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Patterns of genetic variation in anthropognically impacted populations

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Genetic variation is considered critical for allowing natural populations to adapt to their changing environment, and yet the effects of human disturbance on genetic variation in the wild are poorly understood. Different types of human disturbances may genetically impact natural populations in a predictable manner and so the aim of this study was to provide an overview of these changes using a quantitative literature review approach. I examined both allozyme and microsatellite estimates of genetic variation from peer-reviewed journals, using the mean number of alleles per locus and expected heterozygosity as standardized metrics. Populations within each study were categorized according to the type of human disturbance experienced (“hunting/harvest”, “habitat fragmentation”, or “pollution”), and taxon-specific, as well as time- and context-dependent disturbance effects were considered. I found that human disturbances are associated with weak, but consistent changes in neutral genetic variation within natural populations. The direction of change was dependent on the type of human disturbance experienced, with some forms of anthropogenic challenges consistently decreasing genetic variation from background patterns (e.g., habitat fragmentation), whereas others had no effect (e.g., hunting/harvest) or even slightly increased genetic variation (e.g., pollution). These same measures appeared sensitive to both the time of origin and duration of the disturbance as well. This suggests that the presence or absence, strength, type, as well as the spatial and temporal scale of human disturbance experienced may warrant careful consideration when conservation management plans are formulated for natural populations, with particular attention paid to the effects of habitat fragmentation.
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ORIGINAL PAPER
Patterns of genetic variation in anthropogenically impacted
populations
Joseph D. DiBattista
Received: 7 October 2006 / Accepted: 26 February 2007 / Published online: 12 April 2007
Ó Springer Science+Business Media B.V. 2007
Abstract Genetic variation is considered critical for
allowing natural populations to adapt to their changing
environment, and yet the effects of human disturbance on
genetic variation in the wild are poorly understood. Dif-
ferent types of human disturbances may genetically impact
natural populations in a predictable manner and so the aim
of this study was to provide an overview of these changes
using a quantitative literature review approach. I examined
both allozyme and microsatellite estimates of genetic var-
iation from peer-reviewed journals, using the mean number
of alleles per locus and expected heterozygosity as stan-
dardized metrics. Populations within each study were cat-
egorized according to the type of human disturbance
experienced (‘‘hunting/harvest’’, ‘‘habitat fragmentation’’,
or ‘‘pollution’’), and taxon-specific, as well as time- and
context-dependent disturbance effects were considered. I
found that human disturbances are associated with weak,
but consistent changes in neutral genetic variation within
natural populations. The direction of change was dependent
on the type of human disturbance experienced, with some
forms of anthropogenic challenges consistently decreasing
genetic variation from background patterns (e.g., habitat
fragmentation), whereas others had no effect (e.g., hunting/
harvest) or even slightly increased genetic variation (e.g.,
pollution). These same measures appeared sensitive to both
the time of origin and duration of the disturbance as well.
This suggests that the presence or absence, strength, type,
as well as the spatial and temporal scale of human distur-
bance experienced may warrant careful consideration when
conservation management plans are formulated for natural
populations, with particular attention paid to the effects of
habitat fragmentation.
Keywords Conservation genetics Genetic variation
Heterozygosity Human disturbance Mean number of
alleles per locus
Introduction
Genetic variation is the raw material on which selection
acts and thus critical for evolutionary change. Genetic
variation may be particularly important in the case of rapid
environmental change, where evolution must also be rapid
if a population is to persist (Burger and Lynch 1995; Lande
and Shannon 1996). However, as dramatic environmental
changes are often associated with human activities (e.g., De
Pippo et al. 2006), it is here that genetic variation may be
most important. Indeed, human impacts themselves are
thought to decrease genetic variation (Caizergues et al.
2003; Kang et al. 2005), thus compromising necessary
evolutionary change. The aim of this study is therefore to
examine how human activities influence genetic variation
in natural populations.
The ideal experiment to examine human impacts on
genetic variation in nature is to screen a population before
and after a disturbance. However, it is often not possible to
carry out such experiments, therefore, as an alternative I
have examined a large number of published studies to find
a consensus on the effects of different types of human
disturbance on genetic variation. This consideration is
motivated in part by the conflicting results from different
studies of genetic variation. In particular, some studies
report reductions in genetic variation as a result of human
J. D. DiBattista (&)
Redpath Museum and Department of Biology, McGill
University, 859 Sherbrooke St. West, Montreal, QC H3A 2K6,
Canada
e-mail: joseph.dibattista@mail.mcgill.ca
123
Conserv Genet (2008) 9:141–156
DOI 10.1007/s10592-007-9317-z
disturbance (Caizergues et al. 2003; Kang et al. 2005),
whereas others find no such effect (Berckmoes et al. 2005;
Goosens et al. 2005). Genetic variation will reflect a bal-
ance between selection, mutation, and drift, and so human
activities that differentially impact these forces may have
very different effects on genetic variation. Human impacts
that reduce population size and increasingly isolate popu-
lations may increase genetic drift and thereby reduce ge-
netic variation. Human impacts that change environmental
conditions may increase selection and thereby also reduce
genetic variation. Human impacts that increase mutation
rates (e.g., Chernoble; Ellegren et al. 1997) may increase
genetic variation. To examine these effects, I divide dif-
ferent types of human impacts in accordance with the
primary deterministic factors that contribute to modern
population extinction events (for review see Frankham
2003).
Hunting and harvesting reduce population size and at
least sometimes cause significant declines in neutral
genetic variation (Frankham 1996; Godt et al. 1996). In
these cases, genetic variation may be lost through random
genetic drift as the effective population size decreases
(Lacy 1997). Further, inbreeding may increase the pro-
portion of homozygous individuals within a population,
which ultimately leads to a reduction in fitness (Crnokrak
and Roff 1999). Trophy hunting in particular may also
exert strong directional selection by targeting animals with
the largest ornaments, which may then remove specific
alleles or genotypes from a population (Fitzsimmons et al.
1995; Coltman et al. 2003). The prediction here would
therefore be a decrease in genetic variation for hunted and
harvested populations.
Habitat fragmentation, due to human settlements,
fenced motorways, channels, and habitat clearing, results in
the subdivision of populations into smaller, more discrete
units, with limited dispersal among them. These changes
can, in at least some cases, erode genetic variation due to
increased inbreeding and genetic drift within fragments,
and to reduced gene flow among fragmented units (Young
et al. 1996; Frankham et al. 2002). The prediction here
would therefore also be a decrease in genetic variation for
fragmented populations.
Pollution may influence genetic variation, although the
outcome is much less certain here than for the factors
mentioned above (Bickham et al. 2000). On the one hand
pollution might decrease genetic variation owing to genetic
drift and inbreeding, particularly in cases of increased
mortality that decrease population size (Posthuma and Van
Straalen 1993; Belfiore and Anderson 2001). Genetic var-
iation may also decrease owing to selection for pollution-
tolerant genotypes (Keane et al. 2005). On the other hand,
populations chronically exposed to chemical pollutants
may experience an increase in genetic variation due to
increased mutation rates (Yauk and Quinn 1996; Baker
et al. 2001) or selection for heterozygotes (i.e., overdomi-
nant hypothesis; see Bickham et al. 2000). Because of this
complexity, it remains uncertain as to the type of effects
that pollution will have on average.
