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LETTER
Herbarium specimens reveal the footprint of climate change
on flowering trends across north-central North America
Kellen M. Calinger,* Simon
Queenborough and Peter S. Curtis
Department of Evolution, Ecology
and Organismal Biology, The Ohio
State University, Columbus, OH,
USA
*Correspondence: E-mail: kcalin-
ger@gmail.com
Abstract
Shifting flowering phenology with rising temperatures is occurring worldwide, but the rarity of co-occurring
long-term observational and temperature records has hindered the evaluation of phenological responsive-
ness in many species and across large spatial scales. We used herbarium specimens combined with historic
temperature data to examine the impact of climate change on flowering trends in 141 species collected
across 116,000 km
2
in north-central North America. On average, date of maximum flowering advanced
2.4 days °C
1
, although species-specific responses varied from 13.5 to + 7.3 days °C
1
. Plant functional
types exhibited distinct patterns of phenological responsiveness with significant differences between native
and introduced species, among flowering seasons, and between wind- and biotically pollinated species. This
study is the first to assess large-scale patterns of phenological responsiveness with broad species representa-
tion and is an important step towards understanding current and future impacts of climate change on spe-
cies performance and biodiversity.
Keywords
Climate change, invasive species, life history, phenological responsiveness, phenology, pollination syn-
drome.
Ecology Letters (2013) 16: 1037–1044
INTRODUCTION
Phenology, the timing of key life events, is one of the most sensi-
tive biological indicators of climate change (Pe~nuelas & Filella 2001;
Menzel 2002) and its study has become an important tool for
understanding the impacts of warming from local to global scales.
Shifts in plant phenophases (e.g. budburst, leaf senescence and
flowering) over time, correlated with temperature change, have been
documented worldwide and are consistent with climate change pre-
dictions (Parmesan & Yohe 2003). This evidence of alterations in
plant phenology suggests that increased temperatures may already
be impacting species performance and modifying within-community
interactions (Menzel et al. 2006; Rosenzweig et al. 2008).
However, phenological responses to increased temperature are
highly variable, even among closely related species (Abu-Asab et al.
2001; Fitter & Fitter 2002). For example, in North America, Solidago
rugosa advanced flowering by ~ 11 days °C
1
, while Solidago graminifo-
lia showed no temperature response (Miller-Rushing & Primack
2008). In the United Kingdom, Geranium pyrenaicum advanced its first
flowering date (FFD) 3 days between 1954 and 2000 whereas
Geranium rotundifolium showed a 6 days delay in FFD over the same
time period (Fitter & Fitter 2002). As a result of such species-spe-
cific differences in phenological responsiveness to temperature
shifts, climate change may non-randomly alter community assem-
blages as species less well adapted to the new temperature regime
decrease in abundance (Willis et al. 2008).
The magnitude of a species’ phenological response to temperature
may have either positive or negative impacts on growth and repro-
duction depending on various interacting environmental factors. For
instance, phenologically responsive species may benefit from greater
early season productivity (Kudo et al. 2008) leading to an increase in
abundance. Mungia-Rosas et al. (2011) suggested that phenotypic
selection favours earlier blooming species in temperate regions.
Alternatively, earlier flowering can increase risk of frost exposure
(Inouye 2008) or may lead to pollinator mismatch, the disconnect
between pollinator availability and flowering as a result of differing
responses to environmental cues (Kudo et al. 2008). Both scenarios
may lead to decreased local species abundance. In the northeastern
US, Willis et al. (2008) found that species with weak flowering
responses to temperature have disproportionately decreased in
abundance over the past 150 years.
Although species-specific phenological responsiveness is likely to
have significant fitness implications with future warming, it is impossi-
ble to assess responsiveness for all species in a given area. However,
certain life history traits may predispose particular functional groups
to be more or less phenologically responsive and we may be able to
use these traits to predict how currently unstudied species will
respond to warming. Further, if plant functional groups do differ in
their phenological responsiveness, leading to increasing variance in fit-
ness, communities may be drastically altered by non-random patterns
of species removal. Thus, the ability to make generalised predictions
based on functional traits would benefit conservation efforts by allow-
ing identification of species most likely to be negatively impacted (in
terms of phenological responsiveness) by temperature increase, as
well as identifying whole communities that may be at risk.
