under the old name by Joseph Harold Greenberg in a series of essays beginning about 1950. Since the adoption of the family tree metaphor by the linguists, the concept of evolution had been proposed by Charles Darwin and was generally accepted in biology. Taxonomy, the classification of living things, had already been invented by Carl Linnaeus. It used a binomial nomenclature to assign a species name and a genus name to every known living organism. These were arranged in a biological hierarchy under several phyla, or most general groups, branching ultimately to the various species. The basis for this biological classification was the observed shared physical features of the species.[citation needed]

Darwin, however, reviving another ancient metaphor, the tree of life, hypothesized that the groups of the Linnaean classification (today's taxa), descended in a tree structure over time from simplest to most complex. The Linnaean hierarchical tree was synchronic; Darwin envisioned a diachronic process of common descent. Where Linnaeus had conceived ranks, which were consistent with the great chain of being adopted by the rationalists, Darwin conceived lineages. Over the decades after Darwin it became clear that the ranks of Linnaeus' hierarchy did not correspond exactly to the lineages. It became the prime goal of taxonomy to discover the lineages and alter the classification to reflect them, which it did under the overall guidance of the Nomenclature Codes, rule books kept by international organizations to authorize and publish proposals to reclassify species and other taxa. The new approach was called phylogeny, the "generation of phyla," which devised a new tree metaphor, the phylogenetic tree. One unit in the tree and all its offspring units were a clade and the discovery of clades was cladistics.[citation needed]

Classification of African language families

Greenberg began writing during a time when phylogenetic systematics lacked the tools available to it later: the computer (computational systematics) and DNA sequencing (molecular systematics). To discover a cladistic relationship researchers relied on as large a number of morphological similarities among species as could be defined and tabulated. Statistically the greater the number of similarities the more likely species were to be in the same clade. This approach appealed to Greenberg, who was interested in discovering linguistic universals. Altering the tree model to make the family tree a phylogenetic tree he said:[21]

"Any language consists of thousands of forms with both sound and meaning ... any sound whatever can express any meaning whatever. Therefore, if two languages agree in a considerable number of such items ... we necessarily draw a conclusion of common historical origin. Such genetic classifications are not arbitrary ... the analogy here to biological classification is extremely close ... just as in biology we classify species in the same genus or high unit because the resemblances are such as to suggest a hypothesis of common descent, so with genetic hypotheses in language."

In this analogy, a language family is like a clade, the languages are like species, the proto-language is like an ancestor taxon, the language tree is like a phylogenetic tree and languages and dialects are like species and varieties. Greenberg formulated large tables of characteristics of hitherto neglected languages of Africa, the Americas, Indonesia and northern Eurasia and typed them according to their similarities. He called this approach "typological classification", arrived at by descriptive linguistics rather than by comparative linguistics.[22]

Dates and glottochronology

[edit]

The comparative method has been used by historical linguists to piece together tree models utilizing discrete lexical, morphological, and phonological data. Chronology can be found but there is no absolute date estimates utilizing this system.

Glottochronology enables absolute dates to be estimated. Shared cognates (cognates meaning to have common historical origin) are calculate divergence times. However the method was found to be later discredited due to the data being unreliable. Due to this historical linguists have trouble with exact age estimation when pinpointing the age of the Indo-European language family. It could range from 4000 BP to 40,000 BP, or anywhere in-between those dates according to Dixon sourced from the rise and fall of language, (Cambridge University Press).[23] As seen in the article here.[24]

Possible solutions for Glottochronology are forthcoming due to computational phylogenetic methods. Techniques such as using models of evolution improves accuracy of tree branch length and topology. There for, using computational phylogenetic methods computational methods enable researchers to analyze linguistic data from evolutionary biology. This further assists in testing theories against each other, such as the Kurgan theory and the Anatolian theory, both claiming origins of Info-European languages.[24]

Computational phylogenetics in historical linguistics

[edit]

The comparative method compares features of various languages to assess how similar one language is to another. The results of such an assessment are data-oriented; that is, the results depend on the number of features and the number of languages compared. Until the arrival of the computer on the historical linguistics landscape, the numbers in both cases were necessarily small. The effect was of trying to depict a photograph using a small number of large pixels, or picture units. The limitations of the Tree Model were all too painfully apparent, resulting in complaints from the major historical linguists.[citation needed]

In the late 20th century, linguists began using software intended for biological classification to classify languages. Programs and methods became increasingly sophisticated. In the early 21st century, the Computational Phylogenetics in Historical Linguistics (CPHL) project, a consortium of historical linguists, received funding from the National Science Foundation to study phylogenies.[25] The Indo-European family is a major topic of study. As of January, 2012, they had collected and coded a "screened" database of "22 phonological characters, 13 morphological characters, and 259 lexical characters," and an unscreened database of more. Wordlists of 24 Indo-European languages are included. Larger numbers of features and languages increase the precision, provided they meet certain criteria. Using specialized computer software, they test various phylogenetic hypotheses for their ability to account for the characters by genetic descent.[citation needed]

Limitations of the model

[edit]

One endemic limitation of the tree model is the very founding presumption on which it is based: it requires a classification based on languages or, more generally, on language varieties. Since a variety represents an abstraction from the totality of linguistic features, there is the possibility for information loss during the translation of data (from a map of isoglosses) into a tree. For example, there is the issue of dialect continua. They provide varieties that are not unequivocally one language or another but contain features characteristic of more than one. The issue of how they are to be classified is similar to the issue presented by ring species to the concept of species classification in biology.[citation needed]

The limitations of the tree model, in particular its inability to handle the non-discrete distribution of shared innovations in dialect continua, have been addressed through the development of non-cladistic (non-tree-based) methodologies. They include the Wave model; and more recently, the concept of linkage.[3]

An additional limitation of the tree model involves mixed and hybrid languages, as well as language mixing in general since the tree model allows only for divergences. For example, according to Zuckermann (2009:63),[26] "Israeli", his term for Modern Hebrew, which he regards as a Semito-European hybrid, "demonstrates that the reality of linguistic genesis is far more complex than a simple family tree system allows. 'Revived' languages are unlikely to have a single parent."

