Download Artificial selection on flowering time: influence on reproductive

Journal of Ecology 2012, 100, 852–861
doi: 10.1111/j.1365-2745.2012.01967.x
Artificial selection on flowering time: influence on
reproductive phenology across natural light
environments
Laura F. Galloway* and Kevin S. Burgess†
Department of Biology, University of Virginia, Charlottesville, VA 22904, USA
Summary
1. Flowering time is frequently under selection due to a combination of abiotic, biotic and intrinsic
factors. Evolution in response to this selection is likely to have broad effects, altering not only flowering time but reproductive phenology and, potentially, traits throughout the life cycle. We know
little about the broader phenotypic changes associated with evolutionary shifts in flowering time,
and the extent to which expression of these changes depends on local environmental conditions.
2. After three generations of selection for early- and late-flowering, we grew plants of the herb
Campanulastrum americanum in contrasting light environments (light gap and understorey) in its
home population.
3. Response to selection on flowering time and correlated responses in reproductive phenology
were expressed across light environments with the reproduction of early-flowering lines being over
2 weeks ahead of late-flowering lines. Plants in the understorey delayed initiation of flowering but
accelerated flower deployment, fruit maturation and the end of reproduction, resulting in a
condensed reproductive period.
4. Timing of seed dispersal influences whether offspring grow as annuals or biennials in C. americanum. Because evolution of flowering time shifted reproductive phenology, it is likely to alter life history frequency. In contrast, understorey habitats both delayed flowering and accelerated
reproductive phenology, yielding no expected life history change.
5. Synthesis. Evolution of flowering time altered the phenology of all subsequent reproductive traits
and is also likely to affect offspring traits. This ripple effect of changes in flowering time indicates
that it is essential to recognize genetic and functional linkages among traits to understand potential
life cycle consequences of selection on a single character.
Key-words: artificial selection, autopolyploid, correlated response, ecological genetics and
ecogenomics, flowering time, fruit maturation time, life history evolution, maternal effects,
phenotypic plasticity, shade
Introduction
Flowering time is central to plant reproductive success. The
number of flowers produced (Picó & Retana 2000), the abundance of pollinators (Brody 1997; Rafferty & Ives 2011),
environmental conditions during fruit maturation (GiménezBenavides, Escudero & Iriondo 2007) and levels of fruit herbivory (Pilson 2000; Lacey et al. 2003) may all vary with the
timing of flowering. As a consequence of this key role, flowering time is expected to be under strong selection. Selection may
*Correspondence author: E-mail: [email protected]
†Present address: Department of Biology, Columbus State University, Columbus, GA 31907, USA.
be due to abiotic factors such as temperature or water availability (Etterson 2004; Franks, Sim & Weis 2007; GiménezBenavides, Escudero & Iriondo 2007; Giménez-Benavides
et al. 2011), biotic factors such as the presence of pollinators
(Elzinga et al. 2007; Kilkenny & Galloway 2008; Sandring &
Ågren 2009) or seed predators (Elzinga et al. 2007; Parachnowitsch & Caruso 2008), or intrinsic factors such as plant
size (Ollerton & Lack 1998; Colautti & Barrett 2010). These
distinct selective forces may have opposing effects on flowering
time (e.g. Ehrlen & Munzbergova 2009) and may vary in magnitude and direction over time (Ollerton & Lack 1998).
Although we are far from fully understanding selection on
flowering time, a recent meta-analysis found consistent
phenotypic selection favouring early-flowering, especially in
2012 The Authors. Journal of Ecology 2012 British Ecological Society
Phenological shifts by artificial selection 853
temperate regions, supporting the importance of abiotic factors (Munguı́a-Rosas et al. 2011).
Flowering time in temperate populations of many taxa is
advancing as warmer climates result in earlier growing seasons
(e.g. Bradley et al. 1999; Fitter & Fitter 2002; Peñuelas, Filella
& Comas 2002; Parmesan & Yohe 2003; Parmesan 2007;
Gordo & Sanz 2009). These changes in flowering initiation
likely represent plastic responses to warmer temperatures
(Gordo & Sanz 2010). To date, little is known about whether
warmer climates also result in the selection for earlier reproduction (but see Bradshaw & Holzapfel 2006 for animal studies). Such a pattern of selection would be predicted if observed
plastic responses to temperature are adaptive. For example, in
Campanulastrum americanum, earlier flowering was found in
plants that experienced the earlier spring of an experimentally
expanded growing season and this early flowering was
favoured by selection (Haggerty & Galloway 2011). In summary, flowering time is frequently under selection, and this
selection is expected to intensify as populations respond to the
altered environmental conditions associated with warming
climates.
Although date of first flower has been the focus of most
research, it is only one stage in the seasonal reproductive process that starts with the differentiation of reproductive
meristems and finishes with the maturation of the final fruit.