Despite the potential impacts of climate change on species perfor-
mance, few studies have included sufficient species to examine pat-
terns of phenological responsiveness among functional groups
because of the lack of long-term flowering and temperature datasets
that overlap in time and space. The paucity of direct observational
data spanning decades to centuries with broad species representation
has led to key information gaps on species’ and functional groups’
responses to climate change, making generalised predictions of com-
munity responses to climate change challenging. To date, only three
studies have directly evaluated phenological responsiveness to cli-
mate change among plant functional groups (Fitter et al. 1995; Fitter
© 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use,
distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
Ecology Letters, (2013) 16: 1037–1044 doi: 10.1111/ele.12135
& Fitter 2002; Miller-Rushing & Primack 2008). In these studies,
FFDs of species growing under natural conditions were obtained
from observational records that ranged from over 150 years (Miller-
Rushing & Primack 2008; with several large gaps in the collection
record) to less than 40 years (Fitter et al. 1995). While differences in
phenological responsiveness among plant functional groups were
documented, these studies were conducted over relatively small areas
and do not allow evaluation of flowering trends across broad spatial
scales (but see Lavoie & Lachance 2006).
An alternative to the traditional historic observational dataset is the
analysis of plants preserved in herbarium collections (Primack et al.
2004; Lavoie & Lachance 2006; Miller-Rushing et al. 2006; Robbirt
et al. 2011; Panchen et al. 2012). For example, by extracting flowering
date information on specimens from individual plants collected mul-
tiple times at the Arnold Arboretum from 1885 to 2002 and combin-
ing that data with long-term local temperature records, Primack et al.
(2004) found a significant advancement in flowering phenology asso-
ciated with increasing spring temperatures. To determine the validity
of herbarium-based methods for evaluating phenological responsive-
ness, Robbirt et al. (2011) calculated the flowering response of Ophrys
sphegodes to mean spring temperature (March through May) using
both direct observations of peak flowering time and herbarium speci-
mens. The herbarium specimens were collected between 1848 and
1958 while the observational data set spanned 1975 to 2006. Pheno-
logical response to temperature calculated using herbarium specimens
was statistically indistinguishable from the response calculated from
direct field observations (Robbirt et al. 2011). These initial herbar-
ium-based methods were an important step towards increasing our
ability to assess flowering shifts in areas without historic data sets.
However, these methods require intensive historic sampling of a sin-
gle study site as they do not allow for spatial variation in the tempera-
tures paired with individual herbarium specimens. This intensive
sampling is not characteristic of most locations and therefore leaves
many regions still inaccessible to study.
Here, we introduce a new herbarium-based method that allows
the assessment of flowering phenology in large numbers of species
collected across broad geographical regions. We evaluated the phe-
nological responsiveness to temperature of 141 species recorded
over a period of 115 years across a 116,000 km
2
region in north-
central North America. We quantified differences in responsiveness
among plant functional groups defined by flowering season, growth
form, pollination syndrome and native status.
We tested a number of hypotheses: (1) spring flowering species
are more responsive to temperature change than those flowering in
early- or late-summer because advancing phenology among spring
flowering species may enhance pollinator availability and increase
access to light prior to canopy closure (Elzinga et al.2007; Kudo
et al.2008); (2) herbaceous annuals are more phenologically respon-
sive than herbaceous perennials or woody perennials because earlier
flowering may benefit annuals through reduced competition for
pollinators and early-season productivity gains during favourable
weather which are crucial for enhancing fitness in their single grow-
ing season (Mungia-Rosas et al. 2011); (3) insect-pollinated species
respond more to temperature change than wind-pollinated species
because insect-pollinated species may respond to selection promot-
ing earlier flowering to maintain pollinator mutualisms (Fitter &
Fitter 2002); and (4) introduced species advance flowering more
than native species to take advantage of currently unoccupied phe-
nological niches (Wolkovich & Cleland 2011).
Our results support previously published patterns of responsive-
ness among different seasons of flowering and growth forms but
differ from previous work with regard to native status and pollina-
tion syndrome. Our analysis of phenological responsiveness among
many species and plant functional groups in a variety of locations is
an important step towards understanding the impacts of climate
change on species performance and biodiversity.
METHODS
To evaluate flowering phenology, we visually examined specimens
of plant species collected in the US state of Ohio (c. 116,000 km
2
,
between 38
o
and 42
o
north latitude and 80
o
and 85
o
west longitude)
from the Ohio State University herbarium. All specimens with
greater than 50% of flower buds in anthesis were considered at
peak flowering at the time of collection and were included in our
analysis (Primack et al. 2004). However, specimens of the same spe-
cies with identical collection date, location and collector were
included as a single datum to avoid non-independence of samples.
Because we included only those specimens at peak flowering, some
species, such as grasses, were necessarily excluded.
