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- No One In Different Languages
Current distribution of human language families
Numbers from 1 to 10 in over 5000 languages. Compiled by Mark Rosenfelder. If the Unicode doesn't work well for you, try the old files. Notes and warnings.
This article ranks human languages by their number of native speakers.
However, all such rankings should be used with caution, because it is not possible to devise a coherent set of linguistic criteria for distinguishing languages in a dialect continuum.[1]For example, a language is often defined as a set of varieties that are mutually intelligible, but independent national standard languages may be considered to be separate languages even though they are largely mutually intelligible, as in the case of Danish and Norwegian.[2]Conversely, many commonly accepted languages, including German, Italian and even English, encompass varieties that are not mutually intelligible.[1]While Arabic is sometimes considered a single language centred on Modern Standard Arabic, other authors describe its mutually unintelligible varieties as separate languages.[3]Similarly, Chinese is sometimes viewed as a single language due to shared culture and a single written form.It is also common to describe various Chinese dialect groups, such as Mandarin, Wu and Yue, as languages, even though each of these groups contains many mutually unintelligible varieties.[4]
There are also difficulties in obtaining reliable counts of speakers, which vary over time due to population change and language shift.In some areas, there is no reliable census data, the data is not current, or the census may not record languages spoken, or record them ambiguously.Sometimes speaker populations are exaggerated for political reasons, or speakers of minority languages may be under-reported in favour of a national language.[5]
- 1Top languages by population
Top languages by population
Ethnologue (2019, 22nd edition)
The following 90 languages are listed as having at least 10 million first language speakers in the 2019 edition of Ethnologue, a language reference published by SIL International, which is based in the United States.[6]
Languages with at least 10 million first-language speakers[6]Rank | Rank | Language | Primary Country | Total Countries[a] | Speakers (millions) | % of the World population (March 2019)[7] | Macrolanguage | Language family Branch |
---|
— | 1 | Chinese(macrolanguage) | China | 39 | 1,311 | 17.026 | Sino-Tibetan Sinitic |
1 | — | Mandarin | China | 13 | 918 | 11.922 | Chinese | Sino-Tibetan Sinitic |
2 | 2 | Spanish | Spain | 31 | 460 | 5.974 | Indo-European Romance |
3 | 3 | English | United Kingdom | 137 | 379 | 4.922 | Indo-European Germanic |
4 | 4 | Hindi | India | 4 | 341 | 4.429 | Indo-European Indo-Aryan |
— | 5 | Arabic(macrolanguage) | Saudi Arabia | 59 | 319 | 4.143 | Afroasiatic Semitic |