A shift in the initiation of flowering in response to selection is
likely to influence the expression of subsequent reproductive
traits. In particular, the functionally related traits that comprise reproductive timing including seasonal patterns of
flower production, fruit maturation and seed dispersal (i.e.
phenology) are likely to be phenotypically integrated (e.g. Pigliucci 2003; Edwards & Weinig 2011). In turn, this reproductive phenology can have transgenerational effects, influencing
offspring trait expression. Therefore, changes in flowering
time are expected to have ripple effects throughout the life
cycle (Badyaev & Uller 2009; Donohue 2009). For example,
reproductive phenology can determine the abiotic environment during fruit maturation, specifically temperature and
photoperiod, and these may influence offspring germination
timing, survival and phenotype (e.g. Lacey 1996; Donohue
et al. 2005a,b; Walck et al. 2011). Reproductive phenology
also determines dispersal timing, which in turn influences offspring germination opportunities and the presence of seed
predators (reviewed in Lacey et al. 2003; Donohue 2005; also
Lacey & Pace 1983; Picó & Retana 2000; Parachnowitsch &
Caruso 2008; Galloway & Burgess 2009). Therefore, evolution of flowering time in response to either the observed widescale selection for earlier flowering, the diversity of selection
imposed by local biotic and abiotic factors or potential selection associated with warmer climates is likely to have broad
effects on a species’ life history. However, we know little
about the response of reproductive phenology to evolutionary
changes in flowering time.
Artificial selection is a powerful experimental tool to investigate the life cycle consequences of natural selection on a specific trait, such as flowering time (Conner 2003). In particular,
if the traits that comprise reproductive phenology are geneti-
cally correlated, evolution of one character will alter the
expression of the correlated traits. Thus, selection on flowering
time may alter the entire reproductive phenology. Experiments
have shown that environmental manipulations that affect
flowering time, such as warming, frequently shorten, but may
also lengthen the reproductive cycle (Sherry et al. 2007; Post
et al. 2008; Haggerty & Galloway 2011). This suggests that
even if reproductive phenology is not genetically correlated
with flowering time, the altered environmental conditions associated with a shift in flowering time may result in plastic
changes in reproductive phenology. Furthermore, in natural
habitats, many environmental factors influence reproductive
timing; for example, light, nutrients and water (reviewed in
Kelly & Levin 2000; Forrest & Miller-Rushing 2010; also
Dahlgren, von Zeipel & Ehrlen 2007; Jentsch et al. 2009; Crimmins, Crimmins & Bertelsen 2010; Munguı́a-Rosas et al.
2012). Testing artificial selection lines in natural environments
permits a thorough evaluation of potential plastic changes in
reproductive phenology associated with altered flowering
times. Such plastic changes may reduce or magnify the genetic
changes that represent correlated responses to selection.
Despite the potential for artificial selection to illuminate the
broad consequences of selection on specific traits, its use in
natural contexts has been limited.
Here, we use the herbaceous plant C. americanum, selected
for early- and late-flowering, to evaluate correlated responses
in reproductive phenology and whether their expression
depends on local environmental conditions. Campanulastrum
americanum’s life history schedule depends on the season of
germination. Fall-germinating plants grow as annuals, while
spring-germinating seedlings grow as biennials. In this forestedge species, local light environment is often heterogeneous
and influences life history frequency through the effects of the
maternal and offspring environments on germination season
(Galloway & Etterson 2007). In addition, the timing of maternal flowering and seed maturation influences the frequency of
annuals and biennials (Galloway & Burgess 2009).
The association of flowering time and life history schedule
may differ between light environments for C. americanum,
which typically flowers in the later part of the summer.
Early-flowering plants reproduce under warmer conditions
than late-flowering plants. Light gaps, which are typically
warmer than the understorey (Kilkenny & Galloway 2008),
further increase the temperature, potentially accelerating the
reproduction of early-flowering plants. Therefore, we expect
the evolution of early-flowering to alter reproductive phenology more in light gaps than under the canopy. In contrast,
reproductive phenology of late-flowering plants may be more
dramatically altered in the understorey where the initiation
of flowering is already delayed (Galloway & Etterson 2009),
and the combined genetic and environmental effects on flowering time place plants in a cooler part of the growing season. Cooler temperatures may slow reproductive phenology
and reduce fecundity. Therefore, to understand potential life
cycle consequences of the evolution of flowering time, correlated responses to selection must be studied in ecologically
relevant habitats.
2012 The Authors. Journal of Ecology 2012 British Ecological Society, Journal of Ecology, 100, 852–861
854 L. F. Galloway & K. S. Burgess
To evaluate the interplay between the timing of flowering
and local environmental conditions on reproductive phenology, we grew early-flowering, late-flowering and random-flowering C. americanum in understorey and light-gap regions of a
natural population. We then evaluated reproductive phenology to address the following questions. (i) Are genetic changes
in flowering time expressed under field conditions? (ii) Does
the response to selection differ between light-gap and understorey habitats? (iii) Do genetic changes in the initiation of
flowering influence subsequent reproductive phenology under
natural conditions? (iv) Are patterns of reproductive phenology similar between light-gap and understorey habitats? We
then combine these results with those of earlier studies to assess
the probability that genetic and environmental influences on
flowering time will have transgenerational effects, influencing
offspring life history schedule.
