ORIGINAL ARTICLE

doi:10.1111/j.1558-5646.2009.00825.x

DEMOGRAPHIC SOURCE-SINK DYNAMICSRESTRICT LOCAL ADAPTATION IN ELLIOTT’SBLUEBERRY (VACCINIUM ELLIOTTII)Jill T. Anderson1,2,3 and Monica A. Geber1,4

1Ecology and Evolutionary Biology Department, Corson Hall, Cornell University, Ithaca, New York 148533E-mail: jill.anderson@duke.edu4E-mail: mag9@cornell.edu

Received February 24, 2009

Accepted August 6, 2009

In heterogeneous landscapes, divergent selection can favor the evolution of locally adapted ecotypes, especially when interhabi-

tat gene flow is minimal. However, if habitats differ in size or quality, source-sink dynamics can shape evolutionary trajecto-

ries. Upland and bottomland forests of the southeastern USA differ in water table depth, light availability, edaphic conditions,

and plant community. We conducted a multiyear reciprocal transplant experiment to test whether Elliott’s blueberry (Vaccinium

elliottii) is locally adapted to these contrasting environments. Additionally, we exposed seedlings and cuttings to prolonged

drought and flooding in the greenhouse to assess fitness responses to abiotic stress. Contrary to predictions of local adaptation,

V. elliottii families exhibited significantly higher survivorship and growth in upland than in bottomland forests and under drought

than flooded conditions, regardless of habitat of origin. Neutral population differentiation was minimal, suggesting widespread

interhabitat migration. Population density, reproductive output, and genetic diversity were all significantly greater in uplands

than in bottomlands. These disparities likely result in asymmetric gene flow from uplands to bottomlands. Thus, adaptation to

a marginal habitat can be constrained by small populations, limited fitness, and immigration from a benign habitat. Our study

highlights the importance of demography and genetic diversity in the evolution of local (mal)adaptation.

KEY WORDS: Adaptation, flooding, gene flow, microsatellite markers, population structure, reciprocal transplant.

Environmental heterogeneity results in varying patterns of natu-

ral selection across the landscape (e.g., Heywood 1991; Dudley

1996; Nagy and Rice 1997). Divergent selection in alternate habi-

tats promotes adaptation of populations to local conditions (e.g.,

Hedrick 1986) and can drive differentiation in phenotypic and

phenological traits (e.g., Byars et al. 2007; Lowry et al. 2008).

If individuals mate assortatively, or hybrids exhibit reduced vi-

ability and fecundity, local adaptation can reproductively isolate

populations and foster incipient ecological speciation (Rieseberg

and Willis 2007; Lowry et al. 2008; Schluter 2009). Pervasive

interhabitat gene flow, in contrast, unifies populations and can

2Present address: Department of Biology, PO Box 90338, Duke Uni-

versity, Durham, North Carolina, 27708.

constrain the evolution of specialization because immigrants in-

troduce maladapted alleles and decrease the frequency of locally

adapted ecotypes (e.g., Slatkin 1985; Holt and Gomulkiewicz

1997; Stanton et al. 1997; Storfer et al. 1999; Hendry et al. 2002;

Langerhans et al. 2003).

This framework assumes that the quality of habitat patches

is relatively similar across the landscape; however, if habitat size

differs or fitness varies with habitat, source-sink dynamics can

influence the evolutionary trajectory of a species (Pulliam 1988;

Stanton and Galen 1997; Stanton et al. 1997; Turelli 1997). In

this scenario, the majority of the population is found in the source

habitat and natural selection favors traits that maximize fitness

there (Kawecki 2008). Source-sink dynamics can hinder adaptive

evolution in marginal habitats especially when adaptation to the

3 7 0C© 2009 The Author(s). Journal compilation C© 2009 The Society for the Study of Evolution.Evolution 64-2: 370–384

SOURCE-SINK DYNAMICS RESTRICT ADAPTATION

low-quality habitat comes at a cost of fitness in the source (Holt

and Gaines 1992; Kawecki 1995; Dias 1996; Kawecki 2008).

Even when habitat patches are equal in quality, asymmetrical

gene flow can establish source-sink dynamics (Kawecki and Holt

2002). For example, Mediterranean blue tits (Parus caeruleus)

inhabit both evergreen and deciduous forests and these habitats

differ in area across the landscape (Dias and Blondel 1996). This

species has the genetic variation necessary to adapt to both for-

est types, but source-sink dynamics result in local maladaptation

to the less common habitat within a region (Dias and Blondel

1996). Thus, evolution in heterogeneous landscapes depends on

the strength of divergent selection, the extent of genetic isolation

of populations in contrasting habitats, and differences in popula-

tion sizes and fecundity (Turelli 1997; Kawecki and Ebert 2004;

Leimu et al. 2006; Kawecki 2008).

The balance between migration and selection has long been

a central focus of evolutionary theory (Haldane 1930) and is

believed to be a driving force behind population divergence

and phenotypic evolution (Slatkin 1985; Hendry et al. 2001;

Lenormand 2002; Porter and Johnson 2002; Latta 2003). The-

oretical models predict that maladapted alleles can be maintained

in populations when gene flow swamps the effects of local selec-

tion (e.g., Hendry et al. 2001). Recently, a number of empirical

studies have demonstrated the constraining effects of gene flow on

local adaptation in vertebrates (Storfer et al. 1999; Hendry et al.

2002; Langerhans et al. 2003) and invertebrates (Nosil and Crespi

2004). Nevertheless, the importance of interhabitat gene flow in

natural plant populations remains unresolved. Plant populations

often adapt to very localized conditions due to their sedentary

nature, and strong selection can sustain population differentiation

despite extensive gene flow (Sambatti and Rice 2006). More em-

pirical studies are needed to analyze explicitly the influence of

gene flow, habitat quality, genetic variation, and population size

on the evolution of local adaptation in plants.

Our study examined the evolutionary dynamics of a peren-

nial shrub, V. elliottii Chapm. (Ericaceae), which inhabits both

upland and bottomland forests in the southeastern United States

(Radford et al. 1968; Godfrey and Wooten 1981). Bottomland

forests are dynamic systems that experience annual floods (Burke

et al. 1999) and have significantly greater soil moisture, bulk

density, and nutrient concentrations, and lower light levels than

upland forests (Anderson 2009). In contrast, drought stress can

be pronounced in the nutrient-poor sandy soils of upland forests

(Megonigal et al. 1997; Burke et al. 1999). Thus, divergent selec-

tion could lead to different phenotypic optima in these contrast-

ing habitats. Nonetheless, upland forests have greater density of

V. elliottii adults than bottomland forests (Anderson, pers. obs.),

suggesting that source-sink dynamics could influence adaptive

evolution in this species (Leimu et al. 2006; Kawecki 2008). We

designed our study to test whether spatial heterogeneity favors

local adaptation to contrasting habitats or interhabitat gene flow

restricts adaptive population differentiation, potentially resulting

in local maladaptation in ecologically marginal populations. We

selected upland and bottomland populations that abutted a sharp

ecotone, as well as more remote populations. This design per-

mitted us to test whether remote populations expressed a greater

degree of local adaptation than ecotonal populations, where inter-

habitat gene flow is likely to be high. To address our objectives, we

(1) conducted a multiyear reciprocal transplant experiment across

a complex gradient in hydrology, soil chemistry, and light avail-

ability; (2) isolated the effects of flooding and drought on plant fit-

ness in a greenhouse experiment; (3) analyzed genetic population

differentiation using microsatellite markers; and (4) implemented

a demographic study. This study advances our understanding of

the evolutionary dynamics of long-lived woody species, which are

understudied relative to herbaceous annuals and biennials (e.g.,

Leimu et al. 2006; Leimu and Fischer 2008).