5 | 6 | Bengali | Bangladesh | 4 | 228 | 2.961 | Indo-European Indo-Aryan |
6 | 7 | Portuguese | Portugal | 15 | 221 | 2.870 | Indo-European Romance |
7 | 8 | Russian | Russian Federation | 19 | 154 | 2.000 | Indo-European Balto-Slavic |
8 | 9 | Japanese | Japan | 2 | 128 | 1.662 | Japonic Japanese |
— | 10 | Lahnda(macrolanguage) | Pakistan | 6 | 119 | 1.545 | Indo-European Indo-Aryan |
9 | — | Western Punjabi | Pakistan | 2 | 92.7 | 1.204 | Lahnda | Indo-European Indo-Aryan |
10 | 11 | Marathi | India | 1 | 83.1 | 1.079 | Indo-European Indo-Aryan |
11 | 12 | Telugu | India | 2 | 82.0 | 1.065 | Dravidian South-Central |
12 | — | Wu | China | 1 | 81.4 | 1.057 | Chinese | Sino-Tibetan Sinitic |
— | 13 | Malay(macrolanguage) | Malaysia | 20 | 80.3 | 1.043 | Austronesian Malayo-Polynesian |
13 | 14 | Turkish | Turkey | 8 | 79.4 | 1.031 | Turkic Oghuz |
14 | 15 | Korean | South Korea | 6 | 77.3 | 1.004 | Koreanic language isolate |
15 | 16 | French | France | 54 | 77.2 | 1.003 | Indo-European Romance |
16 | 17 | German | Germany | 28 | 76.1 | 0.988 | Indo-European Germanic |
17 | 18 | Vietnamese | Viet Nam | 4 | 76.0 | 0.987 | Austroasiatic Vietic |
18 | 19 | Tamil | India | 7 | 75.0 | 0.974 | Dravidian South |
19 | — | Yue | China | 13 | 73.1 | 0.949 | Chinese | Sino-Tibetan Sinitic |
20 | 20 | Urdu | Pakistan | 7 | 68.6 | 0.891 | Indo-European Indo-Aryan |
21 | 21 | Javanese | Indonesia | 3 | 68.3 | 0.887 | Austronesian Malayo-Polynesian |
22 | 22 | Italian | Italy | 14 | 64.8 | 0.842 | Indo-European Romance |
23 | — | Egyptian Spoken Arabic | Egypt | 1 | 64.6 | 0.839 | Arabic | Afroasiatic Semitic |
— | 23 | Persian(macrolanguage) | Iran | 30 | 61.8 | 0.803 | Indo-European Iranian |
24 | 24 | Gujarati | India | 7 | 56.4 | 0.732 | Indo-European Indo-Aryan |
25 | — | Iranian Persian | Iran | 7 | 52.8 | 0.686 | Persian | Indo-European Iranian |
26 | 25 | Bhojpuri | India | 3 | 53.2 | 0.691 | Indo-European Indo-Aryan |
27 | — | Min Nan | China | 10 | 50.1 | 0.651 | Chinese | Sino-Tibetan Sinitic |
28 | — | Hakka | China | 13 | 48.2 | 0.626 | Chinese | Sino-Tibetan Sinitic |
29 | — | Jinyu | China | 1 | 46.9 | 0.609 | Chinese | Sino-Tibetan Sinitic |
30 | 26 | Hausa | Nigeria | 9 | 43.9 | 0.570 | Afroasiatic Chadic |
31 | 27 | Kannada | India | 1 | 43.6 | 0.566 | Dravidian South |
32 | — | Indonesian | Indonesia | 1 | 43.4 | 0.564 | Malay | Austronesian Malayo-Polynesian |
33 | 28 | Polish | Poland | 10 | 39.7 | 0.516 | Indo-European Balto-Slavic |
— | 29 | Pushto(macrolanguage) | Pakistan | 5 | 38.2 | 0.496 | Indo-European Iranian |
34 | 30 | Yoruba | Nigeria | 3 | 37.8 | 0.491 | Niger–Congo Volta–Niger |
35 | — | Xiang Chinese | China | 1 | 37.3 | 0.484 | Chinese | Sino-Tibetan Sinitic |
36 | 31 | Malayalam | India | 2 | 37.1 | 0.482 | Dravidian South |
— | 32 | Oriya(macrolanguage) | India | 1 | 37.1 | 0.482 | Indo-European Indo-Aryan |
37 | — | Odia | India | 1 | 34.5 | 0.448 | Oriya | Indo-European Indo-Aryan |
