Response of alpine plant flower production
to temperature and snow cover fluctuation
at the species range boundary
Thomas Abeli, Graziano Rossi, Rodolfo
Gentili, Andrea Mondoni & Paolo
Cristofanelli
Plant Ecology
An International Journal
ISSN 1385-0237
Volume 213
Number 1
Plant Ecol (2012) 213:1-13
DOI 10.1007/s11258-011-0001-5
1 23
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Plant Ecol (2012) 213:1–13
DOI 10.1007/s11258-011-0001-5
Response of alpine plant flower production to temperature
and snow cover fluctuation at the species range boundary
Thomas Abeli • Graziano Rossi •
Rodolfo Gentili • Andrea Mondoni
Paolo Cristofanelli
•
Received: 15 April 2011 / Accepted: 28 October 2011 / Published online: 13 November 2011
Ó Springer Science+Business Media B.V. 2011
Abstract Surface temperatures have risen globally
during the last 30 years, especially in alpine areas. It is
recognized that these increases are influencing phenology, physiology and distribution of plants. However, few studies have addressed the effects of climate
warming at the species range boundary, where plants
are expected to be more stressed. We analysed 11-year
data sets of inflorescence production of four alpine
plants (Carex foetida, Leucanthemopsis alpina, Senecio incanus, Silene suecica) at the southern boundary of their distribution range in the N-Apennines
(N-Italy), in relation to air temperature and snow cover
persistence. Inflorescence production of all species
fluctuated greatly and was significantly affected by the
variation of the mean temperature of June/July. We
found significant relationships also between species
data series and the snow cover persistence. Moreover,
species responded differently to such parameters. One
species showed a significant decrease of the
T. Abeli (&) G. Rossi A. Mondoni
Department of Earth and Environmental Sciences,
University of Pavia, Via S. Epifanio 14, 27100 Pavia, Italy
e-mail: [email protected]
R. Gentili
Dipartimento di Scienze dell’Ambiente e del Territorio,
University of Milan-Bicocca, Piazza della Scienza 1,
20126 Milan, Italy
P. Cristofanelli
Institute of Atmospheric Sciences and Climate, National
Research Council, Via Gobetti 101, 40129 Bologna, Italy
reproductive effort, whereas the other three showed
a stable trend of inflorescence production. We have
shown that some alpine species are favoured by
increased temperature and reduced snow cover even at
the boundary of their range, where they are thought to
be particularly sensitive to warming. However, the
aptitude to cope with climate change might be limited
by competition against thermophilous species migrating from lower altitude and in some cases by the low
altitude of mountain peaks that prevent species
upward migration. The individualistic response of
species to climate change found here, support the
statement that the composition of plant communities
might rapidly change in the future.
Keywords Climate change Long-term monitoring Peripheral populations Plant reproduction Snow
cover Species resilience
Introduction
Surface temperatures have been rising globally during
the last 30 years with greater increases over land than
ocean, and with the largest increases at high latitudes
in the Northern Hemisphere (Hansen et al. 2006).
As reported by the IPCC (2007) the increase in
global average temperatures is 0.13°C ± 0.03°C per
decade since the mid-twentieth century. A recent
analysis of global surface temperature by the World
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Meteorological Organization (2011) assessed that the
decade 2001–2010 was the warmest on record dating
back to 1880: temperatures over this decade averaged
0.46°C above the 1961–1990 mean, 0.21°C warmer
than the previous record decade 1991–2000. In
particular, Europe and the Mediterranean Basin represent ‘‘hot-spot’’ areas to climate change, mostly
because of an increase of summer temperatures
(Giorgi 2006). For example, over the Mediterranean,
Kuglitsch et al. (2010) detected strong positive trends
in the temperature of hot summer days since 1960,
whilst Baldi et al. (2006) observed an increase of
summer heat wave frequency during the last decades
of the 20th century. Auer et al. (2007) pointed out that
the so-called Greater Alpine Region has warmed twice
as much since the late 19th century compared to the
global or Northern Hemispheric average.
These rapid changes are affecting ecosystems and
organisms, influencing the phenology, physiology and
distribution of several plant species (Walther et al.
2005; Parolo and Rossi 2008; Pautasso et al. 2010).
