Journal of
Plant Ecology
Volume 7, Number 3,
Pages 211–221
June 2014
doi:10.1093/jpe/rtt036
Advance Access publication
7 August 2013
available online at
www.jpe.oxfordjournals.org
Geographic variation in growth
and phenology of two dominant
central US grasses: consequences
for climate change
Amanda L. Giuliani1, Eugene F. Kelly2,3 and Alan K. Knapp1,3,*
1
Department of Biology, Colorado State University, Fort Collins, CO 80523, USA
Department of Soils and Crops Science, Colorado State University, Fort Collins, CO 80523, USA
3
Graduate Degree Program in Ecology and Department of Biology, Colorado State University, Fort Collins, CO 80523, USA
*Correspondence address. Department of Biology, Colorado State University, Fort Collins, CO 80523, USA.
Tel: +970-491-7010; Fax: +970-491-0649; E-mail: [email protected]
2
Abstract
Aims
The rate of climate change may exceed many plant species’ migration rates, particularly for long-lived perennial species that dominate most ecosystems. If bioclimatic envelopes shift more rapidly
than dominant species can migrate, individuals located peripheral
to biomes or in adjacent biomes may become a significant source of
traits for future dominant populations (DPs). Thus, traits of individuals from peripheral populations (PPs) may affect future ecosystem
functioning more than those of today’s DPs.
Methods
We assessed key traits of individuals collected from populations that
currently dominate two central US grasslands, the shortgrass steppe
(Bouteloua gracilis) and the tallgrass prairie (Andropogon gerardii).
We compared these to individuals from PPs in a reciprocal-transplant common garden experiment with gardens at the Shortgrass
Steppe Long Term Ecological Research site in Colorado and the
Konza Prairie Biological Station Long Term Ecological Research site
in Kansas. DPs and PPs were subjected to high and reduced water
availability in common gardens located in each biome. Traits measured included the following: individual plant biomass, reproductive
allocation, specific leaf area (SLA) and plant–water relations. We
focused on the climate-change relevant comparisons of traits from
PPs versus DPs expressed under the climate of DPs.
Important Findings
PPs of B. gracilis differed from DPs primarily in phenological traits.
Under a semiarid shortgrass steppe climate, PPs initiated flowering
later in the season, produced fewer reproductive tillers and were
more sensitive to water stress. Biomass differences between populations were minimal. For A. gerardii, biomass in PPs was 50% lower
than in DPs under the mesic tallgrass prairie climate and reproductive tillers were considerably smaller, despite higher SLA in PPs.
Biomass of PPs was less sensitive to water stress, however. From
these results, we conclude that key traits of PPs differed from DPs in
both grassland types, but potential effects on reproductive phenology were greater for the bioclimatic shift in which a mesic biome
becomes arid, whereas aboveground productivity may be affected
more when a semiarid biome becomes more mesic.
Keywords: grassland, phenology, productivity, traits, water stress
Received: 16 January 2013, Revised: 10 May 2013, Accepted: 27
June 2013
Introduction
Biomes are defined by a range of climatic parameters (principally temperature and precipitation) and characterized by a
relatively few dominant (or foundation) plant species (Ellison
et al. 2005; Grime 1998; Whittaker 1965). Such dominant species, though widely distributed, can be relatively rare taxonomically. In grasslands, e.g. only ca. 5% of the approximate
11 000 species in the Poaceae are capable of functioning as
dominant species (Edwards et al. 2010). Nonetheless, dominant species contribute most to the total plant biomass in an
ecosystem and their traits are closely linked to ecosystem function (Aarssen 1997; Grime 1998; Huston 1997). Thus, dominant species will determine many community and ecosystem
responses to environmental change (Smith and Knapp 2003).
Although dominant species are expected to be abundant
throughout their biomes, their physiographic ranges almost
always extend far beyond where they function ecologically
© The Author 2013. Published by Oxford University Press on behalf of the Institute of Botany, Chinese Academy of Sciences and the Botanical Society of China.
All rights reserved. For permissions, please email: [email protected]
212
as dominant species. For example, Andropogon gerardii (big
bluestem) is a dominant grass throughout much of the
tallgrass prairie in the central USA, but this species can be
found 800 km west of this grassland type and throughout
much of the eastern two-thirds of the USA (http://plants.
usda.gov). Thus, it may be useful to distinguish between
populations found in areas where they function as the
dominant species (dominant populations [DPs]) from those
populations where they are simply components of the flora
(peripheral populations [PPs]). Not surprisingly, PPs are less
often studied than DPs because they are minor components
of the community or are only locally abundant.