38 | 33 | Maithili | India | 2 | 33.9 | 0.440 | Indo-European Indo-Aryan |
39 | 34 | Burmese | Myanmar | 1 | 32.9 | 0.427 | Sino-Tibetan Lolo-Burmese |
40 | 35 | Eastern Punjabi | India | 3 | 32.6 | 0.423 | Indo-European Indo-Aryan |
41 | 36 | Sunda | Indonesia | 1 | 32.4 | 0.421 | Austronesian Malayo-Polynesian |
42 | — | Sudanese Spoken Arabic | Sudan | 4 | 31.9 | 0.414 | Arabic | Afroasiatic Semitic |
— | 37 | Fulah(macrolanguage) | Senegal | 19 | 29.8 | 0.387 | Niger–Congo Senegambian |
— | 38 | Uzbek(macrolanguage) | Uzbekistan | 8 | 29.5 | 0.383 | Turkic Karluk |
43 | — | Algerian Spoken Arabic | Algeria | 2 | 29.4 | 0.382 | Arabic | Afroasiatic Semitic |
44 | — | Moroccan Spoken Arabic | Morocco | 3 | 27.5 | 0.357 | Arabic | Afroasiatic Semitic |
45 | 39 | Ukrainian | Ukraine | 9 | 27.3 | 0.355 | Indo-European Balto-Slavic |
46 | 40 | Igbo | Nigeria | 1 | 27.0 | 0.351 | Niger–Congo Volta–Niger |
47 | — | Northern Uzbek | Uzbekistan | 6 | 25.1 | 0.326 | Uzbek | Turkic Karluk |
48 | 41 | Sindhi | Pakistan | 3 | 24.6 | 0.319 | Indo-European Indo-Aryan |
49 | — | North Levantine Spoken Arabic | Syria | 5 | 24.6 | 0.319 | Arabic | Afroasiatic Semitic |
50 | 42 | Romanian | Romania | 6 | 24.3 | 0.316 | Indo-European Romance |
51 | 43 | Tagalog | Philippines | 3 | 23.6 | 0.306 | Austronesian Malayo-Polynesian |
52 | 44 | Dutch | Netherlands | 7 | 23.1 | 0.300 | Indo-European Germanic |
— | 45 | Azerbaijani(macrolanguage) | Iran | 8 | 23.0 | 0.299 | Turkic Oghuz |
53 | — | Saʽidi Spoken Arabic | Egypt | 1 | 22.4 | 0.291 | Arabic | Afroasiatic Semitic |
— | 46 | Kurdish(macrolanguage) | Iraq | 9 | 22.1 | 0.287 | Indo-European Iranian |
54 | — | Gan | China | 1 | 22.1 | 0.287 | Chinese | Sino-Tibetan Sinitic |
55 | 47 | Amharic | Ethiopia | 2 | 21.9 | 0.284 | Afroasiatic Semitic |
56 | — | Northern Pashto | Pakistan | 4 | 20.9 | 0.271 | Pushto | Indo-European Iranian |
57 | 48 | Magahi | India | 2 | 20.7 | 0.269 | Indo-European Indo-Aryan |
58 | 49 | Thai | Thailand | 2 | 20.7 | 0.269 | Kra–Dai Tai |
— | 50 | Marwari(macrolanguage) | India | 3 | 20.6 | 0.268 | Indo-European Indo-Aryan |
59 | — | Saraiki | Pakistan | 2 | 20.0 | 0.260 | Lahnda | Indo-European Indo-Aryan |
— | 51 | Malagasy(macrolanguage) | Madagascar | 2 | 18.1 | 0.235 | Austronesian Malayo-Polynesian |
— | 52 | Oromo(macrolanguage) | Ethiopia | 3 | 17.5 | 0.227 | Afroasiatic Cushitic |
— | 53 | Serbo-Croatian(macrolanguage) | Serbia | 13 | 17.1 | 0.222 | Indo-European Balto-Slavic |
— | 54 | Nepali(macrolanguage) | Nepal | 3 | 16.6 | 0.216 | Indo-European Indo-Aryan |
60 | 55 | Khmer | Cambodia | 2 | 16.6 | 0.216 | Austroasiatic Khmer |
61 | 56 | Chhattisgarhi | India | 1 | 16.3 | 0.212 | Indo-European Indo-Aryan |
62 | 57 | Somali | Somalia | 4 | 16.2 | 0.210 | Afroasiatic Cushitic |
63 | — | Malay | Malaysia | 3 | 16.1 | 0.209 | Malay | Austronesian Malayo-Polynesian |
64 | 58 | Cebuano | Philippines | 1 | 15.9 | 0.206 | Austronesian Malayo-Polynesian |
