Conceived and designed the experiments: VMS SP MB. Analyzed the data: VMS SP. Wrote the paper: VMS SP MB. Acquired the data: VMS. Interpreted the results: MVS MB.
The authors have declared that no competing interests exist.
Mounting evidence shows that contrasting selection pressures generate variability in dispersal patterns among individuals or populations of the same species, with potential impacts on both species dynamics and evolution. However, this variability is hardly considered in empirical works, where a single dispersal function is considered to adequately reflect the species-specific dispersal ability, suggesting thereby that within-species variation is negligible as regard to inter-specific differences in dispersal abilities. We propose here an original method to make the comparison of intra- and inter-specific variability in dispersal, by decomposing the diversity of that trait along a phylogeny of closely related species. We used as test group European butterflies that are classic study organisms in spatial ecology. We apply the analysis separately to eight metrics that reflect the dispersal propensity, the dispersal ability or the dispersal efficiency of populations and species. At the inter-specific level, only the dispersal ability showed the signature of a phylogenetic signal while neither the dispersal propensity nor the dispersal efficiency did. At the within-species level, the partitioning of dispersal diversity showed that dispersal was variable or highly variable among populations: intra-specific variability represented from 11% to 133% of inter-specific variability in dispersal metrics. This finding shows that dispersal variation is far from negligible in the wild. Understanding the processes behind this high within-species variation should allow us to properly account for dispersal in demographic models. Accordingly, to encompass the within species variability in life histories the use of more than one value per trait per species should be encouraged in the construction of databases aiming at being sources for modelling purposes.
In most mobile animals, locomotory and navigation limits generate broad, evident differences in dispersal patterns of organisms belonging to contrasted clades. Such huge inter-specific differences in the ability to move among local habitat patches are probably the main reason why dispersal has been so long considered as a species-specific fixed trait. However, there is now mounting evidence that dispersal is variable at the species level because populations and individuals may experience contrasting pressures on their dispersal
Theory predicts, and empirical work confirms, that dispersal is condition-dependent
A high intra-specific variation in dispersal ability resulting from both condition- and phenotype-dependence of dispersal costs and benefits is now widely accepted
Small panel: illustration of hypothetical within-species trait variability (among population differences in the value of a trait) considered without inter-specific reference. The large panel illustrate two hypothetical scenarios, where the variability among populations for the species of interest (summarized by the black rectangle) is now viewed in the light of existing inter-specific variation in the trait (grey symbols: trait values in five other species): left, the situation of trait conservation, where intra-specific variability is low relatively to inter-specific variability; right, a situation of high within-species variability, where differences between populations of a species are of the same order of magnitude than among-species differences.
Butterflies have long been recognized as ideal models for the study of fragmented populations and have now been widely adopted as biological models in the integrated study of dispersal
The relative amount of diversity for a given trait (here dispersal) that is supported by ancient nodes and close-to-tips nodes of a phylogenetic tree provides us with information about the evolutionary history of that trait. By partitioning the functional diversity, it is possible to contrast situations in which the trait evolved early, and then was conserved (in that case, the diversity in trait values would tend to be rooted into the tree) and situations where the trait evolved recently (in that case, closely related species would show different values for the trait and diversity would be skewed to close-to-tip nodes of the tree)
Here, we partitioned the diversity in dispersal traits to assess the importance of the intra-specific diversity in dispersal relative to the diversity observed across species. We considered the values of eight dispersal metrics assessed in different populations of a species as the source of within-species variation and ignored the part of the variation attributable to differences among individuals of the same population. To make the comparison in a phylogenetic context, we considered populations of a given species such as these were distinct sister-taxa (virtual taxa), and hence were supported by the closest-to-tips nodes of the phylogenetic tree. If the intra-specific variation in dispersal ability of butterfly is less than the amount of variation expressed at the inter-specific level, we expect that these terminal nodes, supporting populations of a given species, will also support a significantly lower part of the diversity than other nodes.
Ignoring the within-species variation in dispersal (that is, using values of each metric averaged over populations of each species), we found that there are significant phylogenetic signals in two dispersal metrics coming from multisite mark-recapture studies (
Trait | Metric |
Number of species | Abouheif's |
|
25 | 0.233 | 0.208 | ||
16 | 0.258 | 0.208 | ||
18 | 0.542 | 0.008 | ||
27 | 0.263 | 0.132 | ||
25 | 0.374 | 0.070 | ||
13 | 0.144 | 0.514 | ||
15 | 0.063 | 0.640 | ||
10 | 0.125 | 0.514 |
The value of the dispersal metric considered is the mean value observed across replicates (where applicable).
