Effective and census size, connectivity and the temporal dimension of genetic diversity in aquatic organisms

水生生物遗传多样性的有效和普查规模、连通性和时间维度

• 批准号: RGPIN-2019-04679
• 负责人: Ruzzante, Daniel
• 金额: $ 3.42万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=689464
• 关键词: Effective; census; size; connectivity; temporal

Knowing how many individuals there are in a population is a fundamental first step in conservation and evolutionary biology. The concept of census population size (Nc) is relatively easy to understand as it generally refers to the total number of individuals in a population. This conceptual simplicity, however, belies the fact that estimating abundance with precision and without bias is in most cases extremely difficult. It is particularly a problem in the management of exploited marine populations, as well as in the conservation of small populations under risk of extinction. In marine fisheries, the estimation of abundance has traditionally relied on catch per unit effort (CPUE), a metric that is subject to bias and uncertainty and can often be unreliable and contentious. One of my goals is to estimate census population size, Nc, using genomics. ***Population size is important but by itself provides only a partial answer to questions in management and conservation. In evolutionary biology, what often matters most is not total abundance, but the effective size of the population (Ne). This is the size of an ideal population that exhibits the same genetic properties as the population under study. Both parameters, effective and census size and their relationship (Ne/Nc) are thus important as their relative magnitudes can be used to assess the relative roles of neutral vs. adaptive processes in moulding the genetic composition of the system under study. ***In this proposal I focus on the estimation of both, Nc and Ne. I plan to estimate Nc using genomics and the Close Kin Mark Recapture (CKMR) framework. This method uses the principle that an individual's genotype can be considered a “recapture” of the genotypes of each of its parents, and then analyses the number and pattern of parent-offspring pairs (POP) in a mark-recapture framework. Assuming the sampling of offspring and parents is independent of each other, the number POPs genetically identified in a large collection of both groups can be used to estimate abundance. I plan to do this with four independent systems differing in abundance and mating behavior and thus, in expected patterns of reproductive success. This includes systems where mating is nearly random [striped bass] to systems with moderately [e.g., brook trout, Atlantic salmon] and highly [e.g., grey seals] skewed reproductive success. My goal is to assess the consequences of uncertainties in the estimation of life history traits (age specific survival and fecundity rates) on precision and bias of the abundance estimates over a range of abundance estimates and reproductive skew. For all four systems, the genomic data will also be used to estimate effective population sizes and where feasible their temporal trajectory using a method that requires knowledge of recombination rates among markers. The research will assist in validating the CKMR framework to estimate abundance in managed and data limited populations.**

了解种群中有多少个体是保护和进化生物学的基本第一步。人口普查人口规模（Nc）的概念相对容易理解，因为它通常是指人口中的个人总数。然而，这种概念上的简单性掩盖了这样一个事实，即在大多数情况下，精确而无偏差地估计丰度是极其困难的。在管理被开发的海洋种群以及养护面临灭绝危险的小种群方面，这尤其是一个问题。在海洋渔业中，对丰度的估计传统上依赖于单位努力量渔获量，这一指标存在偏差和不确定性，往往不可靠，也有争议。我的目标之一是使用基因组学估计人口普查人口规模Nc。* 种群规模很重要，但其本身只能部分回答管理和保护方面的问题。在进化生物学中，最重要的往往不是总丰度，而是种群的有效规模（Ne）。这是一个理想种群的大小，它表现出与所研究的种群相同的遗传特性。这两个参数，有效和普查规模和它们的关系（Ne/Nc），因此是重要的，因为它们的相对大小可以用来评估相对作用的中性与适应过程中塑造的遗传组成的系统研究。* 在本建议中，我集中于Nc和Ne两者的估计。我计划使用基因组学和近亲标记重捕获（CKMR）框架来估计Nc。这种方法使用的原则是，一个人的基因型可以被认为是一个“夺回”的基因型的每一个父母，然后分析的数量和模式的父母-后代对（POP）的标记-夺回框架。假定对子代和亲代的取样是相互独立的，则可利用在大量子代和亲代样本中从基因上确定的持久性有机污染物数量来估计丰度。我计划用四个在丰度和交配行为上不同的独立系统来做这件事，因此，在预期的繁殖成功模式上。这包括交配几乎是随机的系统[条纹鲈鱼]到适度的系统[例如，布鲁克鳟鱼，大西洋鲑鱼]和高度[例如，灰色海豹]倾斜的繁殖成功。我的目标是评估的生活史特征（特定年龄的生存率和繁殖率）的精度和偏差的丰度估计在一定范围内的丰度估计和生殖偏斜的估计的不确定性的后果。对于所有四个系统，基因组数据也将用于估计有效的群体大小，并在可行的情况下，使用一种需要了解标记之间重组率的方法来估计其时间轨迹。该研究将有助于验证CKMR框架，以估计管理和数据有限的种群的丰度。