Perfect phylogenies

[edit]

The purpose of phylogenetic software is to generate cladograms, a special kind of tree in which the links only bifurcate; that is, at any node in the same direction only two branches are offered. The input data is a set of characters that can be assigned states in different languages, such as present (1) or absent (0). A language therefore can be described by a unique coordinate set consisting of the state values for all of the characters considered. These coordinates can be like each other or less so. Languages that share the most states are most like each other.[citation needed]

The software massages all the states of all the characters of all the languages by one of several mathematical methods to accomplish a pairwise comparison of each language with all the rest. It then constructs a cladogram based on degrees of similarity; for example, hypothetical languages, a and b, which are closest only to each other, are assumed to have a common ancestor, a-b. The next closest language, c, is assumed to have a common ancestor with a-b, and so on. The result is a projected series of historical paths leading from the overall common ancestor (the root) to the languages (the leaves). Each path is unique. There are no links between paths. Every leaf and node have one and only one ancestor. All the states are accounted for by descent from other states. A cladogram that conforms to these requirements is a perfect phylogeny.[27]

At first there seemed to be little consistency of results in trials varying the factors presumed to be relevant. A new cladogram resulted from any change, which suggested that the method was not capturing the underlying evolution of languages but only reflecting the extemporaneous judgements of the researchers. In order to find the factors that did bear on phylogeny the researchers needed to have some measure of the accuracy of their results; i.e., the results needed to be calibrated against known phylogenies. They ran the experiment using different assumptions looking for the ones that would produce the closest matches to the most secure Indo-European phylogenies. Those assumptions could be used on problem areas of the Indo-European phylogeny with greater confidence.[citation needed]

To obtain a reasonably valid phylogeny, the researchers found they needed to enter as input all three types of characters: phonological, lexical and morphological, which were all required to present a picture that was sufficiently detailed for calculation of phylogeny. Only qualitative characters produced meaningful results. Repeated states were too ambiguous to be correctly interpreted by the software; therefore characters that were subject to back formation and parallel development, which reverted a character to a prior state or adopted a state that evolved in another character, respectively, were screened from the input dataset.[28]

Perfect phylogenetic networks

[edit]
A phylogenetic network, one of many posited by the CPHL. The phylogenetic tree appear in black lines. The contact edges are the red lines. Here there are three, the most parsimonious number required to generate a feasible network for Indo-European.

Despite their care to code the best qualitative characters in sufficient numbers, the researchers could obtain no perfect phylogenies for some groups, such as Germanic and Albanian within Indo-European. They reasoned that a significant number of characters, which could not be explained by genetic descent from the group's calculated ancestor, were borrowed. Presumably, if the wave model, which explained borrowing, were a complete explanation of the group's characters, no phylogeny at all could be found for it. If both models were partially effective, then a tree would exist, but it would need to be supplemented by non-genetic explanations. The researchers therefore modified the software and method to include the possibility of borrowing.[29]

The researchers introduced into the experiment the concept of the interface, or allowed boundary over which character states would flow. A one-way interface, or edge, existed between a parent and a child. If only one-way edges were sufficient to explain the presence of all the states in a language, then there was no need to look beyond the perfect phylogeny. If not, then one or more contact edges, or bidirectional interfaces, could be added to the phylogeny. A language therefore might have more than one source of states: the parent or a contact language.[citation needed]

A tree so modified was no longer a tree as such: there could be more than one path from root to leaf. The researchers called this arrangement a network. The states of a character still evolved along a unique path from root to leaf, but its origin could be either the root under consideration or a contact language. If all the states of the experiment could be accounted for by the network, it was termed a perfect phylogenetic network.[30]

Compatibility and feasibility

[edit]

The generation of networks required two phases. In the first phase, the researchers devised a number of phylogenies, called candidate trees, to be tested for compatibility. A character is compatible when its origin is explained by the phylogeny generated.[31] In a perfect phylogeny, all the characters are compatible and the compatibility of the tree is 100%. By the principle of parsimony, or Occam's razor, no networks are warranted. Candidate trees were obtained by first running the phylogeny-generation software using the Indo-European dataset (the strings of character states) as input, then modifying the resultant tree into other hypotheses to be tested.[citation needed]

None of the original candidate trees were perfect phylogenies, although some of the subtrees within them were. The next phase was to generate networks from the trees of highest compatibility scores by adding interfaces one at a time, selecting the interface of highest compatibility, until sufficiency was obtained; that is, the compatibility of the network was highest. As it turned out, the number of compatible networks generated might vary from none to over a dozen. However, not all the possible interfaces were historically feasible. Interfaces between some languages were geographically and chronologically not very likely. Inspecting the results, the researchers excluded the non-feasible interfaces until a list of only feasible networks remained, which could be arranged in order of compatibility score.[citation needed]

Most feasible network for Indo-European

[edit]

The researchers began with five candidate trees for Indo-European, lettered A-E, one generated from the phylogenetic software, two modifications of it and two suggested by Craig Melchert, a historical linguist and Indo-Europeanist. The trees differed mainly in the placement of the most ambiguous group, the Germanic languages, and Albanian, which did not have enough distinctive characters to place it exactly. Tree A contained 14 incompatible characters; B, 19; C, 17; D, 21; E,18. Trees A and C had the best compatibility scores. The incompatibilities were all lexical, and A's were a subset of C's.[32]

