Community-Level Selection: Laboratory Experiments and Computer Simulations

生物群落经常被描述为有功能组织的单位，类似于单个生物体的和谐和协调。然而，在生物等级的任何层次上，适应的进化都需要在该层次上进行相应的自然选择过程。本拨款提案通过实验室实验和计算机模拟探索社区层面的选择过程。在实验室中，将建立一个孤立的土壤群落种群，并根据表型特征（植物生长）进行评分。得分最高和最低的群落将被用作“父母”来殖民一组新的“后代”群落。该实验设计与标准的人工选择实验相同，只是选择的单位是社区而不是个人。如果试验成功，它将产生在功能上能够促进（或减少）植物生长的土壤群落。计算机模拟将允许探索同样的过程，其中物种之间的相互作用可以详细指定。几个世纪以来，人们一直利用个体层面的人工选择来培育对人类有用的动植物品种。同样的过程可能被用于进化多物种群落，这些群落作为一个协调的团队相互作用，以解决重要的实际问题，例如促进植物生长，从群落中排除目标物种，或降解有毒化合物。人为选择的社区可能比人为选择的个人提供更好的解决方案，同样的原因是协调的团队可以胜过单个人。“团队合作”的好处是显而易见的；问题是如何发展球队。这项提议的研究可能提供一种迄今为止被忽视的简单方法。

Wilson, D. S. DEB-9707650 Biological communities have often been described as functionally organized units, similar to single organisms in the harmony and coordination of their parts. The evolution of adaptations at any level of the biological hierarchy, however, requires a corresponding process of natural selection at that level. This grant proposal explores the process of community-level selection with laboratory experiments and computer simulations. In the laboratory, a population of isolated soil communities will be established and scored with respect to a phenotypic character (plant growth). The highest and lowest scoring communities will be used as the "parents" to colonize a new set of "offspring" communities. This experimental design is identical to standard artificial selection experiments except that the selected units are communities rather than individuals. If the experiment is successful, it will produce soil communities that are functionally designed to increase (or decrease) plant growth. The computer simulations will allow the same process to be explored in which the interactions among the species can be specified in detail. Artificial selection at the individual level has been employed for centuries to develop strains of plants and animals that are useful to man. The same procedure can potentially be used to evolve multi-species communities that interact as a coordinated team to solve important practical problems, such as promoting plant growth, excluding a target species from a community, or degrading a toxic compound. Artificially selected communities may provide better solutions than artificially selected individuals for the same reason that coordinated teams of people can outperform single individuals. The advantages of "teamwork" are obvious; the problem is how to develop the teams. The proposed research may provide a simple method that so far has been overlooked.