BIODIVERSITY
ESEARCH
Fragmentation and comparative genetic
structure of four mediterranean woody
species: complex interactions between life
history traits and the landscape context
Abelardo Aparicio1*, Arndt Hampe2,, Laura Fernández-Carrillo1 and Rafael
G. Albaladejo1
1
Departamento de Biologı́a Vegetal y Ecologı́a,
Universidad de Sevilla, c/Prof. Garcı́a
González no 2, 41012 Sevilla, Spain,
2
Departamento de Ecologı́a Integrativa,
Estación Biológica de Doñana (EBD-CSIC),
Av. Américo Vespucio s/n, 41092 Sevilla,
Spain
ABSTRACT
Aim The effect of habitat fragmentation on population genetic structure results
from the interaction between species’ life history traits and the particular
landscape context, and both components are inherently difficult to tease apart.
Here, we compare the genetic (allozyme) structure of four co-occurring woody
species with contrasting life histories to explore how well their response to the
same fragmentation process can be predicted from their functional traits.
Location A highly fragmented forest landscape located in the lower Guadalquivir
catchment, south-western Spain.
Methods We sampled four species (Cistus salviifolius, Myrtus communis, Pistacia
lentiscus and Quercus coccifera) from the same 23 forest fragments known to form
a representative array of habitat characteristics in the region. We assessed genetic
diversity (A, He and Ng) and differentiation (FIS and FST) for each species and
explored their potential drivers using a model-selection approach with four
fragment features (size, historical and current connectivity, and stability) as
predictor variables.
Results Regional-scale genetic diversity increased from the shortest-lived to the
longest-lived species, while population differentiation of the self-compatible
species was roughly double that of the three self-incompatible species. Fragment
size was the only feature that did not consistently affect the genetic diversity of
local populations across all species. Three species showed signs of being affected
by fragmentation, yet each responded differently to the set of fragment features
considered. We observed several trends that were at odds with simple life historybased predictions but could arise from patterns of gene flow and/or local-scale
demographic processes.
Main conclusions Our comparative study of various landscape features and
*Correspondence: Abelardo Aparicio,
Departamento de Biologı́a Vegetal y Ecologı́a,
Universidad de Sevilla, c/Prof. Garcı́a González
no 2, 41012 Sevilla, Spain.
E-mail: abelardo@us.es
,
Present address: INRA, UMR1202
Biodiversité, Gènes & Communautés, 69 Route
d’Arcachon, F-33610 Cestas, France.
species underscores that the same fragmentation process can have very different,
and complex, consequences for the population genetic structure of plants. This
idiosyncrasy renders generalizations across natural systems very difficult and
highlights the need of context-oriented guidelines for an efficient conservation
management of species-rich landscapes.
Keywords
Conservation genetics, gene flow, genetic diversity, habitat fragmentation, life
history traits.
INTRODUCTI O N
The large-scale transformation of landscapes and the
resulting fragmentation of natural habitats are considered
a major modern threat to global terrestrial biodiversity (Sala
et al., 2000). To assess how habitat loss and fragmentation
affect the genetic structure, fitness and viability of those
populations that persist in remnant habitat patches is a
central purpose of conservation biology (Young & Clarke,
2000). A wealth of case studies have been performed worldwide over the past two decades and the majority reported
overarching negative effects (Fahrig, 2003). However, the
complexity and idiosyncrasy of study systems represent a
challenge for attempts to extract generalizable principles and
to identify key determinants of species’ vulnerability to
habitat fragmentation (Hobbs & Yates, 2003; Lindenmayer
et al., 2008).
The consequences of fragmentation for the genetic structure
of plant populations arise from the interplay of two components: (1) the functional attributes, or life history traits, of the
species in question and (2) the actual landscape context. Both
influence the effective size and the landscape-scale connectivity
of populations, two fundamental characteristics that revert
into their genetic structure and diversity. Expected consequences of fragmentation include a rapid reduction in genetic
variation because of bottlenecks, as well as a successive
decrease in heterozygosity and accumulation of recessive
deleterious alleles because of genetic drift and elevated
inbreeding. These trends should ultimately result in reduced
individual growth and fecundity, elevated offspring mortality,
and eventually population extinction (Barret & Kohn, 1991;
Ellstrand & Elam, 1993; Young et al., 1996; Picó & van
Groenendael, 2007). Empirical evidence confirms that allelic
richness, gene diversity, heterozygosity, and different measures
of individual fitness tend to be tightly related with population
size (Leimu et al., 2006; Honnay & Jacquemyn, 2007; Aguilar
et al., 2008). However, results also show that individual
species respond very differently to fragmentation depending
on their life history traits. Among the numerous traits
examined (e.g. ploidy, mating system, modes of pollen and
seed dispersal, longevity or clonality), mating system – and
specifically the ability to self – appears to play a major role in
determining species’ vulnerability to fragmentation (Aguilar
et al., 2008).
