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Herbarium specimens reveal substantial and unexpected variation in phenological sensitivity across the eastern United States



Phenology is a key biological trait that can determine an organism's survival and provides one of the clearest indicators of the effects of recent climatic change. Long time-series observations of plant phenology collected at continental scales could clarify latitudinal and regional patterns of plant responses and illuminate drivers of that variation, but few such datasets exist. Here, we use the web tool CrowdCurio to crowdsource phenological data from over 7000 herbarium specimens representing 30 diverse flowering plant species distributed across the eastern United States. Our results, spanning 120 years and generated from over 2000 crowdsourcers, illustrate numerous aspects of continental-scale plant reproductive phenology. First, they support prior studies that found plant reproductive phenology significantly advances in response to warming, especially for early-flowering species. Second, they reveal that fruiting in populations from warmer, lower latitudes is significantly more phenologically sensitive to temperature than that for populations from colder, higher-latitude regions. Last, we found that variation in phenological sensitivities to climate within species between regions was of similar magnitude to variation between species. Overall, our results suggest that phenological responses to anthropogenic climate change will be heterogeneous within communities and across regions, with large amounts of regional variability driven by local adaptation, phenotypic plasticity and differences in species assemblages. As millions of imaged herbarium specimens become available online, they will play an increasingly critical role in revealing large-scale patterns within assemblages and across continents that ultimately can improve forecasts of the impacts of climatic change on the structure and function of ecosystems. This article is part of the theme issue ‘Biological collections for understanding biodiversity in the Anthropocene’.
Cite this article: Park DS, Breckheimer I,
Williams AC, Law E, Ellison AM, Davis CC. 2018
Herbarium specimens reveal substantial and
unexpected variation in phenological sensitivity
across the eastern United States. Phil.
Trans. R. Soc. B 374: 20170394.
Accepted: 15 October 2018
One contribution of 16 to a theme issue
‘Biological collections for understanding
biodiversity in the Anthropocene’.
Subject Areas:
ecology, evolution, taxonomy and systematics
citizen science, digitization, geographical
range, herbarium specimens, phenology,
phenological sensitivity
Authors for correspondence:
Daniel S. Park
Charles C. Davis
These authors contributed equally to this
Electronic supplementary material is available
online at
Herbarium specimens reveal substantial
and unexpected variation in phenological
sensitivity across the eastern United States
Daniel S. Park1,†, Ian Breckheimer1,†, Alex C. Williams2, Edith Law2,
Aaron M. Ellison3and Charles C. Davis1
Department of Organismic and Evolutionary Biology and Harvard University Herbaria, Harvard University,
Cambridge, MA 02138, USA
David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1
Harvard Forest, Harvard University, Petersham, MA 01366, USA
CCD, 0000-0001-8747-1101
Phenology is a key biological trait that can determine an organism’s survival
and provides one of the clearest indicators of the effects of recent climatic
change. Long time-series observations of plant phenology collected at conti-
nental scales could clarify latitudinal and regional patterns of plant
responses and illuminate drivers of that variation, but few such datasets
exist. Here, we use the web tool CrowdCurio to crowdsource phenological
data from over 7000 herbarium specimens representing 30 diverse flowering
plant species distributed across the eastern United States. Our results, span-
ning 120 years and generated from over 2000 crowdsourcers, illustrate
numerous aspects of continental-scale plant reproductive phenology. First,
they support prior studies that found plant reproductive phenology signifi-
cantly advances in response to warming, especially for early-flowering
species. Second, they reveal that fruiting in populations from warmer,
lower latitudes is significantly more phenologically sensitive to temperature
than that for populations from colder, higher-latitude regions. Last, we
found that variation in phenological sensitivities to climate within species
between regions was of similar magnitude to variation between species.
Overall, our results suggest that phenological responses to anthropogenic cli-
mate change will be heterogeneous within communities and across regions,
with large amounts of regional variability driven by local adaptation, pheno-
typic plasticity and differences in species assemblages. As millions of
imaged herbarium specimens become available online, they will play an
increasingly critical role in revealing large-scale patterns within assemblages
and across continents that ultimately can improve forecasts of the impacts of
climatic change on the structure and function of ecosystems.
This article is part of the theme issue ‘Biological collections for
understanding biodiversity in the Anthropocene’.
1. Introduction
Ecosystems on every continent have been affected by local, regional and global
changes in climate, especially increases in temperature [1]. Changes in phenol-
ogy—the timing of life-history events—are among the most conspicuous and
well-documented species responses to climatic change, especially for plants
[27]. Phenological disruption has already impacted species’ local persistence
and community diversity [810], which may have widespread consequences
for critical ecosystem processes, including carbon sequestration [11– 13],
ecosystem– atmosphere interactions [14] and trophic interactions [1528].
Despite these trends, our knowledge of plant phenological responses to cli-
matic change remains inadequate. In particular, although phenological
responses may differ among species with different functional or life-history
traits and biogeographical origins [29– 32], long-term observational datasets
&2018 The Author(s) Published by the Royal Society. All rights reserved.
on November 27, 2018 from
to assess such trends are limited in geographical, temporal
and taxonomic scope [33]. Many of these data track woody
plant species of the Northern Hemisphere (most commonly,
abundant tree species), and only for the last approximately
40 years (but see [34,35]). These biases limit our understand-
ing of variation in phenological responses across species and
biomes. Furthermore, although population-level variation in
phenology has been demonstrated for a few species [36 38],
there are very few studies that quantify both inter- and
intraspecific variation in phenological response [32,33].
Variability in species’ phenology is particularly relevant
because climatic change is not geographically uniform. For
example, high-latitude regions are warming faster than sub-
tropical and tropical ones [1,39]. Short growing seasons also
may cause high-latitude ecosystems to be especially sensitive
to temperature, leading to stronger selective pressures for
populations to initiate growth as soon as conditions become
favourable in early spring. Additionally, plants adapted to
highly variable climates may exhibit higher phenological
thresholds to temperature, as it provides a less reliable
signal [40]. Thus, the effects of climatic change on species’
phenology may differ across their ranges depending on vari-
ation in phenological sensitivity. Variability in phenological
responses to climatic change within species may also alter
patterns of gene flow, which could either promote or counter-
act adaptive evolution via the sharing of locally (mal)adapted
alleles [4144]. Recent studies have shown that plant phenol-
ogy may be more responsive in more northern-ranging
populations where there are more variable and extreme cli-
mates, especially during the early part of the growing
season [44,45]. Although these studies are suggestive, they
are restricted in spatial scale and taxonomic scope, and
broad regional patterns of phenological response to climate
may differ from patterns at smaller, local scales.
Herbarium specimens represent snapshots of phenology
(i.e. flowering and fruiting) at a specific place and time, and
have shown tremendous promise to increase the spatial, tem-
poral and taxonomic resolution of phenological data [46– 48].
They provide rich historical depth, wide geographical scope
and taxonomic diversity, all of which allow researchers to
track long-term changes of vast numbers of species and com-
munities through space and time [4,46 49]. Despite their
representation of phenological responses [48,50], herbarium
specimens have been used less frequently than other data
sources, such as field observations, to address phenological
change, in part because they have been inaccessible to
many researchers [46,51]. However, the widespread digitiz-
ation of herbarium collections [52] combined with new
approaches to collecting [46,53] and analysing [54,55] pheno-
logical data derived from herbarium specimens has the
power to transform our understanding of plant responses
to global climatic change.
Here, we applied a newly developed web-enabled crowd-
sourcing platform, CrowdCurio:Thoreau’s Field Notes (https:// [46], to examine more than 7000
specimens of 30 phylogenetically diverse flowering plant
species. The Thoreau’s Field Notes module facilitates the
rapid quantification of phenological traits via image annota-
tion and has been demonstrated to yield reliable data
regardless of the level of expertise among crowdsourcers
(i.e. expert versus non-expert scoring) [46]. We used these
crowdsourced data to infer the magnitude, direction, and
variability in reproductive phenological responses to spring
temperature across 238of latitude in the eastern United
States. We examined both native and introduced plant
species from northern coniferous forests, eastern deciduous
forests, subtropical evergreen forests, grasslands, wetlands,
alpine meadows and aquatic plant communities. Environ-
mental conditions in this region vary considerably across
species’ ranges, and populations may exhibit substantial
variation in phenological response across this latitudinal
gradient. Our overall goals with this study were: (i) to
demonstrate the power of characterizing phenology from
herbarium data using an efficient and rapid workflow that
leverages a nearly fully mobilized online flora of the eastern
United States [56,57]; (ii) to greatly increase the taxonomic
and ecological diversity of species sampled for this purpose
(from woody perennials to herbaceous annuals across a
range of biomes); and (iii) to sample species with broad lati-
tudinal ranges to assess regional and inter- and intra-species
variation in phenological responses.
