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Time series modelling and trophic interactions: rainfall, vegetation and un gulate dynamics

Author

Summary, in English

Abstract Time series analysis is a tool that is now

commonly used when analysing the states of natural populations.

This is a particularly complicated task for ungulates,

since the data involved usually contain large

observation errors and span short periods of time relative to

the species’ life expectancies. Here we develop a method

that expands on previous analyses, combining statistical

state space modelling with biological mechanistic modelling.

This enables biological interpretability of the statistical

parameters. We used this method to analyse African

ungulate census data, and it revealed some clarifying patterns.

The dynamics of one group of species were generally

independent of density and strongly affected by rainfall,

while the other species were governed by a delayed density

dependence and were relatively unaffected by rainfall

variability. Dry season rainfall was more influential than

wet season rainfall, which can be interpreted as indicating

that adult survival is more important than recruitment in

governing ungulate dynamics.

Publishing year

2007

Language

English

Pages

287-296

Publication/Series

Population Ecology

Volume

49

Issue

4

Document type

Journal article

Publisher

Springer

Topic

  • Biological Sciences

Keywords

  • Population dynamics
  • Mechanistic model
  • Kalman filter
  • Time series data

Status

Published

Research group

  • Theoretical Population Ecology and Evolution Group

ISBN/ISSN/Other

  • ISSN: 1438-390X