Appendix S1: Abundance Estimates Detailed Methods and Results
Estimating population sizes of U. inornata is difficult because these lizards are
cryptic and spend most of the time buried in the sand. Barrows developed a method to
approximate lizard density by counting tracks on soft sand dune habitat (Barrows and
Allen 2007). Detailed techniques used to survey multiple species based on tracks are found
in Barrows and Allen 2007, but, briefly, when U. inornata wander over the dunes, they
leave footprints in the sand that are readily distinguishable from all other species. In
addition, it is straightforward to differentiate footprints left by yearlings and adults.
Because strong winds blow in the Coachella Valley most evenings, the sand is wiped clean
each day, thus eliminating the possibility of counting the same track over multiple survey
days. This technique makes it possible to survey relatively large portions of the extant sites
in a reasonable amount of time.
To estimate lizard abundance within the five main sites used for genetic analysis, we
first delineated homogeneous habitat types within each location. At Train Station, Willow
Hole, and Windy Point we identified only continuous fine aeolian sand dune habitat (i.e.,
high quality habitat). At Whitewater, however, the habitat consisted of relatively small
dune patches interspersed with hard packed sand (i.e., low quality habitat). At Thousand
Palms Preserve, we identified both types of habitat. The total areas of each type of
continuous habitat was determined by studying high-resolution satellite images of the plot,
drawing a polygon around the habitat, verifying in the field that the habitat designation
was accurate, and calculating the area of each polygon with the PBSmapping package in
program R v3.0.2 (R Core Team 2013). We randomly placed transects that were separated
by at least 40 m and ran roughly north-south within each habitat type at each site. In total,
we place 34 transects in high-quality habitat and 33 in low quality habitat at Thousand
Palms Preserve, 16 at Willow Hole, 12 at Whitewater, 9 at Windy Point, and 8 at Train
Station. Most transects were 100 x 10 m, but in cases when the width of continuous habitat
was less than 100 m, transect length was shortened to traverse its extent. Surveys were
conducted in the morning when lizards were active (i.e., when the temperature 1 cm above
the ground was between 35 and 43°C). To ensure that the same lizard did not cross
multiple transects we followed each set of tracks until they terminated even if the
footprints left the transect area. Each transect was surveyed six times between May and
September 2008. We determined mean lizard abundance from each transect among the six
surveys and the density (no. lizards/ha) of lizards across all transects within a site (Table
1). We then estimated total abundance for each site by multiplying lizard density (no. ha-1)
by the area of habitat in that site (Table 1). Because two types of habitat were found in
Thousand Palms Preserve, we estimated separately total abundance in each habitat type
and added together these estimates to obtain a total estimate for this site. In addition, we
1
provided separate estimates for yearling and adult lizards when yearlings were present
(yearlings began hatching in early July).
Although estimating lizard abundance through tracking is practical and efficient, it is
ultimately an indirect technique. To help validate track-based abundance estimates, we
conducted more labor-intensive mark-recapture at Windy Point, Train Station, Willow Hole
and South Thousand Palms Preserve concomitant with tracking and tissue sample
collection. We selected locations of mark-recapture plots within high-quality habitat and
randomly placed transects for track surveys within each plot. Plot locations were
constrained by land access and avoidance of areas where long-term track-based surveys
were ongoing (Barrows and Allen 2007). At Windy Point we surveyed 0.97 ha of the 10.55
ha of active dune. Within South Thousand Palms Preserve we randomly selected two 100 x
100 m plots that represented 1.2 % of the high-quality, active dune habitat in this area.
There were 7.3 ha of active dune at Willow Hole, and we surveyed 0.94 ha and 2.86 ha plots
in this region. At Train Station we surveyed 2.21 ha of active dune that was adjacent to
another 3.55 ha of privately owned dune habitat. Mark-recapture sampling took place from
June through September, 2008. We visited each plot between seven and nine times.
