A hidden Markov model approach for determining vessel activity from vessel monitoring system data.

Many fisheries worldwide have adopted vessel monitoring systems (VMS) for compliance purposes. An added benefit of these systems is that they collect a large amount of data on vessel locations at very fine spatial and temporal scales. This data can provide a wealth of information for stock assessment, research, and management. However, since most VMS implementations record vessel location at set time intervals with no regard to vessel activity, some methodology is required to determine which data records correspond to fishing activity. This paper describes a probabilistic approach, based on hidden Markov models (HMMs), to determine vessel activity. A HMM provides a natural framework for the problem and, by definition, models the intrinsic temporal correlation of the data. The paper describes the general approach that was developed and presents an example of this approach applied to the Queensland trawl fishery off the coast of eastern Australia. Finally, a simulation experiment is presented that compares the misallocation rates of the HMM approach with other approaches.

The grand challenge of food security - general lessons from a comprehensive approach to protecting stored grain from insect pests in Australia and India

We outline a philosophical approach to Grand Challenge projects, with particular reference to our experience in our food security project involving the protection of stored grain from insect attack in two countries on different continents. A key consideration throughout has been the management of resistance in these pests to the valuable fumigant phosphine. Emphasis is given to the chain of research issues that required solution and the assembly of a well-integrated team, overlapping in skills for effective communication, in each country to solve the problems identified along that chain. A crucial aspect to maintaining direction is the inclusion of key end users in all deliberations, as well as the establishment and maintenance of effective outlets for the dissemination of practical recommendations. We finish with a summary of our achievements with respect to our approach to this food security Grand Challenge.

Improved Approach for Analyzing Bromophenols in Seafood Using Stable Isotope Dilution Analysis in Combination with SPME

An analytical method for the measurement of five naturally occurring bromophenols of sensory relevance in seafood (barramundi and prawns) is presented. The method combines simultaneous distillation−extraction followed by alkaline back extraction of a hexane extract and subsequent acetylation of the bromophenols. Analysis of the bromophenol acetates was accomplished by headspace solid phase microextraction and gas chromatography−mass spectrometry using selected ion monitoring. The addition of 13C6 bromophenol stable isotope internal standards for each of the five congeners studied permitted the accurate quantitation of 2-bromophenol, 4-bromophenol, 2,6-dibromophenol, 2,4-dibromophenol, and 2,4,6-tribromophenol down to a limit of quantification of 0.05 ng/g of fish flesh. The method indicated acceptable precision and repeatability and excellent linearity over the typical concentration range of these compounds in seafood (0.5−50 ng/g). The analytical method was applied to determine the concentration of bromophenols in a range of farmed and wild barramundi and prawns and was also used to monitor bromophenol uptake in a pilot feeding trial.

Estimation of light interception in research environments: A joint approach using directional light sensors and 3D virtual plants applied to sunflower (Helianthus annuus) and Arabidopsis thaliana in natural and artificial conditions

Light interception is a major factor influencing plant development and biomass production. Several methods have been proposed to determine this variable, but its calculation remains difficult in artificial environments with heterogeneous light. We propose a method that uses 3D virtual plant modelling and directional light characterisation to estimate light interception in highly heterogeneous light environments such as growth chambers and glasshouses. Intercepted light was estimated by coupling an architectural model and a light model for different genotypes of the rosette species Arabidopsis thaliana (L.) Heynh and a sunflower crop. The model was applied to plants of contrasting architectures, cultivated in isolation or in canopy, in natural or artificial environments, and under contrasting light conditions. The model gave satisfactory results when compared with observed data and enabled calculation of light interception in situations where direct measurements or classical methods were inefficient, such as young crops, isolated plants or artificial conditions. Furthermore, the model revealed that A. thaliana increased its light interception efficiency when shaded. To conclude, the method can be used to calculate intercepted light at organ, plant and plot levels, in natural and artificial environments, and should be useful in the investigation of genotype-environment interactions for plant architecture and light interception efficiency. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

Issues of Digital Ecosystems Approach to Biological Ecosystem Simulation Model Fit Optimization

This study examines the application of digital ecosystems concepts to a biological ecosystem simulation problem. The problem involves the use of a digital ecosystem agent to optimize the accuracy of a second digital ecosystem agent, the biological ecosystem simulation. The study also incorporates social ecosystems, with a technological solution design subsystem communicating with a science subsystem and simulation software developer subsystem to determine key characteristics of the biological ecosystem simulation. The findings show similarities between the issues involved in digital ecosystem collaboration and those occurring when digital ecosystems interact with biological ecosystems. The results also suggest that even precise semantic descriptions and comprehensive ontologies may be insufficient to describe agents in enough detail for use within digital ecosystems, and a number of solutions to this problem are proposed.

A participatory systems approach to understanding climate adaptation needs

Emerging literature on climate adaptation suggests the need for effective ways of engaging or activating communities and supporting community roles, coupled with whole-of-system approaches to understanding climate change and adaptation needs. We have developed and evaluated a participatory approach to elicit community and stakeholder understanding of climate change adaptation needs, and connect diverse community members and local office bearers towards potential action. The approach was trialed in a series of connected social-ecological systems along a transect from a rural area to the coast and islands of ecologically sensitive Moreton Bay in Queensland, Australia. We conducted ‘climate roundtables’ in each of three areas along the transect, then a fourth roundtable reviewed and extended the results to the region as a whole. Influence diagrams produced through the process show how each climate variable forecast to affect this region (heat, storm, flood, sea-level rise, fire, drought) affects the natural environment, infrastructure, economic and social behaviour patterns, and psychosocial responses, and how sets of people, species and ecosystems are affected, and act, differentially. The participatory process proved effective as a way of building local empathy, a local knowledge base and empowering participants to join towards future climate adaptation action. Key principles are highlighted to assist in adapting the process for use elsewhere.