Analysis of seasonal growth through the application of a multiple linear regression model on data from tag-and-recapture experiments

Abstract

When the Brody coefficient K is subject to temporal variation, data from tag-and-recapture experiments permit analysis of seasonal growth. Temporal values for K can be estimated without using a pre-determined oscillating function and the impact of seasonality on annual growth can be analyzed more realistically. The method is applicable to intra-annual intervals of single or multiple cohorts.