Plants are particularly sensitive to climate changes,
because of their inability to move to better living
conditions, except for dispersal of propagules and
progenies. Consequently, plant species have responded
to warming through a generally accelerated phenology,
enhanced growth and increased reproductive effort
(Arft et al. 1999; Dormann and Woodin 2002). The
reverse effect might be the exceeding of the optimal
temperatures for metabolic and physiologic processes,
that can lead to an increased stress and to a diversion of
energy and resources from reproduction and growth to
maintenance (Parsons 1990; Ciais et al. 2005). Furthermore, several authors have demonstrated that
altered precipitation regimes might affect plant species
survival and reproduction (e.g. Weber et al. 2007;
Alba-Sánchez et al. 2010). In particular, snow persistence might change the length of the vegetative season
or, when less abundant, expose plants to freezing (e.g.
Körner 1999; Huelber et al. 2006).
Many studies have investigated the effects of
climate change on plants (see Pautasso et al. 2010),
most of them at the ecosystem scale (e.g. Hollister
et al. 2005; Hudson and Henry 2009; Teuling et al.
2010; De Boeck et al. 2011) or in response to drought
(e.g. Björk and Molau 2007; van Mantgem and
Stephenson 2007; Weber et al. 2007; Ambebe and
Dang 2010). However, few studies have analysed the
response of plant reproduction to climate warming
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Plant Ecol (2012) 213:1–13
through continuous long-term data sets which include
data on snow cover persistence and air temperature
(Inouye et al. 2002; Inouye 2008; Green 2010). Even
fewer studies have addressed such response of the
populations at the boundary of species range distributions (Lesica and McCune 2004; Macias et al. 2006),
which are thought to be particularly sensitive to
climate change (Parsons 1990), because they are
usually smaller and more stressed than central populations (Gaston 2003).
In this study, we used summer temperature and
snow cover fluctuations recorded in the Northern
Apennines over 11 years from 1999 to 2009 to infer
possible response of four alpine species at the southern
boundary of their range to climate changes. In
particular, we hypothesize that flowering abundance
is negatively related with increasing summer temperatures and decreasing snow cover persistence.
The Northern Apennines chain is strategic for
understanding how the link between climate change
and range marginality can drive the survival of
isolated plant populations for three reasons: (1) it is
located within the Mediterranean area (in a broad
sense) where climate change is expected to be
strongest even in moderate climate change scenarios
(Nogués-Bravo et al. 2007; Thuiller et al. 2005); (2) it
has middle-low altitude (the highest peak is M.
Cimone, 2165 m a.s.l.) that excludes any further
possibility of upward plant migration, a contrast to
areas such as the Alps (Walther et al. 2005; Parolo and
Rossi 2008); (3) it hosts a relictual alpine flora and
vegetation and represents the southern range boundary
for several arctic-alpine and orophytic plant species,
occurring in a narrow area, with small isolated
populations (Tomaselli et al. 1994; Abeli et al. 2009).
Materials and methods
Site and species description
The study area (Fig. 1) is located along the main ridge
of the Northern Apennine chain into the TuscanEmilian Apennines National Park (N-Italy).
The study site is located between the slopes of M.
Cusna (2120 m a.s.l.) and M. Prado (2054 m a.s.l.) in
relict glacial cirques, with inactive glacial and active/
inactive periglacial landforms (Gruppo di Ricerca
Geomorfologia C.N.R. 1982).
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Plant Ecol (2012) 213:1–13
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Fig. 1 Study area in the
Northern Apennines
The N-Apennines chain is principally composed of
sedimentary rocks of the compact turbiditic sandstone
type (upper Oligocene—lower Miocene), that belong
mainly to the ‘Macigno’ formation (Gruppo di Ricerca
Geomorfologia C.N.R. 1982).
