winter warming as an important co-driver for betula nana growth in western greenland during the...

Winter warming as an important co-driver for Betula nana

growth in western Greenland during the past centuryJØRGEN HOLLESEN 1 , 2 , AGATA BUCHWAL 3 , 4 , GRZEGORZ RACHLEWICZ 3 ,

B I RGER U . HANSEN 1 , MARC O . HANSEN 1 , OLE STECHER 5 and BO ELBERLING1

1Center for Permafrost (CENPERM), Department of Geoscience and Natural Resource Management, University of Copenhagen,

Øster Voldgade 10, DK-1350 Copenhagen, Denmark, 2Department of Conservation and Natural Sciences, National Museum of

Denmark, I.C. Modewegsvej, Brede, DK-2800 Lyngby, Denmark, 3Institute of Geoecology and Geoinformation, Adam Mickiewicz

University, Dziegielowa 27, 61-680 Poznan, Poland, 4 Department of Biological Sciences, University of Alaska Anchorage,

Ecosystem and Biomedical Lab, 3151 Alumni Loop, Anchorage, AK 99508, USA, 5Arctic Station, University of Copenhagen,

Qeqertarsuaq, Greenland

Abstract

Growing season conditions are widely recognized as the main driver for tundra shrub radial growth, but the effects

of winter warming and snow remain an open question. Here, we present a more than 100 years long Betula nana

ring-width chronology from Disko Island in western Greenland that demonstrates a highly significant and positive

growth response to both summer and winter air temperatures during the past century. The importance of winter tem-

peratures for Betula nana growth is especially pronounced during the periods from 1910–1930 to 1990–2011 that were

dominated by significant winter warming. To explain the strong winter importance on growth, we assessed the

importance of different environmental factors using site-specific measurements from 1991 to 2011 of soil tempera-

tures, sea ice coverage, precipitation and snow depths. The results show a strong positive growth response to the

amount of thawing and growing degree-days as well as to winter and spring soil temperatures. In addition to these

direct effects, a strong negative growth response to sea ice extent was identified, indicating a possible link between

local sea ice conditions, local climate variations and Betula nana growth rates. Data also reveal a clear shift within the

last 20 years from a period with thick snow depths (1991–1996) and a positive effect on Betula nana radial growth, to

a period (1997–2011) with generally very shallow snow depths and no significant growth response towards snow.

During this period, winter and spring soil temperatures have increased significantly suggesting that the most recent

increase in Betula nana radial growth is primarily triggered by warmer winter and spring air temperatures causing

earlier snowmelt that allows the soils to drain and warm quicker. The presented results may help to explain the

recently observed ‘greening of the Arctic’ which may further accelerate in future years due to both direct and indirect

effects of winter warming.

Keywords: Arctic, Betula nana, dendrochronology, Greenland, shrub expansion, winter warming

Received 7 October 2014; revised version received 5 February 2015 and accepted 14 February 2015

Introduction

Air temperatures across the Arctic have increased

markedly during the past 20 years (IPCC, 2013). Predic-

tions of the future climate suggest that air temperatures

will continue to increase, not the least during the winter

season, leading to changes in snow depth and duration

of snow cover (Serreze et al., 2000; Serreze & Francis,

2006; IPCC, 2013). The recent warming has increased

productivity and triggered an overall greening of the

Arctic (Tape et al., 2006; Epstein et al., 2012; Henry

et al., 2012; Macias-Fauria et al., 2012), impacting the

surface energy balance (Sturm et al., 2005a,b), the

nutrient cycling and net carbon balance (Elmendorf

et al., 2012a,b). The conventional explanation for this

‘greening’ is improved growing season conditions, but

it has been pointed out that winter biological processes

also play crucial roles with negative as well as positive

effects on plant growth (Sturm et al., 2005a,b; Schmidt

et al., 2006; Hallinger et al., 2010). Positive effects on

shrubs growth have been described in snow fence

experiments and linked to increasing nutrient availabil-

ity due to enhanced decomposition during the warmer

snow-protected winter months (Nobrega & Grogan,

2007; Semenchuk et al., 2015). But so far the net effects

of winter conditions on annual radial growth of Arctic

shrubs are uncertain.

