Part III. Abstracts of Gene Flow Workshop Presentations
(Return to Proceedings on Gene flow workshop)
Adams, W. Thomas, Department of Forest Science,
Oregon State University, Corvallis, OR 97331-7501. Mating patterns and
effective pollen dispersal in two western conifers: Douglas-fir and knobcone
Because pollen density drops off rapidly with increasing distance from
its source, most mating in conifer stands might be expected to occur among
near neighbors. The "neighborhood" model was applied to multilocus allelic
(allozyme) arrays observed in pollen gametes of seeds from individual mother
trees to estimate mating pattern parameters in a high density stand of
knobcone pine (kp, Pinus attenuata Lemmon.), and in one high density
(Dfhd) and one low density (Dfld) stand of Douglas-fir (Pseudotsuga
menziesii (Mirb.) Franco). In the neighborhood model, an arbitrarily
specified area around a mother tree (with radius r) is designated its neighborhood,
and the paternity of the mother tree's offspring is partitioned into three
sources: selfing (with probability s), outcrossing to males outside the
neighborhood (m), and outcrossing to males within the neighborhood (1-s-m).
In kp (mean tree height = 6 m), neighborhoods (r = 11 m) included an average
of 44 potential outcross males, while in Douglas-fir, neighborhoods (r
= 70 m) included 18 potential outcross males in Dfld (mean height = 46
m) and 44 in Dfhd (mean height = 38 m).
Estimated s was zero or nearly so in all three stands, but m was quite
high (0.84 in Dfld, 0.74 in Dfhd, and 0.56 in kp). In addition, mating
success of outcross males within neighborhoods was only weakly associated,
at best, with distance from the mother tree. Thus, near neighbors accounted
for only a small percentage of the effective mating in these stands, such
that the effective number of mates for each mother tree was quite large.
As expected, males within neighborhoods contributed to a higher proportion
of the mating in Dfhd than in Dfld, but only marginally so. The lower estimate
of m in kp neighborhoods is probably because kp was more isolated from
other populations of the same species (i.e., less gene flow), than the
Campbell, Diane R. Dept. of Ecology &
Evolutionary Biology, University of California Irvine, CA 92697. Estimating
gene flow within and between populations in a plant hybrid zone
Natural hybridization is common in plants. If plant distribution is patchy
across the region of hybridization, we can distinguish four kinds of gene
movement in a hybrid zone. Intraspecific gene flow can occur within or
between local populations. Interspecific gene flow can occur between distinct
patches each occupied by a single species, or within a patch (hybrid swarm).
Using two hybridizing species of Ipomopsis (Polemoniaceae) as a
model system, I discuss ongoing efforts to estimate these four kinds of
gene movement and the methods appropriate in each case.
The primary means of gene movement in this system is transfer
of pollen by hummingbirds. Behavioral observations of hummingbirds, combined
with measures of pollen carryover from flower to flower, explain the highly
localized pollen movement (usually a few m) within local populations. Similar
mechanistic studies predict asymmetrical gene movement between I. aggregata
and I. tenuituba and generally high rates of interspecific gene
flow. These predictions were tested using a single genetic marker in mixed-species
experimental populations. Work in progress uses multiple RAPD markers to
estimate patterns of gene movement within a naturally hybridizing population.
At the between population level, paternity analysis with multiple allozyme
markers suggests moderately high rates of gene flow from outside. Minimum
rates of gene flow ranged from 9-25% into experimental populations isolated
by as much as 150 m. The discrepancy between these results and the short
distances of pollen flow within populations suggests that gene movement
between versus within populations may result from different pollinator
behaviors, making it difficult to extrapolate across scales. Determining
the distance of gene flow between populations presents a special challenge.
These studies illustrate the value of combining genetic markers with mechanistic
methods in determining patterns of gene flow.
Gene flow across landscapes is accomplished by gravity, wind, water, and
animals. These transport processes are increasingly studied using dynamic,
spatially explicit models. The purpose of this talk is to provide an overview
of these models and discuss there potential applicability to studying gene
flow in fragmented and managed forests.