Materials and MethodsFOCAL SPECIES

V. elliottii, a species of highbush blueberry reaching 1–3 m in

height, is widely distributed throughout the Southeast in season-

ally flooded bottomland and xeric upland forests (Radford et al.

1968; Godfrey and Wooten 1981). Bottomland and upland popu-

lations of this species are fully intercompatible. In a complemen-

tary study, we conducted cross-pollinations between individuals

in three upland and three bottomland populations in 2005 and

2006. Interhabitat crosses produced similar quantities of seeds

as intrahabitat crosses, seeds from both types of crosses germi-

nated readily and seedling survivorship has not varied by cross

type (J. T. Anderson, unpubl. data). Vaccinium flowers are insect-

pollinated and the seeds are animal-dispersed (Martin et al. 1951);

therefore, substantial gene flow between populations is possible,

potentially leading to low levels of population genetic differenti-

ation (Loveless and Hamrick 1984). Naturally recruited individ-

uals from upland and bottomland forests exhibit distinct foliar

and root-based phenotypes, which may be related to water stress

(Anderson 2009).

STUDY SYSTEM

The primary field site, Beidler Forest (N 33◦12, W 080◦18) in

the Four Holes Swamp watershed in the coastal plain of South

Carolina, consists of approximately 6475 hectares of bottomland

hardwood and swamp forests with conservation easements in xeric

upland forests (Porcher 1981; N. Brunswig, pers. comm.). Four

Holes Swamp is a diffuse brown-water floodplain system, which

averages 1.5–2.5 km wide (Porcher 1981). We also sampled pop-

ulations in the Pee Dee and Santee watersheds; however, popula-

tion genetic analyses were restricted primarily to the Four Holes

EVOLUTION FEBRUARY 2010 3 7 1

J. T. ANDERSON AND M. A. GEBER

Watershed (see Table S1 and Fig. S1 for geographical coordinates

of populations). All three sites lie within the Coastal Plain of South

Carolina and have similar average temperatures and rainfall lev-

els (NOAA 2002). In these watersheds, we sampled 7–9 popula-

tions from each of four forest types (32 total populations): remote

bottomlands (0.75–1.04 km from the nearest upland forest), re-

mote uplands (0.8–3.7 km from the nearest bottomland forest),

ecotonal uplands and their corresponding ecotonal bottomlands

(ecotonal populations <0.05 km apart). We located populations

with GIS-based maps from the U.S. Fish and Wildlife Service,

which identify habitats using National Wetland Indicator habitat

codes; this strategy minimized environmental differences between

sites within each habitat. The plant species composition of upland

and bottomland forests differs substantially (Porcher 1981) and

V. elliottii is the only species that was abundant enough in both

habitats for this study. In our statistical analyses (described be-

low), we distinguished between the effects of habitat of origin

(hereafter: habitat) and population proximity to the alternate habi-

tat (hereafter: proximity; coded as ecotone or remote).

Interannual variation in flooding duration is high in bottom-

land hardwood forests. Floods in bottomland forests of Four Holes

Swamp have lasted a total of 3–139 days/year since 1977 (aver-

age ± SD: 43.6 ± 36.1 days/year; Brunswig, N. and Dawson, M.,

Audubon Society, unpubl. data). Flood waters are only several

centimeters deep during flood events in this habitat. Precipitation

records at the field site also show periods of infrequent rainfall,

which ranges from 0 to 376.7 mm/month during the growing

season (average ± SD: 125.3 ± 79.8 mm/month; Brunswig and

Dawson, unpubl. data); this variability can result in drought stress

in upland forests. Additionally, soil nutrient levels are signifi-

cantly higher in the clay-rich soils of the bottomlands and light

availability in the understory is significantly lower under the dense

canopy of bottomland forests (Anderson 2009).

DEMOGRAPHY

To determine whether population size and reproductive fitness

varied by habitat, we established two 50 m × 10 m transects per

site in each of two remote and ecotonal upland and bottomland

habitats in April 2008 (n = 8 sites; 13 total transects; only one

transect was used at each of three sites). In both transects per site,

we recorded the abundance of adult plants (>50 cm tall, with

stems >0.5 cm diameter at the base; this size is the smallest at

which individuals flower in the field); we were careful to count

stems that represented distinct individuals (not clones). In one

transect per site, we quantified the total number of reproductive

structures (flower buds, flowers, and developing fruits) on each

adult. We conducted separate mixed model ANOVAs to test the ef-

fects of habitat, proximity, their interaction, and site nested within

habitat (a random effect) on two response variables: adult abun-

dance (Poisson distribution, Proc Glimmix, SAS ver. 9.2, SAS

Institute, Cary, NC) and per capita reproductive output (sum of all

reproductive structures per individual, Proc Mixed). As a Poisson

distribution showed poor fit to the model for the reproductive data,

we used a natural log transformation of reproductive structures

(+0.5 due to 0 values). Additionally, in March 2006, we counted

all reproductive structures on a haphazardly selected branch of

3 cm diameter on adult individuals in three remote upland and

three remote bottomland populations in the Four Holes Water-

shed (n = 28 adults total in upland habitat and 27 adults total in

bottomland habitat). A mixed model ANOVA tested the effect of

habitat on per capita reproductive fitness, with site nested within

habitat as a random effect; no data transformations were necessary

for this analysis.

RECIPROCAL TRANSPLANT EXPERIMENT

To test for local adaption, we conducted a multiyear reciprocal

transplant experiment. If V. elliottii exhibits local adaptation, but

there is interhabitat gene flow, adults could show greater adaptive

population divergence than juveniles; therefore, we transplanted

both seedlings and cuttings from adults. In 2004 and 2005, we

collected 4000 cuttings from adult V. elliottii individuals in 32

populations (populations: n = 9 remote upland; 7 remote bottom-

land; 8 ecotonal upland; 8 ecotonal bottomland). Cuttings were

made from new growth and were 10 cm in length. We removed all

but 2–3 leaves, applied rooting hormone (Rhizopon AA #3, 0.8%

IBA, Rhizopon bv, Hazerswoude, Holland), and placed cuttings

under an automated misting system until roots established (two

to three months). Rooted cuttings were grown in the greenhouse

until May (2005 and 2006) when they were transported to the field

site; they were approximately 20 cm tall and had woody stems at

planting. Because V. elliottii seeds are difficult to monitor in the

field due to their small size, we planted seedlings. In 2005, seeds

were collected from plants in 16 populations (n = 4 populations

in each habitat by proximity configuration) and were germinated

in the laboratory. Seedling families, which likely consist of a mix-

ture of half- and full-siblings, were planted in the field in 2006

when individuals were roughly 12 cm tall.

