An Extension of a Galton-Watson Process to a Two-Sex Density Dependent Model.

Author(s):  
Charles J. Mode
2015 ◽  
Vol 39 (1) ◽  
pp. 015101 ◽  
Author(s):  
Jia-Xun Hou ◽  
Guang-Xiong Peng ◽  
Cheng-Jun Xia ◽  
Jian-Feng Xu

1986 ◽  
Vol 43 (1) ◽  
pp. 101-107 ◽  
Author(s):  
William S. Lovejoy

This paper addresses the problem of optimally exploiting an age-structured fishery with stochastic, density-dependent recruitment; stochastic dynamics; and cohort-dependent prices, costs, catchabilities, and survival rates. Sufficient conditions are derived for an age-at-first-capture to be a necessary component of the optimal management regime, and a lower bound on this critical age is calculated. The method consists of replacing the stochastic, density-dependent model with more traditional (stochastic, density-independent and deterministic, density-independent) models which yield lower bounds on the optimal escapement. A numerical example demonstrates the practical applicability of the results.


2014 ◽  
Vol 71 (7) ◽  
pp. 1629-1637 ◽  
Author(s):  
Joseph E. Powers

Abstract Natural mortality (M) rates are difficult to measure empirically and are often specified in stock assessments based on life history characteristics. More recently, these specifications have included M as a function of the size or age of a fish. However, natural mortality is a dynamic parameter that will change with the suite of predators and, thus, indirectly with cohort size and age. As an alternative, a density-dependent M rate function is derived and compared with the commonly used Lorenzen model, where M at age forms an allometric relationship with weight-at-age. The density-dependent model expresses M as a function of two parameters: one density dependent and one density independent. Properties of the two models (size-based vs. density-dependent) were explored to indicate conditions where the results are and are not similar. Associated catch equations, equilibrium analyses, and non-linear replacement lines in stock–recruitment theory are examined. Just as with density-independent values of M, most assessment data are not sufficient to provide precise estimates of density-dependent M parameters. However, the density-dependent model provides a basis for incorporating ecological variability into single-species assessments, noting the differing dynamics between short- and long-lived species. The incorporation of dynamic natural mortality has implications when estimating abundance trends and stock status, and ultimately setting management reference points.


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