1991
DOI: 10.1017/cbo9780511624094
|View full text |Cite
|
Sign up to set email alerts
|

Modelling Biological Populations in Space and Time

Abstract: This volume develops a unifying approach to population studies, emphasising the interplay between modelling and experimentation. Throughout, mathematicians and biologists are provided with a framework within which population dynamics can be fully explored and understood. Aspects of population dynamics covered include birth-death and logistic processes, competition and predator-prey relationships, chaos, reaction time-delays, fluctuating environments, spatial systems, velocities of spread, epidemics, and spatia… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

8
392
0
4

Year Published

2001
2001
2016
2016

Publication Types

Select...
5
5

Relationship

0
10

Authors

Journals

citations
Cited by 585 publications
(404 citation statements)
references
References 0 publications
8
392
0
4
Order By: Relevance
“…Thus, at the end of the calculations, we take the time-step to zero, so time becomes continuous. We note that the models presented have close connections with `pure death' models of population biology (Renshaw, 1993).…”
Section: Appendix Bmentioning
confidence: 77%
“…Thus, at the end of the calculations, we take the time-step to zero, so time becomes continuous. We note that the models presented have close connections with `pure death' models of population biology (Renshaw, 1993).…”
Section: Appendix Bmentioning
confidence: 77%
“…DISCUSSION Theories in conservation biology (Diamond 1975), metapopulation ecology (Hanksi 1999), population ecology (Haccou & Iwasa 1996;Matis & Kiffe 2000;Haccou & Vatunin 2003) and invasion biology (Leung et al 2004;MacIsaac et al 2004) have emphasized the importance of immigration for population persistence. Though the contribution of immigration to population growth rate is typically small, immigration is of considerable importance in stochastic models (Bailey 1964;Renshaw 1991;Matis & Kiffe 2000), and in nature, where rescue effects dramatically enhance growth of nearly extinct populations (Brown & Kodric-Brown 1977;Gotelli 1991).…”
Section: Results (A) Hypothesis 1: Realized Population Growth Ratementioning
confidence: 99%
“…Despite what could be generally considered [6], deterministic models do not describe the average result obtained from an infinite number of stochastic simulations (see, for instance, [16]), and stochastic models result in lower epidemics than deterministic models. This observation, confirmed here (Fig.…”
Section: Discussionmentioning
confidence: 99%