In 2005 and 2006, we transplanted individuals at 1 m intervals

in grids within the matrix of naturally recruiting vegetation in two

upland and two bottomland sites in Four Holes Swamp (data

on abiotic conditions available in Table S2). In 2005, we used

only cuttings (n = 1685 cuttings from 399 genotypes and 22

populations), whereas in 2006, we included both cuttings (n = 548

from 106 genotypes and 22 populations) and seedlings (n = 814

from 81 families and 16 populations). There were 14 populations

in common between the 2005 and 2006 transplant experiments, 7

populations unique to 2005 and 11 unique to 2006. We planted two

to three individuals per clone or seedling family in both upland

and bottomland habitats; however, in a small number of cases, we

could plant only one individual per family per habitat. Individuals

3 7 2 EVOLUTION FEBRUARY 2010

SOURCE-SINK DYNAMICS RESTRICT ADAPTATION

within a family were randomly assigned to bottomland or upland

transplant sites. Within a site, planting was done haphazardly so

that families were not spatially clumped. Prior to planting, we

measured the stem diameter(s) at the base of each individual to

estimate initial biomass (one analysis for both life history stages:

biomass0.5 = −0.29 + 0.59 × total stem diameter − 0.013 ×total stem diameter2 + 0.17 [added for cuttings only]; F3,88 =410, P < 0.0001, R2 = 0.94, n = 39 cuttings + 50 seedlings).

We watered all plants two times per week for two weeks after

outplanting.

Mortality censuses were conducted two to four times per

growing season from 2005 to spring 2008. To calculate relative

growth rate (RGR), we measured the diameter at the base of

each stem in October 2006 (for cuttings planted in 2005) and in

October 2007 (for all plants: cuttings planted in 2005 and cuttings

and seedlings planted in 2006). Statistical analyses are described

below.

The two transplant years differed substantially in abiotic

stress. The mean monthly rainfall in 2005 was 51 mm greater than

average growing season levels (N. Brunswig and M. Dawson,

unpubl. precipitation records). A 45-day flood occurred that

year after approximately half of the bottomland transplants were

planted. The water table was consistently high even after the

flood waters subsided. In contrast, 2006 was substantially drier

with monthly precipitation 16 mm less than the average growing

season value. By replicating this reciprocal transplant experiment

in two years, we were able to assess the effects of interannual

environmental variability on V. elliottii survivorship and

growth.

GREENHOUSE EXPERIMENT

In the greenhouse, we quantified performance of cuttings and

seedlings in response to prolonged drought and flooding. For

this experiment, we randomly allocated multiple individuals per

seedling and cutting families to two treatments: (1) flooded (wa-

ter level 5 cm above soil) and (2) drought (watered once per

week). Here, drought refers to a sustained period of infrequent

water availability. We measured initial stem diameter to estimate

initial biomass. To ensure that individuals had adequate time to

respond to treatment, we gradually exposed plants to increas-

ing or decreasing soil saturation over one month, beginning Oc-

tober 30, 2006. The treatments reached their final flooding or

drought levels on November 27, 2006 and were maintained until

May 4, 2007. We conducted mortality censuses every 7–10 days

on 201 families of seedlings and cuttings (n = 271 seedlings

from 87 families of 16 populations; n = 458 cuttings from

133 families of 25 populations). During the experiment, we

watered drought-stressed plants to saturation once per week

(∼150 mL of water/plant, volumetric water content of ∼32%

mL water/mL soil + water).

Treatment levels were determined based on long-term flood-

ing records from the field site, as well as a previous pilot ex-

periment. In our pilot experiment, we found that daily watering

optimizes V. elliottii growth and survivorship under our green-

house conditions (27–30◦C, 20–30% relative humidity, and 12-h

supplemental lighting). In the drought treatment, the soil dried

completely within three days of watering, resulting in a weekly

average of ∼8% volumetric water content, which is below the

volumetric water content that we measured in upland forests

in March 2007, 2008, and 2009 (mean ± SE: 11.3% ± 0.01,

J. T. Anderson unpubl. data). The drought imposed in the green-

house was likely more severe than most droughts that V. elliottii

experiences in nature as greenhouse plants do not have access to

a water table and are exposed to full light. To inform the flood-

ing treatment, we consulted a 30-year water level data set for the

Beidler Forest watershed (N. Brunswig and M. Dawson, unpubl.

records). Although the flooding period fluctuates considerably

from year to year, floods over 100 days of duration are not un-

common (up to 139 days in 2003). Individuals in both treatments

showed classical signs of stress, such as wilting, leaf abscission,

stem death, and biomass senescence. The prolonged drought and

flooding conditions in the greenhouse experiment are relevant to

conditions that plants could encounter in the field during extreme

years.

Prior to the experiment, plants were grown under well-

watered greenhouse conditions for ∼6 months. To provide space

for continued growth, we transferred all individuals from small

(SC10 Super Cell conetainers: volume = 164 mL) to larger cone-

tainers (Deepot D25L: volume = 410 mL, Stuewe and Sons, Inc.,

Corvallis, OR) in September 2006. We used a 1:1 mixture of peat

moss and sand to mimic the naturally acidic soil in the field.

The experiment consisted of 54 blocks, evenly divided between

treatments. Each block contained a conetainer tray cut to fit in a

14 gallon plastic bin (Rubbermaid Home Products, Fairlawn, OH)

with drainage holes drilled into the bottom of the drought bins. We

included seedlings and cuttings, as well as individuals of multiple

populations from remote and ecotonal upland and bottomlands

in each block. We rotated all blocks weekly and fertilized four

times during the experiment (November, December, February,

and March; Miracle-Gro Azalea, Camellia, Rhododendron Plant

Food, Scotts Miracle Gro Inc., Marysville, OH, 30:10:10 N:P:K).

At the end of the experiment, we harvested all living individuals,

dried (50–60◦C for four to five days), and weighed the biomass.

AnalysesLocal adaptation can be detected through genotype by environ-

ment interactions (G × E) in fitness, where genotype refers to the

habitat of origin of a genotype or family and environment refers

to either transplant environment (field) or treatment (greenhouse).

If interhabitat gene flow restricts adaptive population divergence,

EVOLUTION FEBRUARY 2010 3 7 3

J. T. ANDERSON AND M. A. GEBER

we predict that individuals from ecotonal populations (where gene

flow is likely high) will have reduced fitness relative to individ-

uals from remote populations within the home environment, but

enhanced fitness in the alternative environment (habitat of origin

× proximity × environment interaction). Survivorship and rel-

ative growth rate (RGR) were the fitness components for both

experiments because very few plants flowered. Fitness was ana-

lyzed as a function of habitat of origin (G), transplant habitat or

treatment (E), proximity (ecotone vs. remote), life history stage

(greenhouse experiment and 2006 transplants only), their inter-

actions, and initial plant size. In all analyses, we accounted for

nonindependence of individuals from the same family and popu-

lation by including family nested within population as a random

effect. We did not have sufficient denominator degrees of freedom

to include transplant site nested within environment or population

nested within habitat by proximity as random effects. We incor-

porated transplant site nested within environment as a fixed effect

to control for the effect of site while testing other predictors. All

analyses were conducted in SAS ver. 9.2, except as noted.

