قانون قدرت تیلور: نظم و الگو در طبیعت

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. Provides a single reference describing the properties, scope, and limitations of Taylor's power law Reports the empirical, analytical, and theoretical work without opinion and ends with a critique of the work in order to develop a synthesis Collects together thoughts and suggestions of the hundreds who have written and speculated about Taylor's power law in order to review examples (and counter-examples), as well as examine the various models developed to account for it Cover......Page 1 Taylor’s Power Law: Order and Pattern in Nature......Page 3 Copyright......Page 4 Preface......Page 5 1 Introduction......Page 7 References......Page 15 Sampling......Page 17 Negative binomial distribution......Page 20 Neymans A distribution......Page 21 Lognormal distribution......Page 22 Inverse Gaussian distribution......Page 23 Tweedie family of distributions......Page 24 Origins of aggregation......Page 25 Censuses......Page 27 References......Page 452 3 Measuring aggregation......Page 30 Nearest neighbor......Page 31 Variance-mean ratio......Page 32 Fitting the negative binomial......Page 33 Interpretation of k......Page 34 Negative binomial with common k......Page 35 Lloyds mean crowding......Page 36 Variance-mean relationship......Page 38 TPL as an index of aggregation......Page 40 Adès distribution......Page 42 Perry and Hewitts number of moves index......Page 45 SADIE......Page 46 References......Page 376 4 Fitting TPL......Page 51 The standard regression model......Page 52 Functional regression......Page 53 Geometric mean regression......Page 54 Deming regression......Page 55 Bartletts 3-group regression......Page 56 Methods for fitting TPL......Page 57 Fitting split lines......Page 59 Bias in estimating TPL......Page 60 Comparison of models......Page 62 Ordinary dependent regression......Page 63 Reduced major Axis (geometric mean) regression......Page 64 References......Page 66 Gymnamoebae......Page 68 Bacteria in a Siberian reservoir......Page 69 Foraminifera in Delaware......Page 71 Invasive flagellate in Sweden......Page 72 Ciliates in the East China Sea......Page 74 Marine viruses in California and Sweden......Page 76 Tobacco mosaic virus on beans......Page 77 Verticillium dahliae in potato fields......Page 78 Passalora fulva on tomatoes......Page 80 Mummy berry disease of blueberries......Page 81 Powdery mildew on apples......Page 82 Pear scab......Page 84 On peppers and soybeans......Page 85 In the air......Page 86 Strawberry anthracnose and rain splashes......Page 88 Ciliates on flatworms......Page 89 Pasteuria penetrans on Meloidogyne arenaria......Page 90 Bacteria cultures......Page 92 The human microbiome......Page 93 Appendix: TPL estimates for microorganisms......Page 96 References......Page 597 6 Plants......Page 102 Farmland in England......Page 103 Field margins in Wisconsin......Page 108 In soybean fields......Page 109 Tree seedbank in Taiwan......Page 111 Seedbank diversity in Catalonia......Page 112 Invasive devils thorn in Australia......Page 113 Invasive ragweed in France......Page 114 Grasslands......Page 116 Grassland in Shaanxi Province......Page 117 Tallgrass prairies in Texas......Page 118 Rangeland in Mongolia......Page 120 Edible palm in Brazil......Page 122 Insectivorous plants in Morocco and Iberia......Page 123 Eelgrass in Chesapeake Bay......Page 124 Pollination success in a Yucatan shrub......Page 125 Maize......Page 127 Sugar cane......Page 128 Wheat......Page 129 Potatoes......Page 130 Appendix: TPL estimates for plants......Page 131 References......Page 139 Nematodes......Page 142 Sampling......Page 143 Urban turfgrass in Ohio......Page 147 Oak forest in Bulgaria......Page 150 Subarctic heath......Page 152 Metabolic footprint......Page 153 Perrine marl soil in Florida......Page 155 Cowpeas and cotton in California......Page 157 Potatoes......Page 159 Broad beans......Page 163 Tobacco......Page 164 Mixed vegetables......Page 165 Citrus......Page 166 Clover......Page 168 Banana......Page 169 Pine trees......Page 170 Sampling methods......Page 172 Steinernema feltiae and S. glaseri......Page 173 Steinernema carpocapsae and Heterorhabditis bacteriophora......Page 174 Effect of habitat......Page 177 Baiting effects......Page 178 Cockroaches......Page 179 Vertebrate hosts......Page 180 Sheep......Page 182 Rabbits......Page 184 Mice......Page 186 Carp......Page 187 Aquatic