Download Land use patterns skew sex ratios, decrease genetic diversity and

A Journal of Conservation Biogeography
Diversity and Distributions, (Diversity Distrib.) (2014) 1–13
BIODIVERSITY
RESEARCH
Land use patterns skew sex ratios,
decrease genetic diversity and trump the
effects of recent climate change in an
endangered turtle
Brendan N. Reid* and M. Z. Peery
Department of Forest and Wildlife Ecology,
University of Wisconsin-Madison, Madison,
WI, USA
ABSTRACT
Aim Changes in both land use and climate can cause population declines and
species extinctions, but the relative effects of these two stressors are often
dependent on species-specific life histories. Turtles are highly threatened as a
taxonomic group and are particularly sensitive to environmental change due to
their life history, habitat preferences and physiology. We used both sex data
and genetic diversity across a landscape-scale gradient in land use intensity and
recent climate change to characterize the relative effects of these factors on
three turtle species (including the endangered Blanding’s turtle, Emydoidea
blandingii) with different life histories and thus different vulnerabilities to
environmental change.
Location Wisconsin, USA.
Diversity and Distributions
Methods Turtles were captured and sampled for genetic analyses at 18 sites.
Sampled individuals were genotyped for species-specific sets of microsatellite
markers, and population-level genetic diversity was assessed using rarefied allelic richness and heterozygosity. The relative effects of road density, public land
area and recent climate change on genetic diversity and sex ratio were evaluated
using regression methods and model-selection criteria.
Results Increased land use intensity was associated with male-skewed sex ratios
and decreased genetic diversity in E. blandingii but not co-occurring species.
Recent climate change did not explain variability in either sex ratio or genetic
diversity for any of the three species examined.
*Correspondence: Brendan N. Reid,
Department of Forest and Wildlife Ecology,
University of Wisconsin-Madison 1630
Linden Drive, Madison, WI 53706, USA.
E-mail: [email protected]
Main conclusions Changing land use has multiple impacts on turtle populations that are modulated by species-specific life history traits. Extensive terrestrial movements associated with nesting in E. blandingii increase female
vulnerability to road mortality, which in turn has led to declines in genetic
diversity. The predicted effects of recent climate change may have been dampened by behavioural plasticity. We suggest that the disproportionate effect of
land use on E. blandingii warrants greater legal protection for this species.
Keywords
Climate change, genetic diversity, land use, sex ratios, temperature-dependent
sex determination, turtles.
Ongoing changes in land use and climate are projected to
cause shifts in species’ geographic ranges and increase extinction rates (Hansen et al., 2001; Thomas et al., 2004; Jetz
et al., 2007). Currently, the impacts of land use on
geographic ranges and community composition are more
apparent than the effects of climate change, but analyses that
control for the effects of land use show a clear signature of
the impact of contemporary temperature increases across a
range of taxa (Parmesan & Yohe, 2003). The relative effects
of land use and climate will vary among species due to
ª 2014 John Wiley & Sons Ltd
DOI: 10.1111/ddi.12243
http://wileyonlinelibrary.com/journal/ddi
INTRODUCTION
1
B. N. Reid and M. Z. Peery
differences in life history strategies (Hoehn et al., 2007; Callens et al. 2007, Perry et al., 2005; Jiguet et al., 2007). Thus,
effective conservation planning will require accurate assessments of the relative effects of climate change and land use,
as well as an understanding of how these effects are modulated by interspecific differences (Pressey et al., 2007; Nelson
et al., 2009; Hof et al., 2011).
Turtles (Order Chelonia) are one of the most threatened
animal taxa globally (Buhlmann et al., 2009), as well as one
of the most endangered groups of reptiles (B€
ohm et al.,
2013). Land use change, particularly the expansion of road
systems and urban areas, has been implicated as a potential
cause for declines in turtles (Gibbs & Shriver, 2002). Roads
reduce population size and genetic diversity in many species,
with amphibians and reptiles particularly vulnerable to these
effects (Fahrig & Rytwinski, 2009; Holderegger & Di Giulio,
2010; Jackson & Fahrig, 2011). Additionally, in aquatic turtle
species, females must travel overland to find nest sites and
roads thus are likely to cause female-biased mortality and
male-biased adult sex ratios (Steen et al., 2006). Skewed sex
ratios can in turn reduce population growth rates through
Allee effects (Stephens et al., 1999) and increase the rate at
which genetic variation is lost via reductions in effective
population size (Frankham, 1995). The population-level
effects of road mortality are likely to be modulated by species-level characteristics, and larger or more terrestrial species
are more likely to experience declines due to roads (Gibbs &
Shriver, 2002).
