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

A note on sampling chironomids for RNA-based studies of natural populations that retains critical morphological vouchers

The rapid uptake of transcriptomic approaches in freshwater ecology has seen a wealth of data produced concerning the ways in which organisms interact with their environment on a molecular level. Typically, such studies focus either at the community level and so don’t require species identifications, or on laboratory strains of known species identity or natural populations of large, easily identifiable taxa. For chironomids, impediments still exist for applying these technologies to natural populations because they are small-bodied and often require time-consuming secondary sorting of stream material and morphological voucher preparation to confirm species diagnosis. These procedures limit the ability to maintain RNA quantity and quality in such organisms because RNA degrades rapidly and gene expression can be altered rapidly in organisms; thereby limiting the inclusion of such taxa in transcriptomic studies. Here, we demonstrate that these limitations can be overcome and outline an optimised protocol for collecting, sorting and preserving chironomid larvae that enables retention of both morphological vouchers and RNA for subsequent transcriptomics purposes. By ensuring that sorting and voucher preparation are completed within <4 hours after collection and that samples are kept cold at all times, we successfully retained both RNA and morphological vouchers from all specimens. Although not prescriptive in specific methodology, we anticipate that this paper will assist in promoting transcriptomic investigations of the sublethal impact on chironomid gene expression of changes to aquatic environments.

Evaluation of oil production from oil palm empty fruit bunch by oleaginous micro-organisms

Oil palm empty fruit bunch (EFB) is a readily available, lignocellulosic biomass that has potential to be utilized as a carbon substrate for microbial oil production. In order to evaluate the production of microbial oil from EFB, a technical study was performed through the cultivation of oleaginous micro-organisms (Rhodotorula mucilaginosa, Aspergillus oryzae, and Mucor plumbeus) on EFB hydrolyzates. EFB hydrolyzates were prepared through dilute acid pre-treatment of the biomass, where the liquid fraction of pre-treatment was detoxified and used as an EFB liquid hydrolyzate (EFBLH). The solid residue was enzymatically hydrolyzed prior to be used as an EFB enzymatic hydrolyzate (EFBEH). The highest oil concentrations were obtained from M. plumbeus (1.9 g/L of oil on EFBLH and 4.7 g/L of oil on EFBEH). In order to evaluate the feasibility of large-scale microbial oil production, a techno-economic study was performed based on the oil yields of M. plumbeus per hectare of plantation, followed by the estimation of the feedstock cost for oil production. Other oil palm biomasses (frond and trunk) were also included in this study, as it could potentially improve the economics of large-scale microbial oil production. Microbial oil from oil palm biomasses was estimated to potentially increase oil production in the palm oil industry up to 25%, at a cheaper feedstock cost. The outcome of this study demonstrates the potential integration of microbial oil production from oil palm biomasses with existing palm oil industry (biodiesel, food and oleochemicals production), that could potentially enhance sustainability and profitability of microbial oil production.