Davis, Frank W. NCEAS, University of California
at Santa Barbara. Spatially explicit modeling of landscape-scale transport
In the most general sense, it is useful to distinguish two classes
of spatial models: "object" models, which track discrete spatially referenced
features floating in space (e.g. habitat islands), and "field" models,
which divide continuous space into smaller elements and assign a value
to each element. Most spatially explicit models in ecology are field models
that utilize a 2- or 3-dimensional lattice to represent landscape properties
such as elevation, vegetation, location of organisms, etc. Movement across
such grids is usually modeled by local rules. Examples of field models
include cellular automata, discrete reaction diffusion models, and cellular
networks. Object models are sometimes used to represent individual animals
or populations for individual-based models and metapopulation models, respectively.
There are several different data structures for representing spatio-temporal
dynamics (e.g., image sequences, polygons with a vector of temporal attributes
for each polygon). Modern GIS systems now provide some useful spatial analytical
capabilities relevant to modeling gene flow (e.g., distance and neighborhood
analyses, diffusion models, path cost analysis), but are still very limited
for dynamic modeling, which is instead usually performed using specially
designed research software. Generic issues in the use of spatial dynamic
models include: defining the spatial extent, resolution, and time step
for the model, treatment of boundary effects, and movement/connection rules
(e.g., rules governing the relationship between diagonal cells on a square
Among physical transport processes, modeling movement of water
is well developed and a variety of programs are available to model both
surface and subsurface flow at spatial scales from local to continental.
Wind transport models have mainly been developed to represent larger scale
atmospheric processes, although landscape models have also been developed
to study urban microclimate, valley and land-sea wind systems, and local
snow and sand transport. These wind models are generally computationally
very intensive and require extensive parameterization. Simpler models have
been developed based on surface aerodynamic resistance and fetch that could
be useful in studying local gene flow in rugged or heterogeneous terrain.
Spatially explicit diffusion models have been used to study a
variety of biological processes, for example, biological invasions, seed
dispersal, and disease spread. Animal movements have been simulated using
simple diffusion and cellular automate models, as well as more complex,
spatially explicit individual-based models and metapopulation models, some
of which require large-scale computing resources. Simpler approaches to
studying gene flow among animal populations include analysis of topography,
vegetation, or other surface features to calculate path costs for varying
dispersal routes as a way of modeling likely patterns of animal dispersal
on complex landscapes.
My sense is that spatially-explicit models represent an as yet
relatively untapped set of tools which could be used to study gene flow
in continuous versus fragmented landscapes. Even relatively simple applications
of widely available GIS software could be useful for managing and visualizing
gene flow data as well as for some simple modeling procedures. There are
obvious opportunities here for collaboration between geneticists measuring
gene flow in the field and landscape ecologists with expertise in dynamic
For wind pollinated oaks, the rate of pollen migration into the stand is
the most important factor governing gene flow. However, determining the
significance of the resultant pollen distance distribution is problematic
because of the nature of fractional paternity assignment. This study utilized
starch gel electrophoresis and fractional paternity analysis to estimate
rates of apparent and cryptic gene flow into a stand of red oak in central
Missouri. Progeny arrays from three maternal trees and 234 putative fathers
from a 4 ha stand revealed 15 of the 137 offspring resulting from gene
flow into the stand. Furthermore, Monte Carlo simulations predicted one
offspring to be the result of cryptic gene flow. Total gene flow, converted
to Nm, was 2.0. Resultant pollen distance distributions suggest a leptokertic
distribution, however truncation of individuals with ambiguous paternity
prevents statistical testing. Male fertilities had no significant relationship
with dbh, distance to maternal tree, and/or direction. Suggestions for
statistical analysis of the pollen distribution are offered.
Dyer, Rodney J., Department of Biology, University
of Missouri-St. Louis, Paternity analysis and gene flow in Northern
Red Oak (Quercus rubra L.)
Juan F. Fernandez-M., Department of Biology,
University of Missouri, St. Louis. Estimating optimal sample size for
genetic differentiation using analytical and bootstrap techniques.