Climate change may also distort sex ratios in turtles as
most species exhibit temperature-dependent sex determination (TSD; Janzen, 1994a; Mitchell & Janzen, 2010). For
many turtle species with TSD, changes in incubation temperature of only 1–2°C around the pivotal sex-determining
threshold temperature are sufficient to cause nearly 100%
shifts in clutch sex ratio (Ewert et al. 1994). Plasticity in
nesting behaviour or physiological adaptation will likely mitigate climate change impacts on turtles to some degree
(Tucker et al., 2008; Refsnider & Janzen, 2012). However,
few empirical studies have been conducted examining the
effects of ongoing climate change on sex ratio, and our
understanding of the potential effects of climate change in
species with TSD relies mainly on modelling of nest temperatures under different climate change scenarios. For loggerhead sea turtles (Caretta caretta) nesting in North Carolina,
a 2°C increase in air temperature led to change in the predicted hatchling sex ratio of more than 20% (Hawkes et al.,
2007). In the painted turtle (Chrysemys picta), modelling predicts a persistent change in adult sex ratios of a similar magnitude following a 1°C change in air temperature even after
accounting for potential adaptive response (Morjan, 2003a).
In this study, we characterized the relative impacts of
recent, regional-scale changes in climate and land use patterns on three species with different life history strategies in
Wisconsin, USA. The effects of variability in nest microclimate and yearly climate on clutch and cohort sex ratios are
well documented (Janzen, 1994b; Weisrock & Janzen, 1999;
2
Juliana et al., 2004; Schwanz et al., 2010). Our intent in this
study was to ascertain whether recent trends in macroclimate
have sufficiently altered nest microclimate to produce
changes in population sex ratio. Furthermore, past research
on the effects of roads has often focused on small-scale variability in road density (i.e. within urban areas; Patrick &
Gibbs, 2010) or on situations where individual roads are
likely to dominate other factors that may affect the population (i.e. populations adjacent to highways; Steen & Gibbs,
2004). Thus, these studies have excluded the effects of landscape-level change in land use and the potential additive or
interactive effects of climate. Recent warming in Wisconsin
has been spatially heterogeneous (Kucharik et al., 2010),
meaning that climate-induced changes in sex ratio could
mask the effects of sex-biased adult mortality in some areas.
This heterogeneity, however, also provides an opportunity to
simultaneously test the effects of landscape-scale variation in
climate change and land use.
We used population sex ratio and genetic diversity as metrics to examine the impacts of land use and climate change
on turtles with the expectation that effects would vary among
species due to life history. We expected that sex ratio should
be sensitive to both climate-related changes in hatchling sex
ratio and female-biased road mortality in adults. We
expected that genetic diversity should be mainly sensitive to
population reductions caused by increased road mortality,
but could also be impacted by reduction in effective population size resulting from biased sex ratios associated with
either climate change or sex-biased adult mortality. We
examined three co-occurring species: the globally endangered
(van Dijk & Rhodin, 2010), semi-aquatic Blanding’s turtle
(Emydoidea blandingii) as well as two more common aquatic
species, the painted turtle (Chrysemys picta) and snapping
turtle (Chelydra serpentina). We predicted that sex ratios
would be male-biased and genetic diversity would be lower
at sites with higher land use intensity and that land use
would have a greater impact on E. blandingii due to long
