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Bioindicator Monitoring and Modelling for Informing River Health Management

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Bioindicator Monitoring and Modelling for Informing River Health Management Bioindicator monitoring and modelling for informing river health management A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Jawairia Sultana School of Biological Sciences Faculty of Sciences The University of Adelaide May 2020 Declaration I certify that this work contains no material which has been accepted for the award of any other degree or diploma in my name, in any university or other tertiary institution and, to the best of my knowledge and belief, contains no material previously published or written by another person, except where due reference has been made in the text. In addition, I certify that no part of this work will, in the future, be used in a submission in my name, for any other degree or diploma in any university or other tertiary institution without the prior approval of the University of Adelaide and where applicable, any partner institution responsible for the joint-award of this degree. I acknowledge that copyright of published works contained within this thesis resides with the copyright holder(s) of those works. I also give permission for the digital version of my thesis to be made available on the web, via the University’s digital research repository, the Library Search and also through web search engines, unless permission has been granted by the University to restrict access for a period of time. I acknowledge the support I have received for my research through the provision of an Australian Government Research Training Program Scholarship. Signature: ______ ____ Date: _________________________18-08-2020 i Abstract Freshwaters are considered to be the most degraded ecosystems. In an attempt to monitor river health, macroinvertebrates and diatoms proved to be suitable for routine short- and long-term monitoring. However, making complex decisions for river health management based solely on the data generated by such monitoring efforts is challenging, mainly when data has limited predictive capacity. To overcome this, the thesis focuses on the integration of bioindicator monitoring and novel modelling techniques with the associated challenges to inform river health management. This thesis aimed firstly to document differences between two local catchments using ecological threshold models and then test the performance of two commonly used models. Results suggested three times higher total phosphorus (TP) thresholds in the Onkaparinga River catchment as compared to the River Torrens catchment. It was also found that thresholds for electrical conductivity (EC) specified by Hybrid Evolutionary Algorithms (HEA) exceeded those identified by Threshold Indicator Taxa Analysis (TITAN). Importantly, despite the observed differences in thresholds, results indicated that South Australian water quality guidelines for freshwater systems might be too high. Another study aimed to identify model-based bias in threshold identification, found that two commonly used methods, i.e. gradient forest (GF) and TITAN are robust in identifying change in species responses. Still, threshold identification differs depending on the analysis used and the nature of ecological data. Noting the differences in performance of the two methods on the same field and synthetic data, we recommend careful application of GF and TITAN, will improve their use for river health management. Another critical and neglected aspect of threshold identification is dependence on spatial scale. Data analysis from field monitoring of diatoms and water quality during autumn and spring for two years was further extended by merging with a broader data set from South Australian streams, to highlight spatial influences on thresholds. Consistent or lower thresholds were found across spatial scales when spatial resolution was increased from state to local scale. However, higher TP and EC thresholds were observed for the South East region than for the Adelaide and Mount Lofty Ranges. Thus we highlighted that thresholds derived at broad scales alone are unlikely to be appropriate for finer-scale assessment. Another study applied an integrated modelling approach using GF, Soil and Water Assessment ii Tool (SWAT) and HEA to predict river health for future climate and land use. This study quantified population dynamics of sensitive taxa identified by GF under SWAT simulated future scenarios of deforestation, reforestation, climate change, and 10% increased urbanisation, as projected by local authorities over the next 30 years. HEA, used to predict future abundances, suggested a nonlinear response of species within commonly used Ephemeroptera, Plecoptera and Trichoptera grouping and we recommend to redirect focus of such studies from community to species-level. In reforestation and climate change scenarios, SWAT results also suggested a shift in the unusual permanent flowing stream of Sixth Creek towards intermittency under climate change and reforestation scenarios. Overall, outcomes of this research provide an improved understanding of local catchment processes in the context of global-scale challenges of climate and land use changes. iii Publications arising from this thesis Published Sultana, J., Recknagel, F., Tibby, J. and Maxwell, S. (2019). Comparison of water quality thresholds for macroinvertebrates in two Mediterranean catchments quantified by the inferential techniques TITAN and HEA. Ecological Indicators 101 (867-877). Sultana, J., Tibby, J., Recknagel, F., Maxwell, S. and Goonan, P. (2020). Comparison of two commonly used methods for identifying water quality thresholds in freshwater ecosystems using field and synthetic data, Science of the Total Environment 724, 137999: https://doi.org/10.1016/j.scitotenv.2020.137999 Sultana, J., Recknagel, F., Nguyen, H.H. and Tibby, J. (2019). Integrated approach for predicting impacts of future climate and land use changes on macroinvertebrates in a Mediterranean catchment using GF, SWAT and HEA models. International Congress on Modelling and Simulation, 2019 https://doi.org/10.36334/modsim.2019.G4.sultana Sultana, J., Recknagel, F., Nguyen, H. (2020). Species-specific macroinvertebrate responses to climate and land use scenarios in a Mediterranean catchment revealed by an integrated modelling approach. Ecological Indicators 118, 106766: https://doi.org/10.1016/j.ecolind.2020.106766 In process Sultana, J., Maxwell, S., Tibby, J. Evaluating spatial scale influences on threshold variations: Spatially-explicit responses of diatoms to water quality thresholds across multiple spatial scales (Intention to submit to Journal of Environmental Management) National/International conference abstracts Sultana, J., Tibby, J., Recknagel, F. and Maxwell, S. (2018). A rationale for threshold model selection and identification of ecological thresholds for macroinvertebrate assemblages: Comparison of two commonly used methods. Australian Freshwater Sciences Society Conference 2018, Adelaide, South Australia. Sultana, J., Recknagel, F. (2018). Overall and site-specific response of the macroinvertebrate community of Swan Coastal Plain Wetlands (West Australia) to water quality gradients revealed by GF and HEA. International Conference on Ecological Informatics 2018, Jena, Germany iv Acknowledgments This work was accomplished with the help of many whom I would like to extend my sincere appreciation, including my supervisors, family, friends and colleagues. I would like to acknowledge the Australian Government Research Training Program scholarship for offering me this unique opportunity to explore my research adventure of Australia under provided support. I also acknowledge the financial support for field logistics and training during my candidature from the School of Biological Sciences, the University of Adelaide. I am thankful to my supervisory team, “better than a thousand days of a diligent study is one day with a great mentor”. I would like to pay special regards to my principal supervisor, Friedrich Recknagel, for believing in my abilities as a researcher and providing me with an opportunity to learn from his valuable experience. I am thankful for his support, enthusiasm, patience and pushing me to achieve the last milestones. I wish to express deepest gratitude to my cosupervisor, John Tibby, whose support throughout my candidature helped me to strive for excellence. I am thankful to him for the resources, keen and critical reviews that made me to achieve quality work. I am indebted to the knowledge I gained from him related to the world of diatoms. Many of the diatom species are no longer just complicated names to me, but I can read these names with my heart and my mind. Special thanks to my cosupervisor, Sally Maxwell, for critical reviews, sharing macroinvertebrates knowledge and making me realise that it is never enough, which has improved the quality. I wish to thank you all for your continued online assistance during uncertain times of COVID 19. During my research candidature, number of researchers provided invaluable support whom I would like to acknowledge. I am thankful to my postgraduate coordinator, Steven Delean, for extending his useful expert suggestions on generating synthetic data experiments, Stephen M. Pederson, from Bioinformatics Hub, for his prompt responses, time and expert recommendations on R troubleshooting. I am thankful to the following researchers for sharing support: Peter Goonan from South Australian Environmental Protection authority for his useful review, support and expert opinions on selection of macroinvertebrates; Jennie Fluin, Department of Environment
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