To survey a site, observers walked slowly through a plot. Lizards were captured
with a noose or by hand. We recorded snout to vent (SV) length and weight. We then placed
a unique number on the back of a lizard with a permanent marker and clipped one or two
of the front toenails in unique combination for each individual. In addition, we clipped the
terminal approximately 3 mm section of the tail to provide tissue for genetic analysis. To
minimize handling stress, we did not attempt to recapture an individual following initial
marking if we observed definitively the mark on that individual. We recorded the spatial
location in UTM (NAD83) where an individual was first observed. Once processed the
lizard was returned to the point of capture.
We only conducted surveys if two conditions were met that greatly influenced
detection probability in a given day. First, as with track surveys, we began mark-recapture
surveys in the morning shortly after the minimum temperature for lizard activity (35°C)
was reached and concluded when ground temperature surpassed 45 °C. Second, we
recorded wind speed at the beginning and end of each survey with a Kestrel 1000 wind
meter and did not survey if wind speed was in excess of 10 knots.
We used Huggins closed capture models with heterogeneity (Huggins 1989, 1991)
as implemented by Program MARK (White and Burnham 1999) to estimate abundance
[(N(plot + age)] for yearling and adult lizards from the six mark-recapture plots. This
approach evaluates the efficacy of models that account for capture probability (p) and finite
heterogeneity [π; i.e., multiple groups (in this case, two groups) exist with innately
different capture probabilities]. We tested the plausibility of 16 a priori models (Table S32
2) using Akaike Information Criteria adjusted for small sample size (AICc). The models did
[π(.)] and did not include two groups with overall different detection probabilities. In
addition, capture probability was modeled to be affected by various additive effects of
lizard age (age; yearling or adult), site (site; Windy Point, Train Station, Willow Hole, South
Thousand Palms Preserve), and whether or not recapture probability differed from initial
capture probability (c).
AICc provided strong support for the most complex model that included
heterogeneous capture probabilities among two groups of lizard as well as influence of
lizard age initial capture, and site on capture probability (Table S3-3). The only other
model to receive even moderate support included each of these variables with the
exception of lizard age (Table 3). All models with heterogeneity outperformed those
without this parameter (Table 3).
There was a highly significant, positive correlation between density estimates based
on mark-recapture and tracking surveys within the mark-recapture plots (Fig. 1, Tables 1,
4; adjusted R2 = 0.75, p = 0.0035). Although the intercept did not differ from zero, the slope
was higher than 1 (slope=1.76, standard error=0.38), indicating that estimates from
tracking surveys were higher than mark-recapture surveys. However, this bias seemed to
be driven by yearlings as the ratio between tracking and mark-recapture estimates
averaged 2.70 for yearlings but was only 1.01 for adults. Future work should evaluate the
potential reasons for the discrepancy in yearling estimates, but since we focus on adults for
the purpose of comparing abundance to effective population size, we are confident that
there is not an inherent bias between the two sampling methods.
Total adult abundance estimates among sites differed by two orders of magnitude.
The largest population was in South Thousand Palms Preserve with a combined 5249
lizards in the low and high quality habitat (Table 1). By contrast, we estimated that only 36
lizards were found at Train Station (Table 1). Although densities were similar between
Train Station and Whitewater (6 lizards ha-1), there was much more habitat at Whitewater
and thus we estimated that 948 lizards were found at this site. Adult densities were
relatively high at Windy Point and Willow Hole, but the discrepancy in habitat area resulted
in an estimate of 2583 at Windy Point but only 122 at Willow Hole.
3
Figure 1. Comparison of density estimates from tracking and mark-recapture surveys.
Circles represent plots from Thousand Palms Preserve, triangles from Windy Point,
squares from Train Station, and plus signs from Willow Hole. Red points are for adults and
blue for yearlings. The blue line was generated by simple linear regression and the shaded
area is one standard error around the line.
4
Tables
Table 1. Adult abundance estimates based on 2008 track surveys.