Betula nana (dwarf birch) is one of the circumpolar

Arctic shrubs that play a major role in the ‘greening of

the Arctic’ and for which growth has been shown to

react positively to both experimental summer warmingCorrespondence: Bo Elberling, tel. +45 35322520, fax +45 35322501,

e-mail: [email protected]

2410 © 2015 John Wiley & Sons Ltd

Global Change Biology (2015) 21, 2410–2423, doi: 10.1111/gcb.12913

and fertilization (Bret-Harte et al., 2001; Van Wijk et al.,

2003; Wahren et al., 2005), but so far not to winter

warming. Recent studies on foliar carbon cycling in

Betula nana growth under long-term warming and fertil-

ization treatments at Toolik Lake (Alaska) reveal as fol-

lows: (i) increased concentration of N and P in leaves;

(ii) near-complete dominance of Betula nana at commu-

nity scale; (iii) the highest (among studied species) rates

of photosynthesis; and (iv) increased carbon gain effi-

ciency (Heskel et al., 2013). This suggests a physiologi-

cal advantage of Betula nana, which under continuous

warming may lead to a possible dominance over other

tundra species and a resulting increase in carbon accu-

mulation (Bret-Harte et al., 2001; Deslippe & Simard,

2011; Deslippe et al., 2011; Henry et al., 2012).

Climate–growth response studies of the Arctic tundra

plants require long-term observations and homoge-

neous data sets from the nearby climatic stations. Few

Arctic sites have climate records that represent the past

100 years, but the record of air temperature observa-

tions from Ilulissat in western Greenland, starting in

1873, is among the few. The record correlates well with

air temperature observations in the region, including

1991–2004 observations from our study site Arctic Sta-

tion at Disko Island, 60 km west of Ilulissat (Hansen

et al., 2006). Changes and trends in this long tempera-

ture record have been analysed previously, and five

distinct trend periods have been identified (Putnins,

1970; Cappelen et al., 2001; Box, 2002): 1873–1895, 1896–

1909, 1910–1930, 1931–1960 and 1961–1990 (Fig. 1). The

most consistent period was 1910–1930 where the mean

winter temperature increased by 0.3 °C year�1 without

a corresponding summer warming.

Typically, the effects of winter warming on shrub

growth have been studied through primary growth or

experimental treatment studies (warming and/or fertil-

izing) which are very useful to assess plant responses

to climatic changes over short observational periods.

However, dendroclimatological analyses provide an

opportunity to link secondary growth of shrub with in-

terannual climate variability over longer timescales (i.e.

Forbes et al., 2010; Hallinger et al., 2010; Blok et al.,

2011; Jørgensen et al., 2014). This study investigates the

impact of winter conditions on the annual ring-width

growth (i.e. radial growth) of Betula nana at a high intra-

plant resolution and over a century-long scale. To do so

we: (i) investigate the climatic conditions in southern

Disko in western Greenland and evaluate recent cli-

matic trends (ii) develop a Betula nana ring-width chro-

nology for southern Disko in Western Greenland, (iii)

investigate climate–growth relationships for the last

century, especially focusing on the influence of winter

air temperatures on Betula nana radial growth and (iv)

investigate the importance of soil temperatures, sea ice

and snow depths on Betula nana radial growth during

the last two decades.

—20

—15

—10

—5

0

5

10

15

Air tem

pera

ture

(oC

)

1900 1925 1950 1975 2000 2025 2050 2075 1875

Gre

enla

nd

Fig. 1 Seasonal air temperatures from Arctic Station (Disko Island, western Greenland) combined from historical climate data (1873–

1992), recent observations (1991–2011) (shaded in grey) and regional climate model simulations (2012–2080). The historical data are

based on data from Ilulissat and the future predictions (shaded in blue) are derived from the Danish Meteorological Institute’s HIR-

HAM4 model downscaled for use in the Disko region. The scenario presented is based on a 2.4 °C warming over a 70-year period. Tem-

peratures are shown for the winter (blue), spring (yellow), summer (green) and autumn (red), and the five distinct temperature trend

periods that have been identified from 1873 to 1990 are separated with vertical dotted lines.