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 (
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:
Diamonds show the observed values of
Metric |
Statistic |
Hypothesis | Alternative | |
Skewness to root | 2-sided | 0.076 | ||
Intra-specific conservation | Less | 0.092 | ||
Skewness to root | 2-sided | 0.583 | ||
Intra-specific conservation | Less | 0.628 | ||
Skewness to root | 2-sided | 0.014 |
||
Intra-specific conservation | Less | 0.092 | ||
Skewness to root | 2-sided | 0.008 |
||
Intra-specific conservation | Less | 0.102 | ||
Skewness to root | 2-sided | 0.036 |
||
Intra-specific conservation | Less | 0.015 | ||
Skewness to root | 2-sided | 0.055 | ||
Intra-specific conservation | Less | 0.008 | ||
Skewness to root | 2-sided | 0.583 | ||
Intra-specific conservation | Less | 0.384 | ||
Skewness to root | 2-sided | 0.583 | ||
Intra-specific conservation | Less | 0.054 |
Replicates of a dispersal measurement for a given species are treated as if they were from virtual sister-taxa descending from an artificial terminal node in enlarged trees (see
Test S3 from Pavoine et al.
P: P-values corrected for multiple comparisons.
The diversity is significantly skewed towards nodes that were the most distant from tips in the original phylogeny (with 369 butterfly species considered).
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 (
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. For instance, some families were largely over-represented in our sample relatively to others (for instance, Nymphalidae represent 17% of the 369 European species, but are 20% to 53% of the species for which dispersal metrics were available: see
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
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
The dispersal propensity (here the
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
The absence of a phylogenetic signal on
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
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
There is no general pattern in how the variability in dispersal is distributed among butterfly species: we did not reveal consistently ‘variable’ species and other ‘conservative’ species where all dispersal metrics were conserved. We showed that for a given species, the level of variation strongly depended on the metric considered (
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
Dispersal is a key process in the response of natural populations challenged by spatial problems such as the shift of suitable climatic envelopes
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
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
The various dispersal metrics published for European butterflies were recently reviewed by two of us
Dispersal trait | Dispersal metric |
Number of species considered | Number of species with data available for >1 populations | Maximum number of populations/species for which the metric is available |
Dispersal propensity | 25 | 11 | 6 | |
Dispersal ability | 16 | 10 | 5 | |
18 | 6 | 5 | ||
28 | 10 | 6 | ||
15 | 9 | 4 | ||
Dispersal efficiency | 13 | 7 | 8 | |
15 | 3 | 6 | ||
10 | 4 | 3 |
Metrics are like in
The relative dispersal propensity of butterflies was assessed by the
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
Finally, indirect dispersal metrics inform on the relative efficiency of dispersal of butterflies. Although their sensitivity is questionable,
All eight dispersal metrics were Box-Cox transformed so as to conform to normality and were standardized before subsequent analyses.
The European butterflies' phylogenetic tree used is a combined tree constructed from published phylogenies of individual groups and, for groups with no phylogeny available, from formal classification into genera and subgenera
When a given metric was available for several populations of a species, we considered those values as if they were from sister-taxa. To do that, we constructed eight enlarged trees, corresponding each to one of the pruned trees. In those trees, a terminal (artificial) node was added that supports the populations (now virtual sister-taxa) at the place where the species tip was in the pruned tree (see the eight enlarged trees in
To test the hypothesis that dispersal is constrained by phylogenetic relationships among European butterflies, we searched for a phylogenetic signal in the eight dispersal metrics by using Abouheif's statistic (
If the within-species variability in dispersal is negligibly low relative to the whole diversity observed across butterflies' species, we expect that (i) artificial nodes should not stand for a significant contribution in dispersal diversity as compared to other nodes, and (ii) the dispersal diversity would stay significantly rooted into the phylogenetic tree when accounting for the within-species variability.
To test this, we first applied the visual methodology proposed by Pavoine et al.
Next, to test if dispersal ability is conserved within a given species as compared to dispersal variation among species, we could not use classical statistical frameworks (including the ANOVA) because, for each dispersal traits, intra-specific trait values were available for a few species and a few populations within species only. Using ANOVA-like approach would have reduced the estimation of inter-specific trait variation to those species for which we also had estimations of intra-specific trait variation. Alternatively, we designed a permutation test, named trait conservation test, which was applied per dispersal trait. To do that, we measured trait diversity by the quadratic entropy index
Finally, we used another permutation test, proposed by Pavoine et al.
For both
We thank Jan C. Habel and Camille Turlure, who allowed the use of unpublished material, Zdenek Frik and Martin Konvicka, who kindly provided the phylogenetic dataset.