Precision in the analysis of the distribution of genetic diversity and
estimation of gene flow rates among populations, is constrained by the
sampling design i.e., number of populations and number of individuals per
population. Few attempts have been made to analytically determine a sample
size large enough that will yield statistically significant estimates of
genetic differentiation or gene flow e.g., . Here, I use the methods proposed
by to estimate the optimal sample size per population when the total sample
size is held constant based on the premise of minimizing the variance of
Gst from known genetic data. Allozyme genetic data from five loci
(AAT-2, AAT-3, DIA-1, DIA-2, and MNR-2) from Sassafras albidum (Lauraceae)
from 36 subpopulations from the Missouri Ozarks, was analyzed using the
program HaploDiv (Petit 1995). Although the program is intended for haploid
data , it yields close results to a diploid procedure if the species is
outcrossed (Petit, pers. comm.). The original sample sizes were between
24 and 48 individuals per population.
Only the loci that showed a significant genetic differentiation (MNR-2
Gst = 0.3389, and DIA-2 Gst = 0.0991) were useful in estimating
the optimal sample size. The results indicate that 4 diploid individuals
for the MNR-2 locus, and 9 for the DIA-2 locus per population are enough
to detect population differentiation at those loci.
For the low differentiated loci (AAT-2, AAT-3 and DIA-1) a resample
analysis was performed simulating the 36 populations with a constant sample
size (n = 10, 20, ...100) per population to estimate empirically when the
bootstrap 95% confidence interval on Gst values approached the observed
value for the total data. The simulated samplings suggested: 1) that at
least 20 individuals per population are required for a 95% confidence interval
to overalap with the true mean Gst ; 2) that the estimated variance
stabilizes when sample size is greater than 30 individuals per population;
and 3) that the estimator that approaches the true value the better is
the Gst estimator proposed by Pons and Chaouche (1995). For a locus
by locus analysis, the least differntiated locus will determine the minimum
Assuncao, R. and C. M. Jacobi. 1996. Optimal sampling design for
studies of gene flow from a point using marker genes or marked individuals.
Evolution 50(2): 918-923.
Epperson, B. K. and T. Li. 1996. Measurement of genetic structure within
populations using Moran's spatial autocorrelation statistics. Proc. Natl.
Acad. Sci. USA 93: 10528-10532.
Petit, R.J. 1995. HaploDiv. A Pascal program for the Analysis of diversity
for haploid data.
Pons, O. and K. Chaouche. 1995. Estimation, variance and optimal sampling
of gene diversity II. Diploid locus. Theor. Appl. Genet. 91: 122-130.
Pons, O. and R. J. Petit. 1995. Estimation, variance and optimal sampling
of gene diversity I. Haploid locus. Theor. Appl. Genetics 90: 462-470.
Gilpin, Michael. Department of Biology, University
of California-San Diego. Gene Flow and selection under extinction/recolonization
dynamics for self incompatible plants.
The S-Allele for self-incompatability in plants has long been a subject
for theoretical analysis, since, through frequency dependence, it maintains
dozens of alleles in even small populations. Previous work has been based
on single patch models or on stepping-stone configurations with constant
population sizes. In collaboration with Josh Kohn (UCSD) and Adam Richman
(Montana State University), I'm developing java-based model that incorporates
local extinction of a patch followed by a colonization and founder event.
The model tracks alleles and genetic distance data, such as FST.
Metapopulation dynamics increase isolation with distance and reduce the
regional number of alleles.
The availability of molecular genetic markers coupled with advanced statistical
estimation procedures have significantly increased our ability to estimate
gene flow rates and other population parameters for many plant species.
The improved ability to accurately estimate gene flow into plant populations
allows us to predict the genetic consequences of small population size,
habitat fragmentation, and isolation distance. However, when gene flow
is estimated in conjunction with male reproductive success or effective
population sizes, some problems can arise. For example, when estimating
male reproductive success in populations that experience high rates of
gene flow, the assignment of progeny to certain pollen donors may be biased
towards individuals with multi locus genotypes that most closely approximate
gene frequencies in the immigrant donor population. Perhaps a more serious
problem is the observation that individual trees do not sample the pollen
pool at random as is assumed by most estimation procedures. There is considerable
evidence from the plant mating system literature that individual maternal
trees often receive genetically different pollen. This is probably also
true of pollen that immigrates into a population. Thus, a second generation
of gene flow estimation procedures are needed that can take into account
such heterogeneity in the immigrant pollen pool and use iterative procedures
to better estimate the immigrant pollen pool for individual trees as well
Hamrick, James L. Departments of Botany and
Genetics, University of Georgia, Athens, GA. Predicting the genetic
consequences of gene flow: problems and solutions.
