Premium
On a log‐linear approach to detecting ecological interactions in monitored populations
Author(s) -
FREEMAN STEPHEN N.,
NEWSON STUART E.
Publication year - 2008
Publication title -
ibis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.933
H-Index - 80
eISSN - 1474-919X
pISSN - 0019-1019
DOI - 10.1111/j.1474-919x.2007.00770.x
Subject(s) - covariate , abundance (ecology) , inference , series (stratigraphy) , statistics , log linear model , parameterized complexity , population , ecology , mathematics , econometrics , statistical inference , estimation , space (punctuation) , linear model , biology , computer science , demography , algorithm , economics , artificial intelligence , paleontology , sociology , management , operating system
We discuss a log‐linear model for series of regular bird counts taken at a number of survey sites. The model is parameterized in terms of annual growth rates rather than actual indices of abundance, as is more frequently done. This not only permits easy estimation of and inference about these rates, but also allows us to model the effects upon population growth of covariates, such as the local presence of a competitor or predator, which may themselves vary in space and over time. A recursive relationship permits the expected count at a site to be functionally dependent upon the expected count at the previous visit. We discuss the advantages of using this relationship, rather than replacing the latter with their observed counterparts, as has been used previously.