Fitness component: relative growth rateIn the field experiment, RGR was calculated as (ln(diametert) −ln(diameteri))/t, where t is elapsed time (in months), diametert

is the sum of the diameters at the base of each stem at time

t, and diameteri is the initial diameter. The three sets of RGR

measurements include (1) first year growth for 2005 transplants

(measured October 2006), (2) second year growth for 2005 trans-

plants (measured October 2007), and (3) first year growth for

2006 transplants (measured October 2007). We conducted a re-

peated measures analysis of variance (ANOVA) (Proc Mixed) on

the first and second year RGR values from the 2005 transplants

with a repeated statement for year. We analyzed RGR of the 2006

transplants separately (Proc Mixed).

In the greenhouse experiment, RGR was calculated as

(ln(final biomass)−ln(initial biomass))/t, where t is elapsed time

(in months) and initial biomass was estimated from initial diam-

eter measurements. Block nested within treatment was included

as a random effect in a mixed model ANOVA (Proc Mixed).

Fitness component: survivorshipSurvivorship was monitored 10 (2005 transplants) and eight (2006

transplants) times in the field experiment from planting until April

2008 and 16 times in the greenhouse experiment. We conducted

discrete-time survivorship analyses (Cox proportional hazards

models) separately for the two transplant years and the greenhouse

experiment. Random effects (frailty) modeling permits the analy-

sis of clustered survivorship data, which arise when time-to-event

data are collected on family members (e.g., Kelly 2004). We mod-

eled time until death with a Bayesian approach in WinBUGS ver.

1.4.3 (Imperial College and Medical Research Council, London,

United Kingdom, Bayesian Analysis using Gibbs Sampling; Lunn

et al. 2000) because standard statistical software cannot accom-

modate multiple random effects in survivorship analysis (Kelly

2004). We included family by population of origin as gamma-

distributed random variables and assumed these random state-

ments operated multiplicatively on the baseline hazard, which is

appropriate for clustering at the family level (Sastry 1997; Koissi

and Hognas 2005). In the greenhouse analysis, we incorporated

an additive random effect for block and excluded individuals that

died before final treatment levels were reached on November 27,

2006. We used uninformative priors with 100,000 iterations fol-

lowing a burn-in of 10,000. Convergence was assessed with diag-

nostics in Bayesian Output Analysis Program (Smith 2005). Cox

proportional hazards models assume that the difference in haz-

ard rates between treatments remains similar across time periods;

when this assumption was violated, we included time-dependent

predictor variables in the model (Cox 1972). The WinBugs codes

and datasets are available from the first author.

Fitness trade-offsWe tested whether fitness in bottomland sites (or flooded con-

ditions) comes at the cost of fitness in upland sites (or drought

treatment) in separate analyses for the two years of transplanting

and for the greenhouse experiment. To assess trade-offs in fit-

ness, we regressed family-level RGR and survivorship (number

survived/number planted) in bottomland (or flooded conditions)

against habitat of origin and family level RGR (Proc Mixed) or

survivorship (logistic regression in Proc Glimmix) in upland (or

drought conditions). We included population as a random effect.

For the 2006 transplants and the greenhouse experiment, we also

included life history stage, and interactions between fitness and

life stage. For these analyses, we excluded any families that were

not represented in both transplant environments or both green-

house treatments.

POPULATION GENETIC DIFFERENTIATION

Genetic differentiation can increase during ontogeny, when mal-

adapted seedlings that are the product of gene flow are eliminated

by selection; changes in genetic structure can, therefore, illumi-

nate the action of selection at different ontogenetic stages (Kalisz

et al. 2001; Kittelson and Maron 2001). We used microsatellite

markers to characterize interhabitat gene flow and genetic diver-

sity at two life history stages: adults and seeds. We used seeds

because naturally recruited seedlings and juveniles of V. elliottii

are rare at our field sites (Anderson, pers. obs.). Microsatellites

are highly informative in estimating gene flow (Hamilton et al.

1999) because they are codominant, (putatively) selectively neu-

tral, and highly variable regions of DNA (Jarne and Lagoda 1996).

We haphazardly sampled 315 adults from 17 populations in Four

Holes Watershed (mean ± SE, n = 18.5 ± 1.3 individuals per

population, see Table S3 for information on sampling locations

3 7 4 EVOLUTION FEBRUARY 2010

SOURCE-SINK DYNAMICS RESTRICT ADAPTATION

and sample sizes). Leaf samples were either collected in the field

and stored in silica gel until DNA extraction with Qiagen plant

kits (Qiagen Inc., Valencia, CA), or collected from living cuttings

in the greenhouse and ground fresh in liquid N2. During June and

July 2006 and 2007, we collected seeds directly from adults in 15

populations, germinated them in the lab, and extracted DNA from

fresh leaf tissue of 174 seedlings (n = 11.6 ± 0.73 individuals

per population). Predispersal seeds provide information on pollen

movement.

We used eight primers from a microsatellite library developed

for the heterospecific V. corymbosum (NA961, NA398,CA94F,

CA23F, CA787F, CA169F, CA855F, and CA190R) (Boches et al.

2005). Polymerase chain reaction (PCR) annealing temperatures

were the same as in Boches et al. (2005), but MgCl2 concentra-

tions were optimized for NA398 and CA94F. The 5′ end of each

primer was fluorescently labeled with NED (CA169F, NA398,

CA94F), 6-FAM (CA190R), PET (CA23F, CA855F), or VIC

(NA961, CA787F). Genotypes were resolved by electrophore-

sis using an ABI 3100 capillary sequencer in the evolutionary

genetics core facility at Cornell University. Data were collected

and scored with GeneMapper v. 3.0. We verified each allele score

manually and reamplified and rescored samples with potentially

problematic peaks (Dewoody et al. 2006). We also compared

genotypes of adults with their corresponding offspring for 86

pairs in the program CERVUS 3.0 (e.g., Hoffman and Amos 2005);

when mother and offspring did not share a common allele, both

individuals were reamplified. We assessed gametic disequilib-

rium among loci in GENEPOP (Rousset 2008), selective neutrality

in FDIST2 (Beaumont and Nichols 1996), and null alleles and scor-

ing errors in MICRO-CHECKER using individuals that amplified at

all loci (n = 465) to eliminate samples with potentially degraded

DNA (a subset of leaves stored in silica gel) (Van Oosterhout

et al. 2004).

We assumed an infinite allele mutational model because it

is more robust to violation than the stepwise mutational model

(Selkoe and Toonen 2006) and because one polymorphic locus

(CA855F) contained a compound repeat for which the stepwise

model is not appropriate. We tested for deviation from Hardy–

Weinberg equilibrium for each population and locus combination

for seeds and adults using GENALEX (Peakall and Smouse 2006).

