  Plant survival is a key factor in forest dynamics and survival probabilities
often vary across life stages. Studies specifically aimed at assessing tree
survival are unusual and so data initially designed for other purposes often
need to be used; such data are more likely to contain errors than data
collected for this specific purpose. We investigate the survival rates of ten
tree species in a dataset designed to monitor growth rates. As some individuals
were not included in the census at some time points we use
capture-mark-recapture methods both to allow us to account for missing
individuals, and to estimate relocation probabilities. Growth rates, size, and
light availability were included as covariates in the model predicting survival
rates. The study demonstrates that tree mortality is best described as constant
between years and size-dependent at early life stages and size independent at
later life stages for most species of UK hardwood. We have demonstrated that
even with a twenty-year dataset it is possible to discern variability both
between individuals and between species. Our work illustrates the potential
utility of the method applied here for calculating plant population dynamics
parameters in time replicated datasets with small sample sizes and missing
individuals without any loss of sample size, and including explanatory
covariates.
