Adaptation in complex scenarios

生物适应环境的观察是显而易见的，但我们只能解释这是如何在极端情况下发生的，如抗生素和杀虫剂抗性的进化，重金属耐受性和饥饿。典型的研究旨在了解生物如何适应环境变化后进行的人口在环境中，它是适应不良。这种紧张的环境通常是极端的，以激发可观察到的反应，并且通常是静态的。例如，一个植物种群可以从一个营养丰富的环境转移到一个特定的营养几乎不存在的环境。然后，种群通过连续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种群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，以及如果同一种群多次适应相同的压力环境，我们预期会有多少不同的结果。然而，在实验室和自然灾害之外，很少有环境变化涉及从一个相对稳定的环境突然过渡到第二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改变，因此大多数种群所处的环境与最近的祖先只有轻微的不同，即使它可能与更遥远的祖先有很大的不同。全球变化就是一个例子，植物种群目前暴露在二氧化碳水平是10，000年前最后一次冰河时期的两倍多，但只比十年前高出几个百分点。因此，在任何给定的时间，人口正在适应环境的微妙变化，但环境并没有保持不变，而他们这样做，这表明适应的研究应该包括环境变化的幅度和速度。第二个考虑因素是，种群不会孤立地适应，而是在适应过程中必须与其他种群竞争。如果考虑两个种群在一个不断变化的环境中，有可能一个种群排斥另一个种群，但也有可能种群在这一演替过程中适应，这样群落组成（存在哪些物种）以及给定物种的遗传组成都会随着时间的推移而发生变化。例如，如果我们想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相同的速度吸收碳。因此，了解生态（竞争）和进化（适应）过程如何以及是否相互作用是很重要的。我的研究使用实验室实验，计算机模拟和自然种群的研究来研究单细胞藻类的大种群如何单独或在社区中对不同速率的环境变化做出反应。使用微生物模型系统使我能够使用非常大的种群进行实验，并跨越数百代，这使得自然选择能够固定新的有益突变。这些环境变化之一是二氧化碳浓度升高。由于实验室系统必然是人工的，我将在自然发生的高CO2泉水中寻找藻类群落的类似适应模式。这项工作提供了深入了解生物学中最基本的过程之一，即适应。此外，这项工作使用了许多学科的思想和技术，即进化生物学，生态学，群体遗传学和分子遗传学。这种跨学科的、基于问题的方法使我能够研究可能缺乏理论的复杂场景

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