© 2015 John Wiley & Sons Ltd, Global Change Biology, 21, 2410–2423

WINTER WARMING AFFECTS ARCTIC SHRUB GROWTH 2411

Materials and methods

Study site

Arctic Station was established in 1906 by M.P Porsild near

the Greenlandic settlement Qeqertarsuaq on Disko in wes-

tern Greenland (69o150N, 53o310W) due to the high plant

diversity in the area (Fig. S1 ). The site is located in the erect

dwarf-shrub tundra zone (Walker et al., 2002) and is exposed

to an Arctic maritime climate. The area is dominated by a

low bench of bedrock (gneiss) and Tertiary breccia and pla-

teau lava. To the North, the terrain rises gently to 200 m

above sea level about 1.5 km from the coast. Further away

steep mountain slopes reach 600–800 m extending east and

west.

Meteorological data and sea ice observations

Arctic Stations meteorological station was established in

1990 about 300 m from the coast and 20 m above sea level

(m a.s.l). Measurements include wind speed, wind direction,

precipitation (rain), air temperatures and incoming and out-

going solar radiation. Ground temperatures are measured 5,

60 and 175 cm below the surface in Early Holocene marine

stratified sediments. All sensors are connected to an Aander-

aa datalogger programmed to log every 30 min. Annual val-

ues (1991–2004) have been reported by Hansen et al. (2006).

The meteorological station has experienced several short

breakdowns during its lifetime, and from July 2002 to June

2003, a long period of breakdown and unstable measure-

ments was experienced. Furthermore, precipitation measure-

ments are lacking 7 of the 21 observations years. Data from

a nearby meteorological station (1 km away) run by Asiaq

(available from: www.asiaq.gl) have been used to replace

minor data gaps using linear correlation analyses between

the two stations.

In addition to the automatic meteorological measurements,

measurements of snow depths and visual observations of sea

ice coverage to the South have been made by the different sta-

tion managers from 1991 and onward. The sea ice cover has

been grouped in intervals of ‘no ice’, 0–25%, 26–50%, 51–75%

and 76–100% (Hansen et al., 2006).

Climate record

Monthly mean temperatures from Arctic Station and the sta-

tion in Ilulissat (1992–2012) were used to calculate linear

regression equations between the two stations. The regres-

sion equations were subsequently used to calculate mean

monthly air temperatures for Arctic Station for the period

1873–1991. The climate record constructed in this study is a

continuation of the work made by Hansen et al. (2006) where

1991–2004 observations from Arctic Station were used to

reconstruct monthly air temperatures from 1873 to 1991. Fur-

thermore, modelled precipitation data from the NOAA

(1901–2010) were used to investigate the influence of varia-

tions in precipitation on Betula nana radial growth (Schneider

et al., 2011).

Dendrochronological survey

The dendrochronological survey followed the serial sectioning

approach proposed by Kolishchuk (1990), which consists of

repeated tree-ring width measurements and crossdating at in-

traplant level (Buchwal et al., 2013). Within 5 km from Arctic

Station, 15 intact Betula nana individuals were collected in

early August 2011 from a stable site that represented semi-

erect shrub tundra conditions. The sampling only considered

isolated, mature and healthy individuals to avoid competi-

tion-influenced plant structures. Although a confined number

of shrubs were taken from the field, each individual was care-

fully inspected and sectioning was performed for both below-

ground and above-ground plant segments (Fig. S2). In total,

135 cross sections were analysed from the main root and

below-ground shrub compartments (41% of sections) and

from stems and branches (59% of sections). The number of

cross sections taken per shrub depended on plant size and

morphology. On average, nine cross sections per individual

were inspected but with a variation from 1 to 19 cross sections

per shrub. Cross sections were collected along the main

growth axis, including main roots and up along the stem and

a maximum of two main branches. This approach ensured the

accuracy of the ring-width dating through detection of com-

monly formed partially (i.e. wedging rings) and completely

missing rings (Buchwal et al., 2013) and improved the com-

mon signal and correlation between individual growth series.

Thin sections of ~15–20 lm thick were obtained using the

GLS-1 sledge microtome, stained with a mixture of Safranin

and Astra blue, and permanently fixed on microslides with

Canada balsam (Schweingruber et al., 2011). Images were cap-

tured using a digital camera (CS30, Olympus) connected to a

microscope (Olympus BX41) under 40–100 magnification.