overland nesting movements in this species (Beaudry et al.,
2010; Steen et al., 2012). Summer temperatures in portions
of Wisconsin have increased approximately 1°C while
remaining stable in other parts of the state (Wisconsin
Initiative on Climate Change Impacts (WICCI) 2001), and
simulations predict a roughly 20% shift towards more femalebiased population sex ratios in C. picta after a 1°C increase in
July air temperature (Morjan, 2003a). While simulations of
the effects of climate on hatchling sex ratio have not been
conducted for all species, the male-female transitional range
of temperatures is similar for C. picta (Bull et al., 1982) and
C. serpentina (Ewert et al., 2005) at northern latitudes as well
as E. blandingii (Gutzke & Packard, 1987), and as such a
similar relationship between summer temperature and sex
should hold in all three species. We predicted that shifts in
hatchling sex ratio caused by recent climate change are most
likely to manifest as changes in population-level sex ratio for
C. picta, which has shorter generation times and higher population turnover rates than E. blandingii (Congdon et al.,
Diversity and Distributions, 1–13, ª 2014 John Wiley & Sons Ltd
Land use, climate change, and turtles
Table 1 Average landscape and climate characteristics, capture sex ratio and genetic diversity statistics for all sites. Road density is given
in km/km2, public land in km2 and temperature change in °C
Site
code
Road
density
Public land
area
(A) Emydoidea blandingii
BR
0.46
71.13
CL
2.96
0.38
CM*
0.86
45.28
EC
1.33
28.58
FT
0.90
67.76
GP†
4.98
0.34
KM
1.62
17.46
MC
1.94
12.55
MN†
3.07
2.31
MU
1.12
13.51
MZ
0.76
15.67
NV
0.77
47.39
RB†
1.63
17.86
SH
0.61
39.87
0.98
11.77
TB†
(B) Chrysemys picta
BR
0.46
71.18
CH
0.93
24.20
CL
2.96
0.38
EC
1.70
19.20
FT
1.14
69.40
KM
1.68
12.06
MC
2.05
12.38
MN
4.93
1.34
MR
1.00
2.87
MU
1.08
13.52
MZ
0.73
15.55
NV
0.66
42.89
SH
0.62
37.78
TB
0.88
17.75
WR
0.90
20.00
(C) Chelydra serpentina
BR
0.45
71.13
CH
0.91
30.47
CL†
2.96
0.38
EC
1.46
22.86
FT*
1.14
69.40
KM
1.65
10.84
MN*
4.93
1.34
MR
1.04
2.84
MU
1.12
13.03
MZ*
0.73
15.55
SH
0.59
40.12
TB
0.87
19.86
WR
0.79
28.99
Temperature
change
Adults
trapped
Proportion
male
Genetic
samples
Allelic
richness
Observed
heterozygosity
0.38
0.15
1.04
0.40
0.29
0.96
0.01
1.13
0.19
0.28
0.06
0.15
0.20
0.67
0.23
7
4
–
11
6
5
11
12
15
8
7
7
11
67
2
0.57
0.75
–
0.45
0.17
0.80
0.64
0.75
0.87
0.38
0.71
0.86
0.55
0.60
0.50
7
9
15
11
15
–
11
15
–
32
7
8
–
241
–
4.14
3.43
4.37
4.01
4.23
–
4.49
3.7
–
4.12
3.86
4.42
–
4.26
–
0.66
0.50
0.68
0.59
0.64
–
0.62
0.59
–
0.62
0.64
0.71
–
0.60
–
0.38
0.51
0.15
0.45
0.28
0.00
1.13
0.17
0.16
0.27
0.06
0.15
0.67
0.23
0.31
30
23
19
112
9
107
37
47
15
70
12
21
268
57
74
0.73
0.78
0.58
0.70
0.89
0.72
0.81
0.79
0.20
0.84
1.00
0.81
0.68
0.74
0.81
32
24
23
33
13
54
40
33
17
34
13
23
60
30
32
5.72
5.72
6.01
5.4
5.25
6.18
6
5.92
5.01
5.39
5.94
5.69
5.67
5.79
6.27
0.69
0.73
0.75
0.74
0.69
0.74
0.72
0.73
0.70
0.63
0.67
0.74
0.72
0.70
0.77
0.38
0.57
0.15
0.42
0.28
0.01
0.17
0.16
0.24
0.06
0.67
0.23
0.33
9
7
2
17
–
33
–
5
8
–
47
17
24
0.89
0.86
0.5
0.53
–
0.67
–
1.00
0.63
–
0.64
0.53
0.88
9
9
4.85
5.22
–
5.24
5.22
5.19
4.86
4.11
5.17
4.67
5.25
5.04
4.85
0.61
0.71
–
0.70
0.76
0.67
0.69
0.73
0.65
0.64
0.68
0.62
0.63
–
23
7
45
15
13
8
7
27
18
27
*Sex ratio data were not available for a site.
Genetic data were not available for a site (as the number of genetic samples was below the cut-off of 7).
†
Dependent variables considered were allelic richness and
observed heterozygosity. Heterozygosity data were arcsinesquare-root-transformed (FitzSimmons et al., 1995). Means
of landscape or climate data over all individuals from a site
Diversity and Distributions, 1–13, ª 2014 John Wiley & Sons Ltd
were used as the independent variables in genetic diversity
models.
