Multi-scale structure of ecological communities

变异划分与多尺度PCNM分析相结合，使研究人员能够区分环境控制（基于生态位）和群落动态（中性过程）互补过程的结果。我的长期研究目标是检验关于生态系统中这些过程的假设。这是非常重要的，因为beta多样性的数量变化或其空间组织的变化表明生态系统的自然或人为变化。在我的职业生涯中，我学会了将群落生态学与统计学相结合，创造了新的数值方法，这些方法被证明对群落生态学的发展至关重要。我将在下一个5年周期中探索的新途径在提案中有所描述。这项工作只能由具有统计学倾向的科学家组成的团队来完成，他们了解主要的生态问题，并能够与统计学和计算机科学的研究人员建立联系。基础生态学：我们将分析生态系统的相对重要性的大尺度物理过程相对于当地的环境条件。在更精细的尺度上，我们将评估中性与基于生态位的过程的相对重要性。PCNM分析将应用于多元生态时间序列。它还将扩展到测试历史事件在塑造当今社区中的重要性，为正在进行的人为变化对社区的影响提供线索。第四角分析将被一般化，使其结果具有更丰富的生态信息。第四角分析将被纳入一种新的变异划分形式，用于研究物种特征与环境特征之间的部分关系，同时控制已被理解的环境变量的影响。方法学的发展：我们将发展新的统计模型选择在多元回归树（MRT）的研究。我们还将开发一种新的测试，用于多物种调查中的时空相互作用，而不需要复制。我们将把用于海底测绘的单波束声纳方法和SonarX r语言库扩展到多波束声纳，从而提供更多信息丰富的声纳返回。

Variation partitioning, combined with multi-scale PCNM analysis, allows researchers to differentiate the resuls of the complementary processes of environmental control (niche-based) and community dynamics (neutral processes). My long-term research objective is to test hypotheses about these processes in ecosystems. This is of great importance because quantitative changes in beta diversity, or changes in its spatial organization, indicate natural or anthropogenic changes in ecosystems. During my career, I learned to combine community ecology and statistics, creating new numerical methods that proved to be of prime importance for the progress of community ecology. The new avenues that I will explore during the next 5-year cycle are described in the Proposal. That work can only be done by teams of statistically-inclined scientists who understand the primary ecological questions and are able to relate to researchers in statistics and computer sciences.Fundamental ecology: we will analyze ecosystems for the relative importance of broad-scale physical processes versus local environmental conditions. At finer scales, we will assess the relative importance of neutral versus niche-based processes. PCNM analysis will be applied to multivariate ecological time series. It will also be extended to test the importance of historical events in shaping present-day communities, providing clues about the effect of ongoing anthropogenic changes on communities. Fourth-corner analysis will be generalized to make its results richer in ecological information. Fourth-corner analysis will be incorporated into a new form of variation partitioning for the study of partial relationships between species traits and environmental characteristics while controlling for the effect of well-understood environmental variables. Methodological developments: we will develop new statistics for model selection in the study of multivariate regression trees (MRT). We will also develop a new test for the space-time interaction in multi-species surveys without replication.  We will extend our single-beam sonar methodology for seafloor mapping and our SonarX R-language library to multi-beam sonars, which provide more information-rich sonar returns.