While the role of different life history traits for the
response of populations to fragmentation has recently been
addressed by various meta-analyses (e.g. Leimu et al., 2006;
Honnay & Jacquemyn, 2007; Aguilar et al., 2008), similar
attempts have not been made for parameters of the
landscape context. Most life history traits are relatively easy
to classify and hence amenable for meta-analytical
approaches that can pool diverse case studies conducted on
species sharing the same trait. In contrast, measures of
landscape structure are more complex, usually quantitative
and cannot easily be grouped across studies. Moreover,
different landscape parameters tend to act in concert and
hence need to be considered simultaneously to understand
their respective influence on population genetic structures.
Hence, other approaches than those used so far have to be
adopted for assessing which landscape characteristics tend to
affect population responses to fragmentation across species
(analogue to the question which life history traits affect
population responses to fragmentation across different landscapes).
A potentially powerful yet very rarely attempted study
approach consists in comparing the population genetic structure of species with contrasting life histories that co-occur
across the same fragmented landscape (Hobbs & Yates, 2003;
see also Berge et al., 1998). Given a consequential sampling
design that minimizes differences in the spatial distribution
and management history of the populations sampled, such a
study should permit quantifying to which extent differences in
life history traits are reflected in the population genetic
structure of individual species, and to assess whether some
common relationships between landscape characteristics and
population genetic structures can be detected across species
regardless of their mutual differences. Such comparative
studies require a great sampling effort and hence cannot
consider too many species simultaneously; however, this
limitation is outweighed by their ability to identify complex
interactions between life history traits and (multiple) landscape
characteristics that are not detectable otherwise. Hence, both
approaches can provide highly complementary biological
insights.
Here, we compare the population genetic structure of four
woody species with contrasting life history traits across a
regional mosaic of forest fragments in south-western Spain.
Based on abundant previous knowledge on the distribution
and abundance of the target species, we were able to sample
all four species from exactly the same 23 forest fragments
known to form a broad yet representative array of habitat
characteristics (Aparicio, 2008; Aparicio et al., 2008). This
sampling permitted a hierarchical study with two levels:
species (focussing on life history traits) and populations
(focussing on fragment features). Specifically, we examine the
following questions: (1) Do several estimates of genetic
diversity and its spatial organization differ among species in
accordance with their life history traits (mating system,
longevity and mode of pollen and seed dispersal; Hamrick
& Godt, 1996; Nybom, 2004; Duminil et al., 2007)? (2) Which
relations exist between species’ genetic population structure
and a series of landscape-related predictor variables commonly considered to influence effective population size and
connectivity? (3) Can we infer from the life history traits of a
species which landscape characteristics influence its genetic
population structure (e.g. do self-incompatible, long-lived
species respond primarily to the size or the stability of
fragments)? Addressing these issues within a framework that
considers both multiple species and multiple landscape
characteristics should help progress towards a better understanding of why species respond so differently to landscape
fragmentation.
227
METH ODS
Study area and previous information on species
distributions
Study organisms
We focussed on four woody species – Cistus salviifolius L.
(Cistaceae), Myrtus communis L. (Myrtaceae), Pistacia lentiscus
L. (Anacardiaceae) and Quercus coccifera L. (Fagaceae) – that
will hereafter be referred to as Cistus, Myrtus, Pistacia and
Quercus, respectively. All four species are widespread and
common members of sclerophyllous forests and woodlands in
the study region. We selected this combination of species
because they either share or contrast in several life history traits
considered to influence population genetic structure (e.g.
Hamrick & Godt, 1996; Nybom, 2004; Duminil et al., 2007,
2009): mating system, longevity, and mode of pollen and seed
dispersal (see Table 1). Hence, our selection aimed rather at
maximizing the variation of different life history traits than at
seeking replicates for just a single trait. This strategy focusses
on depicting the complexity of interactions between various
life history traits and landscape characteristics in shaping
genetic population structures, instead of testing for the effect of
a particular trait–landscape combination.