Site
Thousand Palms Preserve (high quality
habitat)
Thousand Palms Preserve (low quality
habitat)
Density
(no./ha)
Total amount of
habitat per site (ha)
Abundance per
site
27
163
4397
2
426
852
Willow Hole
17
7
122
Train Station
6
6
36
Whitewater
6
158
948
Windy Point
21
123
2583
5
Table 2. Candidate models for mark-recapture surveys.
No.
Model
Description; Detection probability affected by:
1
{p(.)}
none of the measured variables
2
{p(c)}
initial capture (subsequent differ from initial capture probability)
3
{p(age)}
lizard age (yearling vs. adult)
4
{p(site)}
site location (Windy Point, Train Station, Willow Hole, South Coachella Valley)
5
{p(c+site)}
initial capture and plot location
6
{p(c+age)}
plot location and lizard age
7
{p(site+age)}
plot location and lizard age
8
{p(c+site+age)}
initial capture, location, and age
9
{π(.)p(.)}
heterogeneity: two groups exist that are relatively easy and hard to capture
10
{π(.)p(c)}
initial capture; heterogeneity
11
{π(.)p(age)}
whether a lizard is a yearling or adult; heterogeneity
12
{π(.)p(site)}
site location; heterogeneity
13
{π(.)p(c+age)}
initial capture and age; two groups that are relatively easy and hard to capture
14
{π(.)p(site+age)}
location and lizard age; heterogeneity
15
{π(.)p(c+site)}
initial capture and location; heterogeneity
16
{π(.)p(c+site+age)}
initial capture, location, lizard age; heterogeneity
6
Table 3. Mark-recapture model selection results ranked by order of plausibility.
No.
Model
AICc
Delta
AICc
AICc
Weights
Model
Likelihood
No.
Parameters
16
{π(.)p(c+site+age)}
747.1
0
0.82
1
17
15
{π(.)p(c+site)}
750.2
3.09
0.18
0.21
16
14
{π(.)p(site+age)}
762.3
15.15
0.0004
0.0005
16
12
{π(.)p(site)}
764.8
17.72
0.0001
0.0001
15
10
{π(.)p(c)}
769.4
22.30
0.0000
0
13
13
{π(.)p(c+age)}
769.6
22.51
0.0000
0
14
11
{π(.)p(age)}
778.7
31.56
0
0
13
9
{π(.)p(.)}
778.9
31.77
0
0
12
8
{p(c+site+age)}
2593.1
1846.01
0
0
15
5
{p(c+site)}
2608.7
1861.61
0
0
14
7
{p(site+age)}
2621.0
1873.87
0
0
14
4
{p(site)}
2631.0
1883.85
0
0
13
6
{p(c+age)}
2666.4
1919.30
0
0
12
3
{p(age)}
2679.0
1931.84
0
0
11
2
{p(c)}
2703.1
1955.97
0
0
11
1
{p(.)}
2710.1
1963.03
0
0
10
7
Table 4. Mark-recapture abundance and density estimates from each plot and age group.
Group
Site
Age
Abundance
(No. plot-1)
SE
Lower
95% CI
Upper
95% CI
Density
(No. ha-1)
Lower
95% CI
Upper
95% CI
1
Thousand Palms Preserve
yearling
33.85
7.51
19.12
48.57
33.85
19.12
48.57
2
Thousand Palms Preserve
adult
20.44
6.71
7.29
33.60
20.44
7.29
33.60
3
Train Station
yearling
23.99
3.12
17.87
30.10
10.84
8.07
13.06
4
Train Station
adult
17.02
3.66
9.85
24.20
7.69
4.45
10.93
5
Willow Hole
yearling
22.82
2.32
18.27
27.38
24.28
19.43
29.13
6
Willow Hole
adult
8.40
1.89
4.70
12.09
8.93
5.00
12.87
7
North Willow Hole
adult
9.95
2.65
4.76
15.14
3.48
1.66
5.29
8
Windy Point
yearling
71.82
11.09
50.09
93.56
74.04
51.64
96.45
9
Windy Point
adult
7.69
3.39
1.05
14.34
7.93
1.08
14.78
Table 5. Mark-recapture abundance estimates extrapolated to each site.