Materials and methods
STUDY SYSTEM
Campanulastrum americanum Small (=Campanula americana L.,
Campanulaceae) is a predominately outcrossing autotetraploid herb
(Gadella 1964; Galloway, Etterson & Hamrick 2003; Galloway &
Etterson 2005). The species is widely distributed throughout disturbed areas in eastern North America. Across this broad distribution, populations are typically located in areas with heterogeneous
light availability; for example, forest edges, roadsides and stream
banks. The study population is located on a steep hillside on Beanfield Mountain, near Mountain Lake Biological Station in south-western Virginia, USA (37¢21¢¢297N, 80¢33¢¢249W). In this population,
plants grow both under a deciduous forest canopy and in light gaps
caused by tree falls. On average, light gaps receive 10 times more radiation than understorey habitats (Galloway & Etterson 2007).
Campanulastrum americanum may grow as an annual or a biennial.
Vegetative rosettes must over-winter prior to flowering. Therefore,
season of germination determines an individual’s life history schedule. Seeds that germinate in the fall flower the following summer as
winter annuals. In contrast, seeds that delay germination until spring
remain a rosette for their first growing season and then flower in their
second summer as biennials. Maternal light environment and maternal flowering time influence germination season and therefore offspring life history schedule (Galloway 2002; Galloway & Etterson
2007; Galloway & Burgess 2009).
The influence of maternal flowering time on offspring life history
schedule is mediated through the reproductive phenology. Flowering
begins in mid-summer and, in the study population, continues until
the beginning of autumn. Flowers are tightly clustered in inflorescences located at nodes on the main stem and any side branches. Typically, single flowers are open at a node, with flowers in adjacent nodes
open at the same time. Flowers are predominately bumblebee pollinated (Galloway, Cirigliano & Gremski 2002; Kilkenny & Galloway
2008) and typically open for 2 days (Evanhoe & Galloway 2002).
When fruits mature, four pores open at the top and seeds disperse
passively when plants are jostled. Half of the seeds are dispersed
within 5 days of fruit maturation, and almost all seeds are dispersed
within 3 weeks (Galloway & Burgess 2009). There is no after-ripening
period (Baskin & Baskin 1984); therefore, seeds can germinate immediately following dispersal. Because there is a strong correlation
between when a flower is open and when the seeds from that flower
mature and disperse (Galloway 2002; Galloway & Burgess 2009),
maternal flowering time acts through reproductive phenology to
influence offspring life history schedule.
CREATION OF SELECTION LINES: ARTIFICIAL
SELECTION ON FLOWERING TIME
To evaluate whether evolution of flowering time may alter offspring
life history in C. americanum, three generations of artificial selection
for early-flowering, late-flowering and a control, selected at random
with respect to flowering time, were conducted under greenhouse conditions (see Burgess, Etterson & Galloway 2007 for details). Artificial
selection was initiated using 200 field-collected maternal seed families
from the study population. One hundred individuals were assigned to
each of two base populations to create independent replicate selection
lines. When flowering, the earliest flowering 20% (E), the latest flowering 20% (L) and a random control group (20%, C) in each base
population were crossed to produce six selection lines, one replicate
of each flowering-time treatment in each base population. Each plant
was crossed to three other members of its selected group acting either
as a male (pollen donor) in two crosses and a female (pollen recipient)
in one cross or as a male once and a female twice, resulting in 30 families per selection line. One hundred plants from these crosses, evenly
distributed among families, were grown from each selection line to
form the next generation. Following three generations of selection
using the same procedure, seeds (fourth generation) were grown in
the greenhouse to evaluate the response to selection on flowering
time. Plants from the early-flowering selection lines flowered on average 25.4 days before plants in the late-flowering selection lines, while
the control lines were intermediate (Burgess, Etterson & Galloway
2007). Seeds from this same generation were planted into their home
population for the current study.
EARLY- AND LATE-FLOWERING SELECTION LINES
UNDER FIELD CONDITIONS
Seeds from the six selection lines were germinated under controlled
conditions to remove potential differences in the season of germination that may have arisen as a correlated response to selection. Six
seeds from each family in the early (E1 and E2, 28 families each), control (C1 28 families and C2 30 families) and late (L1 and L2, 30 families each) selection lines were individually germinated in the growth
chamber in a fully randomized design for a total of 1044 seeds. Seeds
were planted in plug trays in a 6 : 1 ratio of Pro-Mix BX (Premier
Hort., Quebec, Canada) to fritted clay. Trays were placed in a growth
chamber with 21 C day ⁄ 12 C night, 12 h days for 42 days.
