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628_4 | Aldous Huxley | to Vanity Fair and British Vogue magazines.
Contact with the Bloomsbury Set
During the First World War, Huxley spent much of his time at Garsington Manor near Oxford, home of Lady Ottoline Morrell, working as a farm labourer. While at the Manor, he met several Bloomsbury Group figures, including Bertrand Russell, Alfred North Whitehead, and Clive Bell. Later, in Crome Yellow (1921), he caricatured the Garsington lifestyle. Jobs were very scarce, but in 1919, John Middleton Murry was reorganising the Athenaeum and invited Huxley to join the staff. He accepted immediately, and quickly married the Belgian refugee Maria Nys (1899-1955), also at Garsington. They lived with their young son in Italy part of the time during the 1920s, where Huxley would visit his friend D. H. Lawrence. Following Lawrence's death in 1930, Huxley edited Lawrence's letters (1932). Very early in 1929, in London, Huxley met Gerald Heard, a brilliant writer and broadcaster, philosopher and interpreter of contemporary science.
Works of this period included important novels on the dehumanising | 263 | 1,082 |
628_5 | Aldous Huxley | aspects of scientific progress, most famously Brave New World, and on pacifist themes (for example, Eyeless in Gaza). In Brave New World, set in a dystopian London, Huxley portrays a society operating on the principles of mass production and Pavlovian conditioning. Huxley was strongly influenced by F. Matthias Alexander, and included him as a character in Eyeless in Gaza (1936).
Beginning in this period, Huxley began to write and edit non-fiction works on pacifist issues, including Ends and Means (1937), An Encyclopedia of Pacifism, and Pacifism and Philosophy, and was an active member of the Peace Pledge Union.
Life in the United States
In 1937, Huxley moved to Hollywood with his wife Maria, son Matthew Huxley, and friend Gerald Heard. He lived in the U.S., mainly in southern California, until his death, and also for a time in Taos, New Mexico, where he wrote Ends and Means (published in 1937). The book contains tracts on war, religion, nationalism, and ethics.
Heard introduced Huxley to Vedanta (Upanishad-centered philosophy), meditation, and vegetarianism through the principle of ahimsa. | 266 | 1,112 |
628_6 | Aldous Huxley | ahimsa. In 1938, Huxley befriended Jiddu Krishnamurti, whose teachings he greatly admired. Huxley and Krishnamurti entered into an enduring exchange (sometimes edging on debate) over many years, with Krishnamurti representing the more rarefied, detached, ivory-tower perspective and Huxley, with his pragmatic concerns, the more socially and historically informed position. Huxley provided an introduction to Krishnamurti's quintessential statement, The First and Last Freedom (1954).
Huxley also became a Vedantist in the circle of Hindu Swami Prabhavananda, and introduced Christopher Isherwood to this circle. Not long afterwards, Huxley wrote his book on widely held spiritual values and ideas, The Perennial Philosophy, which discussed the teachings of renowned mystics of the world. Huxley's book affirmed a sensibility that insists there are realities beyond the generally accepted "five senses" and that there is genuine meaning for humans beyond both sensual satisfactions and sentimentalities.
Huxley became a close friend of Remsen Bird, president of Occidental College. He spent much time at the college, which is in the Eagle Rock neighbourhood of Los Angeles. The | 264 | 1,180 |
628_7 | Aldous Huxley | college appears as "Tarzana College" in his satirical novel After Many a Summer (1939). The novel won Huxley a British literary award, the 1939 James Tait Black Memorial Prize for fiction. Huxley also incorporated Bird into the novel.
During this period, Huxley earned a substantial income as a Hollywood screenwriter; Christopher Isherwood, in his autobiography My Guru and His Disciple, states that Huxley earned more than $3,000 per week (approximately $50,000 in 2020 dollars) as a screenwriter, and that he used much of it to transport Jewish and left-wing writer and artist refugees from Hitler's Germany to the US. In March 1938, Huxley's friend Anita Loos, a novelist and screenwriter, put him in touch with Metro-Goldwyn-Mayer (MGM), which hired him for Madame Curie which was originally to star Greta Garbo and be directed by George Cukor. (Eventually, the film was completed by MGM in 1943 with a different director and cast.) Huxley received screen credit for Pride and Prejudice (1940) and was paid for his work on a number of other films, including Jane | 263 | 1,069 |
628_8 | Aldous Huxley | Eyre (1944). He was commissioned by Walt Disney in 1945 to write a script based on Alice's Adventures in Wonderland and the biography of the story's author, Lewis Carroll. The script was not used, however.
Huxley wrote an introduction to the posthumous publication of J. D. Unwin's 1940 book Hopousia or The Sexual and Economic Foundations of a New Society.
On 21 October 1949, Huxley wrote to George Orwell, author of Nineteen Eighty-Four, congratulating him on "how fine and how profoundly important the book is". In his letter to Orwell, he predicted:
In 1953, Huxley and Maria applied for United States citizenship and presented themselves for examination. When Huxley refused to bear arms for the U.S. and would not state that his objections were based on religious ideals, the only excuse allowed under the McCarran Act, the judge had to adjourn the proceedings. He withdrew his application. Nevertheless, he remained in the U.S. In 1959, Huxley turned down an offer to be made a Knight Bachelor by the Macmillan government without putting forward a reason; his brother Julian had been knighted in 1958, | 265 | 1,113 |
628_9 | Aldous Huxley | 1958, while another brother Andrew would be knighted in 1974.
In the fall semester of 1960 Huxley was invited by Professor Huston Smith to be the Carnegie Visiting Professor of Humanities at the Massachusetts Institute of Technology (MIT). As part of the MIT centennial program of events organised by the Department of Humanities, Huxley presented a series of lectures titled, "What a Piece of Work is a Man" which concerned history, language, and art.
Late-in-life perspectives
Biographer Harold H. Watts wrote that Huxley's writings in the "final and extended period of his life" are "the work of a man who is meditating on the central problems of many modern men". Huxley had deeply felt apprehensions about the future the developed world might make for itself. From these, he made some warnings in his writings and talks. In a 1958 televised interview conducted by journalist Mike Wallace, Huxley outlined several major concerns: the difficulties and dangers of world overpopulation; the tendency towards distinctly hierarchical social organisation; the crucial importance of evaluating the use of technology in mass societies susceptible to persuasion; the tendency to promote modern politicians to a naive public as well-marketed commodities. In a December 1962 letter to | 265 | 1,281 |
628_10 | Aldous Huxley | brother Julian, summarizing a paper he had presented in Santa Barbara, he wrote, "What I said was that if we didn't pretty quickly start thinking of human problems in ecological terms rather than in terms of power politics we should very soon be in a bad way."
Huxley's engagement with Eastern wisdom traditions was entirely compatible with a strong appreciation of modern science. Biographer Milton Birnbaum wrote that Huxley "ended by embracing both science and Eastern religion". In his last book, Literature and Science, Huxley wrote that "The ethical and philosophical implications of modern science are more Buddhist than Christian...." In "A Philosopher's Visionary Prediction," published one month before he died, Huxley endorsed training in general semantics and "the nonverbal world of culturally uncontaminated consciousness," writing that "We must learn how to be mentally silent, we must cultivate the art of pure receptivity.... [T]he individual must learn to decondition himself, must be able to cut holes in the fence of verbalized symbols that hems him in."
Association with Vedanta
Beginning in 1939 and continuing until his death in 1963, Huxley had an extensive association with the Vedanta Society of Southern California, founded and headed | 263 | 1,265 |
628_11 | Aldous Huxley | by Swami Prabhavananda. Together with Gerald Heard, Christopher Isherwood and other followers, he was initiated by the Swami and was taught meditation and spiritual practices.
In 1944, Huxley wrote the introduction to the "Bhagavad Gita: The Song of God", translated by Swami Prabhavananda and Christopher Isherwood, which was published by the Vedanta Society of Southern California.
From 1941 until 1960, Huxley contributed 48 articles to Vedanta and the West, published by the society. He also served on the editorial board with Isherwood, Heard, and playwright John Van Druten from 1951 through 1962.
Huxley also occasionally lectured at the Hollywood and Santa Barbara Vedanta temples. Two of those lectures have been released on CD: Knowledge and Understanding and Who Are We? from 1955. Nonetheless, Huxley's agnosticism, together with his speculative propensity, made it difficult for him to fully embrace any form of institutionalised religion.
Psychedelic drug use and mystical experiences
In the spring of 1953, Huxley had his first experience with the psychedelic drug mescaline. Huxley had initiated a correspondence with | 263 | 1,139 |
628_12 | Aldous Huxley | Doctor Humphry Osmond, a British psychiatrist then employed in a Canadian institution, and eventually asked him to supply a dose of mescaline; Osmond obliged and supervised Huxley's session in southern California. After the publication of The Doors of Perception, in which he recounted this experience, Huxley and Swami Prabhavananda disagreed about the meaning and importance of the psychedelic drug experience, which may have caused the relationship to cool, but Huxley continued to write articles for the society's journal, lecture at the temple, and attend social functions. Huxley later had an experience on mescaline that he considered more profound than those detailed in The Doors of Perception.
Huxley wrote that "The mystical experience is doubly valuable; it is valuable because it gives the experiencer a better understanding of himself and the world and because it may help him to lead a less self-centered and more creative life."
Eyesight
Differing accounts exist about the details of the quality of Huxley's eyesight at specific points in his life. Circa 1939, Huxley encountered the Bates method, in which he was instructed by Margaret Darst Corbett. In 1940, Huxley relocated from Hollywood to a ranchito | 264 | 1,228 |
628_13 | Aldous Huxley | ranchito in the high desert hamlet of Llano, California, in northern Los Angeles County. Huxley then said that his sight improved dramatically with the Bates Method and the extreme and pure natural lighting of the southwestern American desert. He reported that, for the first time in more than 25 years, he was able to read without glasses and without strain. He even tried driving a car along the dirt road beside the ranch. He wrote a book about his experiences with the Bates Method, The Art of Seeing, which was published in 1942 (U.S.), 1943 (UK). The book contained some generally disputed theories, and its publication created a growing degree of popular controversy about Huxley's eyesight.
It was, and is, widely believed that Huxley was nearly blind since the illness in his teens, despite the partial recovery that had enabled him to study at Oxford. For example, some ten years after publication of The Art of Seeing, in 1952, Bennett Cerf was present when Huxley spoke at a Hollywood banquet, wearing no glasses and apparently reading his paper from the lectern without difficulty: "Then suddenly he faltered—and the disturbing truth became obvious. He wasn't reading his address at all. He had learned | 264 | 1,217 |
628_14 | Aldous Huxley | it by heart. To refresh his memory he brought the paper closer and closer to his eyes. When it was only an inch or so away he still couldn't read it, and had to fish for a magnifying glass in his pocket to make the typing visible to him. It was an agonising moment."
Brazilian author João Ubaldo Ribeiro, who as a young journalist spent several evenings in the Huxleys' company in the late 1950s, wrote that Huxley had said to him, with a wry smile: "I can hardly see at all. And I don't give a damn, really."
On the other hand, Huxley's second wife, Laura Archera, later emphasised in her biographical account, This Timeless Moment: "One of the great achievements of his life: that of having regained his sight." After revealing a letter she wrote to the Los Angeles Times disclaiming the label of Huxley as a "poor fellow who can hardly see" by Walter C. Alvarez, she tempered her statement: "Although I feel it was an injustice to treat Aldous as though he were blind, it is true there were many indications of his impaired vision. For instance, although Aldous | 263 | 1,067 |
628_15 | Aldous Huxley | did not wear glasses, he would quite often use a magnifying lens." Laura Huxley proceeded to elaborate a few nuances of inconsistency peculiar to Huxley's vision. Her account, in this respect, agrees with the following sample of Huxley's own words from The Art of Seeing: "The most characteristic fact about the functioning of the total organism, or any part of the organism, is that it is not constant, but highly variable." Nevertheless, the topic of Huxley's eyesight has continued to endure similar, significant controversy.
American popular science author Steven Johnson, in his book Mind Wide Open, quotes Huxley about his difficulties with visual encoding: "I am and, for as long as I can remember, I have always been a poor visualizer. Words, even the pregnant words of poets, do not evoke pictures in my mind. No hypnagogic visions greet me on the verge of sleep. When I recall something, the memory does not present itself to me as a vividly seen event or object. By an effort of the will, I can evoke a not very vivid image of what happened yesterday afternoon ..."
Personal life
Huxley married on 10 July 1919 Maria Nys (10 September 1899 | 263 | 1,154 |
628_16 | Aldous Huxley | – 12 February 1955), a Belgian epidemiologist from Bellem, a village near Aalter, he met at Garsington, Oxfordshire, in 1919. They had one child, Matthew Huxley (19 April 1920 – 10 February 2005), who had a career as an author, anthropologist, and prominent epidemiologist. In 1955, Maria Huxley died of cancer.