We evaluated models incorporating each additive combination of explanatory variables, as well as models incorporating two-way interactions between each land use variable and
5
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Diversity and Distributions, 1–13, ª 2014 John Wiley & Sons Ltd
Land use, climate change, and turtles
Table 1 Average landscape and climate characteristics, capture sex ratio and genetic diversity statistics for all sites. Road density is given
in km/km2, public land in km2 and temperature change in °C
Site
code
Road
density
Public land
area
(A) Emydoidea blandingii
BR
0.46
71.13
CL
2.96
0.38
CM*
0.86
45.28
EC
1.33
28.58
FT
0.90
67.76
GP†
4.98
0.34
KM
1.62
17.46
MC
1.94
12.55
MN†
3.07
2.31
MU
1.12
13.51
MZ
0.76
15.67
NV
0.77
47.39
RB†
1.63
17.86
SH
0.61
39.87
0.98
11.77
TB†
(B) Chrysemys picta
BR
0.46
71.18
CH
0.93
24.20
CL
2.96
0.38
EC
1.70
19.20
FT
1.14
69.40
KM
1.68
12.06
MC
2.05
12.38
MN
4.93
1.34
MR
1.00
2.87
MU
1.08
13.52
MZ
0.73
15.55
NV
0.66
42.89
SH
0.62
37.78
TB
0.88
17.75
WR
0.90
20.00
(C) Chelydra serpentina
BR
0.45
71.13
CH
0.91
30.47
CL†
2.96
0.38
EC
1.46
22.86
FT*
1.14
69.40
KM
1.65
10.84
MN*
4.93
1.34
MR
1.04
2.84
MU
1.12
13.03
MZ*
0.73
15.55
SH
0.59
40.12
TB
0.87
19.86
WR
0.79
28.99
Temperature
change
Adults
trapped
Proportion
male
Genetic
samples
Allelic
richness
Observed
heterozygosity
0.38
0.15
1.04
0.40
0.29
0.96
0.01
1.13
0.19
0.28
0.06
0.15
0.20
0.67
0.23
7
4
–
11
6
5
11
12
15
8
7
7
11
67
2
0.57
0.75
–
0.45
0.17
0.80
0.64
0.75
0.87
0.38
0.71
0.86
0.55
0.60
0.50
7
9
15
11
15
–
11
15
–
32
7
8
–
241
–
4.14
3.43
4.37
4.01
4.23
–
4.49
3.7
–
4.12
3.86
4.42
–
4.26
–
0.66
0.50
0.68
0.59
0.64
–
0.62
0.59
–
0.62
0.64
0.71
–
0.60
–
0.38
0.51
0.15
0.45
0.28
0.00
1.13
0.17
0.16
0.27
0.06
0.15
0.67
0.23
0.31
30
23
19
112
9
107
37
47
15
70
12
21
268
57
74
0.73
0.78
0.58
0.70
0.89
0.72
0.81
0.79
0.20
0.84
1.00
0.81
0.68
0.74
0.81
32
24
23
33
13
54
40
33
17
34
13
23
60
30
32
5.72
5.72
6.01
5.4
5.25
6.18
6
5.92
5.01
5.39
5.94
5.69
5.67
5.79
6.27
0.69
0.73
0.75
0.74
0.69
0.74
0.72
0.73
0.70
0.63
0.67
0.74
0.72
0.70
0.77
0.38
0.57
0.15
0.42
0.28
0.01
0.17
0.16
0.24
0.06
0.67
0.23
0.33
9
7
2
17
–
33
–
5
8
–
47
17
24
0.89
0.86
0.5
0.53
–
0.67
–
1.00
0.63
–
0.64
0.53
0.88
9
9
4.85
5.22
–
5.24
5.22
5.19
4.86
4.11
5.17
4.67
5.25
5.04
4.85
0.61
0.71
–
0.70
0.76
0.67
0.69
0.73
0.65
0.64
0.68
0.62
0.63
–
23
7
45
15
13
8
7
27
18
27
*Sex ratio data were not available for a site.
Genetic data were not available for a site (as the number of genetic samples was below the cut-off of 7).
†
Dependent variables considered were allelic richness and
observed heterozygosity. Heterozygosity data were arcsinesquare-root-transformed (FitzSimmons et al., 1995). Means
of landscape or climate data over all individuals from a site
Diversity and Distributions, 1–13, ª 2014 John Wiley & Sons Ltd
were used as the independent variables in genetic diversity
models.
We evaluated models incorporating each additive combination of explanatory variables, as well as models incorporating two-way interactions between each land use variable and
5
B. N. Reid and M. Z. Peery
the climate variable. Relative support for each model was
determined using Akaike’s information criterion corrected
for small sample size (AICc; Burnham & Anderson, 2002).
AICc was calculated using the R package AICcmodavg version 1.35 (Mazerolle, 2013). We considered all candidate
models that were ranked higher than the base model (containing either the intercept only or, for the logistic regression
model, the intercept and the random site effect only) to be
relatively well-supported alternate explanations of the data.
RESULTS
After excluding individuals below the size and age cut-offs,
1244 total capture records were included in the final analyses. Capture data were not available from all sites for
all three species (C. picta: 15 sites; E. blandingii: 14 sites;
C. serpentina: 11 sites; Table 1). Captures were male-biased
for all three species, and the overall proportion of males was
0.73 for C. picta (n = 901), 0.70 for C. serpentina (n = 170)
and 0.62 for E. blandingii (n = 173). For genetic analyses, 15
sites had ≥7 samples for C. picta (n = 467), 11 sites had ≥7
samples for E. blandingii (n = 372) and 12 sites had ≥7
samples for C. serpentina (n = 203).