Then, the temperature was reduced to 5 C for 7 weeks to stimulate
flowering.
Plants were transplanted into light-gap and understorey areas of
their home population after snowmelt at the end of March. Thirteen
blocks were haphazardly located in each light environment. Five
plants from each selection line were planted in randomized locations
in each block for a total of 65 plants per line per light environment.
Blocks were cleared of other vegetation prior to planting, and rosettes
were located 25 cm from each other. To minimize transplant shock,
plants were watered after planting. Blocks were surrounded by plastic
mesh to prevent deer browsing. Post-transplant mortality reduced the
number of plants that reached flowering in each selection treatment
and light environment (summed over replicate lines) to 117 earlyflowering, 122 control and 114 late-flowering in the understorey and
82 early-flowering, 91 control and 76 late-flowering in the light gaps.
2012 The Authors. Journal of Ecology 2012 British Ecological Society, Journal of Ecology, 100, 852–861
Phenological shifts by artificial selection 855
Reproductive phenology was scored on all plants. After bolting,
plants were checked daily for the date of first flower. Reproductive
phenology was scored weekly on a five-node section of the main stem
including the first flowering node and the four nodes immediately
above it. Each week, the number of flowers, unripe fruit and mature
fruit were recorded. Mature fruit were those that had dehisced and
could disperse seeds. On many understorey plants, the five-node segment represented the majority of reproductive nodes, whereas it was
closer to a third of the main stem nodes on light-gap individuals. The
number of open flowers on each plant was also counted weekly
throughout the reproductive season to estimate the seasonal patterns
of flower deployment. Total flower production was estimated by the
sum of these weekly whole plant counts. Individual flowers are typically open 2 or 3 days (Evanhoe & Galloway 2002); therefore, this
total is likely an underestimate of the actual flower production. The
end of reproduction, which approximates the end of seed dispersal,
was recorded as the date on which almost all fruit in the five-node
section had dehisced (£ 5 immature fruits remaining).
Seasonal patterns of flower production and fruit maturation for
each plant were summarized with ‘average flower date’ and ‘average
dispersal date’, respectively. Average flower date is a weighted
average of the dates flowers were produced throughout the season. It
was calculated by weighting each census date by the proportion of an
individual’s total flower production that was open on that date and
summing over all census dates (cf. Nuismer & Cunningham 2005).
Similarly, average seed dispersal date, calculated for the five-node
segment on each individual, represents a weighted average of the date
when an individual’s fruits matured and began dispersing seeds.
Average flower and dispersal dates are influenced by the duration,
variation and skew of these phenological processes. While not a substitute for examining seasonal patterns, they permit the distribution
to be represented by a single number. Finally, the duration of reproduction was estimated by the number of days between the start of
flowering and the end of reproduction.
STATISTICAL ANALYSIS
The response to selection on flowering time and correlated responses
in reproductive phenology in the contrasting light environments was
evaluated using analysis of variance (Proc MIXED, SAS Institute
2009). Selection treatment, line nested within selection treatment, and
light environment were included as fixed effects in the analysis,
whereas block was treated as a random effect and nested within environment. The interactions between light environment and both selection treatment and selection line within treatment were also included
in the model. Following a significant effect of the selection treatment,
Tukey’s multiple comparisons of means were used to determine which
treatments differed at a = 0.05. To meet the assumptions of normality, average flower date and average dispersal date were ln-transformed prior to analysis.
Analysis of covariance was used to separate stage-specific effects of
the selection treatments and environment on phenological traits from
the carry-over of effects expressed earlier in ontogeny. In the analysis,
the previous phenological stage was included as a covariate, thereby
permitting a test of genetic and environmental effects on the current
phenological stage. Specifically, date of first flower was the covariate
in the analysis of average flower date, average flower date was the
covariate for average dispersal date and average dispersal date was
the covariate for end of reproduction. All traits and covariates were
ln-transformed providing a uniform scale for variables. We inspected
the data for each covariate (previous phenological stage) to ensure
that there was an overlapping distribution among treatments, despite
differences in means. On average, there was an 83% overlap in distribution of the covariates among treatments (73% average flower date,
82% average dispersal date and 95% end of reproduction) indicating
that it was appropriate to use the previous phenological stage as a covariate, although it did vary among treatments. Structured equation
modelling is a more traditional analytical tool to address stage-specific effects. However, the sequential nature of phenology precludes
developing the branched model required for this approach. Duration
of reproduction was not included in this analysis as it encompasses all
post-flowering traits.
Results
Response to selection on flowering time was expressed under
field conditions. Plants in the late-flowering selection lines initiated flowering on average 15 days after those in the early-flowering selection lines. The unselected controls were in between,
flowering on average 5 days after the early lines and 10 days
before the late lines (Table 1A, Fig. 1a).