In 1956, Huxley married Laura Archera (1911–2007), also an author, as well as a violinist and psychotherapist. She wrote This Timeless Moment, a biography of Huxley. She told the story of their marriage through Mary Ann Braubach's 2010 documentary, Huxley on Huxley.
Huxley was diagnosed with laryngeal cancer in 1960; in the years that followed, with his health deteriorating, he wrote the Utopian novel Island, and gave lectures on "Human Potentialities" both at the UCSF Medical Center and at the Esalen Institute. These lectures were fundamental to the beginning of the Human Potential Movement.
Huxley was a close friend of Jiddu Krishnamurti and Rosalind | 263 | 976 |
628_17 | Aldous Huxley | Rajagopal and was involved in the creation of the Happy Valley School, now Besant Hill School of Happy Valley, in Ojai, California.
The most substantial collection of Huxley's few remaining papers, following the destruction of most in the 1961 Bel Air Fire, is at the Library of the University of California, Los Angeles. Some are also at the Stanford University Libraries.
On 9 April 1962 Huxley was informed he was elected Companion of Literature by the Royal Society of Literature, the senior literary organisation in Britain, and he accepted the title via letter on 28 April 1962. The correspondence between Huxley and the society is kept at the Cambridge University Library. The society invited Huxley to appear at a banquet and give a lecture at Somerset House, London, in June 1963. Huxley wrote a draft of the speech he intended to give at the society; however, his deteriorating health meant he was not able to attend.
Death
On his deathbed, unable to speak owing to advanced laryngeal cancer, Huxley made a written request to his wife Laura for "LSD, 100 µg, intramuscular." According to her account of his death in This Timeless | 264 | 1,144 |
628_18 | Aldous Huxley | Timeless Moment, she obliged with an injection at 11:20 a.m. and a second dose an hour later; Huxley died aged 69, at 5:20 p.m. (Los Angeles time), on 22 November 1963.
Media coverage of Huxley's death, along with that of fellow British author C. S. Lewis, was overshadowed by the assassination of American President John F. Kennedy on the same day, less than seven hours before Huxley's death. In a 2009 article for New York magazine titled "The Eclipsed Celebrity Death Club", Christopher Bonanos wrote:
This coincidence served as the basis for Peter Kreeft's book Between Heaven and Hell: A Dialog Somewhere Beyond Death with John F. Kennedy, C. S. Lewis, & Aldous Huxley, which imagines a conversation among the three men taking place in Purgatory following their deaths.
Huxley's memorial service took place in London in December 1963; it was led by his elder brother Julian. On 27 October 1971, his ashes were interred in the family grave at the Watts Cemetery, home of the Watts Mortuary Chapel in Compton, Guildford, Surrey, | 265 | 1,036 |
628_19 | Aldous Huxley | Surrey, England.
Huxley had been a long-time friend of Russian composer Igor Stravinsky, who dedicated his last orchestral composition to Huxley. What became Variations: Aldous Huxley in memoriam was begun in July 1963, completed in October 1964, and premiered by the Chicago Symphony Orchestra on 17 April 1965.
Awards
1939: James Tait Black Memorial Prize
1959: American Academy of Arts and Letters Award of Merit .
1962: Companion of Literature
Film adaptations of Huxley's work
1950: Prelude to Fame based upon Young Archimedes
1968: Point Counter Point
1971: The Devils
1980: Brave New World
1998: Brave New World
2020: Brave New World
Bibliography
See also
List of peace activists
References
Sources
. Reprinted in Perspectives on Schoenberg and Stravinsky, revised edition, edited by Benjamin Boretz and Edward T. Cone. New York: W. W. Norton, 1972.
Further reading
Anderson, Jack. 4 July 1982. "Ballet: Suzanne Farrell in Variations Premiere". | 265 | 985 |
628_20 | Aldous Huxley | Premiere". The New York Times.
Atkins, John. Aldous Huxley: A Literary Study, J. Calder, 1956
Barnes, Clive. 1 April 1966. "Ballet: Still Another Balanchine-Stravinsky Pearl; City Troupe Performs in Premiere Here Variations for Huxley at State Theater". The New York Times, p. 28.
Firchow, Peter. Aldous Huxley: Satirist and Novelist, U of Minnesota P, 1972
Firchow, Peter. The End of Utopia: A Study of Aldous Huxley's Brave New World, Bucknell UP, 1984
Huxley, Aldous. The Human Situation: Aldous Huxley Lectures at Santa Barbara 1959, Flamingo Modern Classic, 1994,
Huxley, Laura Archera. This Timeless Moment, Celestial Arts, 2001,
Meckier, Jerome. Aldous Huxley: Modern Satirical Novelist of Ideas, Firchow and Nugel editors, LIT Verlag Berlin-Hamburg-Münster, 2006,
Morgan, W. John, 'Pacifism | 266 | 816 |
628_21 | Aldous Huxley | 'Pacifism or Bourgeois Pacifism? Huxley, Orwell, and Caudwell', Chapter 5 in Morgan, W. John and Guilherme, Alexandre (Eds.),Peace and War-Historical, Philosophical, and Anthropological Perspectives, Palgrave Macmillan, 2020, pp, 71–96. .
Murray, Nicholas. Aldous Huxley, Macmillan, 2003,
Poller, Jake. Aldous Huxley, Reaktion Critical Lives, 2021. .
Poller, Jake. Aldous Huxley and Alternative Spirituality, Brill, 2019. .
Rolo, Charles J. (ed.). The World of Aldous Huxley, Grosset Universal Library, 1947.
Shaw, Jeffrey M. Illusions of Freedom: Thomas Merton and Jacques Ellul on Technology and the Human Condition. Eugene, Oregon: Wipf and Stock. 2014. .
Shadurski, Maxim. The Nationality of Utopia: H. G. Wells, England, and the World State. New York and London: Routledge, 2020. (Chapter 5)
Watt, Conrad (ed.). Aldous Huxley, | 267 | 841 |
628_22 | Aldous Huxley | Huxley, Routledge, 1997,
External links
Aldous Huxley full interview 1958: The Problems of Survival and Freedom in America
Portraits at the National Portrait Gallery
Raymond Fraser, George Wickes (Spring 1960). "Interview: Aldous Huxley: The Art of Fiction No. 24". The Paris Review.
BBC discussion programme In our time: "Brave New World". Huxley and the novel. 9 April 2009. (Audio, 45 minutes)
BBC In their own words series. 12 October 1958 (video, 12 mins)
"The Ultimate Revolution" (talk at UC Berkeley, 20 March 1962)
Huxley interviewed on The Mike Wallace Interview 18 May 1958 (video)
Centre for Huxley Research
Aldous Huxley Papers at University of California, Los Angeles Library Special Collections
Online editions
1894 births
1963 deaths
20th-century English novelists
20th-century essayists
Alumni of Balliol College, Oxford
Anti-consumerists
Bates method
English emigrants to the United States
20th-century British short story writers
Burials in Surrey
Consciousness | 268 | 1,010 |
628_23 | Aldous Huxley | English novelists
20th-century essayists
Alumni of Balliol College, Oxford
Anti-consumerists
Bates method
English emigrants to the United States
20th-century British short story writers
Burials in Surrey
Consciousness researchers and theorists
Deaths from cancer in California
Deaths from laryngeal cancer
Duke University faculty
English agnostics
English essayists
English expatriates in the United States
English male novelists
English male poets
English male short story writers
English pacifists
English people of Cornish descent
English satirists
English science fiction writers
English short story writers
English travel writers
Futurologists
Human Potential Movement
Aldous
James Tait Black Memorial Prize recipients
Male essayists
Moral philosophers
Mystics
Neo-Vedanta
People educated at Eton College
People from Godalming
Perennial philosophy
Philosophers of culture
Philosophers of ethics and morality
Philosophers of literature
Philosophers of mind
Philosophers of technology
Psychedelic drug advocates
Writers from Los Angeles
Writers from Taos, New Mexico
20th-century English philosophers
Lost Generation writers | 264 | 1,128 |
630_0 | Ada | Ada
Ada may refer to:
Places
Africa
Ada Foah or Ada, Ghana, a town
Ada (Ghana parliament constituency)
Ada, Osun, a town in Osun State, Nigeria
Asia
Adeh, Urmia, also known as Ada, a village in West Azerbaijan Province
Ada, Karaman, a village in Karaman Province, Turkey
Australia and New Zealand
Ada River (disambiguation), three rivers
Europe
Ada, Bosnia and Herzegovina, a village
Ada, Croatia, a village
Ada, Serbia, a town and municipality
Ada Ciganlija or Ada, a river island artificially turned into a peninsula in Belgrade, Serbia
North America
United States
Ada, Alabama, an unincorporated community
Ada County, Idaho
Ada, Kansas, an unincorporated community
Ada Township, Michigan
Ada, Minnesota, a city
Ada Township, Dickey County, North Dakota
Ada, Ohio, a village
Ada, Oklahoma, a city
Ada, Oregon, an unincorporated community
Ada Township, Perkins County, South Dakota
Ada, West Virginia, an unincorporated community
Ada, Wisconsin, an unincorporated | 259 | 993 |
630_1 | Ada | unincorporated community
Outer space
523 Ada, an asteroid
Film and television
Ada TV, a television channel in the Turkish Republic of Northern Cyprus
Ada (1961 film), a 1961 film by Daniel Mann
Ada (2019 film), a short biopic about Ada Lovelace
Ada... A Way of Life, a 2008 Bollywood musical by Tanvir Ahmed
Ada (dog actor), a dog that played Colin on the sitcom Spaced
Ada, one of the main characters in 1991 movie Armour of God II: Operation Condor
Biology
Ada (plant), a genus of orchids
Adenosine deaminase, an enzyme involved in purine metabolism
Ada (protein), an enzyme induced by treatment of bacterial cells
Computer science
Ada (programming language), programming language based on Pascal
Ada (computer virus)
Air travel
Ada Air, a regional airline based in Tirana, Albania
Ada International Airport or Saipan International Airport, Saipan Island, Northern Mariana Islands
Aerolínea de Antioquia, a Colombian airline
Airline Deregulation Act, a 1978 US bill removing governmental control from commercial aviation
Schools
Ada, the National College for Digital | 261 | 1,092 |
630_2 | Ada | Skills, a further education college in Tottenham Hale, London
Ada High School (Ohio), Ada, Ohio
Ada High School (Oklahoma), Ada, Oklahoma
People
Ada (name), a feminine given name and a surname, including a list of people and fictional characters
Ada Lovelace (1815–1852), computer scientist sometimes regarded as the first computer programmer
Other uses
List of tropical storms named Ada
Ada (food), a traditional Kerala delicacy
Ada, the cryptocurrency of the Cardano blockchain platform
Ada Bridge, Belgrade, Serbia
, a cargo vessel built for the London and South Western Railway
Ada (ship), a wooden ketch, wrecked near Newcastle, New South Wales, Australia
Ada or Ardor: A Family Chronicle, novel by Vladimir Nabokov
Dangme language, spoken in Ghana (ISO 639-2 and 639-3 code "ada")
Ada Health GmbH, a symptom checker app
See also
ADA (disambiguation)
Ada regulon, an Escherichia coli adaptive response protein
Adah (disambiguation)
Adha (disambiguation)
Ada'a, a woreda in the Oromia Region of Ethiopia
Ade (disambiguation)
| 263 | 1,051 |
630_3 | Ada | School (Oklahoma), Ada, Oklahoma
People
Ada (name), a feminine given name and a surname, including a list of people and fictional characters
Ada Lovelace (1815–1852), computer scientist sometimes regarded as the first computer programmer
Other uses
List of tropical storms named Ada
Ada (food), a traditional Kerala delicacy
Ada, the cryptocurrency of the Cardano blockchain platform
Ada Bridge, Belgrade, Serbia
, a cargo vessel built for the London and South Western Railway
Ada (ship), a wooden ketch, wrecked near Newcastle, New South Wales, Australia
Ada or Ardor: A Family Chronicle, novel by Vladimir Nabokov
Dangme language, spoken in Ghana (ISO 639-2 and 639-3 code "ada")
Ada Health GmbH, a symptom checker app
See also
ADA (disambiguation)
Ada regulon, an Escherichia coli adaptive response protein
Adah (disambiguation)
Adha (disambiguation)
Ada'a, a woreda in the Oromia Region of Ethiopia
Ade (disambiguation)
USS Little Ada (1864), a steamer captured by the Union Navy during the American Civil War | 259 | 1,034 |
632_0 | Aberdeen (disambiguation) | Aberdeen (disambiguation)
Aberdeen is a city in Scotland, United Kingdom.
