- •Contents
- •Preface
- •Acknowledgements
- •1 Introduction
- •2 Parameter estimation toolbox
- •3 Population size
- •4 Vital statistics: birth, death and growth rates
- •5 Rate of increase of a population
- •6 Density dependence
- •7 Spatial parameters
- •8 Competition
- •9 Predator–prey, host–parasitoid and plant–herbivore models
- •10 Host–pathogen and host–parasite models
- •11 The state of the art
- •References
- •Index
M E T H O D S I N E C O L O G Y
Population Parameters: Estimation for Ecological Models
H A M I S H M c C A L L U M
Department of Zoology and Entomology and Centre for Conservation Biology
University of Queensland Brisbane, Australia
P O P U L A T I O N E S T I M A T I O N E C O L O G I C A L
P A R A M E T E R S : F O R
M O D E L S
M E T H O D S I N E C O L O G Y
Series Editors
J . H . L A W T O N F R S
Imperial College at Silwood Park
Ascot, UK
G . E . L I K E N S
Institute of Ecosystem Studies
Millbrook, USA
M E T H O D S I N E C O L O G Y
Population Parameters: Estimation for Ecological Models
H A M I S H M c C A L L U M
Department of Zoology and Entomology and Centre for Conservation Biology
University of Queensland Brisbane, Australia
© 2000 by
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Contents
Preface, vii
Acknowledgements, ix
1Introduction, 1
2 Parameter estimation toolbox, 14
3Population size, 49
4 Vital statistics: birth, death and growth rates, 102
5 Rate of increase of a population, 139
6 Density dependence, 157
7 Spatial parameters, 184
8Competition, 216
9 Predator–prey, host–parasitoid and plant–herbivore models, 244
10Host–pathogen and host–parasite models, 284
11The state of the art, 313 References, 320
Index, 339
v
The Methods in Ecology Series
The explosion of new technologies has created the need for a set of concise and authoritative books to guide researchers through the wide range of methods and approaches that are available to ecologists. The aim of this series is to help graduate students and established scientists choose and employ a methodology suited to a particular problem. Each volume is not simply a recipe book, but takes a critical look at different approaches to the solution of a problem, whether in the laboratory or in the field, and whether involving the collection or the analysis of data.
Rather than reiterate established methods, authors have been encouraged to feature new technologies, often borrowed from other disciplines, that ecologists can apply to their work. Innovative techniques, properly used, can offer particularly exciting opportunities for the advancement of ecology.
Each book guides the reader through the range of methods available, letting ecologists know what they could, and could not, hope to learn by using particular methods or approaches. The underlying principles are discussed, as well as the assumptions made in using the methodology, and the potential pitfalls that could occur – the type of information usually passed on by word of mouth or learned by experience. The books also provide a source of reference to further detailed information in the literature. There can be no substitute for working in the laboratory of a real expert on a subject, but we envisage the Methods in Ecology Series as being the ‘next best thing’. We hope that, by consulting these books, ecologists will learn what technologies and techniques are available, what their main advantages and disadvantages are, when and where not to use a particular method, and how to interpret the results.
Much is now expected of the science of ecology, as humankind struggles with a growing environmental crisis. Good methodology alone never solved any problem, but bad or inappropriate methodology can only make matters worse. Ecologists now have a powerful and rapidly growing set of methods and tools with which to confront fundamental problems of a theoretical and applied nature. We see the Methods in Ecology Series as a major contribution towards making these techniques known to a much wider audience.
John H. Lawton
Gene E. Likens
vi
Preface
One of the axioms of modelling is GIGO: garbage in, garbage out. The fundamental aim of this book is to have less garbage going into ecological models, and thus better predictions and improved contributions to ecological understanding coming out the other end.
Modelling has a central role in ecology, as it does in all sciences. Any attempt to generalize or understand how an ecological process works requires a model. Whilst such a model need not be in mathematical form, or involve quantitative parameter estimates, a mathematical model has the advantage that it will require an explicit statement of the underlying assumptions. Any attempt to manage an ecological system also involves a model. Management of a system entails making a choice from a range of possible actions. Making the correct choice depends upon a capacity to predict the likely response of the system to these different actions. Prediction necessarily requires models, and almost always it will be worthwhile to have quantitative predictions, which must be based on quantitative parameter estimates.
Ecological modelling is currently moving away from being largely undertaken by expert mathematicians and programmers and into a situation where models are being used by field ecologists and wildlife managers. Most of these users will rely upon prewritten models, into which they will put their own parameter estimates. Their main requirement is not for nuts and bolts details of how models are constructed, but for information on how to provide appropriate input to the models. A recurrent theme in this book is that the most appropriate way to estimate a given parameter depends on the nature of the model in which the parameter is used, and on the objective of the modelling process. It is also essential for model users to understand how to interpret model results, given the inevitable approximations and errors in the parameter estimation process.
A particular feature of this book is the emphasis on estimating parameters for ecological interactions. Charles Elton (1933) defined animal ecology as ‘the inter-relations of animals, numbers, social organization, migration, food and many [other factors]’. Much theoretical ecology has also, of course, concentrated on interactions. However, most of the existing books concerned with statistical aspects of animal ecology have concentrated on estimating population size and density for single populations, and on estimating birth, death and growth rates, without taking biotic interactions into account. The literature on estimating parameters for interactions has remained scattered.
vii
viii P R E F A C E
I hope that, by bringing it together, I will enable researchers and managers to include interactions in their models more easily, producing improved ecological understanding and predictions.
Hamish McCallum
Brisbane
viii