What are the four evolutionary forces that would disrupt population hardy-weinberg equilibrium

III.F. Gene Flow

Gene flow is a fundamental agent of evolution based on the dispersal of genes between populations of a species. It involves the active or passive movement of individual plants, animals, gametes, or seeds. Gene flow involves not just dispersal but also the successful establishment of the immigrant genotypes in the new population. Gene flow is often confusingly referred to as migration, but the latter term is best reserved to describe dispersal behaviors involving a seasonal or longer term round-trip. Gene flow tends to homogenize linked populations and lack of gene flow permits interpopulation differentiation. It is of interest to geneticists and managers in that to conserve a population one needs to establish the historical patterns and rates of gene flow. This is typically estimated from allele frequency data and reported in terms of the number of “migrants” per generation. In theory, one migrant per generation between two populations will ensure that they remain genetically homogeneous. Inbreeding depression can be ameliorated by the artificial translocation of one reproducing migrant per generation between populations.

Gene flow is often gender biased and limited to certain phases of the life cycle. It may be accelerated under certain climatic conditions that occur at frequencies of many years or at irregular intervals many years apart. Interspecific gene flow results in introgressive hybridization (discussed previously). The translocation of individual organisms results in gene flow if they reproduce at the release site. In the future, genetically depauperate populations will be enhanced by translocation of individuals from more secure areas. Unfortunately, such genetic enhancement carries risks associated with the introduction of pathogens that could harm the target population or completely unrelated species. Furthermore, the introduction of individuals from genetically well-differentiated source populations may result in outbreeding depression in the threatened population of conservation concern (discussed previously). Gene flow can thus erode the genetic basis of adaptation to local conditions.

If previously continuous populations become fragmented, historical patterns of dispersal and gene flow may be disrupted with potentially serious consequences for population viability. For example, if young female chimpanzees can no longer emigrate from their natal social group because of habitat destruction in the surrounding countryside, their isolated natal population will experience increased inbreeding.

Gene Flow Can Promote Local Adaptation

Gene flow need not be an antagonist to adaptation. Most importantly, it spreads universally favored mutations across a species range (for a review see Morjan and Rieseberg, 2004). It can also aid local adaptation by supplying new alleles to populations with limited genetic variance. This can facilitate adaptation at the edge of a species range (see Geber, 2011 and associated papers) or after a drastic reduction in population size. The coevolution between parasites and hosts represents another evolutionary process in constant need of new genetic variation.

The theoretical prediction that gene flow can facilitate local adaptation in such systems (Gandon, 2002) has been experimentally tested with bacterial hosts and bacteriophage “parasitoids.” Experimental evolution in microbes allows for the study of large, replicated populations over many generations and for the direct comparisons of genotypes across time (i.e., from frozen stocks). In the present context, it also enables the experimenter to control a suite of key parameters that would be difficult to measure let alone manipulate in nature. Compared to a set-up without gene flow, regular genetic exchange between replicate microcosms of bacteria and phage increased both the overall occurrence and the spatio-temporal variability of local adaptation in the phage (Forde et al., 2004). The latter observation might explain why snapshots of unmanipulated host–parasite systems in nature give overall inconsistent results with regard to local adaptation. In another study (Morgan et al., 2005), host and parasitoid gene flow rates were manipulated independently (either host or parasitoid or no gene flow). As before, parasitoid gene flow led to increased local adaptation in parasitoids. In addition, there was evidence at the end of the experiment that parasitoid gene flow had increased parasitoid adaptation to nonlocal hosts, which could reflect the spread of universally favored alleles. Interestingly, host gene flow had no effect on the level of local adaptation in the host.