Vegetation, growing above the local Fagus sylvatica L. forest limit (about 1700/1800 m a.s.l.) is
characterised by subalpine shrubland (Vaccinium
spp.) and grassland (Nardus stricta L. and Festuca
violacea Schleich. ex Gaudin subsp. puccinellii Foggi,
Graz. Rossi & Signorini) and locally by relict alpine
plant communities (Tomaselli 1994). Along southern
slopes, vegetation is characterized by Brachypodium
genuense (DC.) Roem. & Schult. and Festuca paniculata (L.) Schinz & Thell. grasslands. The four studied
taxa (Table 1) are: Carex foetida All. (Cyperaceae),
Leucanthemopsis alpina (L.) Heywood (Asteraceae),
Senecio incanus L. subsp. incanus (Asteraceae) and
Silene suecica (Loddiges) Greuter & Burdet (Caryophyllaceae). All these species (hereafter referred to by
their generic epithets only) grow in the study area with
a few isolated populations at the southern boundary of
their distribution. Carex and Senecio are known to
spread vegetatively (Pignatti 1982) as well as by seed.
Senecio and Silene usually produce a single flowering
stem bearing several inflorescences. Carex and Leucanthemopsis usually have a single inflorescence for
each flowering stem. All the species could have more
than one flowering stem for each individual.
In the study area, Carex is the dominant species in
the igrophilous snowbed communities which are
characterized by high amounts of organic matter and
nutrients (Leonardi 2001) and a snow-free period of
about 130 days (Tomaselli 1991; Petraglia and Tomaselli 2007). Leuchantemopsis grows in localities
characterized by fairly long snow cover, but with
low soil moisture (with respect to the previous species)
along with Salix herbacea L. (Reisigl and Keller
1987). Senecio and Silene usually grow in less humid
grassland patches in areas with long-lasting snow
cover, but free draining soil due to the rocky substrate
(Haraldsen and Wesenberg 1993; Aeschimann et al.
2004). Leucanthemopsis, Senecio and Silene grow in
nutrient poor soil (Aeschimann et al. 2004; Leonardi
2001), in sites with a snow-free period of about
140–160 days (Tomaselli 1991). Amongst these last
three species, Senecio and Leucanthemopsis are
included in the typical Sileno exscapae-Trifolietum
alpini that usually is found in the mountain ridge at
higher altitude (Tomaselli and Rossi 1994). Here wind
plays an important role in the snow accumulation by
removing snow that is accumulated in the northern
slope. As a consequence, Senecio and Leucanthemopsis experience longer snow-free periods with respect to
Silene that grows in the northern slope just below the
ridge in the Sileno exscapae-Trifolietum alpini luzuletosum spicatae, variant of Gnaphalium supinum
(Tomaselli and Rossi 1994).
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Table 1 General biological and ecological characteristics of the studied species
Species
Life-form
Chorology
Ecology
Carex foetida
Hemicryptophyte
caespitose
SW-European
orophyte
Snow bed specialist. Snow accumulation areas with moist and humusrich soils. Altitudinal range 1800–3200 m
Leucanthemopsis
alpina
Hemicryptophyte
scapose
SW-European
orophyte
Scree slopes, slopes subject to landslides and rocky cliffs (siliceous
soils). Altitudinal range 2000–3600 m
Senecio incanus
subsp. incanus
Hemicryptophyte
scapose
W Alpine/NApenninic
Alpine grasslands, windy slopes and ridges on acid siliceous soils.
Altitudinal range1800–2600 m
Silene suecica
Hemicryptophyte
rosette
Arctic/Alpine
Siliceous rocky cliffs and alpine grasslands. Altitudinal range
2000–2850 m
Reproductive performance
The number of flowering stems (NFS) and the number
of inflorescences per flowering stem (IFS), were used
as a surrogate measure of reproductive effort. Data
were recorded annually at the end of July, in the peak
flowering season, with the exception of Carex which
flowered at the end of August. Field observation
started in 1999 and ended in 2009. NFS was recorded
inside 5 9 5 m permanent plots (1 9 1 m for Carex,
which grows in highly dense patches) placed at
random and marked at each corner with aluminium
posts. The study species were distributed in the study
area in small patches of few tenths of square metres in
the northern slope of M. Prado. Carex had the most
fragmented distribution with five patches distributed
between M. Prado and M. Cusna. At least a couple of
plots were placed in each patch for all the species.
IFS of Senecio and Silene was recorded by using ten
randomly selected plants inside each plot of the
species. Carex and Leuchantemopsis have only one
inflorescence per stem.