Site
Total adults per
site
Lower
95%
CI
Upper
95%
CI
Thousand Palms Preserve
(high quality habitat only)
3332
1188
5477
Train Station
46
27
66
Willow Hole
63
35
90
Windy Point
975
133
1818
8
Additional Literature Cited
Huggins RM 1989. On the statistical analysis of capture experiments. Biometrika 76:133140.
Huggins RM 1991. Some practical aspects of a conditional likelihood approach to capture
experiments. Biometrics 47:725-732.
R Core Team (2013). R: A language and environment for statistical computing. R
foundation for Statistical Computing, Vienna, Austria. URL http://www.Rproject.org/.
Schnute JT, Boers N, Haigh R, Grandin C, Johnson A, Wessel P and Antonio F 2014.
PBSmapping: Mapping Fisheries Data and Spatial Analysis Tools. R package version
2.67.60. http://CRAN.R-project.org/package=PBSmapping
White GC and Burnham KP 1999. Program MARK: survival estimation from populations of
marked animals. Bird Study 46 Supplement: 120-138.
9
Table S1: Historical parameters and priors used for the three demographic scenarios that were modeled in the DIYABC
analyses (refer to Fig. 3). We simulated 4 x 106 datasets based on models describing each of the three scenarios that were
tested.
Parameter
Ne
Ne1a
Ne 1b
Ne1c
Ne 1d
Ne1e
t1
t2
t3
db1
db2
Prior
uniform
uniform
uniform
uniform
uniform
uniform
uniform
uniform
uniform
uniform
uniform
Range
10 - 5000
10 - 5000
5000 - 10,000
10 - 5000
5000 - 10,000
10 - 5000
1 - 5.0
9 -29.0
31 - 10,000
1 - 5.0
1- 10.0
Conditions
N1a < N1b
N1c < N1d
N1e = Ne
t3 > t2
-
10
Table S2: Microsatellite loci developed for U. inornata and used in this study.
Locus
Repeat
motif
Size range
(bp)
Forward Primer
Reverse Primer
2L
2M
PKLN*
2Q
2O
2S
DI_VQ1
3B
TRI4H
TRI489
TETZJ
TETQY
TET_KL
TG
TC
CA
GT
TG
TG
CA
AAC
CCA
ATT
CTGG
CAAA
AATT
135 - 151
228 - 244
180 - 186
174 - 194
228 - 248
147 - 153
250 - 268
161 - 173
227 - 248
253 - 298
324 - 365
194 - 218
142 - 158
GTG GGG AGG AAT GAG GAA G
GGG CAA CGA GTT CAA GAT GT
GTA CCT TGT GAC TGC AGT GCT
GGC ATG TAC AAA AGC ACC AG
GGG AGT AGC TGA TTG GAT GG
TTG AGA CAC AGG AGG CAG AAG
CCA TGG TGT TCT CCT GGA TT
TTG GCC CAA CTT TCT AAT CTG
ATG GCT AGG GCA AAT CTC CT
CCT GGA AAG CCT CCT TCT CT
TGC TAA AAG GTC TGG AAA CCA
TGA AAC CCA CTG GTG ACC TT
CCC TTT TGT TTT ACC TTC TCT TCT T
GGT TTG GCG TAC ACT TG
CTT CAG CAT GAT TGC GTG AC
CCC TTC CCT GTC ATA GAC CA
ATG GGA GGG TTA CTG GAG GT
CCA CCT GCT GCT CCA TAA CT
AAT GAA TTA GCT TGC CTG CTG
CAT CCC ACG CCA TCT TTT AT
GGC TTG CCT TAG GAT CAC TG
TTT GGA CAT TTG ATG GCT GA
CTT TCC CCA TCC ACT GAA AA
TTT CCA CCC CTT GTC TTC TG
TTC TTA CAG GTG CCC AGG AC
CTC CAG CTG GGT ATT TGG AA
Number
of
alleles
10
10
4
10
11
11
9
4
6
16
9
6
5
HO
0.743
0.839
0.353
0.679
0.766
0.803
0.515
0.226
0.449
0.294
0.033
0.540
0.801
*Locus previously developed (see Zamudio & Sinervo 2000 PNAS 97:14427-14432).
