Density-dependence uncertainty in population models for the conservation management of trout cod, Maccullochella macquariensis

Charles R. Todd, Simon J. Nicol, John D. Koehn

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45 Citations (Scopus)


A stochastic population model has been developed for exploring the conservation management of the endangered fish trout cod (Maccullochella macquariensis) in the circumstances of incomplete understanding of the ecology of the species as well as the absence of appropriate data for the estimation of some vital rates. The model includes a stage-structured approach with environmental and demographic variation, and examines three types of density dependence: Beverton-Holt, Ricker and a biomass approach that we have developed to incorporate intraspecific competition beyond recruitment to 1-year olds. The stochastic model was used to explore the current and future status of the protected and last self-sustaining natural population of trout cod, restricted to a 200km section of the Murray River in south-eastern Australia, under the different density-dependent mechanisms. Current practices for reintroducing trout cod were also evaluated. The analysis indicates that the protected natural population may be stable provided that it remains free from any significant disturbance. However, the analysis also indicates that trout cod may be very sensitive to any reduction in adult survival and remain potentially vulnerable to continued anthropogenic disturbance, in particular fishing. The analysis also indicates that the current practice of releasing fingerlings to establish a reintroduced population was more likely to fail than releasing on-grown 1-year-old fish at reintroduction sites. Furthermore, the traditional density-dependent mechanisms have less support than the applied biomass approach. The stochastic population model developed becomes a resource for guiding the conservation management and further research into the ecology of trout cod. Crown

Original languageEnglish
Pages (from-to)359-380
Number of pages22
JournalEcological Modelling
Issue number4
Publication statusPublished - 1 Feb 2004
Externally publishedYes


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