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

Månsson, Lena LU ; Ripa, Jörgen LU and Lundberg, Per LU (2007) In Population Ecology 49(4). p.287-296
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Population dynamics, Mechanistic model, Kalman filter, Time series data
in
Population Ecology
volume
49
issue
4
pages
287 - 296
publisher
Springer
external identifiers
  • wos:000249523500001
  • scopus:34548690143
ISSN
1438-390X
DOI
10.1007/s10144-007-0053-5
language
English
LU publication?
yes
id
fc649fb2-46da-4514-aedd-de714117df0a (old id 628680)
date added to LUP
2007-11-27 13:25:10
date last changed
2017-01-01 04:57:10
@article{fc649fb2-46da-4514-aedd-de714117df0a,
  abstract     = {Abstract Time series analysis is a tool that is now<br/><br>
commonly used when analysing the states of natural populations.<br/><br>
This is a particularly complicated task for ungulates,<br/><br>
since the data involved usually contain large<br/><br>
observation errors and span short periods of time relative to<br/><br>
the species’ life expectancies. Here we develop a method<br/><br>
that expands on previous analyses, combining statistical<br/><br>
state space modelling with biological mechanistic modelling.<br/><br>
This enables biological interpretability of the statistical<br/><br>
parameters. We used this method to analyse African<br/><br>
ungulate census data, and it revealed some clarifying patterns.<br/><br>
The dynamics of one group of species were generally<br/><br>
independent of density and strongly affected by rainfall,<br/><br>
while the other species were governed by a delayed density<br/><br>
dependence and were relatively unaffected by rainfall<br/><br>
variability. Dry season rainfall was more influential than<br/><br>
wet season rainfall, which can be interpreted as indicating<br/><br>
that adult survival is more important than recruitment in<br/><br>
governing ungulate dynamics.},
  author       = {Månsson, Lena and Ripa, Jörgen and Lundberg, Per},
  issn         = {1438-390X},
  keyword      = {Population dynamics,Mechanistic model,Kalman filter,Time series data},
  language     = {eng},
  number       = {4},
  pages        = {287--296},
  publisher    = {Springer},
  series       = {Population Ecology},
  title        = {Time series modelling and trophic interactions: rainfall, vegetation and un gulate dynamics},
  url          = {http://dx.doi.org/10.1007/s10144-007-0053-5},
  volume       = {49},
  year         = {2007},
}