A Multi-faceted Exploration of Late Paleozoic Communities

摘要为了理解群落多样性（一个生态系统中的物种数量）如何受到包括人类活动在内的干扰的负面影响，我们需要清楚地了解在正常条件下控制生物多样性的因素。四个因素？气候、栖息地、生产力和生物间的相互作用？被认为对社区多样性有影响。虽然存在关于多样性与任何一个因素之间关系的研究，但还没有研究对同一社区的所有四个因素进行调查。这项研究的目的是在德克萨斯州保存完好的宾夕法尼亚（3亿年前）化石海洋群落中检查多样性和四个因素之间的关系，这些群落是最古老的，包括古生代和现代动物群的多样化和丰富的元素。海洋无脊椎动物化石将从8-10个不同的群落中收集、鉴定和计数。这些数据将使用排序进行分析，排序是一种将多维数据（例如由多个社区产生的数据）简化为图形图的技术，可以识别社区之间的相似性。此外，利用地球化学、沉积学和捕食痕迹分析，可以确定每个群落的四个因子的值。在确定了哪些社区相似之后，指数指数将在统计上确定哪些因素影响社区之间的相似程度，以及社区之间的相互作用。整个项目与学生培训、项目和课程紧密相连。几名学生将参与项目从头到尾，并将有一个优秀的实践？有机会作为多学科团队的一员进行真正的研究。虽然单一研究的结果并不能解决多重相互作用的因素如何影响多样性的问题，但希望本研究可以作为群落分析的模型，从而引导未来许多跨越时空的研究。

A Multi-faceted Exploration of Late Paleozoic CommunitiesLindsey Leighton, Stephen Schellenberg, Jerad Morrow, and Christie Schneider San Diego State University: EAR-0746072AbstractTo understand how community diversity (the number of species in an ecosystem) can be negatively affected by disturbances, including those induced by humans, we need a clear understanding of the factors controlling biodiversity under normal conditions. Four factors ? climate, habitat, productivity, and interactions among organisms ? have been recognized as influences on community diversity. Although studies of the relationship between diversity and any one factor exist, there have been no studies examining all four factors on the same communities. The goal of this study is to examine the relationship between diversity and the four factors in a set of well-preserved Pennsylvanian (300 million years ago) fossil marine communities from Texas, which are among the oldest that include diverse and abundant elements of both the Paleozoic and Modern Faunas.Fossil marine invertebrates will be collected, identified, and counted from 8-10 separate communities. These data will be analyzed using ordination, a technique that reduces multi-dimensional data (such as those produced by multiple communities) to a graphical plot that permits recognition of similarity among communities. In addition, using geochemical, sedimentological, and predation-trace analyses, it is possible to determine values for the four factors for each community. Having determined which communities are similar, PIs will determine statistically which of the factors influence the degree of similarity among communities, and the interactions among the communities.The entire project is closely linked with student training, projects and classes. Several students will be involved in the project from start to finish and will have an excellent ?hands-on? opportunity to do real research as part of a multi-disciplinary team.Although the results from a single study will not solve the question of how multiple, interacting, factors influence diversity, it is hoped that this study will serve as a model for community analyses, and thus lead to many future studies through time and space.