Latitudinal and altitudinal range shifts have been documented for numerous species as a result of climate change
(Parmesan and Yohe 2003; Root et al. 2003; Walther et al.
2002), with these predicted to be more prevalent in the
future (Morin et al. 2008). Although dynamic global vegetation models have been limited in their ability to accurately
assess plant migration and local vegetation change (Neilson
et al. 2005; Thuiller et al. 2008), most studies suggest that plant
migration rates faster than those observed during post-glacial
times will be required to keep pace with the projected rate
of global climate change (Malcolm et al. 2002; Solomon and
Kirilenko 1997), particularly in biomes with little topographic
relief (Jump et al. 2009; Loarie et al. 2009). If present-day populations of dominant species cannot keep pace with shifting
climatic envelopes, those populations that dominate future
(geographically shifted) biomes are more likely to reflect traits
of individuals from PPs already present rather than those from
the DPs left behind—in other words, traits from PP individuals may be more important than those of DPs for predicting
ecosystem function as biomes expand into new areas.
For example, with forecasts of continued warming and
altered precipitation amounts and regimes in the Great Plains
(Giorgi and Diffenbaugh 2008; IPCC 2007), the climatic
envelope that defines the current distribution of the shortgrass steppe ecosystem (dominated by Bouteloua gracilis, blue
grama) may extend eastward leaving behind migration-limited DP individuals. Thus, those PP individuals that already
occur farther east would serve as the founder population for
future shortgrass steppe ecosystems dominated by B. gracilis.
If individuals from DPs and PPs are functionally similar, then
there may be little alteration in ecosystem function as biome
distributions shift. But if they are functionally distinct, then
the new DPs (derived from former PP individuals) may drive
important changes in ecosystem function and behavior, at
least until local adaptation occurs (Jump and Penuelas 2005).
In this study, we compared traits from geographically distinct DP and PP individuals for two dominant C4 Great Plains
grasses, B. gracilis and A. gerardii (big bluestem). We used a
reciprocal-transplant common garden approach to address
this issue (Clausen et al. 1941; Turesson 1922) and focused
on a few key morphological and whole plant traits. We collected individuals from populations of B. gracilis and A. gerardii that currently dominate their respective grassland types or
Journal of Plant Ecology
are found in peripheral ecosystems, set up common gardens
for both species and subjected all populations to two levels
of water availability at each garden. This design allowed us
to assess differences between individuals collected from DPs
and PPs and their responses to water stress under common
environmental conditions. Although reciprocal-transplant
experiments represent a well-established approach for assessing adaptation and responses to local environmental conditions (e.g. Bradshaw 1984; Linhart and Grant 1996), in this
case, our focus was on climate-change relevant comparisons
of traits of individuals from present-day PPs versus those from
DPs, when grown together in an environment appropriate for
that species to dominate. Moreover, although drying in general is forecast for much of this region of the world, some
areas are predicted to become wetter (Chou et al. 2009). Thus,
this reciprocal design allowed us to focus on scenarios of both
mesic PPs influencing future xeric grasslands and xeric PPs
impacting future mesic grasslands.
We hypothesized that individuals from DPs and PPs of both
species would have traits that differed and that responses to
water stress would also differ. We also expected that populations originating from more water-stressed environments
(DPs of B. gracilis and PPs of A. gerardii) would be impacted
relatively less by water stress compared to populations from
more mesic environments.
Materials and Methods
We assessed key traits in individuals from PPs and DPs of B. gracilis and A. gerardii in a reciprocal transplant common garden
experiment with two levels of water treatments, as appropriate for a largely water-limited grassland region (Huxman
et al. 2004). Our focus was on the difference between PPs
and DPs when grown in environments where the species
currently dominates. We were particularly interested in the
following two scenarios: (i) a mesic grassland (tallgrass prairie in Kansas) drying to the extent that it becomes semiarid
and thus B. gracilis might be expected to dominate (with traits
from PPs currently in Kansas). And (ii) a semiarid grassland
(shortgrass steppe in Colorado) becoming more mesic and
thus A. gerardii (with traits from PPs currently in Colorado)
would be expected to dominate. Although the former is more
likely to occur than the latter in this particular region, there
are areas of the world that are forecast to become wetter with
climate change (Chou et al. 2009; IPCC 2007), providing relevance for the latter scenario.
