A new method for estimating growth transition matrices.
The vast majority of population models work using age or stage not length but there are many cases where animals cannot be aged sensibly or accurately. For these cases length-based models form the logical alternative but there has been little work done to develop and compare different methods of estimating growth transition matrices to be used in such models. This article demonstrates how a consistent Bayesian framework for estimating growth parameters and a novel method for constructing length transition matrices accounts for variation in growth in a clear and consistent manner and avoids potential subjective choices required using more established methods. The inclusion of the resultant growth uncertainty in population assessment models and the potential impact on management decisions is also addressed.
Hillary
R M
RM
Division of Biology, Imperial College, SL5 7PL, UK. Rich.Hillary@csiro.au
D017677:Age Distribution; D000375:Aging / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D011158:Population Growth