Aberdeen may also refer to:
Places
Africa
Aberdeen, Sierra Leone
Aberdeen, Eastern Cape, South Africa
Asia
Hong Kong
Aberdeen, Hong Kong, an area and town on southwest Hong Kong Island
Aberdeen Channel, a channel between Ap Lei Chau (Aberdeen Island) and Nam Long Shan on the Hong Kong Island in Hong Kong
Aberdeen Country Park, a country park in Hong Kong Island
Aberdeen floating village, at Aberdeen Harbour, containing approximately 600 junks, which house an estimated 6,000 people
Aberdeen Harbour, a harbour between Aberdeen, Hong Kong and Ap Lei Chau (Aberdeen Island)
Aberdeen Tunnel, a tunnel in Hong Kong Island
Aberdeen Tunnel Underground Laboratory, an underground particle physics laboratory in Hong Kong Island
Ap Lei Chau or Aberdeen Island, an island of Hong Kong
Aberdeen (constituency), a constituency of Southern District Council
India
Aberdeen Bazaar, a shopping centre in Port Blair, South Andaman Island
Sri Lanka
Aberdeen Falls, a waterfall in Sri Lanka
Australia
Aberdeen, New South Wales
Aberdeen, South Australia, one of the early townships that | 265 | 1,173 |
632_1 | Aberdeen (disambiguation) | merged in 1940 to create the town of Burra
Aberdeen, Tasmania, a suburb of the City of Devonport
Caribbean
Aberdeen, Jamaica, a town in Saint Elizabeth, Jamaica
Europe
Aberdeen (Parliament of Scotland constituency)
Aberdeen (UK Parliament constituency) 1832-1885
Aberdeen Burghs (UK Parliament constituency) 1801-1832
Aberdeen Central (Scottish Parliament constituency)
Aberdeen Central (UK Parliament constituency)
Aberdeen Donside (Scottish Parliament constituency)
County of Aberdeen, a historic county of Scotland whose county town was Aberdeen
Old Aberdeen, a part of the city of Aberdeen in Scotland
North America
Canada
Aberdeen, community in the township of Champlain, Prescott and Russell County, Ontario
Aberdeen, Abbotsford, a neighbourhood in the City of Abbotsford, British Columbia
Aberdeen Centre, a shopping mall in Richmond, British Columbia
Aberdeen, Grey County, Ontario
Aberdeen, Kamloops, an area in the City of Kamloops, British Columbia
Aberdeen Lake (Nunavut), a lake in Kivalliq Region, Nunavut, Canada
Aberdeen, Nova Scotia, part of the Municipality of Inverness County, Nova Scotia
Aberdeen Parish, New | 265 | 1,154 |
632_2 | Aberdeen (disambiguation) | Brunswick
Rural Municipality of Aberdeen No. 373, Saskatchewan
Aberdeen, Saskatchewan
Aberdeen Bay, a bay between southern Baffin Island and north-eastern Hector Island in the Nunavut territory
Aberdeen Township, Quebec, until 1960 part of Sheen-Esher-Aberdeen-et-Malakoff, now part of Rapides-des-Joachims, Quebec
Aberdeen River, a tributary of rivière aux Castors Noirs in Mauricie, Québec
New Aberdeen, Nova Scotia
United States
Aberdeen, Arkansas
Aberdeen, Florida
Aberdeen, Georgia
Aberdeen, Idaho
Aberdeen, Ohio County, Indiana
Aberdeen, Porter County, Indiana
Aberdeen, Kentucky
Aberdeen, Maryland
Aberdeen Proving Ground, a United States Army facility located near Aberdeen, Maryland
Aberdeen, Massachusetts, a neighborhood of Brighton, Boston
Aberdeen, Mississippi
Aberdeen Lake (Mississippi), a lake in northeast Mississippi on the Tennessee-Tombigbee Waterway, close to Aberdeen, Mississippi
Aberdeen Township, New Jersey
Aberdeen, North Carolina
Aberdeen Historic District (Aberdeen, North Carolina)
Aberdeen, Ohio
Aberdeen, South Dakota
Aberdeen Historic District (Aberdeen, South Dakota)
Aberdeen, Texas
Aberdeen (Disputanta, | 266 | 1,168 |
632_3 | Aberdeen (disambiguation) | (Disputanta, Virginia)
Aberdeen Gardens (Hampton, Virginia)
Aberdeen, Washington
Aberdeen Gardens, Washington
Aberdeen, West Virginia
Business
Abrdn, formerly Standard Life Aberdeen
Aberdeen Asset Management
Education
Aberdeen Business School
Aberdeen College, formerly one of the largest further education colleges in Scotland, merged with Banff & Buchan College to form North East Scotland College
Aberdeen Grammar School, Aberdeen, Scotland
Aberdeen Hall, a university-preparatory school in Kelowna, British Columbia, Canada
Aberdeen High School (disambiguation)
King's College, Aberdeen
University of Aberdeen, a public research university in the city of Aberdeen
Entertainment
Aberdeen (2000 film), a 2000 Norwegian-British film directed by Hans Petter Moland, starring Stellan Skarsgård and Lena Headey
Aberdeen (2014 film), a 2014 Hong Kong film starring Louis Koo
Aberdeen (band), an American rock band
Aberdeen (song), a song by Cage The Elephant
Aberdeen City (band), Boston based indie/alternative rock band
Other transportation
Aberdeen Airport (disambiguation)
Aberdeen Lock and Dam, one of four lock and dam structures on the Tennessee-Tombigbee Waterway
Rail
| 269 | 1,204 |
632_4 | Aberdeen (disambiguation) | Aberdeen, Carolina and Western Railway, a short-line railroad operating in North Carolina
Aberdeen and Rockfish Railroad, a short-line railroad operating in North Carolina
Aberdeen Corporation Tramways
Aberdeen Line (disambiguation)
Aberdeen station (disambiguation)
Dundee and Perth and Aberdeen Junction Railway, a later name of the Dundee and Perth Railway
Shipping
Aberdeen Line, a British shipping company founded in 1825
, one of several ships by that name
, a sloop of the British Royal Navy that served between 1936 and 1948
, a merchant ship operated during the latter stages of World War II, later commissioned as the USS Altair
Sports
Aberdeen Dad Vail Regatta, the largest regular intercollegiate rowing event in the United States, named after its sponsor, Aberdeen Asset Management
Aberdeen F.C. (disambiguation)
Aberdeen GSFP RFC, an amateur rugby union club based in Aberdeen
Aberdeen IronBirds, a minor league baseball team affiliated with the Baltimore Orioles
Aberdeen L.F.C., a women's football team affiliated with Aberdeen F.C.
See also
Aberdeen Act
Aberdeen Angus, a Scottish breed of small beef cattle
Aberdeen Central (disambiguation)
Aberdeen Gardens | 265 | 1,201 |
632_5 | Aberdeen (disambiguation) | 1825
, one of several ships by that name
, a sloop of the British Royal Navy that served between 1936 and 1948
, a merchant ship operated during the latter stages of World War II, later commissioned as the USS Altair
Sports
Aberdeen Dad Vail Regatta, the largest regular intercollegiate rowing event in the United States, named after its sponsor, Aberdeen Asset Management
Aberdeen F.C. (disambiguation)
Aberdeen GSFP RFC, an amateur rugby union club based in Aberdeen
Aberdeen IronBirds, a minor league baseball team affiliated with the Baltimore Orioles
Aberdeen L.F.C., a women's football team affiliated with Aberdeen F.C.
See also
Aberdeen Act
Aberdeen Angus, a Scottish breed of small beef cattle
Aberdeen Central (disambiguation)
Aberdeen Gardens (disambiguation)
Aberdeen Historic District (disambiguation)
Aberdeen Hospital (disambiguation)
Aberdeen Quarry, a granite quarry in Colorado
Battle of Aberdeen (disambiguation)
Diocese of Aberdeen and Orkney, one of the seven dioceses of the Scottish Episcopal Church
Etymology of Aberdeen
Marquess of Aberdeen and Temair, a title in the Peerage of the United Kingdom | 268 | 1,147 |
633_0 | Algae | Algae
Algae (; singular alga ) is an informal term for a large and diverse group of photosynthetic eukaryotic organisms. It is a polyphyletic grouping that includes species from multiple distinct clades. Included organisms range from unicellular microalgae, such as Chlorella, Prototheca and the diatoms, to multicellular forms, such as the giant kelp, a large brown alga which may grow up to in length. Most are aquatic and autotrophic (they generate food internally) and lack many of the distinct cell and tissue types, such as stomata, xylem and phloem that are found in land plants. The largest and most complex marine algae are called seaweeds, while the most complex freshwater forms are the Charophyta, a division of green algae which includes, for example, Spirogyra and stoneworts.
No definition of algae is generally accepted. One definition is that algae "have chlorophyll as their primary photosynthetic pigment and lack a sterile covering of cells around their reproductive cells". Likewise, the colorless Prototheca under Chlorophyta are all devoid of any chlorophyll. Although cyanobacteria are often referred to as "blue-green | 261 | 1,144 |
633_1 | Algae | "blue-green algae", most authorities exclude all prokaryotes from the definition of algae.
Algae constitute a polyphyletic group since they do not include a common ancestor, and although their plastids seem to have a single origin, from cyanobacteria, they were acquired in different ways. Green algae are examples of algae that have primary chloroplasts derived from endosymbiotic cyanobacteria. Diatoms and brown algae are examples of algae with secondary chloroplasts derived from an endosymbiotic red alga. Algae exhibit a wide range of reproductive strategies, from simple asexual cell division to complex forms of sexual reproduction.
Algae lack the various structures that characterize land plants, such as the phyllids (leaf-like structures) of bryophytes, rhizoids of nonvascular plants, and the roots, leaves, and other organs found in tracheophytes (vascular plants). Most are phototrophic, although some are mixotrophic, deriving energy both from photosynthesis and uptake of organic carbon either by osmotrophy, myzotrophy, or phagotrophy. Some unicellular species of green algae, many golden algae, euglenids, dinoflagellates, and other algae have become | 260 | 1,171 |
633_2 | Algae | heterotrophs (also called colorless or apochlorotic algae), sometimes parasitic, relying entirely on external energy sources and have limited or no photosynthetic apparatus. Some other heterotrophic organisms, such as the apicomplexans, are also derived from cells whose ancestors possessed plastids, but are not traditionally considered as algae. Algae have photosynthetic machinery ultimately derived from cyanobacteria that produce oxygen as a by-product of photosynthesis, unlike other photosynthetic bacteria such as purple and green sulfur bacteria. Fossilized filamentous algae from the Vindhya basin have been dated back to 1.6 to 1.7 billion years ago.
Because of the wide range of types of algae, they have increasing different industrial and traditional applications in human society. Traditional seaweed farming practices have existed for thousands of years and have strong traditions in East Asia food cultures. More modern algaculture applications extend the food traditions for other applications include cattle feed, using algae for bioremediation or pollution control, transforming sunlight into algae fuels or other chemicals used in industrial processes, and in medical and scientific applications. A 2020 review, found that these applications of algae could play an important role in carbon sequestration in order to | 259 | 1,338 |
633_3 | Algae | mitigate climate change while providing valuable value-add products for global economies.
Etymology and study
The singular is the Latin word for 'seaweed' and retains that meaning in English. The etymology is obscure. Although some speculate that it is related to Latin , 'be cold', no reason is known to associate seaweed with temperature. A more likely source is , 'binding, entwining'.
The Ancient Greek word for 'seaweed' was (), which could mean either the seaweed (probably red algae) or a red dye derived from it. The Latinization, , meant primarily the cosmetic rouge. The etymology is uncertain, but a strong candidate has long been some word related to the Biblical (), 'paint' (if not that word itself), a cosmetic eye-shadow used by the ancient Egyptians and other inhabitants of the eastern Mediterranean. It could be any color: black, red, green, or blue.
Accordingly, the modern study of marine and freshwater algae is called either phycology or algology, depending on whether the Greek or Latin root is used. The name fucus appears in a number of taxa.
Classifications
The committee on the International Code of Botanical Nomenclature has recommended certain suffixes for use in the | 259 | 1,206 |
633_4 | Algae | classification of algae. These are -phyta for division, -phyceae for class, -phycideae for subclass, -ales for order, -inales for suborder, -aceae for family, -oidease for subfamily, a Greek-based name for genus, and a Latin-based name for species.
Algal characteristics basic to primary classification
The primary classification of algae is based on certain morphological features. The chief among these are (a) pigment constitution of the cell, (b) chemical nature of stored food materials, (c) kind, number, point of insertion and relative length of the flagella on the motile cell, (d) chemical composition of cell wall and (e) presence or absence of a definitely organized nucleus in the cell or any other significant details of cell structure.
History of classification of algae
Although Carolus Linnaeus (1754) included algae along with lichens in his 25th class Cryptogamia, he did not elaborate further on the classification of algae.