Meteorological data
The mean monthly temperatures of the species flowering period (May, June, July and August) were
obtained from observations carried out by ISAC-CNR
(Institute of Atmospheric Sciences and Climate—
Italian National Research Council) at the Global GAW
Station ‘ICO-OV’, the closest meteorological station
to the study area with a complete data series. ICO-OV
is part of the Global Atmospheric Watch (GAW)
programme by the World Meteorological Organization (WMO) and SHARE (Station at High Altitude for
Research on the Environment) by Ev-K2-CNR (Bergamo). Due to the geographic location, the air-
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temperature measurements carried out at M. Cimone
can be considered representative for the seasonal
variability characterising the study area, thus providing a complete time series overlapping the study
period.
The snow cover persistence at M. Prado, measured
as the surface covered by snow, from 1980 to 2054 m
a.s.l. was also recorded by authors directly in the field
from 1999 to 2009 and mapped using GIS. We had
four relevés in each year, every 15 days starting from
1st June to 15th July.
The mean temperature values recorded at the ICOOV and the mean snow cover data at M. Prado, during
the 11-year study are summarized in Tables 2 and 3.
As deduced by ICO-OV observations, during the
investigation period a mean summer (May–August)
temperature of 9.3 ± 1.1°C was observed at M.
Cimone with the highest mean monthly values
(11.1 ± 1.5°C and 11.3 ± 1.8°C, respectively) in
July and August. As also reported in Fig. 2 showing
the time-series of monthly average temperature at M.
Cimone from 1999 to 2009, the highest average
summer temperature was observed in summer 2003,
when long-lasting heat waves occurred over West/
central Europe and Northern Italy (e.g. Cristofanelli
et al. 2007), with significant implication to alpine
vegetation (Abeli et al. in preparation; Jolly et al.
2005). By contrast, the lowest average summer
temperature was observed in 2004.
Data analysis
The time series of each studied species was examined
for the presence of autocorrelation using the DurbinWatson test (Wigley et al. 1985). None of the time
series showed significant autocorrelation.
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Table 2 Summary of the climatic parameters of the study area during the 11-year monitoring period
Temperature (°C)
May
June
July
August
Avg.
5.4
9.4
11.1
11.2
9.3
SD
1.3
1.6
1.4
1.8
1.0
Min (year)
Max (year)
2.4 (2004)
7.4 (2009)
7.7 (1999)
13.5 (2003)
8.2 (2000)
13.4 (2006)
8.4 (2006)
14.7 (2003)
Mean summer
8.3 (2004)
12.1 (2003)
Temperatures were recorded between May and August and deduced by ICO-OV measurements at M. Cimone (2165 m a.s.l.)
Table 3 Summary of the climatic parameters of the study area during the 11-year monitoring period
Snow area (m2)
Snow 1 (1st June)
Snow 2 (15th June)
Snow 3 (1st July)
Snow 4 (15th July)
Mean summer
Avg.
44303.7
9047.7
604.9
12.1
53959.5
SD
71508.8
17172.1
1307.7
26.8
89622.9
0.0
50126.8 (2004)
0.0
4007.0 (2004)
0.0
84.7 (2009)
Min (year)
Max (year)
903.9 (2002)
231743.2 (2004)
903.9 (2002)
285883.3 (2004)
Area of snow cover mapped and measured in GIS from authors’ annual surveys at M. Prado
Fig. 2 Time series of
monthly average
temperatures for summer
months at M. Cimone for the
investigated period
(1999–2009)
The matrix of species data/climatic variables was
subjected to redundancy analysis (RDA) to test
environmental variables (gradient analysis) under a
full model. The mean species NFS and IFS for each of
the 11 years were used. RDA ordinations were
performed for NFS and IFS species matrices with
respect to the following climatic variables: Snow
cover (at 1st, 15th, and 30th June and at 15th July:
Snow_1, Snow_2, Snow_3, Snow_4, respectively),
mean temperatures of May, June, July and August
(T_May, T_Jun, T_Jul, T_Aug, respectively).