Cistus is a hermaphroditic, self-incompatible, entomophilous
shrub up to 90 cm tall. Its seed dispersal is primarily
barochorous, although some dispersal by ants is likely to
occur. Plant longevity does not exceed 20 years (ArianoutsouFaraggitaki & Margaris, 1982). Cistus is an efficient colonizer of
disturbed areas, being subsequently out-competed by taller
woody species.
Myrtus is a hermaphroditic, self-compatible and entomophilous shrub up to 4 m tall, whose berries are regularly dispersed
by small- to mid-sized birds and small mammals (Traveset
et al., 2001). Plants can live more than 100 years, although the
size of individuals encountered in our populations suggests
that relatively few reach such an age.
Pistacia is a dioecious, wind-pollinated shrub or tree up to 4 m
tall, whose drupes are primarily dispersed by small- to midsized birds (Jordano, 1989). The species is slow-growing and
individuals can become over 200 years old.
Quercus is a monoecious, wind-pollinated shrub or tree up to
10 m tall, probably self-incompatible (Ducousso et al., 1993)
whose acorns are locally dispersed by rodents (scatter-hoarding
birds such as jays are rare in the study area) (Pons & Pausas,
2007). The species experiences clonal growth and genets
probably live several centuries.
The study was conducted in the lower catchment of the river
Guadalquivir in south-western Spain, an agricultural landscape
that covers 21,000 km2 (Fig. 1). This area has lost much of its
original forest cover since pre-Roman times (Valbuena-Carabaña et al., 2010) and harbours a forest mosaic within an
agricultural matrix. The landscape is of relictual type (sensu
McIntyre & Hobbs, 1999) with very low habitat retention
(c. 1%), low connectivity between fragments and a high degree
of anthropization (concerning both fragments and the surrounding matrix). We could draw on abundant information for
this study thanks to a previous, exhaustive floristic-ecological
survey of the lower Guadalquivir catchment that identified and
investigated a total of 535 forest fragments in the area (Aparicio,
2008). Cistus, Myrtus, Pistacia and Quercus were recorded in
296, 128, 287 and 169 of these fragments, respectively. All four
species occurred together in 64 fragments.
Sampling and molecular analyses
Out of these 64 patches, we selected 23 fragments well spread
out across the whole study area (Fig. 1) that we considered to
be representative while spanning a large range of characteristics
(i.e. area, isolation and population sizes). All selected fragments were surrounded by a continuous agricultural matrix
and had well-defined edges. Within each fragment, we sampled
young leaves from up to 30 adult plants per species
(average = 27.8). To preclude sampling ramets of the same
genet, only individuals growing at least 10 m apart were
collected.
Protein extract electrophoreses were run in 10% starch gels
following general protocols (Weeden & Wendel, 1989). We
assayed a total of 30 enzyme systems in three different buffer
systems (morpholine–citrate, pH = 6.1; lithium–borate/
tris-citrate, pH = 8.1; and histidine–citrate, pH = 6.5) and
finally used a total of 10–13 systems per species that showed
consistent, readily scoreable and interpretable banding patterns (for details see Table S1 in Supporting Information). We
obtained allozyme profiles for a total of 2559 individual plants
(Cistus: 678; Myrtus: 662; Pistacia: 655; Quercus: 564).
Independence of allozyme loci in each species was assessed
through linkage disequilibrium tests implemented in FSTAT
2.9.3 (Goudet, 2001). Then, we characterized the patterns of
Table 1 Functional traits of the four studied species.
Cistus
Myrtus
Pistacia
Quercus
Mating system
Pollen dispersal
Seed dispersal
Vegetative growth
Longevity*
Self-incompatible
Self-compatible
Dioecious
Self-incompatible
Insects (Coleoptera, Hymenoptera, Diptera)
Insects (Hymenoptera, Diptera)
Wind
Wind
Gravity
Small-sized birds
Small-sized birds
Rodents
Not resprouting
Resprouting
Resprouting
Vegetative propagation
< 20 years
> 100 years
> 200 years
Centuries
*Information from the literature and unpublished data.