Due to differences in their physical properties and in the vectors that
disperse them, pollen and seed movement may generate spatial patterns of
gene dispersion that differ in both continuous and discontinuous populations.
Studies of pollen flow have employed statistical genetic approaches that
fall into one of two categories; those that estimate rates of pollen flow
into discrete populations but do not provide estimates of male fertility
and pollen movement within populations and, conversely, those that infer
male fertilities but do not adjust these estimates for cryptic pollen flow
originating outside of the study population. Combining statistical approaches,
I will present a model that simultaneously estimates rates of total gene
flow and male fertilities adjusted for cryptic pollen gene flow from genotypic
data. In contrast to the problems of quantifying pollen dispersal, the
development and application of statistical models to estimate gene flow
via seed has been hampered by the limited availability of suitable maternally
inherited chloroplast and mitochondrial markers. As a solution to this
problem, I will present a general framework for estimating pollen and seed
components of gene flow from the observed distribution of genotypes at
biparentally inherited loci. The model much more rapidly generates direct
estimates of the levels of pollen flow received by individual maternal
plants and populations than does currently available methods. Moreover,
once a population level estimate of pollen flow has been obtained, nuclear
markers, such as allozymes, can be used to obtain direct estimates of seed
immigration from the multilocus genotypes of dispersed seeds and seedlings.
The application of these models to investigating pollen, seed, and gene
movement in continuous and spatially isolated populations will be discussed.
Nason, John. Dept. of Biological Sciences, University of Iowa, Iowa
City, IA 52242-1324. Measurement of gene flow through pollen and seed
in continuous and discontinuous populations.
The spatial dispersion of an organismal lineage from a single descendant
is a direct consequence of gene flow. Thus, an analysis of this process
can be similar to that used for direct estimates of gene flow from mark-and-recapture
data. Development of this approach as a method for estimating gene flow
requires genetic markers that delineate lineages of sufficiently recent
origin, and models that provide a framework for estimating dispersion parameters.
This approach has been applied to large scale patterns of animal mtDNA
variation, with encouraging results.
Neigel, Joseph E. Department of Biology, The
University of Southwestern Louisiana. Gene flow analysis based on spatial
dispersion of individual lineages.
It may seem inappropriate to investigate chloroplast DNA (cpDNA) or mitochondrial
DNA (mtDNA) to get insights of gene flow in plants. Indeed, the bulk of
gene exchanges is mediated by pollen, and cytoplasmic genomes are usually
maternally inherited. But seed flow may be significant in some species,
whereas cpDNA is paternally inherited in an important group of forest trees
(Gymnosperms). In general, inferring the relative importance of pollen
and seed flow seems important. Indeed, even if often less mobile than pollen
grains, seeds are the only vehicle to move to new environments ('The haploid
phase of environmental exploration cannot act further than what has already
been colonized by the diploid phase' to quote Harper). Also, for some species,
humans have moved seeds and plants around. Cytoplasmic markers may in such
cases be extremely useful to differentiate introduced from native material.
Indeed, genetic structure is often much stronger for maternally inherited
markers compared to biparentally (or paternally) inherited ones. In parentage
analyses, a set of highly polymorphic nuclear microsatellites may be used
to identify the parents of a given seedlings but the differentiation of
the mother from the father may be difficult. On the other hand, if combined
with cytoplasmic markers, a complete picture may be obtained. Clonally
evolving genomes are very appropriate for reconstructing phylogenies, an
information sometimes useful to consider in gene flow studies. Finally,
'interspecific gene flow' also called 'cytoplasmic captures' are reported
to be very frequent in plants. Actually, these expressions may be misleading,
since it is probably often the nuclear genome which moves over a static
maternal bedrock. Nevertheless, it remains true that one may often get
better insights of interspecific gene flow with cytoplasmic than with nuclear
Petit, Rémy J. INRA Forest genetics
and tree improvement laboratory, Bordeaux, France. Contribution of cytoplasmic
markers to studies of gene flow in plants.
