Modelling fish spatial dynamics and local density-dependence relationships: detection of patterns at a global scale
TL;DR: In this article, a model is used to explore whether local density-dependent recruitment relationships can be observed when considering a larger scale, where a virtual population of spawners is tracked within an artificial environment composed of cells.
About: This article is published in Aquatic Living Resources.The article was published on 1998-09-01 and is currently open access. It has received 11 citations till now. The article focuses on the topics: Population.
Citations
More filters
TL;DR: This work considers modelling and other applications, including the role of nearest neighbourhood in experimental design, the representation of connectivity in maps, and a new method for performing field surveys using hexagonal grids, which was demonstrated on montane heath vegetation.
385 citations
Book•
01 Jan 2002
TL;DR: The Human Dimension of Fisheries Science: (P. J. Reynolds, N. Dulvy And C. Roberts) uncovers the human dimension of fisheries science as well as the science and management of fisheries, and some of the aspects of management and ecology that have changed over time.
Abstract: Volume 1: Fish Biology. 1. Banishing Ignorance: Underpinning Fisheries with Basic Biology (P. J. B. Hart and J. D. Reynolds). 2. Phylogeny and Systematics of Fishes (A. C. Gill and R.D. Mooi). 3. Historical Biogeography of Fishes (R. D. Mooi and A. C. Gill). 4. The Physiology of Living in Water (O. Brix). 5. Environmental Factors and Rates of Development and Growth (M. Jobling). 6. Recruitment: Understanding Density--dependence in Fish Populations (R. A. Myers). 7. Life Histories of Fish (J. A. Hutchings). 8. Migration (J. Metcalfe, G. Arnold and R. McDowall). 9. Genetics of Fish Populations (R. D. Ward). 10. Behavioural Ecology of Reproduction in Fish (E. Forsgren, J. D. Reynolds and A. Berglund). 11. Fish Foraging and Habitat Choice: A Theoretical Perspective (G. G. Mittelbach). 12. Feeding Ecology of Piscivorous Fishes (F. Juanes, J. A. Buckel and F. S. Scharf). 13. Fish as Prey (J. Krause, E. M. A. Hensor and G. D. Ruxton). 14. Trophic Ecology and the Structure of Marine Food Webs (N. V.C. Polunin and J.K. Pinnegar). 15. Community Ecology of Freshwater Fishes (L. Persson). 16. Comparative Ecology of Marine Fish Communities (K. Martha M. Jones, D. G. Fitzgerald and P. F. Sale). 17. Interactions Between Fish, Parasites and Disease (I. Barber and R. Poulin). Volume 2: Fisheries. 1. The Human Dimension Of Fisheries Science: (P. J. B. Hart And J. D. Reynolds). 2. Fish Capture Devices In Industrial And Artisanal Fisheries And Their Influence On Management (O. A. Misund, J. Kolding and P. Freon). 3. Marketing Fish (J. A. Young And J. F. Muir). 4. A History Of Fisheries And Their Science And Management (T. D. Smith). 5. Gathering Data For Resource Monitoring And Fisheries Management (D. Evans and R. Grainger). 6. Surplus Production Models (J. T. Schnute And L. Richards). 7. Dynamic Pool Models I: Interpreting The Past Using Virtual Population Analysis (J. G. Shepherd And J. G. Pope). 8. Dynamic Pool Models II: Short--Term And Long--Term Forecasts Of Catch And Biomass (J. G. Shepherd And J. G. Pope). 9. A Bumpy Old Road: Size--Based Methods In Fisheries Assessment (T. J. Pitcher). 10. Ecosystem Models (D. Pauly And V. Christensen). 11. Individual--Based Models (G. Huse, J. Giske And A. G. V. Salvanes). 12. The Economics Of Fisheries (R. Hannesson). 13. Choosing The Best Model For Fisheries Assessment (P. Sparre And P. J. B. Hart). 14. Marine Protected Areas, Fish And Fisheries (N. V. C. Polunin). 15. Exploitation And Other Threats To Fish Conservation (J. D. Reynolds, N. K. Dulvy And C. M. Roberts). 16. Ecosystem Effects Of Fishing (M. J. Kaiser And S. Jennings). 17. Recreational Fishing (I. G. Cowx)
244 citations
TL;DR: This work presents the individual-based model Piscator, which describes a multi-species fish community and demonstrates techniques to deal with the inherent complexity of such a model, and proposes a novel procedure for calibration and analysis, in which the complexity of the model is increased step-by-step.
47 citations
TL;DR: Two individual-based models for the movement of elvers in the French river ‘Adour’ are built and a set of stochastic differential equations and a partial differential equation for the elvers’ density are rigorously obtained.
