scispace - formally typeset
Open AccessBook

Stability and Complexity in Model Ecosystems

Reads0
Chats0
TLDR
Preface vii Preface to the Second Edition Biology Edition 1.
Abstract
Preface vii Preface to the Second Edition Biology Edition 1. Intoduction 3 2. Mathematical Models and Stability 13 3. Stability versus Complexity in Multispecies Models 4. Models with Few Species: Limit Cycles and Time Delays 79 5. Randomly Fluctuating Environments 109 6. Niche Overlap and Limiting Similarity 139 7. Speculations 172 Appendices 187 Afterthoughts for the Second Edition 211 Bibliography to Afterthoghts 234 Bibliography 241 Author Index 259 Subject Index 263

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Who is a Modeler

TL;DR: It is argued that modeling can be distinguished from other forms of theorizing by the procedures modelers use to represent and to study real-world phenomena: indirect representation and analysis.
Journal ArticleDOI

Fluctuation scaling in complex systems: Taylor's law and beyond

TL;DR: A review of the literature on fluctuation scaling can be found in this paper, where a mean-field framework based on sums of random variables is used to show how general the above scaling relationship is by surveying the literature.
Journal ArticleDOI

Allee effect and population dynamics in the Glanville fritillary butterfly

TL;DR: It is shown that emigration rate increases and the fraction of mated females decreases with decreasing local density, and the Allee effect increases the significance of the rescue effect in metapopulations, and thereby the potential for alternative stable states in meetapopulation as well as in local dynamics.
Journal ArticleDOI

Coexistence of Competitors in Patchy Environment

Ilkka Hanski
- 01 Jun 1983 - 
TL;DR: In this article, the authors modify Levins' model to allow for a varying difference between the local and regional time scales, and regional competition between two species is analyzed with the new model.
Journal ArticleDOI

Numerical modelling in biosciences using delay differential equations

TL;DR: In this paper, the authors analyze both the qualitative and quantitative role that delays play in basic time-lag models proposed in population dynamics, epidemiology, physiology, immunology, neural networks and cell kinetics.