65 | — | Nepali | Nepal | 3 | 15.8 | 0.205 | Nepali | Indo-European Indo-Aryan |
66 | — | Mesopotamian Spoken Arabic | Iraq | 4 | 15.7 | 0.204 | Arabic | Afroasiatic Semitic |
67 | 59 | Assamese | India | 1 | 15.3 | 0.199 | Indo-European Indo-Aryan |
68 | 60 | Sinhala | Sri Lanka | 2 | 15.3 | 0.199 | Indo-European Indo-Aryan |
— | 61 | Zhuang(macrolanguage) | China | 2 | 14.9 | 0.194 | Kra–Dai Tai |
69 | — | Northern Kurdish | Turkey | 9 | 14.6 | 0.190 | Kurdish | Indo-European Iranian |
70 | — | Hijazi Spoken Arabic | Saudi Arabia | 3 | 14.5 | 0.188 | Arabic | Afroasiatic Semitic |
71 | — | Nigerian Fulfulde | Nigeria | 3 | 14.5 | 0.188 | Fulah | Niger–Congo Senegambian |
72 | — | South Azerbaijani | Iran | 5 | 13.8 | 0.179 | Azerbaijani | Turkic Oghuz |
73 | 62 | Greek | Greece | 9 | 13.1 | 0.170 | Indo-European Hellenic |
74 | 63 | Chittagonian | Bangladesh | 1 | 13.0 | 0.169 | Indo-European Indo-Aryan |
75 | 64 | Kazakh | Kazakhstan | 6 | 12.9 | 0.168 | Turkic Kipchak |
76 | 65 | Deccan | India | 1 | 12.8 | 0.166 | Indo-European Indo-Aryan |
77 | 66 | Hungarian | Hungary | 9 | 12.6 | 0.164 | Uralic Ugric |
78 | 67 | Kinyarwanda | Rwanda | 3 | 12.1 | 0.157 | Niger–Congo Bantu |
79 | 68 | Zulu | South Africa | 5 | 12.1 | 0.157 | Niger–Congo Bantu |
80 | — | South Levantine Spoken Arabic | Jordan | 4 | 11.6 | 0.151 | Arabic | Afroasiatic Semitic |
81 | — | Tunisian Spoken Arabic | Tunisia | 1 | 11.6 | 0.151 | Arabic | Afroasiatic Semitic |
82 | — | Sanaani Spoken Arabic | Yemen | 1 | 11.4 | 0.148 | Arabic | Afroasiatic Semitic |
83 | — | Min Bei Chinese | China | 2 | 11.0 | 0.143 | Chinese | Sino-Tibetan Sinitic |
84 | — | Southern Pashto | Afghanistan | 4 | 10.9 | 0.142 | Pushto | Indo-European Iranian |
85 | 69 | Rundi | Burundi | 2 | 10.8 | 0.140 | Niger–Congo Bantu |
86 | 70 | Czech | Czechia | 8 | 10.7 | 0.139 | Indo-European Balto-Slavic |
87 | — | Taʽizzi-Adeni Spoken Arabic | Yemen | 2 | 10.5 | 0.136 | Arabic | Afroasiatic Semitic |
88 | 71 | Uyghur | China | 4 | 10.4 | 0.135 | Turkic Karluk |
89 | — | Min Dong Chinese | China | 6 | 10.3 | 0.134 | Chinese | Sino-Tibetan Sinitic |
90 | 72 | Sylheti | Bangladesh | 2 | 10.3 | 0.134 | Indo-European Indo-Aryan |
— | 73 | Baluchi(macrolanguage) | Pakistan | 7 | 10.0 | 0.130 | Indo-European Iranian |
Nationalencyklopedin (2010)
The following table contains the top 100 languages by estimated number of native speakers in the 2007 edition of the Swedish encyclopedia Nationalencyklopedin. As census methods in different countries vary to a considerable extent, and given that some countries do not record language in their censuses, any list of languages by native speakers, or total speakers, is effectively based on estimates. Updated estimates from 2010 are also provided.[8]
The top eleven languages have additional figures from the 2010 edition of the Nationalencyklopedin. Numbers above 95 million are rounded off to the nearest 5 million.