Sex ratio analysis
There was considerable variation in average daily high temperatures (25.89 to 27.92°C; mean 26.93°C) and in the magnitude of recent change in summer temperature ( 0.33 to
+1.13°C; mean +0.66°C) across the sites we sampled. The
proportion of adults hatched within the time windows used
for climate data was approximately half for E. blandingii
(51%) and C. serpentina (44%) over the shorter interval,
over 80% for these two species over the longer interval, and
nearly 100% of C. picta adults over both intervals (Table
S4). Based on Schwanz et al. (2010), we calculated an
expected 20% difference in average cohort sex ratio between
sites with the highest and lowest changes in average temperature change. Road densities and public land across the two
spatial scales were highly positively correlated (r = 0.77 and
0.69, respectively) and average temperature and temperature
trend were highly negatively correlated (r = 0.72) (Table
S5). We retained temperature change and 5-km scale land
use variables for use in regression modelling.
Logistic regression of sex against Julian day of capture was
not significant (a = 0.05) for any species, indicating that
sampled sex ratios were not an artefact of sampling date. For
E. blandingii, the two best models for sex ratio contained
either public land area or road density and the random effect
(Table 2). These models were 1.2 and 1.5 AICc lower and
were approximately twice as likely compared to the base
model according to AICc weights (Table 2). Regression coefficients were positive for road density (bRoad = 0.31; 95%
confidence interval (CI) = 0.04 to 0.66) and negative for
public area (bPublic = 0.015; 95% CI 0.0005 to 0.03).
Thus, our results suggest that the proportion of males
6
increases with road density and decreases with the public
land area (Fig. 2), although CIs slightly overlapped 0 in both
cases. An additive model containing both road density and
public land also performed slightly better than the base
model. For C. picta, models containing public land area
alone plus the random effect or the random effect alone had
roughly equal levels of support. The probability of catching a
male, however, was slightly higher in areas with more public
land (bPublic = 0.008; 95% CI 0.006 to 0.019), contrary to
expectations of decreased female mortality with increasing
public land. For C. serpentina, the model containing only a
random effect of site had the lowest AICc, indicating that
road density, public land area and temperature change were
not strong predictors of sex ratios in this species.
Genetic diversity
After sequential Bonferroni correction for multiple comparisons, no markers or pairs of markers exhibited significant
deviation from Hardy–Weinberg equilibrium or significant
linkage disequilibrium in more than one population. Allelic
richness per locus was lower and more variable across sites
in E. blandingii (mean = 4.09, range 3.43 to 4.49, coefficient
of variation (CV) = 0.079) compared with C. serpentina
(mean = 4.97, range 4.11–5.25, CV = 0.068) and C. picta
(mean = 5.73, range 5.01–6.27, CV = 0.061). Heterozygosity
followed the same pattern, with lowest average heterozygosity
in E. blandingii (mean = 0.623, range 0.495–0.714,
CV = 0.09) compared with C. serpentina (mean = 0.675,
range 0.605–0.762, CV = 0.069) and C. picta (mean = 0.716,
range 0.626–0.771, CV = 0.051).
Models containing road density performed best in explaining both measures of genetic diversity for E. blandingii
(Table 2). For allelic richness and heterozygosity, the road
density model ranked 3 AICc and 8.6 AICc higher (respectively) than the base model and was 4.5 and 82 times more
likely (respectively) than the base model. Both allelic richness
(bRoad = 0.303, 95% CI 0.539 to 0.067) and heterozygosity (bRoad = 0.062, 95% CI 0.092 to 0.033) declined
with increasing road density. For C. picta and C. serpentina,
the base model performed best for both diversity metrics
(Fig. 3).