Light environment had a strong influence on flowering time
with plants in the understorey flowering on average 8 days
after those in light gaps (Table 1A, Fig. 1a). However, there
was no difference in the expression of response to selection
between light environments (Table 1A). On average, late-flowering lines flowered 15 days and control lines 5 days, after the
early-flowering lines regardless of whether plants were grown
in light gaps or understorey habitats (Fig. 1a).
The differences between the early- and late-flowering
selection lines were also found in later reproductive traits.
Average flower date of the late-flowering selection lines
was 17 days later, average dispersal date was 16 days later
and the end of reproduction was 17 days later than the
early-flowering selection lines (Table 1A, Fig. 1b–d). Similarly, average flower date, average dispersal date and the
end of reproduction of the control lines were 5 or 6 days
later than the early-flowering selection lines and 11 days
before the late-flowering selection lines. When the previous
phenological stage was included as a covariate in the analyses, none of the differences between the selection treatments remained significant (Table 1B). Therefore,
differences in reproductive phenology between the earlyand late-flowering selection lines can be attributed to the
altered initiation of reproduction.
Reproductive phenology was more similar than flowering
date between light-gap and understorey habitats. Although
plants grown in the understorey initiated flowering 8 days after
those in light gaps, there was no difference in average flower
date between the two light environments (Table 1A, Fig. 1b).
Average dispersal date showed a similar pattern of no difference in timing between the light environments with the exception of early-flowering selection lines that dispersed their seeds
earlier on average in light gap than understorey habitats
(Table 1A: light*selection, Fig. 1c). The end of reproduction,
in contrast, was slightly later in the light gaps than in the understorey (Table 1A, Fig. 1d). This 6-day delay in the end of
reproduction in the light-gap environments was found across
the flowering-time treatments.
2012 The Authors. Journal of Ecology 2012 British Ecological Society, Journal of Ecology, 100, 852–861
856 L. F. Galloway & K. S. Burgess
Table 1. Analysis of variance (A) and covariance (B) of reproductive phenology in Campanulastrum americanum selected for three generations
for early-flowering, late-flowering and randomly with respect to flowering. Individuals were grown in light-gap and understorey regions of their
home population
Source
d.f.
(A)
Light†
Selection
Line (Selection)
Light*Selection
Light*Line (Sel)
Block (Light)
Denominator d.f.
(B)
Light†
Selection
Line (Selection)
Light*Selection
Light*Line (Sel)
Block (Light)
Covariate
Denominator d.f.
1
2
3
2
3
–
Flowering
start
Average
flower date
Average
dispersal date
54.33***
164.81***
2.85*
0.56
0.23
2.23*
565
2.60
141.30***
0.31
0.07
1.00
2.62**
555
3.36(*)
61.97***
1.07
3.81*
2.33(*)
2.98**
546
5.97*
63.32***
0.46
1.93
1.35
2.71**
517
36.30***
0.31
4.36**
1.66
0.87
2.64**
721.32***
553
3.05(*)
1.00
2.43(*)
5.75**
4.49**
2.80**
716.57***
545
112.61***
0.26
0.61
0.13
0.98
1.64*
4023.61***
501
1
2
3
2
3
–
1
End of
reproduction
Duration of
reproduction
34.01***
1.37
0.77
3.91*
1.45
2.81**
512
†Denominator d.f. = 24.
In the ancova, the previous phenological stage was included as a covariate to separate stage-specific effects from the carry-over of effects
expressed earlier in ontogeny, see text for details. F-values are reported for fixed effects and Z-values for random effects. (*)P < 0.1;
*P < 0.05, **P < 0.01 and ***P < 0.001.
Flowering time selection line
E1
E2
C1
C2
(a)
Average flower date
Flowering start
15-Aug
5-Aug
26-Jul
16-Jul
4-Sept
25-Aug
15-Aug
Understorey
Light gap
(c)
14 Oct
End of reproduction
Average dispersal date
L2
5-Aug
Light gap
4-Oct
L1
(b)
24-Sept
14-Sept
4-Sept
Understorey
(d)
4-Oct
24-Sept
14-Sept
4-Sept
25-Aug
Light gap
Understorey
Light gap
Understorey
Fig. 1. Mean (SE) date of the start of flowering (a), average flower date (b), average seed dispersal date (c) and end of reproduction (d) in Campanulastrum americanum selected for three generations for early-flowering (lines E1 & E2), late-flowering (lines L1 & L2) and a control (lines C1
& C2), selected randomly with respect to flowering time. Plants were grown in light-gap and understorey regions of their home population.
Environmental effects on reproductive timing were stronger
after accounting for earlier phenological traits (Table 1B). For
example, after adjusting for differences in the initiation of
flowering, the average flower date was 6 days later in light gaps
than in the understorey, suggesting that flowers are deployed
over a broader window of time in light gaps (Fig. 2a,b).