Given our interest in evolutionary potential, we would
most like to track changes in genetic variation at fitness
related traits. This information, however, is largely lacking
for natural populations. Instead, it is sometimes possible to
use neutral genetic variation as a surrogate (Frankham
et al. 2002). This can be tenuous when examining variation
among populations (McKay and Latta
2002), but it is often
defensible within populations (Gilligan et al. 2005). In-
deed, neutral genetic variation largely appears associated
with population fitness and extinction risk (Frankham
2003, 2005; Reed and Frankham 2003). I will therefore
analyze patterns of neutral genetic variation in hope that it
also informs the amount of variation for traits and genes
under selection.
In the present study, I specifically test the null hypoth-
esis that estimates of neutral genetic variation are not
significantly different between populations in habitats not
disturbed by humans versus those in habitat subject to the
above types of human disturbance. My analyses are based
on a compilation of studies examining allozyme and mi-
crosatellite variation across a wide range of species. Other
studies have performed similar analyses (see Garner et al.
2005), but mine differs in (1) explicitly examining different
types of human disturbance, (2) excluding cases of dis-
turbances not directly related to human activity (i.e., sto-
chastic factors) (3) including more studies (and from a
wider range of taxa), and (4) examining effects of the age
and duration of disturbance.
Methods
I searched the literature for allozyme and microsatellite
data on genetic variation in disturbed or undisturbed pop-
ulations in nature. This process took the form of keyword
searches (genetic variation, heterozygosity, allelic diver-
sity, natural population, and population size) in Pubmed,
Web of Science, BIOSIS Previews, and BioOne databases.
Note that no keyword suggestive of disturbance was in-
cluded, thus avoiding a bias toward studies specifically
examining this effect. Keyword searches were then sup-
plemented by examining the literature cited section of
papers thus revealed.
Studies were included in the database if they met spe-
cific criteria. First, at least one of two relevant measures of
genetic variation had to be reported: mean number of al-
leles per locus or heterozygosity. The mean number of
alleles per locus is representative of the potential genetic
142 Conserv Genet (2008) 9:141–156
123
polymorphism, dictating the true limit of the response to
selection (Schoen and Brown 1993; Bataillon et al. 1996).
Heterozygosity is often thought of as a measure of actual
genetic diversity (Nei 1987). For each study, I averaged
population-specific values to obtain an overall value within
each study. Mean heterozygosities were arc-sine square
root transformed and number of alleles were log
10
-trans-
formed, which improved normality. Second, I avoided
pseudoreplication by using only a single study for a given
species, specifically the most recent study. Third, genetic
variation had to be reported for at least five microsatellite
or polymorphic allozyme loci. Fourth, at least ten indi-
viduals had to be sampled per population. Fifth, the pop-
ulations examined had to be natural, rather than domestic,
captive, or experimental.
Information recorded from each study included the
species, the number of populations sampled, the average
number of individuals per population, the type of marker
used, the number of loci, the mean number of alleles per
locus, and the mean observed and expected heterozygosity.
When loci deviated from Hardy–Weinberg equilibrium,
heterozygosity values were recalculated, where possible,
after eliminating those loci. This was done because the
causes of deviation from Hardy–Weinberg equilibrium
could be many (null alleles, admixture, selection), and the
specific cause is rarely known. Expected heterozygosities
were reported in most studies (87% of all papers collected),
and when they were not, I instead used observed hetero-
zygosities, which should be similar at equilibrium (Hedrick
2000).
Human disturbance within each study was categorized
as ‘‘hunting/harvest’’, ‘‘habitat fragmentation’’ (including
habitat loss), or ‘‘pollution’’. Studies of populations
experiencing natural disturbances, such as disease, preda-
tion, natural disasters, and fire, were excluded in an attempt
to restrict the focus to anthropogenic factors. If a popula-
tion suffered more than one type of disturbance (29% of
studies), it was included in the analysis for only the pri-
mary disturbance type mentioned in the publication (thus
preventing non-independent data points). Papers in which
the primary disturbance type was either not explicitly sta-
ted or unclear were excluded. When no disturbance was
noted in a study, the populations were considered
‘‘undisturbed’’. This was confirmed by reading relevant
references also cited within these papers. When studies
included both disturbed and undisturbed populations of the
same species, both were included in the analysis (see also
below). In the end, a total of 220 relevant publications were
identified (Appendix).
In order to consider the long-term effects of human
activity on genetic variation, disturbances were further
classified as to their time of origin and duration. A dis-
turbance was deemed ‘‘historic’’ if it had occurred and
ended prior to 1900. A disturbance was considered
‘‘recent’’ if it occurred after 1950. Few disturbances began
between 1900 and 1950 and were therefore not here con-
sidered. Further, a ‘‘short-term’’ disturbance is one that
occurred after 1950 and is still present, whereas a ‘‘long-
term’’ disturbance is one which began prior to 1950 and
persists to the present. These distinctions could not be
made for 26 studies, which were therefore excluded from
this part of the analysis.
Statistical analyses
Formal meta-analytic approaches require that studies report
measures of variability from which effect sizes can be
calculated (Arnqvist and Wooster 1995; Gurevitch and
Hedges 1999). This was not the case for many studies in
the database, and so I instead relied on conventional sta-
tistical tests. These tests may have lower power than formal
meta-analyses, but Type I error rates are at least similar
when the pattern of sampling-error variances is not sub-
stantially different among categories (Gurevitch and
Hedges 1999).
I first evaluated the relationship between the mean
number of individuals sampled in a study and the mean
number of alleles per locus (Von Segesser et al. 1999).
These variables were weakly, but significantly correlated
for microsatellites (r
2
= 0.061, P < 0.0001) and not sig-
nificant for allozymes (r
2
= 0.032, P = 0.10). Sample size
variation was therefore unlikely to affect interpretations
based on alleles per locus. I nevertheless repeated all
analyses (see below) after standardizing the number of
alleles by the number of sampled individuals. Standardized
and un-standardized estimates were significantly and pos-
itively correlated with each other (Pearson Product Mo-
ment: r = 0.58, P < 0.0001), and observed patterns were
similar in all cases. Analyses of numbers of alleles were
therefore based on unstandardized values.
Two types of analyses were performed. First, I com-
pared genetic variation among studies, which itself
involved several analyses. Second, I compared genetic
variation among populations within studies. All statistical
analyses were performed using SPSS v11.1 software, at the
a = 0.05 level of significance.