nematodes......Page 188 Rivers in Germany......Page 189 Highland streams in Germany......Page 190 Farm ponds in Belgium......Page 191 Restored wetland in Georgia......Page 193 Comparing samplers......Page 194 Sediment texture......Page 195 Pollution gradient......Page 196 Depth gradient......Page 197 Nematodes on kelp......Page 198 An extreme case......Page 199 Other worms......Page 201 Platyhelminths......Page 202 Primary hosts-grey mullet......Page 203 Primary hosts-Domestic fowl......Page 204 Leeches in a Cumbrian stream......Page 205 Earthworms in Scotland......Page 206 Earthworms in Colombia......Page 207 Biomass as proxy for abundance......Page 208 Ways of arranging data......Page 210 Appendix: TPL estimates for nematodes and other worms......Page 212 References......Page 324 Lepidoptera......Page 234 European corn borer......Page 235 Winter moth......Page 236 Gypsy moth......Page 238 Wireworms......Page 241 In England and Wales......Page 242 Colorado potato beetle......Page 243 Larvae......Page 246 Adults......Page 249 In the Azores......Page 251 Chthamalus species in Japan......Page 253 Stratification in barnacle distribution......Page 256 Settling behavior of barnacle cyprid larvae......Page 257 A general survey......Page 259 Consistency across space, time, and stage......Page 260 Sampling efficiency and consistency between samplers......Page 265 Effect of sampling method......Page 267 Predation......Page 270 Competition......Page 272 Effect of changes in scale......Page 273 Crustaceans......Page 275 Appendix: TPL estimates for arthropods......Page 276 Appendix 8.M......Page 279 Key to Appendix 8.M......Page 294 References......Page 295 Lake Eufaula, Oklahoma......Page 303 Upper Paraña River basin, Brazil......Page 304 River Elbe Estuary, Germany......Page 306 Molluscs......Page 307 Tellina tenuis in the Firth of Clyde, Scotland......Page 308 Intertidal molluscs on the Isle of Man......Page 309 Terrestrial gastropods in Alberta......Page 311 Slugs in Northumberland......Page 313 Starfish in North Wales......Page 315 Crinoids in São Paulo State, Brazil......Page 316 Bryozoans in the Greenland Sea......Page 317 Hydroids in the Argentine Sea......Page 318 Jellyfish in Oregon-Washington coastal waters......Page 320 Appendix: TPL estimates for other invertebrates......Page 322 Distance sampling......Page 325 Haddock and whiting off Massachusetts......Page 326 Herring and Mackerel in the Norwegian Sea......Page 327 Salmon in the Northeast Pacific Ocean......Page 329 Demersal fish in a tropical bay in Brazil......Page 330 Pelagic fish larvae in Portugal......Page 332 Pelagic fish larvae in New Jersey......Page 333 Fish larvae entering Pamlico and Albemarle Sounds, North Carolina......Page 334 Sea trout fry in England's Lake District......Page 335 Adult sea trout catches in England and Wales......Page 338 Californian commercial fisheries......Page 340 Reptiles in the Florida Everglades......Page 342 Herptiles in Arizonas Rincón Mountains......Page 343 Frogs in an Alpine habitat in California......Page 345 Eagle prey in Northern Greece......Page 346 Willow ptarmigan in Norway......Page 347 Jays in Western USA......Page 349 Grassland sparrows in continental USA......Page 351 Birds in urban and nonurban environments......Page 352 British trust for ornithology annual survey......Page 354 Audubon Societys Christmas Bird Count......Page 357 Cetaceans near the Azores......Page 361 Cetaceans around the British Isles......Page 362 Harbor porpoise in the North Sea......Page 364 Herding ungulates in Kenyas Rift Valley......Page 367 Kangaroo rat mounds in New Mexico......Page 369 Appendix: TPL estimates for vertebrates abstracted or calculated from the literature......Page 370 Rate of evolution......Page 380 Exoenzymes in soil......Page 382 Metabolism in a river system......Page 384 Phosphorus in lakes......Page 385 Metastatic cancers......Page 386 Physiological responses to stimuli......Page 387 United States decennial census......Page 389 Population of Norway......Page 392 Mortality in England and Wales......Page 394 Human immunodeficiency virus......Page 396 Typhoid in Cambodia......Page 398 Measles and whooping cough......Page 399 Disease monitoring......Page 400 Stress in air traffic controllers......Page 402 Crime in Britain......Page 403 European wars......Page 406 Convenience store sales in Japan......Page 407 Size of corporations......Page 409 Size of cities......Page 411 Appendix: TPL estimates for