A Monte-Carlo permutation test (999 replications)
was performed to assess the significance of the
environmental variables (forward selection under
CANOCO output). The software employed for ordination of the plots was CANOCO version 4.5 (Leps
and Smilauer 2003). Linear regressions were also
performed to find out species trends in the study
period, whereas correlation analysis was run to
analyse the relationships between species reproductive
performance (NFS and IFS) and temperatures (Pearson) and snow cover (Spearman) of each separate
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month. Finally, the relationships between the reproductive performance of the four species were investigated by Pearson’s correlation analysis.
–
–
–
Results
–
The mean NFS and IFS of the study species for all the
study years are summarized in Table 4. IFS of Senecio
and Silene were correlated to each other and varied
slightly from the mean values along the time series
(8.82 ± 1.4 and 8.74 ± 1.4, mean ? SD, respectively; Table 4). The number of plots varied, depending on species abundance (Table 4).
The RDA ordinations resulted in high eigenvalues
for the first axes and cumulative percent variance of
species data and species-environment correlations
(Table 5a). In both NFS and IFS ordinations the first
axis accounted for most of the variance in speciesenvironment correlations. In the NFS ordination all
four eigenvalues reported are canonical and correspond to axes that are constrained by the environmental variables. In the IFS ordination only the first two
eigenvalues reported are canonical, the other two are
not, since there are only two species. In the NFS RDA
triplot (Fig. 3a; Table 5) the first and second axes
accounted for over 80% of species variance. The
Monte-Carlo permutation test indicated that, under the
full model, the effect of T_Jun and T_Jul were
significant (P \ 0.024, and P \ 0.048, respectively,
with 999 permutations). Such factors explained
most of the variance (highest conditional effect:
Table 5b) of the model (lambdaA = 0.38 and 0.24,
respectively).
RDA ordinated the species according to the
following gradients:
Table 4 Number of permanent plots, mean number of flowering stems (NFS) and mean number of inflorescences per stem
(IFS) of the study species for all the years
Species
Plot
Carex foetida
Average NFS
(S.E.)
Average
IFS
(S.E.)
16
62.93 (14.5)
Leucanthemopsis alpina
Senecio incanus subsp.
incanus
5
5
67.07 (14.8)
178.43 (32.0)
8.82 (0.4)
Silene suecica
4
393.60 (52.5)
8.74 (0.4)
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Silene was distributed according to an increase of
T_Jun and decreasing snow cover;
Carex was distributed according to a decrease of
T_Jun;
Leucanthemopsis was mostly distributed in relation to a decrease of T_Jul;
Senecio was mostly distributed in relation to an
increase of T_Jul and snow cover (Snow_1, 2, 3;
not significant).
In the IFS RDA triplot (Fig. 3b; Table 5) the first
and second axes accounted for 100% of species
variance. The Monte-Carlo permutation test indicated
that, under the full model, only the effect of the
variables Snow_3, T_Aug, T_Jul and T_May were
significant (P \ 0.014, P \ 0.006, P \ 0.04,
P \ 0.016, respectively, with 999 permutations).
The factors explaining most of the variance (highest
conditional effect, Table 5b) were T_May and T_Jul
(lambdaA = 0.53 and 0.23, respectively).
The resulting RDA triplot ordinated the species
according to the following gradients (Fig. 3b):
–
–
Silene IFS was distributed according to an increase
of T_May and a decrease of the snow cover
(Snow_3);
Senecio IFS was mostly distributed in relation to
an increase in both T_Jul and snow cover.
Correlation analysis between the NFS and climatic
parameters were substantially in accordance with the
RDA analysis (Table 6).
Amongst the study species, Leucanthemopsis significantly decreased its reproductive performance as
NFS throughout the 11-year study period (F = 5.208;
P = 0.048; R = 0.605). Pearson correlations showed
a positive significant correlation between C. foetida
and L. alpina time series (Table 6).
Discussion
The present data of the 11 year monitoring program of
four alpine and arctic-alpine plant species at the
southern boundary of their range showed significant
relationships between inflorescence production and
fluctuation of temperature and snow cover persistence.