Figure 1 Geographic location of the forest mosaic in the lower Guadalquivir catchment (south-western Spain). Circles indicate all forest
fragments in the area (n = 535) with circle size proportional to fragment area on a logarithmic scale. Solid circles represent the 23 fragments
sampled for this study.
genetic variation both for each species as a whole and for
individual fragments. We calculated the number of alleles per
locus (A), Nei’s within-population gene diversity or expected
heterozygosity (He), and the percentage of unique multilocus
genotypes per population (Ng), as well as the withinpopulation inbreeding coefficient (FIS) and the level of
among-population genetic differentiation (FST) (Weir &
Cockerham, 1984). For the latter, we calculated both the
global FST (for analyses at species level) and the average
pairwise FST (for analyses at population level). We confirmed
by means of rarefaction that A was hardly affected by the
slight differences in sample size. Departures from zero for FIS
and FST values were assessed through constructing 95%
confidence intervals by bootstrapping over loci. Finally, we
examined the spatial distribution of genetic variation under an
isolation-by-distance model by correlating matrices of geographical and Rousset’s genetic distances (Rousset, 1997) with
Mantel tests. All analyses were performed in FSTAT 2.9.3
(Goudet, 2001) or GIMLET 1.3.3 (Valiè re, 2002). We assume
that the obtained species-level patterns of genetic variation
reflect to a reasonable extent the ‘original’ variation of species
in the region (thereby allowing to trace the effects of their life
history traits).
Fragment characteristics
We characterized each of the 23 fragments using information
from two collections of aerial digital orthophotos (available at
http://desdeelcielo.andaluciajunta.es) dating from 1956 and
2002, respectively. This information allowed us to derive a
series of predictor variables related to the size of fragments and
their spatial arrangement within the landscape. Specifically, we
considered the following predictors:
1. Fragment size: We determined this variable from the 2002
aerial photographs. A complementary analysis showed that the
variable was closely correlated with population size in Cistus
(r = 0.78) and Myrtus (0.76), and somewhat less in Pistacia
(0.48). (Population sizes were determined in small fragments
by counting all individuals and in large fragments by counting
the individuals in 30 randomly placed sampling plots
(10 · 10 m for Pistacia and Myrtus, and 5 · 5 m for Cistus)
and extrapolating it to the total fragment area; Quercus was not
censused because its clonal growth renders the identification of
individuals very difficult).
2. Current connectivity: We computed this variable in
Fragstats 3.3 (McGarigal et al., 2002) as the sum of the
forest area (m2) divided by the square of the nearest edge-toedge distance between the focal fragment and all fragments
within a specified radius. After trying several distances (200,
500, 1000, 2000, 5000 and 10,000 m) and finding that
estimates were highly correlated, we used the 10,000 m
radius as the most integrative representation of the landscape.
3. Historical connectivity: We measured the net increase/
decrease in the amount of forest habitat between 1956 and 2002
within a specified buffer area around the centroid of the focal
fragment. After trying several areas and finding that estimates
were highly correlated, we decided to retain the 500 ha buffer.
4. Fragment stability: We generated this variable by clipping
the ad hoc 2002 digital coverage on that from 1956 and
measuring which percentage of the current fragment had
already been existing five decades earlier (as opposed to the
percentage of recently colonized terrain).
Further details regarding fragment characteristics and the
predictor variables can be found in Table S2 of the Supplementary Information.
229
Model building and selection
RE S UL T S
In accordance with previous analyses (Leimu et al., 2006;
Honnay & Jacquemyn, 2007; Aguilar et al., 2008), we used the
diversity measures A, He and Ng as response variables.
Moreover, we considered the two measures of genetic structure
FIS and average pairwise FST.
First, we performed analyses of covariance (ANCOVAs)
with species identity and fragment characteristics as independent variables and genetic estimates for the individual
populations as dependent variables. In these models, firstorder effects indicate whether a given fragment characteristic
affects patterns of genetic variation across all four species,
whereas interaction terms indicate whether species respond
differently to landscape features. We performed separate
analyses for the measures of genetic structure (FIS and
average pairwise FST) but assembled the three diversity
measures (A, He and Ng) within a single multiple analysis of
covariance (MANCOVA). This seems justified as they are
conceptually related and showed similar patterns of variation
(see Results).
