Aquaponics has the potential to be a superior food production method compared to traditional agriculture through its potential for sustainability. This is particularly important in advanced aquaponic systems that integrate waste disposal (e.g., kitchen waste) and involve several steps linking waste decomposition to protein production. In such systems a success of one type of organism propagates down the food chain and may have negative impact on contribution of other organisms, which reduces system efficiency. I hypothesised that a combination of top-down and bottom-up regulations, concepts borrowed from resilient natural ecosystems, would allow to optimize environment for aquaponics systems to avoid such negative impacts. First, I conducted an experiment using simplified systems with two trophic levels only to determine productivity, resistance and resilience of the various combinations of top-down and bottom-up forces. The simple systems contained algae and Daphnia magna and were placed under a light removal disturbance to observe the abilities of these different combinations to resist and recover from a generic negative environmental impact. Next, a similar light disturbance was implemented on a large complex aquaponics system to discover if it would react differently from the smaller ones. The resistance and resilience of algae in the small systems was not found to have any relationship to predation. The resilience of algae was better at low nutrient levels compared to high ones. There was evidence that low nutrient treatments had better resistance and resilience of abiotic factors. The larger systems appeared to have inferior resistance and resilience as compared to the simple, small systems. However, a time series analysis indicates that these large systems, in contrast to the simpler systems, actually improved in the amount of algae after the disturbance. New methods for accounting for this in resilience calculations are needed to eliminate potential statistical artifacts that might lead to some of my observations. / Thesis / Master of Science (MSc) / Aquaponics has the potential to be a superior food production method compared to traditional agriculture through its potential for sustainability. This is particularly important in advanced aquaponic systems that integrate waste disposal (e.g., kitchen waste) and involve several steps linking waste decomposition to protein production. In such systems a success of one type of organism propagates down the food chain and may have negative impact on contribution of other organisms, which reduces system efficiency. I hypothesised that a combination of top-down and bottom-up regulations, concepts borrowed from resilient natural ecosystems, would allow to optimize environment for aquaponics systems to avoid such negative impacts. First, I conducted an experiment using simplified systems with two trophic levels only to determine productivity, resistance and resilience of the various combinations of top-down and bottom-up forces. The simple systems contained algae and Daphnia magna and were placed under a light removal disturbance to observe the abilities of these different combinations to resist and recover from a generic negative environmental impact. Next, a similar light disturbance was implemented on a large complex aquaponics system to discover if it would react differently from the smaller ones. The resistance and resilience of algae in the small systems was not found to have any relationship to predation. The resilience of algae was better at low nutrient levels compared to high ones. There was evidence that low nutrient treatments had better resistance and resilience of abiotic factors. The larger systems appeared to have inferior resistance and resilience as compared to the simple, small systems. However, a time series analysis indicates that these large systems, in contrast to the simpler systems, actually improved in the amount of algae after the disturbance. New methods for accounting for this in resilience calculations are needed to eliminate potential statistical artifacts that might lead to some of my observations.
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/23464 |
| Date | 18 May 2018 |
| Creators | Takahashi, Michael |
| Contributors | Kolasa, Jurek, Biology |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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