We used FSTAT (Goudet 1995, ver. 2.9.3.2) to calculate observed

(HO) and expected heterozygosity (HE), F-statistics and pairwise

FST using the estimators of Weir and Cockerham (1984). A sim-

ple Mantel test using the program zt (100,000 iterations, Bonnet

and Peer 2002) assessed the difference in pairwise FST values be-

tween seeds and adults for the 15 populations for which we had

data at both life history stages. To assess isolation by distance,

and to detect whether intrahabitat gene flow exceeds interhabitat

gene flow, we used a partial Mantel test (100,000 iterations in zt)

to assess the correlation between pairwise genetic differentiation

(FST/(1 − FST)) and geographic distance (natural logarithm trans-

formed) (Rousset 1997) in a habitat context for both undispersed

seeds and adults. The habitat matrix included values of 1 for pop-

ulation pairs located in the same habitat, and 2 for population

pairs in opposing habitats.

POPULATION GENETIC DIVERSITY

We calculated standard metrics of within population genetic di-

versity using HP-RARE (Kalinowski 2005): allelic richness rarefied

to a sample of 10 genes, which was the minimum sample size per

locus per population after correction for null alleles (mean sample

size ± SE: 29.8 ± 0.79 genes; maximum: 56 genes); rar-

efied private allele richness, which measures the number of

unique alleles within a population; and expected heterozygosity

(HE), which represents the probability that two randomly cho-

sen alleles from a population are different (Kalinowski 2004;

Vellend 2004). We conducted a mixed multivariate analysis of

variance (MANOVA, Proc Mixed) to test the effects of life

history stage (seed vs. adult), habitat (bottomland vs. upland),

proximity (ecotone vs. remote), and two- and three-way inter-

actions on these response variables, with locus and life history

stage nested within population as random effects. Because the

MANOVA produced significant results (online Table S4), we

implemented univariate mixed ANOVAs to test each response

variable independently. These analyses were conducted in Proc

Glimmix with two R-sided covariance structures (equivalent to a

repeated statement) for the random effects of locus nested within

population and life history stage within population (Proc Glim-

mix: http://support.sas.com/rnd/app/papers/glimmix.pdf).

POPULATION GENETIC STRUCTURE

We assessed population structure with the Bayesian clustering

program STRUCTURE to assign individuals to K populations

(Pritchard et al. 2000). We conducted STRUCTURE analyses for

K = 1 to K = 15 (seeds) and K = 17 (adults) with 1 million

generations after a 200,000 MCMC (Markov Chain Monte Carlo)

burn-in to generate the posterior sample distribution for 10 iter-

ations at each level of K. We used the admixture and correlated

frequency models with λ = 1 for both life history stages and

determined the optimal value of K by comparing ln P(D) (the

likelihood of the data, given each value of K) at different K, fol-

lowing Pritchard and Wen (2003). If the optimal value K was >1,

we used the �K method of Evanno et al. (2005). We combined the

results of 20 runs at the optimal K using CLUMMP (Jakobsson

and Rosenberg 2007) and graphed with DISTRUCT (Rosenberg

2004).

GENE FLOW

We tested for asymmetrical gene flow using Bayesian inference in

MIGRATE ver. 3.0 (Beerli and Felsenstein 2001). Simulations were

performed separately for seeds and adults with two concurrent

EVOLUTION FEBRUARY 2010 3 7 5

J. T. ANDERSON AND M. A. GEBER

Figure 1. Variation in: (A) population size (mean number of in-

dividuals per transect) and (B) reproductive fitness (average per

capita number of flower buds, flowers, and developing fruits) as

a function of habitat.

independent chains and heating with four temperatures. We used

a paired t-test (Proc TTEST) to determine whether the number

of migrants (4Nem) was significantly greater from upland into

bottomland populations than the reverse.

ResultsDEMOGRAPHY

The density of adult V. elliottii was significantly greater in upland

than in bottomland populations (F1,4 = 18.3, P = 0.01, Fig. 1a).

Additionally, upland populations produced significantly more re-

productive structures per capita than bottomland populations in

2008 (F1,4 = 14.2, P = 0.02, Fig. 1b) and in 2006 (upland:

105.7 ± 11.9; bottomland: 52.2 ± 12.1, F1,4 = 9.9, P = 0.035).

Population proximity did not influence density or reproductive

output in 2008 (P > 0.6). Ecotonal populations were not included

in the 2006 surveys; therefore, we could not test the effect of

population proximity in that year. At the initiation of this study

in May–August 2004, we mapped and tagged naturally recruited

adult individuals in all populations within the Four Holes Swamp

watershed. Since that time, we have not observed any mortality

events. Our observations of this species at our other sites accord

well with the results that we report here on population density and

reproductive fitness.

RECIPROCAL TRANSPLANT EXPERIMENT:

SURVIVORSHIP

Cox proportional hazards models indicated a significant and

strong effect of transplant environment on the time until mortality

in the field experiment; across years, survivorship was higher in

upland than bottomland forests (Table 1, Fig. 2). For the 2006

transplants, seedlings had significantly lower survivorship than

cuttings and had very poor success in the bottomlands (Figs. 2b,c).

Due to the long generation time of V. elliottii, it was not

possible to rear multiple generations in the greenhouse. We min-

imized maternal or latent environmental effects by growing all

individuals in benign greenhouse conditions for 6–8 months be-

fore experimentation. Initial size did not differ between plants

transplanted into bottomland and upland habitats in 2005 (P =0.09) and bottomland transplants were slightly, but significantly,

larger than upland transplants in 2006 (initial diameter (± S.E.):

bottomland transplants: 1.89 ± 0.06; upland transplants: 1.71 ±0.06; P = 0.0002). Thus upland transplants did not have a sys-

tematic initial advantage over bottomland transplants in either

year.

GREENHOUSE EXPERIMENT: SURVIVORSHIP

In the greenhouse, mortality was significantly higher in the

flooded than in the drought treatment (Table 1, Fig. 2d). Seedlings

from bottomland populations had significantly greater overall sur-

vivorship than seedlings from upland populations; cuttings did not

exhibit this pattern (life history by habitat interaction, Table 1). Fi-

nally, seedlings from remote populations outperformed seedlings

from ecotonal populations, whereas the opposite pattern was true

for cuttings (life history by proximity interaction, Table 1).

RECIPROCAL TRANSPLANT EXPERIMENT: RELATIVE

GROWTH RATE

Across years, individuals in upland transplant sites significantly

outgrew their relatives in bottomland sites (Table 2, Fig. 3). For

the 2005 transplants, individuals from bottomland populations

outperformed those from upland populations (Table 2) and there

is a trend that suggests that this effect was pronounced in the

bottomland habitat (transplant environment by habitat of origin

interaction, Table 2). For the 2006 transplants (measured in 2007),

seedlings had greater relative growth rates than cuttings (life his-

tory stage effect, Table 2).

GREENHOUSE EXPERIMENT: RELATIVE GROWTH

RATE

Relative growth rate was significantly greater in the drought than

in the flooded treatment in the greenhouse (F1,52 = 52.9, P <

0.0001); seedlings also had greater RGR than adults (F1,206 =13.0, P = 0.0004, Fig. 4). An interaction between life history stage

and treatment was driven by significantly greater performance of

seedlings in the drought treatment than the flooded treatment and

relatively equivalent performance of cuttings in both treatments

(F1,206 = 41.0, P < 0.0001, Fig. 4).