IV.A. Direct and Indirect Measures of Gene Flow

Gene flow clearly plays a central role in the dynamics of ecological variants in heterogeneous environments. Its role has been the matter of considerable controversy in the past. Does wide ranging gene flow impose limits on intraspecific differentiation or is gene flow on the contrary so limited that populations of a species behave as nearly independent evolutionary units? Based on the available evidence, the latter view is closer to the truth. Nevertheless, it is difficult to predict the potential for local adaptation and differentiation for any given species. Reliable estimates of gene flow are thus highly desirable. They might be obtained by monitoring the movement of marked individuals. However, such direct estimates typically give an underestimate of gene flow. Long distance dispersers will often be missed, yet they play an important role in the spread of genes. Mark-recapture studies provide a snapshot of dispersal whereas a longer-term average is required for evolutionary inferences. On the other hand, not all observed movement necessarily leads to gene flow. For example, immigrants might be less successful than residents in the competition for territories. Much effort has therefore been devoted to the developments of indirect measures of gene flow that can provide a suitably averaged estimate. Most of these methods are based on the spatial distribution of neutral genetic markers.

Consider again the island model: a large number of demes, each of constant size N, are connected by gene flow at a rate m via a common pool of migrants. The overall frequency of a certain selectively neutral allele in the population as a whole, and consequently in the migrant pool, is p¯. Genetic drift within demes produces variance in p across demes as a function of local population size. Without gene flow, this process would inevitably lead to the random fixation of one or the other allele in each deme. With gene flow there is an equilibrium amount of differentiation: the divergence among demes due to drift is balanced by the homogenizing effect of gene flow such that the variance in p, Vp, is constant. For a locus with two alleles, Sewall Wright defined the standardized variance in allele frequency as Fst = Vp/p¯(1−p¯) and showed for the island model that

Fst≈11+4Nm

The degree of differentiation among demes in the island model thus depends on the number of migrants per deme per generation. Consider a given combination of N and m. An increase in N reduces random drift such that a smaller migration rate suffices to keep Vp constant. The two forces exactly balance each other. The analysis of the island model shows that only a small amount of gene flow is enough to maintain neutral genetic variability within demes. The threshold number of migrants below which there is a tendency for demes to fix by chance one or the other allele is Nm = 0.5, which is equivalent to one migrant every other generation or an Fst-value of 0.33.

Gene Flow

Gene flow describes the spatial movement of genes, typically through seed and pollen dispersal, either within a population or between separated stands. (An alternative term, ‘migration,’ is reserved here for shifts in time of the geographic range of species or populations.) Wind-pollinated species, producing abundant pollen, such as most temperate forest trees, show major gene flow. In favorable weather, pollen clouds may travel hundreds of kilometers and contribute significantly to local pollination (Figure 2).

Animal-pollinated (mostly tropical) tree species depend on the movement of their pollen vectors. Investigations have shown pollen transport of several kilometers and medium-level gene flow between trees and stands. The very rare apomictic and self-pollinating tree species show the lowest gene exchange rate.

The evolutionary and practical significance of gene flow is high. Its function is to counter genetic drift (random fluctuations in allele frequencies) within the range, to disperse fitness-improving mutant alleles, to maintain high levels of genetic variation and adaptability, and to avert inbreeding in fragmented populations. Gene flow has therefore a decisive role in shaping within-species genetic variation patterns (Table 2), and consequently influences appropriate strategies for forest reproductive material use and conservation.

Detecting Introgression and Genetic Swamping

Introgression refers to gene flow from another taxon. While low levels of gene flow between species are not uncommon, it is a serious issue when an introduced invasive species hybridizes with a native species and overwhelms its genetic constitution (genetic swamping). This is a major threat in canids, ducks, fish and plants. For example, exotic rainbow trout introduced into the habitats of native cutthroat trout in the Western United States led to hybrid swarms that eventually overwhelmed the local species. Introgression is readily detected by molecular genetic and genomic methods.