Population and garden site descriptions
Individuals from DPs and PPs of A. gerardii and B. gracilis were
collected from an array of undisturbed sites in Colorado and
Kansas, USA (Table 1). A total of 12 populations were sampled,
six for each species (three DP and three PP). Populations were
collected from a range of sites to capture natural variability
within the populations. For B. gracilis, DPs were collected
from different sites that varied in grazing intensity at the
Giuliani et al. | Geographic variation and climate change213
Table 1: general description of the collection sites for the DPs and
PPs of the semiarid grassland dominant B. gracilis and the tallgrass
prairie dominant A. gerardii
DPs
PPs
B. gracilis
From Colorado
From Kansas
Latitude
40°48′43′′–40°48′44′′N
39°04′28′′–39°04′40′′N
Longitude
105°12′55”–104°38′51′′W
96°34′57′′–96°33′37′′W
2009 growing
season
precipitation
254 mm
528 mm
Mean growing
season
temperature
18.6°C
23.0°C
2009 growing
season
temperature
17.2°C
21.2°C
A. gerardii
From Kansas
From Colorado
Latitude
39°04′25′′–39°04′54′′N
39°58′24′′–40°31′59′′N
Longitude
96°33′51′′–96°33′41′′W
105°12′55′′–105°8′12′′W
2009 growing
season
precipitation
528 mm
218.3 mma
Mean growing
season
temperature
23.0°C
18.5°C
2009 growing
season
temperature
21.2°C
18.9°C
Mean growing season precipitation and temperature are 30-year
averages (1971–2000) for the months of May through September.
2009 data are shown as context for the common garden results.
a
Averaged between Fort Collins, Colorado and Boulder, Colorado
(where populations were collected).
Shortgrass Steppe Long Term Ecological Research site in Weld
County, Colorado (SGS, see description below). The PPs for
this species came from the Konza Prairie Biological Station
Long Term Ecological Research site in Geary County, Kansas
(KNZ, description below); to increase variability in traits, each
population was collected from a different KNZ watershed
that varied in grazing regime and long-term fire history. For
A. gerardii, the DPs were located at KNZ (also in different
watersheds with different grazing and burning histories), and
the PPs of this species were located along the Front Range of
Colorado, two from Boulder County and one from Larimer
County. These populations were found within 70 km of
each other.
Transplants along with some residual soil to include mycorrhizae and other important soil biota were moved to two
common gardens at the start of the 2008 growing season.
The SGS common garden, located at the Central Plains
Experimental Range, was in a semiarid grassland located in
northeastern Colorado (40°49′N, 104°46′W). SGS is primarily dominated by the C4 grass B. gracilis, with other major
species including Buchloe dactyloides (buffalo grass), Artemisia
frigida (fringed sagewort), Sphaeralcea coccinea (scarlet
globemallow) and Opuntia polycantha (plains prickly pear;
Lauenroth and Burke 2008). SGS has a mean annual precipitation of 321 mm (Lauenroth and Sala 1992) and a mean
annual temperature of 8.6°C (Milchunas and Lauenroth
1995). Average aboveground net primary productivity
(ANPP) is estimated at ca. 100 g m−2 (Lauenroth and Sala
1992), with B. gracilis comprising up to 90% of the total biomass (Lauenroth et al. 1978). The garden was established
near the site headquarters on a soil with clay loam texture
(top 20 cm), which is typical of SGS (Lauenroth and Burke
2008).
The KNZ common garden was established at the headquarters area of the site, which is a native tallgrass prairie located
in the Flint Hills of northeastern Kansas (39°05′N, 96°35′W).
KNZ encompasses 3487 hectares of native tallgrass prairie and
is dominated by C4 grasses, primarily A. gerardii Vitman and
Sorghastrum nutans (L.) Nash (Freeman 1998). Average ANPP
at KNZ is ca. 420 g m−2 (Knapp et al. 1998), with A. gerardii
comprising up to 80% of the total (Smith and Knapp 2003).
The climate consists of cold, dry winters and warm, wet summers (Hayden 1998). Mean annual precipitation is 835 mm,
and mean annual temperature is 13°C. The garden was established on soil with a silt loam texture (top 20 cm), which is
typical of KNZ (Knapp et al. 1998).
Population collection and common garden
establishment
From each population, 30 individuals were collected, 15 for
each garden. In these highly clonal species, we defined an
individual as all tillers located within a 20-30-cm diameter
circle within a monospecific stand of the target species. We
collected all roots and rhizomes to 15–20-cm soil depth and
all aboveground tissue. Despite the strongly clonal habit of
these species, it is possible that more than one genotype
was included in each individual sample (Avolio et al. 2011).