Top languages by population per NationalencyklopedinRank | Language | Native speakers in millions 2007 (2010) | Percentage of world population (2007) |
---|
1 | Mandarin (entire branch) | 935 (955) | 14.1% |
2 | Spanish | 390 (405) | 5.85% |
3 | English | 365 (360) | 5.52% |
4 | Hindi[b] | 295 (310) | 4.46% |
5 | Arabic | 280 (295) | 4.23% |
6 | Portuguese | 205 (215) | 3.08% |
7 | Bengali (Bangla) | 200 (205) | 3.05% |
8 | Russian | 160 (155) | 2.42% |
9 | Japanese | 125 (125) | 1.92% |
10 | Punjabi | 95 (100) | 1.44% |
11 | German | 92 (95) | 1.39% |
12 | Javanese | 82 | 1.25% |
13 | Wu (inc. Shanghainese) | 80 | 1.20% |
14 | Malay (inc. Indonesian and Malaysian) | 77 | 1.16% |
15 | Telugu | 76 | 1.15% |
16 | Vietnamese | 76 | 1.14% |
17 | Korean | 76 | 1.14% |
18 | French | 75 | 1.12% |
19 | Marathi | 73 | 1.10% |
20 | Tamil | 70 | 1.06% |
21 | Urdu | 66 | 0.99% |
22 | Turkish | 63 | 0.95% |
23 | Italian | 59 | 0.90% |
24 | Yue (inc. Cantonese) | 59 | 0.89% |
25 | Thai | 56 | 0.85% |
26 | Gujarati | 49 | 0.74% |
27 | Jin | 48 | 0.72% |
28 | Southern Min (inc. Hokkien and Teochew) | 47 | 0.71% |
29 | Persian | 45 | 0.68% |
30 | Polish | 40 | 0.61% |
31 | Pashto | 39 | 0.58% |
32 | Kannada | 38 | 0.58% |
33 | Xiang | 38 | 0.58% |
34 | Malayalam | 38 | 0.57% |
35 | Sundanese | 38 | 0.57% |
36 | Hausa | 34 | 0.52% |
37 | Odia (Oriya) | 33 | 0.50% |
38 | Burmese | 33 | 0.50% |
39 | Hakka | 31 | 0.46% |
40 | Ukrainian | 30 | 0.46% |
41 | Bhojpuri | 29[c] | 0.43% |
42 | Tagalog (Filipino) | 28 | 0.42% |
43 | Yoruba | 28 | 0.42% |
44 | Maithili | 27[c] | 0.41% |
45 | Uzbek | 26 | 0.39% |
46 | Sindhi | 26 | 0.39% |
47 | Amharic | 25 | 0.37% |
48 | Fula | 24 | 0.37% |
49 | Romanian | 24 | 0.37% |
50 | Oromo | 24 | 0.36% |
51 | Igbo | 24 | 0.36% |
52 | Azerbaijani | 23 | 0.34% |
53 | Awadhi | 22[c] | 0.33% |
54 | Gan | 22 | 0.33% |
55 | Cebuano (Visayan) | 21 | 0.32% |
56 | Dutch | 21 | 0.32% |
57 | Kurdish | 21 | 0.31% |
58 | Serbo-Croatian | 19 | 0.28% |
59 | Malagasy | 18 | 0.28% |
60 | Saraiki | 17[d] | 0.26% |
61 | Nepali | 17 | 0.25% |
62 | Sinhalese | 16 | 0.25% |
63 | Chittagonian | 16 | 0.24% |
64 | Zhuang | 16 | 0.24% |
65 | Khmer | 16 | 0.24% |
66 | Turkmen | 16 | 0.24% |
67 | Assamese | 15 | 0.23% |
68 | Madurese | 15 | 0.23% |
69 | Somali | 15 | 0.22% |
70 | Marwari | 14[c] | 0.21% |
71 | Magahi | 14[c] | 0.21% |
72 | Haryanvi | 14[c] | 0.21% |
73 | Hungarian | 13 | 0.19% |
74 | Chhattisgarhi | 12[c] | 0.19% |
75 | Greek | 12 | 0.18% |
76 | Chewa | 12 | 0.17% |
77 | Deccan | 11 | 0.17% |
78 | Akan | 11 | 0.17% |
79 | Kazakh | 11 | 0.17% |
80 | Northern Min[disputed] | 10.9 | 0.16% |
81 | Sylheti | 10.7 | 0.16% |
82 | Zulu | 10.4 | 0.16% |