Subsequent generation of networks found that all incompatibilities could be resolved with a minimum of three contact edges except for Tree E. As it did not have a high compatibility, it was excluded. Tree A had 16 possible networks, which a feasibility inspection reduced to three. Tree C had one network, but as it required an interface to Baltic and not Slavic, it was not feasible.[33]

Tree A, the most compatible and feasible tree, hypothesizes seven groups separating from Proto-Indo-European between about 4000 BC and 2250 BC, as follows.[34]

  • The first to separate was Anatolian, about 4000 BC.
  • Tocharian followed at about 3500 BC.
  • Shortly thereafter, about 3250, Proto-Italo-Celtic (western Indo-European) separated, becoming Proto-Italic and Proto-Celtic at about 2500 BC.
  • At about 3000, Proto-Albano-Germanic separated, becoming Albanian and Proto-Germanic at about 2000.
  • At about 3000 Proto-Greco-Armenian (southern Indo-European) divided, becoming Proto-Greek and Proto-Armenian at about 1800.
  • Balto-Slavic appeared about 2500, dividing into Proto-Baltic and Proto-Slavic at about 1000.
  • Finally, Proto-Indo-European became Proto-Indo-Iranian (eastern Indo-European) at about 2250.

Trees B and E offer the alternative of Proto-Germano-Balto-Slavic (northern Indo-European), making Albanian an independent branch. The only date for which authors vouch is the last, based on the continuity of the Yamna culture, the Andronovo Culture and known Indo-Aryan speaking cultures. All others are described as "dead reckoning."[35]

Given the phylogeny of best compatibility, A, three contact edges are required to complete the compatibility. This is group of edges with the fewest borrowing events:[35]

  • First, an edge between Proto-Italic and Proto-Germanic, which must have begun after 2000, according to the dating scheme given.
  • A second contact edge was between Proto-Italic and Proto-Greco-Armenian, which must have begun after 2500.
  • The third contact edge is between Proto-Germanic and Proto-Baltic, which must have begun after 1000.

Tree A with the edges described above is described by the authors as "our best PPN."[36] In all PPNs, it is clear that although the initial daughter languages became distinct in relative isolation, the later evolution of the groups can be explained only by evolution in proximity to other languages with which an exchange takes place by the wave model.

See also

[edit]

Notes

[edit]

Bibliography

[edit]
[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
In , the tree model (German: Stammbaumtheorie, "family tree theory") is a model of the analogous to a , particularly a . It posits that s develop from a common ancestral through successive binary splits, with daughter languages diverging independently and without significant mixing or borrowing between branches after separation. The model was first systematically applied by the German linguist in the mid-19th century to the Indo-European , providing a visual and hierarchical representation of genetic relationships among languages. It remains a foundational tool in for reconstructing proto-languages and classifying , though it is often complemented by other approaches to account for .

Overview

Definition and core principles

The tree model, also known as the Stammbaumtheorie or family-tree model, is a theoretical framework in that represents the evolution of languages as a process of from a common ancestral through successive binary splits, forming distinct branches without substantial horizontal influences after separation. This model posits that languages descend genetically from a shared origin, emphasizing inheritance and internal change as the primary drivers of diversification. At its core, the tree model operates on the principle of unidirectional descent, where languages evolve linearly from a parent in a single direction, with no reversion to prior states. A key assumption is that, following , branches develop in isolation, akin to in biological , with minimal convergence, borrowing, or external contact between them to maintain clear genetic boundaries. This isolation ensures that shared innovations—systematic changes unique to subgroups—serve as the principal criterion for establishing relationships, mirroring cladistic methods in . Visually, the tree model is depicted as a branching diagram, with the root representing the proto-language, internal nodes indicating intermediate proto-languages at points of split, branches symbolizing divergent lineages, and leaves denoting modern or attested languages. For a hypothetical language family, consider Proto-X splitting into Proto-Y and Proto-Z; Proto-Y then branches into Modern Y1 and Y2, while Proto-Z diverges into Z1 and Z2, illustrating independent evolution post-split without inter-branch mixing. This structure highlights the model's focus on vertical transmission over areal diffusion.

Relation to other models of language change

The tree model, also known as the Stammbaumtheorie, posits language diversification through discrete, hierarchical splits from a common proto-language, assuming isolation and divergence among descendant communities. In contrast, the wave model (Wellentheorie) conceptualizes change as the diffusion of innovations across a continuous dialect network, allowing for overlapping isoglosses and convergence through areal contact rather than strict separation. This fundamental difference highlights the tree model's emphasis on vertical inheritance and binary branching, while the wave model better accommodates horizontal transfer and gradual fragmentation in interconnected speech areas. The tree model serves as the structural foundation for the in , enabling the reconstruction of proto-languages by identifying regular sound correspondences and exclusively shared innovations within . Through this integration, the model facilitates the positing of ancestral forms and hierarchies, providing a falsifiable framework for tracing genealogical relationships. However, critics argue that rigidly applying the tree model can constrain the 's flexibility in handling non-tree-like patterns, such as those arising from prolonged contact. Modern linguistics often employs hybrid approaches that integrate the tree and wave models within areal linguistics, recognizing both vertical descent and horizontal diffusion to model complex diversification patterns more realistically. For instance, methods like historical glottometry combine the comparative method's precision with wave-inspired quantification of subgroup cohesiveness and intersecting innovations, allowing for visualizations that capture both nested hierarchies and linkages without assuming exclusive splits. These integrations address the limitations of pure models by incorporating areal influences, though they require extensive data on innovations to delineate boundaries effectively. Among its strengths, the tree model offers a clear, hierarchical representation for subgrouping languages, aiding in the systematic classification of families and the detection of inherited features over borrowed ones. It excels in scenarios of clear social divergence, providing a straightforward visual and analytical tool for reconstruction. Conversely, its disadvantages include an oversimplification of multilingualism and contact phenomena, as it struggles to represent dialect continua or reconvergence, potentially leading to inaccurate genealogies in diverse linguistic ecologies.