Genetic and Isotope Analysis

Data on gene flow can also be used to infer dispersal. Ecologists can use allozyme, microsatellite, restriction fragment length polymorphism (RFLP), single-nucleotide polymorphism (SNP), and other genotype data to estimate gene flow among populations. There are at least 2 methods of estimating migration parameters. The coalescent approach uses genealogical information contained in deoxyribonucleic acid (DNA) sequences to estimate long-term migration parameters. These traditional indirect estimators of gene flow rely on the assumption that population sizes and migration rates are constant and that populations persist for a time period sufficient to achieve genetic equilibrium. The second approach uses multilocus genotype to estimate short-term migrations (Faubet et al., 2007). This approach uses Bayesian methods to estimate the posterior probability distributions of allele frequencies, migrant proportions, and individual immigrant ancestries. This method also operates under fewer assumptions than the coalescent approach, allowing genotype frequencies to deviate from the Hardy–Weinberg equilibrium. Simulation experiments have shown that with sufficient differentiation among populations and sufficient number of loci, ecologists can derive accurate estimates of recent migration rates using multilocus genotypes (Wilson and Rannala, 2003).

The use of environmental DNA (eDNA) is a relatively novel approach to study dispersal. eDNA is DNA that is collected from the environment, such as soil and water samples, rather than directly from the study species. The presence/absence and even quantitative comparisons of eDNA from a study species in various habitats (i.e., different stretches of the rivers and lakes or freshwater vs. marine environments) can provide information concerning migration routes and potential barriers to movement (Erickson et al., 2016).

The presence of naturally occurring stable isotopes in animal tissues (i.e., carbon [δ13C], nitrogen [δ15N], and deuterium [δD]) can also be used to trace migration (reviewed in Hobson, 1999). Briefly, this approach relies on differential concentration of stable isotopes in different food webs. For example, if differences between food webs exist and they are spatially clustered, organisms moving between geographic regions can carry information on the location of previous feeding. This information can be used to understand movements between different types of habitat (e.g., mesic and xeric, inshore and offshore, marine and freshwater, etc.). Moreover, δD levels in plants and organisms at higher trophic levels vary predictably across continents with growing season precipitation (Cormie et al., 1994). Thus, this stable isotope can be used to study large-scale migration patterns.

Gene flow could facilitate adaptive evolution

In heterogeneous landscapes, gene flow can serve two key evolutionary roles: constraining and creative (Lenormand, 2002). For one, gene flow may limit adaptive population divergence by continuously introducing maladaptive alleles into local populations (Lenormand, 2002). Large populations in favorable environments typically have greater growth rates (λ) and produce more emigrants than populations in marginal habitats or those at the edges of the range. Asymmetrical gene flow from central to marginal populations can maintain positive population growth rates (Angert, 2009), thereby preventing local extinctions, but it can also prevent those populations from adapting to local conditions (Anderson and Geber, 2010).

Gene flow among populations can also spread advantageous alleles, increasing the genetic variation upon which selection can act. Persistent strong directional selection—as expected under climate change—can deplete genetic variation from local populations (Buckley and Bridle, 2014). Gene flow could hasten adaptation to rapidly changing environments by introducing alleles that confer tolerance to stresses that are becoming more frequent and severe under climate change (Aitken and Whitlock, 2013). That is, gene flow could promote adaptation to novel suites of environments if alleles adapted to elevated temperatures, drought, reduced snowpack, or other conditions associated with climate change become introgressed into locally adapted populations in upslope or poleward locations (Aitken and Whitlock, 2013). This “evolutionary rescue” has been incorporated in to assisted gene flow conservation management plans, whereby individuals or genetic material from robust populations are introduced to imperiled populations to facilitate rapid evolutionary responses to selection (Aitken and Whitlock, 2013). Range expansions and migration are clear signals that natural populations are responding rapidly to climate change (Parmesan et al., 1999; Parmesan and Yohe, 2003; Hickling et al., 2006; Parmesan, 2006). Nevertheless, we know little about the importance of gene flow for promoting or constraining evolutionary responses to climate change (Kremer et al., 2012, 2014).