Petit, Rémy J. INRA Forest genetics
and tree improvement laboratory, Bordeaux, France. Measuring genetic
differentiation with molecular markers to identify populations for conservation.
The purpose of this talk was to introduce some work done in
collaboration with Odile Pons (INRA, Jouy-en Josas) on the estimation of
genetic differentiation in various contexts. Among the questions studied
are the following: How to obtain confidence intervals for estimates of
genetic differentiation (GST)? How to optimize sampling in order to obtain
a better (more precise) estimate of differentiation? How to measure differentiation
while taking into account information on the nature of the alleles (NST
(sequence) or RST (microsatellite) data)? How to compare differentiation
for ordered versus unordered alleles? What does this difference mean? How
to get pairwise measures of differentiation? How to measure the differentiation
of one population from the rest ? Is a given population important to conserve
because it is variable or because it is distinct, or because of both? How
to measure that? How to compare measures of allelic richness? What do statements
such as: 10% of the diversity is distributed among populations' really
Scots pine can serve as a case study for considering many aspects of gene
flow. The reproductive biology of Scots pine is better known than that
of most other conifers (Sarvas 1962, Koski 1970). The distribution of quantitative
genetic variation of adaptive traits has been extensively studied, and
for many important traits the populations are highly differentiated (Mikola
1982, Karhu et al. 1996, Hurme et al. 1997, Hurme and Savolainen in prep).
The distribution of variation in molecular markers has been well characterized.
Until now, all markers, isozymes, RFLP, RAPD, microsatellites, have shown
very limited degrees of differentiation. Thus, so far we have not found
markers for those parts of the genome that are differentiated. At least
many northern conifers may share similar patterns of biology (Savolainen
and Kuittinen, in press). The basic findings of gene flow in Scots pine,
through direct measures by marking pollen, paternity analysis and indirect
genetic inference all suggest that gene flow through pollen is likely to
be extensive. The influence of timing of flowering in different populations
is in the direction of facilitating south to north gene flow. There is
strong selection for adaptation to local environmental conditions. The
results of the contrasting influences of migration and selection result
in these divergent patterns of differentiation discussed above. These results
can also be used for considering the consequences of fragmentation and
Savolainen,Outi. Department of Biology,
University of Oulu, Finland. Gene flow and local adaptation in Scots
For literature cited see:
Savolainen, O. and Hurme, P. 1997. Conifers from the cold. Pp. 43-62 in
Environmental stress, adaptation and evolution (R. Bijlsma and V. Loeschcke,
eds.). Birkhäuser Verlag.
Smouse1, Peter E. Sylvan R. Kaufman1,
and Elena R. Alvarez-Bullya2. 1Department of
Ecology, Evolution & Natural Resources and Center for Theoretical &
Applied Genetics, Cook College, Rutgers University; 2Centro
de Ecologia, Universidad Nacional Autonoma de Mexico. Use of parentage
analysis in the assessment of gene flow.
Much attention has been directed to the use of F-statistics (and similar
measures) for the indirect estimation of gene flow between populations.
While such approaches allow estimation from a crosscutting survey of a
single generation, they have their limitations. An alternative is to use
a two-generation approach, based on paternity analysis. There are many
different situations one can treat, given proper mendelian inheritance
of a set of genetic markers, but we will concentrate on the situation with
known mothers and offspring, coupled with candidate male (pollen donor)
populations of "well-estimated" genetic composition. This approach is a
simple extension of single-male analysis, not unlike a mixed stock (migrational)
fisheries analysis. We can also model the respective contributions of the
pollen donor populations, in terms of interesting features or in terms
of their distance from the recipient (female) population. We will illustrate
with a tropical pioneer tree species, Cecropia obtusifolia,
for which the appropriate data provide a telling demonstration of patterned
gene flow. Parentage analysis, while it requires additional information,
would appear to be more powerful than F-statistics analysis, in elucidating
Until recently, most spatial autocorrelation analysis of genetic data has
been conducted with univariate techniques. Each allele at each locus has
been analyzed separately, yielding many different analyses, usually treated
(incorrectly) as independent replicates of the process, thought to be (broadly)
demographic and spatial. With the recent interest in micro satellite loci,
with myriad alleles, this univariate strategy is hopelessly cumbersome.