The date of peak flowering (D
i
) and collection location were
recorded from the label attached to each specimen. From the col-
lection location, specimens were assigned to one of the ten climate
divisions established by the US National Oceanic and Atmospheric
Administration (NOAA) for Ohio (See Appendix S1).
We used average monthly temperature data from the US Histori-
cal Climatology Network (USHCN, Menne et al. 2010) to calculate
the average monthly temperature,
T
mjk
, for each climate division in
each year;
T
mjk
¼ RT
myk
=n ð1Þ
where m is month, j is climate division, k is year, y is a recording
station within a division, and n is the number of recording stations
within division j. Of the 10 climate divisions in Ohio, all but one
had multiple USHCN climate stations. Thus,
T
mjk
is the average of
individual USHCN recording station temperatures within a climate
division. Locations of Ohio’s 26 USHCN stations are situated to
minimise urban heat island effects and have remained constant since
1895, thus making their data particularly useful for climate change
studies.
Phenological responsiveness
To determine the effect of temperature on flowering date, or a spe-
cies’ phenological responsiveness (q
x
, day °C
1
), we regressed D
i
against the average temperature of each specimen’s month of flow-
ering and the 3 months prior (
T
4i
), for that specimen’s year and cli-
mate division of collection. That is,
D
xi
¼ b
x
þ q
x
ðT
4i
Þð2Þ
where D
xi
is the flowering date of specimen i in species x, T
4i
is
the average temperature of the month of D
xi
and 3 months prior,
and q
x
is the slope, or temperature effect size, of this relationship.
For example, if a specimen was collected on May 26, 1940, in cli-
mate division 10, it would be paired with the average combined
temperatures of February, March, April and May, 1940 in that cli-
mate division (in this example, 5.21 °C, see Appendix S2). The
regression model for each species was built from specimens col-
© 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS
1038 K. M. Calinger, S. Queenborough and P. S. Curtis Letter
lected in different years and from a variety of climate divisions, with
a minimum of 10 specimens required for each regression. To estab-
lish the temperature averaging period,
T
4i
, we correlated D
xi
for
every species with the average temperature of its month of flower-
ing and the 11 months prior (see Miller-Rushing & Primack 2008
and Appendix S2). We found strong correlations between D
xi
and
the average temperature of the month of D
xi
and 3 months prior,
and thus used
T
4i
in the regression models. However, as species
flowering in April were not strongly correlated with average January
temperatures, D
xi
for these species were regressed only against Feb-
ruary, March and April monthly average temperatures. Flowering
time of species flowering in late-summer were typically not strongly
correlated with temperature and were also regressed against
T
4i
.
While precipitation is often cited as an important driver of phenol-
ogy in tropical environments (Rathcke & Lacey 1985), we did not
assess the impacts of precipitation on phenological responsiveness
as temperature is generally considered the primary variable driving
phenology in temperate mesic environments such as our study site.
A total of 141 species (x = 141) using 5053 specimens (i = 5053)
were included in our analysis with sample sizes ranging from 10 to
235 specimens per species (see Appendix S3).
Functional groups
Each species was characterised based on its season of flowering
[spring (April to May), early summer (June to July) or late summer
(August or later)], pollination syndrome (wind or insect, and faculta-
tive or obligate outcrossing), origin (native or non-native to North
America) and growth form (woody perennial, herbaceous perennial,
herbaceous annual or perennial vine). Information on species’ growth
forms was obtained from the USDA Plants Database [http://www.
nrs.fs.fed.us/atlas/; Prasad et al. (2007)]. Some species exhibit differing
growth forms under different environmental conditions and were clas-
sified as having multiple growth forms (i.e. herbaceous annual/bien-
nial). Species with a biennial or annual/perennial growth habit were
grouped with annuals (as in Fitter & Fitter 2002, see Appendix S3).
Within pollination syndrome, we classified species as insect- or wind-
pollinated based on an extensive literature search and the USDA Tree
Atlas (http://www.nrs.fs.fed.us/atlas/tree/tree_atlas.html). Insect-
pollinated species were further classified as facultative or obligate out-
crossers. Obligate out-crossing species are completely self-incompatible
while facultative out-crossing species are capable of selfing.
All 141 species were classified according to growth form, flower-
ing time and origin. Thirty-eight species could not be definitively
classified with regard to pollination syndrome.