DISCUSSION
Species-specific effects of land use change
In this study, we present genetic and demographic evidence
for an effect of land use on the endangered Blanding’s turtle, but not for the more common painted and snapping
turtles. Previous studies conducted across species with varying life histories have shown more severe effects of contemporary habitat fragmentation in less mobile species (Hoehn
et al., 2007; Callens et al., 2011), and more mobile species
are often better equipped to deal with the effects of global
change (Warren et al., 2001). For the species examined here,
Diversity and Distributions, 1–13, ª 2014 John Wiley & Sons Ltd
Land use, climate change, and turtles
Table 2 Levels of support for all models evaluated. Statistics for all models with higher AICc values than the base model are shown in
grey, and the model with the most support for each species and dependent variable is shown in bold
Sex
Allelic Richness
Heterozygosity
(A) E. blandingii
Model
k
AICc
ΔAICc
w
AICc
ΔAICc
w
Base
Road
Public
Temp
Road + Public
Road + Temp
Public + Temp
Road 9 Temp
Public 9 Temp
Road + Public + Temp
1
2
2
2
3
3
3
4
4
4
234.0
232.8
232.5
236.0
233.9
234.7
234.1
236.7
236.1
235.7
1.5
0.3
0.0
3.5
1.4
2.2
1.6
4.2
3.6
3.2
0.11
0.20
0.24
0.04
0.11
0.08
0.10
0.03
0.04
0.05
10.8
7.9
10.4
14.6
12.8
12.8
14.9
19.3
21.8
19.7
3.0
0.0
2.6
6.7
5.0
4.9
7.1
11.5
13.9
11.9
0.13
0.58
0.16
0.02
0.05
0.05
0.02
0.00
0.00
0.00
Sex
Allelic Richness
26.8
35.4
28.8
22.9
30.4
30.3
24.2
26.0
17.0
23.3
ΔAICc
w
8.6
0.0
6.6
12.5
5.0
5.1
11.2
11.0
18.4
12.1
0.01
0.82
0.03
0.00
0.07
0.06
0.00
0.00
0.00
0.00
Heterozygosity
(B) C. picta
Model
k
AICc
ΔAICc
w
AIC
ΔAIC
w
Base
Road
Public
Temp
Road + Public
Road + Temp
Public + Temp
Road 9 Temp
Public 9 Temp
Road + Public + Temp
1
2
2
2
3
3
3
4
4
4
1053.6
1054.7
1053.5
1055.5
1055.3
1056.7
1055.4
1057.8
1057.0
1057.2
0.1
1.2
0.0
2.0
1.8
3.2
1.9
4.3
3.5
3.7
0.22
0.13
0.23
0.09
0.09
0.05
0.09
0.03
0.04
0.04
15.0
17.1
17.2
17.1
20.6
19.9
19.5
24.4
22.9
23.9
0.0
2.1
2.2
2.1
5.6
4.9
4.5
9.4
8.0
8.9
0.43
0.15
0.14
0.15
0.03
0.04
0.05
0.00
0.01
0.00
Sex
AICc
Allelic Richness
AIC
49.9
48.1
47.2
48.0
44.3
45.6
45.0
41.3
41.8
41.0
ΔAIC
w
0.0
1.8
2.7
1.9
5.6
4.4
4.9
8.6
8.2
8.9
0.43
0.17
0.11
0.16
0.03
0.05
0.04
0.01
0.01
0.00
Heterozygosity
(C) C. serpentina
Model
k
AICc
ΔAICc
w
AIC
ΔAIC
w
Base
Road
Public
Temp
Road + Public
Road + Temp
Public + Temp
Road 9 Temp
Public 9 Temp
Road + Public + Temp
1
2
2
2
3
3
3
4
4
4
214.4
215.7
214.6
216.4
216.6
217.1
215.1
219.1
216.9
217.1
0.0
1.3
0.2
2.0
2.2
2.7
0.7
4.7
2.5
2.7
0.21
0.11
0.20
0.08
0.07
0.05
0.15
0.02
0.06
0.05
12.2
15.8
14.4
12.6
18.8
17.3
17.2
23.5
21.6
23.3
0.0
3.7
2.2
0.5
6.7
5.1
5.0
11.4
9.4
11.2
0.40
0.06
0.13
0.32
0.01
0.03
0.03
0.00
0.00
0.00
AIC
33.6
30.4
29.9
29.9
25.9
25.7
25.2
20.2
19.0
19.6
ΔAIC
w
0.0
3.2
3.7
3.7
7.7
7.8
8.4
13.3
14.6
13.9
0.63
0.13
0.10
0.10
0.01
0.01
0.00
0.00
0.00
0.00
k = number of parameters; ΔAICc = difference in AICc between a particular model and best supported model for the given variable; w = model
weight.
however, increased terrestrial movement tendencies in
E. blandingii have the paradoxical effect of increasing the
genetic and demographic impacts of fragmentation. As
mobility in E. blandingii is associated with seasonal use of
multiple terrestrial and aquatic habitats (Beaudry et al.,
2009), disruption of the complex habitat networks used by
this species may increase its vulnerability to the detrimental
effects of land use change relative to the less mobile C. picta
and C. serpentina. Management actions aimed at mitigating
the effects of environmental change are likely to be more
efficient and successful when complex habitat requirements,
Diversity and Distributions, 1–13, ª 2014 John Wiley & Sons Ltd
such as those demonstrated by Emydoidea, are taken into
account during conservation planning (Baldwin et al.,
2006).
Our analysis identified both road density and public land
area as potential factors impacting sex ratios in E. blandingii.