Various workers, notably such people as Sokal, Barbujani, and Epperson,
have begun to switch over to a multiple-character treatment. We show that
by switching to genetic distance techniques, we can produce a completely
general multivariate treatment, can use multiple-alleles, multiple-loci,
weighted or unweighted information, and so on. We then illustrate new non-parametric
testing procedures on the entire autocorrelation profile. We illustrate
with published allozyme data on the Australian orchid, Caledenia tentaculata.
The new analysis is easily tractable and very powerful, reliably detecting
pattern when it is there, and demonstrating its absence when it is not.
Smouse1, Peter E. and Rod Peakall2. 1Department
of Ecology, Evolution & Natural Resources and Center for Theoretical
& Applied Genetics, Cook College, Rutgers University; 2
Dept. Botany and Zoology, Australian National University. Micro-spatial
autocorrelation analysis for multiple-locus, multi-allelic genetic data
Gene flow among populations can be studied using an evolutionary time frame
or an on going time frame. Evolutionary questions concerning the role of
gene flow in genetic diversity, population differentiation, species identity,
and speciation emphasize the evolutionary time scale. However, conservation
biological questions concerning the role of gene flow in future patterns
must rely on estimates of on-going gene flow under current landscape conditions.
My question, and to some extent the main question of the workshop, is to
evaluate the extent to which gene flow models developed to answer evolutionary
questions in an evolutionary framework can be used to estimate on-going
gene flow. In this introductory talk, I will briefly review categories
of gene flow models--some of which will be developed in more detail by
workshop participants. Then, I will present evidence of ecological and
landscape influences on patterns of gene flow. My talk will end with a
list of questions about which models are most appropriate for the estimation
of on-going gene flow and whether new models should be developed which
utilize metapopulation approaches or the spatially explicit models.
Sork, Victoria L. Sabbatical Research Fellow, NCEAS, University
of California-Santa Barbara and Department of Biology, University of Missouri-St.
Louis. Introduction to workshop: studying gene flow on an ecological
The ecological impacts of habitat fragmentation due to human-induced landscape
modifications are of serious concern to conservation biologists. Such fragmentation
may reduce the exchange of individuals between populations, resulting in
isolated patches made vulnerable to extinction due to environmental stochasticity
and/or inbreeding depression. Unfortunately, studies of species at risk
are typically plagued by logistical problems, making it difficult to collect
the detailed but large-scale demographic data necessary to address this
issue. Conservation biologists have thus increasingly been turning to molecular
genetics to study threatened populations. One goal of these studies is
to use current patterns of genetic structure to elucidate underlying population
processes, in particular, those dealing with migration dynamics. However,
this approach has some serious limitations. Importantly, because many different
population processes lead to similar patterns of genetic structure, particular
processes are difficult to infer from pattern. In addition, the population
genetics models most commonly applied to these systems are based on equilibrium
conditions not typically found in nature, and are framed in abstract terms
that are difficult to link to biological data. Finally, influences of current
and historical conditions are not easily separated. I will present an individual-based
simulation model (based on pocket gopher biology) that incorporates genetics
and demography to explore scenarios of change in genetic structure as a
result of habitat fragmentation. In particular, I will use the simulation
to illustrate limitations in using models based on F-statistics as a generic
tool (particularly for management applications), and will suggest possible
future directions for applying this modeling approach to interpret both
spatial and temporal patterns of genetic variation.
Steinberg, Eleanor L University of Washington. Using and individual-based,
spatially-explicit simulation model to evaluate the power of FST
as an indicator of recent habitat fragmentation.
Steinberg, E.K. and C.E. Jordan. Using molecular genetics to learn about
the ecology of threatened species: the allure and illusion of measuring
genetic structure in natural populations. Pp. 440-460 in Conservation Biology
for the Coming Decade (P. Fiedler and P. Kareiva eds.). Chapman and Hall,