Jean Pierre Étienne Vaucher (1803) was perhaps the first to propose a system of classification of algae, and he recognized three groups, Conferves, Ulves, and Tremelles. While Johann Heinrich | 260 | 1,141 |
633_5 | Algae | Heinrich Friedrich Link (1820) classified algae on the basis of the colour of the pigment and structure, William Henry Harvey (1836) proposed a system of classification on the basis of the habitat and the pigment. J. G. Agardh (1849–1898) divided algae into six orders: Diatomaceae, Nostochineae, Confervoideae, Ulvaceae, Floriadeae and Fucoideae. Around 1880, algae along with fungi were grouped under Thallophyta, a division created by Eichler (1836). Encouraged by this, Adolf Engler and Karl A. E. Prantl (1912) proposed a revised scheme of classification of algae and included fungi in algae as they were of opinion that fungi have been derived from algae. The scheme proposed by Engler and Prantl is summarised as follows:
Schizophyta
Phytosarcodina
Flagellata
Dinoflagellata
Bacillariophyta
Conjugatae
Chlorophyceae
Charophyta
Phaeophyceae
Rhodophyceae
Eumycetes (Fungi)
The algae contain | 260 | 909 |
633_6 | Algae | chloroplasts that are similar in structure to cyanobacteria. Chloroplasts contain circular DNA like that in cyanobacteria and are interpreted as representing reduced endosymbiotic cyanobacteria. However, the exact origin of the chloroplasts is different among separate lineages of algae, reflecting their acquisition during different endosymbiotic events. The table below describes the composition of the three major groups of algae. Their lineage relationships are shown in the figure in the upper right. Many of these groups contain some members that are no longer photosynthetic. Some retain plastids, but not chloroplasts, while others have lost plastids entirely.
Phylogeny based on plastid not nucleocytoplasmic genealogy:
Linnaeus, in Species Plantarum (1753), the starting point for modern botanical nomenclature, recognized 14 genera of algae, of which only four are currently considered among algae. In Systema Naturae, Linnaeus described the genera Volvox and Corallina, and a species of Acetabularia (as Madrepora), among the animals.
In 1768, Samuel Gottlieb Gmelin (1744–1774) published the Historia Fucorum, the first work dedicated | 259 | 1,151 |
633_7 | Algae | to marine algae and the first book on marine biology to use the then new binomial nomenclature of Linnaeus. It included elaborate illustrations of seaweed and marine algae on folded leaves.
W. H. Harvey (1811–1866) and Lamouroux (1813) were the first to divide macroscopic algae into four divisions based on their pigmentation. This is the first use of a biochemical criterion in plant systematics. Harvey's four divisions are: red algae (Rhodospermae), brown algae (Melanospermae), green algae (Chlorospermae), and Diatomaceae.
At this time, microscopic algae were discovered and reported by a different group of workers (e.g., O. F. Müller and Ehrenberg) studying the Infusoria (microscopic organisms). Unlike macroalgae, which were clearly viewed as plants, microalgae were frequently considered animals because they are often motile. Even the nonmotile (coccoid) microalgae were sometimes merely seen as stages of the lifecycle of plants, macroalgae, or animals.
Although used as a taxonomic category in some pre-Darwinian classifications, e.g., Linnaeus (1753), de Jussieu | 261 | 1,081 |
633_8 | Algae | Jussieu (1789), Horaninow (1843), Agassiz (1859), Wilson & Cassin (1864), in further classifications, the "algae" are seen as an artificial, polyphyletic group.
Throughout the 20th century, most classifications treated the following groups as divisions or classes of algae: cyanophytes, rhodophytes, chrysophytes, xanthophytes, bacillariophytes, phaeophytes, pyrrhophytes (cryptophytes and dinophytes), euglenophytes, and chlorophytes. Later, many new groups were discovered (e.g., Bolidophyceae), and others were splintered from older groups: charophytes and glaucophytes (from chlorophytes), many heterokontophytes (e.g., synurophytes from chrysophytes, or eustigmatophytes from xanthophytes), haptophytes (from chrysophytes), and chlorarachniophytes (from xanthophytes).
With the abandonment of plant-animal dichotomous | 261 | 825 |
633_9 | Algae | dichotomous classification, most groups of algae (sometimes all) were included in Protista, later also abandoned in favour of Eukaryota. However, as a legacy of the older plant life scheme, some groups that were also treated as protozoans in the past still have duplicated classifications (see ambiregnal protists).
Some parasitic algae (e.g., the green algae Prototheca and Helicosporidium, parasites of metazoans, or Cephaleuros, parasites of plants) were originally classified as fungi, sporozoans, or protistans of incertae sedis, while others (e.g., the green algae Phyllosiphon and Rhodochytrium, parasites of plants, or the red algae Pterocladiophila and Gelidiocolax mammillatus, parasites of other red algae, or the dinoflagellates Oodinium, parasites of fish) had their relationship with algae conjectured early. In other cases, some groups were originally characterized as parasitic algae (e.g., Chlorochytrium), but later were seen as endophytic algae. Some filamentous bacteria (e.g., Beggiatoa) were originally seen as algae. Furthermore, groups like the | 262 | 1,070 |
633_10 | Algae | apicomplexans are also parasites derived from ancestors that possessed plastids, but are not included in any group traditionally seen as algae.
Relationship to land plants
The first land plants probably evolved from shallow freshwater charophyte algae much like Chara almost 500 million years ago. These probably had an isomorphic alternation of generations and were probably filamentous. Fossils of isolated land plant spores suggest land plants may have been around as long as 475 million years ago.
Morphology
A range of algal morphologies is exhibited, and convergence of features in unrelated groups is common. The only groups to exhibit three-dimensional multicellular thalli are the reds and browns, and some chlorophytes. Apical growth is constrained to subsets of these groups: the florideophyte reds, various browns, and the charophytes. The form of charophytes is quite different from those of reds and browns, because they have distinct nodes, separated by internode 'stems'; whorls of branches reminiscent of the horsetails occur at the nodes. Conceptacles are another polyphyletic trait; they appear in the coralline algae and the Hildenbrandiales, as well as | 259 | 1,177 |
633_11 | Algae | the browns.
Most of the simpler algae are unicellular flagellates or amoeboids, but colonial and nonmotile forms have developed independently among several of the groups. Some of the more common organizational levels, more than one of which may occur in the lifecycle of a species, are
Colonial: small, regular groups of motile cells
Capsoid: individual non-motile cells embedded in mucilage
Coccoid: individual non-motile cells with cell walls
Palmelloid: nonmotile cells embedded in mucilage
Filamentous: a string of nonmotile cells connected together, sometimes branching
Parenchymatous: cells forming a thallus with partial differentiation of tissues
In three lines, even higher levels of organization have been reached, with full tissue differentiation. These are the brown algae,—some of which may reach 50 m in length (kelps)—the red algae, and the green algae. The most complex forms are found among the charophyte algae (see Charales and Charophyta), in a lineage that eventually led to the higher land plants. The innovation that defines these nonalgal plants is the presence of female reproductive organs with protective cell layers that protect the zygote and | 259 | 1,180 |
633_12 | Algae | developing embryo. Hence, the land plants are referred to as the Embryophytes.
Turfs
The term algal turf is commonly used but poorly defined. Algal turfs are thick, carpet-like beds of seaweed that retain sediment and compete with foundation species like corals and kelps, and they are usually less than 15 cm tall. Such a turf may consist of one or more species, and will generally cover an area in the order of a square metre or more. Some common characteristics are listed:
Algae that form aggregations that have been described as turfs include diatoms, cyanobacteria, chlorophytes, phaeophytes and rhodophytes. Turfs are often composed of numerous species at a wide range of spatial scales, but monospecific turfs are frequently reported.
Turfs can be morphologically highly variable over geographic scales and even within species on local scales and can be difficult to identify in terms of the constituent species.
Turfs have been defined as short algae, but this has been used to describe height ranges from less than 0.5 cm to more than 10 cm. In some regions, the descriptions approached heights which might be described as canopies (20 to 30 cm).
Physiology
Many | 267 | 1,178 |
633_13 | Algae | 30 cm).
Physiology
Many algae, particularly members of the Characeae species, have served as model experimental organisms to understand the mechanisms of the water permeability of membranes, osmoregulation, turgor regulation, salt tolerance, cytoplasmic streaming, and the generation of action potentials.
Phytohormones are found not only in higher plants, but in algae, too.
Symbiotic algae
Some species of algae form symbiotic relationships with other organisms. In these symbioses, the algae supply photosynthates (organic substances) to the host organism providing protection to the algal cells. The host organism derives some or all of its energy requirements from the algae. Examples are:
Lichens
Lichens are defined by the International Association for Lichenology to be "an association of a fungus and a photosynthetic symbiont resulting in a stable vegetative body having a specific structure". The fungi, or mycobionts, are mainly from the Ascomycota with a few from the Basidiomycota. In nature they do not occur separate from lichens. It is unknown when they began to associate. One mycobiont associates with the same phycobiont species, | 260 | 1,155 |
633_14 | Algae | rarely two, from the green algae, except that alternatively, the mycobiont may associate with a species of cyanobacteria (hence "photobiont" is the more accurate term). A photobiont may be associated with many different mycobionts or may live independently; accordingly, lichens are named and classified as fungal species. The association is termed a morphogenesis because the lichen has a form and capabilities not possessed by the symbiont species alone (they can be experimentally isolated). The photobiont possibly triggers otherwise latent genes in the mycobiont.
Trentepohlia is an example of a common green alga genus worldwide that can grow on its own or be lichenised. Lichen thus share some of the habitat and often similar appearance with specialized species of algae (aerophytes) growing on exposed surfaces such as tree trunks and rocks and sometimes discoloring them.
Coral reefs
Coral reefs are accumulated from the calcareous exoskeletons of marine invertebrates of the order Scleractinia (stony corals). These animals metabolize sugar and oxygen to obtain energy for their cell-building processes, including secretion of the exoskeleton, with water | 259 | 1,170 |
633_15 | Algae | and carbon dioxide as byproducts. Dinoflagellates (algal protists) are often endosymbionts in the cells of the coral-forming marine invertebrates, where they accelerate host-cell metabolism by generating sugar and oxygen immediately available through photosynthesis using incident light and the carbon dioxide produced by the host. Reef-building stony corals (hermatypic corals) require endosymbiotic algae from the genus Symbiodinium to be in a healthy condition. The loss of Symbiodinium from the host is known as coral bleaching, a condition which leads to the deterioration of a reef.
Sea sponges
Endosymbiontic green algae live close to the surface of some sponges, for example, breadcrumb sponges (Halichondria panicea). The alga is thus protected from predators; the sponge is provided with oxygen and sugars which can account for 50 to 80% of sponge growth in some species.
Lifecycle
Rhodophyta, Chlorophyta, and Heterokontophyta, the three main algal divisions, have lifecycles which show considerable variation and complexity. In general, an asexual phase exists where the seaweed's cells are | 259 | 1,106 |
633_16 | Algae | diploid, a sexual phase where the cells are haploid, followed by fusion of the male and female gametes. Asexual reproduction permits efficient population increases, but less variation is possible. Commonly, in sexual reproduction of unicellular and colonial algae, two specialized, sexually compatible, haploid gametes make physical contact and fuse to form a zygote. To ensure a successful mating, the development and release of gametes is highly synchronized and regulated; pheromones may play a key role in these processes. Sexual reproduction allows for more variation and provides the benefit of efficient recombinational repair of DNA damages during meiosis, a key stage of the sexual cycle. However, sexual reproduction is more costly than asexual reproduction. Meiosis has been shown to occur in many different species of algae.
Numbers
The Algal Collection of the US National Herbarium (located in the National Museum of Natural History) consists of approximately 320,500 dried specimens, which, although not exhaustive (no exhaustive collection exists), gives an idea of the order of magnitude of the number of algal species (that number remains unknown). Estimates vary widely. For example, according to one standard textbook, in the British Isles the UK Biodiversity Steering Group Report estimated there to | 259 | 1,323 |
633_17 | Algae | be 20,000 algal species in the UK. Another checklist reports only about 5,000 species. Regarding the difference of about 15,000 species, the text concludes: "It will require many detailed field surveys before it is possible to provide a reliable estimate of the total number of species ..."
Regional and group estimates have been made, as well:
5,000–5,500 species of red algae worldwide
"some 1,300 in Australian Seas"
400 seaweed species for the western coastline of South Africa, and 212 species from the coast of KwaZulu-Natal. Some of these are duplicates, as the range extends across both coasts, and the total recorded is probably about 500 species. Most of these are listed in List of seaweeds of South Africa. These exclude phytoplankton and crustose corallines.
669 marine species from California (US)
642 in the check-list of Britain and Ireland
and so on, but lacking any scientific basis or reliable sources, these numbers have no more credibility than the British ones mentioned above. Most estimates also omit microscopic algae, such as phytoplankton.
The most recent estimate suggests 72,500 algal species worldwide.
Distribution
The | 260 | 1,158 |
633_18 | Algae | worldwide.
Distribution
The distribution of algal species has been fairly well studied since the founding of phytogeography in the mid-19th century. Algae spread mainly by the dispersal of spores analogously to the dispersal of Plantae by seeds and spores. This dispersal can be accomplished by air, water, or other organisms. Due to this, spores can be found in a variety of environments: fresh and marine waters, air, soil, and in or on other organisms. Whether a spore is to grow into an organism depends on the combination of the species and the environmental conditions where the spore lands.