2. Methods
(a) Specimen data collection
We examined phenological responses of species using digitized
specimens from two of the most comprehensive digitized regional
floras in the world, the Consortium of Northeastern Herbaria
(CNH; [56] and Southeast
Regional Network of Expertise and Collections (SERNEC; [57]. These two
online portals include more than six million digitized herbarium
records, including specimen images. Our criteria for selecting
angiosperm species for analysis were that specimens: (i) included
at least county-level location data; (ii) included at least 50 unique
collections across space and time; (iii) were of species with rela-
tively easily identifiable and quantifiable reproductive structures;
and (iv) were from species with broad latitudinal ranges sufficient
to enable quantification of population-level variation.
Applying these criteria yielded 30 species with varying life-
history traits, growth forms, native status and general reproduc-
tive seasonality (e.g. early- versus late-spring flowering). We
downloaded over 10 000 digital herbarium specimen images of
these species from CNH and SERNEC, removed duplicate, mis-
identified or sterile specimens, and those with notable insect
damage on reproductive structures, extensive physical damage
or poor preservation. We also removed all 30 specimens from
Florida, which were geographical and climatic outliers. Our
final dataset comprised 7722 specimens and spanned 120 years
across 512 United States counties (table 1). Species’ life-history
(annual versus perennial), growth form (woody versus herbac-
eous) and native status (native versus introduced) were
inferred from the United States Department of Agriculture
PLANTS Database ( For individual
specimen metadata, see electronic supplementary material,
table S1.
(b) Crowdsourcing phenological data collection
The phenological state (phenophase) of a plant can be inferred
from the presence and quantity of relevant structures, such as
leaves, flowers or fruits [46,48]. Past researchers generally have
focused on the presence or the absence of a single structure or
trait (e.g. [58]) or applied majority estimates for scoring a
single phenophase (e.g. [49]). Here, we quantified data for two
reproductive phenophases, flowering and fruiting. Specimens
were scored as flowering if open flowers represented greater
than or equal to 50% of the total reproductive structure count Phil. Trans. R. Soc. B 374: 20170394
on November 27, 2018 from
and scored as fruiting if they had less than 50% flowers and buds
and at least one fruit present. We used the Thoreau’s Field Notes
instance of CrowdCurio to crowdsource phenological data from
digitized herbarium specimens [46]. Citizen scientists hired
through Amazon’s Mechanical Turk service (MTurk; https:// counted the number of buds, flowers and
fruits observed for a set of 10 specimen images. Participants
first watched a short (1 min) instructional video on how to
score phenological traits using CrowdCurio and then were
provided with three tutorial images of each reproductive struc-
ture for every species. The 2364 anonymous participants were
compensated at a rate of $0.12 per image.
To provide an estimate of measurement error, each 10-image
set scored by a single crowdsourcer included nine unique images
and a single duplicate image randomly selected from the other
nine [55]. We estimated the reliability score for each participant
based on the data for each 10-image set by dividing the absolute
difference in organ counts for each phenophase by the total
count of that specimen across the two duplicate specimens and
subtracting this value from 1 (1 – (jcount1 – count2j/(count1 þ
count2)) [55]. Reliability scores range from zero (unreliable/
inconsistent) to one (reliable/consistent). Participants who
reported no organs on one sheet and a non-zero number of the
same organ on the duplicate sheet were assigned a reliability
score of zero for that organ (i.e. the lowest reliability score).
We conservatively selected the lowest reliability score among
the three calculated for each organ per participant and
assigned it to each participant as their final score. That is, if a
participant got a reliability score equal to zero on one organ,
they would be assigned a reliability score of zero for all
organs. Specimen observations scored by crowdsourcers with a
reliability score of zero were excluded from the analysis. We
also spot checked for suspicious outliers manually and removed
such data.
Table 1. The number of specimens and different categorical traits of examined species. FL and FR refer to the number of specimens classified as flowering and
fruiting, respectively.
family species
time span
(years) FL FR lifespan growth form status
Ranunculaceae Anemone canadensis L. 116 41 59 perennial herbaceous native
Ranunculaceae Anemone hepatica L. 95 40 60 perennial herbaceous native
Ranunculaceae Aquilegia canadensis L. 119 251 238 perennial herbaceous native
Asteraceae Bidens vulgata Greene 119 83 136 annual herbaceous native
Celastraceae Celastrus orbiculatus Thunb. 103 151 220 perennial herbaceous introduced
Asteraceae Centaurea stoebe Tausch 111 93 161 perennial herbaceous introduced
Asteraceae Cirsium arvense (L.) Scop. 118 186 171 perennial herbaceous introduced
Asteraceae Cirsium discolor (Muhl. ex Willd.)
117 46 93 perennial herbaceous native
Geraniaceae Geranium maculatum L. 119 489 513 perennial herbaceous native
Geraniaceae Geranium robertianum L. 119 48 307 perennial herbaceous native
Xanthorrhoeaceae Hemerocallis fulva (L.) L. 115 144 45 perennial herbaceous introduced
Malvaceae Hibiscus moscheutos L. 119 105 100 perennial herbaceous native
Balsaminaceae Impatiens capensis Meerb. 120 153 501 annual herbaceous native
Iridaceae Iris pseudacorus L. 117 90 66 perennial herbaceous introduced
Iridaceae Iris versicolor L. 119 344 185 perennial herbaceous native
Liliaceae Lilium canadense L. 117 139 27 perennial herbaceous native
Caprifoliaceae Lonicerabella Zab. 107 37 62 perennial woody introduced
Caprifoliaceae Lonicera canadensis Bartram
ex Marshall
120 194 201 perennial woody native
Caprifoliaceae Lonicera japonica Thunb. 116 329 115 perennial woody introduced
Rosaceae Malus pumila Mill. 118 74 40 perennial woody introduced
Malvaceae Malva neglecta Wallr. 116 25 140 perennial herbaceous introduced
Onagraceae Oenothera perennis L. 120 194 214 perennial herbaceous native
Orobanchaceae Orobanche uniflora L. 118 213 105 annual herbaceous native
Rosaceae Rosa gallica L. 108 45 17 perennial woody introduced
Rosaceae Rubus odoratus L. 120 176 318 perennial woody native
Sarraceniaceae Sarracenia purpurea L. 119 234 75 perennial herbaceous native
Iridaceae Sisyrinchium mucronatum Michx. 117 86 157 perennial herbaceous native
Solanaceae Solanum rostratum Dunal 115 21 85 annual herbaceous native
Melanthiaceae Trillium grandiflorum (Michx.) Salisb. 119 129 40 perennial herbaceous native
Melanthiaceae Trillium undulatum Willd. 120 402 156 perennial herbaceous native Phil. Trans. R. Soc. B 374: 20170394
on November 27, 2018 from
(c) Historical climate data
We used estimates of historic (1895– 2016) average monthly temp-
erature and precipitation data at 4 km resolution from PRISM
( product AN81 m;, which provide
high-resolution time-series estimates of climatic elements for the
contiguous UnitedStates. As accurate locality data are not available
for the majority of historic specimen records[59], we used county as
our geographical unit of analysis. The vast majority (79%) of speci-
mens used in this study were collected before 1980, and while 72%
of the specimens used in this study had associated coordinate data,
at least 91% of those coordinates had been georeferenced post hoc
(e.g. assigned county or township centroid coordinates), and thus
may not represent precise sampling locales. For each county and
year, we estimated the mean monthly temperature, precipitation
and elevation, and assigned these values to each specimen [59].
Although counties can vary in size and climate, counties in states
along the Atlantic coast of the United States are generally small in
size and geographically homogeneous. We estimated within-
county climatic heterogeneity as the standard deviation of
estimated monthly climatic values across each county and year
and included it in our initial analyses, but coefficients had Bayesian
credibility intervals that werenot credibly different from zero, sowe
dropped these terms from our final models.
(d) Statistical analyses
Phenological sensitivity to spring temperature—defined as the
mean of March, April and May temperatures [46]—was defined
as the slope of the linear relationship between the day of year
(DOY) of a phenophase and the spring temperature of the corre-
sponding location and year (shifts in days per degree Celsius
change: days/8C) [44,46]. These months have been used to
define spring across the east coast of the United States [46,60].
To calculate phenological sensitivity, we binned our specimen
data into both broad climatic zones [61,62] and finer-scale
National Ecological Observatory Network (NEON) domains.
Our data comprised two climatic zones (cold/very cold; mixed-
humid/hot-humid—hereafter referred to as cold and mixed-
warm) and five NEON ecoclimatic domains (NE, northeast;
MA, mid-Atlantic; AP, Appalachians & Cumberland Plateau;
OZ, Ozarks Complex; SE, southeast; electronic supplementary
material, table S2). We also estimated phenological sensitivity to
elevation as the slope of the linear relationship between the
DOY of a phenophase and metres above sea level (m a.s.l.).
We estimated the mean timing of flowering and fruiting phe-
nophases, and environmental influences on them, using Bayesian
hierarchical linear regression models [63]. In our models, species,
region, county and observer were considered random effects,
while spring temperature and county elevation were covariates.
The hierarchical nature of the model, in which the phenological
responses of individual species were assumed to be drawn
from statistical distributions instead of fixed estimates [64],
allowed us to better estimate their climatic sensitivities. These
models also more accurately quantified uncertainty in our esti-
mates and partitioned the variance in phenological timing and
phenological sensitivity within and between species and regions.