Historical Development

Early religious and philosophical origins

The narrative of the in Genesis 11:1-9 portrays a unified humanity speaking a single until divine intervention confuses their speech, resulting in linguistic diversification and dispersion across the , serving as an early for languages branching from a common origin. This biblical account influenced pre-modern conceptions of language descent by positing a primordial unity shattered by , with the resulting multiplicity echoing a tree-like spread from one root source. Early interpreters viewed the event not merely as etiological but as explaining why languages form distinct families, foreshadowing later phylogenetic models without empirical methodology. St. , in his late 4th-century work , articulated a theological framework for origins rooted in divine creation, positing that human speech derives from God's perfect communication and serves as a for understanding scripture. He emphasized Hebrew's primacy as the closest to the original, preserved post-Babel through the lineage of , while acknowledging that introduced ambiguity and imperfection into linguistic expression over time. Augustine's ideas framed evolution as a degeneration from an Edenic ideal, where words once perfectly mirrored divine intent but now require interpretive effort due to human fallenness, linking biblical authority to the stability of sacred tongues. By the , the concept of Ursprache—a primal or original language—emerged in European thought, often tied to the "language of paradise" as depicted in biblical narratives of Eden and Babel, envisioning it as the undivided ancestor from which all others diverged. Thinkers invoked Genesis to argue that this , typically identified with Hebrew, represented linguistic purity before postlapsarian fragmentation, influencing debates on whether modern tongues retained echoes of this sacred root. This notion bridged theology and emerging , portraying language history as a degenerative stemming from a paradisiacal source, though without systematic reconstruction methods. Philosophical precursor Gottfried Wilhelm Leibniz, in his 1710 speculations, extended these ideas by proposing a universal proto-language as the common ancestor of all human tongues, suggesting that comparative study of linguistic structures could trace back to this origin much like a genealogical tree. Drawing on biblical unity before Babel, Leibniz viewed languages as historical artifacts revealing deeper connections among peoples, advocating for a "universal characteristic" to revive this lost perfection. His framework anticipated systematic linguistics by emphasizing descent and divergence, though grounded in philosophical rather than empirical observation.

19th-century linguistic foundations

The foundations of the tree model in emerged in the late 18th and early 19th centuries through comparative studies of , beginning with Sir William Jones's observation of striking similarities among , Greek, and Latin that suggested descent from a common ancestral language. In his Third Anniversary Discourse delivered to the Asiatick Society on February 2, 1786, Jones proposed that these languages shared a familial relationship, positing that "no could examine the , Greek, and Latin, without believing them to have sprung from some common source, which, perhaps, no longer exists." This insight, drawn from Jones's firsthand study of texts in , marked a pivotal shift toward empirical comparative philology, though he initially framed it within a biblical context of a pre-Babel Ursprache. Building on Jones's hypothesis, Franz Bopp systematized the in his 1816 monograph , which analyzed grammatical structures—particularly verb conjugations—across these languages to demonstrate their genetic affinities. Bopp's work established key principles of reconstruction by identifying systematic correspondences in inflectional morphology, laying the groundwork for viewing language evolution as branching rather than mere borrowing. Concurrently, Danish philologist advanced the evidence for regular sound changes in his 1818 Undersøgelse om det gamle Nordiske eller Islandske Sprogs Oprindelse, where he documented consistent phonetic correspondences between Icelandic (and other ) and Indo-European counterparts, such as the shift from Proto-Indo-European p to Germanic f (e.g., Latin pater vs. Old Norse *). Jacob further formalized these patterns in the second volume of his Deutsche Grammatik (1822), articulating what became known as : a set of regular consonant shifts distinguishing Germanic from other Indo-European branches, including p, t, k to f, þ, h (e.g., Latin pēs vs. English foot). These discoveries provided empirical support for divergence through predictable sound laws, essential to the tree model's assumption of bifurcating lineages. August Schleicher synthesized these developments by introducing the first visual representation of the tree model in 1853, publishing a Stammbaum () diagram in his article "Die ersten Spaltungen des indogermanischen Urvolkes," which illustrated the branching from a reconstructed proto-form. This genealogical diagram depicted Indo-European as diverging into major groups like , Slavic, and Teutonic, emphasizing isolation and independent evolution post-separation. By mid-century, scholars increasingly rejected the divine Ursprache tied to biblical narratives in favor of a naturalistic Proto-Indo-European (PIE), a prehistoric reconstructed through comparative rather than theological assumption, reflecting the era's embrace of scientific over religious origins.

