[show abstract][hide abstract] ABSTRACT: While it is well understood that the pace of evolution depends on the interplay between natural selection, random genetic drift, mutation, and gene flow, it is not always easy to disentangle the relative roles of these factors with data from natural populations. One popular approach to infer whether the observed degree of population differentiation has been influenced by local adaptation is the comparison of neutral marker gene differentiation (as reflected in FST) and quantitative trait divergence (as reflected in QST). However, this method may lead to compromised statistical power, because FST and QST are summary statistics which neglect information on specific pairs of populations, and because current multivariate tests of neutrality involve an averaging procedure over the traits. Further, most FST-QST comparisons actually replace QST by its expectation over the evolutionary process and are thus theoretically flawed. To overcome these caveats, we derived the statistical distribution of population means generated by random genetic drift and used the probability density of this distribution to test whether the observed pattern could be generated by drift alone. We show that our method can differentiate between genetic drift and selection as a cause of population differentiation even in cases with FST=QST and demonstrate with simulated data that it disentangles drift from selection more accurately than conventional FST-QST tests especially when data sets are small.
[show abstract][hide abstract] ABSTRACT: We modeled hierarchical multiscale colonization-extinction dynamics of two aphid species living in a shared host plant. We parameterized the model with data collected at the level of individual ramets of the host plant, with the plants being organized as groups within islands. As expected, the extinction rates and per capita colonization rates decreased with increasing spatial scale. The per capita colonization rates were greater for winged than for unwinged individuals, but as the unwinged individuals were much more abundant, they actually performed most of the colonizations. Colonizations and extinctions were negatively correlated, so that when the colonization rate in a given island was high, the extinction rate in the same island was low. There was a clear indication of interspecific interaction, with the presence of one species increasing the extinction rate and decreasing the colonization rate of the other species. Further simulation results based on the parameterized model show a contrasting pattern between the two species, with Metopeurum fuscoviride (with relatively stable dynamics) being favored by a highly aggregated distribution of the ramets, whereas for Macrosiphoniella tanacetaria (with a high turnover rate), an equally high persistence time follows if the plants are distributed in a segregated manner over several islands.
The American Naturalist 10/2009; 174(3):331-41. · 4.55 Impact Factor
[show abstract][hide abstract] ABSTRACT: Dispersal comprises a complex life-history syndrome that influences the demographic dynamics of especially those species that live in fragmented landscapes, the structure of which may in turn be expected to impose selection on dispersal. We have constructed an individual-based evolutionary sexual model of dispersal for species occurring as metapopulations in habitat patch networks. The model assumes correlated random walk dispersal with edge-mediated behaviour (habitat selection) and spatially correlated stochastic local dynamics. The model is parametrized with extensive data for the Glanville fritillary butterfly. Based on empirical results for a single nucleotide polymorphism (SNP) in the phosphoglucose isomerase (Pgi) gene, we assume that dispersal rate in the landscape matrix, fecundity and survival are affected by a locus with two alleles, A and C, individuals with the C allele being more mobile. The model was successfully tested with two independent empirical datasets on spatial variation in Pgi allele frequency. First, at the level of local populations, the frequency of the C allele is the highest in newly established isolated populations and the lowest in old isolated populations. Second, at the level of sub-networks with dissimilar numbers and connectivities of patches, the frequency of C increases with decreasing network size and hence with decreasing average metapopulation size. The frequency of C is the highest in landscapes where local extinction risk is high and where there are abundant opportunities to establish new populations. Our results indicate that the strength of the coupling of the ecological and evolutionary dynamics depends on the spatial scale and is asymmetric, demographic dynamics having a greater immediate impact on genetic dynamics than vice versa.