Inflorescence production of all species fluctuated
greatly and was significantly affected by the variation
of the mean temperature of June and/or July. However,
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Table 5 Redundancy analysis
Axes
1
2
3
4
Total inertia
a
NFS
Eigenvalues
Species-environment correlations
0.604
0.997
0.196
0.748
0.019
0.827
0.012
0.896
1
Cumulative % variance
Of species data
26.6
Of species-environment correlations
48.6
67.9
79.6
0.997
0.998
0.999
0.997
Species-environment correlations
0.998
0.001
0.001
0
Cumulative % variance
0.999
1
0
0
100
0
0
0
IFS
Eigenvalues
Of species data
99.8
Of species-environment correlations
99.9
99.9
100
NFS
Variable
1
IFS
Marginal effects
Conditional effects
Marginal effects
Conditional effects
Lambda1
LambdaA
P
F
Lambda1
LambdaA
P
Snow_1
0.16
0.02
Snow_2
0.2
0.01
0.832
0.14
0.34
0
0.534
0.898
0.1
0.4
0
0.368
Snow_3
0.16
1.23
0.03
0.762
0.27
0.34
0.14
0.014
15.61
Snow_4
T_May
0.1
0.03
0.534
0.51
0.01
0.06
0.238
1.71
0.07
0.08
0.256
1.45
0.53
0.53
0.016
9.16
T_Jun
0.38
0.38
0.024
4.91
0.04
0.01
0.218
1.95
T_Jul
0.13
0.24
0.048
4.55
0.09
0.23
0.04
6.81
T_Aug
0.13
0.04
0.446
0.85
0.4
0.03
0.006
28.15
F
b
0.41
a Ordination parameters for the first four constrained ordination axes. b Variance values according to marginal effect (absolute) and
conditional effect (additional) explained by each environmental variable in the constrained ordination listed after the automatic
forward selection by CANOCO. Significant variables are shown in bold
NFS Number of flowering stems, IFS number of inflorescences per flowering stem, Snow_1 snow cover at 1st June, Snow_2 snow
cover at 15th June, Snow_3 snow cover at 30th June, Snow_4 snow cover at 1st July
as shown by the RDA model and correlation analysis,
species response to temperature was contrasting, some
being negatively and others being positively affected.
Senecio and Silene increased their inflorescence
production following increasing temperature, whilst
the opposite was observed in Carex and Leucanthemopsis (Fig. 4).
In many arctic-alpine and alpine species flower
production is favoured by increased temperature,
probably due to an increased productivity enhanced
by warmer temperature (Hudson and Henry 2009; Hill
and Henry 2011). For instance, experimental warming
enhanced the growth and gas exchange along with
efficiency of photosystem II of Elymus nutans Griseb.
in the Tibetan Plateau (Shi et al. 2010), and in Oxyria
digina (L.) Hill in the Arctic (Pyancov and Vaskovskii
1994). By contrast, prolonged exposure to high
temperature can reduce the reproductive performance
in many species, as a consequence of morphological
modifications and the reduced activity of other physiological processes, such as photosynthesis. Pyancov
and Vaskovskii (1994) found a decreased number of
chloroplasts in plants of Alopecurus alpinus Smith.
exposed to high temperatures, whilst Shi et al. (2010)
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Fig. 3 Redundancy analysis (RDA) triplot showing the distribution of species NFS (a) and IFS (b) in relation to the climatic
environmental variables and the years of observation
showed reduced efficiency of photosynthesis in
Potentilla anserina L. accompanied by oxidative
stress due to accumulation of oxidative compounds.
It is therefore possible that different physiological
responses to temperature variations may have
occurred in our species. However, ad hoc studies are
needed to prove these hypotheses.
The response of inflorescence production to snow
cover persistence was also not consistent across our
species. RDA and correlation analysis showed that
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Silene was negatively affected by the long lasting
snow cover, as suggested by the negative relation
between NFS and IFS and snow cover persistence in
mid-June (Table 6). This result agrees with GimenezBenavides et al. (2005) who found a higher fitness in
the Mediterranean-Montane species Silene ciliata
Pourret, when flowering earlier. Surprisingly, similar
behaviour was observed in the snow bed specialist
Carex. Indeed, Carex phenology seems to be more
related to soil moisture, provided by the gradual snow
melting (Petraglia and Tomaselli 2007), than directly
by the amount of snow. In further support to this,
Baptist et al. (2010) found that C. foetida productivity
in its core distribution area in the Alps was not affected
by experimental snow cover manipulation. Similarly,
Leucanthemopsis and Senecio were not significantly
related with snow cover persistence (Tables 5, 6). This
is probably due to the fact that these species grow on
the mountain ridge where most of the snow is removed
by the dominant winds (Tomaselli and Rossi 1994).