Genetic variation among studies was primarily analyzed
with MANOVAs. The dependent variables were numbers
of alleles and heterozygosity (referred to jointly as
‘‘genetic variation’’). The independent variables were
disturbance and molecular marker type (both fixed). These
analyses were supplemented by separate univariate ANO-
VAs for each marker type and genetic variance measure,
followed by Fisher’s LSD post hoc tests. This analysis was
repeated for only the two best-represented groups in the
database: mammals and plants, which ensured that
Conserv Genet (2008) 9:141–156 143
123
observed patterns were not dependant on particular dis-
turbance types having a disproportionate number of data
points from a particular taxon. In all instances, a full model
was first run and non-significant interactions were then
removed. Overall inferences about changes in genetic
variation were based on the MANOVAs, whereas infer-
ences about specific response variables were based on the
ANOVAs. These analyses should be broadly similar given
that the two genetic variation measures were strongly
correlated with each other (Pearson Product Moment,
r = 0.905, P < 0.0001). The data were treated in a similar
manner when the temporal effects of human disturbance
were considered (with time of origin or duration of a dis-
turbance as fixed factors).
Opposing effects in different taxa, however, may cancel
each other out in a metaanalysis (e.g., disturbance may lead
to a decrease in genetic diversity in mammals, but an in-
crease in birds, and thus no effect overall), and so a com-
parison among individual taxa is important. To test for
taxonomic effects, species were grouped into mammals,
birds, fish, herp-fauna (i.e., amphibians and reptiles),
invertebrates, and plants. These analyses included only
taxa with at least two disturbed and undisturbed species
and pooled the various disturbance types (to ensure suffi-
cient sample size). Similar to above, MANOVAs were
employed, with the numbers of alleles and heterozygosity
as dependent variables. In this case, however, the inde-
pendent variables were disturbance, molecular marker
type, and taxon (all fixed factors). These analyses were also
supplemented by separate univariate ANOVAs for each
marker type and genetic variation measure.
Variation within studies was analyzed by considering
differences between disturbed and undisturbed populations
within a given study (N = 50 studies). This analysis thus
controls for differences in the methodology employed by
each individual study (e.g., marker loci used, study species,
and sample size). Further, 11 of these data sets actually
included the same populations before and after human
disturbance, thus controlling for site-specific differences. In
particular, I used Wilcoxon Signed Rank t tests to assess
the relationship between mean heterozygosity in disturbed
versus undisturbed reference populations within the same
study and species. Heterozygosity is measured on a scale
ranging from 0 to 1 and thus lends itself to this type of
analysis.
Results
In analyses of variation among studies, genetic variation
was much higher for microsatellites than for allozymes
(MANOVA: F
2,270
= 290.98, P < 0.0001), and was also
influenced by disturbance type (MANOVA: F
6,540
= 2.86,
P = 0.009); different types of human disturbance had dif-
ferent genetic effects. In general, genetic variation in
undisturbed populations was significantly higher than that
in fragmented populations, non-significantly higher than
that in hunted/harvested populations, and non-significantly
lower than that in polluted populations (Table 1). For
allozyme markers in particular, disturbance had a signifi-
cant effect on the mean number of alleles per locus
(F
3,87
= 6.75, P < 0.0001) but not heterozygosity
(F
3,96
= 2.33, P = 0.08); fragmented populations had fewer
allozyme alleles than did polluted (P = 0.001), hunted/
harvested (P = 0.041), or undisturbed (P < 0.0001) popu-
lations. The same was true for the number of alleles
(F
3,192
= 3.23, P = 0.024) and heterozygosity
(F
3,197
= 2.24, P = 0.085) estimated with microsatellite
markers; fragmented populations had fewer microsatellite
alleles than did polluted (P = 0.041) or undisturbed
(P = 0.011) populations, although in this case, not hunted/
harvested (P = 0.459) populations. Thus, habitat frag-
mentation clearly had the strongest effect, consistently
decreasing genetic variation from background patterns.
The above trends were maintained when accounting for
possible effects of taxon. First, when species were grouped
into distinct taxa, genetic variation was typically (but not
always) lower in disturbed versus undisturbed populations
(Fig. 1A,B,C,D). Although marker type (MANOVA:
F
2,261
= 145.17, P < 0.0001) and taxon (MANOVA:
F
10,522
= 3.47, P < 0.0001) had a significant effect on
genetic variation, surprisingly disturbance did not (MA-
NOVA: F
2,261
= 1.88, P = 0.155). Disturbance effects
increased (and were significant), however, after removal
of pollution studies (MANOVA: marker type,
F
2,245
= 131.71, P < 0.0001; taxon, F
10,490
= 2.86,
P = 0.002; disturbed versus undisturbed, F
2,245
= 3.33,
P = 0.043), reinforcing the idea that pollution had quali-
tatively different effects than other types of disturbance
here considered. Following this modification, the mean
number of alleles per locus (allozyme: F
1,72
= 9.41,
P < 0.0001; microsatellite: F
1,185
= 3.62, P = 0.029), but
not heterozygosity (allozyme: F
1,81
= 1.98, P = 0.15;
microsatellite: F
1,189
= 2.52, P = 0.084), was significantly
lower in disturbed populations across all taxa. Second,
trends in genetic variation among the disturbance types
were similar (pollution > undisturbed > hunting/
harvest > fragmented) and significant (MANOVA:
F
6,354
= 2.12, P = 0.05), albeit marginally, when compar-
ing genetic variation estimates strictly within plants and
mammals (Table 2). Fragmented plant populations (dis-
turbance type: F
3,43
= 4.042, P = 0.031) had significantly
fewer allozyme alleles per locus than undisturbed
(P = 0.015) or polluted (P = 0.027) populations, whereas
fragmented mammalian populations (disturbance type:
F
1,4
= 14.59, P = 0.032) had significantly fewer allozyme
144 Conserv Genet (2008) 9:141–156
123
alleles than undisturbed populations (P = 0.032). Thus, the
observed differences in genetic variation among distur-
bance categories did not appear to be dictated by a single
taxonomic group.
