|Appears in Collections:||Biological and Environmental Sciences eTheses|
|Title:||Climate and nutrient controls of cyanobacteria|
|Author(s):||Richardson, Jessica A|
|Supervisor(s):||Hunter, Peter D|
Maberly, Stephen C
Harmful Algal Blooms
|Publisher:||University of Stirling|
|Citation:||Richardson. J., Feuchtmayr. H., Miller. C., Hunter. P. D., Maberly. S. C., Carvalho. L. (2019) Response of cyanobacteria and phytoplankton abundance to warming, extreme rainfall events and nutrient enrichment. Global Change Biology. 25, 3365–3380. https://doi.org/10.1111/gcb.14701|
Richardson. J., Miller. C., Maberly. S. C., Taylor. P., Globevnik. L., Hunter. P. D., … & Søndergaard, M. (2018) Effects of multiple stressors on cyanobacteria abundance vary with lake type. Global Change Biology. 24, 5044–5055. DOI: 10.1111/gcb.14396
|Abstract:||Cyanobacteria are a diverse group of primary producers that can form dense blooms which are a major threat to freshwater quality and global water security. While nutrient enrichment is a key driver of cyanobacteria abundance, there is a broad consensus that ‘blooms like it hot’ and that climate warming will promote the proliferation of cyanobacterial blooms. A highly cited hypothesis suggests that nutrients and temperature enhance cyanobacterial blooms synergistically, but only a few studies have tested this directly. Furthermore, while climate change is often treated as a single stressor – warming – the impact on cyanobacteria of other potentially interacting factors, such as seasonal or extreme rainfall patterns, also need to be understood. This thesis explores, the multiple stressor effects of global change factors – eutrophication, climate warming and changes in rainfall patterns – on cyanobacterial abundance. This extends our knowledge from simple single stressor studies to dynamic, multiple-stressor studies using a range of approaches and scales. This includes analysis of European scale observational data from 494 lakes (chapter two), a mesocosm experiment (chapter three) and a process-based phytoplankton community model, PROTECH (chapter four). Overall, it is hard to generalise cyanobacterial responses to multiple stressors; both synergistic and some surprising antagonistic relationships were observed influenced by: lake characteristics (chapter two); the gradient of the stressor tested (chapter three); the measure of the response (chapter three); the timing and magnitude of the stressor (chapter four) and the location of the waterbody (chapters two and four). Broad generalisations can be made within lake types, yet, despite the need for complex models to deliver improved understanding, complex solutions may not be required. While precise sensitivities to climate stressors may vary, nutrient control remains the clearest mitigation measure to reduce the abundance of cyanobacteria in freshwaters, and this becomes even more important in the face of climate warming.|
|Type:||Thesis or Dissertation|
|Jessica Richardson PhD thesis.pdf||6.69 MB||Adobe PDF||View/Open|
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