other biological examples......Page 413 Cyanogen in a comet halo......Page 420 The distribution of heavenly bodies......Page 421 Yale Bright Star Catalog......Page 422 Principal Galaxy Catalog......Page 423 Earthquakes off the east coast of Japan......Page 425 Tornadoes in the continental USA......Page 426 Precipitation actual and simulated......Page 428 Traffic through networks......Page 430 Foreign exchange markets......Page 432 Prime numbers......Page 434 Appendix: TPL estimates for nonbiological phenomena......Page 437 References......Page 439 Inadequate NQ or NB......Page 441 Meiobenthos in the Balearic Islands......Page 442 Thrips in a cucumber crop......Page 443 Powdery mildew on apples......Page 444 A modeling example......Page 445 Effect of pesticides......Page 446 Parasite prevalence......Page 447 Commodity crops......Page 448 Temperature......Page 451 14 Applications of TPL......Page 454 Transformations......Page 455 Stabilizing variance......Page 456 Sampling......Page 458 Binomial sampling......Page 459 Sequential sampling......Page 461 Optimum sample size......Page 462 Number of samples......Page 463 Sampling efficiency......Page 465 Postscript......Page 468 Detecting environmental perturbations......Page 469 The cost of conservation......Page 471 Stream water quality......Page 472 Testing vaccines......Page 474 Model calibration and validation......Page 475 Quality control......Page 476 References......Page 477 Self-similarity......Page 481 Effect of small samples......Page 483 Direct effect......Page 484 Anatomy......Page 487 Sampling efficiency......Page 488 Density-dependence......Page 489 Trap saturation......Page 492 References......Page 557 Pareto distribution......Page 495 Spectra......Page 496 Scale-free networks......Page 497 Diffusion-limited aggregation......Page 498 Repetition as a source of self-similarity......Page 499 Self-organized criticality......Page 500 Meteorology......Page 501 Hydrology......Page 502 Allometric growth......Page 503 Dimensional relationships for flying animals......Page 504 Species-area......Page 507 Respiration......Page 510 Self-thinning and space-filling......Page 511 Soil fertility and crop yields......Page 514 Binomial power law......Page 515 Density-size and variance-size laws......Page 516 Taxonomy......Page 518 Richardsons law of conflict......Page 519 Physical models......Page 525 Diffusion-limited aggregation......Page 527 A network model......Page 528 Statistical physics......Page 529 A biophysical model......Page 531 Reformulating TPL......Page 533 Higher moments......Page 534 Simulated sampling......Page 535 Sampling and feasible sets......Page 536 A lattice model......Page 537 Biological models......Page 538 Models in time......Page 539 Strong density dependence......Page 540 Effect of competition......Page 543 Temporal TPL and stability......Page 544 The Lewontin-Cohen model......Page 545 A singularity in TPL......Page 546 Singularities in other models......Page 548 Dispersal distance......Page 550 Ideal free distribution......Page 552 Agent-based models......Page 553 Cellular automaton......Page 554 Arrangement in space......Page 555 18 Summary and synthesis......Page 560 The biological evidence......Page 562 TPL and the pattern of sampling......Page 563 Physical versus biological......Page 564 Sources of range of means......Page 565 The role of the sampler......Page 566 Sampling effort and efficiency......Page 567 The time of sampling......Page 568 Box counting......Page 569 Orthogonal directions......Page 570 Intersection of TPL and Poisson line......Page 571 The effect of scale......Page 572 Super aggregation......Page 574 Predation......Page 575 Competition......Page 576 Mixed-species and community TPLs......Page 577 Human demographics and sociology......Page 578 Other uses of TPL......Page 579 When TPL doesnt work......Page 581 Models......Page 582 Are the power laws related?......Page 586 Is TPL universal?......Page 587 References......Page 590 19 Epilogue......Page 595 B......Page 598 C......Page 600 E......Page 601 G......Page 602 H......Page 603 K......Page 604 L......Page 605 M......Page 606 O......Page 607 R......Page 608 S......Page 609 T......Page 610 W......Page 611 Z......Page 612 A......Page 614 B......Page 615 C......Page 616 F......Page 617 H......Page 618 L......Page 619 M......Page 620 P......Page 621 R......Page 623 S......Page 624 T......Page 625 V......Page 627 Z......Page 628 Back Cover......Page 629