Adaptation in complex scenarios

The observation that organisms are adapted to their environment is obvious, yet we can only explain how this occurs in extreme scenarios such as the evolution of antibiotic and pesticide resistance, heavy metal tolerance, and starvation. Typical studies that aim to understand how organisms adapt following an environmental change proceed by placing a population in an environment to which it is poorly adapted. This stressful environment is usually extreme so as to provoke an observable response, and is also usually static. For example, a plant population may be transferred from a nutrient-rich environment to one where a particular nutrient is nearly absent. The population then adapts by the sequential fixation of novel mutations that increase its growth and reproduction in the new environment. Theory and experiments that use this framework have allowed us to describe how fast a population adapts over time, how many mutations are involved in a typical round of adaptation, and how many different outcomes we expect if the same population adapts to the same stressful environment many times. However, very few environmental changes outside of laboratories and natural disasters involve the sudden transition from one relatively stable environment to a second, drastically different, stable environment. Instead, environments tend to change gradually over time, such that most populations exist in an environment that is only slightly different from that of a recent ancestor, even though it may differ substantially from a more distant ancestor. Global change is an example of this, where plant populations are currently exposed to levels of carbon dioxide more than twice as high as those of the last glaciation 10,000 years ago, but only a few percent higher than those of a decade ago. Thus, at any given time, populations are adapting to a subtle shift in environment, but the environment does not hold still while they do it. This suggests that studies of adaptation should incorporate both the magnitude and rate of environmental change. A second consideration is that populations do not adapt in isolation, but must compete with other populations while they are doing so. If one considers two populations in a changing environment, it is possible that one population excludes the other, but it is also possible that the populations adapt during this succession, such that both the community composition (which species are present) as well as the genetic makeup of a given species changes over time. For example, if we wish to guess how much carbon will be taken up by oceans in the future, we need to know which species of phytoplankton will be dominant as well as if the future populations of the dominant species will take up carbon at much the same rate as contemporary populations of that same species. Because of this, it is important to know how and if ecological (competitive) and evolutionary (adaptive) processes interact. My research uses laboratory experiments, computer simulations, and studies of natural populations to examine how large populations of single-celled algae respond to different rates of environmental change, either alone or in communities. Using a microbial model system allows me to do experiments using very large populations and span hundreds of generations, which allows the fixation of novel beneficial mutations by natural selection. One of these environmental changes is elevated CO2. Because laboratory systems are necessarily artificial, I will look for similar patterns of adaptation in algal communities from naturally occurring high CO2 springs. This work provides insight into one of the most fundamental processes in biology, that of adaptation. In addition, this work uses ideas and techniques from many disciplines, namely evolutionary biology, ecology, population genetics and molecular genetics. This sort of interdisciplinary, problem-based approach allows me to examine complex scenarios where the theory to do so may be lack