A biological species is defined as a group of interbreeding natural populations that are reproductively isolated from other such groups (Coyne & Orr, 2004;Dobzhansky, 1937;Mayr, 1942). The notion of reproductive isolation (RI) is thus central to understanding species and speciation. But what, exactly, do we mean by 'reproductive isolation'? Despite being deeply embedded in the language of speciation, the term is used in seemingly different ways, usually without a precise definition; attempts to quantify it have used very different approaches that measure different things. Connecting different perspectives and approaching a general definition is important for our conceptual understanding of speciation and for efforts to quantify RI empirically. The main aim of this article is to contribute to progress in this respect.In Box 1, we briefly summarize the history of the term and present the results of a recent survey on RI among evolutionary biologists working on speciation. Both the survey and the historical
Many studies have quantified the distribution of heterozygosity and relatedness in natural populations, but few have examined the demographic processes driving these patterns. In this study, we take a novel approach by studying how population structure affects both pairwise identity and the distribution of heterozygosity in a natural population of the self-incompatible plant Antirrhinum majus. Excess variance in heterozygosity between individuals is due to identity disequilibrium (ID), which reflects the variance in inbreeding between individuals; it is measured by the statistic g2. We calculated g2 together with FST and pairwise relatedness (Fij) using 91 SNPs in 22,353 individuals collected over 11 years. We find that pairwise Fij declines rapidly over short spatial scales, and the excess variance in heterozygosity between individuals reflects significant variation in inbreeding. Additionally, we detect an excess of individuals with around half the average heterozygosity, indicating either selfing or matings between close relatives. We use two types of simulation to ask whether variation in heterozygosity is consistent with fine-scale spatial population structure. First, by simulating offspring using parents drawn from a range of spatial scales, we show that the known pollen dispersal kernel explains g2. Second, we simulate a 1000-generation pedigree using the known dispersal and spatial distribution and find that the resulting g2 is consistent with that observed from the field data. In contrast, a simulated population with uniform density underestimates g2, indicating that heterogeneous density promotes identity disequilibrium. Our study shows that heterogeneous density and leptokurtic dispersal can together explain the distribution of heterozygosity.
Inbreeding depression can be estimated by correlating heterozygosity with fitness components, but such heterozygosity-fitness correlations are typically weak. For over ten years, we studied a population of the self-incompatible plant, Antirrhinummajus, measuring heterozygosity and fitness proxies from 22,353 plants. Using a panel of 91 SNPs, we find that relatedness declines rapidly over short spatial scales. Individual heterozygosity varies more between individuals than expected, reflecting identity disequilibrium (g2) due to variation in inbreeding − a prerequisite for detecting inbreeding depression. We use two types of simulations to ask whether the heterozygosity distribution is consistent with spatially structured mating. First, we simulate offspring from matings with fathers at different distances and find that the distribution of heterozygosity in the field data is consistent with the measured pollen dispersal kernel. Second, we simulate a 1000-generation pedigree using the known spatial distribution, and find that identity disequilibrium, though highly variable between simulations, is consistent with that observed. Finally, we estimate inbreeding depression through the relationships between heterozygosity and six fitness proxies. Only the number of flowering stems is predicted by heterozygosity. Our approach provides a novel example of how long-term studies can elucidate population structure and fitness variation in the wild.
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