We fitted two models for each phenological phase. ‘Model 1’
estimated species-specific phenological sensitivities and parti-
tioned their variances. ‘Model 2’ provided a more powerful
comparison between phenological sensitivities found in the
warmer, lower latitudes of our study area and those in
the cooler, higher-latitude regions (figure 1).
In Model 1, the dependent variable was the DOY for which a
given phenological phase (flowering or fruiting) was recorded
for the ith specimen. DOY
was assumed to be normally
distributed, with mean
and species-specific variance
The linear predictor
was estimated as a function of covariates,
including mean spring (MarchMay) air temperatures
) and the average elevation of the county in which
the specimen was recorded (Elev
). Additional intercept terms
5) were added for each species (s), region (r), species
region combination (sr), county (c) and observer (o). The full
expression for estimating
Species-specific slope and intercept terms (
in equation (2.2)) were drawn from normal distribu-
tions, with species assemblage means
, and
1), ð2:3Þ
Region and species region slopes (
), and region,
species region, county and observer intercepts (
) in equation (2.2) were drawn from zero-centred
normal distributions with hypervariances
, respectively. The species-specific sampling variation
) terms in equation (2.1) were estimated independently to
account for differences in the duration of flowering and fruiting
phases between species.
The three different groups of slopes estimated for spring
temperature decomposed variation in phenological sensitivity
into components representing between-species variability (
between-region variability (
) and within-species variability
across regions (
). The accompanying hypervariances (
) directly represented these different sources of variability;
comparing their relative magnitudes quantified the contributions
of each source of variation to overall variation in phenological sen-
sitivity. This model structure also provided estimates of the
contributions of species turnover to differences in phenological
sensitivity between regions. We estimated these contributions
by analysing the output of Model 1, computing phenological sen-
sitivities for each observation for each iteration of our model. We
then used the mean and standard deviation of these estimates for
each region to create region-specific estimates of mean phenologi-
cal sensitivities and their variability. We assessed the contribution
of community turnover by comparing estimates that included all
three climate sensitivity terms (
) with esti-
mates that included only the terms that represent species-level
variability in climate sensitivity (
). This strategy allowed us
to infer what the mean phenological sensitivities would be
across regions in the hypothetical case that they differed only in
species composition, and species responded identically to climate
across their ranges.
Model 2 differed from Model 1 in treating the region term
) as a two-level fixed effect representing the climatic
region from which the specimen was drawn.
Model 2 maximized statistical power to compare overall phe-
nological sensitivities of species between warmer, more southerly
parts of our study area and cooler, more northerly areas. Instead
of treating region-specific slopes and intercepts as normally dis-
tributed random grouping factors, we represented species
region, county and observer terms as zero-centred and normally
distributed. This structure allowed more direct inference about
overall differences in phenological sensitivity between cool and Phil. Trans. R. Soc. B 374: 20170394
on November 27, 2018 from
mixed-warm climate regions (differences between estimates of
for the two regions). Unlike Model 1, however, Model 2
lacks species-specific parameters (
) and did not
provide species-specific estimates of phenological sensitivity or
permit comparison of variability in phenological sensitivity
within and between species.
We estimated all parameters of the two models using
Hamiltonian Monte Carlo (HMC) [65] implemented in Stan
(v. 2.17.3) [66] called from the rstan interface [67] in R [68].
HMC is a form of Markov chain Monte Carlo (MCMC) that effi-
ciently estimates hierarchical Bayesian regression models for
larger datasets like ours [69]. We used relatively uninformative
prior distributions: zero-centred normal priors for slopes and
intercepts, and truncated normal distributions for variances
and hypervariances. To account for sampling behaviour and sim-
plify prior choices, we scaled and centred the response variable
and all continuous predictors by subtracting the mean
and dividing by the standard deviation of each variable. For
each model run for each phenophase, we estimated parameters
using four MCMC chains of 4000 iterations each and discarded
the first 2000 iterations of each chain (as burn-in). We assessed
convergence of each model both visually and with the
GelmanRubin statistic (^
r,1:1 for all parameters). We also
assessed good model fit using visual posterior predictive
checks implemented in the bayesplot R package [70]. All
parameter estimates were based on at least 1000 effective pos-
terior samples. Estimates reported in the results were back-
transformed to the original data scale to facilitate illustration
and interpretation.
Code and data for reproducing these analyses are archived
by Harvard Forest [71].
3. Results
Our focal species spanned wide geographical and climatic
space (figure 1). They demonstrated diverse patterns of
phenology and significant variation in responses to climate
across species and geographies. Using Model 1, estimated
mean (non-leap-year) flower timing at 7.48C and 216 m a.s.l.
(mean collection conditions for the specimens) varied from
10 May (Day 130, Anemone hepatica) to 10 September (Day
253, Bidens vulgata) for flowering and 22 May (Day 142, A.
hepatica) to 14 September (Day 257, B. vulgata) for fruiting
(figure 2). The average lag time between flowering and fruit-
ing across all species was approximately 20 days. Most
species flowered and fruited earlier with warmer spring temp-
eratures (assemblage mean 22.56 days/8C, 95% CI 23.64 to
21.48, figure 2), and these responses were credibly different
from zero ( posterior probability .0.95) for 21 out of 30
species for flowering and 15 out of 30 species for fruiting
(electronic supplementary material, tables S3 and S4).
0 300 600
elevation a.s.l. (m)
5101520–85 –80 –75
spring temperature (ºC)
–85 –80 –75 –70
NEON domain
climate zone
Appalachians (AP)
mid-Atlantic (MA)
northeast (NE)
Ozarks Complex (OC)
southeast (SE)
Figure 1. Distribution of herbarium specimens across geographical and environmental space, colour-coded by NEON domain (a,c) or climate region (b,d). Panels (a)
and (c) show specimens in flower, and panels (b) and (d) show specimens in fruit. Specimens are referenced to county centroids, and jitter has been added to
coordinates to reduce over-plotting. Average spring (March May) air temperatures are strongly negatively correlated with latitude (Pearson correlation r¼20.92,
panel c), but elevation and latitude are largely independent (panel d). Phil. Trans. R. Soc. B 374: 20170394
on November 27, 2018 from
For both flowering and fruiting, species with earlier
reproductive phenologies were substantially more sensitive
to spring temperature than species that flowered and fruited
later in the season. This sensitivity manifested in a strong
positive correlation between mean flowering and fruiting
date and spring temperature sensitivity, with a slope of
0.018 days/8C per day for flowering and 0.023 days/8C per
day for fruiting (figure 2a,b). These slopes were different
from zero with greater than 99% posterior probability. We
also found that, all other conditions being equal, flowering
and fruiting came earlier at higher elevations (community
means 21.71 to 20.11 days earlier per 100 m greater
elevation for flowering, and 22.07 to 0.14 days earlier for
fruiting, figure 2c,d). These effects were credibly different
from zero for 7 of 30 species for flowering and 8 of 30 species
for fruiting, but elevation influenced early-flowering and
late-flowering species approximately equally.
Species in the warm and mixed-temperate climatic
regions showed greater mean sensitivities to spring tempera-
ture and also greater variability (standard deviation) in
climate sensitivity between species than in the cool-temperate
northeast and Appalachians (figure 3; electronic supplemen-
tary material, figures S1 and S2). Using Model 2, we
estimated that mean sensitivities in the mixed-warm region
(figure 1b) were 22.96 days/8C (95% CI 3.69 to 22.25) for
flowering and 23.37 days/8C (95% CI 24.12 to 22.60) for
fruiting, but were substantially closer to zero in the cool-
temperate region (22.51 days/8C, 95% CI 22.86 to 22.19
for flowering, and 22.09 days/8C, 95% CI 22.63 to 21.57
for fruiting, figure 3a). The mixed-warm climatic region also
had greater assemblage variability in phenological sensitivity
(figure 3b). All differences between cold and mixed-warm
climatic regions had a posterior probability greater than
0.95 except for mean differences in flowering, where differ-
ences had a posterior probability of 0.87. These qualitative
patterns were robust to an alternative spatial binning strategy
that used only latitude, and not climate, to differentiate more
northerly and southerly regions (electronic supplementary
material, figure S3).
Overall differences between cool, northern and warm,
southerly parts of the study area were accompanied by
large amounts of regional variation not explained by climate
or latitude (figure 4). For example, using Model 1 we esti-
mated that plants in the Ozark Complex and mid-Atlantic
NEON domains were substantially more phenologically
sensitive than those in the northeast and Appalachians
(figure 4a), while the northeast and Ozark Complex had
plant assemblages with greater variability in phenological
sensitivity (figure 4c). Differences in phenological sensitivity
between regions were not adequately explained by differ-
ences in species composition, as per-sample weighted
means computed using only species effects (
in equation
(2.2)), did not show strong regional differences (figure 4b,d).
