Estimating demographic contributions to effective population size in an age‐structured wild population experiencing environmental and demographic stochasticity

Abstract

A population's effective size (N ) is a key parameter that shapes rates of inbreeding and loss of genetic diversity, thereby influencing evolutionary processes and population viability. However, estimating N , and identifying key demographic mechanisms that underlie the N to census population size (N) ratio, remains challenging, especially for small populations with overlapping generations and substantial environmental and demographic stochasticity and hence dynamic age-structure. A sophisticated demographic method of estimating N /N, which uses Fisher's reproductive value to account for dynamic age-structure, has been formulated. However, this method requires detailed individual- and population-level data on sex- and age-specific reproduction and survival, and has rarely been implemented. Here, we use the reproductive value method and detailed demographic data to estimate N /N for a small and apparently isolated red-billed chough (Pyrrhocorax pyrrhocorax) population of high conservation concern. We additionally calculated two single-sample molecular genetic estimates of N to corroborate the demographic estimate and examine evidence for unobserved immigration and gene flow. The demographic estimate of N /N was 0.21, reflecting a high total demographic variance (σ2dg) of 0.71. Females and males made similar overall contributions to σ2dg. However, contributions varied among sex-age classes, with greater contributions from 3 year-old females than males, but greater contributions from ≥5 year-old males than females. The demographic estimate of N was ~30, suggesting that rates of increase of inbreeding and loss of genetic variation per generation will be relatively high. Molecular genetic estimates of N computed from linkage disequilibrium and approximate Bayesian computation were approximately 50 and 30, respectively, providing no evidence of substantial unobserved immigration which could bias demographic estimates of N . Our analyses identify key sex-age classes contributing to demographic variance and thus decreasing N /N in a small age-structured population inhabiting a variable environment. They thereby demonstrate how assessments of N can incorporate stochastic sex- and age-specific demography and elucidate key demographic processes affecting a population's evolutionary trajectory and viability. Furthermore, our analyses show that N for the focal chough population is critically small, implying that management to re-establish genetic connectivity may be required to ensure population viability.

Phenotypic evolution in stochastic environments: The contribution of frequency‐ and density‐dependent selection

“…2016; Trask et al. 2017). This is due to the fact that demographic variance and genetic drift arise from stochastic contributions that are independent among individuals.…”

Genetic structure and population dynamics of the silver pheasant (Lophuranycthemera) in southern China

“…The Pleistocene seriously affected the structure of most birds (Hewitt CD, 2000;Greer, 2013). Nevertheless, quite a few studies have discovered that the populations during the interglacial period were stable (Marín et al, 2013;Zhu et al, 2018), while other studies have shown that gene flow and genetic diversity are vital for population existence and evolution (Clement and Crandall, 2000;Trask et al, 2017). the pattern of sex-biased dispersal of the silver pheasant and its influencing factors and to determine whether and how the interglacial period affected the population structure, gene flow, genetic diversity, and dynamics of the silver pheasant in southern China.…”

Estimating effective population size using RADseq: Effects of SNP selection and sample size

“…Only one demographic method allows demographic stochasticity and heterogeneity at the expense of challenging data demands such as individual-level information (Engen, Lande, Saether, & Gienapp, 2010). This might explain why the method has not been much used so far (but see Trask, Bignal, McCracken, Piertney, & Reid, 2017).…”