Second, we used ordinary least squares (OLS) linear regression models to address, for each study species, specific
relationships between the four explanatory variables and the
five genetic parameters. Prior to model construction, all
predictor and response variables were checked for normality
and transformed when necessary; predictor variables were
moreover tested for non-collinearity using Pearson correlations
(allowed threshold: r = |0.6|). We ranked the resulting models
following a model-selection approach on the basis of the Akaike
information criterion corrected for small sample size (AICc)
(Burnham & Anderson, 2002). Because Cistus showed a weak
yet significant spatial autocorrelation, AICc values for this
species were calculated with their ‘spatially-corrected’ associated variances (Olalla-Tá rraga et al., 2006). We retained all
equivalent models with a DAICc (i.e. the difference between the
AICc of each model and the minimum AICc found among all
competing models) value £ 2 and also showing statistical
significance (P < 0.05) under the classical hypothesis testing
framework. For each retained model, we calculated the
associated R2-value. OLS regression models and Akaike
values calculation were carried out with sam 3.0 (Rangel et al.,
2006).
Loci and alleles scored
A total of 30 of the 46 loci tested were polymorphic and
produced a total of 135 alleles (see Table S1 in Supporting
Information). Quercus contained 47 alleles, followed by
Pistacia and Cistus with 32 each, and by Myrtus with 24. A
total of five, three and one alleles were restricted to a single
fragment in Quercus, Cistus and Pistacia, respectively.
Genetic diversity and structure at species level
Species-level estimates of genetic diversity and differentiation
are summarized in Table 2. All three diversity measures (A, He
and Ng) increased consistently in the order Cistus < Myrtus < Pistacia < Quercus. Pistacia was the only species that
showed a significant deviation from Hardy–Weinberg equilibrium with a moderate heterozygote deficit (FIS = 0.122)
(although all four species had some populations with heterozygote deficit or excess; see Table S3 of the Supplementary
Information for detailed results). Finally, population differentiation was low albeit significant. Myrtus showed the highest
global FST (0.064), clearly exceeding the values of the other
three species (0.025–0.038). We found no association between
genetic and geographic distance except for Cistus, which
showed a weak pattern of isolation by distance (r = 0.205,
P = 0.027).
Relationships between genetic structure and
fragment features
The MANCOVA on the three measures of genetic diversity
(A, He and Ng) revealed that species were significantly affected
by most landscape features (Table 3). Interestingly, the only
variable that did not influence all four species strongly enough
to produce a statistically significant effect was fragment size.
On the other hand, the significant interaction terms of the
MANCOVA model indicated that species tended to respond
differently to all landscape features considered (although the
effect of historical connectivity was only marginally significant:
P = 0.087). The ANCOVAs that we performed with FIS and
FST did not generate any significant effects (either for
Table 2 Measures of genetic diversity (mean ± SE) and F-statistics (with 95% CI) of the four species investigated.
Parameter
Cistus
Myrtus
Pistacia
Quercus
A
He
Ng
FIS
FST
1.385 (0.027)
0.049 (0.003)
0.286 (0.020)
0.016 ()0.012 to 0.087)
0.037 (0.015 to 0.052)
1.442 (0.029)
0.088 (0.005)
0.416 (0.027)
)0.026 ()0.052 to 0.026)
0.064 (0.045 to 0.085)
1.692 (0.030)
0.122 (0.004)
0.604 (0.026)
0.122 (0.025 to 0.384)
0.038 (0.017 to 0.082)
2.239 (0.085)
0.154 (0.005)
0.711 (0.025)
0.011 ()0.003 to 0.040)
0.025 (0.015 to 0.032)
A, mean number of alleles per locus; He, Nei’s within-population gene diversity or expected heterozygosity; Ng, percentage of unique multilocus
genotypes per population; FIS, within-population inbreeding coefficient; FST, among-population genetic differentiation.
Table 3 Results of multivariate analysis of covariance (MANCOVA) examining the effect of species identity and landscape
variables on measures of genetic diversity (A, He and Ng).
Effect
Species
Size
Current connectivity
Historical connectivity
Stability
Species · size
Species · current
connectivity
Species · historical
connectivity
Species · stability
Wilk’s
lambda
F
d.f.
P
0.536
0.964
0.863
0.857
0.818
0.743
0.686
5.531
0.867
3.718
3.886
5.175
2.458
3.167
9
3
3
3
3
9
9
< 0.001
0.463
0.015
0.013
0.003
0.012
0.001
0.809
1.722
9
0.087
0.721
2.722
9
0.005
predictors or interaction terms), except for the factor species
on FIS values (F = 3.067, d.f. = 3, P = 0.033). This effect
reflects the fact that Pistacia showed a significant departure
from Hardy–Weinberg equilibrium while the other species did
not (see also Table 2).