Alpine species phenology and reproductive performance may show similar response to different snow
cover persistence. For example, early snow melting
may cause early drought (Björk and Molau 2007) and
higher risk of freezing (Inouye et al. 2002; Baptist
et al. 2010). By contrast, longer lasting snow cover
reduces the vegetative season and in turn might affect
the normal expression of the seasonal life cycle (Björk
and Molau 2007; Cooper et al. 2011). Interestingly,
2002 and 2004, characterized by very early and very
late snow melting, respectively, had similar effects on
inflorescence production, decreasing NFS in Carex
and Leucanthemopsis and increasing NFS in Senecio.
Detailed considerations about the effect of snow
depth are necessary. Light can penetrate the snow pack
up to 2 m and many alpine plants start to grow under
the snow pack in response to light penetration
(Richardson and Salisbury 1977). However, the snow
depth and snow melting date are often highly correlated (Hejcman et al. 2006), and we consider the effect
of these two parameters strictly linked.
Along with macroclimatic factors, microclimate
conditions also play a role in plant reproductive
efforts, mitigating or enhancing the effect of temperature and snow cover accumulation at the soil level
(Körner 1999). An effect of microclimatic conditions
is supported, in our case, by the occurrence of
Leucanthemopsis, Senecio and Silene that grow very
close to each other in a few metre square area, despite
1
T_Jul
1
T_Aug
Snow_1
Rho 0.679*
Rho
0.746*
1
Snow_2
Rho
0.819**
1
Snow_3
1
Snow_4
NFS Number of flowering stems, IFS number of inflorescences per flowering stem, Snow_1 snow cover at 1st June, Snow_2 snow cover at 15th June, Snow_3 snow cover at 30th
June, Snow_4 snow cover at 1st July
If not specified, values refer to Pearson’s r. * P \ 0.05; ** P \ 0.01
Snow_4
Snow_3
Rho
0.900**
Rho 0.736*
1
T_Jun
Snow_2
1
T_May
1
Rho 0.657*
0.605*
1
IFS Sil
Snow_1
T_Aug
T_Jul
T_Jun
T_May
-0.619*
IFS
Sen
0.650*
1
NFS Sil
1
0.639*
1
NFS
Sen
IFS Sil
0.639*
1
NFS
Leu
IFS Sen
NFS Sil
Rho 0.694*
0.682*
NFS
Leu
NFS
Sen
1
NFS
Car
NFS Car
Table 6 Correlation table
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Plant Ecol (2012) 213:1–13
9
123
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10
Plant Ecol (2012) 213:1–13
Fig. 4 Trends (solid line)
of the number of flowering
stems (NFS) of the studied
species from 1999 to 2009;
a C. foetida, b L. alpina,
c S. incanus subsp. incanus,
d S. suecica. Dashed line in
b and c represents the mean
temperature of July recorded
at M. Cimone and resulted
significantly correlated with
the flowering abundance of
L. alpina and S. incanus
their different ecological requirements (Leonardi
2001). Indeed, there is a gradient of soil moisture
and length of the growing season from Leucanthemopsis to Senecio and Silene habitats (Tomaselli 1991).
Other factors may also play a role, including photoperiod length. In particular, Keller and Körner (2003)
found that the flower production of L. alpina increases
with increasing length of the photoperiod. This means
that in the case of longer free snow periods due to
climate changes L. alpina might be favoured by the
consequent longer growing season.
In addition to the temperature and the snow cover
abundance, the rate of flowering can be affected by the
resources available, either already stored in the plants
or present in the soil (Crone and Lesica 2004).
Following high inflorescence production there is a
depletion of resources that cannot be used in the next
year. On the other hand, low inflorescence production,
due to unsuitable climatic conditions, results in more
available resources for flowering in the next reproductive season (Crone and Lesica 2006). This may
explain why in our species, years after high flowering
peaks were often characterized by lower inflorescence
production and vice versa (Fig. 4).
Plant populations at the margins of their geographical and ecological ranges are thought to be particularly sensitive to global warming (Parsons 1990).