Samples were stored in a cool, moist environment until they
were transplanted (within 2 weeks of collection). Transplant
survival success was >95%.
To establish the common gardens, a 10 × 10-m area was
tilled to 25 cm and the perimeter was fenced to exclude
grazers. Plastic lawn edging was formed into 39-cm diameter
circles and inserted 10 cm into the ground to isolate and
contain the individuals. We transplanted 144 individuals into
these circular plots in each garden; 12 individuals of B. gracilis
and A. gerardii from each of the 12 populations. Transplants
were arrayed in a 6 × 6 Latin square design repeated once for
each species—this allowed us to subject half the transplants
to a water availability treatment in the second year. Intact
rhizomes and tillers were separated from other vegetation
initially to establish monospecific stands in each plot, and
we removed other species throughout both growing seasons
via weeding by hand. Three extra individuals from each
population were placed around the perimeter of the gardens
to provide replacements in the case of transplant mortality.
The 2008 growing season was dedicated to the establishment,
214
growth and acclimation of the populations, thus all plants
were watered frequently to facilitate survival and growth.
In order to create a wet versus dry treatment at each site,
we excluded precipitation to half of the KNZ garden and
irrigated half of the SGS garden in 2009. Four soil moisture
probes were placed in each half of each garden to monitor
treatments. At SGS, ambient conditions constituted the dry
side of the garden. We irrigated the other half of the garden
to reduce water stress; each individual received water twice
daily via drip irrigation. The amount of water added varied
depending on rainfall and the water status of the plants.
Conversely at KNZ, ambient conditions constituted the wet
side of the garden, and a rain exclusion shelter was erected
over half the garden to reduce soil moisture. The shelter consisted of clear polyethylene greenhouse material stretched
across a wooden frame ~2 m above the plants (similar to the
design described in Fay et al. 2000). The roof deflected most
rainfall off the plot and could be removed if the plots became
too dry. However, due to the winter recharge of moisture in
the deep soils at this site, the roof remained intact over half
the garden for most of the growing season. The shelter was
designed with open sides so that alterations to air movement,
temperature and relative humidity were minimized. The roof
was slanted to facilitate water run off and the plastic sheeting
reduced the transmission of light by 19%.
In general, differences in soil moisture between wet versus dry treatments increased over the growing season and
were greater at SGS than the KNZ garden, likely because
the deep soils at KNZ were nearly saturated prior to erecting the rain exclusion shelter. Average growing season soil
moisture was 28.2 ± 0.5% in the wet versus 17.6 ± 0.9%
in the dry treatment at SGS (P < 0.05) and 29.0 ± 0.4% in
the wet versus 24.7 ± 0.7% in the dry treatment at KNZ
(P < 0.05). The seasonal maximum treatment differences
observed at each garden were 23.2% at SGS and 9.3% at
KNZ. Leaf water potential (LWP) measurements (predawn
and mid-day) confirmed that these two grasses experienced different levels of water availability in both gardens
(Table 2) with the more shallow rooted B. gracilis generally
responding more strongly to the water treatments than the
deeper rooted A. gerardii.
Data collection
For all sites (the two gardens and the collection sites for the 12
populations), soil texture and pH were determined from composite samples of three 10-cm deep soil cores (Colorado State
University Soil, Water and Plant Testing Laboratory). In both
gardens in 2009, soil moisture (volumetric water content in
the top 20 cm) was estimated at approximately weekly intervals with ECH2O soil moisture sensors (Decagon, Pullman,
WA, USA). Eight probes were placed in eight plots (four each
in the dry and wet portions) arrayed in two transects through
each garden (northeast to southwest and northwest to southeast). Soils in each garden ranged in pH value from 6.2–6.9
and most of the population collection sites fell within this
range, with soil texture varying from loam to sandy loam.
Journal of Plant Ecology
Table 2: seasonal minimal LWP when differences between
watering treatments were generally the largest for the growing
season
SGS garden
B. gracilis
KNZ garden
A. gerardii
B. gracilis
A. gerardii
Predawn wet (MPa) −0.87 ± 0.20 −0.24 ± 0.06 −1.03 ± 0.16 −0.17 ± 0.08
NS
Dry (MPa)
0.034, 6.03
0.007, 14.27 0.032, 6.79
−0.71 ± 0.20 −0.43 ± 0.06 −1.94 ± 0.18 −0.47 ± 0.08
Mid-day wet (MPa) −2.40 ± 0.23 −1.42 ± 0.15 −2.31 ± 0.30 −1.45 ± 0.11
0.042, 5.85
Dry (MPa)
0.028, 6.12
0.007, 11.35 NS
−2.99 ± 0.24 −1.95 ± 0.15 −3.78 ± 0.31 −1.68 ± 0.11
Abbreviation: NS = not significant.
