Environmental variation can generate life-long similarities among individuals born in
the same breeding event, so-called cohort effects. Studies of cohort effects have to account for the
potentially confounding effects of current conditions (observation year) and age of individuals. How-
ever, estimation of such models is hampered by inherent collinearity, as age is the difference between
observation year (period) and cohort year. The difficulties of separating linear trends in any of the
three variables in Age-Period-Cohort (APC) models are the subject of ongoing debate in social
sciences and medicine but have remained unnoticed in ecology. After reviewing the use of APC mod-
els, we investigate the consequences of model specification on the estimation of cohort effects, using
both simulated data and empirical data from a long-term individual-based study of reindeer in Sval-
bard. We demonstrate that APC models are highly sensitive to the model’s treatment of age, period
and cohort, which may generate spurious temporal trends in cohort effects. Avoiding grouping ages
and using environmental covariates believed to be drivers of temporal variation reduces the APC iden-
tification problem. Nonetheless, ecologists should use caution, given that the specification issues in
APC models may have substantial impacts on estimated effect sizes and therefore conclusions.
age-period-cohort models; cohort; collinearity; phenotypic change; reindeer shrinking; senescence;
statistical model identification; temporal trend