Our hierarchical approach allowed us to compare within-
species, between-species and between-region sources of
variability for both mean flowering time and sensitivity to
spring temperature (figure 5). This analysis shows that
between-species variation dominated variability in mean
flowering time (figure 5a), but there was a similar amount
of variation in phenological sensitivity within species
between regions to that seen between species for both
flowering and fruiting (figure 5b).
phenological sensitivity
Anemone canadensis
Anemone hepatica
Aquilegia canadensis
Bidens vulgata
Celastrus orbiculatus
Centaurea stoebe
Cirsium arvense
Cirsium discolor
Geranium maculatum
Geranium robertianum
Hemerocallis fulva
Hibiscus moscheutos
Impatiens capensis
Iris pseudacorus
Iris versicolor
Lilium canadense
Lonicera bella
Lonicera canadensis
Lonicera japonica
Malus pumila
Malva neglecta
Oenothera perennis
Orobanche uniflora
Rosa gallica
Rubus odoratus
Sarracenia purpurea
Sisyrinchium mucronatum
Solanum rostratum
Trillium grandiflorum
Trillium undulatum
community means
50% CI
30 1
20 21
23 24
27 28
29 30
100 150 200 250 100 150 200 250
phase mean at 7.4°C and 216 m a.s.l. (DOY)
phenological sensitivity
(days/100 m a.s.l.)
flowering fruiting
80% CI
Figure 2. Mean flowering and fruiting time compared with estimated phenological sensitivities to spring (MarchMay) temperatures (a,b), and collection elevation
(c,d) of 30 species estimated from herbarium specimens using a Bayesian hierarchical model (Model 1). Coloured and enumerated dots indicate species-specific
estimates, and white circles at panel margins represent estimated community means for each quantity. Thick and thin bars represent 50 and 80% posterior credible
intervals, respectively. Thick black lines represent credible linear relationships between quantities on x- and y-axes (posterior slope estimate different from zero
with greater than 90% probability). Dotted lines represent non-credible relationships (posterior slope estimate not different from zero with greater than
90% probability). Phil. Trans. R. Soc. B 374: 20170394
on November 27, 2018 from
4. Discussion
Our analyses revealed that (i) plant species from the eastern
United States exhibit advanced timing of flowering and fruit-
ing in response to warmer spring temperatures, (ii) the
magnitude of these responses varies significantly between
and within species across their latitudinal ranges and (iii)
that phenological sensitivity to temperature tends to be
higher in the warmer, more stable climates of lower-latitude
(a) Differential responses to spring warming
across species
Consistent with previous field observations of community
phenology, we found that reproductive phenology of flower-
ing plants accelerated with warming spring temperatures
(e.g. [46,72,73]; but see [63]). The average number of days of
phenological advancement per degree increase in temperature
(22.56 days/8C) that we observed also fell within previous
estimates [46,74,75]. All else being equal, flowering and fruit-
ing tended to occur earlier at higher elevations. Higher
elevations tend to be relatively colder and have shorter
growing seasons, which exert pressure for species to initiate
growth as soon as conditions become favourable [44,7678].
Despite these general trends, we observed significant
variation among species in their responses to warming. In
general, early-flowering and early-fruiting species were
more sensitive to spring temperatures than late-flowering/
fruiting species (figure 2), a pattern also observed at smaller
scales [75,79]. Warming-induced leaf budburst advancement
has been suggested to be less prominent in late-flushing
species compared with early-flushing ones owing to their
greater chilling requirements [80]. Similar mechanisms may
affect flowering and fruiting, where advances in the flowering
date of late-flowering species caused by spring warming
would be smaller than those of early-flowering species,
which would manifest as weaker phenological responses to
temperature in late-flowering species. Further, as flowering
and fruiting events later in the year are more separated from
spring climatic conditions, there is an extended window of
time in which other factors could affect or modify reproduc-
tive timing. For instance, late-flowering species may be more
sensitive to photoperiod or precipitation.
A large amount of variability in phenological sensitivity
across species suggests that phenological responses to cli-
matic change will be heterogeneous within communities.
This could cause temporal reorganization of the structure
and composition of plant communities, potentially altering
direct and indirect interactions among plant species and
between plant and animal species, and ecosystem services
(b) Phenological sensitivity to spring temperature tends
to decrease with latitude
The consequences of phenological shifts can be further com-
plicated by intraspecific variation in phenological sensitivity
to environmental cues [33,38]. For instance, using 20 years
of observational data, Preve
´yet al. [44] found that the pheno-
logical sensitivity to temperature of tundra plants at colder,
higher latitudes was greater than at warmer, lower latitudes.
However, contrary to such studies, we found that plants in
warmer, lower-latitude regions tended to be more pheno-
logically sensitive to temperature, especially for fruiting
(figure 3). We hypothesize that this is due to the lower and
less predictable winter and spring climates of the north-
eastern United States. In such environments, dynamic
phenological tracking of spring temperatures (i.e. high phe-
nological sensitivity to temperature) presents high risks to
reproductive success, because warm periods may often be fol-
lowed by periods of dramatic chilling [40]. At lower latitudes,
the advent and progression of spring is less variable and
average temperatures are higher; thus phenological tracking
of temperature is less risky (electronic supplementary
material, figures S1 and S2). Indeed, species exhibited a
larger amount of variability in their responses to temperature
in the warmer, lower-latitudinal parts of their ranges.
Climate and phenology might play different roles in filter-
ing species assemblages in regions with longer growing
seasons than in regions where the growing season is short
and reproductive phenologies are strongly constrained by
shorter freeze-free periods [35]. Indeed, studies synthesizing
plot-level observational data have suggested phenological
sensitivity of plant communities to warming may be
positively correlated with mean annual temperature, but
assemblage mean
e s.d.
cool warm-mixed
climate re
phenological sensitivity
phenological sensitivity
flowering fruiting
Figure 3. Estimated community phenological sensitivities to spring (March
May) air temperature in cold-temperate versus mixed-warm temperate climate
zones (depicted in figure 1) using a Bayesian hierarchical model (Model 2).
Panel (a) depicts species assemblage means, and panel (b) depicts assemblage
standard deviations. Black and grey represent flowering and fruiting stages, and
thick and thin bars represent 50 and 80% posterior credible intervals, respect-
ively. Comparisons with a posterior probability greater than or equal to 0.8 and
less than 0.95 are depicted with a ‘B’, comparisons with probabilities greater
than or equal to 0.95 and less than 0.99 are depicted with ‘*’, and comparisons
with probabilities greater than or equal to 0.99 are depicted with ‘**’. Phil. Trans. R. Soc. B 374: 20170394
on November 27, 2018 from
negatively correlated with seasonal temperature range (i.e.
variability) in Europe [84] and China [85]. Alternatively, it
is possible that plants in warmer climates exist closer to
their response thresholds in terms of phenology, and thus
react more dramatically to small changes in temperature.
However, Ko
¨rner & Basler [86] noted that cherry cultivars
from regions with less variable spring temperatures flowered
earlier in common gardens, suggesting phenological sensi-
tivity does vary with climate. Plants in regions with high
spring temperature variability also tend to be less pheno-
logically sensitive in terms of leaf out and bud break to
temperature than those in less variable climates [40]. Our
results demonstrating that phenological sensitivity to temp-
erature is higher in areas with low standard deviation of
intra-annual temperature and inter-annual variation in
spring temperature and high mean annual temperature
support these findings.
(c) Consequences of variation in phenological responses
across species ranges
Our results imply that with equal warming, individuals in
lower-latitude populations will advance their reproductive
phenology more dramatically than those at higher latitudes.
This observed variation in phenological response may reflect
adaptation to local climatic conditions, especially in annual
species. We found a large amount of regional variation in
phenological sensitivity that was not clearly linked to climate
or latitude. These regional differences were not explained
by species turnover, but rather suggest the presence of
inter-population variation driven by local adaptation or
phenological plasticity (figure 4). Further, within-species
variation in phenological sensitivity between regions was of
similar magnitude to differences in sensitivity between species
(figure 5). Other studies examining leaf out and senescence in
trees also have shown that individuals from geographically
and climatically separated populations differ in their
phenology even when grown in common gardens [40,87,88].
