The Logic of Comparative Life History Studies for Estimating Key Population Parameters

Certain key parameters in population dynamics are difficult to estimate, such as natural mortality, intrinsic rate of population growth, stock-recruitment relationships and Fmsy. Often, parameters are estimated indirectly. The relationship between a difficult to estimate parameter and life history correlates is examined over many species to develop predictive equations whose form is derived from life history theory or is suggested by exploratory data analysis. Little has been done to evaluate these indirect estimators and there is little guidance on conducting and evaluating comparative studies. We consider six issues: 1) the parameter(s) of interest may be ill-defined, 2) true parameter values are not known for any species, 3) estimates available for comparison are often of unknown quality, 4) available estimates constitute a non-random sample from an ill-defined population of species of interest, 5) multiple estimates may exist for some species necessitating decisions on which values to use, and 6) thought may need to be given to the hierarchical structure of the data (i.e., stocks within species within genera within families) and to weighting observations. We discuss how to handle these issues and how they shape the kinds of questions that can be asked of a database of life history studies.