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Taylor's power law relates the variability of a process or population to its average value. It was first described in relation to insect populations and then more broadly to other animal and plant populations. Subsequently it has been recognized in microbiology, genetics, economics, astronomy, physics, and computer science, and it is thought to be one of the few general laws in ecology where it is routinely used to describe the spatial and temporal distributions of populations.
Biologists who know the law as Taylor's power law and physical scientists who know it as fluctuation scaling will be interested in the bigger picture on this fascinating subject. As the relationship between variance and mean is found in so wide a range of disciplines, it seems possible it is a deep property of number, not just a phenomenon in ecology as was thought originally. Although theories abound that purport to explain or predict TPL, none is entirely satisfactory either because it fails to be very predictive, or it does not account for all the available empirical data. To uncover such a property requires a synthesis across disciplines, an acute need that is approached by this exciting work.
Taylor's power law relates the variability of a process or population to its average value. It was first described in relation to insect populations and then more broadly to other animal and plant populations. Subsequently it has been recognized in microbiology, genetics, economics, astronomy, physics, and computer science, and it is thought to be one of the few general laws in ecology where it is routinely used to describe the spatial and temporal distributions of populations.
Biologists who know the law as Taylor's power law and physical scientists who know it as fluctuation scaling will be interested in the bigger picture on this fascinating subject. As the relationship between variance and mean is found in so wide a range of disciplines, it seems possible it is a deep property of number, not just a phenomenon in ecology as was thought originally. Although theories abound that purport to explain or predict TPL, none is entirely satisfactory either because it fails to be very predictive, or it does not account for all the available empirical data. To uncover such a property requires a synthesis across disciplines, an acute need that is approached by this exciting work.
| Erscheinungsjahr: | 2019 |
|---|---|
| Genre: | Biologie |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: | Einband - fest (Hardcover) |
| ISBN-13: | 9780128109878 |
| ISBN-10: | 0128109874 |
| Sprache: | Englisch |
| Herstellernummer: | C2016-0-00333-9 |
| Einband: | Kartoniert / Broschiert |
| Autor: | Taylor, R. A. J. |
| Hersteller: |
Academic Press
Elsevier Science & Technology |
| Verantwortliche Person für die EU: | preigu GmbH & Co. KG, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de |
| Maße: | 30 x 152 x 229 mm |
| Von/Mit: | R. A. J. Taylor |
| Erscheinungsdatum: | 20.06.2019 |
| Gewicht: | 1,13 kg |
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