48th Annual North American Symposium on Bat Research, 24-27 October 2018 Puerto Vallarta, Jalisco

1. Using Genetics to Explain Acoustic
Divergence in the Pteronotus
parnellii Species Complex
Liliana M. Dávalos, Winston C. Lancaster, Miguel S. Núñez-Novas,
Yolanda M. León, Bonnie Lei, Jon Flanders, and Amy L. Russell

2. Pteronotus cf. parnellii
CF echolocation with Doppler shift compensation in
the Neotropics
Puerto Rico Hispaniola

3. Why divergence? (in allopatry)
• Null hypothesis
• Genetic drift (e.g., Puechmaille
et al. 2011)
• Selection
• Habitat physical features (e.g.,
Odendaal et al. 2014, Guillén et
al. 2000)
• Acoustic environment (e.g.,
Gillam & McCracken 2007)
• Other species (Kingston et al.
2001)
• Prey (Kingston & Rossiter 2004)
• Sexual selection (Mutumi et al.
2016)
• Cultural drift (Yoshino et al.
2008)

4. STATISTICAL IXTERPRETATION OF POPULATION STRUC
PROGRESS OF FIXATION IN POPULATIONS OF EIGHT
I ef, 7
44,
...MAX. A
COU
HALF-S
.80
.20
F
1.00 1---------=======------,
.60
.40
504010
00'=" .,-::-__---,-..,....-__...........,.. ---1
FIG. 7.
If genetic drift is the driver
• Quantitative
divergence ~ genetic
divergence expected
by drift
• Quantitative
divergence ~ FST
Wright 1965 Evolution
FST

6. Where could
we find such
estimates?
In the genetics data
Hey & Nielsen 2007 PNAS

7. 0
1
2
3
4
0 200 400 600
Effective Population Size (thousands of individuals)
JointPosteriorDensity
Puerto Rico
Hispaniola
A
0.0
0.2
0.4
0 1000
D
Dávalos et al. 2018 Heredity

8. 0.0
0.5
1.0
1.5
0 2 4 6
Effective Number of Migrants (Nm)
JointPosteriorDensity
Migration into
Hispaniola
Supplementary Figure 1
Puerto Rico
Dávalos et al. 2018 Heredity

9. F
ns from coalescent
mated global G′ST
us sequence data,
of subpopulations
to obtain a dis-
package mmod v.
direct comparison
nd previous meth-
ithin the genome.
n the R statistical
mmary statistics of
ions for call fre-
ngth phenotypes.
n populations were
uschke 2013).
cσB þ 2h2σW h2 σB þ 2σW
in which c/h2
is the additive genetic contribution to
proportion of the between-population variance. In m
empirical cases the c/h2
ratio is unknown, but it determi
how robust the PST approximation to the QST is. If the
exceeds the neutral expectation —the FST—at c = h2
, the
will also exceed this expectation when c > h2
. Howe
when c < h2
, there is a limit to the extent to which the
reflects the QST exceeding the neutral expectation. T
critical value is estimated by calculating c / h2
critical (Eq
for the lower 5% tail of PST and the upper 5% tail of
distributions (Brommer 2011):
c
h2critical
¼
2σ2
W0:05FST 0:95
σ2
B 0:05ð1 À FST 0:95Þ
¼
ð1 À PST 0:05ÞFST 0:95
PST 0:05ð1 À FST 0:95Þ
:
When c / h2
critical is low, there is a large range of c / h2
o
tes. In addition, by estimating directional
sing a non-equilibrium coalescent-based
the assumptions of equal Ne and m for all
well as the condition of mutation-drift-
rium for the entire system.
obtaining FST distributions from coalescent
tions of Nm, we estimated global G′ST
ST) from the multi-locus sequence data,
ction for finite number of subpopulations
and then bootstrapped to obtain a dis-
that value using the R package mmod v.
12). This provided a direct comparison
escent-based method and previous meth-
zing neutral variation within the genome.
ait comparisons
lyses were conducted in the R statistical
We estimated the summary statistics of
Puerto Rican populations for call fre-
(Brommer 2011). In this case, the varianc
be scaled by a constant c and the heritabilit
the estimate of phenotypic differentiation,
PST ¼
cσ2
B
cσ2
B þ 2h2σ2
W
¼
c
h2 σ2
B
c
h2 σ2
B þ 2σ2
W
;
in which c/h2
is the additive genetic con
proportion of the between-population va
empirical cases the c/h2
ratio is unknown,
how robust the PST approximation to the Q
exceeds the neutral expectation —the FST—
will also exceed this expectation when c
when c < h2
, there is a limit to the extent
reflects the QST exceeding the neutral e
critical value is estimated by calculating c
for the lower 5% tail of PST and the uppe
distributions (Brommer 2011):
c
¼
2σ2
W0:05FST 0:95
¼
ð1 À PST 0
A B
Constant−frequencyecholocation(kHz) ●
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60.0
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67.5
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Hispaniola Puerto Rico
Island
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48 50
Forearm le
Dávalos et al. 2018 Heredity
Lande 1992 Evolution
Sex
Female
Male
Figure 2
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48 50 52 54
Forearm length (mm) C

10. Supplementary Figure 3
Female Puerto Rico Male Puerto Rico
Female Hispaniola Male Hispaniola
0.25 0.50 0.75 1.00 0.25 0.50 0.75 1.00
0.4 0.6 0.8 0.5 0.7 0.9 1.1
Female Puerto Rico Male Puerto Rico
Female Hispaniola Male Hispaniola
0.3 0.6 0.9 1.2 1.5 0.5 1.0 1.5
0.6 0.8 1.0 1.2 0.4 0.6 0.8 1.0 1.2
Standard deviation
Estimate from simulations
Estimate from data
Dávalos et al. 2018 Heredity
With sex by island interaction Without sex by island interaction

11. BodymassEcholocationfrequencyForearmlength0.00 0.25 0.50 0.75 1.00
0
5
10
15
0
5
10
15
0
5
10
15
FST or PST
Density
FST Hispaniola
FST Puerto Rico
PST

12. Sex
Female
Male
Figure 2
A B
Constant−frequencyecholocation(kHz)
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Hispaniola Puerto Rico
Island
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Forearm length (mm) C
Dávalos et al. 2018 Heredity

13. What is left?
• Null hypothesis
• Genetic drift (e.g., Puechmaille
et al. 2011)
• Selection
• Habitat physical features (e.g.,
Odendaal et al. 2014, Guillén et
al. 2000)
• Acoustic environment (e.g.,
Gillam & McCracken 2007)
• Other species (Kingston et al.
2001)
• Prey (Kingston & Rossiter 2004)
• Sexual selection (Mutumi et al.
2016)
• Cultural drift (Yoshino et al.
2008)

14. Thanks!
• Dávalos lab
• Omar Warsi
• Laurel Yohe
• Puerto Rico
• Armando Rodríguez
• Ashley Rolfe
• Jean Sandoval
• Dominican Republic
• Grupo Jaragua
• Sixto Incháustegui