What does variation within a species cause

The visual examination of how dispersal diversity partitions onto phylogenetic trees shows that artificial nodes within-species generally bear a non-negligible part of the diversity in dispersal traits Figure 2. For the majority of dispersal metrics, the artificial nodes accounted for a portion of the diversity that was not significantly different from a random distribution of trait diversity among the nodes of the corresponding tree, indicating that within-species variation in dispersal is not different from that observed at the inter-specific level Table 2.

Two out of eight observed S c were significantly lower than the theoretical distribution obtained from permutations daily moves , FstL : Table 2 ; Figure 3. FstC also showed a slightly significant trend to low variation within species. For the five other metrics, the variation observed between two populations of a species is of the same order of magnitude as that observed between two species, as shown by the position of S c in the theoretical distribution Table 2 ; Figure 3. The circles at nodes provide the contribution of the node to total diversity in dispersal metric.

The scale is given at the bottom left-hand corner of each panel. White circles are for nodes in the original classification, grey circles are for the contribution of within-species diversity to the total diversity.

Grey branches denote replicates for a given species, here described as virtual sister-taxa. A: dispersal fraction : proportion of recaptures with inter-patch movement in multisite mark-recapture.

E: Daily moves , the mean daily displacements in mark-release-recapture surveys. Diamonds show the observed values of S c. Although artificial nodes and some other near-to-tips nodes stand for a significant part of the diversity in dispersal, this diversity generally remains significantly rooted into the phylogeny for most direct estimates of dispersal Table 2 : test S 3.

The diversity of indirect dispersal estimates F ST did not show a significant bias towards close-to-root nodes when accounting for within-species variability Table 2 : S 3. By partitioning the dispersal diversity along the phylogenetic trees, we considered the variation in dispersal traits observed at the species level in the light of that existing across related species. This method provides the first quantitative demonstration that, in European butterflies, dispersal is as diverse at the species level among populations as it is across species.

However, for two direct estimators of dispersal, the variability in dispersal was significantly lower within-species than among-species, which indicates that trait conservation at the species level might also exist for some traits. This importance of within-species variation in dispersal traits will deeply impact the way dispersal models should be built to address specific questions such as the dynamics of metapopulations in fragmented landscapes or that of biological invasions.

These implications are discussed below. We start here by some technical considerations about the method. Our method constitutes an original way to quantitatively appreciate the liability of functional traits in a phylogenetically explicit context.

Here we used the decomposition of trait diversity to ask whether dispersal traits were less variable among populations of a species than across species in butterflies, but the method was constructed so that it could be applied to other questions and be extended to a suite of traits.

For instance, by measuring the diversity at chosen nodes in the phylogeny, it is possible to detect regions in the phylogeny where a trait or a combination of traits shows a higher variability than random expectations. The null model in that case is that the trait diversity among the species that descend from that node is equivalent to the trait diversity expected by randomly drawing the same number of species from the species pool that includes species at all tips of the phylogeny.

Unfortunately, the data available did not allow us to make such analysis for dispersal in butterflies. Analysing the partition of diversity for the combined facets of dispersal that is: combining the dispersal propensity, the dispersal ability and the dispersal efficiency was not feasible here because all these traits were available for different groups of species see Figure 2.

However, the statistic S c could potentially be applied to a suite of functional traits as we measured trait diversity by the quadratic entropy index see methods.

A complication of our approach comes from the use of published material. The studies from which we extracted the dispersal metrics did not all focus on dispersal. However, standardized Mark-Release-Recapture surveys allow to routinely detect among-patches movements assimilated to dispersal , even when these are not central to the study; and genetic studies inform on the relative ability of populations to maintain gene flow through space, which is the net result of dispersal.

However, we cannot rule out the possibility that part of the variation observed is attributable to the way dispersal was measured. For instance, the use of different sets of allozymes may result in slight differences in F ST , even within the same set of populations.

In the same vein, there is a possibility that dispersal metrics were underestimated in some field studies. For instance, we have to assume that all possible sources for immigrants were properly surveyed, and that spatial scales were adequately chosen to detect most dispersal movements in the surveys that provided the dispersal metrics used here.

The dispersal propensity here the dispersal fraction , the ability to disperse at given distances alphas , P5km , daily moves and the efficiency of dispersal movements F ST did not show the same pattern of diversity partitioning across butterfly species.

Noticeably, only two metrics related to the ability to disperse alpha2 , daily moves presented the signature of a phylogenetic signal while neither the dispersal propensity nor the dispersal efficiency did Table 1. Dispersal efficiency depends on several behavioural decisions of the butterfly: leaving its habitat, settling into another, and mating. On the contrary, we expect dispersal distances to be related to butterfly's flying capacity, which is related to morphological traits, like wing length or shape [14].