Because the eastern United States is experiencing geo-
graphically variable climatic change, the heterogeneity in
phenological responses to warming that we observed within
and among species may have important consequences for
plant communities in the near future. Colder, climatically
variable high-latitude regions are experiencing dispropor-
tionate warming and climatic homogenization (i.e. reduced
standard variation of intra-annual temperature), while
warmer, climatically less variable more southerly regions are
experiencing increases in intra-annual temperature variability
(electronic supplementary material, figure S1). These climatic
changes could alter patterns of overlap in reproductive timing
among species in a community and across their individual
ranges. Changes in phenological overlap across ranges could
have direct consequences for adaptive evolution and species
resilience to current and impending climatic changes, as
assemblage meanassemblage s.d.
turnover +
local adaptation/plasticity
turnover only
NEON domain NEON domain
phenological sensitivity (days/°C) phenological sensitivity (days/°C)
Figure 4. Differences in sensitivity to spring temperatures between NEON domains are driven by regional variation due to local adaptation or plasticity, not com-
munity turnover between regions. This applies to both differences in species assemblage mean phenological sensitivities (a,b) and assemblage standard deviations
(c,d). Panels (a) and (b) represent best estimates of regional variations in phenological sensitivity incorporating species identity, NEON Domain and NEON Domain
species identity as random effects (
) and panels (c) and (d) represent estimates incorporating only species-level effects (
). This means that in
panels (c) and (d), phenological sensitivity is assumed to be constant within a species across domains. Estimates for flowering are represented in black and
estimates for fruiting are represented in grey. Thick and thin bars represent 50 and 80% posterior credible intervals, respectively, from a hierarchical Bayesian
model (Model 1). Phil. Trans. R. Soc. B 374: 20170394
on November 27, 2018 from
gene flow may increase among previously (temporally) iso-
lated populations of some species and decrease among
others [4143,8991]. Decreased phenological overlap could
genetically isolate fringe populations, potentially leading to
local extirpation and species range contractions. Moreover,
phenologically sensitive plants at lower latitudes may
especially be at risk due to increasingly variable temperatures
and increased probabilities of phenological mismatch with
mutualists [92]. However, we cannot fully rule out the
possibility that individuals of long-lived perennial species
may also be able to acclimate their phenological sensitivity
to changing climatic conditions over longer periods of time.
Some of the variation we observe in phenological sensi-
tivity to temperature across and within species may be due
to differences in microclimate. However, the lack of accurate
location data for most historic specimens limited our ability
to infer fine-scale climate, necessitating coarser, county-level
analyses. Also, we cannot ignore the possibility that the phe-
nological trends we observed are unique to the species that
we studied and/or reflect biases in herbarium collections
[93]. To minimize effects of spatial bias and uncertainty, we
studied common, well-collected species and accounted for
climatic heterogeneity present in each sampling locale in
our models. However, these taxa are not necessarily represen-
tative of species assemblages across regions, and our analyses
do not account explicitly for spatial and temporal sampling
biases; some regional differences could be due to differing
patterns of collection across space and time. Including
county-level random effects as we have done here minimizes
the impacts of these biases but does not eliminate them
altogether. It is possible that different patterns of pheno-
logical sensitivity may be observed across species ranges
depending on how climatic and/or geographical regions
are delimited, though testing an alternative threshold yielded
similar results, suggesting that the patterns we observe are
robust to spatial binning choices. Additionally, we addressed
crowdsourcing bias by including crowdsourcer random
effects and removing observations for crowdsourcers with
low reliability scores even though phenological data
collected by citizen scientists do not differ significantly in
quality from those collected by experts [46,55]. Lastly,
although spring temperature is a critical driver of flowering
phenology in temperate climates, we cannot fully exclude
the possibility that other variables correlated with latitude
or mean spring temperature may determine observed
variance in phenological sensitivity [46,73,75,94 97]. For
example, spring temperature tends to be highly correlated
with mean annual and mean monthly temperatures in east-
ern North America (electronic supplementary material,
figure S4). Photoperiod or snow melt may further influence
and alter species phenological responses [98103]. Future
research into how these environmental cues interact to trigger
phenological events is necessary and will greatly improve our
understanding of plant phenology.
5. Conclusion
Building on previous phenological research by scoring mul-
tiple phenological traits across over 8000 herbarium
specimens spanning 120 years, we have demonstrated that
phenological sensitivity can vary greatly across species’
ranges. This variance may be attributed to adaptation or
acclimation to local climates. The large amount of within-
species variation in phenological sensitivity that we observed
underlines the complex and contingent nature of phenological
sensitivities. Phenological responses of individual species to
climate are not stable phenotypic traits, but instead emerge
from a multitude of potentially reciprocal interactions between
organisms and their environment. Populations in different
regions could have differences in frequencies of genes that
control how climate affects the timing of development or
differences in microhabitat distributions between regions that
alter how populations experience local climate. The regions
themselves may have differences in unmeasured environ-
mental factors that interact with responses to temperature or
differences in species interactions that may alter phenological
signalling. The circumstances and extent to which these or
other factors explain regional variation in species responses
to climate is currently unknown. To untangle the roles of
ecological and evolutionary processes governing the hetero-
geneous phenological responses of plant species to warming,
researchers will have to take advantage of new techniques
and datasets. In addition to continued field observations and
laboratory analysis of mechanisms responsible for flowering
and fruiting, herbarium specimens can provide a comprehen-
sive, nuanced picture of phenological responses to ongoing
climatic change across many species. Our study further
demonstrates that we can now harness the treasure trove of
variance component
variance (s)variance (s)
intercept (DOY)phenolo
ical sensitivit
flowering fruiting
Figure 5. Variance components from Model 1, allowing comparisons of varia-
bility between NEON domains, between species and within species. Variance in
the intercept (a) represents variability in flowering (black) or fruiting times (grey)
at 7.48C spring temperature and 216 m elevation above sea level, median con-
ditions for the specimens. Variance in phenological sensitivity to spring air
temperature (days/8C) represents variability in the slope of the linear relationship
between spring temperature and flowering or fruiting times. Phil. Trans. R. Soc. B 374: 20170394
on November 27, 2018 from
information in herbaria across the world to examine hundreds,
if not thousands of species across myriad plant lineages, habi-
tats and regions. Such efforts will be critical to enhance our
ability to forecast future changes in plant assemblages across
space and time in an era of accelerating climate change
Ethics. The use and collection of data by citizen scientists were
approved by an ethics review committee at the University of
Waterloo (ORE no. 21647).
Data accessibility. Data and R code are available from the Harvard Forest
Data Archive (,
dataset HF309).
Authors’ contributions. C.C.D. conceived the study; D.S.P., C.C.D., A.C.W.
and E.L. designed the study; D.S.P. and A.C.W. collected data; D.S.P.,
A.M.E. and I.B. analysed the data; D.S.P. drafted the first version of
the manuscript; C.C.D. and D.S.P. made first substantial revisions
to this draft, and all authors contributed to subsequent revisions.
Competing interests. We declare we have no competing interests.
Funding. This study was funded as part of the New England Vascular
Plant Project to C.C.D. (NSF-DBI: EF1208835), NSF-DEB 1754584 to
C.C.D. and A.M.E., and an NSERC Discovery Grant to E.L.
(RGPIN-2015-04543). A.M.E.’s participation in this project was sup-
ported by Harvard Forest. D.S.P.’s contribution was supported by
the Harvard University Herbaria and NSF-DEB 1754584. I.B.’s contri-
bution was supported by the National Science Foundation’s
Postdoctoral Research Fellowship in Biology (NSF-DBI-1711936).
Acknowledgements. The authors thank X. Feng, S. Worthington, and
members of the Davis lab for their invaluable insights and comments
on the project and manuscript.
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... Such shifts in flowering time affect the reproduction and survival of plant species as well as those of other species that interact with them (4)(5)(6)(7). Along these lines, herbarium specimens represent an inval uable resource increasingly applied in studies of reproductive phenology, which have uncov ered significant inter-and intra-specific variation in how flowering and fruiting times respond to changes in climate (4,(8)(9)(10)(11). Therefore, climate change may cause heterogeneous temporal shifts among interacting members of communities and species. ...
... Therefore, climate change may cause heterogeneous temporal shifts among interacting members of communities and species. However, most of this research has been limited to animal-pollinated species with large and/or showy flowers due to their ease of phenological scoring from herbarium specimens (9). Thus, less is known about how flowering phenology, and its sensitivity to environmental forcings, may vary across the wider array of pollination syndromes. ...
... However, male and female plants can differ across many traits, especially those related to reproduction (26)(27)(28)(29), and the slightly earlier flowering of males has been observed in some wind-pollinated dioecious species (14,30,31). Given that earlier flowering individuals have generally been found to be more sensitive to early-season climatic cues within the same species, (4,7,9) we hypothesize that male flowering phe nology is more sensitive to shifts in temperature than that of females and that this sexual variation will cause flowering times to diverge among sexes with future climate change, resulting in lower pollina tion efficiency. Previous studies have suggested that even subtle differences among sexes in their responses to climate change can negatively affect plant population growth, survival, and adaptive potential by altering effective population size (32)(33)(34). ...
Anthropogenic climate change has significantly altered the flowering times (i.e., phenology) of plants worldwide, affecting their reproduction, survival, and interactions. Recent studies utilizing herbarium specimens have uncovered significant intra- and inter-specific variation in flowering phenology and its response to changes in climate but have mostly been limited to animal-pollinated species. Thus, despite their economic and ecological importance, variation in phenological responses to climate remain largely unexplored among and within wind-pollinated dioecious species and across their sexes. Using both herbarium specimens and volunteer observations of cottonwood ( Populus ) species, we examined how phenological sensitivity to climate varies across species, their ranges, sexes, and phenophases. The timing of flowering varied significantly across and within species, as did their sensitivity to spring temperature. In particular, male flowering generally happened earlier in the season and was more sensitive to warming than female flowering. Further, the onset of flowering was more sensitive to changes in temperature than leaf out. Increased temporal gaps between male and female flowering time and between the first open flower date and leaf out date were predicted for the future under two climate change scenarios. These shifts will impact the efficacy of sexual reproduction and gene flow among species. Our study demonstrates significant inter- and intra-specific variation in phenology and its responses to environmental cues, across species’ ranges, phenophases, and sex, in wind-pollinated species. These variations need to be considered to predict accurately the effects of climate change and assess their ecological and evolutionary consequences.
