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

Författare:
Publiceringsår: 2007
Språk: Engelska
Sidor: 287-296
Publikation/Tidskrift/Serie: Population Ecology
Volym: 49
Nummer: 4
Dokumenttyp: Artikel i tidskrift
Förlag: Springer

Sammanfattning

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.

Nyckelord

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

Övriga

Published
  • ISSN: 1438-390X

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