Taylor's Power Law: Order and Pattern in Nature is a broad synthesis of this ubiquitous property of natural and man-made phenomena. This stimulating and approachable work surveys the biological and non-biological empirical data, describes the statistical uses of Taylor’s power law (TPL) and its relationship to statistical distributions, exposes the mathematical connections to other power laws, covers the competing explanatory models; and develops an argument for TPL's genesis.
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.
1. Chapter 1: Introduction - p. xviii 2. Part I - p. 10 3. Chapter 2: Spatial pattern - p. 10 4. Chapter 3: Measuring aggregation - p. 25 5. Chapter 4: Fitting TPL - p. 47 6. Part II - p. 65 7. Chapter 5: Microorganisms - p. 65 8. Chapter 6: Plants - p. 102 9. Chapter 7: Nematodes and other worms - p. 142 10. Abstract - p. 143 11. Nematodes - p. 143 12. Other worms - p. 202 13. Platyhelminths - p. 203 14. Cestodes - p. 205 15. Annelids - p. 206 16. Appendix: TPL estimates for nematodes and other worms - p. 213 17. Chapter 8: Insects and other arthropods - p. 234 18. Abstract - p. 235 19. Insects - p. 235 20. Crustacea - p. 254 21. A general survey - p. 260 22. Appendix: TPL estimates for arthropods - p. 277 23. Appendix 8.M - p. 281 24. Key to Appendix 8.M - p. 298 25. Chapter 9: Other invertebrates - p. 303 26. Chapter 10: Vertebrates - p. 326 27. Chapter 11: Other biological examples - p. 381 28. Chapter 12: Nonbiological examples - p. 422 29. Chapter 13: Counter examples - p. 443 30. Part III - p. 457 31. Chapter 14: Applications of TPL - p. 457 32. Chapter 15: Properties of TPL - p. 487 33. Chapter 16: Allometry and other power laws - p. 502 34. Chapter 17: Modeling TPL - p. 532 35. Chapter 18: Summary and synthesis - p. 567 36. Chapter 19: Epilogue - p. 603 37. Author index - p. 609 38. Index - p. 625
Taylor's Power Law: Order and Pattern in Nature is a broad synthesis of this ubiquitous property of natural and man-made phenomena. This stimulating and approachable work surveys the biological and non-biological empirical data, describes the statistical uses of Taylor’s power law (TPL) and its relationship to statistical distributions, exposes the mathematical connections to other power laws, covers the competing explanatory models; and develops an argument for TPL's genesis.
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.
1. Chapter 1: Introduction - p. xviii 2. Part I - p. 10 3. Chapter 2: Spatial pattern - p. 10 4. Chapter 3: Measuring aggregation - p. 25 5. Chapter 4: Fitting TPL - p. 47 6. Part II - p. 65 7. Chapter 5: Microorganisms - p. 65 8. Chapter 6: Plants - p. 102 9. Chapter 7: Nematodes and other worms - p. 142 10. Abstract - p. 143 11. Nematodes - p. 143 12. Other worms - p. 202 13. Platyhelminths - p. 203 14. Cestodes - p. 205 15. Annelids - p. 206 16. Appendix: TPL estimates for nematodes and other worms - p. 213 17. Chapter 8: Insects and other arthropods - p. 234 18. Abstract - p. 235 19. Insects - p. 235 20. Crustacea - p. 254 21. A general survey - p. 260 22. Appendix: TPL estimates for arthropods - p. 277 23. Appendix 8.M - p. 281 24. Key to Appendix 8.M - p. 298 25. Chapter 9: Other invertebrates - p. 303 26. Chapter 10: Vertebrates - p. 326 27. Chapter 11: Other biological examples - p. 381 28. Chapter 12: Nonbiological examples - p. 422 29. Chapter 13: Counter examples - p. 443 30. Part III - p. 457 31. Chapter 14: Applications of TPL - p. 457 32. Chapter 15: Properties of TPL - p. 487 33. Chapter 16: Allometry and other power laws - p. 502 34. Chapter 17: Modeling TPL - p. 532 35. Chapter 18: Summary and synthesis - p. 567 36. Chapter 19: Epilogue - p. 603 37. Author index - p. 609 38. Index - p. 625
