DATLife is a curated data source for the comparative analysis of mortality and fertility across animals. In this context, “curated” means that the quality of information is assessed and recorded in the database. Moreover, all information is recalculated and continuously updated. We will also develop an R-package to provide advanced search functions, basic analysis, and visualization of data. All data in DATLife are published, but an embargo option allows for the inclusion of data before publication. For each data type, the study location, the study duration, and the end date of the study are recorded.
DATLife contains the following data types:
- Age-specific mortality information, mostly published as “life tables” or “age structures.” The data may stem from a variety of studies, such as short-term surveys, long-term individual-based research projects, or mark-recapture studies. As a minimal inclusion criterion, data for at least three ages after attaining sexual maturity must be provided. To properly assess data quality, we record the type of data gathered and the number of individuals in the study, or the number of encounters. The complete life table is calculated using standard assumptions after formulas given by see Preston et al. (2001) Demography: Measuring and Modeling Population Processes, Blackwell Publishers. Assumptions are:
- Stationary population. This means that
- Age-specific death rates are constant over time (but usually not constant over age)
- The flow of births is constant over time; the same number of newborn are added to the population per unit of time, whether the unit is a yeaer, a month, or a day
- Net migration rates are zero at all ages; the population is assumed to be closed to migration
- ax = 0.1 in the first age class, ax = 0.5 in all other age classes
- Age-specific fertility information may be published together with age-specific mortality. But we also collect data independent of mortality, such as the type of data and sex (e.g., the percentage of females that are pregnant at a certain age, the number of copulations observed, the number of eggs per female, female recruitment) as well as the number of animals the measure is derived from.
- Stage-specific survival is defined for our purposes as survival at a specific stage at which the exact ages are unknown. Typical examples of stage-specific survival data are annual juvenile and annual adult survival of animals. We also record the number of animals, or the number of encounters the survival measure was derived from; the recapture probability φ; and the measure of dispersion, as recommended in Lebreton (1992).
- Maximum observed lifespan is an extreme value of an individual. Large shares of the data stem from Carey’s book (Carey and Judge 2002: "Longevity Records:" Monographs on Population Aging, 8, Odense University Press) and the AnAge Database by Magalhaes, but also from our own bibliographic searches. Experience shows that it is important to record the “maximum potentially observable lifespan” of a species. For example, in a banding study on long-lived seabirds in which age assessment is impossible without the bird being banded, the maximum observed lifespan cannot exceed the study length. To facilitate quality assessment, we include the number of individual lifespans known within a study group, and whether the maximum observed lifespan was from an animal that was dead or alive.
- Age at sexual maturity. Although this age is frequently recorded in other compilations of data (Pantheria database, Animal Diversity Web), there are many fundamentally different definitions of the “age at sexual maturity.” The term may, for example, refer to the mean age at first birth in a population, or to the age of the animal at the earliest birth observed. Alternatively, it may refer to the mean age at or to the first observation of estrus, or the mean of the first age at which adult characteristics are displayed. Here, the original publications are retrieved and the exact data category is determined.