2012 The Authors. Journal of Ecology 2012 British Ecological Society, Journal of Ecology, 100, 852–861
Phenological shifts by artificial selection 857
Light gap
(a)
Prop. fruit dispersing seeds
Proportion seasonal flowers
Late flowering
Control
Early flowering
0.3
0.2
0.1
0
1.0
(c)
0.8
0.6
0.4
0.2
0.0
0.3
0.2
0.1
0
Prop. fruit dispersing seeds
Proportion seasonal flowers
Understorey
(b)
1.0
(d)
0.8
0.6
0.4
0.2
0.0
Fig. 2. Seasonal patterns of flowering and fruit maturation for Campanulastrum americanum selected for three generations for early-flowering,
late-flowering and a control, selected at random with respect to flowering time. Weekly whole plant flower counts were summed over the reproductive season, and the proportion of the seasonal total open each week was averaged across individuals and replicate selection lines (a, b). The
proportion of the total number of fruit that were mature and potentially dispersing seeds that were present each week in the five-node segment
(c, d). Plants were grown in light-gap and understorey regions of their home population.
Similarly, after accounting for differences in average dispersal
date, reproduction finished more slowly in the light gaps than
the understorey (Fig. 2c,d). In contrast, after accounting for
differences in average flowering date, average dispersal date
was similar between light environments for control and lateflowering selection lines, but for the early-flowering selection
lines was later for understorey than light-gap plants.
Although shifts in average flower date among the three
selection treatments were similar to that of initiation of flowering, patterns of floral deployment differed somewhat among
the selection treatments (Fig. 2a,b). Early-flowering plants had
a broad early peak; in the light gap, two-thirds of the season’s
flowers were produced in that peak. In contrast, flower production in the control lines grown in light gaps had a discrete peak
where 30% of the season’s flowers were open on a single day.
Finally, in the late-flowering selection lines, peak flowering
included a smaller proportion of the season’s flowers with a
greater proportion of flowers produced on plants that had
been flowering longer.
There was a greater difference in seed dispersal patterns than
seasonal flowering phenology between the light environments.
Seasonal patterns of flower deployment were similar between
light-gap and understorey habitats with early-flowering selection lines having a broader early peak and all three flowering
treatments having a synchronized but smaller later peak
(Fig. 2a,b). In contrast, while the differences between the selection lines were comparable across both light environments for
seed dispersal, the temporal pattern differed. Mature fruit
began dispersing seed over a longer time period in light gaps
than in the understorey (Fig. 2c,d). For example, in the understorey early-flowering, control and late-flowering selection
lines had 43%, 42% and 31% of their fruit ripen in 1 weekly
census interval. In contrast, in the light gaps, the interval with
the peak fruit ripening had only 20% of the fruits initiate seed
dispersal, regardless of selection line. A condensed seed dispersal period resulted in an earlier end to reproduction in the
understorey (Fig. 1d). In total, with a later start and a more
rapid finish, the reproductive phenology was more condensed
in understorey than light-gap habitats (Table 1A, Fig. 3).
Although the duration of reproduction was longer in light
gaps, the difference between light environments was greater
for the late-flowering selection lines (18 days) than for the
early-flowering or control lines (11 and 13 days, respectively;
Table 1A and Fig. 3).
Discussion
Response to artificial selection on flowering date was expressed
under natural environmental conditions in C. americanum.
Three generations of selection for earlier and later flowering in
controlled, greenhouse conditions resulted in a divergence of
25 days in greenhouse-grown plants (Burgess, Etterson &
Galloway 2007). When plants from the same generation were
planted into the natural habitat of the source population, lateflowering selection lines initiated flowering on average 15 days
after the early-flowering selection lines. This difference
between selection lines was found regardless of whether plants
were grown in understorey or light-gap regions of the natural
2012 The Authors. Journal of Ecology 2012 British Ecological Society, Journal of Ecology, 100, 852–861
858 L. F. Galloway & K. S. Burgess
Early flowering
Control
Late flowering
Selection treatment
Start
reproduction
Average
flower date
Average
dispersal date
End
reproduction
Light gap
Understorey
Light gap
Understorey
Light gap
Understorey
16-Jul
5-Aug
25-Aug
4-Sept
24-Sept
14-Oct
Fig. 3. Reproductive phenology for Campanulastrum americanum selected for three generations for early-flowering, late-flowering and a control,
selected at random with respect to flowering time. For each selection treatment, averaged across replicate lines, the dates of first flower, the production of the average flower, the average dispersal date and the end of reproduction are shown. The length of the bar indicates the duration of
reproduction.
population, despite a tenfold difference in light availability. In
addition, response of flowering time to selection was similar
between the independent lines within each treatment. A 15-day
difference in flowering time between the selection treatments is
substantial in this species where the mean initiation of flowering among years within a light environment varies by less than
a week (Galloway 2002; Galloway & Etterson 2009; Lin &
Galloway 2010). In contrast, flowering time may be substantially more variable in other taxa (e.g. Ollerton & Diaz 1999;
Tarayre et al. 2007; Kudo et al. 2008).
