The crucial role of genome-wide genetic variation in conservation

Abstract

The unprecedented rate of extinction calls for efficient use of genetics to help conserve biodiversity. Several recent genomic and simulation-based studies have argued that the field of conservation biology has placed too much focus on conserving genome-wide genetic variation, and that the field should instead focus on managing the subset of functional genetic variation that is thought to affect fitness. Here, we critically evaluate the feasibility and likely benefits of this approach in conservation. We find that population genetics theory and empirical results show that conserving genome-wide genetic variation is generally the best approach to prevent inbreeding depression and loss of adaptive potential from driving populations toward extinction. Focusing conservation efforts on presumably functional genetic variation will only be feasible occasionally, often misleading, and counterproductive when prioritized over genome-wide genetic variation. Given the increasing rate of habitat loss and other environmental changes, failure to recognize the detrimental effects of lost genome-wide genetic variation on long-term population viability will only worsen the biodiversity crisis.

Keywords: extinction; genomics; population dynamics.

Fig. 1.

Relationship of nucleotide diversity ($\pi$) with the inbreeding load (lethal equivalents) (A), drift load (B), and additive genetic variance in a quantitative trait (V_a) (C). The data are from the 1,000th generation of 10 simulated populations with nine different constant effective population sizes (N_e).

Fig. 2.

Genetic effects of bottlenecks with and without immigration. Nucleotide diversity ($\pi$) (A), number of lethal equivalents (B), drift load (C), and the additive genetic variance in a quantitative trait (V_a) (D) are shown for 100 generations after a simulated bottleneck in isolated populations (orange) and with five immigrants every two generations up to generation 50 (blue). Population size was held constant at N_e = 1,000 for 1,000 generations before the bottleneck and then at N_e = 25 starting at generation 0. The thin lines show the results from 25 replicates. The thick lines represent the mean across 25 replicates. Immigrants during the first 50 generations are from a population with N_e = 500 that split from the receiving population the generation of the bottleneck. Details of the simulation model and parameters are provided in SI Appendix.

Fig. 3.

Population viability during bottlenecks from carrying capacity K = 1,000 (Left) and K = 500 (Right) to K = 100. The bottlenecks were 2 (A), 10 (B), and 50 (C) generations in length. The black line shows the proportion of extant populations. Gray lines show population size for each of 50 replicate simulations in each scenario.