Possible long-term effects of human disturbance on
genetic variation were also assessed, but only for micro-
satellite markers (Fig. 2A,B) due to small sample sizes for
allozymes. A subtle trend for a decrease in genetic varia-
Table 1 Mean allozyme and microsatellite genetic variation esti-
mates in ‘‘undisturbed’’ and ‘‘disturbed’’ populations (disturbance
categories: Hunting/Harvest, Habitat Fragmentation, and Pollution),
characterized as the mean number of alleles per locus (A) and
expected heterozygosity (H
e
)
Undisturbed Hunting/Harvest Fragmentation Pollution
Allozyme
b,c
A 2.13 ± 0.09
a
(46) 2.076 ± 0.34 (7) 1.56 ± 0.088
*
(30) 2.19 ± 0.17 (13)
H
e
0.19 ± 0.016 (48) 0.16 ± 0.028 (8) 0.14 ± 0.02
*
(33) 0.22 ± 0.036 (14)
Microsatellite
b,c
A 8.84 ± 0.57 (80) 6.89 ± 0.46 (49) 6.83 ± 0.52
**
(60) 13.12 ± 4.03 (6)
H
e
0.65 ± 0.018 (82) 0.60 ± 0.02 (50) 0.59 ± 0.023 (62) 0.70 ± 0.088 (7)
a
Values are means ± 1 SEM (N)
b
MANOVA tests were carried out for both estimators of genetic diversity (A and H
e
together), using disturbance and molecular marker type as
fixed factors. Univariate ANOVA tests were also conducted to identify case specific differences
c
An asterisk ‘‘*’’ indicates a significant difference from all other disturbance types, P < 0.05, whereas a double asterisk ‘‘**’’ indicates a
significant difference from polluted (P = 0.041) and undisturbed populations (P = 0.011) only
Mean heterozygosity
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
Undisturbed
Disturbed
Mean Heterozygosity
0.52
0.56
0.60
0.64
0.68
0.72
0.76
0.80
Undisturbed
Disturbed
Mean number of alleles per locus
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Undisturbed
Disturbed
A)
Mean number of alleles per locus
0
2
4
6
8
10
12
14
16
18
Undisturbed
Disturbed
B)
C)
D)
Mammals
Herp-Fauna
Birds
Fish
Plants
Invertebrates
)2(
)4(
)9(
)8(
)01(
)11(
)91(
)
5
2(
)94(
)27(
)4(
)31(
)01(
)8(
)4(
)7(
)6(
)6(
)8(
)8(
)2(
)4(
)9(
)8(
)51(
)
11
(
)
22(
)62(
)
9
4(
)
47(
)4(
)
31(
)11(
)9(
)5(
)7(
)6(
)
6
(
)8(
)8(
Mammals
Herp-Fauna
Birds
Fish
Plants
Invertebrates
Mammals
Herp-Fauna
Birds
Fish
Plants
Invertebrates
Mammals
Herp-Fauna
Birds
Fish
Plants
Invertebrates
Fig. 1 Number of alleles per locus (A, B) and heterozygosity (C, D)
across a wide range of animal taxa as a function of human
disturbance, investigated using both allozyme (A, C) and microsat-
ellite markers (B, D). Numbers in parentheses represent sample sizes
(N). All values are means ± SEM
Conserv Genet (2008) 9:141–156 145
123
tion with increasing time since disturbance was evident
(Fig. 2A) but non-significant (MANOVA: F
4,376
= 2.22,
P = 0.066). It was significant, however, when the number
of alleles (F
2,192
= 4.36, P = 0.014) and heterozygosity
(F
2,197
= 3.45, P = 0.034) were considered separately;
undisturbed populations had significantly more alleles
(P = 0.007) and higher heterozygosity (P = 0.017) than
populations that had experienced disturbances prior to the
1900s, which was not the case for more recent disturbances
(mean number of alleles per locus, P = 0.07; heterozy-
gosity, P = 0.099). Human disturbances of increasing
duration (Fig. 2B) also decreased genetic variation overall
(F
4,334
= 2.38, P = 0.045). It was only significant, how-
ever, for the mean number of alleles (F
2,171
= 3.77,
P = 0.025) and not heterozygosity (F
2,174
= 1.62, P = 0.2)
when considered separately. Populations experiencing
long-term disturbances had significantly fewer alleles than
undisturbed (P = 0.007) populations, and populations
subject to short-term disturbances (P = 0.046).
A more rigorous test of the effects of human disturbance
on genetic variation was performed by correlating hetero-
zygosity estimates from both disturbed and undisturbed
reference populations of the same species, reported within
the same study (Fig. 3). Variation within studies included
analyses for 8 mammals, 3 birds, 12 fishes, 3 herp-fauna,
10 invertebrates, and 14 plants. As might be expected,
genetic variation in disturbed and undisturbed populations
was strongly correlated across studies (Pearson Product
Moment: r = 0.93, P < 0.0001), but no consistent trend for
differences (i.e., disturbed versus undisturbed) was evident
when all disturbance types were considered together
(Wilcoxon Signed Rank t test: P = 0.31). However, nine of
the 12 studies showing qualitatively higher values in dis-
turbed populations were for instances of pollution, and so
polluted populations on their own had significantly higher
genetic variation than their undisturbed counterparts
(Wilcoxon Signed Rank t test: P = 0.045). When pollution
data were removed from the analysis, disturbed and
undisturbed heterozygosity estimates were significantly
different among the remaining categories (Wilcoxon
Signed Rank t test: P = 0.004), although, in this case,
indicating a consistent negative impact of human distur-
bance on genetic variation. I observed the same pattern
when the mean number of alleles per locus was analyzed in
this manner (data not shown).
Discussion
My goal was to evaluate the genetic impacts of different
types of human disturbance. I found that the direction of
responses, in terms of changes in neutral genetic variation
from undisturbed background patterns, were dependent on
the type of disturbance experienced. In general, fragmen-
tation reduced genetic variation, hunting/harvesting had no
appreciable effect, and pollution may actually increase
genetic variation, although this last effect was not signifi-
cant when tested directly. These results were largely con-
sistent across different taxa (Fig. 1, Table 2), and were
robust to differences in molecular marker types (allozymes
or microsatellites) and genetic variation estimators (num-
bers of alleles or heterozygosity). Interestingly, however,
the mean number of alleles per locus was more likely to
show significant differences than was heterozygosity. This
result fits with work showing that allelic diversity is af-
fected more by demographic disturbances than are other
estimates of neutral genetic variation (Hartl and Pucek
1994). Further, the observed patterns remained when the
number of alleles was expressed as a ratio of sample size,
indicating that my results were not driven simply by dif-
ferences in sampling effort.
Table 2 Mean allozyme and microsatellite genetic variation
estimates in ‘‘undisturbed’’ and ‘‘disturbed’’ populations of mam-
mals and plants (disturbance categories: Hunting/Harvest, Habitat
Fragmentation, and Pollution), characterized as the mean number of
alleles per locus (A) and expected heterozygosity (H
e
)
Undisturbed Hunting/Harvest Fragmentation Pollution
Mammals: Allozyme
b,c
A 2.75 ± 0.46
*,a
(2) NA 1.43 ± 0.13 (3) NA
H
e
0.34 ± 0.16 (2) NA 0.11 ± 0.051 (3) NA
Mammals: Microsatellite
b,c
A 8.18 ± 0.69 (49) 6.59 ± 0.55 (34) 6.17 ± 0.54 (38) NA
H
e
0.65 ± 0.026 (49) 0.60 ± 0.024 (35) 0.59 ± 0.029 (39) NA
Plants: Allozyme
b,c
A 1.99 ± 0.11
*
(20) 2.23 ± 0.49 (2) 1.68 ± 0.13 (18) 2.17 ± 0.21
*
(5)
H
e
0.21 ± 0.018 (22) 0.18 ± 0.03 (2) 0.16 ± 0.022 (20) 0.21 ± 0.035 (5)
Plants: Microsatellite
b,c
A 8.31 ± 1.074 (8) 8.27 ± 2.24 (5) 5.53 ± 2.00 (3) NA
H
e
0.62 ± 0.031 (8) 0.57 ± 0.061 (5) 0.51 ± 0.18 (3) NA
a
Values are means ± 1 SEM (N)
b
MANOVA tests were carried out for both estimators of genetic variation (A and H
e
together), using disturbance type, molecular marker type,
and taxon as fixed factors. Only categories represented by at least two samples were included in the analysis
c
An asterisk ‘‘*’’ indicates a significant difference from the fragmented group, P < 0.05
146 Conserv Genet (2008) 9:141–156
123
Could my findings be the result of a publication bias?
