- Title
- Detecting the infrastructural, demographic and climatic changes on macroalgal blooms using cellular automata simulation
- Creator
- O'Neill, K.; Schreider, M.; McArthur, L.; Schrieder, S.
- Relation
- 20th International Congress on Modelling and Simulation (MODSIM2013). Proceedings of the 20th International Congress on Modelling and Simulation (Adelaide, S.A. 1-6 December, 2013) p. 441-447
- Relation
- https://www.mssanz.org.au/modsim2013/
- Publisher
- Modelling and Simulation Society of Australia and New Zealand
- Resource Type
- conference paper
- Date
- 2013
- Description
- Worldwide, the effects of anthropogenic nutrient loading into estuaries include a shift from sea grass to macroalgae, particularly the “bloom and bust” cycle of the ephemeral Chlorophyta. Macroalgal blooms only occur in spring and summer when rainfall prior to and during this time is low. This study describes temporal and spatial dynamics of nuisance macroalgal blooms in Avoca Lake, an intermittently closed and open lagoon lake (ICOLL) in NSW, Australia and identifies the main factors influencing algal growth in that lagoon. The dynamics are modelled using discrete cellular automata (CA) and a set of algorithms to capture the spread of the blooms. The objective at this stage is to identify the factors that contribute to the spread and ultimately to identify the factors that cause the initial outbreaks. Water temperature, salinity, dissolved oxygen, turbidity and bioavailable nutrients (nitrogen and phosphate) were measured, at weekly intervals, throughout the Lake during the major bloom which occurred in late 2012 as these variables are all considered likely candidates for blooms. Salinity and light were identified as two most important factors influencing algal growth; blooms always started at the shallow edges of the lake or around seagrass patches where algae attached to seagrass blades were positioned closer to the surface. No bloom occurred during the same period of the previous year when there was a lot more rainfall and much lower salinity in the ICOLL. Aerial photographs taken on four occasions over this period were digitised to record the extent of macroalgal cover. The CA model is initialised using knowledge of the behavioural dynamics of the algae; notably, that usually they are first observed at the edges of the ICOLL, where the water is warm and the light is good, due to the shallow water level. Later models will be initiated with observed data at the start of the 2012 bloom and validated by comparison of the simulated data with the observed. The CA model presented in this work is a further extension of the model developed by the authors. The discrete-Laplacian description for biomass provided a method to describe the spread and growth of algae, which incorporated currents, seagrass distribution, water depth and other parameters. The results of the present study highlight that when developing a model to predict the occurrence, spread and duration of macroalgal blooms in this ICOLL; such a model must include detailed data on dissolved oxygen, turbidity, salinity and nutrients. Additional complexity arises from the periodic opening of the ICOLL to the ocean. This also influences algal biomass dynamics, and the model will assist with determining the effect of the opening on the dynamics.
- Subject
- macroalgal bloom; Avoca ICOLL; cellular automata; parameter optimisation; simulation modelling
- Identifier
- http://hdl.handle.net/1959.13/1340935
- Identifier
- uon:28623
- Identifier
- ISBN:9780987214331
- Language
- eng
- Full Text
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