83 | Czech | 10.0 | 0.15% |
84 | Kinyarwanda | 9.8 | 0.15% |
85 | Dhundhari | 9.6[c] | 0.15% |
86 | Haitian Creole | 9.6 | 0.15% |
87 | Eastern Min (inc. Fuzhou dialect) | 9.5 | 0.14% |
88 | Ilocano | 9.1 | 0.14% |
89 | Quechua | 8.9 | 0.13% |
90 | Kirundi | 8.8 | 0.13% |
91 | Swedish | 8.7 | 0.13% |
92 | Hmong | 8.4 | 0.13% |
93 | Shona | 8.3 | 0.13% |
94 | Uyghur | 8.2 | 0.12% |
95 | Hiligaynon/Ilonggo (Visayan) | 8.2 | 0.12% |
96 | Mossi | 7.6 | 0.11% |
97 | Xhosa | 7.6 | 0.11% |
98 | Belarusian | 7.6[e] | 0.11% |
99 | Balochi | 7.6 | 0.11% |
100 | Konkani | 7.4 | 0.11% |
Total | 5,610 | 85% |
---|
Charts and graphs
Bubble chart of languages by proportion of native speakers worldwide[8]
Languages with at least 50 million first-language speakers, millions (according to: Ethnologue[10])
See also
- List of languages by number of native speakers in India (uses a different definition of Hindi)
Notes
- ^Ethnologue counts some dependent territories as countries in its tallies.
- ^Refers to only Modern Standard Hindi here. The Census of India defines Hindi on a loose and broad basis. It does not include the entire Hindustani language, only the Hindi register of it. In addition to Standard Hindi, it incorporates a set of other Indo-Aryan languages written in Devanagari script including Awadhi, Bhojpuri, Haryanvi, Dhundhari etc. under Hindi group which have more than 422 million native speakers as of 2001.[9] However, the census also acknowledges Standard Hindi, the above mentioned languages and others as separate mother tongues of the Hindi language and provides individual figures for all these languages.[9]
- ^ abcdefghThis is only a fraction of total speakers; others are counted under 'Hindi' as they regard their language a Hindi dialect.
- ^Numbers may also be counted in Punjabi above
- ^Only half this many use Belarusian as their home language.
References
- ^ abPaolillo, John C.; Das, Anupam (31 March 2006). 'Evaluating language statistics: the Ethnologue and beyond'(PDF). UNESCO Institute of Statistics. pp. 3–5. Retrieved 17 November 2018.
- ^Chambers, J.K.; Trudgill, Peter (1998). Dialectology (2nd ed.). Cambridge University Press. ISBN978-0-521-59646-6.
- ^Kaye, Alan S.; Rosenhouse, Judith (1997). 'Arabic Dialects and Maltese'. In Hetzron, Robert (ed.). The Semitic Languages. Routledge. pp. 263–311. ISBN978-0-415-05767-7.
- ^Norman, Jerry (2003). 'The Chinese dialects: phonology'. In Thurgood, Graham; LaPolla, Randy J. (eds.). The Sino-Tibetan languages. Routledge. pp. 72–83. ISBN978-0-7007-1129-1.
- ^Crystal, David (1988). The Cambridge Encyclopedia of Language. Cambridge University Press. pp. 286–287. ISBN978-0-521-26438-9.