The relative effects of habitat protection and road density,
however, are difficult to disentangle. Public land area was
somewhat negatively correlated with road density
(r = 0.56), and sites with high road density (>2 km/km2)
had uniformly low public land area (<10 km2). Public land
area alone performed slightly better in explaining variability
7
B. N. Reid and M. Z. Peery
(a)
(b)
(c)
Figure 2 Proportion male captured per site plotted against average site road density and public land for each species. Fitted
relationships from the best models for Emydoidea blandingii are shown.
in sex ratio than the model containing road density alone,
possibly indicating that variability in public land area
accounted better for variability in sex ratios among sites with
low road densities (Fig. 2). Roads within or around protected areas may have lower traffic volumes or speed limits,
which could result in less frequent sex-biased road mortality.
Alternately, protected areas may have higher levels of recruitment due to decreased predation on nests or offspring,
which could increase the population turnover rate and dampen the effect of increased mortality of adult females. As
poor recruitment has been observed for E. blandingii even
within protected areas (Congdon et al., 1993; Browne &
Hecnar, 2007); however, this explanation is unlikely to apply
broadly across E. blandingii populations.
For both genetic diversity metrics, on the other hand,
roads were a better predictor of variability than public land
area, with models containing only road density weighted 3
times higher (for allelic richness) or 27 times higher (for heterozygosity) than models containing public land area alone.
While a number of studies have assessed microsatellite
genetic variability at regional scales in E. blandingii (Mock-
8
ford et al., 2007; Davy et al., 2013; Sethuraman et al., 2013),
none have explicitly examined the effects of land use on
genetic diversity. Continuing loss of individuals of either sex
causes loss of genetic diversity over time (Jackson & Fahrig,
2011) and additional effects of habitat fragmentation (such
as reduced gene flow) will likely compound this effect (Keyghobadi 2007), meaning that genetic diversity may be more
sensitive to persistent low levels of road mortality than sex
ratio.
While no increasing bias towards males was detected in
this study for C. picta and C. serpentina with higher road
densities or lower public land area, sex ratio biases correlated
with land use have been detected for one or both of these
species by several others (Marchand & Litvaitis, 2004; Steen
& Gibbs, 2004; Patrick & Gibbs, 2010). These previous studies examined the effects of roads on a smaller scale (within
100–1000 m of the resident wetland) than we have used
here. However, in separate regression analyses conducted
using a 1-km buffer distance, we did not detect a significant
increase in proportion male associated with either increased
road density or decreased public land area (data not shown),
Diversity and Distributions, 1–13, ª 2014 John Wiley & Sons Ltd
Land use, climate change, and turtles
(a)
(b)
(c)
Figure 3 Rarefied allelic richness and average observed heterozygosity plotted against average site road density for each species. Fitted
relationships from the best models for Emydoidea blandingii are shown.
suggesting that our results are robust across a range of spatial scales. Studies examining the effects of roads on genetic
diversity in these species are sparse; however, Laporte et al.
(2013) recently detected decreased mitochondrial (but not
nuclear) genetic diversity and higher variance in reproductive
success associated with increased roads for C. picta in Quebec. Our surveys focused on areas where E. blandingii was
known or suspected to occur, a factor that likely led to selection of sites where traffic volume was relatively low. Steen &
Gibbs (2004), for example, chose wetlands close to the New
York State Thruway as their ‘high road density’ sites, whereas
all of our capture sites were >1 km from major multilane
arteries. Further research comparing C. picta and C. serpentina populations among sites where E. blandingii either
persists or has been extirpated could be used to determine
whether the continued presence of E. blandingii corresponds
with decreased impact of land use on co-occurring species.
Climate change and potential for adaptation
We found little evidence for an effect of temperature change
on sex ratio or genetic diversity in any of the three species
examined here. No effect was evident despite a predicted
20% change in the sex ratios of C. picta across the observed
Diversity and Distributions, 1–13, ª 2014 John Wiley & Sons Ltd
gradient of climate change. This effect size was similar to the
change in sex ratio associated with land use that we detected
in E. blandingii with much smaller sample sizes and similar
to observed changes in C. picta sex ratios due to variation in
land use patterns detected by Steen & Gibbs (2004). Furthermore, there was no evidence that climate effects masked sexbiased mortality in C. picta and C. serpentina (or vice versa
in E. blandingii), and models incorporating climate variables
alone or climate and land use together tended to perform
worse than models containing only land use variables in
these species. These findings are consistent with the metaanalysis of Gibbs and Steen (2005), in which changes in
observed sex ratios over the past century were more consistent with the effects of growth of road networks than
changes in climate over the same period.