Neogrammarian formulation and Stammbaumtheorie

The Neogrammarian school emerged in the late 1870s at the University of , led by linguists such as August Leskien, Hermann Paul, and Karl Brugmann, who sought to establish on empirical and psychological foundations. Central to their approach was the principle that sound changes operate mechanically and without exceptions, a doctrine first articulated by Leskien in his 1876 study on in Old Lithuanian, where he stated that "sound laws admit no exceptions." This tenet, elaborated in Paul's Principien der Sprachgeschichte (1880) and the 1878 declaration by Osthoff and Brugmann, rejected earlier explanations of irregularities as analogical or sporadic, insisting instead on regular, phonetic processes governed by universal laws. Building on August Schleicher's earlier genealogical diagrams from the 1850s and 1860s, the Neogrammarians formalized the Stammbaumtheorie (family tree theory) as a strict model of descent, emphasizing binary branching to represent from a common without significant horizontal influences. Although Schleicher had introduced the concept, the Neogrammarians refined it by integrating their exceptionless sound laws to explain formation, viewing languages as diverging through inherited innovations rather than diffusion. Schmidt's 1872 coinage of the term Stammbaumtheorie in critiquing its rigidity further highlighted its role, but the school adopted and sharpened it for precise phylogenetic reconstruction. A landmark in this formulation was Brugmann's Grundriss der vergleichenden Grammatik der indogermanischen Sprachen (1886), the first volume of which detailed phonological sound laws and applied the tree model to Indo-European subgrouping, such as positing shared innovations like the to delineate branches. This work rejected borrowing as a primary driver of change, attributing most resemblances to vertical inheritance and using shared sound shifts—such as the consistent treatment of proto-Indo-European in centum languages—to define subgroups like Germanic and Italic. By prioritizing diagnostic innovations over retentions, the Neogrammarians provided a methodological framework for tree-based classification that remains foundational in .

Applications in Historical Linguistics

Indo-European language family

The tree model has been instrumental in the reconstruction of , the hypothetical ancestor of the , by positing a hierarchical divergence from a common proto-language into distinct branches, allowing linguists to apply the systematically. Through this approach, scholars compare cognates across descendant languages to identify regular sound correspondences and reconstruct proto-forms, assuming that innovations occurred after branch separations. A canonical example is the PIE word for "father," *ph₂tḗr, derived from correspondences such as Latin pater, Greek patḗr, pitḗ, and fæder, where the initial *p- remains in Italic and Indo-Iranian branches but shifts to *f- in Germanic via . In the Indo-European family tree, early divergences include the Anatolian branch (e.g., Hittite) and Tocharian, which split off before major internal developments, preserving archaic features like the retention of PIE laryngeals in Anatolian. These early branches support the tree model's vertical inheritance, as their forms show fewer shared innovations with later groups. A key internal division is the centum-satem split, where centum languages (e.g., Germanic, Italic, Celtic, Greek) preserved the velar stops (e.g., PIE *ḱ as k in Latin centum "hundred"), while satem languages (e.g., Indo-Iranian, Balto-Slavic) palatalized them (e.g., satəm). This reflects an early areal or branching distinction rather than a strict binary split, but it aligns with the tree by marking post-PIE innovations in eastern branches. Subgrouping within Indo-European further exemplifies the tree model's efficacy, with branches defined by shared innovations post-divergence from . The Germanic branch, encompassing languages like English, German, and Gothic, is unified by innovations such as the First Germanic Consonant Shift (), which systematically altered stops (e.g., *p > f, as in *ph₂tḗr > English father). Similarly, the Romance branch, descending from , shares vowel reductions and nasal assimilations (e.g., Latin centum > Italian cento), distinguishing it from other Italic relatives. The Slavic branch, including Russian, Polish, and , coheres through common palatalizations and the loss of nasal vowels (e.g., *h₁n̥dʰér > Slavic *inˀterъ "under"). These innovations, absent in other branches, confirm the tree's branching structure. The tree model's empirical successes in Indo-European linguistics lie in its ability to explain regular sound shifts as branch-specific exceptions to phonology, enabling precise reconstructions. For instance, the Neogrammarian hypothesis of exceptionless sound laws underpins this, as seen in the consistent application of in Italic (e.g., PIE *swésōr > Latin soror "sister") versus its absence elsewhere. Such patterns across branches have facilitated the reconstruction of over 3,000 PIE roots, demonstrating the model's robustness for in this family.

Other language families and phylogenetic trees

The tree model, which posits vertical descent with minimal horizontal influence, has been applied to numerous language families outside the Indo-European domain, often requiring adaptations to account for extensive geographic spread and contact. In the Austronesian family, encompassing over 1,200 languages spoken and , linguist Robert Blust developed a comprehensive subgrouping based on shared innovations and regular sound correspondences, establishing a . This includes nine primary Formosan subgroups in and a major Malayo-Polynesian branch further divided into Western Malayo-Polynesian (with 20–25 internal groups), Central Malayo-Polynesian, and the Oceanic subgroup, reflecting proto-language divergence through tree-like inheritance. Blust's framework, detailed in works such as his 1977 analysis of Proto-Malayo-Polynesian and 1999 Formosan , demonstrates the model's utility for reconstructing dispersal patterns from a Taiwanese , despite challenges from prolonged contact in western branches. In African linguistics, the tree model facilitated the classification of , a expansive subgroup of the Niger-Congo family comprising around 500 languages across . Malcolm 1948 monograph proposed an initial tree-based taxonomy dividing Bantu into 16 geographic zones (A–P), later refined into genetic s using lexical comparisons and phonological criteria to trace expansions from a West-Central African origin. This structure emphasized bifurcating descent lines, such as the Northwest (A–C) and Central (D–H) branches, aligning with the Stammbaumtheorie by prioritizing inherited features over areal diffusion. approach, published by , provided a foundational phylogenetic scaffold for understanding Bantu migrations and diversification, influencing subsequent revisions like Meeussen's 1975 updates. For Eurasian families like Uralic and the proposed Altaic, tree models have been employed amid ongoing debates over genetic unity. The Uralic family, including Finnish, Hungarian, and Sami languages spoken from to , is routinely subgrouped via phylogenetic trees derived from distributions and reconstructed proto-forms, as in Honkola et al.'s 2013 Bayesian analysis estimating divergence times for its Finno-Ugric and Samoyedic branches. Despite controversies over deeper connections, such as potential links to Yukaghir, the model supports a binary-branching tree from Proto-Uralic around 4,000–6,000 years ago. Similarly, for the controversial Altaic hypothesis—encompassing Turkic, Mongolic, Tungusic, and sometimes Koreanic and Japonic—scholars have applied tree structures to individual subfamilies, like Ramstedt's early 20th-century proposals for a unified stemma, even as genetic relatedness remains unproven due to insufficient regular correspondences. Vovin's 2016 overview highlights how tree-based subgrouping persists for Turkic and Mongolic internals, treating Altaic as a rather than a strict genetic unit. In isolate-poor families, where languages form dense clusters with limited unclassified remnants, has emerged as a key adaptation for tree construction, quantifying relatedness through percentages of shared basic vocabulary (e.g., Swadesh lists) to infer branching topologies. This method, pioneered by Swadesh in the and refined in projects like the Automated Similarity Judgment Program (ASJP), excels in large families such as Austronesian or Niger-Congo by generating distance matrices convertible to trees via neighbor-joining algorithms, bypassing exhaustive phonological reconstruction. For instance, Serva and Petroni (2008) applied to Uralic data, yielding trees congruent with traditional subgroupings and highlighting its role in handling contact-heavy environments. Such approaches prioritize rapid, data-driven phylogenies, though they complement rather than replace the for validation.

