Elasmobranch bycatch in the demersal prawn trawl fishery in the Gulf of Papua, Papua New Guinea.

The elasmobranch bycatch of the Gulf of Papua Prawn Fishery is investigated in detail for the first time. Fisheries observers collected data on the elasmobranch bycatch from a total of 403 trawl sets (1,273 hrs) in the Gulf of Papua. A total of 40 species of elasmobranchs were recorded ranging in size from a 12 cm disc width stingray to a 350 cm total length sawfish. High mortality rates were recorded (>80%), attributed to the long trawl durations (up to 4 hours). The future inclusion of bycatch reduction devices would likely reduce the number of larger elasmobranchs being caught, based on evidence from the prawn trawl fisheries of northern Australia, and is being investigated by the PNG National Fisheries Authority. Differences in catch compositions were detected across the management zones as well as between the two monsoonal seasons (SE Monsoon and NW Monsoon). Increased monitoring and additional research is required and management plans should address the elasmobranch bycatch and in particular their high mortality rate.

Artificial neural networks and geometric morphometric methods as a means for classification: A case-study using teeth from Carcharhinus sp. (Carcharhinidae).

Over the past few decades, geometric morphometric methods have become increasingly popular and powerful tools to describe morphological data while over the same period artificial neural networks have had a similar rise in the classification of specimens to preconceived groups. However, there has been little research into how well these two systems operate together, particularly in comparison to preexisting techniques. In this study, geometric morphometric data and multilayer perceptrons, a style of artificial neural network, were used to classify shark teeth from the genus Carcharhinus to species. Three datasets of varying size and species differences were used. We compared the performance of this combination with geometric morphometric data in a linear discriminate function analysis, linear measurements in a linear discriminate function analysis, and a preexisting methodology from the literature that incorporates linear measurements and a two-layered discriminate function analysis. Across datasets, geometric morphometric data in a multilayer perceptron tended to yield modest accuracies but accuracies that varied less across species whereas other methods were able to achieve higher accuracies in some species at the expense of lower accuracies in others. Further, the performance of the two-layered discriminate function analysis illustrates that constraining what material is classified can increase the accuracy of a method. Based on this tradeoff, the best methodology will then depend on the scope of the study and the amount of material available. J. Morphol. 278:131-141, 2017. ©© 2016 Wiley Periodicals,Inc.

Investigating evolutionary lines of least resistance using the inverse protein-folding problem.

We present a polynomial time algorithm for estimating optimal HP sequences that fold to a specified target protein conformation based on Sun et al's Grand Canonical (GC) model. Application of the algorithm to related proteins taken from the PDB allows us to explore the nature of the protein genotype:phenotype map. Results suggest: (1) that the GC model captures important biological aspects of the mapping between protein sequences and their corresponding structures, and (2) the set of sequences that map to a target structure with optimal energy is affected by minor differences in structure.