Statistical analysis
We evaluated differences in the strength of phenological response
among functional groups using a linear mixed effects model using
the package lme4 of the statistical software R which uses restricted
maximum likelihood methods to determine effect sizes (R Develop-
ment Core Team 2008; Bates et al. 2012). Because lme4 does not
return P-values, we performed a likelihood ratio test using maxi-
mum likelihood methods for each term in the model to determine
significance (Moore 2010). For each functional group, we included a
covariate in our initial model of flowering date as a function of
temperature, thereby allowing slope to vary with functional trait
(eqn 2). To account for the variation in phenological response
among species, the model included the species level intercept and
slope of
T
4i
as random effects, thus allowing both the slope and
intercept as a function of
T
4i
to vary among species.
We examined spatial heterogeneity of phenological responsiveness
among climate divisions (Appendix S1). We used a linear mixed
effects model with climate division as a covariate added to the ini-
tial model of flowering date as a function of temperature with spe-
cies as a random effect. This model allows the slope to vary
between climate divisions and produces mean phenological respon-
siveness values for each of the 10 climate divisions. We found sig-
nificant variation in responsiveness only among climate divisions 6
and 7 suggesting little spatial heterogeneity in phenological respon-
siveness (Appendix S1, Fig. 2).
We further assessed the impacts of spatial variation in our models
of functional trait heterogeneity in phenological responsiveness by
adding Division, along with species, as random effects to these ini-
tial models. This model allows the slope of
T
4i
and the intercept to
vary both among species and divisions. Our models were not signif-
icantly altered by adding Division as a random effect, suggesting
that spatial heterogeneity adds no unexplained variation to our func-
tional group analyses (Appendix S1, Figs 3 and 4). Thus, Division
was not included in the final models.
Because of their shared evolutionary history, closely related species
are likely to be more similar than those species less closely related, lead-
ing to non-independence of data and violation of the assumptions of
statistical tests in comparative analyses that do not account for this
autocorrelation (Revell et al. 2008). To test whether significant phyloge-
netic autocorrelation was present in the phenological responsiveness of
species, we first generated a phylogenetic tree of our study species using
the software Phylomatic (Stevens 2004; Webb & Donoghue 2005; see
Appendix S4). The influence of phylogenetic non-independence on
phenological responsiveness was modelled by incorporating the phylo-
genetic covariance matrix in a generalised least squares model. The phy-
logenetic covariance structure was multiplied by a phylogenetic signal
value (k), ranging from 0 (no phylogenetic autocorrelation) to 1 (maxi-
mum phylogenetic autocorrelation), and the log-likelihood of each run
was recorded; from the resulting likelihood surface a maximum likeli-
hood phylogenetic signal value of k was obtained (Pagel 1999). k mea-
sures the degree to which the variation/covariation of traits across a
tree agrees with the Brownian process (Freckleton et al. 2002). A value
of k = 0 implies that phenology is distributed among species at random
with respect to phylogeny. A value of k = 1 indicates that phenology is
phylogenetically conserved; that is, closely related groups have more
similar flowering times than would be expected by chance. Approxi-
mate confidence intervals for the maximum likelihood value of k were
calculated via likelihood ratio tests (Freckleton et al. 2002) on values
derived from the likelihood surface. We used the maximum likelihood
method ‘pgls.profile’ function in the R package ‘caper’ to estimate the
likelihood profile for k for species’ phenological responsiveness (Orme
et al. 2012, see Appendix S5).
RESULTS
Average spring temperatures (February to May) across Ohio have
increased by 0.9 °C(P ≤ 0.01) since 1895 (Fig. 1a) with some areas
experiencing warming of up to 2 °C (Fig. 1b). Seventeen of the 26
counties within Ohio with USHCN weather stations recorded a sig-
nificant warming trend in the spring. Temperature trends for the
late summer to early fall (June to September) were more variable
© 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS
Letter Earlier flowering and climate change in N. America 1039
with no significant state-wide changes over the past 115 years. Ten
counties reported a significant cooling trend since 1895 (average
1 °C) for late summer to early fall, two showed a significant
warming trend (average 0.8 °C), and 14 showed no significant
change.
Phenological responsiveness to temperature change showed a
high degree of variability among species (Fig. 2). Sixty-six species
(46%) showed a significant negative phenological response (i.e.
advancement of flowering date with increasing temperature), while
only two species (1%) showed a significant positive phenological
response (i.e. delay in flowering time with increasing temperature).
Among significantly responsive species, Carduus nutans, an intro-
duced spring flowering perennial showed the greatest advancement
of flowering (12 days °C
1
) while Monotropa uniflora, a native,
early-summer flowering perennial showed the greatest delay in flow-
ering (5 days °C
1
). On average, flowering advanced 2.4 days °C
1
across all species, or 3.7 days °C
1
among those species showing a
significant negative phenological response. With the increase in
spring temperatures state-wide over the past 115 years, flowering
may already be 1–3 weeks earlier in particularly responsive species
or in areas of locally greater warming.