Glottochronology and dating methods

, a quantitative method for estimating the time of language divergence, was pioneered by in the 1950s. Swadesh proposed using standardized lists of 100 to 200 basic vocabulary items—such as body parts, numerals, and common natural phenomena—assumed to be relatively stable across languages due to their universal relevance and resistance to borrowing. The core assumption is that the rate of retention of these cognates (shared ancestral words) in daughter languages follows a constant , calibrated at approximately 14% loss per millennium, or an 86% retention rate. This approach draws an analogy to in physics, allowing linguists to calculate divergence times from the percentage of shared cognates between compared languages. The foundational equation for divergence time tt (in millennia) is derived from the retention model: t=ln(c)2λt = \frac{-\ln(c)}{2 \lambda} where cc is the observed retention rate between two s, and λ\lambda is the decay constant (typically λ=ln(0.86)0.151\lambda = -\ln(0.86) \approx 0.151 for a 1000-year period, adjusted from empirical data). The factor of 2 accounts for the symmetric from a common ancestor. This formula, formalized by Robert B. Lees based on Swadesh's data, enables the assignment of approximate dates to branch points in a language tree by comparing pairwise lexical similarities. In applications to , has been used to date key nodes in family trees, such as estimating the breakup of Proto-Indo-European around 4500 BCE based on counts from its descendant languages like , Greek, and Latin. Such estimates provide a temporal framework for correlating linguistic divergence with archaeological or cultural events, though results vary depending on the word list and calibration. However, significant critiques have emerged regarding the stability of Swadesh's word lists; studies have shown that retention rates are not universally constant and can fluctuate due to cultural differences, borrowing influences, or semantic shifts, undermining the method's reliability for depths. As an alternative to traditional , Russell D. Gray and Quentin D. Atkinson introduced a Bayesian phylogenetic approach in 2003, which models lexical evolution on pre-constructed trees using methods to infer times. This framework incorporates uncertainty in identification and rate variation, while allowing integration of external calibrations like archaeological dates, yielding more robust estimates—for instance, placing the Indo-European origin around 7800–9800 years ago in support of the .

Computational Approaches

Phylogenetic tree construction in linguistics

Phylogenetic tree construction in applies computational algorithms, borrowed and adapted from , to infer hierarchical relationships among languages using data such as sets and sound correspondences. sets, which are homologous words across languages sharing a common etymological origin, serve as primary input, often encoded as binary matrices indicating presence or absence in each language. Sound correspondences, representing systematic phonetic shifts (e.g., in ), provide character-based data to model evolutionary changes. These inputs differ from biological sequences by capturing discrete, culturally influenced traits rather than continuous . The construction process follows structured steps tailored to linguistic data. First, lexical items from standardized wordlists (e.g., Swadesh lists) are aligned across languages to detect potential cognates and correspondences, often using automated tools for phonetic alignment. A is then computed, measuring divergence via metrics like normalized for sound strings or shared cognate proportions. Finally, tree optimization algorithms build and refine the to best explain the data, potentially incorporating rooting via outgroup languages. Recent developments as of 2025 include advanced methods for automated cognate detection beyond traditional approaches and systematic assessments of limitations in cognate-based phylogenetic inference. Among distance-based methods, neighbor-joining (NJ), introduced by Saitou and Nei (1987), is widely adapted for by iteratively clustering languages based on minimized evolutionary distances, yielding an unrooted that can be rerooted for interpretation. NJ has proven effective for reconstructing topologies in families like Austronesian, where cognate-based distances highlight branching patterns. Character-based approaches, such as maximum parsimony (MP), evaluate trees by minimizing the number of inferred changes in discrete states (e.g., presence of a sound correspondence), treating linguistic evolution as a series of parsimonious transformations. Adaptations of MP for handle cognate polymorphisms by favoring majority states to reduce ambiguity in ancestral reconstructions. Specialized software supports these methods in linguistic contexts. offers command-line tools for NJ, MP, and distance calculations on cognate matrices, enabling rapid prototyping of trees from lexical data. BEAST, a Bayesian framework, extends these by sampling trees probabilistically, incorporating priors on substitution rates derived from models. Unlike biological , which often assumes constant molecular clocks and vertical inheritance, linguistic applications must accommodate irregular changes—such as sporadic analogical shifts or conditioned exceptions to regular sound laws—through relaxed clock models or multistate characters that permit higher variability in change rates.

