Grant: Discovery Grants Program - Individual

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.