The spores of freshwater algae are dispersed mainly by running water and wind, as well as by living carriers. However, not all bodies of water can carry all species of algae, as the chemical composition of certain water bodies limits the algae that can survive within them. Marine spores are often spread by ocean currents. Ocean water presents many vastly different habitats based on temperature and nutrient availability, resulting in phytogeographic zones, regions, and provinces.
To some degree, the distribution of algae is subject to floristic discontinuities caused by geographical features, such as Antarctica, long distances of ocean or general land masses. It is, therefore, possible | 263 | 1,295 |
633_19 | Algae | to identify species occurring by locality, such as "Pacific algae" or "North Sea algae". When they occur out of their localities, hypothesizing a transport mechanism is usually possible, such as the hulls of ships. For example, Ulva reticulata and U. fasciata travelled from the mainland to Hawaii in this manner.
Mapping is possible for select species only: "there are many valid examples of confined distribution patterns." For example, Clathromorphum is an arctic genus and is not mapped far south of there. However, scientists regard the overall data as insufficient due to the "difficulties of undertaking such studies."
Ecology
Algae are prominent in bodies of water, common in terrestrial environments, and are found in unusual environments, such as on snow and ice. Seaweeds grow mostly in shallow marine waters, under deep; however, some such as Navicula pennata have been recorded to a depth of . A type of algae, Ancylonema nordenskioeldii, was found in Greenland in areas known as the 'Dark Zone', which caused an increase in the rate of melting ice sheet. Same algae was found in the Italian Alps, after pink ice appeared on parts of the Presena glacier.
The | 261 | 1,177 |
633_20 | Algae | glacier.
The various sorts of algae play significant roles in aquatic ecology. Microscopic forms that live suspended in the water column (phytoplankton) provide the food base for most marine food chains. In very high densities (algal blooms), these algae may discolor the water and outcompete, poison, or asphyxiate other life forms.
Algae can be used as indicator organisms to monitor pollution in various aquatic systems. In many cases, algal metabolism is sensitive to various pollutants. Due to this, the species composition of algal populations may shift in the presence of chemical pollutants. To detect these changes, algae can be sampled from the environment and maintained in laboratories with relative ease.
On the basis of their habitat, algae can be categorized as: aquatic (planktonic, benthic, marine, freshwater, lentic, lotic), terrestrial, aerial (subaerial), lithophytic, halophytic (or euryhaline), psammon, thermophilic, cryophilic, epibiont (epiphytic, epizoic), endosymbiont (endophytic, endozoic), parasitic, calcifilic or lichenic (phycobiont).
Cultural associations
In | 262 | 1,098 |
633_21 | Algae | associations
In classical Chinese, the word is used both for "algae" and (in the modest tradition of the imperial scholars) for "literary talent". The third island in Kunming Lake beside the Summer Palace in Beijing is known as the Zaojian Tang Dao, which thus simultaneously means "Island of the Algae-Viewing Hall" and "Island of the Hall for Reflecting on Literary Talent".
Cultivation
Seaweed farming
Bioreactors
Uses
Agar
Agar, a gelatinous substance derived from red algae, has a number of commercial uses. It is a good medium on which to grow bacteria and fungi, as most microorganisms cannot digest agar.
Alginates
Alginic acid, or alginate, is extracted from brown algae. Its uses range from gelling agents in food, to medical dressings. Alginic acid also has been used in the field of biotechnology as a biocompatible medium for cell encapsulation and cell immobilization. Molecular cuisine is also a user of the substance for its gelling properties, by which it becomes a delivery vehicle for flavours.
Between 100,000 and 170,000 wet tons of Macrocystis are harvested annually in New Mexico | 260 | 1,111 |
633_22 | Algae | for alginate extraction and abalone feed.
Energy source
To be competitive and independent from fluctuating support from (local) policy on the long run, biofuels should equal or beat the cost level of fossil fuels. Here, algae-based fuels hold great promise, directly related to the potential to produce more biomass per unit area in a year than any other form of biomass. The break-even point for algae-based biofuels is estimated to occur by 2025.
Fertilizer
For centuries, seaweed has been used as a fertilizer; George Owen of Henllys writing in the 16th century referring to drift weed in South Wales:
Today, algae are used by humans in many ways; for example, as fertilizers, soil conditioners, and livestock feed. Aquatic and microscopic species are cultured in clear tanks or ponds and are either harvested or used to treat effluents pumped through the ponds. Algaculture on a large scale is an important type of aquaculture in some places. Maerl is commonly used as a soil conditioner.
Nutrition
Naturally growing seaweeds are an important source of food, especially in Asia, leading some to label them as superfoods. They provide many vitamins including: A, B1, | 259 | 1,177 |
633_23 | Algae | B2, B6, niacin, and C, and are rich in iodine, potassium, iron, magnesium, and calcium. In addition, commercially cultivated microalgae, including both algae and cyanobacteria, are marketed as nutritional supplements, such as spirulina, Chlorella and the vitamin-C supplement from Dunaliella, high in beta-carotene.
Algae are national foods of many nations: China consumes more than 70 species, including fat choy, a cyanobacterium considered a vegetable; Japan, over 20 species such as nori and aonori; Ireland, dulse; Chile, cochayuyo. Laver is used to make laver bread in Wales, where it is known as ; in Korea, . It is also used along the west coast of North America from California to British Columbia, in Hawaii and by the Māori of New Zealand. Sea lettuce and badderlocks are salad ingredients in Scotland, Ireland, Greenland, and Iceland. Algae is being considered a potential solution for world hunger problem.
Two popular forms of algae are used in cuisine:
Chlorella: This form of alga is found in freshwater and contains photosynthetic pigments in its chloroplast. It is high in | 259 | 1,094 |
633_24 | Algae | iron, zinc, magnesium, vitamin B2 and Omega-3 Fatty acids.
Furthermore, it contains all nine of the essential amino acids the body does not produce on its own
Spirulina: Known otherwise as a cyanobacterium (a prokaryote, incorrectly referred to as a "blue-green alga"), contains 10% more protein than Chlorella as well as more thiamine and copper.
The oils from some algae have high levels of unsaturated fatty acids. For example, Parietochloris incisa is very high in arachidonic acid, where it reaches up to 47% of the triglyceride pool. Some varieties of algae favored by vegetarianism and veganism contain the long-chain, essential omega-3 fatty acids, docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA). Fish oil contains the omega-3 fatty acids, but the original source is algae (microalgae in particular), which are eaten by marine life such as copepods and are passed up the food chain. Algae have emerged in recent years as a popular source of omega-3 fatty acids for vegetarians who cannot get long-chain EPA and DHA | 259 | 1,038 |
633_25 | Algae | from other vegetarian sources such as flaxseed oil, which only contains the short-chain alpha-linolenic acid (ALA).
Pollution control
Sewage can be treated with algae, reducing the use of large amounts of toxic chemicals that would otherwise be needed.
Algae can be used to capture fertilizers in runoff from farms. When subsequently harvested, the enriched algae can be used as fertilizer.
Aquaria and ponds can be filtered using algae, which absorb nutrients from the water in a device called an algae scrubber, also known as an algae turf scrubber.
Agricultural Research Service scientists found that 60–90% of nitrogen runoff and 70–100% of phosphorus runoff can be captured from manure effluents using a horizontal algae scrubber, also called an algal turf scrubber (ATS). Scientists developed the ATS, which consists of shallow, 100-foot raceways of nylon netting where algae colonies can form, and studied its efficacy for three years. They found that algae can readily be used to reduce the nutrient runoff from agricultural fields and increase the quality of water flowing into rivers, streams, and oceans. Researchers collected and dried the nutrient-rich algae from the ATS and studied its potential as an organic fertilizer. They found that cucumber and | 259 | 1,271 |
633_26 | Algae | corn seedlings grew just as well using ATS organic fertilizer as they did with commercial fertilizers. Algae scrubbers, using bubbling upflow or vertical waterfall versions, are now also being used to filter aquaria and ponds.
Polymers
Various polymers can be created from algae, which can be especially useful in the creation of bioplastics. These include hybrid plastics, cellulose-based plastics, poly-lactic acid, and bio-polyethylene. Several companies have begun to produce algae polymers commercially, including for use in flip-flops and in surf boards.
Bioremediation
The alga Stichococcus bacillaris has been seen to colonize silicone resins used at archaeological sites; biodegrading the synthetic substance.
Pigments
The natural pigments (carotenoids and chlorophylls) produced by algae can be used as alternatives to chemical dyes and coloring agents.
The presence of some individual algal pigments, together with specific pigment concentration ratios, are taxon-specific: analysis of their concentrations with various analytical methods, particularly high-performance liquid chromatography, can therefore offer deep insight into the taxonomic composition and relative abundance of natural algae populations in sea water samples.
Stabilizing substances
Carrageenan, | 260 | 1,284 |
633_27 | Algae | be used as alternatives to chemical dyes and coloring agents.
The presence of some individual algal pigments, together with specific pigment concentration ratios, are taxon-specific: analysis of their concentrations with various analytical methods, particularly high-performance liquid chromatography, can therefore offer deep insight into the taxonomic composition and relative abundance of natural algae populations in sea water samples.
Stabilizing substances
Carrageenan, from the red alga Chondrus crispus, is used as a stabilizer in milk products.
Additional images
See also
AlgaeBase
AlgaePARC
Eutrophication
Iron fertilization
Marimo algae
Microbiofuels
Microphyte
Photobioreactor
Phycotechnology
Plant
Toxoid – anatoxin
References
Bibliography
General
.
Regional
Britain and Ireland
Australia
New Zealand
Europe
Arctic
Greenland
Faroe Islands
.
Canary Islands
Morocco
South Africa
North America
External links
– a database of all algal names including images, nomenclature, taxonomy, distribution, bibliography, uses, extracts
EnAlgae
Endosymbiotic events
Polyphyletic groups | 260 | 1,159 |
634_0 | Analysis of variance | Analysis of variance
Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the t-test beyond two means.
History
While the analysis of variance reached fruition in the 20th century, antecedents extend centuries into the past according to Stigler. These include hypothesis testing, the partitioning of sums of squares, experimental techniques and the additive model. Laplace was performing hypothesis testing in the 1770s. Around 1800, Laplace and Gauss developed the least-squares method for combining observations, which improved upon methods then used in astronomy and geodesy. It also initiated much study of the contributions to sums of squares. Laplace knew how to estimate a variance from a residual (rather than a total) sum of squares. By 1827, Laplace | 261 | 1,279 |
634_1 | Analysis of variance | Laplace was using least squares methods to address ANOVA problems regarding measurements of atmospheric tides. Before 1800, astronomers had isolated observational errors resulting
from reaction times (the "personal equation") and had developed methods of reducing the errors. The experimental methods used in the study of the personal equation were later accepted by the emerging field of psychology which developed strong (full factorial) experimental methods to which randomization and blinding were soon added. An eloquent non-mathematical explanation of the additive effects model was available in 1885.
Ronald Fisher introduced the term variance and proposed its formal analysis in a 1918 article The Correlation Between Relatives on the Supposition of Mendelian Inheritance. His first application of the analysis of variance was published in 1921. Analysis of variance became widely known after being included in Fisher's 1925 book Statistical Methods for Research Workers.
Randomization models were developed by several researchers. The first was published in Polish by Jerzy Neyman in 1923.
Example
The analysis of variance can be used to describe otherwise complex relations among variables. A dog show provides an example. A dog show is not a random sampling of the breed: it is typically limited to dogs that are | 261 | 1,335 |
634_2 | Analysis of variance | adult, pure-bred, and exemplary. A histogram of dog weights from a show might plausibly be rather complex, like the yellow-orange distribution shown in the illustrations. Suppose we wanted to predict the weight of a dog based on a certain set of characteristics of each dog. One way to do that is to explain the distribution of weights by dividing the dog population into groups based on those characteristics. A successful grouping will split dogs such that (a) each group has a low variance of dog weights (meaning the group is relatively homogeneous) and (b) the mean of each group is distinct (if two groups have the same mean, then it isn't reasonable to conclude that the groups are, in fact, separate in any meaningful way).
In the illustrations to the right, groups are identified as X1, X2, etc. In the first illustration, the dogs are divided according to the product (interaction) of two binary groupings: young vs old, and short-haired vs long-haired (e.g., group 1 is young, short-haired dogs, group 2 is young, long-haired dogs, etc.). Since the distributions of dog weight within each of the groups (shown in blue) has a relatively large variance, and since the means are very | 260 | 1,194 |
634_3 | Analysis of variance | similar across groups, grouping dogs by these characteristics does not produce an effective way to explain the variation in dog weights: knowing which group a dog is in doesn't allow us to predict its weight much better than simply knowing the dog is in a dog show. Thus, this grouping fails to explain the variation in the overall distribution (yellow-orange).