Importantly, we found no significant phylogenetic signal in our data
(see Appendices S4 and S5). Thus, we can interpret the impacts of
functional groups on phenological responsiveness independently from
phylogenetic signal. We found significant differences in phenological
responsiveness to temperature among functional groups based on sea-
sonality of flowering, growth form and origin (Fig. 3).
There were strong differences in species’ phenological responsive-
ness based on flowering season. Spring flowering species were sig-
nificantly more responsive to increasing temperatures
(2.5 days °C
1
,LR
1
,
9
= 118.5, P < 0.001, Fig. 3) than either
early- or late-summer flowering species (1.4 days °C
1
,
LR
1,9
= 6.1, P = 0.014, and 0.6 day °C
1
,LR
1,9
= 10.4,
P = 0.001; Fig. 3). Given these differences we then evaluated the
remaining functional group responses separately for spring, early-
summer, and late-summer flowering species. There were few signifi-
cant differences among functional groups in the early- or late-sum-
mer, and thus we focused on between-group differences in spring-
flowering species (Appendix S6, Tables 2.1–2.3).
Growth form also played a role in a species’ phenological respon-
siveness, with herbaceous annuals and woody perennials showing a
similar, strong negative phenological response to increased tempera-
ture (herbaceous annuals: 2.2 days °C
1
,LR
1,11
= 25.0,
–3
–2
–1
0
1
2
3
4
1895 1915 1935 1955 1975 1995 2015
–4
–3
–2
–1
0
1
2
3
Spring temperature anomaly (°C)
Year
y = 0.0008x – 0.546
y = 0.0177x – 1.205
Statewide
(a)
Trumbull county
(b)
Figure 1 Spring temperature trends across the state of Ohio (a) and in Trumbull
County (b). Yearly spring (February to May) temperature anomalies were
calculated by subtracting the 115-year (1895–2009) average for these four
months from yearly averages. Simple linear regression lines were added to
determine shifts in spring temperatures over the 115-year period. Trumbull Co.
has experienced a 2.0 °C average spring temperature increase compared with the
state-wide 0.9 °C average increase.
(a)
(b)
Figure 2 Variation in phenological responsiveness to changing temperature
among 141 species of plants in Ohio. (a) For each species, the day of year of
maximum flowering (D
xi
) was regressed against the average temperature from
the average month of flowering and the 3 months prior T
4i
. The slope of each
line quantifies the phenological responsiveness for each species. (b) Rank order
of each species’ phenological responsiveness is represented by a point SE
bars. Closed points show a significant (P ≤ 0.05) phenological response to
temperature, while open points designate no significant change. The dashed line
indicates 0, or no phenological response. A negative phenological responsiveness
indicates earlier flowering with warming while a positive shift represents delayed
flowering with warming.
© 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS
1040 K. M. Calinger, S. Queenborough and P. S. Curtis Letter
P < 0.001; woody perennials: 2.4 days °C
1
,LR
1,11
= 0.2,
P = 0.68; Fig. 3). Herbaceous perennials had a weaker phenologi-
cal response of 1.5 days °C
1
compared with woody perennials
and annuals, although this difference was not significant
(LR
1,11
= 2.38, P = 0.12). In contrast to the other growth form
groups, perennial vines delayed flowering with increased tempera-
tures although this response was not significant (2.1 days °C
1
,
LR
1,11
= 4.8, P = 0.028). However, the three perennial vine species
in our dataset were all early- or late-summer flowering species, and
thus growth form was confounded with seasonality for these spe-
cies. Further, there was significant variability in phenological
responsiveness among growth forms during the spring (Fig. 4).
Herbaceous annuals showed the strongest spring flowering
response of 3.4 days °C
1
(LR
1,9
= 66.1, P < 0.001), and were
significantly more responsive than herbaceous perennials, which
displayed the weakest response of 2.4 days °C
1
(LR
1,9
= 6.9,
P=0.008). Woody perennials shifted flowering 2.9 days °C
1
and were not significantly different from annuals or herbaceous
perennials (LR
1,9
= 1.0, P = 0.325).
There were no significant differences in phenological responsive-
ness among different pollination syndromes across seasons (Fig. 3).