Characterizing the effects of climate change on turtle sex
ratios in Wisconsin is complicated by the fact that areas traditionally experiencing cooler summer temperatures have
warmed much faster than traditionally warm areas. If turtles
were not locally adapted (via differences in developmental
physiology or behaviour) to past climate regimes, this pattern of climate change might be expected to equalize sex
ratios between traditionally cooler and warmer areas rather
than produce an increase in females in areas with more
9
B. N. Reid and M. Z. Peery
warming. Because average climate and climate change were
highly correlated, we could not evaluate this possibility statistically. In separate regression analyses, however, we found no
significant effect of average temperature on sex ratio in any
of the three species (data not shown). Local adaption to a
much wider range of climate conditions than those within
our study area has been shown in the widely distributed
C. picta, in which nest temperatures (Morjan, 2003b) and
adult sex ratios (Refsnider et al., 2014) are similar across a
broad latitudinal gradient. Latitudinal variability in the pivotal sex-determining threshold temperature has also been
shown in both C. picta and C. serpentina (Bull et al., 1982;
Ewert et al., 2005). E. blandingii inhabits a narrower latitudinal range and may be more sensitive to climate change than
C. picta and C. serpentina (Herman & Scott, 1994).
A number of factors may account for the observed lack of
an effect of climate on sex ratios. Long maturation and generation times may provide a temporary buffer against the
effects of gradual climate change, especially in C. serpentina
and E. blandingii. Plasticity or evolutionary change may also
be a sufficient to mitigate the limited degree of change
observed here. Multiple studies have indicated female choice
of nest depth as a possible means of compensation for variability in climate in both C. picta (Refsnider & Janzen, 2012)
and in other reptile species with TSD (Doody, 2009; Telemeco et al., 2009). Examining nest depths across the spatial
gradient of climate change examined here would be a promising avenue for future research. However, changes in nesting
behaviour are unlikely to fully compensate for the present
effects of climate change (Telemeco et al., 2009; Refsnider
et al., 2013), and the total potential for adaptation is not
likely to be sufficient to compensate for most projected
climate change scenarios (Morjan, 2003a).
Implications for conservation
Emydoidea blandingii was recently assessed as globally endangered (van Dijk & Rhodin, 2013) and has been submitted as
a candidate for the US Endangered Species Act (Giese et al.,
2012). In Wisconsin, E. blandingii was recently removed
from the threatened species list despite continuing declines
throughout the state (Wisconsin Department of Natural
Resources, 2012). The data presented here suggest that ongoing land use change disproportionally impacts E. blandingii
compared with co-occurring species. Stage-based life history
analysis has shown that population growth is sensitive to
changes in adult survival in this species and that small
decreases in survival can result in negative demographic
trends (Congdon et al., 1993). Other factors related to land
use, such as changes in abundance of nest predators, can also
impact population structure in this species by essentially
eliminating recruitment (Congdon et al., 1993; Browne &
Hecnar, 2007), and the interaction of these two effects may
have synergistic impacts that act to speed declines. To prevent or reverse declines in E. blandingii, all of these threats
will likely need to be addressed. Thus, we recommend stron-
10
ger legal protection for this species to prevent further population declines.
ACKNOWLEDGEMENTS
Funding was provided by a USDA Hatch Act Formula Grant
(to M.Z. Peery) and an EPA-STAR Fellowship (to B.N. Reid).
This work was conducted under Endangered and Threatened
Resources (#681) and Scientific Collector’s (#135) permits
issued by the Wisconsin DNR and approved by UWMadison’s Animal Care and Use Committee (approval #
A3368-01). Additional trapping data for E. blandingii were
provided by S. Foster, M. Linton, A. Thompson and S. Murphy, and genetic samples were provided by the Field
Museum, E. Wild, J. Zellmer and R. Hay. We also thank
several anonymous referees for providing constructive
commentary.
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SUPPORTING INFORMATION
Additional Supporting Information may be found in the
online version of this article:
Table S1. Voucher information for museum samples.
Table S2. Locus information for microsatellite markers.
Table S3. Primer information for new microsatellite loci.
Table S4. Proportion hatched within climate data windows
for each species.
Table S5. Matrix of correlations among potential predictor
variables.
BIOSKETCHES
The Peery Conservation Biology Lab uses cutting edge ecological, genetic and population modelling approaches to provide managers and policymakers with information needed to
make sound decisions about the conservation of species at
risk of extinction. The laboratory focuses on providing pragmatic solutions to challenging problem in conservation. Further information can be found at http://labs.russell.wisc.edu/
peery/.
Authors’ contributions: Both authors were engaged in study
planning and manuscript development. B.N. Reid conducted
field and laboratory work as well as analyses.
Editor: Jeremy Austin
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