An attempt to explain the weight distribution by grouping dogs as pet vs working breed and less athletic vs more athletic would probably be somewhat more successful (fair fit). The heaviest show dogs are likely to be big, strong, working breeds, while breeds kept as pets tend to be smaller and thus lighter. As shown by the second illustration, the distributions have variances that are considerably smaller than in the first case, and the means are more distinguishable. However, the significant overlap of distributions, for example, means that we cannot distinguish X1 and X2 reliably. Grouping dogs according to a coin flip might produce distributions that look similar.
An attempt to explain weight by breed is likely to produce a very good fit. All Chihuahuas are light and all St Bernards are heavy. The difference in weights between Setters and Pointers does not justify separate breeds. The analysis of variance provides the formal tools | 260 | 1,317 |
634_4 | Analysis of variance | to justify these intuitive judgments. A common use of the method is the analysis of experimental data or the development of models. The method has some advantages over correlation: not all of the data must be numeric and one result of the method is a judgment in the confidence in an explanatory relationship.
Classes of models
There are three classes of models used in the analysis of variance, and these are outlined here.
Fixed-effects models
The fixed-effects model (class I) of analysis of variance applies to situations in which the experimenter applies one or more treatments to the subjects of the experiment to see whether the response variable values change. This allows the experimenter to estimate the ranges of response variable values that the treatment would generate in the population as a whole.
Random-effects models
Random-effects model (class II) is used when the treatments are not fixed. This occurs when the various factor levels are sampled from a larger population. Because the levels themselves are random variables, some assumptions and the method of contrasting the treatments (a multi-variable generalization of simple differences) differ from the fixed-effects model.
Mixed-effects models
A mixed-effects model (class III) contains experimental factors of both fixed and random-effects types, with appropriately different interpretations and analysis for the two types.
Example:
Teaching | 263 | 1,429 |
634_5 | Analysis of variance | types.
Example:
Teaching experiments could be performed by a college or university department to find a good introductory textbook, with each text considered a treatment. The fixed-effects model would compare a list of candidate texts. The random-effects model would determine whether important differences exist among a list of randomly selected texts. The mixed-effects model would compare the (fixed) incumbent texts to randomly selected alternatives.
Defining fixed and random effects has proven elusive, with competing definitions arguably leading toward a linguistic quagmire.
Assumptions
The analysis of variance has been studied from several approaches, the most common of which uses a linear model that relates the response to the treatments and blocks. Note that the model is linear in parameters but may be nonlinear across factor levels. Interpretation is easy when data is balanced across factors but much deeper understanding is needed for unbalanced data.
Textbook analysis using a normal distribution
The analysis of variance can be presented in terms of a linear model, which makes the following assumptions about the probability distribution of the responses:
Independence of observations – this is an assumption of the model that simplifies the statistical analysis.
Normality – the distributions of the residuals are normal.
Equality (or "homogeneity") of variances, called homoscedasticity — the variance of | 263 | 1,439 |
634_6 | Analysis of variance | data in groups should be the same.
The separate assumptions of the textbook model imply that the errors are independently, identically, and normally distributed for fixed effects models, that is, that the errors () are independent and
Randomization-based analysis
In a randomized controlled experiment, the treatments are randomly assigned to experimental units, following the experimental protocol. This randomization is objective and declared before the experiment is carried out. The objective random-assignment is used to test the significance of the null hypothesis, following the ideas of C. S. Peirce and Ronald Fisher. This design-based analysis was discussed and developed by Francis J. Anscombe at Rothamsted Experimental Station and by Oscar Kempthorne at Iowa State University. Kempthorne and his students make an assumption of unit treatment additivity, which is discussed in the books of Kempthorne and David R. Cox.
Unit-treatment additivity
In its simplest form, the assumption of unit-treatment additivity states that the observed response from experimental unit when receiving treatment can be written as the sum of the unit's response and the treatment-effect , that is
The assumption of unit-treatment additivity implies that, for every treatment , the th treatment has exactly the same effect on every | 260 | 1,335 |
634_7 | Analysis of variance | experiment unit.
The assumption of unit treatment additivity usually cannot be directly falsified, according to Cox and Kempthorne. However, many consequences of treatment-unit additivity can be falsified. For a randomized experiment, the assumption of unit-treatment additivity implies that the variance is constant for all treatments. Therefore, by contraposition, a necessary condition for unit-treatment additivity is that the variance is constant.
The use of unit treatment additivity and randomization is similar to the design-based inference that is standard in finite-population survey sampling.
Derived linear model
Kempthorne uses the randomization-distribution and the assumption of unit treatment additivity to produce a derived linear model, very similar to the textbook model discussed previously. The test statistics of this derived linear model are closely approximated by the test statistics of an appropriate normal linear model, according to approximation theorems and simulation studies. However, there are differences. For example, the randomization-based analysis results in a small but (strictly) negative correlation between the observations. In the randomization-based analysis, there is no assumption of a normal distribution and certainly no assumption of independence. On the contrary, the observations are dependent!
The randomization-based analysis has the disadvantage that its exposition | 260 | 1,426 |
634_8 | Analysis of variance | involves tedious algebra and extensive time. Since the randomization-based analysis is complicated and is closely approximated by the approach using a normal linear model, most teachers emphasize the normal linear model approach. Few statisticians object to model-based analysis of balanced randomized experiments.
Statistical models for observational data
However, when applied to data from non-randomized experiments or observational studies, model-based analysis lacks the warrant of randomization. For observational data, the derivation of confidence intervals must use subjective models, as emphasized by Ronald Fisher and his followers. In practice, the estimates of treatment-effects from observational studies generally are often inconsistent. In practice, "statistical models" and observational data are useful for suggesting hypotheses that should be treated very cautiously by the public.
Summary of assumptions
The normal-model based ANOVA analysis assumes the independence, normality and homogeneity of variances of the residuals. The randomization-based analysis assumes only the homogeneity of the variances of the residuals (as a consequence of unit-treatment additivity) and uses the randomization procedure of the experiment. Both these analyses require homoscedasticity, as an assumption for the normal-model analysis and as a consequence of randomization and additivity for the randomization-based analysis.
However, studies of | 260 | 1,455 |
634_9 | Analysis of variance | processes that change variances rather than means (called dispersion effects) have been successfully conducted using ANOVA. There are no necessary assumptions for ANOVA in its full generality, but the F-test used for ANOVA hypothesis testing has assumptions and practical
limitations which are of continuing interest.
Problems which do not satisfy the assumptions of ANOVA can often be transformed to satisfy the assumptions.
The property of unit-treatment additivity is not invariant under a "change of scale", so statisticians often use transformations to achieve unit-treatment additivity. If the response variable is expected to follow a parametric family of probability distributions, then the statistician may specify (in the protocol for the experiment or observational study) that the responses be transformed to stabilize the variance. Also, a statistician may specify that logarithmic transforms be applied to the responses, which are believed to follow a multiplicative model.
According to Cauchy's functional equation theorem, the logarithm is the only continuous transformation that transforms real multiplication to addition.
Characteristics
ANOVA is used in the analysis of comparative experiments, those in which only the difference in outcomes is of interest. The statistical significance of the experiment is determined by a ratio of two variances. This ratio | 260 | 1,385 |
634_10 | Analysis of variance | is independent of several possible alterations to the experimental observations: Adding a constant to all observations does not alter significance. Multiplying all observations by a constant does not alter significance. So ANOVA statistical significance result is independent of constant bias and scaling errors as well as the units used in expressing observations. In the era of mechanical calculation it was common to subtract a constant from all observations (when equivalent to dropping leading digits) to simplify data entry. This is an example of data coding.
Logic
The calculations of ANOVA can be characterized as computing a number of means and variances, dividing two variances and comparing the ratio to a handbook value to determine statistical significance. Calculating a treatment effect is then trivial: "the effect of any treatment is estimated by taking the difference between the mean of the observations which receive the treatment and the general mean".
Partitioning of the sum of squares
ANOVA uses traditional standardized terminology. The definitional equation of sample variance is , where the divisor is called the degrees of freedom (DF), the summation is called
the sum of squares (SS), the result is called the mean square (MS) and the squared terms are deviations from the sample mean. ANOVA estimates 3 sample variances: | 261 | 1,362 |
634_11 | Analysis of variance | variances: a total variance based on all the observation deviations from the grand mean, an error variance based on all the observation deviations from their appropriate treatment means, and a treatment variance. The treatment variance is based on the deviations of treatment means from the grand mean, the result being multiplied by the number of observations in each treatment to account for the difference between the variance of observations and the variance of means.
The fundamental technique is a partitioning of the total sum of squares SS into components related to the effects used in the model. For example, the model for a simplified ANOVA with one type of treatment at different levels.
The number of degrees of freedom DF can be partitioned in a similar way: one of these components (that for error) specifies a chi-squared distribution which describes the associated sum of squares, while the same is true for "treatments" if there is no treatment effect.
See also Lack-of-fit sum of squares.
The F-test
The F-test is used for comparing the factors of the total deviation. For example, in one-way, or single-factor ANOVA, statistical significance is tested for by comparing the F test statistic
where MS is mean square, is the number of treatments and is the total number of cases
to | 263 | 1,309 |
634_12 | Analysis of variance | cases
to the F-distribution with , degrees of freedom. Using the F-distribution is a natural candidate because the test statistic is the ratio of two scaled sums of squares each of which follows a scaled chi-squared distribution.
The expected value of F is (where is the treatment sample size) which is 1 for no treatment effect. As values of F increase above 1, the evidence is increasingly inconsistent with the null hypothesis. Two apparent experimental methods of increasing F are increasing the sample size and reducing the error variance by tight experimental controls.
There are two methods of concluding the ANOVA hypothesis test, both of which produce the same result:
The textbook method is to compare the observed value of F with the critical value of F determined from tables. The critical value of F is a function of the degrees of freedom of the numerator and the denominator and the significance level (α). If F ≥ FCritical, the null hypothesis is rejected.
The computer method calculates the probability (p-value) of a value of F greater than or equal to the observed value. The null hypothesis is rejected if this probability is less than or equal to the significance level (α).
The ANOVA F-test is known to be nearly optimal in the sense of minimizing false | 262 | 1,288 |
634_13 | Analysis of variance | negative errors for a fixed rate of false positive errors (i.e. maximizing power for a fixed significance level). For example, to test the hypothesis that various medical treatments have exactly the same effect, the F-test's p-values closely approximate the permutation test's p-values: The approximation is particularly close when the design is balanced. Such permutation tests characterize tests with maximum power against all alternative hypotheses, as observed by Rosenbaum. The ANOVA F-test (of the null-hypothesis that all treatments have exactly the same effect) is recommended as a practical test, because of its robustness against many alternative distributions.
Extended logic
ANOVA consists of separable parts; partitioning sources of variance and hypothesis testing can be used individually. ANOVA is used to support other statistical tools. Regression is first used to fit more complex models to data, then ANOVA is used to compare models with the objective of selecting simple(r) models that adequately describe the data. "Such models could be fit without any reference to ANOVA, but ANOVA tools could then be used to make some sense of the fitted models, and to test hypotheses about batches of coefficients." "[W]e think of the analysis of variance as a way of understanding and structuring | 261 | 1,312 |
634_14 | Analysis of variance | structuring multilevel models—not as an alternative to regression but as a tool for summarizing complex high-dimensional inferences ..."
For a single factor
The simplest experiment suitable for ANOVA analysis is the completely randomized experiment with a single factor. More complex experiments with a single factor involve constraints on randomization and include completely randomized blocks and Latin squares (and variants: Graeco-Latin squares, etc.). The more complex experiments share many of the complexities of multiple factors. A relatively complete discussion of the analysis (models, data summaries, ANOVA table) of the completely randomized experiment is available.
There are some alternatives to conventional one-way analysis of variance, e.g.: Welch's heteroscedastic F test, Welch's heteroscedastic F test with trimmed means and Winsorized variances, Brown-Forsythe test, Alexander-Govern test, James second order test and Kruskal-Wallis test, available in onewaytests R
It is useful to represent each data point in the following form, called a statistical model:
where
i = 1, 2, 3, …, R
j = 1, 2, 3, …, C
μ = overall average (mean)
τj = differential | 261 | 1,179 |
634_15 | Analysis of variance | effect (response) associated with the j level of X; this assumes that overall the values of τj add to zero (that is, )
εij = noise or error associated with the particular ij data value
That is, we envision an additive model that says every data point can be represented by summing three quantities: the true mean, averaged over all factor levels being investigated, plus an incremental component associated with the particular column (factor level), plus a final component associated with everything else affecting that specific data value.
For multiple factors
ANOVA generalizes to the study of the effects of multiple factors. When the experiment includes observations at all combinations of levels of each factor, it is termed factorial. Factorial experiments are more efficient than a series of single factor experiments and the efficiency grows as the number of factors increases. Consequently, factorial designs are heavily used.
The use of ANOVA to study the effects of multiple factors has a complication. In a 3-way ANOVA with factors x, y and z, the ANOVA model includes terms for the main effects (x, y, z) and terms for interactions (xy, xz, yz, xyz).
