Improving productivity in mixed-species plantations.

A workshop held in Ballina (NSW, Australia) during 5–7 August 2005 in association with the XXII IUFRO World Congress, sought to quantify the potential of mixtures to sustain and enhance the growth and productivity, soil fertility, tree and stand health, wood quality, and economics of polyculture plantations. Participants were specifically asked to address whether demonstrable productivity gains in mixed-species plantations, compared with monoculture plantations, could make mixtures a commercially attractive option. We specifically sought to attract presentations addressing the operational challenges of making mixed-species plantations practical and successful, and attracted representatives from several industrial plantation agencies.

Generalised growth models for aquatic species with an application to blacklip abalone (Haliotis rubra)

This paper presents a maximum likelihood method for estimating growth parameters for an aquatic species that incorporates growth covariates, and takes into consideration multiple tag-recapture data. Individual variability in asymptotic length, age-at-tagging, and measurement error are also considered in the model structure. Using distribution theory, the log-likelihood function is derived under a generalised framework for the von Bertalanffy and Gompertz growth models. Due to the generality of the derivation, covariate effects can be included for both models with seasonality and tagging effects investigated. Method robustness is established via comparison with the Fabens, improved Fabens, James and a non-linear mixed-effects growth models, with the maximum likelihood method performing the best. The method is illustrated further with an application to blacklip abalone (Haliotis rubra) for which a strong growth-retarding tagging effect that persisted for several months was detected. (C) 2013 Elsevier B.V. All rights reserved.