... Studies utilizing such data sets have revealed patterns in phenological events that are easy to measure, such as earlier dates for first flowering (Piao et al., 2019) and spring bud break and leaf out of woody plants (Panchen et al., 2014) in response to warming temperatures. However, such studies require long-term monitoring efforts and are often limited in taxonomic scope (Wolkovich et al., 2014;Park et al., 2019). Herbarium collections have become increasingly popular resources for phenological research over the past decade because they contain location-specific historical data that allow for the exploration of long-term trends predicted with climate change (Jones and Daehler, 2018). ...
... These criteria resulted in a group of 14 species that span 11 plant families and flower across the spring growing season (Table 1). After compiling our list of focal species, we obtained phenological data from digitized herbarium Although studies including elevation as a covariate in phenology models often use the mean elevation of a county (e.g., Park et al., 2019), this metric is not helpful for our study because elevations within counties split between the Blue Ridge and the Ridge and Valley can differ by >1500 m (e.g., in Sevier County, city of Sevierville ≈ 275 m, Clingman's Dome ≈ 2025 m). Additionally, the majority of specimens in this study (especially ones from the earlier half of the 19th century) lack locality information specific enough to determine a latitude and longitude needed to derive elevation data. ...
... The majority of phenological studies using digitized herbarium specimens apply one of two approaches to categorizing reproductive phenology: (1) a binary approach, where a score of 1 or 0 indicates either the presence or absence of flowers on a specimen (e.g., Bertin, 2015;Park and Schwartz, 2015) or (2) a "relative" approach, where a specimen is considered flowering if a given proportion of flowers are open (typically 50% but up to 75%; e.g., Primack et al., 2004;Davis et al., 2015;Park et al., 2019). While these approaches are sufficient for capturing general phenological trends across broad spatial scales, finer-scale scoring methods that assign a phenophase based on the relative number of buds, flowers, and fruits present on a specimen enable more precise estimates of phenological trends . ...
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Premise: Plant phenological shifts are among the clearest indicators of the effects of climate change. In North America, numerous studies in New England have demonstrated earlier spring flowering compared to historical records. However, few studies have examined phenological shifts in the southeastern United States, a highly biodiverse region of North America characterized by dramatic variation in abiotic conditions over small geographic areas. Methods: We used 1000+ digitized herbarium records along with location-specific temperature data to examine phenological shifts of 14 spring-flowering species in two adjacent ecoregions in eastern Tennessee. Key results: Spring-flowering plant communities in the Blue Ridge and Ridge & Valley ecoregions differed in their sensitivity to temperature; plants in the Ridge & Valley flower 0.73 days earlier/ºC on average compared to 1.09 days/ºC for plants in the Blue Ridge. Additionally, for the majority of species in both ecoregions, flowering is sensitive to spring temperature; i.e., in warmer years, most species flowered earlier. Despite this sensitivity, we did not find support for community-level shifts in flowering within eastern Tennessee in recent decades, likely because increases in annual temperature in the southeast are driven primarily by warming summer (rather than spring) temperatures. Conclusions: These results highlight the importance of including ecoregion as a predictor in phenological models for capturing variation in sensitivity among populations and suggest that even small shifts in temperature can have dramatic effects on phenology in response to climate in the southeastern United States. This article is protected by copyright. All rights reserved.
... Finally, when both adaptation and plasticity drive phenological variation along the climate gradient, the resulting empirical pattern should depend on the relative direction of plastic and adaptive responses. Speci cally, we should observe a greater spatial than temporal sensitivity when adaptation operates in the same direction as plasticity (i.e., "co-gradient adaptation"; Fig. 1e,f), and a lesser spatial sensitivity or one of opposite direction to the temporal response when adaptation operates in the opposite direction (i.e., "counter-gradient adaptation"; Phenological sensitivity to temperature often varies among species occurring in different regions or that initiate phenological events at different times throughout the growing season [17][18][19][20][21][22][23][24] . However, comparisons of phenological sensitivity to climate over space and time-which are necessary to evaluate the apparent contributions of plasticity and adaptation across ecological contexts ( Fig. 1)-require spatiotemporally extensive datasets and therefore remain rare. ...
... However, comparisons of phenological sensitivity to climate over space and time-which are necessary to evaluate the apparent contributions of plasticity and adaptation across ecological contexts ( Fig. 1)-require spatiotemporally extensive datasets and therefore remain rare. Herbaria provide abundant and increasingly available data to conduct these analyses at unprecedented taxonomic, temporal, and spatial scales 21,[25][26][27][28][29][30] . However, few studies have separately estimated sensitivity to spatial versus temporal climate variation using specimens (but see 28,31-34 ), and none have leveraged their unique scope to determine the ecological contexts in which plasticity or adaptation might contribute more strongly to spatial variation in phenology. ...
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Phenology varies widely over space and time because of its sensitivity to climate. However, whether phenological variation is primarily generated by rapid organismal responses (i.e., plasticity) or local adaptation remains unresolved. Here, we used 1,038,027 herbarium specimens representing 1,605 species to measure flowering time sensitivity to temperature over time (‘S time ’) and space (‘S space ’). By comparing these estimates, we inferred how adaptation and plasticity historically influenced phenology along temperature gradients and how their contributions vary among species with different phenology and native climates, and among ecoregions differing in species composition. S space and S time were highly positively correlated ( r = 0.87), of similar magnitude, and more frequently consistent with plasticity than adaptation. Apparent plasticity and adaptation generated earlier flowering in spring, limited responsiveness in summer, and delayed flowering in fall in response to temperature increases. Nonetheless, ecoregions differed in the relative contributions of adaptation and plasticity, from consistently greater importance of plasticity (e.g., Southeastern USA Plains) to their nearly equal importance throughout the season (e.g., Western Sierra Madre Piedmont). Our results support the hypothesis that plasticity is the primary driver of flowering time variation along climatic gradients, with local adaptation having a widespread but comparatively limited role.
... Herbarium specimens have been used to study the phenological responses of plants to climate change (Calinger et al., 2013;Nualart et al., 2017;Willis et al., 2017;Gallinat et al., 2018). A lot of papers have captured the fact that plants are blooming earlier as a result of climate change using herbarium specimens (e.g., Park et al., 2018;Miller et al., 2021). For example, Munson and Sher (2015) found that rare plant species in the Rocky Mountains have accelerated their blooming date by over a month since the late 1800s. ...
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Funding for rare plant conservation is limited. In addition, many aspects of the biology and ecology of rare plants are unknown. Therefore, low-cost data generation approaches to fill these gaps should be pursued. Herbarium specimens can be used as a low-cost alternative to learn about the basic biology and ecology of rare plant species. The information provided on herbarium labels has dramatically increased in recent decades to include precise locality (i.e., latitude/longitude), exact dates, habitat, associated species, and substrate. In addition, herbarium specimens are being digitized and the resulting images and data are available via clearinghouses such as GBIF and SEINet. Already, herbarium specimens of rare plants have been used to develop habitat suitability models, predict range shifts, and assess changes in flower phenology due to climate change. Herbarium specimens can also provide a wealth of information about the reproductive biology and biotic interactions of rare plants. In this paper, we will demonstrate how this information can be accessed and present a practical application for using this information to populate an important federal listing document in the USA, Species Status Assessments (SSA). We will provide examples from the literature, as well as case studies from our own research, to demonstrate how this information can be collected from herbarium specimens and how and where to incorporate this information into SSAs. More generally, data gleaned from herbarium specimens can become part of a conservationist’s tool kit to further our knowledge of past, present, and future trends for rare plants. Additional knowledge of a species’ biology and ecology allows land managers and conservationists to make more informed decisions and allows for greater protection of listed species.
... To our knowledge, our study is unique in combining data on whole flowering distributions and long-term phenological monitoring to assess the effect of temperature on flowering synchrony within plant populations. Studies investigating the role of temperature or climate change on synchrony at larger spatial scales, along latitudinal or altitudinal gradients, have found contrasting trends: a decrease (Menzel et al., 2008;Rivest et al., 2021;Wang et al., 2015;Zohner et al., 2018), an increase (Fisogni et al., 2022;Prevéy et al., 2017;Rafferty et al., 2020) or no trend (Park et al., 2019) comparable in magnitude to our global average of a 0.21 day divergence in peak dates per °C. In these latter studies, the observed variability in synchrony with climate could sometimes be attributed to spatial variability in the intensity of climate warming-for example, colder sites warming faster. ...