All terms require hypothesis tests. The proliferation of interaction | 260 | 1,246 |
634_16 | Analysis of variance | terms increases the risk that some hypothesis test will produce a false positive by chance. Fortunately, experience says that high order interactions are rare.
The ability to detect interactions is a major advantage of multiple factor ANOVA. Testing one factor at a time hides interactions, but produces apparently inconsistent experimental results.
Caution is advised when encountering interactions; Test interaction terms first and expand the analysis beyond ANOVA if interactions are found. Texts vary in their recommendations regarding the continuation of the ANOVA procedure after encountering an interaction. Interactions complicate the interpretation of experimental data. Neither the calculations of significance nor the estimated treatment effects can be taken at face value. "A significant interaction will often mask the significance of main effects." Graphical methods are recommended to enhance understanding. Regression is often useful. A lengthy discussion of interactions is available in Cox (1958). Some interactions can be removed (by transformations) while others cannot.
A variety of techniques are used with multiple factor ANOVA to reduce expense. One technique used in factorial designs is to minimize replication (possibly no replication with support of analytical trickery) and to combine groups when effects are found to be statistically (or practically) insignificant. An experiment with many insignificant factors may | 260 | 1,461 |
634_17 | Analysis of variance | collapse into one with a few factors supported by many replications.
Associated analysis
Some analysis is required in support of the design of the experiment while other analysis is performed after changes in the factors are formally found to produce statistically significant changes in the responses. Because experimentation is iterative, the results of one experiment alter plans for following experiments.
Preparatory analysis
The number of experimental units
In the design of an experiment, the number of experimental units is planned to satisfy the goals of the experiment. Experimentation is often sequential.
Early experiments are often designed to provide mean-unbiased estimates of treatment effects and of experimental error. Later experiments are often designed to test a hypothesis that a treatment effect has an important magnitude; in this case, the number of experimental units is chosen so that the experiment is within budget and has adequate power, among other goals.
Reporting sample size analysis is generally required in psychology. "Provide information on sample size and the process that led to sample size decisions." The analysis, which is written in the experimental protocol before the experiment is conducted, is examined in grant applications and administrative review boards.
Besides the power analysis, there are less formal methods for selecting the number of experimental units. These include graphical methods based on limiting the probability of false negative errors, graphical | 260 | 1,524 |
634_18 | Analysis of variance | methods based on an expected variation increase (above the residuals) and methods based on achieving a desired confidence interval.
Power analysis
Power analysis is often applied in the context of ANOVA in order to assess the probability of successfully rejecting the null hypothesis if we assume a certain ANOVA design, effect size in the population, sample size and significance level. Power analysis can assist in study design by determining what sample size would be required in order to have a reasonable chance of rejecting the null hypothesis when the alternative hypothesis is true.
Effect size
Several standardized measures of effect have been proposed for ANOVA to summarize the strength of the association between a predictor(s) and the dependent variable or the overall standardized difference of the complete model. Standardized effect-size estimates facilitate comparison of findings across studies and disciplines. However, while standardized effect sizes are commonly used in much of the professional literature, a non-standardized measure of effect size that has immediately "meaningful" units may be preferable for reporting purposes.
Model confirmation
Sometimes tests are conducted to determine whether the assumptions of ANOVA appear to be violated. Residuals are examined or analyzed to confirm homoscedasticity and gross normality. Residuals should have the appearance of (zero mean normal distribution) noise | 260 | 1,439 |
634_19 | Analysis of variance | when plotted as a function of anything including time and
modeled data values. Trends hint at interactions among factors or among observations.
Follow-up tests
A statistically significant effect in ANOVA is often followed by additional tests. This can be done in order to assess which groups are different from which other groups or to test various other focused hypotheses. Follow-up tests are often distinguished in terms of whether they are "planned" (a priori) or "post hoc." Planned tests are determined before looking at the data, and post hoc tests are conceived only after looking at the data (though the term "post hoc" is inconsistently used).
The follow-up tests may be "simple" pairwise comparisons of individual group means or may be "compound" comparisons (e.g., comparing the mean pooling across groups A, B and C to the mean of group D). Comparisons can also look at tests of trend, such as linear and quadratic relationships, when the independent variable involves ordered levels. Often the follow-up tests incorporate a method of adjusting for the multiple comparisons problem.
Study designs
There are several types of ANOVA. Many statisticians base ANOVA on the design of the experiment, especially on the protocol that specifies the random assignment of treatments to subjects; the | 260 | 1,306 |
634_20 | Analysis of variance | protocol's description of the assignment mechanism should include a specification of the structure of the treatments and of any blocking. It is also common to apply ANOVA to observational data using an appropriate statistical model.
Some popular designs use the following types of ANOVA:
One-way ANOVA is used to test for differences among two or more independent groups (means), e.g. different levels of urea application in a crop, or different levels of antibiotic action on several different bacterial species, or different levels of effect of some medicine on groups of patients. However, should these groups not be independent, and there is an order in the groups (such as mild, moderate and severe disease), or in the dose of a drug (such as 5 mg/mL, 10 mg/mL, 20 mg/mL) given to the same group of patients, then a linear trend estimation should be used. Typically, however, the one-way ANOVA is used to test for differences among at least three groups, since the two-group case can be covered by a t-test. When there are only two means to compare, the t-test and the ANOVA F-test are equivalent; the relation between ANOVA and t is given by .
Factorial ANOVA | 260 | 1,167 |
634_21 | Analysis of variance | is used when there is more than one factor.
Repeated measures ANOVA is used when the same subjects are used for each factor (e.g., in a longitudinal study).
Multivariate analysis of variance (MANOVA) is used when there is more than one response variable.
Cautions
Balanced experiments (those with an equal sample size for each treatment) are relatively easy to interpret; unbalanced experiments offer more complexity. For single-factor (one-way) ANOVA, the adjustment for unbalanced data is easy, but the unbalanced analysis lacks both robustness and power. For more complex designs the lack of balance leads to further complications. "The orthogonality property of main effects and interactions present in balanced data does not carry over to the unbalanced case. This means that the usual analysis of variance techniques do not apply. Consequently, the analysis of unbalanced factorials is much more difficult than that for balanced designs." In the general case, "The analysis of variance can also be applied to unbalanced data, but then the sums of squares, mean squares, and F-ratios will depend on the order in which the sources of variation are considered."
ANOVA is (in part) a test of statistical significance. The | 260 | 1,230 |
634_22 | Analysis of variance | American Psychological Association (and many other organisations) holds the view that simply reporting statistical significance is insufficient and that reporting confidence bounds is preferred.
Generalizations
ANOVA is considered to be a special case of linear regression which in turn is a special case of the general linear model. All consider the observations to be the sum of a model (fit) and a residual (error) to be minimized.
The Kruskal–Wallis test and the Friedman test are nonparametric tests, which do not rely on an assumption of normality.
Connection to linear regression
Below we make clear the connection between multi-way ANOVA and linear regression.
Linearly re-order the data so that -th observation is associated with a response and factors where denotes the different factors and is the total number of factors. In one-way ANOVA and in two-way ANOVA . Furthermore, we assume the -th factor has levels, namely . Now, we can one-hot encode the factors into the dimensional vector .
The one-hot encoding function is defined such that the -th entry of is
The vector is the concatenation of all of the above vectors for all . Thus, . In order to obtain a fully general -way interaction | 260 | 1,220 |
634_23 | Analysis of variance | ANOVA we must also concatenate every additional interaction term in the vector and then add an intercept term. Let that vector be .
With this notation in place, we now have the exact connection with linear regression. We simply regress response against the vector . However, there is a concern about identifiability. In order to overcome such issues we assume that the sum of the parameters within each set of interactions is equal to zero. From here, one can use F-statistics or other methods to determine the relevance of the individual factors.
Example
We can consider the 2-way interaction example where we assume that the first factor has 2 levels and the second factor has 3 levels.
Define if and if , i.e. is the one-hot encoding of the first factor and is the one-hot encoding of the second factor.
With that,
where the last term is an intercept term. For a more concrete example suppose that
Then,
See also
ANOVA on ranks
ANOVA-simultaneous component analysis
Analysis of covariance (ANCOVA)
Analysis of molecular variance (AMOVA)
Analysis of rhythmic variance (ANORVA)
Explained variation
Linear trend estimation
Mixed-design analysis of variance
Multivariate analysis | 260 | 1,195 |
634_24 | Analysis of variance | of covariance (MANCOVA)
Permutational analysis of variance
Variance decomposition
Expected mean squares
Footnotes
Notes
References
Pre-publication chapters are available on-line.
Cohen, Jacob (1988). Statistical power analysis for the behavior sciences (2nd ed.). Routledge
Cox, David R. (1958). Planning of experiments. Reprinted as
Freedman, David A.(2005). Statistical Models: Theory and Practice, Cambridge University Press.
Lehmann, E.L. (1959) Testing Statistical Hypotheses. John Wiley & Sons.
Moore, David S. & McCabe, George P. (2003). Introduction to the Practice of Statistics (4e). W H Freeman & Co.
Rosenbaum, Paul R. (2002). Observational Studies (2nd ed.). New York: Springer-Verlag.
Further reading
Cox, David R. & Reid, Nancy M. (2000). The theory of design of experiments. (Chapman & Hall/CRC).
Freedman, David A.; Pisani, Robert; Purves, Roger (2007) Statistics, 4th edition. W.W. | 261 | 955 |
634_25 | Analysis of variance | (2003). Introduction to the Practice of Statistics (4e). W H Freeman & Co.
Rosenbaum, Paul R. (2002). Observational Studies (2nd ed.). New York: Springer-Verlag.
Further reading
Cox, David R. & Reid, Nancy M. (2000). The theory of design of experiments. (Chapman & Hall/CRC).
Freedman, David A.; Pisani, Robert; Purves, Roger (2007) Statistics, 4th edition. W.W. Norton & Company
Tabachnick, Barbara G. & Fidell, Linda S. (2007). Using Multivariate Statistics (5th ed.). Boston: Pearson International Edition.
External links
SOCR ANOVA Activity
Examples of all ANOVA and ANCOVA models with up to three treatment factors, including randomized block, split plot, repeated measures, and Latin squares, and their analysis in R (University of Southampton)
NIST/SEMATECH e-Handbook of Statistical Methods, section 7.4.3: "Are the means equal?"
Analysis of variance: Introduction
Design of experiments
Statistical tests
Parametric statistics | 261 | 973 |
639_0 | Alkane | Alkane
In organic chemistry, an alkane, or paraffin (a historical trivial name that also has other meanings), is an acyclic saturated hydrocarbon. In other words, an alkane consists of hydrogen and carbon atoms arranged in a tree structure in which all the carbon–carbon bonds are single. Alkanes have the general chemical formula . The alkanes range in complexity from the simplest case of methane (), where n = 1 (sometimes called the parent molecule), to arbitrarily large and complex molecules, like pentacontane () or 6-ethyl-2-methyl-5-(1-methylethyl) octane, an isomer of tetradecane ().
The International Union of Pure and Applied Chemistry (IUPAC) defines alkanes as "acyclic branched or unbranched hydrocarbons having the general formula , and therefore consisting entirely of hydrogen atoms and saturated carbon atoms". However, some sources use the term to denote any saturated hydrocarbon, including those that are either monocyclic (i.e. the cycloalkanes) or polycyclic, despite their having a distinct general formula (i.e. cycloalkanes are ).
In an alkane, each carbon atom is | 260 | 1,094 |
639_1 | Alkane | sp3-hybridized with 4 sigma bonds (either C–C or C–H), and each hydrogen atom is joined to one of the carbon atoms (in a C–H bond). The longest series of linked carbon atoms in a molecule is known as its carbon skeleton or carbon backbone. The number of carbon atoms may be considered as the size of the alkane.
One group of the higher alkanes are waxes, solids at standard ambient temperature and pressure (SATP), for which the number of carbon atoms in the carbon backbone is greater than about 17.
With their repeated – units, the alkanes constitute a homologous series of organic compounds in which the members differ in molecular mass by multiples of 14.03 u (the total mass of each such methylene-bridge unit, which comprises a single carbon atom of mass 12.01 u and two hydrogen atoms of mass ~1.01 u each).
Methane is produced by methanogenic bacteria and some long-chain alkanes function as pheromones in certain animal species or as protective waxes in plants and fungi. Nevertheless, most alkanes do not have much biological activity. They can be viewed as molecular trees upon which can be | 260 | 1,105 |
639_2 | Alkane | hung the more active/reactive functional groups of biological molecules.
The alkanes have two main commercial sources: petroleum (crude oil) and natural gas.
An alkyl group is an alkane-based molecular fragment that bears one open valence for bonding. They are generally abbreviated with the symbol for any organyl group, R, although Alk is sometimes used to specifically symbolize an alkyl group (as opposed to an alkenyl group or aryl group).
Structure and classification
Ordinarily the C-C single bond distance is .
Saturated hydrocarbons can be linear, branched, or cyclic. The third group is sometimes called cycloalkanes. Very complicated structures are possible by combining linear, branch, cyclic alkanes.
