Structuring of ecological communities

生态社区构建

• 批准号: RGPIN-2014-05011
• 负责人: Jackson, Donald
• 金额: $ 3.64万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=631883
• 关键词: Structuring; ecological; communities

Ecological communities are presumed to have non-random relationships in characteristics such as species composition. This premise is fundamental to most of our studies involving both basic (e.g., interspecific interactions such as competition) and applied science (restoration ecology), yet it is rarely tested formally. Early work (1970s & 1980s) provided significant new conceptual and methodological approaches to enable us to test whether or not ecological communities differ from random assemblages of species, specifically null models. During this earlier work most studies focused on the role of competition in leading to negative patterns of species co-occurrence when using these null models, yet some studies identified various other factors that may contribute to the same observed patterns (e.g. differential habitat preferences amongst species). Although some progress has been made in advancing some of these methods further, considerable questions remain unanswered or insufficiently addressed. Furthermore, advances in ecology have been hindered by the unique histories of species and sites considered, leading to variable outcomes. In order to broadly advance the generality of our understanding, it is important to consider the average and variability of the outcomes that we see across different groups of species (e.g. fish versus plants) and ecosystems (freshwater versus terrestrial). The proposed work will address several of these issues. Using extensive datasets from the literature plus a combination of field and experimental work, we will quantify and test the relative importance of habitat differences, experimental design and study scale in contributing to finding non-random community structure versus potential interspecific interactions. We will examine the relative roles of environmental disturbance (both natural and anthropogenic origins) in disrupting perceived community structure. Species dispersal has the potential to homogenize species composition across sites, leading to most species occurring everywhere and therefore may play a significant role in differences (or lack of differences) noted in null model studies. Therefore, considering extensive sets of data representing many different types of taxa from various ecosystems will allow us to partition the relative roles these various factors having in contributing to finding non-random community composition (or results not differing from random), determine generalization that can be drawn from these contrasts, and facilitate the development of relevant theory. Such an approach will characterize the generalities of these answers rather than being unduly influenced by the characteristics of individual datasets. We will also advance the types of null models available to the research community through the development of new approaches that explicitly incorporate differences among species in habitat selection – an area identified as an important one in this research field.From previous work on a large spatial analysis of crayfish communities, we identified dramatic declines in their abundance and species richness in many Ontario lakes, likely reflecting a suite of interacting environmental stressors. We will use a lengthy time series of population abundances for these species from a set of lakes and associated environmental data to better determine what factors are contributing to the decline and loss of these important components of freshwater food webs.

生态群落被认为在物种组成等特征上具有非随机关系。这个前提对于我们大多数涉及基础科学（例如竞争等种间相互作用）和应用科学（恢复生态学）的研究来说是基础，但它很少经过正式测试。早期的工作（1970 年代和 1980 年代）提供了重要的新概念和方法，使我们能够测试生态群落是否不同于物种的随机组合，特别是零模型。在这项早期工作中，大多数研究都集中在使用这些零模型时竞争在导致物种共现的负面模式中的作用，但一些研究发现了可能导致相同观察到的模式的各种其他因素（例如物种之间不同的栖息地偏好）。尽管在进一步推进其中一些方法方面已经取得了一些进展，但仍有相当多的问题没有得到解答或没有得到充分解决。此外，生态学的进步受到所考虑的物种和地点的独特历史的阻碍，导致不同的结果。为了广泛地提高我们理解的普遍性，重要的是要考虑我们在不同物种群体（例如鱼类与植物）和生态系统（淡水与陆地）中看到的结果的平均值和变异性。拟议的工作将解决其中几个问题。利用文献中的大量数据集以及实地和实验工作的结合，我们将量化和测试栖息地差异、实验设计和研究规模在寻找非随机群落结构与潜在种间相互作用方面的相对重要性。我们将研究环境干扰（自然和人为起源）在破坏感知的群落结构中的相对作用。物种扩散有可能使不同地点的物种组成均质化，导致大多数物种出现在任何地方，因此可能在零模型研究中注意到的差异（或缺乏差异）中发挥重要作用。因此，考虑代表来自不同生态系统的许多不同类型的类群的广泛数据集将使我们能够划分这些不同因素在寻找非随机群落组成（或与随机没有区别的结果）方面的相对作用，确定可以从这些对比中得出的概括，并促进相关理论的发展。这种方法将描述这些答案的普遍性，而不是受到单个数据集特征的过度影响。我们还将通过开发新方法来推进研究界可用的零模型类型，这些方法明确地将物种之间的差异纳入栖息地选择——这一领域被认为是本研究领域的一个重要领域。根据之前对小龙虾群落的大型空间分析的工作，我们发现安大略省许多湖泊的小龙虾丰度和物种丰富度急剧下降，这可能反映了一系列相互作用的环境压力因素。我们将使用一组湖泊中这些物种的种群丰度的长期时间序列和相关环境数据，以更好地确定哪些因素导致淡水食物网这些重要组成部分的减少和丧失。