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Time series modelling and trophic interactions: rainfall, vegetation and ungulate dynamics
Author(s) -
Månsson Lena,
Ripa Jörgen,
Lundberg Per
Publication year - 2007
Publication title -
population ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.819
H-Index - 59
eISSN - 1438-390X
pISSN - 1438-3896
DOI - 10.1007/s10144-007-0053-5
Subject(s) - ungulate , trophic level , interpretability , ecology , vegetation (pathology) , biology , herbivore , series (stratigraphy) , density dependence , habitat , population , computer science , demography , pathology , machine learning , sociology , medicine , paleontology
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.