| Summary: | cum laude graduation (with distinction) There is concern that a warmer climate may boost carbon emissions from lakes and promote the chance that they lose their vegetation and become dominated by phytoplankton or cyanobacteria. However, these hypotheses have been difficult to evaluate due to the scarcity of relevant field data. To explore potential climate effects we sampled 83 lakes along a latitudinal gradient of more than 6000 km ranging from Rio Grande do Norte in Brazil to the South of Argentina (5-55 oS). The lakes were selected so as to be as similar as possible in morphology and altitude while varying as much as possible in trophic state within regions. All lakes were sampled once during summer (subtropical, temperate and tundra lakes) or during the dry season (tropical lakes) between November 2004 and March 2006 by the same team. In the first chapters I address the question how climate might affect the chances for shallow lakes to be dominated by submerged plants. It has been shown that temperate lakes tend to have two contrasting states over a range of conditions: a clear state dominated by aquatic vegetation or a turbid state. The turbid state is typically dominated by phytoplankton and often characterized by poorer water quality than the clear state. The backbone of the theory explaining this pattern is a supposed positive feedback of submerged vegetation on water clarity: vegetation enhances water clarity and clearer water, in turn, promotes vegetation growth. The theory furthermore asserts that submerged vegetation coverage diminishes when nutrient concentrations increase until a critical point at which the entire vegetation disappears due to light limitation. Both aspects of the alternative state theory have been well studied in temperate shallow lakes, but the validity of the theory for warmer lakes has been questioned. In chapter 2 a graphical model is used to show how climate effects on different mechanisms assumed in the theory may affect the general predictions. An analysis of our data ...
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