The OLS regressions produced a total of 63 models with
DAICc £ 2. However, only 11 were statistically significant
(P < 0.05). These models had a moderate to reasonably high
explicative power (0.19 < R2 < 0.43). Table 4 summarizes
results of the OLS analysis. Significant models were generated
for A, He and FIS of two species each, respectively. No
significant model was found for the variables Ng and FST. There
were three cases in which a given species counted with more
than one model; however, all ‘secondary’ models shared the
same major predictors and very similar trends with the
corresponding best-fit model (i.e. model no. 1 in Table 4).
The results shown in Table 4 indicate that no single
fragment characteristic explained patterns of genetic diversity
or structure consistently across all four species; instead, trends
were strongly species specific. Fragment size was the only
feature that affected genetic estimates of Myrtus, being
positively related with A and He and negatively with FIS. The
two measures of fragment connectivity showed a clear positive
relationship with A values of Quercus. Fragment stability had a
somewhat weaker positive effect on A values of this species
while it was negatively related with its He levels. Fragment
stability also had a negative effect on FIS values of Cistus.
Finally, trends were too weak and/or inconsistent to generate
any significant model for the estimates Ng, FST, and for the
species Pistacia.
DI S C USS I O N
In their influential review on fragmentation effects in plants,
Hobbs & Yates (2003, p. 482) conclude that ‘there is much to
be gained from comparative studies that include a range of
species selected to have different functional attributes’. Our
study involves only one landscape and four species, and its
power of generalization can therefore not compete with metaanalytical approaches. Our analyses are also limited by the
comparatively low polymorphism of the allozyme markers
used. Notwithstanding, our comparison illustrates that the
same fragmentation process can have very different, and
complex, consequences for the population genetic structure of
plants. These cannot easily be predicted from plant functional
traits.
Genetic variation at species level: relationships with
life history traits
Breeding system and life form are commonly considered the
two major determinants of genetic structure and diversity in
natural plant populations (Hamrick & Godt, 1996; Nybom,
2004; Glémin et al., 2006; Duminil et al., 2007, 2009).
Table 4 Standardized coefficients of the multiple OLS regression models examining effects of fragment features on genetic diversity and
differentiation.
Response variable
Species
Model no.
A
Myrtus
Quercus
1
1
2
1
1
2
3
1
2
3
1
He
FIS
Myrtus
Quercus
Cistus
Myrtus
Size
Current
connectivity
Historical
connectivity
0.674
0.642
0.590
0.588
0.465
0.457
0.212
)0.542
)0.512
)0.545
)0.513
)0.516
)0.401
Stability
0.435
0.229
0.658
0.244
0.197
0.203
)0.465
R2 (%)
P
AICc
18.9
35.8
40.9
43.3
29.4
35.3
33.3
26.4
30.5
29.6
21.6
0.038
0.035
0.041
< 0.001
0.007
0.013
0.017
0.012
0.026
0.030
0.025
)24.208
26.306
28.101
)117.077
)108.565
)107.592
)106.906
)41.152
)39.517
)39.223
)49.148
Only significant models (P < 0.05) with DAICc £ 2 are shown (see Methods for further details).
A, mean number of alleles per locus; He, Nei’s within-population gene diversity or expected heterozygosity; FIS, within-population inbreeding
coefficient; AICc, Akaike information criterion corrected for small sample size; OLS, ordinary least squares.
231
Long-lived and primarily outcrossing species typically display
greater within-population diversity and lower among-population differentiation than short-lived and predominantly selfing
species. Four of our five genetic parameters were in line with
these trends. In contrast, and in line with Duminil et al.
(2007), we found no evidence that the mode of pollen or seed
dispersal plays a major role for the regional-scale genetic
population structure of our species.
All three diversity measures (A, He and Ng) increased clearly
and consistently from the shortest-lived to the longest-lived
species (Cistus < Myrtus < Pistacia < Quercus). This relationship appears especially remarkable because extremely few
empirical studies have to date described effects of longevity or
generation time per se on the genetic diversity of woody plant
populations (Petit & Hampe, 2006). Instead, the plant growth
form is typically used as a proxy (commonly with a notably
coarse distinction between annuals, herbaceous perennials and
woody perennials), which makes it difficult to distinguish the
respective effects of several mutually associated life history
traits (e.g. longevity, stature and mating system; Hamrick &
Godt, 1996; Petit & Hampe, 2006; Duminil et al., 2007, 2009).