Perfect phylogenies and compatibility

In historical linguistics, a perfect phylogeny refers to an evolutionary tree model in which each character state—such as a specific sound change or innovation—arises exactly once along the branches, with no reversals, convergences, or parallel evolutions (). This ideal assumes a strictly vertical transmission of traits from to descendant languages, aligning with the core tenets of the family tree model. Perfect phylogenies provide a stringent test for whether observed linguistic data can be explained without horizontal influences like borrowing. The compatibility problem addresses whether a given set of characters (e.g., phonological or morphological innovations) can be simultaneously explained by a single perfect phylogeny without conflicts. A key result is Buneman's 1971 theorem, which states that for binary characters (two states per character), a perfect phylogeny exists every pair of characters is compatible—meaning their state distributions do not form an incompatible pattern, such as the "forbidden " where two characters cross-cut each other in a way that requires multiple changes. This pairwise compatibility condition extends to global compatibility under the theorem, enabling efficient verification for common in linguistic analyses of sound laws. In linguistic applications, perfect phylogenies have been tested on datasets of Indo-European languages using characters derived from established sound laws and lexical innovations. For instance, an analysis of 24 Indo-European languages using 333 lexical characters, 22 phonological, and 15 morphological characters found substantial but incomplete compatibility, with no perfect phylogeny for the full and 18 incompatible characters; the largest compatible supported a tree that aligns with some traditional subgroupings such as Italic and Indo-Iranian, though Germanic placement is problematic. However, full perfect fit is rare in real linguistic data, as conflicts often arise from borrowing or incomplete resolution of shared innovations, necessitating subsets of characters for construction. Algorithms for solving the compatibility problem typically construct a partition intersection graph (PIG), where vertices represent character-state pairs and edges connect pairs that co-occur in at least one . A perfect phylogeny exists if the PIG is chordal (every cycle of length four or more has a chord) or admits a chordal completion consistent with the data; this can be checked via enumeration of potential maximal cliques to identify minimal triangulations. For binary cases, Buneman's theorem allows simpler pairwise checks, while multi-state extensions (relevant for linguistic characters with more than two outcomes) use clique-based optimizations to find compatible subsets efficiently.

Phylogenetic networks as extensions

Phylogenetic networks extend the tree model by incorporating reticulation events, such as language borrowing or contact-induced changes, which violate the strict bifurcating structure of trees. These networks are typically represented as directed acyclic graphs (DAGs) where nodes can have multiple parents, allowing hybridization nodes to model the fusion of linguistic features from different lineages. This approach addresses the limitations of pure tree models in capturing horizontal transfer, a common phenomenon in language evolution where vocabulary or structural elements are borrowed between related or unrelated languages. One prominent type of phylogenetic network is the Neighbor-net algorithm, introduced by Bryant and Moulton in 2004, which constructs planar networks from distance matrices to visualize splits and fusions in data. Neighbor-net extends the neighbor-joining method by agglomeratively building a network that displays conflicting signals in evolutionary distances, such as those arising from borrowing, without assuming a tree-like history. In , this method has been applied to continua and families to highlight reticulate patterns, producing splits graphs that reveal non-tree-like relationships more intuitively than unresolved polytomies in trees. The transition to becomes necessary when linguistic fail to satisfy the compatibility conditions required for perfect phylogenies, as incompatible character states—often due to borrowing—cannot be explained by a single . In such cases, resolve these conflicts by permitting reticulation, providing a more accurate representation of evolutionary history without discarding . This extension builds directly on tree-based compatibility tests, allowing researchers to retain the vertical framework while accommodating horizontal influences. In , phylogenetic networks have been applied to model substrate influences and borrowing within the Indo-European () language family, particularly in cases involving and their contacts with pre-IE populations in the . For instance, network analyses of IE lexical data have identified hidden borrowing events, estimating that approximately 8% of basic vocabulary cognates involve horizontal transfer, which helps reconstruct contact scenarios like those affecting early Anatolian branches through substrate effects from local non-IE languages. These applications demonstrate how networks enhance tree models by quantifying reticulation's role in family diversification.

Limitations and Criticisms

Issues with borrowing and horizontal transfer

The tree model in posits a strictly vertical descent of languages from common ancestors, akin to a , but this assumption is undermined by extensive borrowing, where linguistic elements are transferred horizontally between unrelated or distantly related languages through contact. Lexical borrowing, in particular, introduces foreign words into a language's , often comprising a substantial portion; for instance, English contains approximately 41% words overall, with significant contributions from French following the in 1066, illustrating how conquest and cultural exchange can infuse up to 30% of a language's from a single source. Structural diffusion, such as calques (loan translations), further complicates tree-based reconstructions by altering syntax and morphology without direct lexical replacement, as seen in expressions like English "superman" borrowed from German "." These processes violate the model's isolation premise, leading to reticulate phylogenies where languages exhibit mixed ancestries. Horizontal transfer in linguistics draws an analogy to lateral gene transfer in , where genetic material moves between rather than solely through vertical , similarly allowing linguistic features to spread across language boundaries via prolonged contact. In creoles and pidgins, this transfer is pronounced, as these contact languages emerge from multilingual settings where substrates, superstrates, and adstrates contribute elements non-hierarchically; for example, shows parallel trajectories of genetic and linguistic admixture, with cotransmission of features from and African languages reflecting demographic mixing rather than tree-like descent. Such scenarios highlight how horizontal influences can dominate in high-contact environments, obscuring genealogical signals and rendering pure tree models inadequate for capturing evolutionary dynamics. Detecting borrowing remains challenging, as methods rely on distinguishing stable core vocabulary—basic terms for body parts, numerals, and pronouns—from more permeable cultural loans, with the former exhibiting higher resistance due to entrenchment in frequent usage and cognitive salience. Studies confirm an inverse relationship between a concept's coreness (measured by and stability) and its borrowability, as core items are less likely to be replaced, allowing phylogenies to use Swadesh lists for vertical signals while areal features, like shared or , indicate horizontal diffusion. However, undetected loans in datasets can skew tree inferences, with up to 31% of cognate sets in Indo-European data potentially borrowed. A prominent is the , where languages from diverse families—Indo-European (e.g., Albanian, Greek, Slavic) and Romance (Romanian)—converge on shared features like postposed definite articles, evidential mood, and infinitive loss due to millennia of in the region, overriding genealogical trees. This areal convergence, identified as the first documented , demonstrates multilateral horizontal transfer without a dominant donor, challenging the Indo-European tree's purity and emphasizing contact-induced change over isolation.