However, pollination syndrome significantly impacted phenological
responsiveness of spring flowering species (Fig 4). Spring flowering
wind-pollinated species had the strongest phenological responsive-
ness of 4.3 days °C
1
(LR
1,9
= 49.6, P < 0.001) compared to the
weaker responses of facultative and obligate out-crossing insect-pol-
linated species (facultative: 2.7 days °C
1
,LR
1,9
= 6.1, P = 0.014,
obligate: 2.3 days °C
1
,LR
1,9
= 9.5, P = 0.002 respectively).
Introduced species were almost twice as responsive in advancing
flowering time with temperature (2.8 days °C
1
,LR
1,7
= 26.9,
P < 0.001) compared to native species (1.5 days °C
1
,
LR
1,7
= 5.9, P=0.015, Fig. 3). The three most phenologically
responsive species in our data set, Datura stramonium
(13.5 days ° C
1
), Carduus nutans (12.5 days °C
1
) and Trifolium
pratense (7.6 days °C
1
) all were non-natives. Further, the effect of
place of origin was even more pronounced among herbaceous
annuals, with introduced species of that group advancing flowering
4.2 days °C
1
vs. 1.3 days °C
1
in native species (LR
1,7
= 6.87,
P = 0.01, Fig. 5). We found no significant difference between native
and non-native species among herbaceous or woody perennials
(Fig. 5). When comparing only spring flowering species, introduced
species were not significantly more responsiveness than native spe-
cies (introduced: 3.5 days °C
1
, native: 2.5 days °C
1
,
LR
1,7
= 2.9, P = 0.08; Fig. 4).
DISCUSSI ON
This study is the first to assess large-scale patterns of phenological
responsiveness with broad species representation. Among the 141
species studied, 46% showed significant advancement of flowering
phenology with higher temperatures. Considering the average
0.9 °C temperature increase across Ohio over the past 115 years,
this suggests that climate change is already altering our ecosystems
by causing some species to flower as much as 3 weeks earlier while
others show no change. For example, in Trumbull County, where
average spring temperatures have increased by 2 °C, Phacelia purshii
now flowers 2 weeks earlier while Cypripedium acaule advances flow-
ering by only 1 week and Cardamine diphylla shows no change.
Phenologic responsiveness (d/ºC)
–4 –2 0 2 4 6
Introduced
Native
Obligate
Facultative
Wind
Perennial vine
Woody perennial
Herbaceous perennial
Herbaceous annual
Late summer
Early summer
Spring
(120)
(21)
(32)
(65)
(41)
(3)
(82)
(38)
(21)
(54)
(36)
(13)
*
*
*
*
Figure 3 Phenological responsiveness to increasing temperature within different
plant functional groups. Mean 1 SE with the number of species per group
indicated in parentheses. Asterisks indicate a significant difference from the
reference group, which is the topmost group in a sub-panel (P = 0.05).
Phenologic responsiveness (d/ºC)
–6 –5 –4 –3 –2 –1
Introduced
Native
Obligate
Facultative
Wind
Woody perennial
Herbaceous perennial
Herbaceous annual
(13)
(44)
(25)
(75)
(7)
(9)
(27)
(18)
*
*
*
Figure 4 Phenological responsiveness to rising temperature among spring
flowering species separated by functional group. Points indicate group mean
phenological responsiveness with standard error bars; the number of species
included in a group is given in parentheses. Groups that are significantly
different from the reference group (the topmost group in a sub-panel) are
shown with asterisks (P = 0.05).
Phenologic responsiveness (d/ºC)
–6 –5 –4 –3 –2 –1 0 1
Woody introduced
Woody native
Herb. perennial introduced
Herb. perennial native
Herb. annual introduced
Herb. annual native
(23)
(9)
(58)
(7)
(37)
(4)
*
Figure 5 Differing phenological responsiveness to temperature based on origin
among differing growth forms. Group mean phenological responsiveness is
indicated by points and 1 SE bars. Species numbers per group are given in
parentheses; significant differences between groups are indicated with asterisks
(P = 0.05).
© 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS
Letter Earlier flowering and climate change in N. America 1041
Along with species-specific differences, we found distinct patterns
of phenological responsiveness among functional groups. Our
results are a significant addition to the limited number of studies
worldwide that have evaluated phenological responsiveness at the
functional group level. By expanding our understanding of how
functional traits shape group-level responsiveness in a novel region
as well as across broad spatial scales, we are now better able to pre-
dict species-specific and community scale responses to climate
change. Given the direct reproductive consequences of phenology
shifts, selection for or against phenologically responsive species with
future climate warming may result in an unbalanced loss or gain of
species sharing certain functional characteristics.