We divided these loci into 4 groups and performed multiplex PCRs (annealing temperature at 58 - 60° Celsius ) using a Qiagen
Multiplex PCR Kit®, and following recommended PCR conditions: 10 L reactions contained 5 L of Qiagen multiplex PCR
Master Mix, 1 L primer mix (containing 2 M of each primer), 1 L Q-solution and 2 L of RNase-free water.
11
Table S3: Structure results across 10 iterations of sample sets where the 2008 sample sizes were randomly reduced to the
1996 sample sizes at each site. For each sample set, we assumed the highest value of ∆ K corresponded to the optimal number
of clusters.
Sample
Set
Set 1
Set 2
Set 3
Set 4
Set 5
Set 6
Set 7
Set 8
Set 9
Set 10
K
Reps
3
4
3
4
3
3
4
3
4
3
10
10
10
10
10
10
10
10
10
10
Mean
LnP(K)
-1654.2
-1629.5
-1648.8
-1705.2
-1727.9
-1678.6
-1671.3
-1650.6
-1664.8
-1643.9
Stdev
LnP(K)
9.6
23.9
29.9
23.5
33.4
18.1
15.6
28.1
17.7
2.4
Delta K
3.6
1.0
1.7
0.6
0.9
1.1
0.6
1.2
2.2
14.0
12
Table S4: Distributions of global and pairwise FST (estimated as θ [Weir & Cockerham, 1984]) and associated p-values for
population differentiation from 1000 random draws of 2008 samples reduced to sample sizes that were equal to 1996.
FST
P-value
Mean
Median
Std
Dev
Min
Max
Upper
95
%tile
Lower
95
%tile
Mean
Global (All Populations)
0.0383
0.0380
0.0084
0.0162
0.0700
0.0525
0.0250
0.0013
Windy Point-Whitewater
0.0762
0.0756
0.0180
0.0275
0.1357
0.1063
0.0471
0.0107
Windy Point -Willow Hole
0.0506
0.0484
0.0214
-0.0087
0.1255
0.0879
0.0169
0.0381
Windy Point-S. Th. Palms
0.0452
0.0443
0.0154
0.0028
0.0954
0.0720
0.0221
Whitewater-Willow Hole
0.0148
0.0147
0.0116
-0.0138
0.0582
0.0343
-0.0037
Whitewater-S. Th. Palms
0.0367
0.0356
0.0119
0.0057
0.0782
0.0573
Willow Hole-S. Th. Palms
0.0151
0.0142
0.0126
-0.0168
0.0559
0.0364
Median
Std
Dev
Min
Max
Upper
95
%tile
Lower
95
%tile
0.0011
0.0000
0.0170
0.0020
0.0000
0.0099
0.0041
0.0099
0.0594
0.0198
0.0099
0.0099
0.0634
0.0099
0.6832
0.1634
0.0099
0.0220
0.0099
0.0330
0.0099
0.4158
0.0693
0.0099
0.1915
0.1287
0.1823
0.0099
0.9604
0.5842
0.0198
0.0186
0.0203
0.0099
0.0226
0.0099
0.2871
0.0594
0.0099
-0.0039
0.1940
0.1287
0.1934
0.0099
0.9604
0.6040
0.0099
13
Table S5: Demographic models, model confidence, and the posterior estimates of Ne for each site. Data show the mean,
quantiles (0.025-0.975), and Type I and Type II error estimates for each scenario. For Type I (probability that the scenario was
rejected even though it was the 'true' scenario) and Type II (probability of favoring the scenario when it is not the 'true'
scenario) error estimates for direct and logistic approaches, respectively. The confidence was assessed using 500 simulated
data sets (number of times the scenario had the highest posterior probability: direct, logistic).