Images of a single cross section were merged in ADOBE

PHOTO SHOP CS2 (Adobe Systems Incorporated, San Jose,

CA, USA). Annual ring widths (RW) were measured using

manual path analyses mode in the WINCELL software (Regent

Instruments Inc, Quebec, Canada). Growth rings (i.e. ring

width) were measured within each cross section along two to

three radii. Altogether, detection of growth rings, missing and

partially missing rings was conducted along 294 radii. Radial

measurements along chosen radii were supplemented by care-

ful visual inspection of each cross section to eliminate annual

growth underestimation caused by partially missing rings,

that is incomplete growth rings formed due to failure of cam-

bial activity. The principal three stages of crossdating were

based on visual comparison of growth curves (i) between 2–3

radii measured within a single cross section, (ii) among the

mean growth curves of all the sections within individual

shrubs and finally (iii) between the mean growth curves of all

shrubs. Alignment of growth curves was based on comparison

of positive and negative pointer years (Schweingruber et al.,

1990). The output of visual crossdating was statistically

checked in COFECHA (Holmes, 1983).

Within all 135 cross sections, it was not possible to success-

fully crossdate eight cross sections, mostly showing growth

suppression in the above-ground shrub parts. Additionally, 11

sections were eliminated from the final data set because of

their low (i.e. <0.3) correlations with the master chronology.


2412 J . HOLLESEN et al.

http://www.asiaq.gl

The raw ring-width measurements were standardized to

remove a nonclimatic variance from the time series (Cook

et al., 1990). Although there were no evidences of an unequiv-

ocal age trend presence in the raw Betula nana chronology,

detrending was executed to account for (i) autocorrelation in

the annual growth series, (ii) competition effects and (iii) a

possible age trend (not visible in a raw series) superimposed

by the climatic signal, that is enhanced growth over time as a

result of a warming climate. Three methods of detrending of

Betula nana chronology were tested using the dplR package in

R (Bunn, 2008). Initially, a linear trend in the mean raw growth

series was removed by subtracting a least-squares-fit straight

line. Secondly, a cubic smoothing spline was used to fit and

remove a nonlinear trend, which was observed in our ring-

width chronology. Thirdly, a horizontal line was fitted to the

raw growth series. Each detrended chronology was tested in

the climate–growth relationship analyses to confirm the stabil-

ity of the temperature signal obtained while using the raw (i.e.

undetrended) series. Finally, the cubic smooth spline method

was determined to be the most flexible and representative

method for removing a possible trend in our growth rings

data and further to be used for a comparable climate–growth

relationship analyses. A relative flexible smooth spline func-

tion with 50% frequency response at 32 years was used to

remove low-frequency variability (i.e. any possible biological

effects) and act as a final standardized Betula nana ring-width

chronology in our study (Fig. 2).

The strength of the common signal of both detrended and

undetrended chronologies was quantified using the mean cor-

relation between the time series (Rbt) (Briffa & Jones, 1990)

and the expressed population signal (EPS) (Wigley et al.,

1984).

Climate–growth relationships

The exploration of climate–growth relationships for the Betula

nana chronology was conducted in three steps using three

complementary methods. First, the overall linear dependences

between the available climatic variables from the study area

and the Betula nana chronology were investigated. This was

carried out by computing Pearson’s correlation coefficients

between raw (i.e. undetrended) and detrended (i.e. standard-

ized) chronologies and monthly air temperatures (1910–2011)

and precipitation rates (1910–2010) including prior dormant

season (starting from previous November) and following year

conditions (from January to September). Additionally for air

temperature, two seasonal averages for winter (previous

December and current January) and summer (current June

and July) were used. The climate–growth relationship analy-

ses were performed for both a century-long period as well as

for five distinct climatic trend periods which have been identi-

fied previously (Putnins, 1970; Cappelen et al., 2001; Box,

2002). Also Pearson’s correlation coefficients were calculated

between detrended Betula nana chronologies and standardized

air temperature data for last century. Climate data were detr-

ended by fitting a 30-year smooth spline into a monthly aver-

age temperature records from Arctic Station. Subsequently,

linear correlations were made between the raw and the stan-

dardized Betula nana chronology and 1991–2011 soil tempera-

tures, snow depth, growing degree-days (GDD), thawing

degree-days (TDD) and sea ice cover. All climate–growth rela-

tionships were performed using R software. Secondly, boot-

strapped response coefficients (BRC) were calculated between

monthly climatic variables (including previous and current

growing season conditions) and the Betula nana chronology

(a)