Consistency in the expression of flowering time across environments was not necessarily expected because the expression
of quantitative traits is environment-dependent. For example,
controlled-environment results from artificial selection for
temperature tolerance in Drosophila were found only half of
the time in natural conditions (Kristensen, Volker &
Hoffmann 2007). For flowering time, where the molecular
basis of the trait is fairly well understood, studies have found
different QTLs influence trait expression between experimental
environments (i.e. day-length Weinig et al. 2002; Blackman
et al. 2011) and between controlled and field environments
(Weinig et al. 2002; Anderson, Lee & Mitchell-Olds 2011). The
altered genetic architecture suggests trait expression will differ
across environments. As an example, there was a low correlation between greenhouse and field expression of flowering time
in Boechera (average R = 0.22, Anderson, Lee & MitchellOlds 2011). In contrast, the relatively consistent expression of
selection response in field-grown C. americanum suggests limited genotype-by-environment interaction for genes that determine flowering time under a range of natural conditions.
Selection on flowering time altered the phenology of all subsequent reproductive traits. Correlated responses to the selection on flowering time were found for average flower date,
average dispersal date and the end of reproduction. All these
traits shifted as a consequence of selection at least as much as
flowering date itself, suggesting that they are tightly correlated
with the timing of flowering (Falconer & Mackay 1996). The
tight correlation was further supported by the similarity
among selection treatments when the previous phenological
trait was included as a covariate in the analysis. This result
indicates that there were no stage-specific effects of the selection treatments on phenology beyond altering flowering time;
all differences in reproductive phenology between the selection
treatments represent the carry-over of effects expressed earlier
in ontogeny. In other species, it is typically not known whether
phenological changes associated with a shift in flowering time
represent independent responses to environmental conditions
or the carry-over of earlier effects (e.g. Lacey et al. 2003;
Sherry et al. 2007; Post et al. 2008). A previous study that
altered flowering time in C. americanum through environmental manipulation also found reproductive phenology showed
strong phenotypic integration (Galloway & Burgess 2009).
However, that integration was environmentally based, whereas
the strong phenotypic integration in these artificial selection
lines likely has both genetic and environmental components.
Regardless, the strong integration of reproductive phenology
suggests that selection on flowering time in natural populations
will alter the timing of all subsequent stages of reproduction.
Selection lines planted in the forest understorey flowered on
average 8 days after those in light gaps. This result mirrors previous studies in C. americanum (Galloway & Etterson 2009;
Lin & Galloway 2010) and other herbaceous taxa (e.g. Sultan
2001; Steinger, Roy & Stanton 2003), although the reverse, earlier flowering with increased shade is a common shade-avoidance response (reviewed in Smith & Whitelam 1997; also
Donohue et al. 2001; Callahan & Pigliucci 2002). However,
differences in timing across light environments were not found
for the later traits, average flower date and average dispersal
2012 The Authors. Journal of Ecology 2012 British Ecological Society, Journal of Ecology, 100, 852–861
Phenological shifts by artificial selection 859
date (two of the three selection treatments), despite the tight
correlation in reproductive phenology found among selection
treatments. Even more so, when the previous phenological
stage was accounted for, later phenological traits were reached
at a relatively earlier time in the understorey. Therefore,
although average flower date was the same between understorey and light-gap habitats, later initiation of flowering for
understorey plants resulted in a shorter time interval between
phenological stages than plants in light gaps. The same pattern
was found without accounting for earlier phenology in the earlier end of reproduction in the understorey relative to light
gaps. Over the time span of reproduction, the cumulative effect
of these differences in phenology across light environments
was a 29% longer reproductive period in light gaps than in the
understorey, a pattern comparable to typical shade-avoidance
responses (Smith & Whitelam 1997). These differences, in part,
are driven by divergence in the size of plants in the two light
environments. When plant size was included as a covariate, differences between the light environments were reduced (results
not shown), indicating the smaller plants, such as those found
in the understorey, have a shorter reproductive period (e.g.
Ollerton & Lack 1998).
Although flowering was uniformly delayed in all selection
lines in the understorey, later reproductive traits had modest
differences in response to the light environment between the
flowering time treatments. For example, seed dispersal date
was earlier in light gaps than the understorey for the earlyflowering selection lines but not the other lines, and late-flowering lines lengthened their reproductive duration in light gaps
slightly more than early-flowering or control lines. However,
these differences in response to the light environment between
the selection lines were modest. Reproductive phenology was
most strongly influenced by genetic differences that were
expressed across environments and responses to the light environments that were expressed across all selection lines. Similarly, in Brassica rapa, selection due to natural drought
resulted in earlier flowering but no difference in plasticity in
response to experimental drought (Franks 2011).