Population differentiation was strongest in the only selfcompatible species Myrtus, whose FST value was roughly
double that of the other three species. This trend is likewise in
line with expectations because Myrtus experiences non-negligible selfing in our study area (González-Varo et al., 2009,
2010; note that self-compatibility does not automatically imply
frequent selfing; Goodwillie et al., 2005) and should therefore
be particularly susceptible to genetic drift. Finally, FIS is the
only parameter at odds with expectations (Duminil et al.,
2009), as signs of some inbreeding at species level appeared
only in the long-lived and dioecious Pistacia. Our finding
might indicate that populations of the other three species are
on average (still) too large and well connected to experience
notable inbreeding (cf. Angeloni et al., 2011).
Genetic variation at population level: effects of
different landscape features
Differences between populations were too small and/or
inconsistent to produce readily interpretable global results
for the two measures of genetic structure. This is not surprising
because at least FST tends to respond slowly to fragmentation
processes (Landguth et al., 2010). Our MANCOVA on the
three diversity measures revealed consistent effects of fragment
connectivity and stability across all species, whereas we failed
to detect a similar relationship for fragment size. The latter
result is particularly noteworthy because fragment or population size is by far the most commonly used predictor variable
in research on the genetic consequences of fragmentation
(including the cited meta-analyses on life history traits). The
most likely explanation of our finding rests on the character of
our study system, well depicted by Kramer et al. (2008, p. 878;
see also Bacles & Jump, 2011): ‘Fragment boundaries often do
not represent boundaries for mating populations of trees that
benefit from long-distance pollination… Where fragments do
not delineate populations, genetic theory of small populations
does not apply’. In such a context, our results suggest that the
population genetic diversity of our four species could be
influenced primarily by patterns of among-fragment gene flow
(reflected in the effect of fragment connectivity) and/or withinfragment population dynamics (reflected by the effect of
fragment stability). Our results illustrate why genetic studies of
fragmentation effects ought to analyse genetic parameters
across different spatial scales (or, ideally, use modern landscape
genetics approaches).
Our failure to find an overall effect of fragment size on
genetic diversity does not imply that none of the four species
were affected by the size of fragments. Instead, the significant
interaction terms of the MANCOVA model demonstrate that
species differed in their response to all four landscape features
that we considered. This is what one would expect given their
differences in life history traits and the proven effects of these
traits for the genetic diversity of fragmented populations
(Leimu et al., 2006; Honnay & Jacquemyn, 2007; Aguilar et al.,
2008). The subsequent OLS analysis allowed us to assess
whether the response of species was actually in agreement with
expectations based on their life history traits.
Species-specific responses to different landscape
features
Ordinary least squares models indicated that three of our four
species (Cistus, Myrtus and Quercus) experienced some trends
that could be interpreted as consequences of fragmentation.
However, each responded differently to the landscape
features that we considered. Fragment size governed both the
genetic diversity and the structure of Myrtus, whereas fragment
connectivity and stability triggered the diversity of Quercus.
Levels of inbreeding in Cistus depended primarily on fragment
stability, whereas trends in Pistacia were too inconsistent to
generate any readily interpretable result.
The behaviour of Myrtus agrees with simple models of
fragmentation that directly link the genetic diversity of
populations with their effective size. This appears particularly
remarkable because self-compatible species tend to be less
affected by small population size than self-incompatible species
(Leimu et al., 2006; Honnay & Jacquemyn, 2007). The most
likely reason of this apparent contradiction is again the nature
of our study system. Populations are neither very small nor
highly isolated, and their genetic structure and diversity should
therefore primarily be governed by patterns of long-distance
gene flow (Kramer et al., 2008). Whereas many self-incompatible species respond to a scarcity of local mates with an
increased frequency of long-distance pollination events (Sork
& Smouse, 2006; Kramer et al., 2008), Myrtus responds with
increased selfing (Gonzá lez-Varo et al., 2009, 2010; see also
Goodwillie et al., 2005). This response should reduce gene flow
and favour drift (Duminil et al., 2009), explaining the observed
relevance of fragment size for levels of genetic diversity and
inbreeding in Myrtus populations. The effectivity of this
process is reflected by the fact that fragment size explains as
much as 43% of the total variation in He of our Myrtus
populations (see Table 4).