Water potentials were averaged across populations to determine if
watering treatments were effective (n = 30). Where results were significant, the P value and F-statistic are provided (P value, F-statistic).
Statistical significance between watering treatments at P = 0.05 level.
There were no consistent patterns noted among the 12 collection sites or the two gardens in other soil characteristics.
LWP was measured for each species at 3-week intervals
throughout the growing season (PMS 1000 pressure chamber). For both predawn and mid-day estimates, single leaves
were measured (n = 3 from each population for each treatment) from both wet and dry portions of the garden.
At the end of the season, biomass was measured by harvesting all individuals in 10 × 10-cm quadrats, drying the biomass
at 60°C for at least 3 days and weighing to the nearest 0.01 g.
To determine reproductive allocation, reproductive biomass
was separated and divided by total biomass to calculate the
proportional allocation. Additionally for A. gerardii, 10 individual tillers (both reproductive and vegetative) were randomly
selected in each plot, harvested, dried and weighed.
The total number of flowering tillers in each plot was censused every 2–3 weeks throughout the growing season for both
species to assess flowering phenology. Additionally, six stages
of reproductive phenology were monitored in each plot every
2–3 weeks for A. gerardii (emergent reproductive tiller, covered
flower, flower 3 cm exposed, fully exposed flower, anthesis,
post-anthesis). Each stage was scored 1–6, respectively, and
an average phenological stage was computed for both DPs and
PPs under wet and dry treatments. Such fine-scale phonological measurements were not possible in B. gracilis due to the
rapid production of flowering stalks in this species.
Specific leaf area (SLA), the ratio of leaf area to dry weight,
was measured on fully expanded green leaves for each
population (n = 3) at 3-week intervals during the growing
season. This trait was chosen because SLA is often positively
correlated with plant growth (Garnier et al. 2001a, 2001b;
Shipley 2002) and may be indicative of the trade-off between
rapid biomass production (high SLA) and efficient conservation
of nutrients (low SLA; Poorter and de Jong 1999).
Statistical analysis
A two-way mixed model analysis of variance (ANOVA;
SAS 9.2, SAS Institute 2005) was performed for biomass,
Giuliani et al. | Geographic variation and climate change215
reproductive allocation, individual reproductive tiller mass
and individual vegetative tiller mass for each species at each
garden. We used a two-way mixed model repeated measures ANOVA to assess responses for phenology, predawn
and mid-day LWP and SLA. Fixed effects were water treatment (wet/dry) and population (DP/PP). Random effects
were row (water), column (water), pop (individual population) and water*pop. A Latin Square analysis was initially performed for each response variable to assess row,
column or individual population effects. None of these
effects were significant; thus, the six individual populations
were combined into two geographic locations (DP and PP).
When necessary, log (y + c) transformations were used to
satisfy homogeneity assumptions for the ANOVA model
(B. gracilis: biomass, reproductive allocation of biomass,
predawn, phenology; A. gerardii: biomass, individual tiller
mass, predawn). The constant ‘c’ varied depending on the
variable and was chosen (reflecting the lower values in the
data) so that zeroes did not dominate the analyses. Based
on the Akaike Information Criterion goodness of fit test,
an autoregressive parameter was included for several analyses at both gardens (B. gracilis: phenology, SLA [SGS only];