FITNESS TRADE-OFFS

Genotypes exhibited a negative correlation between survivorship

in upland and bottomland transplant sites in the 2005 transplant

experiment (odds ratio (95% CI): 0.24 (0.11, 0.53); F1,82 =12.6, P = 0.0006, online Fig. S2). That is, survivorship in the

bottomland sites corresponded with reduced survivorship

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Table 1. Results of Bayesian survivorship analyses, conducted in Winbugs. Environment refers to transplant environment (field) or

treatment (greenhouse). Parameter estimates are hazard ratios (HR), which represent the relative risk of mortality during each time

period for the baseline group compared with the alternate group. Parameters whose 95% credible intervals (C.I.) do not include 1 have

a significant influence on mortality and are highlighted in bold. Hazard ratios < 1 indicate that the baseline group had a significantly

increased risk of mortality. Baseline groups in these analyses were: bottomland (transplant environment and habitat of origin), remote

(proximity), seedling (life history stage), flooded (treatment). For the continuous variable (plant size), HR < 1 specifies that larger

individuals had a significantly diminished risk of mortality; for example, a 1 mm increase in initial diameter in the 2005 transplants

corresponded with a 25% reduction in mortality. Seedlings were not included in the 2005 transplants.

2005 transplants 2006 transplants Greenhouse experiment

Posterior Posterior PosteriorHR mean 95% C.I. HR mean 95% C.I. HR mean 95% C.I.

Initial plant size 0.75 (0.69, 0.81) 0.39 (0.35, 0.45) 0.93 (0.81, 1.06)Environment (ENV) 0.22 (0.1, 0.46) 0.32 (0.19, 0.54) 0.054 (0.0043, 0.56)Habitat of origin (HAB) 0.94 (0.83, 1.09) 0.93 (0.81, 1.06) 1.11 (0.95, 1.3)Proximity (PROX) 1.12 (0.96, 1.82) 0.99 (0.87, 1.14) 1.02 (0.97, 1.18)Life history stage (LIFE) N/A 0.86 (0.77, 0.98) 9.6 × 10−6 (7.8 × 10−7, 1.5 × 10−4)HAB × PROX 1.09 (0.94, 1.26) 094 (0.82, 1.08) 1.05 (0.9, 1.22)HAB × ENV 0.97 (0.90, 1.06) 1.04 (0.96,1.13) 1.04 (0.9, 1.2)PROX × ENV 1.06 (0.97, 1.15) 1.01 (0.93, 1.09) 0.99 (0.87, 1.14)HAB × PROX × ENV 1.07 (0.98, 1.16) 0.99 (0.91, 1.08) 1.06 (0.92, 1.21)LIFE × HAB N/A 0.94 (0.84, 1.05) 1.16 (1.02, 1.32)LIFE × PROX N/A 0.95 (0.85, 1.06) 1.15 (1.01, 1.31)LIFE × ENV N/A 0.95 (0.86, 1.05) 0.95 (0.82, 1.1)LIFE × PROX× ENV N/A 0.99 (0.89, 1.11) 1.01 (0.88, 1.17)LIFE × HAB × PROX × ENV N/A 0.99 (0.91, 1.09) 0.98 (0.86, 1.13)Site 0.086 (0.06, 0.12) 0.28 (0.20, 039) N/AVariance of Population 1.25 (1.1, 4.9) 1.22 (1.09, 1.45) 1.12 (1.05, 1.27)Variance of Family 1.16 (1.1, 1.2) 1.19 (1.07, 1.39) 1.11 (1.05, 1.23)Variance of Block N/A N/A 1.19 (1.07, 1.41)

(0.24 odds of survivorship) within the uplands. Habitat of ori-

gin (F1,21 = 0.6, P = 0.45) and the interaction between habitat

and survivorship in the bottomlands (F1,89 = 1.26, P = 0.26) were

nonsignificant in this model. No trade-offs were evident for the

2006 transplants and the greenhouse experiment.

POPULATION GENETIC DIFFERENTIATION

Our population genetic results are robust because our loci con-

formed to assumptions of neutrality and our genotyping had low

error rates. We detected no evidence for selection at any of the

eight loci tested (online Table S5); however, GENEPOP revealed

significant linkage disequilibrium between two loci (CA23F and

CA787F) and three others. We removed these two loci from the

dataset and resolved the disequilibrium problem. The remaining

six loci were in Hardy–Weinberg equilibrium; there were only

seven significant deviations out of 88 tests for adults (loci were

monomorphic at 14 population-locus combinations) and three de-

viations out of 80 tests for seedlings (10 monomorphic population-

locus combinations). MICROCHECKER found no evidence for scor-

ing errors due to stutter, or large allele drop out. Several loci

showed an excess of homozygotes, suggesting the presence of

null alleles. Null allele frequencies were estimated (Brookfield 2)

and used in downstream analyses (Brookfield 1996). Overall

genotyping error rate for mother offspring pairs was low (online

Table S6).

Multilocus estimates of F-statistics indicate that adults and

seeds were more homozygous than would be expected under ran-

dom mating, both across populations (adult F IT: 0.108, 95% CI:

[0.074, 0.127]; seedling F IT: 0.080, 95% CI: [0.034, 0.094]) and

within populations (adult F IS: 0.078, 95% CI: [0.044, 0.091];

seedling F IS: 0.043, 95% CI: [−0.013, 0.067]). Overall FST val-

ues were small, indicating little population differentiation (adult

FST: 0.032, 95% CI = 0.022, 0.045; seed FST: 0.038, 95% CI =0.027, 0.052). A Mantel test revealed no significant correlation

(r = 0.21, P = 0.2) between pairwise population differentiation

for the 15 populations assessed at the adult and seed life his-

tory stages. Per-locus and weighted multilocus F-statistics, and

observed and expected heterozygosities are presented in online

Tables S7 (adults) and S6 (seeds). Bottomland populations con-

tained a subset of the alleles present in upland populations. Partial

Mantel tests revealed that genetic population differentiation in

adults increased significantly with geographic distance (r = 0.42,

EVOLUTION FEBRUARY 2010 3 7 7

J. T. ANDERSON AND M. A. GEBER

P = 0.0014), but habitat was not significant (P = 0.68, Support-

ing Figure S3a). For undispersed seeds, there was no effect of

geographic distance (P = 0.75) or habitat (P = 0.69) on genetic

divergence, suggesting relatively unrestricted gene flow via pollen

(Supporting Figure S3b).

POPULATION GENETIC DIVERSITY

An analysis accounting for private (unique) alleles uncovered

significant effects of habitat (F1,13 = 7.0, P = 0.02), proximity

(F1,13 = 5.0, P = 0.04), habitat × proximity (F1,11 = 10.3, P =0.007), and habitat × proximity × life history stage (F1,11 = 7.8,

P = 0.02). Upland populations had significantly greater private

allelic richness (PAR) than bottomland populations. Additionally,

remote upland populations had significantly greater PAR than all

other populations, especially for predispersed seeds. Similarly,

remote upland populations had significantly greater PAR than all

other populations (Fig. 5). We found no effect of life history,

habitat, proximity, or their interactions on rarefied allelic richness

or expected heterozygosity.