Such a bias could occur if studies reporting significant
results are more likely to be published (Arnqvist and
Wooster 1995; Gurevitch and Hedges 1999). This would be
a problem in my study if there was a bias toward publi-
cation of disturbed populations that show reductions in
genetic variation. Some such bias is possible but seems
unlikely to explain all the main trends. First, patterns of
genetic change were largely consistent across taxa,
molecular marker type, and genetic variation estimators.
Second, genetic changes owing to human disturbances are
likely underrepresented in this study, as species or popu-
lations driven to extinction by human activities were not
considered. Third, many of the studies included in the
database collected data for purposes mostly unrelated to
assessing the impacts of human disturbances on genetic
variation (e.g., social structure, breeding biology, or iso-
lation by distance). Fourth, the pollution data actually seem
to suggest an increase in genetic variation, indicating that
the decrease in fragmentation studies is unlikely to be just
the result of a bias.
Do my results reflect human effects? I specifically
examined disturbances attributable to humans, and so my
results clearly apply to that context. It is also possible,
however, that natural disturbances could have similar ef-
fects. Indeed, previous studies did not separate these effects
(Garner et al. 2005). My main goal, however, is to compare
different types of human disturbance, and so here infer-
ences do not depend on an understanding of the effects of
natural disturbances.
Undisturbed
sucol rep selella fo rebmun naeM
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
8.5
9.0
9.5
10.0
ytisogyzoreteh naeM
0.50
0.52
0.54
0.56
0.58
0.60
0.62
0.64
0.66
0.68
0.70
Mean number of alleles per locus
Mean heterozygosity
A)
B)
Historic disturbance
Recent disturbance
*
sucol rep selella fo rebmun naeM
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
7.0
7.5
8.0
8.5
9.0
9.5
10.0
yti
sogy
z
orete
h
naeM
0.50
0.52
0.54
0.56
0.58
0.60
0.62
0.64
0.66
0.68
0.70
Mean number of alleles per locus
Mean heterozygosity
Undisturbed
Short-term disturbance
Long-term disturbance
**
(80)
(82)
(13)
(13)
(100)
(103)
(80)
(82)
(55)
(55)
(37)
(39)
*
Fig. 2 Genetic variation (± SEM) in populations subject to historical
or recent (A) in addition to short-term or long-term human
disturbances (B) relative to undisturbed populations, considering
microsatellite marker data only. MANOVA tests were carried out for
both estimators of genetic variation (mean number of alleles per locus
and heterozygosity together), using time of origin or duration of
disturbance as fixed factors. Univariate ANOVA tests were also
conducted to identify case specific differences. An asterisk ‘‘*’’
indicates a significant difference from the undisturbed group only
(P < 0.05), whereas a double asterisk ‘‘**’’ indicates a significant
difference from both the undisturbed and short-term disturbance
group (P < 0.05). Numbers in parentheses represent sample sizes (N)
Habitat fragmentation
Hunting/Harvest
Pollution
Undisturbed heterozygosity
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Disturbed heterozygosity
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Habitat fragmentation
Hunting/Harvest
Pollution
Fig. 3 The relationship between disturbed and undisturbed hetero-
zygosity estimates reported within the same study (Pearson Product
Moment Correlation: r = 0.93, P < 0.0001), considering all catego-
ries of disturbance (N = 50). The line in bold represents a line of
unity, which is the point at which heterozygosity estimates in
disturbed and undisturbed populations are equal. Data points below
the line of unity indicate a negative impact of disturbance, whereas
points falling above the line are positively impacted by human
disturbance
Conserv Genet (2008) 9:141–156 147
123
Disturbance types
Fragmentation clearly decreases genetic variation. One
possible driver of this effect is reductions in population size
(Young et al. 1996). Another is reduced gene flow as a
result of habitat fragmentation (Frankham et al. 2002; Toro
and Caballero 2005). Habitat fragmentation may reduce
population size the most out of all disturbance types con-
sidered in this study, thus producing statistically significant
reductions in genetic variation. Unfortunately, few studies
provided estimates of census or effective population size,
preventing a proper test of the idea that population size is
heavily influencing the outcome. Alternatively, population
size may decrease substantially with all disturbance types,
and so the pronounced negative effect on genetic variation
in fragmented populations may be due to reduced dispersal.
Although previous work has shown a significant and po-
sitive relationship between population size and genetic
diversity (Frankham 1996), further studies, comparing
undisturbed and fragmented populations while controlling
for population size, would indicate whether factors above
and beyond population size are responsible for a lowering
of genetic variation. Nonetheless, habitat fragmentation
clearly has a significant impact on genetic variation in
natural populations, and so conservation case studies
involving fragmentation should be given priority.
Hunting/harvesting appeared to have little effect on
genetic variation. This is surprising given the rapid
reductions in population size generally associated with
hunting and harvesting practices. Thus, I would expect a
decrease in genetic variation owing to effects associated
with bottlenecks (i.e., genetic drift and inbreeding), and yet
I do not find this in my study. However, it should also be
noted that this relationship is not always as straightforward
as assumed, with past work identifying relatively abundant
species having limited variability and other endangered
populations maintaining high variability (for review see
Frankham 1995; Amos and Harwood 1998). Thus, other
factors may be involved, such as selection acting on spe-
cific genotypes, which are indirectly targeted by hunters
(Fitzsimmons et al. 1995; Coltman et al. 2003; Hartl et al.
2003). One possible explanation for our results, however, is
that hunting/harvest reduces population size to a lesser
extent than other types of disturbance (i.e., fragmentation),
and so the effects are weaker or more inconsistent (and thus
non-significant).
Pollution appeared as though it might have a positive
impact on genetic variation. I make this inference because
every genetic variation measure was qualitatively greater
for populations subject to pollution than for those in
undisturbed conditions, although only some of these were
significant owing to small sample sizes (Table 1). More-
over, comparisons within studies suggested a similar effect
(Fig. 3), and negative genetic impacts of human distur-
bance were only evident when pollution data were removed
from several analyses. Whether or not pollution increases
genetic variation, it clearly has a qualitatively different
effect than fragmentation, as evidenced by the significantly
greater number of alleles and higher heterozygosity in
polluted populations (Table 1). Thus, I suggest that pollu-
tion can have both positive and negative effects through
different mechanisms. On the one hand, pollution may
decrease population size (Posthuma and Van Straalen
1993) or increase selection for homozygous genotypes
(Keane et al. 2005), which would decrease genetic varia-
tion. Indeed, some studies have clearly found reductions in
genetic variation because of pollution (e.g., Ma et al. 2000;
Belfiore and Anderson 2001). On the other hand, pollution
could increase mutation rates at marker loci (Yauk and
Quinn 1996; Baker et al. 2001) or increase selection for
heterozygotes (Falconer and MacKay 1996). The net effect
of pollution on genetic variation should therefore reflect a
balance between these various forces.
