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

Applying mathematics to biology has a long history, but only recently has there been an explosion of interest in the field. Some reasons for this include: the explosion of data-rich information sets, due to the genomics revolution, which are difficult to understand without the use of analytical tools, recent development of mathematical tools such as chaos theory to help understand complex, non-linear mechanisms in biology, an increase in computing power which enables calculations and simulations to be performed that were not previously possible, and an increasing interest in in-silico experimentation due to the complications involved in human and animal research. This new book presents the latest leading-edge research in the field.

Coverage: 1982- current; updated: monthly. This database covers current ecology research across a wide range of disciplines, reflecting recent advances in light of growing evidence regarding global environmental change and destruction. Major ares of subject coverage include: Algae/lichens, Animals, Annelids, Aquatic ecosystems, Arachnids, Arid zones, Birds, Brackish water, Bryophytes/pteridophytes, Coastal ecosystems, Conifers, Conservation, Control, Crustaceans, Ecosyst em studies, Fungi, Grasses, Grasslands, High altitude environments, Human ecology, Insects, Legumes, Mammals, Management, Microorganisms, Molluscs, Nematodes, Paleo-ecology, Plants, Pollution studies, Reptiles, River basins, Soil, TAiga/tundra, Terrestrial ecosystems, Vertebrates, Wetlands, Woodlands.