A. gerardii: phenology, SLA).
Results
Bouteloua gracilis
Our focus for comparing traits from PPs and DPs for B. gracilis was in the SGS garden because this represents the
climate where this species is dominant. Thus, individuals from PPs from a higher resource environment (greater
precipitation) were compared to DP individuals from a low
resource environment. In the SGS garden, we detected no
difference between these two populations in total end-ofseason biomass (Fig. 1, top), but PPs (from KNZ) allocated
less biomass to reproduction than DPs (Fig. 1, bottom) and
were significantly shorter at the end of the season (DP
average maximum height = 39.8 ± 1.9 cm vs. 16.6 ± 2.1 cm
for PP). PPs also initiated flowering later and had lower
reproductive tiller density throughout the growing season
16
Biomass (g/0.01 m2)
14
12
10
* water
DP, wet trt
DP, dry trt
PP, wet trt
PP, dry trt
x KNZ = 6.59 + 1.13 g/0.01m
* water
* pop
z
x SGS = 5.63 + 0.60 g/0.01m
2
2
a
a
x
8
x
6
b
4
y
b
2
Reproductive Allocation (%)
0
100
* water
* pop
* water
* pop
80
60
x
40
a
20
0
a
x
x
a
b
Shortgrass Steppe
y
Konza Prairie
Figure 1: Bouteloua gracilis end-of-season biomass (top panel) and reproductive allocation (bottom panel) at Shortgrass Steppe (left) and Konza
Prairie (right) garden sites. There was a significant difference between the total biomass at each garden (top panel). Significant main effects
(asterisk) and pairwise comparisons (different letters) are noted in each panel (P = 0.05). Main effect P values can be found in Table 3; no significant interactions were detected. Mean values ± 1 SE are shown.
216
Journal of Plant Ecology
Table 3: results from ANOVAs for the main effects of water treatment (wet vs. dry) and population (DP vs. PP) at both gardens (SGS and
KNZ)
B. gracilis
A. gerardii
Water treatment
SGS
ANPP
RTM
VTM
RP
RTD
SLA
Height
Population
KNZ
SGS
Water treatment
KNZ
Population
SGS
KNZ
SGS
KNZ
<0.0001*
0.0120*
0.8404
0.0005*
0.0726
0.1537
0.9128
0.1273
53.69, 72
8.93, 72
0.05, 72
14.15, 72
3.85, 63
2.38, 65
0.01, 63
3.75, 65
NA
0.3102
0.3306
0.0287*
0.0072*
1.13, 46
0.96, 66
14.25, 46
23.39, 66
0.0498*
0.6969
0.0006*
0.0329*
4.44, 63
0.16, 53
27.46, 63
9.50, 53
0.0033*
0.0744
0.0208*
0.0102*
0.1700
NA
NA
NA
NA
NA
NA
0.0492*
NA
0.0121*
0.0246*
6.65, 72
7.71, 72
4.01, 72
9.54, 72
4.79, 63
5.63, 65
20.58, 63
1.93, 65
<0.0001*
0.0020*
<0.0001*
<0.0001*
0.0085*
0.0083*
<0.0001*
<0.0001*
6.53, 503
3.54, 502
44.07, 503
13.47, 502
4.01, 273
3.51, 325
24.94, 273
0.1098
0.0121*
0.0516
0.0706
0.0060*
0.5759
0.0022*
<0.0001*
16.31, 325
3.11, 68
9.46, 66
3.99, 68
3.42, 66
8.09, 66
0.32, 65
10.18, 66
20.69, 65
<0.0001*
0.0024*
0.0021*
0.0761
0.1717
0.0751
0.7802
0.0571
57.07, 67
17.81, 63
50.19, 67
5.43, 63
2.12
0.0751
0.08
7.59, 66
Abbreviations: RP = reproductive percentage, RTD = reproductive tiller density, RTM = reproductive tiller mass, VTM = vegetative tiller mass.
P values are shown in the first line, followed by F-statistics and sample size. ANOVAs were run separately for each trait. With the exception
of RTD, all values are for end-of-season data. RTD is analyzed over the growing season (main effect*time). NA indicates that data were not
collected.
*Statistical significance at P = 0.05 level.
compared to DPs (Fig. 2, top). When water availability
was reduced, biomass and reproductive tiller density were
also reduced in both population types (Figs 1 and 2, top),
but only the PPs experienced a decrease in reproductive
allocation (Fig. 1, bottom). There was no measureable
population or water stress effect on SLA (Fig. 3). There
were no significant differences in predawn or mid-day
LWP between PPs and DPs under wet or dry conditions
(Table 2).
Although trait responses for B. gracilis in the reciprocal
mesic environment garden (KNZ) were not the primary
focus of this study, individuals from PPs produced significantly more biomass growing in Kansas than those from
the more arid DPs (Fig. 1, top), the dry treatment reduced
SLA for PPs (Fig. 3), and in contrast to responses in the SGS
environment, reproductive allocation in DPs was negatively
affected by a reduction in water availability (Fig. 1, bottom).
Patterns in reproductive phenology were similar for both
gardens, with the exception that PPs surpassed DPs in reproductive tiller density by the end of the season at KNZ (Fig. 2,
bottom).
