Study mortality with hazard rates, not probabilities
O_LIMortality is a key process in ecology and evolution, and much effort is spent on statistical and theoretical modelling of this process. Mortality hazard rates describe individuals instantaneous ability to survive at different times, whereas survival probabilities are defined for time-intervals of a given length. In this commentary, we argue that it is often more meaningful to model and interpret interval-specific time-averaged mortality hazard rates than survival probabilities, also when using discrete-time models.\nC_LIO_LIWe discuss three topics where the concept of hazard rates is essential for sound biological inference, but nevertheless often not used: (i) modelling of covariate effects on survival probabilities or mortality hazard rates, (ii) modelling of multiple sources of mortality and competing risks, and (iii) elasticity analyses of population growth rate to demographic parameters. To facilitate estimation of cause-specific mortality hazard rates, we provide amendments to R package marked.\nC_LIO_LIBy focusing on modelling mortality hazard rates, one avoids several inherent problems of comparing survival or mortality probabilities. In particular, interpretations about relative differences between mortality hazard rates (measurements on a ratio scale), or effects of relative changes in mortality hazard rates on population growth (elasticities), are more meaningful than similar interpretations involving survival (or mortality) probabilities or odds (measurements on an absolute scale).\nC_LIO_LIThe concept of hazard rates is essential for understanding ecological and evolutionary processes and we give an intuitive explanation for this, using several examples. We provide some practical guidelines and suggestions for further methods developments.\nC_LI