25 citations
References
More filters
TL;DR: This paper presents a dynamical regime in which (depending on the initial population value) cycles of any period, or even totally aperiodic but boundedpopulation fluctuations, can occur.
Abstract: Some of the simplest nonlinear difference equations describing the growth of biological populations with nonoverlapping generations can exhibit a remarkable spectrum of dynamical behavior, from stable equilibrium points, to stable cyclic oscillations between 2 population points, to stable cycles with 4, 8, 16, . . . points, through to a chaotic regime in which (depending on the initial population value) cycles of any period, or even totally aperiodic but boundedpopulation fluctuations, can occur. This rich dynamical structure is overlooked in conventional linearized analyses; its existence in such fully deterministic nonlinear difference equations is a fact of considerable mathematical and ecological interest.
1,456 citations
TL;DR: In this article, the authors study mathematical models for host-parasitoid interactions, where in each generation specified fractions (µN and µp, respectively) of the host and parasitoid subpopulations in each patch move to adjacent patches; in most previous work, the movement is not localized but is to any other patch.
Abstract: MOST environments are spatially subdivided, or patchy, and there has been much interest in the relationship between the dynamics of populations at the local and regional (metapopulation) scales1 Here we study mathematical models for host-parasitoid interactions, where in each generation specified fractions (µN and µp, respectively) of the host and parasitoid subpopulations in each patch move to adjacent patches; in most previous work, the movement is not localized but is to any other patch2 These simple and biologically sensible models with limited diffusive dispersal exhibit a remarkable range of dynamic behaviour: the density of the host and parasitoid subpopulations in a two-dimensional array of patches may exhibit complex patterns of spiral waves or spatially chaotic variation, they may show static 'crystal lattice' patterns, or they may become extinct This range of behaviour is obtained with the local dynamics being deterministically unstable, with a constant host reproductive rate and no density dependence in the movement patterns The dynamics depend on the host reproductive rate, and on the values of the parameters µN and µp The results are relatively insensitive to the details of the interactions; we get essentially the same results from the mathematically-explicit Nicholon–Bailey model of host-parasitoid interactions, and from a very general 'cellular automaton' model in which only qualitative rules are specified We conclude that local movement in a patchy environment can help otherwise unstable host and parasitoid populations to persist together, but that the deterministically generated spatial patterns in population density can be exceedingly complex (and sometimes indistinguishable from random environmental fluctuations)
804 citations
Book•
[...]
01 Jan 1997
TL;DR: Chaos Theory Tamed as mentioned in this paper provides a toolkit for readers, including vectors, phase space, Fourier analysis, time-series analysis, and autocorrelation, to learn and use the vocabulary of chaos.
Abstract: What is this business called 'chaos'? What does it deal with? Why do people think it's important? And how did the term 'chaos' - long associated with disorder - come to signify a new paradigm in the orderly realm of mathematics? The concept of chaos is one of the most exciting and rapidly expanding research topics of recent decades. Chaos might underlie many kinds of well-known processes - the performance of the stock market, the weather, the cries of newborn babies, the dripping of a leaky faucet, and more.In "Chaos Theory Tamed", scientist Garnett P. Williams walks the reader through this exciting territory, building an understanding of chaos and its significance in our lives. "Chaos" is a mathematical subject. If you seek bodice-ripping romance, this book is not for you. But if you are a researcher working with data...a scientist, engineer, or economist who has specialized outside the field of mathematics...or an interested person with a bit of background in algebra and statistics...then "Chaos Theory Tamed" can help you understand the basic concepts of this relatively new arm of science.Williams explains the terms necessary for an understanding of chaos theory. He discusses 'sensitive dependence on initial conditions' and what that means for long-term predictions. He explores the role of the chaotic or 'strange' attractor, order within chaos, fractal structure, and the emerging concepts of self-organization and complexity. Drawing from mathematics, physics, and statistics, the book provides a toolkit for readers, including vectors, phase space, Fourier analysis, time-series analysis, and autocorrelation.Williams describes routes that systems may take from regular behavior to chaos - period doubling, intermittency, and quasiperiodicity - and discusses nonlinear equations that can give rise to chaos. Dimension is a basic ingredient of chaos, and Williams brings clarity to the many ways in which this term is used by specialists in the field. And he explains how the magnitude of chaos may be gauged by Lyapunov exponents, Kolmogorov-Sinai entropy, and mutual information - mysterious terms that 'aren't all that difficult once we pick them apart,' says Williams. "Chaos Theory Tamed" makes generous use of lists, graphs, field examples, summaries, and - perhaps most important - friendly language to help the reader learn and use the vocabulary of chaos. It will help scientists, students, and others outside mathematics to use the concepts of chaos in working with data, and it will give the interested lay reader a foothold on the fundamentals of this new realm of thought.
593 citations