Figure 2. Kaplan–Meier survivorship curves for (A) the 2005 transplants (cuttings), (B) the 2006 cuttings, (C) the 2006 seedlings, and (D)

the greenhouse experiment. Panels indicate transplant habitat, as well as habitat of origin and population proximity to the ecotone.

POPULATION GENETIC STRUCTURE

Results from STRUCTURE indicated a high degree of admixture

for both life history stages. STRUCTURE identified one pan-

mictic adult population (Supporting Figure S4). In contrast, the

optimal value of K for undispersed seeds was 2, following both

Pritchard and Wen (2003) and the �K method of Evanno et al.

(2005). Nevertheless, we found no natural groupings of upland

versus bottomland populations or remote vsersus ecotonal pop-

ulations in the K = 2 populations identified by STRUCTURE

(supporting Figure S5 a and b). Rather all populations consisted

of a mixture of both demes.

GENE FLOW

At the predispersed seed level, significantly more migrants

(4Nem) moved from upland into bottomland populations (3.6 ±0.28) than the reverse (2.7 ± 0. 29, t55 = 3.45, P = 0.001). For

adults, we found no evidence for asymmetrical migration, but this

may be due to low population divergence.

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Figure 2. Continued.

DiscussionDespite the steepness of the environmental gradient between up-

land and bottomland forests, V. elliottii showed no evidence for

adaptive population differentiation. Instead, V. elliottii individu-

als consistently had greater survivorship and relative growth rates

(reciprocal transplant experiment), as well as reproductive fitness

(demographic study) in upland than in bottomland habitats. Ad-

ditionally, in the greenhouse V. elliottii individuals in the drought

treatment had significantly greater fitness than their relatives in

the flooded treatment, suggesting that this species is better adapted

to long-term drought than flooding. Our molecular study revealed

very little population genetic differentiation. Finally, remote up-

land populations harbored significantly greater genetic diversity

(unique alleles) than all other populations. These demographic,

fitness-related, and population genetic attributes are character-

istic of systems with genetic source-sink dynamics (Dias and

Blondel 1996; Stanton and Galen 1997; Pulliam 1988; Kawecki

2008).

The small population size and per capita reproductive fitness

in bottomland forests suggest that bottomland populations have

reduced genetic contributions to future generations, thereby con-

straining selection within this marginal habitat (Kawecki 2008).

These demographic differences also likely result in asymmetri-

cal movement of pollen and seeds from upland into bottomland

populations (Kawecki 2008); indeed, our molecular results were

consistent with asymmetrical gene flow at the pollen level (i.e.,

undispersed seeds). The flowers of Vaccinium spp. (including

elliottii) are pollinated primarily by bees and the seeds are dis-

persed by a variety of birds and mammals (e.g., Vander Kloet

and Austin-Smith 1986; Javorek et al. 2002; Yang et al. 2008).

We hypothesize that pollinators and seed dispersers focus their

foraging efforts on the more productive upland populations with

relatively infrequent forays into the bottomlands, which could re-

sult in pollination limitation (e.g., Ashman et al. 2004) and altered

patterns seed dispersal (e.g., Morales and Carlo 2006) in bottom-

land populations. The ability of bottomland populations to adapt

EVOLUTION FEBRUARY 2010 3 7 9

J. T. ANDERSON AND M. A. GEBER

Table 2. Results of repeated measures ANOVA on relative growth rate (RGR) of 2005 transplants (cuttings only) measured in October

2006 and 2007 and mixed model ANOVA on RGR of 2006 transplants (cuttings and seedlings) measured in October 2007. No other

interactions involving year of measurement were significant for the 2005 transplants. Values in bold are P-values.

2005 transplants 2006 transplants

F1,1370 P-value F1,342 P-value

Transplant environment (ENV) 43.5 <0.0001 40.4 <0.0001Habitat of origin (HAB) 5.3 0.022 0.11 0.74Proximity (PROX) 1.1 0.29 1.8 0.18Life history stage (LIFE) N/A 11.7 0.0007HAB × PROX 0.24 0.63 0.07 0.79HAB × ENV 3.44 0.064 2.5 0.11PROX × ENV 0 0.96 1.8 0.18HAB × PROX × ENV 0.96 0.33 0 0.96LIFE × HAB N/A 1.03 0.31LIFE × PROX N/A 0.08 0.77LIFE × ENV N/A 0.09 0.77LIFE × HAB × ENV N/A 0.56 0.46LIFE × PROX × ENV N/A 7.75 0.006LIFE × HAB × PROX × ENV N/A 0.72 0.40Year of measurement 107.1 <0.0001 N/AYear × ENV 17.8 <0.0001 N/AYear × HAB 4.7 0.031 N/ASite (transplant environment) F2,1370 = 39.4 <0.0001 8.7 0.0034Genotype (population of origin) 0.24 0.05

to local conditions is diminished by asymmetrical gene flow into

bottomland forests, coupled with reduced fitness, and depressed

genetic variation in bottomland forests. This hypothesis accords

well with theoretical predictions that source-sink dynamics can

limit adaptive evolution in marginal habitats (Kawecki and Holt

2002).

Abiotic and biotic factors appear to contribute to fitness dif-

ferences of V. elliottii in upland and bottomland forests. For one,

flooding is clearly a severe stress for this species. Flooded in-

dividuals from the greenhouse study showed poor performance

compared with their drought-stressed relatives. Additionally, the

flood of 2005 led to high mortality in bottomland transplants. In-

deed, survivorship declined more rapidly in bottomland sites for

the 2005 transplants than the 2006 transplants, which have still not

experienced a flood. The drier conditions of 2006 could underlie

increases in survivorship in the bottomlands and decreases in the

uplands for that transplant year. However, flooding is clearly not

the sole determinant of plant performance, or the fitness of 2006

transplants would not vary with habitat. Leaf herbivory is signif-

icantly greater in bottomland than in upland forests (Anderson

2009). Interspecific competition is an additional biotic stress that

could influence fitness in the bottomlands. Upland forests have a

sparse understory, whereas a dense layer of dwarf palmetto (Sabal

minor, Arecaceae) covers the forest floor in bottomland forests

(Porcher 1981, Anderson unpub. data). Thus, a complex suite of

factors, including flooding, herbivory, resource availability, and

interspecific competition, likely reduces the fitness of V. elliottii

individuals in the bottomlands.

In a classic study, Stanton and Galen (1997) found no evi-

dence for local adaptation in the snow buttercup across a snowmelt

gradient. Rather, plants from high-quality microsites produced

high-quality seeds, presumably due to greater resource availabil-

ity; differences in seed quality resulted in asymmetric gene flow

and the creation of source-sink dynamics (Stanton and Galen

1997). Due to the small size of V. elliottii seeds, we did not as-

sess fitness at the seed to seedling transition; however, we saw

no evidence that upland seeds were consistently bigger, or had

greater germination rates in the laboratory (Anderson, pers. obs.).

The source-sink dynamics present in this system are likely due to

environmental conditions that restrict both population size and fit-

ness in bottomland forests, but could be compounded by intrinsic

genetic differences between upland and bottomland populations.