The heritability of morphological attributes is generally higher than that of behavioural traits [15] , [16]. This difference may explain why the phylogenetic signal is only detected in dispersal ability and not in dispersal efficiency.

The absence of a phylogenetic signal on F ST diversity might also be due to the fact that dispersal is not the only driver accounting for the spatial structuring of allozymic diversity, which is in effect the ultimate result of the contradicting forces of selection, random drift, mutation, and gene flow.

All these forces probably vary among butterflies species, which may have confused the pattern of diversity in F ST. For instance, local adaptation is expected to occur with the selection of certain allozymes under certain sets of conditions in the environment [17] , [18] , [19] , with the possibility of contrasting selective pressures on allozymes in different butterfly species.

Moreover, gene flow itself may be not directly related to dispersal flows because it results from both dispersal movements and the relative ability of the disperser to transfer its genes to the next generation. The indirect relation between genetic structuring and dispersal flows might explain the absence of a detectable phylogenetic signal on F ST.

The phylogenetic perspective on dispersal variation shows that dispersal is highly variable at the species level. The importance of within-species diversity in dispersal traits was already suggested in our recent meta-analysis [20] , but is here quantified for the first time.

Only two out of the eight dispersal metrics considered tend to be conserved at the species level Figures 2 , 3 ; Table 2. The variation among different populations of the same species is generally not significantly less than the differences observed among species like in the situation depicted right of Figure 1. S c compares the diversity in dispersal at artificial nodes that is the within-species diversity to the diversity at all other nodes of the classification, and not only at other terminal nodes.

This means that the difference in dispersal metrics between two populations of the same species could also have been observed between two randomly chosen species, not necessarily between particularly closely related species. This is a strong argument against dispersal as a species-specific, fixed trait. The source for this high within-species variation is not investigated here, and is probably multiple. As mentioned, dispersal is condition- and phenotype-dependent, which may have caused variability in dispersal traits among populations of a species, either through the selection of contrasting dispersal patterns, or by the contrasting expression of butterflies' dispersal traits in different populations due to phenotypic plasticity or behavioural flexibility.

Some evidence indicates that landscape configuration can cause within-species variation in dispersal propensity in butterflies [21] , [22]. In a spider, Bonte et al. Others have shown that insect's performances related to dispersal ability, like flight endurance or the perceptual range the distance at which the individual is able to perceive suitable habitats are both heritable [25] and plastic [26].

Different traits associated to dispersal might thus either have been selected in population living in contrasted environments, or have been indirectly selected because they are dependent on morphological attributes selected for other reasons indirect selection , or they might be expressed plastically by organisms experiencing contrasting conditions.

To identify the relative importance of both processes local adaptation vs. We showed that for a given species, the level of variation strongly depended on the metric considered Figure 2. The studies from which data were extracted for our analyses were generally not designed so as to maximize the chance to detect differences in dispersal patterns, with the noticeable exception of Proclossiana eunomia , for which dispersal was measured in four landscapes along a gradient of fragmentation [21].

In other cases, study sites were chosen independently of a potential filtering on dispersal processes, which probably impeded the detection of a general pattern in species' variability in dispersal traits if existing.

The heterogeneity of the variation observed among the metrics for a given species should be related to the heterogeneity of the dispersal process itself. What we call dispersal is in effect a process resulting from a suite of decisions, from emigration, through transfer, to immigration [27]. At first sight, our results suggest that those different dispersal estimates that we analyzed were under uncoupled selective pressures.

In fact, the different dispersal metrics recorded in butterflies emphasize on a part of the whole dispersal process without taking into account the fitness rewards of the whole process.

Complex feedbacks between them are possible; for instance, costs of transfer may limit the dispersal propensity [21]. How the various steps of the dispersal process co-vary or trade off with each other is still a relatively unaddressed question in dispersal research that certainly deserves further attention. Dispersal is a key process in the response of natural populations challenged by spatial problems such as the shift of suitable climatic envelopes [28] or the fragmentation of their habitats [29] , and also participates in the propagation of alien species into new areas [30] , [31].

We demonstrate here for the first time that dispersal is as variable between populations of a species as it is between species within a phylogenetically complex group.

The accurate estimation of dispersal is therefore an essential prerequisite to realistically predict the demographic trajectories of threatened and invasive species with models. The identification of the processes at the origin of variation in dispersal traits should be addressed in future studies. Because it participates to gene flow, dispersal is most probably not independent from other life-history traits. The few theoretical and empirical studies that investigated such relationships found strong dependency between dispersal and other traits [25] , [32,32].

We show here that individuals from different populations of a given species vary in their propensity, their ability and their efficiency to disperse, which might cause local variation in the genetic conditions under which selection will operate. To identify and measure the dependency of life histories to dispersal is crucial to adequately predict the response of populations threatened by environmental changes, from both the demographic and the evolutionary points of view.