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Flowering phenology can vary considerably even at fine spatial scales, potentially leading to temporal reproductive isolation among habitat patches. Climate change could alter flowering synchrony, and hence temporal isolation, if plants in different microhabitats vary in their phenological response to climate change. Despite the importance of temporal isolation in determining patterns of gene flow, and hence population genetic structure and local adaptation, little is known about how changes in climate affect temporal isolation within populations. Here, we use flowering phenology and floral abundance data of 50 subalpine plant species over 44 years to test whether temporal isolation between habitat patches is affected by spring temperature. For each species and year, we analysed temporal separation in peak flowering and flowering overlap between habitat patches separated by 5–950 m. Across our study species, warmer springs were associated with more temporal differentiation in flowering peaks among habitat patches, and less flowering overlap, increasing potential for temporal isolation within populations. Synthesis . By reducing opportunities for mating among plants in nearby habitat patches, our results suggest that warmer springs may reduce opportunities for gene flow within populations, and, consequently, the capacity of plant populations to adapt to environmental changes.
... In recent studies, herbarium specimens have been used to quantify long-term changes in plant morphological traits (e.g. leaf size and plant size) (Law and Salick, 2005;Li et al., 2020), plant phenology (Miller-Rushing et al., 2006;Davis et al., 2015;Park et al., 2018;Everingham et al., 2022;Tadeo et al., 2022), and to detect the changing interactions between plants and their antagonists (Meineke et al., 2019). In general, herbarium specimens provide a wide range of biological information that can be used to study the changes of phenology in response to climate change in both temperate (Davis et al., 2015;Park et al., 2022) and tropical regions (Davis et al., 2022). ...
... Herbarium records and other specimen-based data represent the most taxonomically, geographically, and temporally extensive source of phenological information for wild and naturalized species (Davis et al. 2015, Willis et al. 2017. Moreover, herbarium specimens have been widely used to estimate phenological responses to climate in temperate regions (Davis et al. 2015, Rawal et al. 2015, Jones and Daehler 2018, Park and Mazer 2018, Park et al. 2019, Taylor 2019, Ramirez-Parada et al. 2022 and have captured patterns of phenological variation that are similar to those observed in the field (Miller-Rushing et al. 2006, Ramirez-Parada et al. 2022). ...
Forecasting the impacts of changing climate on the phenology of plant populations is essential for anticipating and managing potential ecological disruptions to biotic communities. Herbarium specimens enable assessments of plant phenology across broad spatiotemporal scales. However, specimens are collected opportunistically, and it is unclear whether their collection dates—used as proxies of phenology—are closest to the onset, peak, or termination of a phenophase, or whether sampled individuals represent early, average, or late occurrences in their populations. Despite this, no studies have assessed whether these uncertainties limit the utility of herbarium specimens for estimating the onset and termination of a phenophase. Using simulated data mimicking such uncertainties, we evaluated the accuracy with which the onset and termination of population-level phenological displays (in this case, of flowering) can be predicted from natural-history collections data (in the absence of other biases not evaluated here), and how attributes of the flowering period of a species and temporal collection biases influence model accuracy. Estimates of population-level onset and termination were highly accurate for a wide range of simulated species’ attributes, but accuracy declined among species with longer individual-level flowering duration and when there were temporal biases in sample collection, as is common among the earliest and latest-flowering species. The amount of data required to model population-level phenological displays is not impractical to obtain; model accuracy declined by less than 1 day as sample sizes rose from 300 to 1000 specimens. Our analyses of simulated data indicate that, absent pervasive biases in collection and if the climate conditions that affect phenological timing are correctly identified, then specimen data can predict the onset, termination, and duration of a population’s flowering period with similar accuracy to estimates of median flowering time that are commonplace in the literature.
Species are altering their phenology to track warming temperatures. In forests, understorey plants experience tree canopy shading resulting in light and temperature conditions, which strongly deviate from open habitats. Yet, little is known about understorey phenology responses to forest microclimates. We recorded flowering onset, peak, end and duration of 10 temperate forest understorey plant species in two mesocosm experiments to understand how phenology is affected by sub‐canopy warming and how this response is modulated by illumination, which is related to canopy change. Furthermore, we investigated whether phenological sensitivities can be explained by species' characteristics, such as thermal niche. We found a mean advance of flowering onset of 7.1 d per 1°C warming, more than previously reported in studies not accounting for microclimatic buffering. Warm‐adapted species exhibited greater advances. Temperature sensitivity did not differ between early‐ and later‐flowering species. Experimental illumination did not significantly affect species' phenological temperature sensitivities, but slightly delayed flowering phenology independent from warming. Our study suggests that integrating sub‐canopy temperature and light availability will help us better understand future understorey phenology responses. Climate warming together with intensifying canopy disturbances will continue to drive phenological shifts and potentially disrupt understorey communities, thereby affecting forest biodiversity and functioning.
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Recent evidence suggests that community science and herbarium datasets yield similar estimates of species’ phenological sensitivities to temperature. Despite this, two recent studies by Alecrim et al. (2023) and Miller et al. (2022) found contradictory results when investigating an identical ecological mechanism (phenological mismatch of wildflower flowering and of shading by deciduous trees; “phenological escape”) with separate datasets. Here, we investigated whether differences between the two studies’ results could be reconciled by testing four hypotheses related to model design, species selection, spatiotemporal data extent, and phenophase selection. Hybrid model structures brought results from the two datasets closer together but did not fully reconcile the differences between the studies. Cropping the datasets to match spatial and temporal extents appeared to reconcile most differences but only at the cost of much higher uncertainty associated with reduced sample size. Neither species selection nor phenophase selection seemed to be responsible for differences in results. Synthesis: Our analysis suggests that although species-level estimates of phenological sensitivity may be similar between crowd-sourced and herbarium datasets, inherent differences in the types and extent of data may lead to contradictory inference about complex biotic interactions. We conclude that, until community science data repositories grow to match the range of climate conditions present in herbarium collections or until herbarium collections grow to match the spatial extent and temporal frequency of community science repositories, ecological studies should ideally be evaluated using both datasets to test the possibility of biased results from either.
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Climate warming has the potential to influence plant flowering phenology which in turn can have broader ecological consequences. Herbarium collections offer a source of historical plant data that makes possible the ability to document and better understand how warming climate can influence long-term shifts in flowering phenology. We examined the influence of annual, winter, and spring temperatures on the flowering phenology of herbarium specimens for 36 species collected from 1884–2015. We then compared the response to warming between native and non-native, woody and herbaceous, dry and fleshy fruit, and spring vs summer blooming species. Across all species, plants flowered 2.26 days earlier per 1 °C increase in annual average temperatures and 2.93 days earlier per 1 °C increase in spring onset average temperatures. Winter temperatures did not significantly influence flowering phenology. The relationship of temperature and flowering phenology was not significantly different between native and non-native species. Woody species flowered earlier than herbaceous species only in response to increasing annual temperatures. There was no difference in the phenological response between species with dry fruits and those fleshy fruits for any of the temperature periods. Spring blooming species exhibited a significantly greater phenological response to warming yearly average temperatures than summer blooming species. Although herbarium specimens can reveal climate change impacts on phenology, it is also evident that the phenological responses to warming vary greatly among species due to differences in functional traits such as those considered here, as well as other factors.
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Determining the manner in which plant species shift their flowering times in response to climatic conditions is essential to understanding and forecasting the impacts of climate change on the world's flora. The limited taxonomic diversity and duration of most phenological datasets, however, have impeded a comprehensive, systematic determination of the best predictors of flowering phenology. Additionally, many studies of the relationship between climate conditions and plant phenology have included only a limited set of climate parameters that are often chosen a priori and may therefore overlook those parameters to which plants are most phenologically sensitive. This study harnesses 894,392 digital herbarium records and 1,959 in situ observations to produce the first assessment of the effects of a large number (25) of climate parameters on the flowering time of a very large number (2,468) of angiosperm taxa throughout North America. In addition, we compare the predictive capacity of phenological models constructed from the collection dates of herbarium specimens vs. repeated in situ observations of individual plants using a regression approach-elastic net regularization-that has not previously been used in phenological modeling, but exhibits several advantages over ordinary least squares and stepwise regression. When herbarium-derived data and in situ phenological observations were used to predict flowering onset, the multivariate models based on each of these data sources had similar predictive capacity (R2 = 0.27). Further, apart from mean maximum temperature (TMAX), the two best predictors of flowering time have not commonly been included in phenological models: the number of frost-free days (NFFD) and the quantity of precipitation as snow (PAS) in the seasons preceding flowering. By vetting these models across an unprecedented number of taxa, this work demonstrates a new approach to phenological modeling.
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Significance Shifts in the timing of species interactions are often cited as a consequence of climate change and, if present, are expected to have wide-reaching implications for ecological communities. Our knowledge about these shifts mostly comes from single systems, which have provided no clear picture, thus limiting our understanding of how species interactions may be responding overall. Using a new global database based on long-term data on the seasonal timing of biological events for pairwise species interactions, we find that the relative timing of interacting species has changed substantially in recent decades. The observed shifts are greater in magnitude than before recent climate change began, suggesting that there will be widespread warming-related shifts in the synchrony of species in the future.