That being said, conservation biologists may need to
consider genetic threats from pollution carefully, separat-
ing them from other forms of human disturbance. Given the
general belief that the maintenance of genetic variation is
healthy in natural populations, in the short term, polluted
populations may appear to be doing well genetically. Long-
term effects of pollution, however, which may include
adverse effects on the physiology of an organism and its
environment as well as a possible increase in mutational
load, are all detrimental to a population’s viability.
Time of origin and duration of disturbance
The level of genetic variation maintained within a popu-
lation may also be dependant on both the time of origin and
duration of a particular human disturbance (Frankham
2003, 2005). Although rare alleles are likely the first to be
lost, a long-term disturbance, acting over many genera-
tions, will cause the loss of more common alleles and a
steeper decline in genetic variation (Lande 1988). In fact, a
prolonged disturbance would likely leave a more distinct
genetic ‘‘footprint’’ within a population than a transient
challenge. My findings support this idea, with short-term
disturbances having a lesser effect on genetic variation than
long-term ones. Further, populations that had experienced
historic disturbances were associated with a lower level of
genetic variation than those disturbed only recently, sug-
gesting that within-population genetic variation may be
sensitive to the temporal scale of human-related activities.
Although, increased conservation efforts in recent years
could also explain the trend for higher genetic variation in
populations disturbed only within the last 50 years.
148 Conserv Genet (2008) 9:141–156
123
Future considerations
The loss of genetic variation may not only affect organisms at
the population level but lead to the loss of entire species
given enough time, thus, the maintenance of genetic variation
is of critical importance. But why is it important to under-
stand genetic effects in natural populations specifically
attributable to human activity? First, in order to mitigate
against loss of genetic variation, it is essential we understand
the source or cause. Second, by identifying specific human
activities related to detrimental genetic effects we can either
eliminate the source of the impact altogether or seek viable,
less intrusive alternatives. Finally, a more comprehensive
knowledge of past or current genetic impacts on natural
populations may increase our predictive power and ability to
control future impacts. This information would be of par-
ticular use to incorporate into existing models and simulation
programs directed at threatened or endangered populations,
where direct sampling is limited or often impossible. Al-
though this issue merits further consideration, my study has
provided essential baseline information which will facilitate
future comparisons, and presents the most comprehensive
assessment of genetic variation in human impacted popula-
tions to date.
The weak patterns of neutral genetic change observed in
this study, despite large sample sizes in general, do raise
one concern. Genetic variation is overwhelmingly moni-
tored by neutral molecular variation in natural populations
(Frankham et al. 2002) and so it was used in this study.
However, there is a growing debate about whether
molecular measures of genetic variation reflect adaptive
differences among populations, or even the ability to re-
spond to future environmental changes (Reed and Frank-
ham 2001). Most environmental changes associated with
human activities will affect different morphological or life-
history traits of particular species, thus quantitative genetic
variation may serve as a more sensitive bioindicator. In
fact, a recent simulation study found that some human
impacts on genetic variation could not be detected with
neutral molecular markers, but only become apparent when
changes in quantitative genetic variation were assessed
(Carvajal-Rodrı
´
guez et al. 2005). Thus, although logisti-
cally difficult, a comprehensive assessment of quantitative
genetic variation in natural populations may be the only
means of estimating the ‘‘true’’ magnitude of human-re-
lated genetic effects.
Acknowledgments This study was supported by a postgraduate
fellowship from NSERC. Thanks are extended to A. Garner, J.L.
Rachlow, and J.F. Hicks for providing a complete reference list from
their recent paper in Conservation Biology. Thanks also to A.P.
Hendry, K.A. Feldheim, J. Bates, K. Gilmour, the Field museum
journal club, and two anonymous referees for providing comments on
an earlier version of this manuscript.
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... All rights reserved Kinnunen, Bowman, & Garroway, 2020). Mammals are the most well-studied taxa in urban evolutionary ecology (Miles et al., 2019;Schell, 2018) and they tend to adhere to the expectation of increased drift and genetic differentiation in disturbed environments (DiBattista, 2008;Schmidt et al., 2020). Whether these effects are generalizable across other groups is unclear (Miles et al., 2019). ...
... Overall, our results add to existing evidence that genetic diversity in amphibians is not affected by urban development or human disturbance in ways that are easily generalizable across species (Browne et al., 2009;Coster, Babbitt, Cooper, & Kovach, 2015;Furman et al., 2016;Fusco et al., 2020;Homola et al., 2019;Lourenço et al., 2017;Nowakowski et al., 2018;Peterman et al., 2015;Purrenhage et al., 2009;Wilk et al., 2020). This contrasts similar multi-species assessments that found consistent effects of urbanization on birds and mammals (DiBattista, 2008;Schmidt et al., 2020). ...
... It appears general effects of urbanization are not discernible within or across amphibian species, as we did not detect any relationships even at the most local scale (30 m impervious surface) after applying analytical techniques capable of detecting weak effects using data from multiple species. This contrasts with consistent interspecific patterns of reduced genetic diversity and increased differentiation in mammals (DiBattista, 2008;Schmidt et al., 2020). ...
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Human land transformation is one of the leading causes of vertebrate population declines. These declines are thought to be partly due to decreased connectivity and habitat loss reducing animal population sizes in disturbed habitats. With time, this can lead to declines in effective population size and genetic diversity which restrict the ability of wildlife to efficiently cope with environmental change through genetic adaptation. However, it is not well understood whether these effects generally hold across taxa. We address this question by repurposing and synthesizing raw microsatellite data from online repositories for 19 amphibian species sampled at 554 georeferenced sites in North America. For each site, we estimated gene diversity, allelic richness, effective population size, and population differentiation. Using binary urban-rural census designations, and continuous measures of human population density, the Human Footprint Index, and impervious surface cover, we tested for generalizable effects of human land use on amphibian genetic diversity. We found minimal evidence, either positive or negative, for relationships between genetic metrics and urbanization. Together with previous work on focal species that also found varying effects of urbanization on genetic composition, it seems likely that the consequences of urbanization are not easily generalizable within or across amphibian species. Questions about the genetic consequences of urbanization for amphibians should be addressed on a case-by-case basis. This contrasts with general negative effects of urbanization in mammals and consistent, but species-specific, positive and negative effects in birds.
... Formal meta-analytic approaches also require that studies report measures of variability from which effect sizes can be calculated, but this was not the case for many studies in our database. We instead relied on conventional statistical tests (see below; also see Carlson & Seamons, 2008;Darimont et al., 2009;DiBattista, 2008;Sanderson et al., 2022). It should be noted that the primary focus of many of the included studies was not to directly interrogate the differences between insular versus non-insular populations, and so there should be no systematic bias between these categories. ...