Site
Windy Point
Whitewater
Willow Hole
South Thousand Palms
Best-fit
Scenario
Scenario 1
Scenario 1
None
Scenario 1
Ne estimate
(mean, mode)
312, 45.4
1810, 39.5
1490, 48.3
Quantiles
(0.025 0.975)
22.1 - 2450
21.9 - 4870
38.1 - 4730
Type I error
(direct, logistic)
0.19, 0.17
0.15, 0.14
0.22, 0.20
Type II error
(direct, logistic)
0.14, 0.15
0.12, 0.13
0.19, 0.21
14
Table S6: P-values from 1-sided signed-rank tests for heterozygote excess performed in BOTTLENECK under a range of different
mutational models. Tests were performed for all sites sampled with 5 or more individuals. Whitewater 2008 and North
Thousand Palms 1996 were significant for heterozygote excess under the IAM and a limited range of TPM.
TPM
Sampling Site & Year
IAM
16,20
16, 40
16, 60
16, 80
4, 20
4, 40
4, 60
4, 80
SMM
Windy Point 1996
0.232
0.350
0.350
0.449
0.449
0.350
0.618
0.449
0.449
0.517
Windy Point 2008
0.289
0.449
0.681
0.740
0.926
0.740
0.817
0.926
0.959
0.990
Train Station 2008
0.160
0.483
0.584
0.768
0.897
0.681
0.793
0.897
0.949
0.994
Whitewater 1996
0.551
0.650
0.681
0.711
0.793
0.711
0.740
0.768
0.880
0.959
Whitewater 2008
0.003
0.042
0.120
0.183
0.551
0.160
0.382
0.483
0.618
0.880
Willow Hole 1996
0.103
0.183
0.289
0.289
0.483
0.289
0.319
0.350
0.551
0.681
Willow Hole 2008
0.062
0.260
0.449
0.711
0.840
0.618
0.740
0.840
0.861
0.926
North Thousand Palms 1996
0.002
0.008
0.034
0.062
0.120
0.062
0.087
0.120
0.183
0.382
South Thousand Palms 1996
0.062
0.120
0.120
0.139
0.232
0.139
0.160
0.207
0.289
0.517
South Thousand Palms 2008
0.011
0.139
0.232
0.382
0.681
0.382
0.449
0.681
0.681
0.926
East Indio Hills 1996
0.042
0.074
0.074
0.103
0.183
0.087
0.103
0.183
0.183
0.232
15
Table S7: Adjusted allelic richness (Ar) for Whitewater samples from 1996 and 2008,
rarified to 26 gene copies.
Locus
1996
2008
2L
4.00
4.38
2M
5.85
5.63
PLKN
2.00
2.63
2Q
6.78
5.50
2O
7.00
6.60
2S
8.71
7.47
3B
2.93
2.81
TRI4H
3.86
3.14
TETQY
3.86
4.24
TET_KL
4.99
3.86
DI_VQ1
3.86
3.46
AVG OVER LOCI
4.89
4.52
16
Figure S1: Structure posterior probability distribution of the data given a range of K (1-7)
from 1996 and 2008 STRUCTURE analyses. In 1996, one genetic cluster was most highly
supported. In 2008, up to three genetic clusters were supported; higher K values resulted
in non-informative grouping of allelic information. Results from the ΔK tests supported
K=3-4 (see Table S3).
17
Figure S2: PCA plots of posterior model checks between the summary statistics of the
observed dataset and the corresponding summary statistics from the posterior predictive
distribution.
18