To conclude, the low conservation of dispersal traits we detected here within species will undoubtedly impact both the evolution and the metapopulation dynamics of butterflies, and hence must be accounted for in metapopulation modelling. This message is reinforced by the evidence that variability in metapopulation dynamics is dependent on both condition and phenotype [1] , [34].

Considering dispersal as an invariant within species will severely limit our predictive capabilities for any spatial ecological problem. We show here that two metapopulations of a given species may differ in their dispersal abilities as much as do two metapopulations from different species. Predicting the fate of a metapopulation and consequently that of a metacommunity in a given region therefore requires that we estimate as exactly as possible the value of dispersal traits in the populations of interest.

Accordingly, our results stress the need of incorporating dispersal variability into those predictive models that aim at forecasting species distribution according to global change. Dynamic modelling coupling habitat suitability models with spatially explicit stochastic meta population models including dispersal have been developed to explore factors that influence the viability of populations under stable and changing climate scenarios [35] , [36].

However, our findings imply that single species-specific dispersal parameter should be replaced in such models by the use of a distribution of dispersal parameters sampled in each local population of interest. The various dispersal metrics published for European butterflies were recently reviewed by two of us [20]. We used here the dispersal metrics collected in this review that were available for several populations of the same species Table 3.

As we are interested in the within-species variation in dispersal, we considered only the dispersal metrics that were available for at least 10 species, among which at least three were represented by three or more replicates i.

Using these criteria, we selected eight metrics that reflect butterfly dispersal capability, coming from direct measurement in standardized Mark-Release-Recapture surveys MRR or, indirectly, from the genetic structure among populations inferred from allozyme screening.

The relative dispersal propensity of butterflies was assessed by the dispersal fraction : the proportion of recaptured butterflies that were recaptured in a patch different from that of their first capture in MRR. The relative dispersal ability of butterflies was described by four metrics, all coming from standardized MRR surveys.

Butterflies' dispersal kernels—that is the inverse cumulative proportion of individuals moving certain distances—can generally be fitted either to a negative exponential or to an inverse power function. We used the shape of these two types of kernels as an indication of butterflies' dispersal ability. Negative exponential kernels were described by alpha , the only parameter of the function.

As alpha was sensitive to the scale over which mark-recapture was performed, we considered separately alphas inferred from movement rates in study sites smaller or larger than the median length of the study sites. These were named respectively alpha1 and alpha2.

Overall, the forces that cause relative allele frequencies to change at the population level can also influence the selection forces that shape them over successive generations. For example, if moths with genotype aa migrate into a population composed of AA and Aa individuals, they will increase the relative allele frequency of a.

However, if the aa genotype has a clear disadvantage to survival e. This page appears in the following eBook. Aa Aa Aa. Genetic variation describes naturally occurring genetic differences among individuals of the same species. This variation permits flexibility and survival of a population in the face of changing environmental circumstances. Consequently, genetic variation is often considered an advantage, as it is a form of preparation for the unexpected.

But how does genetic variation increase or decrease? And what effect do fluctuations in genetic variation have on populations over time? Mating patterns are important. Random forces lead to genetic drift. If the individuals at either end of the range reconnect and continue mating, the resulting genetic intermixing can contribute to more genetic variation overall.

However, if the range becomes wide enough that interbreeding between opposite ends becomes less and less likely, and the different forces acting at either end become more and more pronounced, and the individuals at each end of the population range may eventually become genetically distinct from one another. Here is an example of migration affecting relative allele frequency:.

The overall effect. Here is an example of how a specific genotype is less favorable than another genotype:. Genetic variation in a population is derived from a wide assortment of genes and alleles. The persistence of populations over time through changing environments depends on their capacity to adapt to shifting external conditions.

Sometimes the addition of a new allele to a population makes it more able to survive; sometimes the addition of a new allele to a population makes it less able. Still other times, the addition of a new allele to a population has no effect at all, yet the new allele will persist over generations because its contribution to survival is neutral.

Key Questions How can genetic variation influence evolution? What is an example of genetic drift? Topic rooms within Genetics Close. No topic rooms are there. Browse Visually. Other Topic Rooms Genetics. Student Voices. Examples of genetic variation in humans include blood group, skin colour and eye colour. Gender is also an inherited variation — whether you are male or female is a result of the genes you inherited from your parents.

Characteristics of animal and plant species can be affected by factors such as climate, diet, accidents, culture and lifestyle. For example, if you eat too much food you will gain weight, and if you eat too little you will lose weight. Another example is that of a plant that grows in the shade of a big tree - it will grow taller to reach more light. Other examples of features that show environmental variation include:. Some features vary because of a combination of genetic and environmental causes.