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We conducted a quantitative literature review of genetic diversity (GD) within and among populations in relation to categorical population size and isolation (together referred to as “insularity”). Using populations from within the same studies, we were able to control for between‐study variation in methodology, as well as demographic and life histories of focal species. Contrary to typical expectations, insularity had relatively minor effects on GD within and among populations, which points to the more important role of other factors in shaping evolutionary processes. Such effects of insularity were sometimes seen—particularly in study systems where GD was already high overall. That is, insularity influenced GD in a study system when GD was high even in non‐insular populations of the same study system—suggesting an important role for the “scope” of influences on GD. These conclusions were more robust for within population GD versus among population GD, although several biases might underlie this difference. Overall, our findings indicate that population‐level genetic assumptions need to be tested rather than assumed in nature, particularly for topics underlying current conservation management practices. We conducted a quantitative literature review of genetic diversity (GD) within and among populations in relation to categorical population size and isolation (together referred to as “insularity”). Contradictory to typical expectations, we found that insularity had relatively minor effects on GD within and among populations, which points to the more important roles of other factors in shaping evolutionary processes. Our findings indicate that population‐level genetic assumptions need to be tested rather than assumed in nature, particularly for topics underlying current conservation management practices.
... In contrast to historical events, anthropogenic disturbance can affect genetic diversity and population structure operating at smaller spatial and temporal scales. Under a habitat disturbance scenario, genetic diversity and gene flow are differentially affected depending on life-history traits, such as lifespan, lifeform or self-compatibility (DiBattista, 2008;González et al., 2020), and on key ecological interactions such as pollination (Aguilar et al., 2006;Albrecht et al., 2016;Schleuning et al., 2015) and seed dispersal (Fontúrbel, Candia, et al., 2015;Markl et al., 2012;McConkey et al., 2012). Thus, the genetic diversity and differentiation patterns that we observe today are the result of both geographical and anthropogenic disturbance processes, but their relative contribution to the final outcome is rarely assessed. ...
Article
Genetic differentiation depends on ecological and evolutionary processes that operate at different spatial and temporal scales. While the geographical context is likely to determine large-scale genetic variation patterns, habitat disturbance events will likely influence small-scale genetic diversity and gene flow patterns. Therefore, the genetic diversity patterns that we observe today result from the combination of both processes, but they are rarely assessed simultaneously. We determined the population structure and genetic diversity of a hemiparasitic mistletoe (Tristerix corymbosus) from the temperate rainforests of southern Chile to determine the effects of the geographic context and habitat disturbance at a regional scale and if it is affected by the abundance and occurrence of its seed disperser mutualist (the arboreal marsupial Dromiciops gliroides). We genotyped 359 individuals from 12 populations using SNPs, across three different geographic contexts and four disturbance conditions. We also used camera traps to estimate the abundance and occurrence of the seed disperser. Our results suggest that genetic differences among populations are more related to the geographical context than to habitat disturbance. However, as disturbance increased, D. gliroides abundance and occurrence decreased, and mistletoe inbreeding index (FIS) increased. We also found highly uneven gene flow among study sites. Despite the high levels of disturbance that these temperate rainforests are facing, our results suggest that mistletoe genetic differentiation at a regional scale was more influenced by historical events. However, habitat disturbance can indirectly affect mistletoe population genetic differentiation via the seed dispersal process, which may increase inbreeding levels.
... La biodiversité est actuellement menacée par les activités d'une espèce en particulier : l'espèce humaine ( Figure 1) (Díaz et al., 2019 ;Dirzo et Raven, 2003 ;Duraiappah et al., 2005 ;Ceballos et al., 2015 ;Pereira et al., 2012 ;Sala et al., 2000 ;Vitousek et al., 1997). En effet, les activités humaines sont responsables du déclin et de la disparition de nombreuses espèces (Ceballos et al., 2015 ;Díaz et al., 2019 ;Dirzo et al., 2014) et elles bouleversent les patrons de diversités spécifique et génétique (DiBattista, 2008 ;Garner et al., 2005 ;Miraldo et al., 2016) 1 . Alors que la pollution des milieux (Penuelas et al., 2013) et le changement climatique (Bellard et al., 2012) modifient entre autres les aires de distribution potentielle des espèces, l'introduction d'espèces exotiques invasives bouleverse les interactions entre espèces (Vitousek et al., 1996). ...
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La connectivité écologique des habitats est nécessaire aux processus écologiques assurant le maintien de la biodiversité. Des méthodes ont donc été développées pour la modéliser afin de comprendre précisément son influence et d’orienter les mesures de conservation de la biodiversité. Parmi ces méthodes, les graphes paysagers modélisent un réseau d’habitat sous la forme d’un ensemble de taches d’habitat (noeuds) reliées par des chemins de dispersion potentiels (liens). La validité écologique de ces outils nécessitait néanmoins d’être évaluée à l’aide de données reflétant les réponses biologiques des populations à la connectivité de leurs habitats. Les données génétiques permettent cette validation car la structure génétique des populations dépend notamment des flux génétiques entre leurs taches d’habitat. La structure génétique peut également être modélisée par un graphe génétique dont les noeuds correspondent à des populations et dont les liens sont pondérés par le degré de différenciation génétique entre populations. L’objectif de cette thèse était d’utiliser conjointement des graphes génétiques et paysagers pour (i) évaluer la validité écologique des graphes paysagers et (ii) améliorer notre compréhension de la relation entre connectivité et structure génétique. Après avoir identifié les méthodes de construction et d’analyse des graphes génétiques les plus adaptées à chaque contexte et développé un outil informatique permettant l’utilisation conjointe des graphes génétiques et paysagers, nous les avons comparés dans le cadre de deux études empiriques. Elles ont permis (i) d’évaluer l’influence respective des différentes composantes de la connectivité des habitats sur la diversité et la différenciation génétiques et (ii) de confirmer la validité écologique des graphes paysagers. Nous avons ensuite montré que l’intégration de variables associées à la fois aux noeuds et aux liens de ces deux types de graphes améliorait l’estimation de l’influence des éléments du paysage sur la connectivité. Les méthodes développées dans cette thèse pourraient trouver d’autres applications dans ce champ d’étude comme dans d’autres. Nous espérons que les résultats de cette thèse et l’outil informatique développé y contribueront.
... While clonality provides advantages to individual genets, high levels of genetic diversity within populations enhance ecosystem recovery after extreme events and is key for the longevity of those populations in a rapidly changing climate (Baums, 2008;Baums et al., 2019;Booy, Hendriks, Smulders, Groenendael, & Vosman, 2000;DiBattista, 2008). The decline of coral reefs has led to an increased interest in coral restoration efforts worldwide (reviewed in (Boström-Einarsson et al., 2020), but one concern is that the newly restored population will have less genetic diversity than the original population due to few donor colonies or small or non-existent genetic diversity among the donor colonies (Baums, 2008;Baums et al., 2019;Shearer, Porto, & Zubillaga, 2009), leading to genetic swamping or maladaptation. ...