Interesting inferences can also be drawn from the other two
relationships identified. First, fragment connectivity was more
determinant than fragment size for the maintenance of allelic
richness in Quercus. Oaks are known to experience spatially
very extensive pollen gene flow (Lepais et al., 2009), and it is
therefore unsurprising that the larger landscape context
overwhelms possible effects of fragment size. However, the
clear positive effect of fragment connectivity on allelic richness
also indicates that even Quercus stands are far from panmictic.
Second, the importance of fragment stability for expected
heterozygosity of Quercus and inbreeding in Cistus indicates
that both measures should be primarily determined by
population dynamics within fragments. We can only speculate
about the particular demographic processes involved (e.g.
local-scale colonization events should be more frequent in
unstable than in stable fragments). Notwithstanding, our
finding seems notable given that within-fragment processes
are usually not considered in relation with fragmentation in
strict sense (Fahrig, 2003).
CON C L US I ONS
This study illustrates to our belief that much can still be gained
from comparative studies, especially when these are based on a
consequential sampling of populations. The approach adopted
here provides a highly complementary perspective to metaanalytical species comparisons. These enquire for example
whether fragment size affects self-incompatible species more
strongly than self-compatible species. We ask instead whether
fragment size affects a particular species more strongly than
fragment connectivity or stability, and whether this may be due
to the species’ functional attributes.
Our simultaneous consideration of both various landscape
features and various species allows to fully appreciate the
complexity and individualistic nature of species’ responses to
fragmentation that meta-analyses need to blind out to
‘generalize the idiosyncratic’ (Hobbs & Yates, 2003). Results
represent a cautionary tale against notions that overemphasize
the role of population size as single predominant driver of
genetic diversity in fragmented plant populations. Ultimately,
our study also underpins that disentangling the respective
influence of life history traits and the landscape context on
species’ genetic makeup is, at best, a challenging task (cf.
Aguilar et al., 2008).
The individualistic response of species to fragmentation
processes represents a great challenge for an efficient conservation of species-rich landscapes. It is therefore tempting to
think that certain key life history traits of species could help
inform – and thus greatly simplify – the development of
management responses to the fragmentation of such landscapes (Lindenmayer et al., 2008). Our study indicates, however, that it may be a good investment to spend some effort in
a more thorough evaluation of species’ functional attributes
and ecological strategy (i.e. their natural history; Margules &
Pressey, 2000; Pressey, 2004) that keeps the complexity of real
landscapes in mind.
ACKNO W LEDGEMENT S
Financial support was provided by the Fundació n BBVA,
the Spanish Ministerio de Ciencia e Innovació n (grants
CGL2004-0002/BOS and RYC-2008-02603) and the Regional
Government (Junta de Andalucı́a, Proyecto de Excelencia
PR06-RNM-01499). The Andalusian Regional Government
also provided the aerial digital orthophotos. We are indebted
to Miguel Á ngel Fortuna, Xavier Picó, Jordi Bascompte, Jose
Marı́a Iriondo, Miguel Verdú and four anonymous referees for
valuable comments and criticisms on previous drafts of the
manuscript.
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S U P P O RT I NG I N F O R M ATI O N
Additional Supporting Information may be found in the online
version of this article:
Table S1 Enzyme systems and number of loci that showed
consistent, scoreable and interpretable banding patterns in the
studied species.
Table S2 Fragment characteristics and explanatory variables
used to build the linear regression models.
Table S3 Population genetic parameters at fragment level for
each species.
As a service to our authors and readers, this journal provides
supporting information supplied by the authors. Such materials are peer-reviewed and may be re-organized for online
delivery, but are not copy-edited or typeset. Technical support
issues arising from supporting information (other than missing
files) should be addressed to the authors.
BIOSKETCHES
This contribution stems from the EVOCA research team (http://
grupo.us.es/grnm210) whose work focusses on the ecology,
evolution and conservation of mediterranean plant species.
Author contributions: A.A. designed the research, assisted field
work and computed predictor variables; L.F.-C. and R.G.A. led
field and laboratory work and performed statistical analyses;
A.H. led the writing.
Editor: Andrew Lowe
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