Temporal changes in telomere and tarsus lengths during artificial
selection
In order to analyze how nestling tarsus length and TL were affected by
the artificial selection for longer (high ) and shorter tarsi
(low ) during the study from 2002-2006, we used linear mixed
effects models (R package lme4 , Bates et al. 2015) including year
(i.e. birth cohort 1 to 5) as a continuous predictor variable, as well
as the quadratic effect of year (year2). Tarsus length
and TL are expected to change during development within individual
nestlings (Hall et al., 2004; Boonekamp et al., 2014) and there might be
sexual differences in morphology (Cordero et al., 2000) and telomere
dynamics (Barrett & Richardson, 2011). Thus, nestling age (number of
days since hatching) and sex were included as explanatory variables in
all models. Selection status category (0, 0.5, or 1) was included in
addition to an interaction term between selection status and year. All
models assumed a Gaussian error
distribution and included a random intercept for brood identity
to account for the
non-independence of nestlings from the same brood. We structured these
analyses into four sections, where we analyzed each selection regime
(high or low population) separately for each response
variable (tarsus length and TL). In order to identify the predictors
most supported by the empirical data we constructed and compared
alternative candidate models (Burnham & Anderson, 2002) fitted with
maximum likelihood within each section using
Akaike’s information criterion
(Akaike, 1973) corrected for small sample sizes (AICc, Hurvich & Tsai,
1989). All models were validated
visually by diagnostic plots and model parameters are given from models
refitted with restricted maximum likelihood (REML). To reduce the
problem of multicollinearity in multiple regression analyses, we only
included predictor variables with intercorrelation Pearson’sr <0.5 for all relevant pairs of explanatory variables.
All statistical analyses were performed in R version 3.5.2 (R Core Team,
2018).