Within a species, populations likely differ in their potential to adapt to ongoing changes (Hampe and Petit, 2005). For example, contracting populations at the trailing edge of the range of a species are less likely to adapt for several reasons. For one, these populations are located at the warmest edge of the distribution and will not experience an influx of migrants from equatorial or downslope populations. That is, these populations cannot be rescued by gene flow from populations that evolved in historically hotter sites (for a discussion of evolutionary rescue, see Alberto et al., 2013; Gonzalez et al., 2013). As conditions continue to change, novel selection could cause optimal trait values to fall far from current average trait values (Anderson et al., 2012), reducing average fitness and causing population growth rates to decline. For example, trailing edge populations of Scots pine (Pinus sylvestris) show reduced seedling survival under elevated temperatures and novel precipitation regimes projected with climate change (Matias and Jump, 2014). Whereas southern pine populations will likely experience reduced recruitment under increased temperature and drought stress, recruitment may increase in northern populations (Matias and Jump, 2014). These results highlight that biological responses to climate change likely differ across the range, with trailing edge populations experiencing declines and leading edge populations potentially growing (Matias and Jump, 2014).

Diminishing population sizes puts trailing populations at risk of increased mortality due to both demographic and environmental stochasticity (Keith et al., 2008). That is, trailing populations will likely confront the challenges that face small populations, including increased risk that intrinsic and extrinsic factors could hasten population decline. For example, small populations are subject to demographic stochasticity (random fluctuations in birth and death rates) and environmental stochasticity (variation in resources and natural enemies), reduced genetic diversity, increased rates of genetic drift, inbreeding depression, and Allee effects (reduced mating success) (Heschel and Paige, 1995; Hampe and Petit, 2005; Heschel et al., 2005; Bijlsma and Loeschcke, 2012; Gossmann et al., 2012). Reduced genetic diversity will restrict adaptive responses to novel selection imposed by climate change.

Abstract

Next to mutation, gene flow, and natural selection, genetic drift is one of the four factors causing a gene pool to change over time. Genetic drift is defined as the random variation in allele frequencies between generations in finite populations, due to sampling error. Genetic drift is a nondirectional process, causing (1) loss of genetic variation from populations, (2) genetic differentiation among populations, and (3) increased homozygosity of the individuals. Even currently, large populations may have been subjected to genetic drift through bottleneck or founder effects. Genetic drift plays an important role in conservation biology where it is one of the factors that determines the minimal viable population size of a species. Genetic drift is also at the heart of the shifting-balance theory of evolution and of the neutral theory of molecular evolution.

Effects of Isolation

Migration itself does not guarantee gene flow. If individuals are locally adapted to their natal environment, the reproductive fitness of those individuals in a different population residing in a new environment may be quite low, leading to an effective isolation of the populations. Selection may act differentially on parts of the genome that are most directly affected by environmental differences. For example, if an individual migrates into a population and successfully reproduces with a native individual, sexual recombination of gametes will generate offspring with combinations of ‘native’ and immigrant gene copies. Considering two physically unlinked genes A and B, where different copies at the A gene are selectively neutral but alleles at the B gene are not, many offspring may survive in the population that carry the immigrant allele at the A gene, but few or none may survive if they carry the immigrant allele at the B gene. Here, isolation is again quantitative in that the isolation may only be for particular elements of an organism’s genome, rather than isolating two populations or species entirely.

The net result of these varying types of isolation is that to a certain extent, indirect techniques such as measuring allelic diversity at a variety of genetic loci in multiple populations can be used to characterize the degree to which populations fit the equilibrium neutral model governed by mutation, drift, and migration. There are a number of ways in which this model may be violated, particularly in cases where one or more populations being compared is or has recently expanded from a founder population (e.g., range expansions or species introductions); nevertheless, the comparison of isolation measures across many markers may be indicative of both demographic and selective forces that promote the evolutionary divergence of populations in isolation.

Isolation is not a static characteristic of populations. The Isthmus of Panama is an excellent case of complete contemporary isolation of marine populations on either side; there is no gene flow, no migration, and no interaction between individuals from the tropical eastern Pacific and the Caribbean. However, as the Isthmus formed over the course of a million years or more, populations that were initially freely mixing were slowly but increasingly isolated by the uplift of land masses and reduction of currents by freshwater inflows and mangrove swamps, and the final reduction in the number of pathways by which individuals could travel from one side to the other. This more realistic scenario of isolation allows for migration to persist beyond the initiation of the isolating event. Known as the isolation-migration model, this statistical approach allows more complete description of the cause and timing of isolation between populations. Without considering both factors, it is difficult to distinguish whether two populations share many alleles due to high migration, or recent (complete) isolation, or a mixture of intermediate migration and intermediate levels of isolation.

