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STOCHASTIC POPULATION DYNAMICS OF AN INTRODUCED SWISS POPULATION OF THE IBEX
Author(s) -
Sæther Bernt-Erik,
Engen Steinar,
Filli Flurin,
Aanes Ronny,
Schröder Wolfgang,
Andersen Reidar
Publication year - 2002
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/0012-9658(2002)083[3457:spdoai]2.0.co;2
Subject(s) - population , density dependence , climate change , statistics , population density , ecology , logistic function , carrying capacity , stochastic modelling , population size , econometrics , population model , population growth , mathematics , environmental science , biology , demography , sociology
Using a long‐term data set on the fluctuations of a reintroduced Swiss population of ibex we estimated the parameters in a stochastic population model with theta‐logistic density regulation, and how the environmental stochasticity was related to different climate variables. Our aim was to examine quantitatively the relative effects of variation in parameters describing the expected dynamics and the environmental stochasticity as well as the uncertainties in them for the development of reliable population projections. The specific growth rate r 1 was 0.14. Density regulation mainly happened close to the carrying capacity K , indicating that the commonly used assumption in population ecology of loglinear density regulation is not always valid. Annual variation in the point estimates of the environmental stochasticity was correlated with winter climate. Uncertainties in parameter estimates were high, especially in the estimates of density regulation and r 1 . In order to examine the dynamical consequences of the estimates as well as the uncertainties in them, we constructed Population Prediction Intervals (PPI). A PPI is the stochastic interval that includes the unknown population size with probability (1 − α). Analyses of factors affecting the width of the PPI showed that the form of the density regulation as well as uncertainties in model parameters should be estimated when making projections of future fluctuations of introduced populations.