Adaptation in complex scenarios

生物适应环境的观察是显而易见的，但我们只能解释这种情况是如何在极端情况下发生的，例如抗生素和农药抗药性的进化、重金属耐受性和饥饿。旨在了解生物体在环境变化后如何适应的典型研究，是通过将种群置于适应能力较差的环境中进行的。这种有压力的环境通常是极端的，以便引起可观察到的反应，而且通常也是静态的。例如，植物种群可能从营养丰富的环境转移到几乎缺乏特定营养的环境中。然后，种群通过顺序固定新的突变来适应，这些突变增加了种群在新环境中的生长和繁殖。使用这个框架的理论和实验使我们能够描述一个群体随着时间的推移适应的速度有多快，在一轮典型的适应中涉及多少突变，以及如果相同的群体多次适应相同的压力环境，我们预计会有多少不同的结果。然而，实验室和自然灾害之外的环境变化很少涉及从一个相对稳定的环境突然转变为另一个截然不同的稳定环境。相反，环境往往会随着时间的推移而逐渐变化，因此大多数种群生活在与最近祖先略有不同的环境中，即使它可能与更遥远的祖先有很大不同。全球变化就是一个例子，那里的植物种群目前面临的二氧化碳水平是1万年前最后一次冰川时期的两倍多，但只比10年前高出几个百分点。因此，在任何给定的时间，人们都在适应环境的微妙变化，但环境并不是在他们这样做的时候保持不变。这表明，对适应的研究应该包括环境变化的幅度和速度。第二个考虑是，种群不会孤立地适应，而是必须在这样做的同时与其他种群竞争。如果考虑到处于不断变化的环境中的两个种群，有可能一个种群排斥另一个种群，但也有可能种群在这种演替过程中适应，从而使群落组成(存在哪些物种)以及给定物种的基因组成随着时间的推移而变化。例如，如果我们想要猜测未来海洋将吸收多少碳，我们需要知道哪种浮游植物将占主导地位，以及占主导地位的物种未来的种群是否会以与同一物种当代种群大致相同的速度吸收碳。因此，重要的是要了解生态(竞争)和进化(适应)过程如何以及是否相互作用。我的研究使用实验室实验、计算机模拟和对自然种群的研究，来检验大量的单细胞藻类种群如何应对不同速度的环境变化，无论是单独的还是在社区中。使用微生物模型系统允许我使用非常大的种群和跨越数百代人进行实验，这允许通过自然选择固定新的有益突变。这些环境变化之一就是二氧化碳浓度升高。由于实验室系统必然是人工的，我将从自然产生的高二氧化碳泉水中寻找藻类群落中类似的适应模式。这项工作提供了对生物学中最基本的过程之一--适应过程的洞察。此外，这项工作还使用了许多学科的思想和技术，即进化生物学、生态学、种群遗传学和分子遗传学。这种跨学科、基于问题的方法使我能够研究复杂的场景，而这样做的理论可能是缺乏的

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