Here, we have shown that the reproductive effort,
123
measured as inflorescence production, of some alpine
species are favoured by increased temperature and
reduced snow cover, whilst others are disadvantaged
or indifferent. Whilst we cannot say if these changes
reflect an advantage or disadvantage for the populations, the possibility that a long-term effect of climate
on the species reproductive performance might alter
the population dynamics cannot be ruled out. Similar
contrasting responses were also found by Lesica and
McCune (2004) in similar habitats of North America,
suggesting that the response of these populations to
climate change cannot be generalised.
During the 11 years of plant monitoring Leucanthemopsis was the only species showing a significant
decline of inflorescence production. In the other
species NFS and IFS have varied according with
summer temperature and snow cover of each year as
described above, but regression analysis did not detect
any significant increase/decrease of inflorescence
production. From 1999 to 2009, there was not a
significant increase of temperature in the study area
except in July, when summer meteorological conditions have been characterised by lower monthly
temperatures during the first 4 years of the investigation period (Figs. 2, 4). During this month, the NFS of
Leucanthemopsis was negatively correlated with the
mean temperature of July (Table 6). Although
11 years of temperature records are not enough to
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Plant Ecol (2012) 213:1–13
detect significant climate warming, possible relations
between the decreasing of inflorescence production of
Leucanthemopsis and the increased temperature of
July cannot be ruled out. A longer data series on
Leucanthemopsis inflorescence production would be
needed to better clarify this point. However, Leucanthemopsis at M. Prado grows in just one small and
isolated population, suggesting that low genetic variability and high degree of differentiation compared to
central populations may occur in this plant. Indeed,
low genetic variability and inbreeding depression have
been found in nearby populations of other species such
as Rhododendron ferrugineum L. (Bruni et al. 2011)
and Abies alba Mill. (Piovani et al. 2010).
The individualistic response of species to different
meteorological conditions found here, further support
the statement that the composition of plant communities might change in the future due to climate change
(Walther et al. 2002), with some species becoming
more abundant then others. In this scenario, the
survival of marginal populations is particularly uncertain. Indeed, the aptitude to cope with climate change
might be limited by intrinsic factors of these populations such as the high inbreeding rate and the low
dispersal ability. The increased competition against
more thermophilous species migrating from lower
altitude (Parolo and Rossi 2008), and the low altitude
of some mountain chains (e.g. Apennines, Vosges,
Appalachian Mountains, etc.), which prevent possible
species upward migration, are further concerns. Both
these phenomena are thought to be the major contributors to the species turnover and extinction expected
for mid-latitude and Mediterranean mountain chains
(Thuiller et al. 2005). In particular, since the studied
species are already growing on, or close to, the top of
M. Prado, they have no chances to move upward.
However, snow accumulation is expected to mitigate the effects of warming temperatures and probably
represents a barrier against the colonization of thermophilous species (Ferrari and Rossi 1995; Petraglia
and Tomaselli 2007), at least in snow beds.
In agreement with Hollister et al. (2005) our results
hint that better evaluation of the response of orophytic
and arctic-alpine species to climate change is needed.
In particular, long-term monitoring of study species
may be one of the most important sources of
information to understand the effects of increased
temperature and snow cover variation on orophytic
and arctic-alpine species and their chances of survival.
11
Acknowledgements Authors are grateful to Cecilia Amosso,
Luigi Bertin, Paolo Cauzzi, Roberto Dellavedova, Tommaso
Dones, Martina Gentilini, Andrea Leonardi, Gilberto Parolo
(University of Pavia) for their support in the field during the tenyears monitoring. The Appennino Tosco-Emiliano National
Park, University of Pavia, L-TER and SHARE (Ev-K2-CNR,
Bergamo) for their interest and funding support to the research.
Author thanks Prof. Franco Barbaini (University of Pavia) for
his suggestions on the statistical analysis. Authors thank Ruth
Eastwood (Seed Conservation Department, Royal Botanic
Gardens, Kew) for the improvement of the language and
Paolo Bonasoni (ISAC-CNR, Bologna) for his useful comments
on climate issues and M. Cimone data. We are also grateful to
the two anonymous reviewer for their suggestions useful for
improving the quality of our manuscript.
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