Philosophical Transactions of The Royal Society B Biological Sciences 07/2009; 364(1523):1519-32. · 6.23 Impact Factor
[show abstract][hide abstract] ABSTRACT: Quantifying dispersal is crucial both for understanding ecological population dynamics, and for gaining insight into factors that affect the genetic structure of populations. The role of dispersal becomes pronounced in highly fragmented landscapes inhabited by spatially structured populations. We consider a landscape consisting of a set of habitat patches surrounded by unsuitable matrix, and model dispersal by assuming that the individuals follow a random walk with parameters that may be specific to the habitat type. We allow for spatial variation in patch quality, and account for edge-mediated behavior, the latter meaning that the individuals bias their movement towards the patches when close to an edge between a patch and the matrix. We employ a diffusion approximation of the random walk model to derive analytical expressions for various characteristics of the dispersal process. For example, we derive formulae for the time that an individual is expected to spend in its current patch i, and for the time that it will spend in the matrix, both conditional on the individual hitting next a given patch j before hitting any of the other patches or dying. The analytical formulae are based on the assumptions that the landscape is infinitely large, that the patches are circularly shaped, and that the patches are small compared to interpatch distances. We evaluate the effect of these assumptions by comparing the analytical results to numerical results in a real patch network that violates all of the three assumptions. We then consider a landscape that fulfills the assumptions, and show that in this case the analytical results are in a very good agreement with the numerical results. The results obtained here allow the construction of computationally efficient dispersal models that can be used as components of metapopulation models.
[show abstract][hide abstract] ABSTRACT: We describe a Bayesian random effects model of mark-recapture data that accounts for age-dependence in survival and individual heterogeneity in capture probabilities and survival. The model is applied to data on the Glanville fritillary butterfly (Melitaea cinxia) collected from a population enclosed in a large cage in the field. The cage population consisted of a mixture of butterflies originating from newly established and old populations in a large metapopulation in the Aland Islands in Finland. The explanatory variables in the model included the effects of temperature, sex, and population type (new vs. old) on capture probabilities, and the effects of age, sex, population type, and day vs. night on survival. We found that mortality rate increased with age, that mortality rate was much higher during the day than during the night, and that the life span of females originating from newly established populations was shorter than the life span of females from old populations. Capture probability decreased with increasing temperature and decreased with increasing mobility of individuals.
[show abstract][hide abstract] ABSTRACT: Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components. Ekologisten ja evolutiivisten prosessien mallinnus tilarakenteisissa populaatioissa Monet lajit asuttavat maisemia joiden rakenne on pirstoutunut joko luonnostaan tai ihmisen toimesta. Tällaisia maisemia asuttavien populaatioden ekologiseen ja evolutiiviseen dynamiikkaan vaikuttaa hyvin monenlaisten tekijöiden vuorovaikutus, ja niiden tutkimus on siten haastavaa. Väitöskirjassani olen kehittänyt matemaattisia ja tilastotieteellisiä menetelmiä tilassa pirstoutuneiden populaatioiden ekologian ja evoluutiobiologian tarkasteluun. Olen testannut ja soveltanut kehittämiäni menetelmiä käyttäen empiirisiä aineistoja kahdesta mallisysteemistä, jotka ovat Ahvenanmaan täpläverkkoperhonen ja Tvärminnen saarten kirvapopulaatiot. Molemmat systeemit ovat rakenteeltaan hierarkisia, eli lajeille sopiva elinympäristö esiintyy pienten laikkujen muodostamina verkostoina, ja yksittäiset osaverkostot ovat osa laajempaa kokonaisuutta. Tällaisista systeemeistä kerättyjä aineistoja on luontevaa analysoida käyttäen hierarkisia Bayesilaisia malleja, ja väitöskirjatyöni keskeinen osa on näiden mallien kehittämisessä ja parametrisoinnissa. Pirstouneiden maisemien populaatiodynamiikka riippuu yksilöiden kyvystä liikkua elinympäristölaikulta toiselle, ja väitöskirjatyöni toinen painopistealue on yksilöiden liikkumisen matemaattisessa mallintamisessa.