(b)

Fig. 2 (a) Betula nana ring-width chronology (1888–2011) for southern Disko Island, western Greenland (red bold line) with fitted

smoothing spline (black line), individual ring-width series (grey lines) based on three-step crossdating of 15 shrubs and 116 cross sec-

tions. (b) Standardized Betula nana chronology (RWI – ring-width index) after fitting a 32-year smoothing spline. The sample depth

expresses a total number of cross section. Note the decreasing number of cross sections in the recent years due to the outermost rings

missing in some individuals, both in below- and above-ground shrub parts.



(raw series) to test the overall stability and significance of the

obtained summer and winter climate–growth relationships.

Finally, moving correlation functions (MCF) were used

between the Betula nana chronology (raw series) and air tem-

peratures (1910–2011) and precipitation rates (1910–2010) to

test the seasonal variation of the climatic signal reflected in the

Betula nana growth rings. The MCF were computed using a

30-year moving window, offset by 1 year, which produced a

temporal set of coefficients for each monthly predictor. The

analyses were conducted in R using the bootRes (Zang & Bi-

ondi, 2013) and treeclim package (Zang & Biondi, 2015). The

significance of the response (BRC) and correlation (MCF) coef-

ficients was calculated based on 1000 bootstrapped iterations,

obtained by random extraction with replacement from the ini-

tial data set (Guiot, 1991).

Results

Meteorological measurements and sea ice observations

The mean annual air temperature for the period 1991–

2011 was �3.0 °C � 1.8 °C (� 1 SD) (Fig. 3a). The

warmest month was July with a mean temperature of

7.9 °C � 1.6 °C, and the coldest month was March with

a mean of �14.0 °C � 5.0 °C. Air temperatures ranged

from an absolute maximum of 21.9 °C (June 23, 2003) to

a minimum of �32.9 °C (March 22, 1996). During the

observation period, the mean annual air temperature at

the station increased by 0.2 °C year�1 but with a strong

seasonal variation, as winter temperatures (Dec to Feb)

increased by 0.4 °C year�1, spring temperatures (March

to May) by 0.3 °C year�1, summer temperatures (June

to Aug) by 0.1 °C year�1 and autumn temperatures by

0.1 °C year�1 (Fig. 3a). When comparing the first

10 years (1991–2000) with the last 10 years (2002–2011),

the mean annual number of freezing degree-days

(FDD) decreased from 2240 to 1585 FDD and the num-

ber of thawing (TDD) and growing degree-days (GDD)

increased from 680 to 912 TDD and from 160 to 284

GDD (Fig. 3b).

The mean annual amount of rain measured from

1994 to 2006 was 273 mm � 100 mm (Fig. 3c), with

September (63 mm) being the wettest and March the

driest month (15 mm). At Arctic Station, ~60% of the

total precipitation has been estimated to fall as rain

(Hansen et al., 2006) and hence the mean annual

amount precipitation (rain and snow) is estimated to be

~400 mm. As precipitation data are lacking in part of

the observation period, it was not possible to report the

overall trends in precipitation from 1991 to 2011.

The soil was covered with snow from October to

May with an average snow cover of 16 cm (Fig. 4a).

There was a large year-to-year variation in both the tim-

ing of the snow cover and in the snow thickness and a

general trend towards a decrease in the maximum

snow depth in recent years (Fig. 4b). Furthermore,

there has been an increase in the duration of the snow-

free period (SFP) from 120 days the first 10 years

(1991–2000) to 145 days the last 10 years (2002–2011),

and the onset of the SFP overall has shifted from the

beginning of June to mid/early May (Fig. S3).