Andropogon gerardii
For A. gerardii, we focused on traits of individuals from PPs
versus DPs growing in the tallgrass prairie climate (KNZ garden). Under wet conditions at KNZ, PPs (from Colorado)
produced only half as much biomass as DPs (Fig. 4, top) and
although the populations did not show significant differences in reproductive allocation (Fig. 4, middle), individual
reproductive tiller size was reduced by ca. 60% in individuals from PPs compared to DPs (Fig. 4, bottom). Vegetative
tiller size was similarly reduced (data not shown). Despite
their small individual size, PPs increased their reproductive
tiller density more rapidly and had a much higher density
at KNZ throughout the season (Fig. 5, top). When examining phenology, PPs were more phenologically advanced than
DPs (data not shown). SLA was greater in PPs at KNZ (Fig. 6,
left). Individuals from PPs were less affected by reduced water
availability in biomass, reproductive allocation and individual
reproductive tiller size than those from DPs (Fig. 4, left).
In the reciprocal garden (at SGS), no population or treatment effects were observed in total biomass (Fig. 4, top).
However, contrary to the KNZ garden, individuals from PPs
allocated significantly more biomass to reproduction (Fig. 4,
middle). The density of reproductive tillers at the end of the
season was significantly greater in PPs (Fig. 5) and the individual reproductive tillers of PPs were again reduced in size
(Fig. 4, bottom). Differences in SLA between populations at
SGS were similar to patterns at KNZ (Fig. 6, right).
Discussion
There has been much recent interest in the attributes and traits
of organisms found in the core versus edge of a species range
Giuliani et al. | Geographic variation and climate change217
Reproductive tiller density (m -2)
25
Shortgrass Steppe
DP, wet trt
DP, dry trt
PP, wet trt
PP, dry trt
20
*†
15
*†
*†
†
*†
†
10
5
Reproductive tiller density (m-2)
0
40
main effects:
* water effect
† population effect
Konza Prairie
*†
*
*
30
*
20
†
10
†
0
Jun
Jul
Aug
Sep
Oct
Figure 2: Bouteloua gracilis reproductive tiller density (in meters per square) at Shortgrass Steppe (top panel) and Konza Prairie (bottom panel) garden sites
throughout the growing season. Significant main effects are indicated by asterisk (water effect) and/or dagger (population effect) directly above the date
where significance occurred (P = 0.05). Main effect P values can be found in Table 3. Some points were offset slightly so error bars can be seen clearly. Note
the change in scale between panels; KNZ was much more productive than SGS despite the similar trends at both sites. Mean values ± 1 SE are included.
200
DP, wet trt
Specific Leaf Area (cm2g-1)
DP, dry trt
PP, wet trt
150
a
PP, dry trt
a
a
a
* water
x
x
x
y
100
50
0
Shortgrass Steppe
Konza Prairie
Figure 3: Bouteloua gracilis end-of-season SLA at Shortgrass Steppe (28 August 2009; left) and Konza Prairie (21 August 2009; right) garden
sites. Significant main effects (asterisk) and pairwise comparisons (different letters) are noted (P = 0.05). Main effect P values can be found in
Table 3; no significant interactions were detected. Mean values ± 1 SE are included.
218
Figure 4: Andropogon gerardii end-of-season biomass (top panel),
reproductive allocation (middle panel) and individual reproductive
tiller size (bottom panel) at Shortgrass Steppe (left) and Konza Prairie
(right) garden sites. There was a significant difference between the
total biomass at each garden (top panel). Significant main effects and
interactions (asterisk) and pairwise comparisons (different letters) are
noted in each panel (P = 0.05). Main effect P values can be found in
Table 3; significant interaction P values are indicated by appropriate
asterisks. Mean values ± 1 SE are included.
(Dudaniec et al. 2012; Jarema et al. 2009; Munwes et al. 2010;
Villellas et al. 2012), the strength of local adaptation in core
populations which may limit their ability to respond to climate
change (Bennington et al. 2012; Hereford 2009) and potential
climate change barriers to migration (Chen et al. 2011; Jalili
et al. 2010). We have argued that if the rate of climate change
is greater than the rate of migration for species that dominate
biomes, individuals from PPs may play a significant role in
the future in determining initial ecosystem structure and
function. This is because it is the dominant species that largely
determine ecosystem structure and function (Ellison et al.
Journal of Plant Ecology
2005; Grime 1998; Whittaker 1965). Thus, the goal of this
study was to better understand the potential consequences
of ecosystems being dominated by individuals with traits of
formerly PPs.