We found very low levels of population genetic differenti-

ation and no increase in adaptive or neutral population differ-

entiation through ontogeny, which suggests that selection against

immigrants is likely weak (Kalisz et al. 2001). The only indication

of local adaptation was a slight trend for enhanced growth rates of

bottomland relative to upland genotypes in bottomland transplants

sites for the cuttings planted in 2005. We are hesitant to conclude

that cuttings are more locally adapted than seedlings because

3 8 0 EVOLUTION FEBRUARY 2010

SOURCE-SINK DYNAMICS RESTRICT ADAPTATION

Figure 3. Relative growth rate as a function of transplant envi-

ronment and habitat of origin for (A) 2005 and (B) 2006 trans-

plants. Habitat of origin is indicated by B (bottomland) and U

(upland).

seedlings were not transplanted in 2005. However, seedlings were

less tolerant of flooding than cuttings. Seedling growth rate in the

greenhouse experiment was actually negative in the flooded treat-

ment, whereas drought-stressed seedlings had the greatest growth

Figure 4. Effects of treatment and life history stage on relative

growth rate in the greenhouse experiment.

Figure 5. Genetic diversity (private allelic richness) as a function

of life history stage, habitat, and proximity to the ecotone.

rates, exceeding those of cuttings in either treatment. Thus, suc-

cessful seedling establishment could be particularly difficult under

flooded conditions.

If bottomland forests occupy a substantially larger proportion

of the landscape than upland forests, then selection in this ecolog-

ically marginal habitat could influence the evolutionary trajectory

of V. elliottii even though population density is greater in upland

sites. However, historically, upland hardwood forests dominated

the landscape of the Southeastern USA (Phillips 1994 and ref-

erences therein). Contemporary patterns, however, are likely to

be quite different, as upland forests were disproportionately con-

verted to agriculture due to favorable drainage conditions (Phillips

1994). In three counties of North Carolina, for example, an esti-

mated 54–96% of upland hardwood forests have been lost since

the 16th century, compared with an estimated 32–43% loss of

wetland habitats (Phillips 1994). A recent GIS-based study of

habitat frequency in Arkansas indicated that 67% of the land was

in agriculture, 13% in bottomland hardwood forest, and only 9%

in upland forest (Carter and Biagas 2007). We know of no GIS-

based analysis of the frequency of bottomland hardwood versus

upland forests in the 418,237 acre Four Holes Swamp Watershed,

our primary field site. However, due to conservation of wetland

forests by the National Audubon Society and conversion of upland

areas in this watershed, it seems likely that bottomland forests are

relatively more common now than historically. Thus, V. elliottii

is better adapted to upland habitats whose frequency has likely

decreased due to human influence.

In the absence of migration from source to sink popula-

tions, the sink could either go extinct if mortality exceeds birth

and survivorship (absolute sink), or adapt to local conditions if

sufficient genetic variation exists (pseudosink in which immigra-

tion elevates population sizes above nonzero carrying capacity)

EVOLUTION FEBRUARY 2010 3 8 1

J. T. ANDERSON AND M. A. GEBER

(Dias 1996; Garcı́a-Ramos and Kirkpatrick 1997; Pulliam 1988;

Kawecki and Holt 2002; Kawecki 2008). Vaccinium is not mono-

phyletic and a complete phylogeny of the hundreds of species in

this genus is not yet available (Kron et al. 2002). Without more de-

tailed phylogenetic data, it is difficult to resolve the ancestral niche

breadth of V. elliottii. Nevertheless, other species of Vaccinium

and other genera in the Ericaceae (e.g., Leucothoe) sustain pop-

ulations in bottomland habitats and five North American species

of Vaccinium are considered obligately associated with wetlands

(http://www.fws.gov/nwi/bha/downloads/1996/national.pdf). Be-

cause other Vaccinium species have adapted to wetland conditions

(Braendle and Crawford 1999), V. elliottii could harbor the ge-

netic potential to adapt to these conditions as well. However, in

our system, V.elliottii exhibits low fitness in bottomland forests

and flooded conditions at multiple life history stages. Spatial ge-

netic analyses indicated that gene flow is likely very high across

the landscape and may be primarily from upland to bottomland

populations. Asymmetrical migration is thought to inhibit adap-

tation to ecologically marginal habitats, especially when fitness

in marginal habitats comes at the cost of fitness in the core habitat

(Kawecki 2008) as is the case in our 2005 transplant experiment.

It seems likely that interhabitat gene flow, in conjunction with

small population size, fitness trade-offs, and limited genetic vari-

ation, reduces the potential for bottomland populations to adapt

to the local environment.

ACKNOWLEDGMENTSWe are very grateful to N. Brunswig, M. Dawson, A. Shahid, and thestaff of Beidler forest for logistical support and permission to conductthis research. Permission to sample at other sites was granted by the U.S.Forest Service and S.C. Department of Natural Resources. P. Marks, F.West, A. Landi, and T. Pendergast helped with the field work and E. Fabioassisted with the greenhouse experiment. S. Bogdanowicz aided with thegenotyping. We would like to thank B. Barringer, S. Cook, A. Eller, A.Erwin, L. Evanhoe, A. Flecker, P. Marks, A. Parachnowitsch, J. Paul, T.Pendergast, S. Reilly, and J. Sparks, for valuable discussions about thisresearch and insightful comments on previous versions of this manuscript.We thank T. Juenger, M. Stanton, and an anonymous reviewer for theirconstructive criticism on previous drafts. Funding was provided by anNSF Doctoral Dissertation Improvement Grant (DEB 0607992) and anAndrew Mellon foundation grant.

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Associate Editor: T. Juenger

Supporting InformationThe following supporting information is available for this article:

Table S1. Geographical locations of populations sampled for reciprocal transplant and greenhouse experiments.

Table S2. Abiotic conditions in upland and bottomland transplant sites.

Table S3. Populations sampled for genotyping with microsatellites.

Table S4. Results of multivariate analysis of variance (MANOVA) examining the effect of habitat, proximity, life history stage, and

two and three-way interactions on Vaccinium elliottii population-level genetic diversity.

Table S5. Test of selective neutrality of microsatellite loci used in this study.

Table S6. Genotyping scoring error rate for mother-offspring pairs.

Table S7. Adult Vaccinium elliottii mean F-statistics.

Table S8. Mean F-statistics for seeds of Vaccinium elliottii.

Figure S1. Map of (a) watersheds sampled in South Carolina and (b) populations in Four Holes Watershed.

Figure S2. Trade-off between survivorship in bottomland and upland transplant sites for families planted in both habitats in 2005.

Figure S3. Genetic population divergence as a function of geographic distance for (a) adults and (b) undispersed seeds.

Figure S4. STRUCTURE results for adults. Plot of K (population size) against ln P(D), which represents the likelihood of the data,

given each value of K.

Figure S5. STRUCTURE results for undispersed seeds. (a) The optimal value of K for undispersed seeds was 2, following both

Pritchard and Wen (2003) and the �K method of Evanno et al. (2005). (b) Neither upland versus bottomland nor remote versus

ecotonal populations corresponded well with the two demes identified by STRUCTURE.

Supporting Information may be found in the online version of this article.

(This link will take you to the article abstract).

Please note: Wiley-Blackwell is not responsible for the content or functionality of any supporting materials supplied by the authors.

Any queries (other than missing material) should be directed to the corresponding author for the article.

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