Isomerism
Alkanes with more than three carbon atoms can be arranged in various ways, forming structural isomers. The simplest isomer of an alkane is the one in which the carbon atoms are arranged in a single chain with no branches. This isomer is sometimes called the n-isomer (n for "normal", although it is not necessarily the most common). However, the chain of carbon atoms may also be branched at one or more points. The number of possible isomers increases rapidly with | 260 | 1,196 |
639_3 | Alkane | the number of carbon atoms. For example, for acyclic alkanes:
C1: methane only
C2: ethane only
C3: propane only
C4: 2 isomers: butane and isobutane
C5: 3 isomers: pentane, isopentane, and neopentane
C6: 5 isomers: hexane, 2-methylpentane, 3-methylpentane, 2,2-dimethylbutane, and 2,3-dimethylbutane
C7: 9 isomers: heptane, methylhexane (2 isomers), dimethylpentane (4 isomers), 3-ethylpentane, 2,2,3-trimethylbutane
C8: 18 isomers: octane, 2-methylheptane, 3-methylheptane, 2,3-dimethylhexane, 3,4-dimethylhexane, 2,3,4-trimethylpentane, 3,3-dimethylhexane, 2,2-trimethylpentane, 2,4-dimethylhexane, | 261 | 608 |
639_4 | Alkane | 2,4-dimethylhexane, 2,2,4-trimethylpentane, 2,3,3-Trimethylpentane, 3,3,4-trimethyl-pentane, 3,4,4-trimethylpentane, 2,4,4-trimethylpentane, (5 isomers)
C9: 35 isomers
C10: 75 isomers
C12: 355 isomers
C32: 27,711,253,769 isomers
C60: 22,158,734,535,770,411,074,184 isomers, many of which are not stable.
Branched alkanes can be chiral. For example, 3-methylhexane and its higher homologues are chiral due to their stereogenic center at carbon atom number 3. The above list only includes differences of connectivity, not stereochemistry. In addition to the alkane isomers, the chain of carbon atoms may form one or more rings. Such compounds are called cycloalkanes, and are also excluded from the above list because changing the number of rings changes the molecular formula. For example, cyclobutane and methylcyclopropane are isomers of | 269 | 845 |
639_5 | Alkane | each other (C4H8), but are not isomers of butane (C4H10).
Nomenclature
The IUPAC nomenclature (systematic way of naming compounds) for alkanes is based on identifying hydrocarbon chains. Unbranched, saturated hydrocarbon chains are named systematically with a Greek numerical prefix denoting the number of carbons and the suffix "-ane".
In 1866, August Wilhelm von Hofmann suggested systematizing nomenclature by using the whole sequence of vowels a, e, i, o and u to create suffixes -ane, -ene, -ine (or -yne), -one, -une, for the hydrocarbons CnH2n+2, CnH2n, CnH2n−2, CnH2n−4, CnH2n−6. In modern nomenclature, the first three specifically name hydrocarbons with single, double and triple bonds; while "-one" now represents a ketone.
Linear alkanes
Straight-chain alkanes are sometimes indicated by the prefix "n-" or "n-"(for "normal") where a non-linear isomer exists. Although this is not strictly necessary | 260 | 917 |
639_6 | Alkane | and is not part of the IUPAC naming system, the usage is still common in cases where one wishes to emphasize or distinguish between the straight-chain and branched-chain isomers, e.g., "n-butane" rather than simply "butane" to differentiate it from isobutane. Alternative names for this group used in the petroleum industry are linear paraffins or n-paraffins.
The first six members of the series (in terms of number of carbon atoms) are named as follows:
methane CH4 – one carbon and 4 hydrogen
ethane C2H6 – two carbon and 6 hydrogen
propane C3H8 – three carbon and 8 hydrogen
butane C4H10 – four carbon and 10 hydrogen
pentane C5H12 – five carbon and 12 hydrogen
hexane C6H14 – six carbon and 14 hydrogen
The first four names were derived from methanol, ether, propionic acid and butyric acid. Alkanes with five or more carbon atoms are named by adding the suffix -ane to the appropriate numerical multiplier prefix with elision of any terminal vowel (-a or -o) from the basic numerical term. Hence, pentane, C5H12; | 263 | 1,030 |
639_7 | Alkane | C5H12; hexane, C6H14; heptane, C7H16; octane, C8H18; etc. The numeral prefix is generally Greek, however alkanes with a carbon atom count ending in nine, for example nonane, use the Latin prefix non-. For a more complete list, see list of straight-chain alkanes.
Branched alkanes
Simple branched alkanes often have a common name using a prefix to distinguish them from linear alkanes, for example n-pentane, isopentane, and neopentane.
IUPAC naming conventions can be used to produce a systematic name.
The key steps in the naming of more complicated branched alkanes are as follows:
Identify the longest continuous chain of carbon atoms
Name this longest root chain using standard naming rules
Name each side chain by changing the suffix of the name of the alkane from "-ane" to "-yl"
Number the longest continuous chain in order to give the lowest possible numbers for the side-chains
Number and name the side chains before the name of the root chain
If there are multiple side chains of the same type, use prefixes such as "di-" and "tri-" to indicate it | 262 | 1,068 |
639_8 | Alkane | as such, and number each one.
Add side chain names in alphabetical (disregarding "di-" etc. prefixes) order in front of the name of the root chain
Saturated cyclic hydrocarbons
Though technically distinct from the alkanes, this class of hydrocarbons is referred to by some as the "cyclic alkanes." As their description implies, they contain one or more rings.
Simple cycloalkanes have a prefix "cyclo-" to distinguish them from alkanes. Cycloalkanes are named as per their acyclic counterparts with respect to the number of carbon atoms in their backbones, e.g., cyclopentane (C5H10) is a cycloalkane with 5 carbon atoms just like pentane (C5H12), but they are joined up in a five-membered ring. In a similar manner, propane and cyclopropane, butane and cyclobutane, etc.
Substituted cycloalkanes are named similarly to substituted alkanes – the cycloalkane ring is stated, and the substituents are according to their position on the ring, with the numbering decided by the Cahn–Ingold–Prelog priority rules.
Trivial/common | 261 | 1,030 |
639_9 | Alkane | rules.
Trivial/common names
The trivial (non-systematic) name for alkanes is 'paraffins'. Together, alkanes are known as the 'paraffin series'. Trivial names for compounds are usually historical artifacts. They were coined before the development of systematic names, and have been retained due to familiar usage in industry. Cycloalkanes are also called naphthenes.
Branched-chain alkanes are called isoparaffins. "Paraffin" is a general term and often does not distinguish between pure compounds and mixtures of isomers, i.e., compounds of the same chemical formula, e.g., pentane and isopentane.
In IUPAC
The following trivial names are retained in the IUPAC system:
isobutane for 2-methylpropane
isopentane for 2-methylbutane
neopentane for 2,2-dimethylpropane.
Non-IUPAC
Some non-IUPAC trivial names are occasionally used:
cetane, for hexadecane
cerane, for hexacosane
Physical properties
All alkanes are colorless. Alkanes with the lowest molecular weights are gasses, those of intermediate molecular | 264 | 1,017 |
639_10 | Alkane | weight are liquids, and the heaviest are waxy solids.
Table of alkanes
Boiling point
Alkanes experience intermolecular van der Waals forces. Stronger intermolecular van der Waals forces give rise to greater boiling points of alkanes.
There are two determinants for the strength of the van der Waals forces:
the number of electrons surrounding the molecule, which increases with the alkane's molecular weight
the surface area of the molecule
Under standard conditions, from CH4 to C4H10 alkanes are gaseous; from C5H12 to C17H36 they are liquids; and after C18H38 they are solids. As the boiling point of alkanes is primarily determined by weight, it should not be a surprise that the boiling point has almost a linear relationship with the size (molecular weight) of the molecule. As a rule of thumb, the boiling point rises 20–30 °C for each carbon added to the chain; this rule applies to other homologous series.
A straight-chain alkane will have a boiling point higher than a branched-chain alkane due to the greater surface area in contact, thus the greater van der Waals forces, between adjacent molecules. | 261 | 1,121 |
639_11 | Alkane | molecules. For example, compare isobutane (2-methylpropane) and n-butane (butane), which boil at −12 and 0 °C, and 2,2-dimethylbutane and 2,3-dimethylbutane which boil at 50 and 58 °C, respectively.
On the other hand, cycloalkanes tend to have higher boiling points than their linear counterparts due to the locked conformations of the molecules, which give a plane of intermolecular contact.
Melting points
The melting points of the alkanes follow a similar trend to boiling points for the same reason as outlined above. That is, (all other things being equal) the larger the molecule the higher the melting point. There is one significant difference between boiling points and melting points. Solids have more rigid and fixed structure than liquids. This rigid structure requires energy to break down. Thus the better put together solid structures will require more energy to break apart. For alkanes, this can be seen from the graph above (i.e., the blue line). The odd-numbered alkanes have a lower trend in melting points than even numbered alkanes. This is because even numbered alkanes pack well in the | 261 | 1,113 |
639_12 | Alkane | solid phase, forming a well-organized structure, which requires more energy to break apart. The odd-numbered alkanes pack less well and so the "looser" organized solid packing structure requires less energy to break apart. For a visualization of the crystal structures see.
The melting points of branched-chain alkanes can be either higher or lower than those of the corresponding straight-chain alkanes, again depending on the ability of the alkane in question to pack well in the solid phase.
Conductivity and solubility
Alkanes do not conduct electricity in any way, nor are they substantially polarized by an electric field. For this reason, they do not form hydrogen bonds and are insoluble in polar solvents such as water. Since the hydrogen bonds between individual water molecules are aligned away from an alkane molecule, the coexistence of an alkane and water leads to an increase in molecular order (a reduction in entropy). As there is no significant bonding between water molecules and alkane molecules, the second law of thermodynamics suggests that this reduction in entropy should be minimized by minimizing the contact between alkane and water: Alkanes are said to be hydrophobic as they are insoluble in water.
Their solubility in nonpolar | 261 | 1,261 |
639_13 | Alkane | nonpolar solvents is relatively high, a property that is called lipophilicity. Alkanes are, for example, miscible in all proportions among themselves.
The density of the alkanes usually increases with the number of carbon atoms but remains less than that of water. Hence, alkanes form the upper layer in an alkane–water mixture.
Molecular geometry
The molecular structure of the alkanes directly affects their physical and chemical characteristics. It is derived from the electron configuration of carbon, which has four valence electrons. The carbon atoms in alkanes are described as sp3 hybrids, that is to say that, to a good approximation, the valence electrons are in orbitals directed towards the corners of a tetrahedron which are derived from the combination of the 2s orbital and the three 2p orbitals. Geometrically, the angle between the bonds are cos−1(−) ≈ 109.47°. This is exact for the case of methane, while larger alkanes containing a combination of C–H and C–C bonds generally have bonds that are within several degrees of this idealized value.
Bond lengths and bond angles
An alkane has only C–H and C–C | 264 | 1,129 |
639_14 | Alkane | C–C single bonds. The former result from the overlap of an sp3 orbital of carbon with the 1s orbital of a hydrogen; the latter by the overlap of two sp3 orbitals on adjacent carbon atoms. The bond lengths amount to 1.09 × 10−10 m for a C–H bond and 1.54 × 10−10 m for a C–C bond.
The spatial arrangement of the bonds is similar to that of the four sp3 orbitals—they are tetrahedrally arranged, with an angle of 109.47° between them. Structural formulae that represent the bonds as being at right angles to one another, while both common and useful, do not accurately depict the geometry.
Conformation
The structural formula and the bond angles are not usually sufficient to completely describe the geometry of a molecule. There is a further degree of freedom for each carbon–carbon bond: the torsion angle between the atoms or groups bound to the atoms at each end of the bond. The spatial arrangement described by the torsion angles of the molecule is known as its conformation.
Ethane forms the simplest case for studying the conformation of alkanes, as there is only one C–C bond. | 261 | 1,088 |
639_15 | Alkane | If one looks down the axis of the C–C bond, one will see the so-called Newman projection. The hydrogen atoms on both the front and rear carbon atoms have an angle of 120° between them, resulting from the projection of the base of the tetrahedron onto a flat plane. However, the torsion angle between a given hydrogen atom attached to the front carbon and a given hydrogen atom attached to the rear carbon can vary freely between 0° and 360°. This is a consequence of the free rotation about a carbon–carbon single bond. Despite this apparent freedom, only two limiting conformations are important: eclipsed conformation and staggered conformation.
The two conformations differ in energy: the staggered conformation is 12.6 kJ/mol (3.0 kcal/mol) lower in energy (more stable) than the eclipsed conformation (the least stable).
This difference in energy between the two conformations, known as the torsion energy, is low compared to the thermal energy of an ethane molecule at ambient temperature. There is constant rotation about the C–C bond. The time taken for an ethane molecule to pass from one staggered conformation to the next, equivalent to the rotation of one CH3 | 260 | 1,174 |
Subsets and Splits