Overall, spring flowering species showed higher phenological
responsiveness to temperature than did early- and late-summer
flowering species. Earlier onset of growth and flowering for spring
species may allow increased light availability by extending the
growth and reproductive periods before canopy closure (Kudo
et al. 2008). Fitter & Fitter (2002) also found that spring flowering
species were most sensitive to temperature increase. Kudo et al.
(2008) suggested a link between earlier phenology, higher produc-
tivity, and reproductive benefits for spring flowering species as a
result of greater light availability. However, earlier flowering spring
species may not increase productivity if leaf phenology remains
stable while flower phenology advances. Advanced flowering for
spring flowering species may still improve reproductive success by
allowing more seeds to germinate and grow in more favourable
conditions before summer droughts. The lower responsiveness of
early- and late-summer flowering species to temperature may sug-
gest that these species respond more strongly to other environ-
mental factors such as precipitation. For instance, Jentsch et al.
(2008) found an average flowering advancement of 4 days in
response to 32 days of drought in ten grassland and heath species.
In contrast, in an experimental warming study, Sherry et al. (2007)
found no impacts of water availability on the flowering phenology
of twelve grassland species with the exception of Panicum virgatum.
Overall, precipitation seems to be a stronger factor driving flower-
ing phenology in tropical rather than temperate environments
(Rathcke & Lacey 1985).
We found significantly earlier flowering with temperature increase
in introduced species than in natives, particularly among herbaceous
annuals. Several introduced species showed particularly strong phe-
nological responsiveness including Carduus nutans (12.5
days °C
1
), Datura stramonium (13.5 days °C
1
), Trifolium hybridum
(6.4 days °C
1
) and Trifolium pretense (7.6 days °C
1
). Wolkovich
& Cleland (2011) suggest that if high phenological responsiveness
among introduced species allows them to adjust more rapidly to
warming climate, they may become a greater invasion risk. Pheno-
logically responsive non-natives may shift flowering to occupy pre-
viously unfilled niches (the vacant niche hypothesis) or by
advancing flowering earlier in the spring before natives flower
(priority effects, Wolkovich & Cleland 2011). However, the link
between phenological responsiveness and invasiveness remains lar-
gely untested. Willis et al. (2010) found that non-native species in a
67 km
2
region of New England advanced flowering significantly
more with temperature increase than did native species. In addition,
non-native species classified as invasive advanced flowering by
roughly 9 days more than non-native non-invasives over the past
100 years (Willis et al. 2010). Our similar findings indicate that
phenological responsiveness is linked to non-nativeness at small-
scales (as in Willis et al. 2010) but also across much larger spatial
scales. Given previous linkages between phenological responsiveness
and invasiveness of non-natives, our research may indicate that
introduced species flowering throughout the spring and late summer
could utilise flowering advancement to aid invasion. Unlike natives,
introduced species maintain high phenological responsiveness
throughout the late summer, potentially shifting their flowering
before unfavourable autumn weather begins.
We found that spring flowering wind-pollinated species were
more phenologically responsive than biotically pollinated species. In
contrast to our findings, Fitter & Fitter (2002) found greater
advancement of flowering with increased temperature among bioti-
cally pollinated species with a weaker response among wind-polli-
nated species. Strong phenological responsiveness to temperature
change among wind-pollinated species likely reflects the high benefit
of releasing pollen before trees leaf out in the spring allowing
greater pollen dispersal through the leafless canopy (Rathcke &
Lacey 1985; Whitehead 1969). Bolmgren et al. (2003) found more
synchronous flowering times among a variety of wind-pollinated
species compared to biotically pollinated species, suggesting a strong
response among wind-pollinated species to environmental condi-
tions favouring pollen dispersal (Culley et al. 2002; Bolmgren et al.
2003). Advancing flowering with higher temperatures may be less
advantageous for herbaceous wind-pollinated species than for
woody species that flower in the canopy. Herbaceous wind-polli-
nated species may use over-topping, or growing taller than other
members of the understory, as the primary means of enhancing pol-
len dispersal (Bolmgren et al. 2003).
