Types of GEM
Blackwell Publishing Ltd Congruent population structure inferred
from dispersal behaviour and intensive genetic surveys of the
threatened Florida scrub-jay (Aphelocoma coerulescens)
This example illustrates how genetic information, coupled with Bayesian
cluster analysis, can be used to identify distinct genetic groups
within a species. The Florida scrub-jay (Aphelocoma coerulescens)
|The Florida scrub-jay is endemic to Florida, and classified
as a Threatened species there.
a non-migratory bird endemic to Florida that is federally listed
as a threatened species. The species is restricted to early successional,
fire-maintained xeric oak scrub (Woolfenden
and Fitzpatrick 1984) that has declined substantially due to
land-type conversion and suppression of fire. As a result, scrub-jay
populations are believed to be at approximately 3% of historical
levels (Pranty 1996)
and are continuing to decline. Recovery of the species must be based
on habitat restoration as well as on knowledge of the species' dispersal
capabilities and genetic structure.
For this study, Coulon et al. (2008) collected blood samples
from the brachial vein of one or both wings on 1028 scrub-jays
collected widely across Florida. They genotyped the individuals
using PCR analysis at 20 microsatellite loci that were previously
developed for the Florida scrub-jay.
Following this, they delineated 8 - 13 genetically distinct groups
using Bayesian clustering algorithms from two different programs,
et al. 2000) and GENELAND (Guillot
et al. 2005). Further analysis suggested 10 genetically distinct
groups across the range of the species.
|Study area showing relevant landscape characteristics [from
Coulon et al. 2008]
Prior to the study by Coulon et al. (2008), Stith et al. (1996)
had delineated 42 meta-populations of Florida scrub-jay based
on dispersal probabilities. Their model was based on observed
dispersal distances, coupled with knowledge about land-use types
that scrub-jays use or avoid during dispersal.
One of the fundamental questions asked by Coulon et al. (2008)
was whether these dispersal-based meta-populations showed any
relationship to the groups that they identified through genetic
Nearly all of the meta-populations defined by Stith et al. (1996)
are embedded within the genetic groups defined by Couloun et al.
(2008), and no metapopulation is genetically subdivided. The close
congruence between dispersal-defined metapopulations and genetically-distinct
groups suggests genuine genetic boundaries.
|Polygons are minimum convex polygons (MCP) delineating the
area shared by individuals belonging to the same genetic group
as determined with GENELAND and color coded accordingly. [from
Coulon et al. 2008]
As noted by Koenig and Walters (2008)
this study represents a substantial accomplishment by identifying
nearly identical patterns with two distinct methods (genetic and
demographic surveys). Population genetic structure obtained via
these methods is of high enough quality to inform conservation
efforts and provides a new tool in the management of a threatened
species over large areas.
|Model of population structure in Columbia spotted
frogs. Large circles represent low elevation populations with
large effective population sizes. Arrow thickness denotes
the relative level of geneflow among populations.
Animal dispersal and subsequent geneflow among
populations may be affected by a multitude of landscape features.
Highways, rivers, and mountains are just a few factors that influence
how animals move. Significant features may even lead to isolation,
hence impacting evolutionary trajectories.
Funk et al. (2005) examined genetic variation in Columbia spotted
frogs (Rana luteiventris) from 28 breeding ponds in western
Montana and Idaho, USA, in order to investigate the effects of
landscape structure on patterns of gene flow. Amphibians are thought
to have limited ability to disperse and may therefore be especially
vulnerable to isolation. Specifically, they wanted to look at
the influence of elevational changes and topographical features
(i.e., ridges) on geneflow, and whether ponds equate to a randomly
Using six microsatellites, the authors used pairwise Fst to
qualitatively assess the effects of topographic features on genetic
divergence. They used program ARLEQUIN version 2.001 (Schneider
et al. 2000) to examine broad geographical subdivisions using
analysis of molecular variance with Fst (amova; Excoffier
et al. 1992). They then used Mantel tests (Mantel
1967) and partial Mantel tests (Smouse
et al. 1986) to examine the effect of straight-line distance,
river distance, elevational differences, and mountain ridges.
Their results suggested that gene flow is restricted by ridges
and elevation in this species. However, they found that frog populations
generally included more than a single pond except for very isolated
ponds. Their results also suggested surprisingly high levels of
gene flow among ponds separated by large distances at low elevations.
|Green circles contain animals grouped into populations defined
by both exact tests and a clustering algorithm (Pritchard
et al. 2000). Blue circles are by exact tests only, yellow
circles by clustering algorithm only.
Genetic variation within populations was strongly negatively
correlated with elevation, suggesting effective population sizes
are much smaller at high elevation than at low elevation.
Finally, the authors concluded that low elevation populations
may act as important sources of immigrants for high elevation
populations. As such, extinction of low elevation populations
may have direct impacts on the persistence of high elevation popualations
as well by isolating them as effective islands.
Given that lower elevation areas are typically the first to be
degraded, isolated, and infested with exotic species, such a scenario
is far too likely and has been observed already in multiple frog