- ^ ab'Summary by language size'. Ethnologue. Retrieved 12 March 2019. For items below #26, see individual Ethnologue entry for each language.
- ^'World Population Clock: 7.7 Billion People (2019) - Worldometers'. www.worldometers.info. Retrieved 31 March 2019.
- ^ abMikael Parkvall, 'Världens 100 största språk 2007' (The World's 100 Largest Languages in 2007), in Nationalencyklopedin. Asterisks mark the 2010 estimates for the top dozen languages.
- ^ abAbstract of speakers' strength of languages and mother tongues – 2000, Census of India, 2001
- ^Summary by language size
External links
- The Ethnologue's most recent list of languages by number of speakers
- Languages Spoken by More Than 10 Million People (Archived 2009-10-31) – Encarta list, based on data from Ethnologue, but some figures (e.g. for Arabic) widely vary from it
Retrieved from 'https://en.wikipedia.org/w/index.php?title=List_of_languages_by_number_of_native_speakers&oldid=897167986'
This article was originally published on The Conversation. Read the original article.
The thatched roof held back the sun’s rays, but it could not keep the tropical heat at bay. As everyone at the research workshop headed outside for a break, small groups splintered off to gather in the shade of coconut trees and enjoy a breeze. I wandered from group to group, joining in the discussions. Each time, I noticed that the language of the conversation would change from an indigenous language to something they knew I could understand, Bislama or English. I was amazed by the ease with which the meeting’s participants switched between languages, but I was even more astonished by the number of different indigenous languages.
Thirty people had gathered for the workshop on this island in the South Pacific, and all except for me came from the island, called Makelua, in the nation of Vanuatu. They lived in 16 different communities and spoke 16 distinct languages.
In many cases, you could stand at the edge of one village and see the outskirts of the next community. Yet the residents of each village spoke completely different languages. According to recent work by my colleagues at the Max Planck Institute for the Science of Human History, this island, just 100 kilometers long and 20 kilometers wide, is home to speakers of perhaps 40 different indigenous languages. Why so many?
We could ask this same question of the entire globe. People don’t speak one universal language, or even a handful. Instead, today our species collectively speaks over 7,000 distinct languages.
And these languages are not spread randomly across the planet. For example, far more languages are found in tropical regions than in the temperate zones. The tropical island of New Guinea is home to over 900 languages. Russia, 20 times larger, has 105 indigenous languages. Even within the tropics, language diversity varies widely. For example, the 250,000 people who live on Vanuatu’s 80 islands speak 110 different languages, but in Bangladesh, a population 600 times greater speaks only 41 languages.
Why is it that humans speak so many languages? And why are they so unevenly spread across the planet? As it turns out, we have few clear answers to these fundamental questions about how humanity communicates.
Some ideas, but little evidence
Most people can easily brainstorm possible answers to these intriguing questions. They hypothesize that language diversity must be about history, cultural differences, mountains or oceans dividing populations, or old squabbles writ large—“we hated them, so we don’t talk to them.”
Tamil hd movie download 720p. The questions also seem like they should be fundamental to many academic disciplines—linguistics, anthropology, human geography. But, starting in 2010, when our diverse team of researchers from six different disciplines and eight different countries began to review what was known, we were shocked that only a dozen previous studies had been done, including one we ourselves completed on language diversity in the Pacific.
Trust No One In Different Languages
These prior efforts all examined the degree to which different environmental, social and geographic variables correlated with the number of languages found in a given location. The results varied a lot from one study to another, and no clear patterns emerged. The studies also ran up against many methodological challenges, the biggest of which centered on the old statistical adage—correlation does not equal causation.
We wanted to know the exact steps that led to so many languages forming in certain places and so few in others. But previous work provided few robust theories on the specific processes involved, and the methods used did not get us any closer to understanding the causes of language diversity patterns.
