Plastic and evolutionary responses of Chlamydomonas reinhardtii to multiple environmental drivers
Brennan, Georgina Lauren
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In my thesis I present data collected from a long-term selection experiment using the freshwater model organism Chlamydomonas reinhardtii. The selection experiment was designed to disentangle the effects of the number of multiple environmental drivers (MEDs) and the identity of those environmental drivers including high CO2, high temperature, general nutrient depletion, reduced light intensity, reduced phosphate availability, the addition of a herbicide, UV radiation and reduced pH. Using up to eight environmental drivers, I show how simple organisms such as C. reinhardtii evolve in response to MEDs. The first step in this investigation is to examine the short-term response of MEDs. Data collected at the beginning of the selection experiment will provide insight into the early stages of microevolution by investigating key differences in the short-term (plastic) responses to few vs. many MEDs. Here, I focus on how the data collected from the responses to single environmental drivers can help us predict the responses to MEDs by using ecological models (additive, comparative, multiplicative). I show that the short-term plastic responses to single environmental drivers can predict the effect of MEDs using the comparative model because the response is largely driven by the single dominant driver present. I also demonstrate the importance of the number of environmental drivers (NED) for making predictions from the single environmental drivers and show that predictions become more reliable as the NED increases. The results gathered from short-term responses provide evidence that single environmental driver studies are useful for predicting the effect of MEDs. After evolution, I found that the strength of selection varies with NED in a predictable way, which connects the NED to the evolutionary response (size of the direct response) through the strength of selection. Here, I used statistical models to quantify the effect of NED on the evolutionary response to MEDs and then interpreted this by considering the possible genetic constraints on adaptation to MEDs. A subset of populations evolved in environments with five environmental drivers and all populations evolved in the single environmental driver environments are used to examine how adapting to single vs. many environmental drivers affect local adaptation. I examine how populations selected in environments with one environmental driver, five environmental drivers and the evolved control, differ in their response to new environments with the same NED, environments with different NED, and a novel environment. I found that there is a relationship between local adaptation and the strength of selection in the local environment and patterns of local adaptation are affected by the NED of new environments. Lastly, I present the phenotypic consequences of evolution under MEDs. I found that before evolution, measures of chlorophyll content and cell size decline with increasing NED. However, after evolution the relationship between chlorophyll content and cell size with NED is weaker because populations converge on the same phenotypes as they evolve. I also present a case-study of how mass spectrometry methods can be used to better understand underlying molecular mechanisms of two phenotypes (chlorophyll positive and chlorophyll negative cells). This selection experiment is a good example of how laboratory investigations and model organisms can be used to design experiments with enough replication to have high statistical power in order to make more accurate predictions on the short- long-term effects of MEDs. Whilst there have been some studies on the effects of MEDs, these studies rarely have more than three environmental drivers (sometimes 5 environmental drivers) and there are only a handful of long-term MED studies. This study can be used to develop a priori hypotheses for investigating how environmental change will shape natural microbial communities, and is especially useful for organisms where long-term studies with multiple environmental drivers are unfeasible.