Altering reproductive phenology may influence offspring
life history schedule in C. americanum. Because fall-germinating seeds grow as annuals, while spring germinants have a
biennial life cycle, shifting the reproductive phenology may
change life history frequency. Earlier work in this population,
simulating an expanded seed dispersal window, found that
seeds planted early, at the end of the summer, were more likely
to germinate as annuals, while seeds planted later, in midautumn, were more likely to germinate as biennials (Galloway
& Burgess 2009). The average dispersal date measured here is a
summary statistic that represents the dispersal time of the average fruit on the main stem of each plant. The average dispersal
date of the late-flowering selection lines was over 2 weeks later
than the early-flowering selection lines. Therefore, on average,
more annual offspring are expected from the early-flowering
selection lines and more biennial offspring from the late-flowering selection lines. The extent to which a 2-week shift in dispersal time would be expected to alter offspring life history
depends on the light environment. Germination frequency of
annuals in the understorey declines linearly with planting date
until the first week in September (Galloway & Burgess 2009).
After that, the germination frequency of annuals is small
through September and near-zero for later planted seeds. In
the current study, by the first week of September, only earlyflowering selection lines had a non-negligible proportion of
fruit that were dispersing seeds, suggesting that only these lines
would be likely to produce annual offspring in the understorey.
Although less information is available about the relationship
between dispersal time and germination season for seeds dispersed in light gaps, germination of annuals is more common
in light gaps than in the understorey (Galloway & Etterson
2007), and more annuals germinate from early planted seeds in
these gaps (L. F. Galloway & K. S. Burgess, unpubl. data).
Therefore, we again expect a greater frequency of annuals from
the early-flowering selection lines that ripened their fruits
before the late-flowering lines.
In contrast to the genetic differences in flowering time, our
results suggest that light environment is not expected to influence offspring life history schedule. Seed dispersal time was the
same across light environments for control, late-flowering and
one of the early-flowering selection lines, indicating that the understorey light habitat, while delaying the initiation of reproduction, does not similarly delay seed dispersal. Indeed,
estimating life cycle or transgenerational influences of the light
environment from flowering date alone would be inaccurate. In
total, although annuals are more common in light gaps and
biennials in the understorey (Galloway & Etterson 2007), results
presented here suggest these differences are due to the germination environment and not to the timing of seed dispersal.
Evolution of flowering time in response to selection, such as
the pervasive selection for earlier flowering in temperate populations (Munguı́a-Rosas et al. 2011), requires genetic
variation. In C. americanum, there is substantial genetic variation for flowering time in natural populations. Following three
generations of selection where 20% of the population contributed to the next generation, flowering time of the early and late
selection lines was separated by over 2 weeks under field
conditions. Other studies that have found strong response to
selection on flowering time have often started with composite
populations representing a diverse genetic pool (e.g. Campbell
et al. 2009; Van Dijk 2009). It is noteworthy that in C. americanum, within a single natural population, there was sufficient
genetic variation to result in substantial, ecologically relevant,
evolutionary change following only three generations of selection. The estimated heritability (0.44; Galloway, Etterson &
McGlothlin 2009) and realized heritability (0.31 early-flowering, 0.23 late-flowering; Burgess, Etterson & Galloway 2007)
of flowering time in C. americanum are similar to the estimates
in other taxa (0.38; Geber & Griffen 2003). This similarity suggests that phenotypic selection, such as that imposed by warmer climates, will likely alter flowering time in C. americanum
and a range of other plant taxa.
Evolution of flowering time is likely to alter traits throughout the life cycle, in part by creating transgenerational effects.
The extent to which changes in flowering time have cascading
effects throughout the life cycle depends on whether correlated
2012 The Authors. Journal of Ecology 2012 British Ecological Society, Journal of Ecology, 100, 852–861
860 L. F. Galloway & K. S. Burgess
responses to selection expressed in subsequent phenological
traits maintain, reduce or enhance the changes in flowering
time. In addition, expression of life cycle effects also depends
on whether plasticity to local conditions, such as the light environment, enhances or reduces the shift in flowering time.
Between-generation consequences of flowering time evolution
represent indirect genetic effects (Wolf et al. 1998), and evolutionary change in a trait that itself is not under direct selection.
The combination of between-generation indirect genetic effects
with within-generation genetic correlations results in the
potential for selection on a single trait to alter the expression of
a suite of other traits. Similar patterns of evolution are equally
likely in animals indicating the broad relevance of these ideas;
for example, life history trade-offs (Roff 2002) or the influence
of maternal provisioning or body size on offspring traits
(Mousseau & Fox 1998; Räsänen & Kruuk 2007). In summary, the presence of widespread linkages among traits must
be recognized in order to understand the potential shifts in
phenotype in response to selection.
Acknowledgements
We thank C. Ballare, R. Gittman, B. Haggerty, L. Lee, J. Painter, D.
Stone, H. Truong and T. Kugler for assistance; Mountain Lake Biological
Station for logistical support; the Galloway laboratory for comments on
the manuscript; and NSF DEB-0316298, NSF DEB-1020717 and a UVAFEST award to LFG for financial support.
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Received 14 October 2011; accepted 20 February 2012
Handling Editor: Honor C. Prentice
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