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Author(s) -
Dennis B.,
Kemp W. P.,
Taper M. L.
Publication year - 1998
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(1998)079[0426:jdd]2.0.co;2
Subject(s) - metapopulation , multivariate statistics , ecology , acrididae , density dependence , population , statistics , mathematics , biology , orthoptera , biological dispersal , demography , sociology
We present a new multivariate model for describing jointly fluctuating, density‐dependent populations. The model is a stochastic, multivariate version of a discrete‐time logistic model that explicitly accounts for spatial variation of growth rate parameters and covariances of fluctuations between populations. Statistical methods for applying the model to time series data on population abundances are described in detail. We derive formulas for maximum‐likelihood estimates of model parameters, and we develop hypothesis tests for various reduced model structures, such as density independence or zero covariance. The applicability of the model to any given data set can be thoroughly evaluated with diagnostic procedures. As examples, we apply the model to two population systems: rangeland grasshoppers (Orthoptera: Acrididae) in three physiographic regions of Montana, USA, and bull trout ( Salvelinus confluentus ) in four tributaries of the Flathead River in Montana. The model and associated statistical methods have potentially important applications in conservation biology for describing metapopulations and for assessing joint jeopardy of multiple populations.