Complex scenarios may arise due to the interaction between historical and contemporary causes of isolation. While the variance in allele frequencies from one population to another is a standard method of measuring isolation it is not always clear whether that isolation is truly due to an equilibrium of mutation, drift, and migration – the isolation by distance model. It is also possible that ancestral events could separate a single population into two or more disjunct populations; subsequent environmental change, again permitting migration between the two areas, would cause a pattern of secondary gene flow. Geographic areas where two genetically or morphologically distinct groups interact, with incomplete isolation, are called clines. Many well-studied clines are caused by the secondary interaction between historically isolated populations.

One case study that illustrates both isolation by distance and the interaction of historically isolated lineages involves a ‘ring species’ of warblers in Asia. The geographic range of Phylloscopus trochiloides wraps around the Tibetan Plateau, and limited dispersal from the nest site results in populations from western Siberia through Tibet that exhibit a strong correlation of the geographic distance between sampled sites and the genetic distance measured at a mitochondrial gene. With greater geographic distance around the Tibetan Plateau, genetic distance gradually increases. However, there is a zone of overlap in central Siberia in which populations at one end of the ‘ring’ encounter populations from the other end – but in this region, the birds differ significantly in terms of plumage and song. This case is made more interesting by the isolation of eastern Siberian populations from those further south on the Tibetan Plateau due to deforestation – eventually, without any means of dispersal between the two sites, the east Siberia populations of P. trochiloides could become completely distinct (ecologically and demographically isolated).

Isolation and its subsequent effect on the evolutionary trajectory of a species has been the central theme of speciation literature over the past century. Only recently has this topic begun to be regularly incorporated into the study and theory of ecology and demography. Much of the diversity in form and function observed in our present-day environment can be thought to be the result of past isolation events and should therefore be considered a topic of much importance in fields of study other than evolutionary biology. Isolation events and their underlying mechanisms can have wide-ranging effects on a species. The effects of isolation may be detectable in genetic, ecological, and demographic patterns. Therefore, these topics should be of increasing relevance to current research focused on population ecology, local adaptive processes, and conservation biology.

Seed Dispersal as Key Ecosystem Function and Service

Seed dispersal may drive plant gene flow, plant population dynamics and functional connectivity along landscapes and affect to key ecosystem functions related to (a) revegetation, recolonization and population dynamics of vegetation, and (b) the connectance and connectivity of information (species and genetic diversity), and it intimately depends on the scale of landscape structure of habitat. Due to these roles, seed dispersal is now considered a key ecosystem function as it has major implication for the colonization and recovery of fragmented and altered landscapes and the conservation and resilience of native ecosystems. Seed dispersal outcome may even be quantified in economic terms, when linking the process of vegetation recovery to recreation or carbon-sink uses as seed dispersal enhances the ecological succession. As suggested for other provisioning ecosystem services, at least three relevant components may be distinguished in seed dispersal function: the magnitude of seed delivery (abundance of seeds), the composition of seed input (richness of species dispersed), and the spatial pattern of seed rain which cascades into those processes structuring species communities.

In the case of seed dispersal by animals, frugivores are considered to be mobile links as they are able to connect habitat patches across landscapes. A large proportion of plants in tropical and temperate ecosystems bear fleshy fruits and thus the plant species richness there should be highly dependent on the relationship between the plant spatial pattern within the landscape and the activity of frugivorous animals. Frugivores may drop many seeds under plant canopies, and this deposition may be highly contingent to the individual plant location relative to co-fruiting partners, which strongly vary yearly. In this sense, seed dispersal by frugivores could additionally has properties related to spatially-explicit ecological networks, defined by nodes (represented by individual habitat patches or individual trees) and links (represented by the probability of dispersal among individual habitat patches or trees).