As noted previously, we focused on two scenarios: (i) a
mesic grassland drying to the extent that it becomes semiarid
and (ii) a semiarid grassland becoming more mesic. For the
first scenario, although there were no significant differences
between DPs and PPs in total biomass of B. gracilis in the shortgrass prairie environment (a climate similar to that the PPs
would experience in the future), differences were noted in
reproductive allocation, reproductive tiller density, flower initiation, average maximum end-of-season height and sensitivity to water stress (Figs 1–3).
For the second scenario, A. gerardii biomass and growth
traits differed significantly between DPs and PPs. Individuals
from PPs had much reduced biomass under well-watered conditions compared with DPs (despite greater SLA), as well as
significantly smaller reproductive tillers (although at a higher
density). Biomass of individuals from PPs was less sensitive to
water stress however. Thus in both scenarios, under common
garden conditions, the traits of individuals from PPs differed
in a number of ecologically meaningful ways from individuals collected from today’s DPs. Although production responses
might be expected to have the greatest array of ecosystem
consequences, alterations in reproductive phenology could be
very important for the capability of these dominant species to
locally adapt to new climatic conditions (Jump and Penuelas
2005).
Although it would be unwise to generalize from these
two specific scenarios, our results lead to two important
conclusions. First, a relatively broad range of traits differed
between PPs and DPs—from phenological, to those related
to growth, and to sensitivity to resource limitation (water
stress). Second, these trait differences between populations
were distinctive—they were largely related to reproduction
for the first scenario versus growth in the second. Both of
these support the contention that present-day ecosystem
functioning, as determined by traits of the dominant
species, may be altered significantly as a function of these
population-level trait differences. An assumption made in
this study is that the dispersal distance needed for traits to
track climate change is too great for seed and pollen dispersal.
An alternative perspective is that pollen-mediated gene flow
could lead to lower differentiation among core, intermediate
and leading-edge populations (Shi and Chen 2012), although
this did not appear to be the case in these grasses. Thus,
intraspecific geographic variation in the traits of dominant
species adds another, more subtle layer of uncertainty to our
ability to predict future ecosystem function based on our
extant knowledge.
Previous studies have already identified no-analog environmental conditions and novel community composition as
mechanisms driving changes in future ecosystem structure
and function (Nippert et al. 2006; Seastedt et al. 2008; Veloz
Giuliani et al. | Geographic variation and climate change219
Figure 5: Andropogon gerardii reproductive tiller density (in meters per square) at Konza Prairie (top) and Shortgrass Steppe (bottom) garden sites throughout
the growing season. Significant main effects are indicated by asterisk (water effect) and/or dagger (population effect) directly above the date where significance was found (P = 0.05). Main effect P values can be found in Table 3. Some points were offset slightly so error bars can be seen clearly. Note the change
in scale between panels. Although similar trends were seen between sites, KNZ was much more productive than SGS. Mean values ± 1 SE are included.
250
* pop
DP, wet trt
* water
* pop
Specific Leaf Area (cm2 g-1)
DP, dry trt
200
PP, wet trt
PP, dry trt
b
a
150
b
a
x
x
x
y
100
50
0
Konza Prairie
Shortgrass Steppe
Figure 6: Andropogon gerardii end-of-season SLA at Konza Prairie (21 August 2009; left) and Shortgrass Steppe (28 August 2009; right) sites.
Significant main effects (asterisk) and pairwise comparisons (different letters) are noted (P = 0.05). Main effect P values can be found in Table 3;
no significant interaction P values were observed. Mean values ± 1 SE are included.
220
et al. 2012; Williams and Jackson 2007). The results of this
research suggest that even without these two mechanisms,
forecasting the future of ecosystems and the services they provide will require knowledge, currently lacking, on the migration rates (and barriers to migration) of key species. If today’s
populations of dominant plant species cannot keep pace with
climate change, then greater understanding of genetic and
phenotypic variation throughout a species range, and the
rates of adaptation for these dominant species must be investigated, particularly under conditions where there are realistic interspecific interactions (Eckert et al. 2008; Hoffmann and
Blows 1994; Lesica and Allendorf 1995; Moser et al. 2011).
Funding
National Science Foundation (1027319, 0218210 and
0823341).
Journal of Plant Ecology
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Acknowledgements
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We thank Dr Phillip Chapman (Department of Statistics, Colorado
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Conflict of interest statement. None declared.
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