We found that herbaceous annuals had the highest average pheno-
logical responsiveness in the spring congruent with the results of Fit-
ter & Fitter (2002) and Miller-Rushing & Primack (2008), who both
reported greater flowering shift in annuals compared with perennial
species. With their single growing season, phenologically responsive
annuals may benefit from a rapid onset of productivity and nutrient
uptake, possibly allowing increased nutrient allocation to flowers and
seeds. Earlier flowering annuals may also experience greater pollina-
tor availability by avoiding peak flowering time and thus increase
their reproductive success (Elzinga et al. 2007), although the signifi-
cant advancement of this group may also increase the risk of pollina-
tor mismatch (Kudo et al. 2008). This risk would be particularly
significant for those obligate out-crossing species. Of the 26 annual
species in this study that could be classified regarding pollination syn-
drome, 18 had selfing ability and would likely have relatively little
impact from pollinator mismatch. Along with potential benefits of
flowering advancement, highly responsive annual species may also
run a significant risk of frost damage. Extreme weather events
including unusually high and low temperatures are becoming more
frequent and thus, the risk of late season frosts may increase with cli-
mate change (Inouye 2008). Frost may be a potent selective force
negatively impacting highly responsive annuals as delicate floral struc-
tures are susceptible to frost damage (Inouye 2008).
By combining biological and temperature records, we were able to
study phenological responsiveness of many species across a broad
spatial scale in an area unrepresented by historic observational data
sets. Herbarium collections are common at universities and museums
throughout the Unites States and contain hundreds to thousands of
species collected over long periods of time. Coupled with tempera-
ture data from the USHCN, which has 1218 monitoring stations
throughout the contiguous US, these records are an untapped wealth
© 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS
1042 K. M. Calinger, S. Queenborough and P. S. Curtis Letter
of biological information. By using USHCN temperature data to nor-
malise species’ flowering responses across a large area rather than
using environmental variables specific to limited areas, our method
allows evaluation of phenological responses across much of the Uni-
tes States. Using this method, studies of phenological responsiveness
to climate change in previously unstudied areas may provide crucial
information needed for conservation efforts.
When evaluating phenological responsiveness, particularly with
herbarium specimens, we must consider potential errors associated
with the choice of the target phenophase and varying flowering
duration among species. First-flowering date is commonly chosen
as the target phenophase rather than peak flowering time because
observing plants for the duration of flowering is challenging and
labour intensive. However, assessing FFD can introduce bias
resulting from differing population sizes and sampling efforts
(Miller-Rushing et al. 2008). Our assessment of peak flowering
rather than FFD constrains theses effects on responsiveness calcu-
lations (Miller-Rushing et al. 2008). Evaluation of peak flowering
should also limit uncertainty regarding impacts of flowering dura-
tion on responsiveness calculations by sampling at a specific point
along a potentially broad distribution of flower opening. Further,
Primack et al. (2004) evaluated differences in flowering shifts
derived using herbarium specimens of species with brief (1 week
or less), medium (2 weeks) and long flowering durations (3 weeks
or more). The mean flowering shifts for each of these groups
were not significantly different, indicating that flowering duration
did not impact flowering shift calculations. Through our analysis
of peak-flowering, it is unlikely that our results are biased by flow-
ering duration, population size fluctuations, or variation in sam-
pling effort over time.
Evaluating species-specific and functional-group level variability
in phenological responsiveness is a key step to understanding how
climate change is already altering and will continue to alter ecosys-
tems. Our results suggest that future warming will differentially
impact plant functional groups. As less responsive species and
groups of species are pushed beyond their optimal temperature
ranges, performance may decline, decreasing species abundance.
Coupled with factors such as habitat loss, decreasing pollinator
diversity, introduced species and altered precipitation patterns, a
decline in phenologically non-responsive species could represent a
major impact on biodiversity.
ACKNOWLEDGEMENTS
We gratefully acknowledge the tireless support of Don and Manetta
Calinger and Mary Vargo. We also thank Amanda Wubben who
allowed this research to progress more rapidly through her assis-
tance processing data. Finally, we thank Brandon Sinn for his help
accessing herbarium records.
AUT HOR SH IP
KMC designed the methods, collected data, performed initial statis-
tical analyses and wrote the first draft of the manuscript. SQ com-
pleted phylogenetic analyses, developed linear mixed effects models
in R and wrote the statistics portion of the methods. PSC provided
guidance and support throughout methods development and statisti-
cal analyses. All authors contributed substantially to revision of the
manuscript.
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SUPPORTING INFORMATION
Additional Supporting Information may be downloaded via the online
version of this article at Wiley Online Library (www.ecologyletters.com).
Editor, Yvonne Buckley
Manuscript received 10 January 2013
First decision made 11 February 2013
Second decision made 30 March 2013
Third decision made 12 April 2013
Manuscript accepted 6 May 2013
© 2013 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS
1044 K. M. Calinger, S. Queenborough and P. S. Curtis Letter
