Coastal estuaries are among the most productive areas of the ocean, both ecologically and economically. Increases in anthropogenic stress factors such as climate change, habitat alteration, contamination and high levels of disturbance in many estuaries have combined with natural stressors inherent in these systems to alter stress regimes on organisms. In NSW, Australia, coastal and estuarine environments support urban and industrial development activities, with many estuarine areas supporting valuable aquaculture farming. Bivalves are filter-feeding sessile organisms that inhabit a wide range of habitats. Bivalve species inhabiting estuarine and coastal environments have been used in environmental biomarker and monitoring studies due to their longevity, filter-feeding, sessile nature, ability to accumulate toxins and global distribution. The acquisition, transfer and use of energy is key to the growth, repair and reproduction of organisms, including bivalves. Changing environmental conditions influence an organism’s capacity to undertake these fitness-related activities and can be limited through their tolerance to stress. Measuring energy stores in the form of protein, lipid and glycogen and potential energy use in the form of electron transport activity (ETS) provides an approach to understanding how organisms are responding to these changing environmental conditions and to assess their capacity for fitness activities. Energy stores versus energy usage can be incorporated into the energetic measure of Cellular Energy Allocation (CEA) that can provide quantitative data on an organism’s energetic response to stress. Measurement of energetic components using classical chemical and enzymatic measurements is time consuming, difficult and can be quite costly. An alternative approach is to develop quantitative modelling using near infra-red spectroscopy (NIRS). NIRS is one of the classical methods for structure determination of small molecules. Using NIRS and statistical analysis techniques, it is possible to develop a quantitative predictive model for bioenergetic components in bivalves, using spectral image capture and entering the sample’s related analytical chemistry data. Application of quantitative NIRS models reduces both the time and cost associated with energy condition assessment of bivalves. NIRS quantitative models for total protein, lipid and glycogen stores and ETS activity in five Australian estuarine bivalve species (Saccostrea glomerata, Ostrea angasi, Crassostrea gigas, Mytilus galloprovincialis and Anadara trapezia) were developed, along with a comparison of single species versus multi-species models for protein, lipid and glycogen, with the benefits of multi-species models demonstrating greater model range and applicability. Model quality was assessed using the ratio of performance to the interquartile distance (RPIQ) and root mean square error of prediction (RMSEP). All five-species models had an RPIQ greater than 3 and RMSEP less than 12%,indicating that combining like species into models provides robust, reliable results. Comparisons between individual species models and aggregated models for three oyster species and five bivalve species for each storage component indicates that aggregating data from like species produces high quality models with robust and reliable quantitative application. The use of bivalve energy assessment is demonstrated by applying bioenergetic assessments to two bivalve stress scenarios. The first is the assessment of energetic changes in an Australian aquaculture oyster species, S. glomerata, over four seasons to demonstrate the seasonal fluctuations in bioenergetic measurements associated with naturally changing v environmental conditions. The study demonstrated clear seasonal trends, with glycogen and lipid content decreasing from summer maximums to autumn minimums then slowly increasing through winter and into spring. Protein and ETS activity demonstrated an opposite trend, with increases in autumn and stable through the other seasons. CEA showed a seasonal change, with higher values over summer, gradually decreasing over autumn and winter then starting to increase again in spring. These results indicate that seasonal changes have a significant influence on S. glomerata storage and allocation of energy. The second assessment demonstrates the energetic stress response of two oyster species, S. glomerata and O. angasi, exposed to a known metal contamination gradient in Lake Macquarie, NSW Australia. All energetic measures showed a downward trend in both species in response to sediment metal contamination, demonstrating the value of measuring energetics in bivalves as a measure of stress. Future studies into the NIRS modelling process should include determining methods for a more direct measure of energy consumption potential. Further useful NIRS models may be built for specific stress proteins such as heat shock proteins and metallothioneins. Application of energetic assessments to aquaculture-relevant scenarios such as basket and lease density stocking, potential new oyster growing areas and effectiveness of aquaculture techniques may allow for increased productivity. Application of the energetics method to new ecological scenarios and species may also be useful to allow health assessments of other aquatic organisms.
|Date of Award||2018|
|Supervisor||Bill Maher (Supervisor) & MD Tariq Ezaz (Supervisor)|