No One In Different Languages
For example, previous studies pointed out that at lower latitudes languages are often spoken across smaller areas than at higher latitudes. You can fit more languages into a given area the closer you get to the equator. But this result does not tell us much about the processes that create language diversity. Just because a group of people crosses an imaginary latitudinal line on the map doesn’t mean they’ll automatically divide into two different populations speaking two different languages. Latitude might be correlated with language diversity, but it certainly did not create it.
Can a simple model predict reality?
A better way to identify the causes of particular patterns is to simulate the processes we think might be creating them. The closer the model’s products are to the reality we know exists, the greater the chances are that we understand the actual processes at work.
Two members of our group, ecologists Thiago Rangel and Robert Colwell, had developed this simulation modeling technique for their studies of species diversity patterns. But no one had ever used this approach to study the diversity of human populations.
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We decided to explore its potential by first building a simple model to test the degree to which a few basic processes might explain language diversity patterns in just one part of the globe, the continent of Australia.
Our colleague Claire Bowern, a linguist at Yale University, created a map that shows the diversity of aboriginal languages—a total of 406—found in Australia prior to contact with Europeans. There were far more languages in the north and along the coasts, with relatively few in the desert interior. We wanted to see how closely a model, based on a simple set of processes, could match this geographic pattern of language diversity.
Our simulation model made only three basic assumptions. First, populations will move to fill available spaces where no one else lives.
Second, rainfall will limit the number of people that can live in a place; Our model assumed that people would live in higher densities in areas where it rained more. Annual precipitation varies widely in Australia, from over three meters in the northeastern rainforests to one-tenth of a meter in the Outback.
Third, we assumed that human populations have a maximum size. Ideal group size is a trade-off between benefits of a larger group (wider selection of potential mates) and costs (keeping track of unrelated individuals). In our model, when a population grew larger than a maximum threshold—set randomly based on a global distribution of hunter-gatherer population sizes—it divided into two populations, each speaking a distinct language.
We used this model to simulate language diversity maps for Australia. In each iteration, an initial population sprung up randomly somewhere on the map and began to grow and spread in a random direction. An underlying rainfall map determined the population density, and when the population size hit the predetermined maximum, the group divided. In this way, the simulated human populations grew and divided as they spread to fill up the entire Australian continent.
Our simple model didn’t include any impact from contact among groups, changes in subsistence strategies, the effects of the borrowing of cultural ideas or components of language from nearby groups, or many other potential processes. So, we expected it would fail miserably.
Incredibly, the model produced 407 languages, just one off from the actual number.
The simulated language maps also show more languages in the north and along the coasts, and less in the dry regions of central Australia, mirroring the geographic patterns in observed language diversity.
And so for the continent of Australia it appears that a small number of factors—limitations rainfall places on population density and limits on group size—might explain both the number of languages and much of the variation in how many languages are spoken in different locations.
Applying the model elsewhere
But we suspect that the patterns of language diversity in other places may be shaped by different factors and processes. In other locations, such as Vanuatu, rainfall levels do not vary as widely as in Australia, and population densities may be shaped by other environmental conditions.
In other instances, contact among human groups probably reshaped the landscape of language diversity. For example, the spread of agricultural groups speaking Indo-European or Bantu languages may have changed the structure of populations and the languages spoken across huge areas of Europe and Africa, respectively.
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Undoubtedly, a wide variety of social and environmental factors and processes have contributed to the patterns in language diversity we see across the globe. In some places topography, climate or the density of key natural resources may be more critical; in others the history of warfare, political organization or the subsistence strategies of different groups may play a bigger role in shaping group boundaries and language diversity patterns. What we have established for now is a template for a method that can be used to uncover the different processes at work in each location.
Language diversity has played a key role in shaping the interactions of human groups and the history of our species, and yet we know surprisingly little about the factors shaping this diversity. We hope other scientists will become as fascinated by the geography of language diversity as our research group is and join us in the search for understanding why humans speak so many languages.
Michael Gavin is associate professor of human dimensions of natural resources at Colorado State University.