Decomposing demographic contributions to the effective population size with moose as a case study

Harvest and decimation affect genetic drift and the effective population size in wild reindeer

Harvesting and culling are methods used to monitor and manage wildlife diseases. An important consequence of these practices is a change in the genetic dynamics of affected populations that may threaten their long-term viability. The effective population size (N e) is a fundamental parameter for describing such changes as it determines the amount of genetic drift in a population. Here, we estimate N e of a harvested wild reindeer population in Norway. Then we use simulations to investigate the genetic consequences of management efforts for handling a recent spread of chronic wasting disease, including increased adult male harvest and population decimation. The N e/N ratio in this population was found to be 0.124 at the end of the study period, compared to 0.239 in the preceding 14 years period. The difference was caused by increased harvest rates with a high proportion of adult males (older than 2.5 years) being shot (15.2% in 2005-2018 and 44.8% in 2021). Increased harvest rates decreased N e in the simulations, but less sex biased harvest strategies had a lower negative impact. For harvest strategies that yield stable population dynamics, shifting the harvest from calves to adult males and females increased N e. Population decimation always resulted in decreased genetic variation in the population, with higher loss of heterozygosity and rare alleles with more severe decimation or longer periods of low population size. A very high proportion of males in the harvest had the most severe consequences for the loss of genetic variation. This study clearly shows how the effects of harvest strategies and changes in population size interact to determine the genetic drift of a managed population. The long-term genetic viability of wildlife populations subject to a disease will also depend on population impacts of the disease and how these interact with management actions.

A chromosome-level genome of electric catfish (Malapterurus electricus) provided new insights into order Siluriformes evolution

The electric catfish (Malapterurus electricus), belonging to the family Malapteruridae, order Siluriformes (Actinopterygii: Ostariophysi), is one of the six branches that has independently evolved electrical organs. We assembled a 796.75 Mb M. electricus genome and anchored 88.72% sequences into 28 chromosomes. Gene family analysis revealed 295 expanded gene families that were enriched on functions related to glutamate receptors. Convergent evolutionary analyses of electric organs among different lineage of electric fishes further revealed that the coding gene of rho guanine nucleotide exchange factor 4-like (arhgef4), which is associated with G-protein coupled receptor (GPCR) signaling pathway, underwent adaptive parallel evolution. Gene identification suggests visual degradation in catfishes, and an important role for taste in environmental adaptation. Our findings fill in the genomic data for a branch of electric fish and provide a relevant genetic basis for the adaptive evolution of Siluriformes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-023-00197-8.

Partitioning variance in reproductive success, within years and across lifetimes

Variance in reproductive success (s k 2 , with k = number of offspring) plays a large role in determining the rate of genetic drift and the scope within which selection acts. Various frameworks have been proposed to parse factors that contribute to s k 2 , but none has focused on age-specific values of ϕ = s k 2 / k ¯ , which indicate the degree to which reproductive skew is overdispersed (compared to the random Poisson expectation) among individuals of the same age and sex. Instead, within-age effects are generally lumped with residual variance and treated as "noise." Here, an ANOVA sums-of-squares framework is used to partition variance in annual and lifetime reproductive success into between-group and within-group components. For annual reproduction, the between-age effect depends on age-specific fecundity (b x), but relatively few empirical data are available on the within-age effect, which depends on ϕ x. By defining groups by age-at-death rather than age, the same ANOVA framework can be used to partition variance in lifetime reproductive success (LRS) into between-group and within-group components. Analytical methods are used to develop null-model expectations for random contributions to within-group and between-group components. For analysis of LRS, random variation in longevity appears as part of the between-group variance, and effects (if any) of skip breeding and persistent individual differences contribute to the within-group variance. Simulations are used to show that the methods for variance partitioning are asymptotically unbiased. Practical application is illustrated with empirical data for annual reproduction in American black bears and lifetime reproduction in Dutch great tits. Results show that overdispersed within-age variance (1) dominates annual s k 2 in both male and female black bears, (2) is the primary factor that reduces annual effective size to a fraction of the number of adults, and (3) represents most of the opportunity for selection. In contrast, about a quarter of the variance in LRS in great tits can be attributed to random variation in longevity, and most of the rest is due to modest differences in fecundity with age estimated for a single cohort of females. R code is provided that reads generic input files for annual and lifetime reproductive success and allows users to conduct variance partitioning with their own data.

Robustness of Hill's overlapping-generation method for calculating Ne to extreme patterns of reproductive success

For species with overlapping generations, the most widely used method to calculate effective population size (Ne) is Hill's, the key parameter for which is lifetime variance in offspring number ([Formula: see text]). Hill's model assumes a stable age structure and constant abundance, and sensitivity to those assumptions has been evaluated previously. Here I evaluate the robustness of Hill's model to extreme patterns of reproductive success, whose effects have not been previously examined: (1) very strong reproductive skew; (2) strong temporal autocorrelations in individual reproductive success; and (3) strong covariance of individual reproduction and survival. Genetic drift (loss of heterozygosity and increase in allele frequency variance) was simulated in age-structured populations using methods that generated no autocorrelations or covariances (Model NoCor); or created strong positive (Model Positive) or strong negative (Model Negative) temporal autocorrelations in reproduction and covariances between reproduction and survival. Compared to Model NoCor, the other models led to greatly elevated or reduced [Formula: see text], and hence greatly reduced or elevated Ne, respectively. A new index is introduced (ρα,α+), which is the correlation between (1) the number of offspring produced by each individual at the age at maturity (α), and (2) the total number of offspring produced during the rest of their lifetimes. Mean ρα,α+ was ≈0 under Model NoCor, strongly positive under Model Positive, and strongly negative under Model Negative. Even under the most extreme reproductive scenarios in Models Positive and Negative, when [Formula: see text] was calculated from the realized population pedigree and used to calculate Ne in Hill's model, the result accurately predicted the rate of genetic drift in simulated populations. These results held for scenarios where age-specific reproductive skew was random (variance ≈ mean) and highly overdispersed (variance up to 20 times the mean). Collectively, these results are good news for researchers as they demonstrate the robustness of Hill's model even in extreme reproductive scenarios.