Fisheries Research Articles
The logic of comparative life history studies for estimating key parameters, with a focus on natural mortality rate
Document Type
Article
Publication Date
6-21-2016
Journal Title
ICES Journal of Marine Science
ISSN
Print: 1054-3139 Electronic: 1095-9289
Keywords
biological reference points, data selection bias, empirical relationships, Fmsy, hierarchical Bayesian models, indirect methods, intrinsic rate of population growth, life history correlates, mixed effects models, steepness parameter, stock-recruit relationships.
Disciplines
Aquaculture and Fisheries | Marine Biology
Abstract
There are a number of key parameters in population dynamics that are difficult to estimate, such as natural mortality rate, intrinsic rate of population growth, and stock-recruitment relationships. Often, these parameters of a stock are, or can be, estimated indirectly on the basis of comparative life history studies. That is, the relationship between a difficult to estimate parameter and life history correlates is examined over a wide variety of species in order to develop predictive equations. The form of these equations may be derived from life history theory or simply be suggested by exploratory data analysis. Similarly, population characteristics such as potential yield can be estimated by making use of a relationship between the population parameter and bio-chemico–physical characteristics of the ecosystem. Surprisingly, little work has been done to evaluate how well these indirect estimators work and, in fact, there is little guidance on how to conduct comparative life history studies and how to evaluate them. We consider five issues arising in such studies: (i) the parameters of interest may be ill-defined idealizations of the real world, (ii) true values of the parameters are not known for any species, (iii) selecting data based on the quality of the estimates can introduce a host of problems, (iv) the estimates that are available for comparison constitute a non-random sample of species from an ill-defined population of species of interest, and (v) the hierarchical nature of the data (e.g. stocks within species within genera within families, etc., with multiple observations at each level) warrants consideration. We discuss how these issues can be handled and how they shape the kinds of questions that can be asked of a database of life history studies.
Recommended Citation
Hoenig, J M,
Then, A Y,
Babcock, E A,
Hall, N G,
Hewitt, D A,
and
Hesp, S A.
(2016), The logic of comparative life history studies for estimating key parameters, with a focus on natural mortality rate. ICES Journal of Marine Science, 73 (10), 2453-2467.
https://library.dpird.wa.gov.au/fr_fja/177