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Premise of the Study | Herbarium specimens provide a robust record of historical plant phenology (the timing of seasonal events such as flowering or fruiting). However, the difficulty of aggregating phenological data from specimens arises from a lack of standardized scoring methods and definitions for phenological states across the collections community. Methods and Results | To address this problem, we report on a consensus reached by an iDigBio working group of curators, researchers, and data standards experts regarding an efficient scoring protocol and a data-sharing protocol for reproductive traits available from herbarium specimens of seed plants. The phenological data sets generated can be shared via Darwin Core Archives using the Extended MeasurementOrFact extension. Conclusions | Our hope is that curators and others interested in collecting phenological trait data from specimens will use the recommendations presented here in current and future scoring efforts. New tools for scoring specimens are reviewed.
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Climate change affects not just where species are found, but also when species' key life-history events occur-their phenology. Measuring such changes in timing is often hampered by a reliance on biased survey data: surveys identify that an event has taken place (for example, the flower is in bloom), but not when that event happened (for example, the flower bloomed yesterday). Here, we show that this problem can be circumvented using statistical estimators, which can provide accurate and unbiased estimates from sparsely sampled observations. We demonstrate that such methods can resolve an ongoing debate about the relative timings of the onset and cessation of flowering, and allow us to place modern observations reliably within the context of the vast wealth of historical data that reside in herbaria, museum collections, and written records. We also analyse large-scale citizen science data from the United States National Phenology Network and reveal not just earlier but also potentially more variable flowering in recent years. Evidence for greater variability through time is important because increases in variation are characteristic of systems approaching a state change.
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Nonrandom collecting practices may bias conclusions drawn from analyses of herbarium records. Recent efforts to fully digitize and mobilize regional floras online offer a timely opportunity to assess commonalities and differences in herbarium sampling biases. We determined spatial, temporal, trait, phylogenetic, and collector biases in c . 5 million herbarium records, representing three of the most complete digitized floras of the world: Australia ( AU ), South Africa ( SA ), and New England, USA ( NE ). We identified numerous shared and unique biases among these regions. Shared biases included specimens collected close to roads and herbaria; specimens collected more frequently during biological spring and summer; specimens of threatened species collected less frequently; and specimens of close relatives collected in similar numbers. Regional differences included overrepresentation of graminoids in SA and AU and of annuals in AU ; and peak collection during the 1910s in NE , 1980s in SA , and 1990s in AU . Finally, in all regions, a disproportionately large percentage of specimens were collected by very few individuals. We hypothesize that these mega‐collectors, with their associated preferences and idiosyncrasies, shaped patterns of collection bias via ‘founder effects’. Studies using herbarium collections should account for sampling biases, and future collecting efforts should avoid compounding these biases to the extent possible.
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Spatial community reassembly driven by changes in species abundances or habitat occupancy is a well-documented response to anthropogenic global change, but communities can also reassemble temporally if the environment drives differential shifts in the timing of life events across community members. Much like spatial community reassembly, temporal reassembly could be particularly important when critical species interactions are temporally concentrated (e.g., plant-pollinator dynamics during flowering). Previous studies have documented species-specific shifts in phenology driven by climate change, implying that temporal reassembly, a process we term “phenological reassembly,” is likely. However, few studies have documented changes in the temporal co-occurrence of community members driven by environmental change, likely because few datasets of entire communities exist. We addressed this gap by quantifying the relationship between flowering phenology and climate for 48 co-occurring subalpine wildflower species at Mount Rainier (Washington, USA) in a large network of plots distributed across Mt. Rainier's steep environmental gradients; large spatio-temporal variability in climate over the 6 yr of our study (including the earliest and latest snowmelt year on record) provided robust estimates of climate-phenology relationships for individual species. We used these relationships to examine changes to community co-flowering composition driven by ‘climate change analog’ conditions experienced at our sites in 2015. We found that both the timing and duration of flowering of focal species was strongly sensitive to multiple climatic factors (snowmelt, temperature, and soil moisture). Some consistent responses emerged, including earlier snowmelt and warmer growing seasons driving flowering phenology earlier for all focal species. However, variation among species in their phenological sensitivities to these climate drivers was large enough that phenological reassembly occurred in the climate change analog conditions of 2015. An unexpected driver of phenological reassembly was fine-scale variation in the direction and magnitude of climatic change, causing phenological reassembly to be most apparent early and late in the season and in topographic locations where snow duration was shortest (i.e., at low elevations and on ridges in the landscape). Because phenological reassembly may have implications for many types of ecological interactions, failing to monitor community-level repercussions of species-specific phenological shifts could underestimate climate change impacts.
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The length of the vegetation period (LVP), which is the time between leaf-out and leaf senescence, affects numerous ecosystem functions, including biogeochemical cycles and interspecific interactions. The evolutionary mechanisms determining LVP, however, are poorly understood, and thus, it is unknown whether innate LVPs differ between eastern North American (ENA), European and East Asian species. Here we monitored LVP in 2014–2015 in 396 Northern Hemisphere woody species grown in a common garden. We found that ENA species, under the same conditions, have three weeks (11%) shorter vegetation periods than their European and East Asian relatives, because their leaves flushed 9 ± 4 and 13 ± 4 days later and senesced 9 ± 4 and 11 ± 4 days earlier. LVPs of species introduced from Eurasia into ENA are therefore longer than those of native species, suggesting that the spread of non-natives might alter seasonal forest productivity in ENA. LVP between naturalized invasive and non-invasive species, however, did not differ, rejecting the common assumption that longer leaf presentation generally fosters invasive success. A likely explanation for the shorter LVP of ENA species is that region’s uniquely high inter-annual temperature variation. These results highlight the footprint of regional climate history, which will affect forest response to climate change.
Consistency is a practical metric that evaluates an instrument's reliability based on its ability to yield the same output when repeatedly given a particular input. Despite its broad usage, little is understood about the feasibility of using consistency as a measure of worker reliability in crowdwork. In this paper, we explore the viability of measuring a worker's reliability by their ability to conform to themselves. We introduce and describe Deja Vu, a mechanism for dynamically generating task queues with consistency probes to measure the consistency of workers who repeat the same task twice. We present a study that utilizes Deja Vu to examine how generic characteristics of the duplicate task - such as placement, difficulty, and transformation - affect a worker’s task consistency in the context of two unique object detection tasks. Our findings provide insight into the design and use of consistency-based reliability metrics.
The Inula complex (Asteraceae: Inulinae) is a monophyletic group which comprises eight genera distributed in Eurasia and Africa: Amblyocarpum, Carpesium, Chrysophthalmum, Inula, Pentanema, Rhanteriopsis, Telekia , and Varthemia. With the aim to shed light on the circumscription of these genera, phylogenetic analyses were performed with 293 new DNA sequences (ITS region from nrDNA and three plastid spacers from cpDNA: rps16–trnQ, rpl32–trnL, ndhF–rpl32). It is concluded that both Inula and Pentanema are paraphyletic and that generic delimitations within the Inula complex need to be revised. Based on the results of the analyses, together with morphological and karyological data, we argue that the best solution is a new circumscription of the genus Pentanema including an amended description and 24 new combinations of former Inula species. Resurrection of the names Codonocephalum, Monactinocephalus and Vicoa is proposed to preserve the monophyly of the genera included in the Inula complex. Incongruences between nrDNA and cpDNA are documented and discussed.
Climate‐driven changes in the relative phenologies of interacting species may potentially alter the outcome of species interactions. Phenotypic plasticity is expected to be important for short‐term response to new climate conditions, and differences between species in plasticity are likely to influence their temporal overlap and interaction patterns. As reaction norms of interacting species may be locally adapted, any such climate‐induced change in interaction patterns may vary among localities. However, consequences of spatial variation in plastic responses for species interactions are understudied. We experimentally explored how temperature affected synchrony between spring emergence of a butterfly, A nthocharis cardamines , and onset of flowering of five of its host plant species across a latitudinal gradient. We also studied potential effects on synchrony if climate‐driven northward expansions would be faster in the butterflies than in host plants. Lastly, to assess how changes in synchrony influence host use we carried out an experiment to examine the importance of the developmental stage of plant reproductive structures for butterfly oviposition preference. In southern locations, the butterflies were well‐synchronized with the majority of their local host plant species across temperatures, suggesting that thermal plasticity in butterfly development matches oviposition to host plant development and that thermal reaction norms of insects and plants result in similar advancement of spring phenology in response to warming. In the most northern region, however, relative phenology between the butterfly and two of its host plant species changed with increased temperature. We also show that the developmental stage of plants was important for egg‐laying, and conclude that temperature‐induced changes in synchrony in the northernmost region are likely to lead to shifts in host use in A . cardamines if spring temperatures become warmer. Northern expansion of butterfly populations might possibly have a positive effect on keeping up with host plant phenology with more northern host plant populations. Considering that the majority of insect herbivores exploit multiple plant species differing in their phenological response to spring temperatures, temperature‐induced changes in synchrony might lead to shifts in host use and changes in species interactions in many temperate communities.