Feasibility and testing in real data

The feasibility of the tree model in is evaluated through statistical testing frameworks that assess how well linguistic data conform to a bifurcating structure versus alternatives accommodating horizontal transfer. Likelihood ratio tests compare the fit of strict tree models to those incorporating reticulation, such as phylogenetic networks, by calculating the difference in log-likelihoods between models; significant differences indicate poor tree fit due to borrowing or convergence. Bootstrap support, obtained by resampling datasets (typically 1,000–10,000 iterations) and reconstructing trees from each, measures robustness, with values above 70% often considered reliable but lower thresholds highlighting in contact-heavy regions. These methods, rooted in , have been applied to lexical and structural data to quantify the model's viability. In real-world datasets, the tree model demonstrates variable success, particularly in the Austronesian family, where analyses of lexical cognates from over 200 languages support major expansions like the "Out of " hypothesis but falter in contact zones such as and . For instance, Bayesian phylogenetic reconstructions recover about 70% congruence with established subgroups in core Oceanic branches, yet fail to resolve relationships in Melanesian areas due to extensive borrowing and dialect continua, resulting in low bootstrap support (often below 50%) for affected nodes. This partial viability underscores the model's utility for isolated evolutions but its breakdown where languages interact intensively. For the Indo-European family, the tree model achieves partial success in delineating core branches like Germanic, Romance, and Balto-Slavic, with high-confidence topologies emerging from cognate-based datasets spanning 100+ languages. However, outliers such as Armenian require ad hoc adjustments, as its position near Greek and Indo-Iranian shows weak support (bootstrap ~60%) owing to heavy Anatolian substrate influence and loans, necessitating hybrid interpretations to fit the data. Recent large-scale analyses confirm robust internal structure for ancient splits but highlight overall instability from areal effects. Statistical measures like the partition homogeneity test (also called the incongruence length difference test) further probe the model's assumptions by detecting conflicts among data partitions, such as lexical versus morphological characters. The test randomizes partitions (e.g., 1,000 replicates) and compares tree lengths; significant incongruence (p < 0.05) signals character incompatibilities incompatible with pure vertical descent, as seen in Indo-European datasets where borrowing-induced conflicts are observed. This metric has validated tree feasibility for low-contact subgroups but exposed systemic issues in expansive families.

Alternatives like the wave model

The wave model, also known as the Wellentheorie, posits that linguistic innovations spread gradually across geographic areas through contact between speakers, resembling concentric waves emanating from a point of origin, rather than through strict bifurcations in a family tree. This approach emphasizes diffusion via interpersonal and areal interactions, leading to overlapping isoglosses—boundaries of linguistic features—that create blended dialect continua instead of discrete branches. Hugo Schuchardt advanced this theory in the 1880s, particularly in his 1885 critique Über die Lautgesetze: Gegen die Junggrammatiker, where he argued against the Neogrammarians' exceptionless sound laws, proposing instead that sound changes diffuse irregularly through social contact in Sprachbund-like zones of linguistic convergence, resulting in gradual blending of features across languages. Hybrid models combining elements of the and wave approaches have emerged, particularly in , where tree structures capture deeper genetic descent while wave diffusion accounts for shallower, contact-induced variations within speech areas. For instance, dialectometry quantifies lexical and phonological similarities to map wave-like spreads in regional varieties, integrating -based subgrouping with geographic gradients. Debates between methods—rooted in tree-like phylogenies from —and network models highlight tensions, with cladistics favoring vertical inheritance for well-defined subgroups and networks accommodating reticulate evolution through horizontal transfers, as seen in analyses of Austronesian and . Modern syntheses, such as Paul Heggarty's areal-typological framework outlined in his 2007 work Linguistics for Archaeologists: Principles, Methods and the Case of the Incas, integrate phylogenetic trees with geographic and typological data to model language divergence, recognizing continua (wave-like) alongside branching events (tree-like) influenced by migration and contact. This approach uses quantitative measures, like distance-based divergence rates calibrated against geography, to reconstruct prehistories, as applied to Andean where areal features overlay genetic subgroups. Such methods bridge the models by weighting vertical inheritance for deep-time relationships and diffusion for recent interactions. Tree models are typically preferred for reconstructing ancient, vertically transmitted relationships over , where contact effects diminish, while wave models better suit recent or ongoing changes driven by borrowing and proximity, such as in Sprachbunds or dialect chains.

References

Add your contribution
Related Hubs
User Avatar
No comments yet.