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Spatial genetic structure (SGS) is important to a population’s ability to adapt to environmental change. For species that reproduce both sexually and asexually, the relative contribution of each reproductive mode has important ecological and evolutionary implications because asexual reproduction can have a strong effect on SGS. Reef building corals reproduce sexually, but many species also propagate asexually under certain conditions. In order to understand SGS and the relative importance of reproductive mode across environmental gradients, we evaluated genetic relatedness in almost 600 colonies of Montipora capitata across 30 environmentally characterized sites in Kāne’ohe Bay, O’ahu, Hawai’i using low-depth restriction digest associated sequencing. Clonal colonies were relatively rare overall but influenced SGS. Clones were located significantly closer to one another spatially than average colonies and were more frequent on sites where wave energy was relatively high, suggesting a strong role of mechanical breakage in their formation. Excluding clones, we found no evidence of isolation by distance within sites or across the bay. Several environmental characteristics were significant predictors of the underlying genetic variation (including degree heating weeks, time spent above 30°C, depth, sedimentation rate and wave height); however, they only explained 5% of this genetic variation. Our results show that colony fragmentation contributes to the ecology of M. capitata at local scales and that genetic diversity is maintained despite strong environmental gradients in a highly impacted ecosystem, suggesting potential for broad adaptation or acclimatization in this population.
... Recent analyses show that genetic diversity has declined globally over the past century in wild populations (Leigh et al., 2019), that geographic ranges are shrinking, resulting in dramatic losses of genetically distinct populations for most species (Ceballos et al., 2017), and that remaining genetic diversity is not well safeguarded in situ or ex situ (Khoury et al., 2019;Hoban et al., 2020b). Major drivers of genetic diversity loss include climate change, habitat fragmentation and destruction, overharvest, and reduction of population sizes (IPBES, 2019;CBD, 2014;DiBattista, 2008;Aguilar et al., 2008;Pinsky and Palumbi, 2014;Schlaepfer et al., 2018). In spite of this, biodiversity assessments often exclude genetic diversity (Vernesi et al., 2008;Laikre et al., 2010;Pierson et al., 2016), with some exceptions (see Santamaría and Mendez, 2012). ...
Article
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International agreements such as the Convention on Biological Diversity (CBD) have committed to conserve, and sustainably and equitably use, biodiversity. The CBD is a vital instrument for global conservation because it guides 195 countries and the European Union in setting priorities and allocating resources, and requires regular reporting on progress. However, the CBD and similar policy agreements have often neglected genetic diversity. 2 Genetic monitoring Target 13 Indicators This is a critical gap because genetic diversity underlies adaptation to environmental change and ecosystem resilience. Here we aim to inform future policy, monitoring, and reporting efforts focused on limiting biodiversity loss by conducting the largest yet evaluation of how Parties to the CBD report on genetic diversity. A large, globally representative sample of 114 CBD National Reports was examined to assess reported actions, progress, values and indicators related to genetic diversity. Although the importance of genetic diversity is recognized by most Parties to the CBD, genetic diversity targets mainly addressed variation within crops and livestock (a small fraction of all species). Reported actions to conserve genetic diversity primarily concerned ex situ facilities and legislation, rather than monitoring and in situ intervention. The most commonly reported status indicators are not well correlated to maintaining genetic diversity. Lastly, few reports mentioned genetic monitoring using DNA data, indigenous use and knowledge of genetic diversity, or development of strategies to conserve genetic diversity. We make several recommendations for the post-2020 CBD Biodiversity Framework, and similar efforts such as IPBES, to improve awareness, assessment, and monitoring of genetic diversity, and facilitate consistent and complete reporting in the future.
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Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well‐being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within‐species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: (i) Genetic Diversity; (ii) Genetic Differentiation; (iii) Inbreeding; and (iv) Effective Population Size (Ne). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large‐scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long‐term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally.
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Many of the 8 extant bear species have large ranges, yet range-wide studies of genetic diversity are often impractical because of logistic challenges or focus on local questions. However, understanding the levels of diversity among populations of a species can be useful for conservation and management. Bear researchers were at the forefront of using microsatellites to study the demographics and diversity of populations, such that 3 species have complete sampling and 3 others are represented across their range breadth. Yet there has not been a synthesis of these data within or among species because of difficulties comparing microsatellites. We extracted microsatellite summary statistics from 104 papers that sampled 284 populations of any species within Ursidae, then yardstick-transformed the data for direct comparison. Studies had a median of 2 geographic sites, 30 individuals sampled per site, and 12 loci genotyped. We identified 193 loci genotyped in bears and argue this is a limitation within and among species comparisons. Tremarctos ornatus had the lowest average range-wide genetic diversity (Ar = 2.5; He = 0.43), although ascertainment bias may affect the results, whereas Ursus arctos had the highest diversity (Ar = 6.4; He = 0.69). We argue that at the spatial scale of a species' range, variation due to phylogeography and anthropogenically influenced diversity will overwhelm accuracy issues between studies and reveal broad spatial patterns. Further, by comparing allelic richness to heterozygosity across the range of a species, managers may identify populations in need of genetic management. We end by summarizing what is known about within-species lineages and genetic diversity and identify priority areas for future studies.
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Humans are dominant global drivers of ecological and evolutionary change, rearranging ecosystems and natural selection. In the present article, we show increasing evidence that human activity also plays a disproportionate role in shaping the eco-evolutionary potential of systems—the likelihood of ecological change generating evolutionary change and vice versa. We suggest that the net outcome of human influences on trait change, ecology, and the feedback loops that link them will often (but not always) be to increase eco-evolutionary potential, with important consequences for stability and resilience of populations, communities, and ecosystems. We also integrate existing ecological and evolutionary metrics to predict and manage the eco-evolutionary dynamics of human-affected systems. To support this framework, we use a simple eco–evo feedback model to show that factors affecting eco-evolutionary potential are major determinants of eco-evolutionary dynamics. Our framework suggests that proper management of anthropogenic effects requires a science of human effects on eco-evolutionary potential.
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We have developed microsatellite or simple sequence repeat (SSR) genetic markers for the tropical tree Pithecellobium elegans (Mimosoideae). The frequency of this class of marker is estimated and the level and distribution of variability at these markers is assessed and contrasted to that found at isozyme markers in the same populations. The results indicate that SSR loci are powerful tools for the analysis of population structure and that, in these populations, they provide a means of accurately examining two important parameters in conservation biology, gene flow and paternity.
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Horizontal starch gel electrophoresis of enzymes and multivariate analysis of morphometric variations were used to compare the genetic structure of cicada populations, Magicicada cassini, collected from a radionuclide contaminated site with those collected from four reference sites. Homogeneity was observed between sites at the phosphoglucomutase (PGM) and alpha-glycerophosphate dehydrogenase (α-GPDH) loci. Heterogeneity was found among populations within the contaminated site at the α-GPDH loci. The esterase (EST-2,3,5) loci examined were heterogeneous between sites and among populations. With few exceptions little morphometric variation was discovered between cicada populations. However, more morphometric variation was observed among populations within sites. The data indicate that population genetic structure of cicadas from the uranium production facility was not affected by soil contamination. Morphological patterns were unique in cicadas from one population at the facility.