Temperature readings from the meteorological sta-

tion show average soil temperatures of �0.9, �0.4 and

�0.5 °C at depths 5, 60 and 175 cm, respectively (Fig.

S4a). Throughout the observation period, temperatures

above 0 °C were recorded at all depths confirming that

the active layer depth in the coarse marine stratified

sediments at Arctic Station is deeper than 175 cm. Soil

temperatures have been following the same increasing

trend as air temperatures both on an annual and

Year

Sum

of degre

es (

oC

) P

recip

itation (

mm

)

—25

—15

—5

5

15

—4000

—3000

—2000

—1000

0

1000

2000

0

100

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

200

300

400

500

(a)

(b)

(c)

Air tem

pera

ture

(oC

)

Fig. 3 (a) Mean annual air temperatures and seasonal tempera-

ture trends at Arctic Station (Disko Island, western Greenland)

from 1991 to 2011. Temperatures are shown for the whole year

(black), the winter (blue), spring (yellow), summer (green) and

autumn (red). (b) Freezing degree-days <0 °C (blue), thawing

degree-days >0 °C (red) and growing degree-days >5 °C (green)

at Arctic Station. (c) Annual precipitation rates measured near

Arctic Station.



seasonal scale (Fig. S4b). Correlation analyses show that

soil temperature in the upper part of the soil is posi-

tively related to air temperatures (Fig. S5) but not to

snow cover (Fig. S6). The results also show that winter

soil temperatures in recent years have become more

directly linked to air temperatures as a consequence of

the decreasing snow depths (Fig. S7). When comparing

the first 10 years (1991–2000) to the last 10 years (2002–

2011), it is also clear that winter and spring soil temper-

atures have become markedly warmer despite of less

snow (Fig. S8).

In average, a sea ice cover of more than 50% was

observed for 95 days each winter (1991–2011). The lon-

gest period with a sea ice cover below 50% was in 1993

with 167 days and the shortest in 2010 with 0 days.

From 1991 to 2011, the sea ice cover was roughly

reduced by 50% (Fig. 5) with a tendency of the sea ice

being formed later and disappearing earlier in the sea-

son. There was a negative correlation between winter

air temperatures (December–February) and sea ice

cover (r = �0.65, P < 0.05).

Climate record

Linear regression analyses between 1992 and 2011

monthly air temperatures from Arctic Station and Ilu-

lissat were highly significant (R2= 0.99) (Fig. S9). Based

on the regression, an 1873–2011 record of monthly air

temperatures was calculated for Arctic Station (Fig. 1).

The record shows that warming periods of 10–20 years

have been noted at least twice in the past 100 years –

from 1910 to 1930 and from 1991 to 2011, and for both

of these intervals, the greatest warming occurred dur-

ing the winter (>0.3 °C year�1).

Linear correlation analyses were made between mea-

sured and modelled precipitation data (Schneider et al.,

2011). Because the weather station at Arctic Station only

measures rain, this could only be performed for the

three summer months. The results showed that the

modelled values are within range of the measured val-

ues although not on a significant level (Figs S10 and

11). The limitation and complications associated with

using the modelled precipitation rates are considered

in the discussion.

Chronology characteristics and quality

After crossdating, ring-width chronologies (RW) for the

below-ground and above-ground parts were com-

pleted. Based on all 116 sections, a final Betula nana

chronology for Southern Disko was established for the

period 1888–2011 (Fig. 2). The chronology was charac-

terized by a high common signal represented by overall

mean interseries correlation of 0.59 (raw RW data) and

an average mean sensitivity of 0.47. The mean interser-

ies correlation calculated for the detrended chronology

was 0.42 and the expressed population signal (EPS),

which is a function of mean interseries correlation and

series replication, varied from 0.75 to 0.99

(mean = 0.97) (Fig. S12). Annual Betula nana radial

growth rates at the root collar base were in the order of

50–400 microns. Wedging rings were common, which

often corresponded to a missing ring in some part of

the same plant.

Temperature-controlled growth relationships

The three complementary climate–growth relationship

analyses all revealed summer and winter temperature

sensitivity of the Betula nana chronology during the

last century (Figs 6–8; Table S1). The highest positive

Pearson’s product–moment correlation coefficients for

the long time series (1910–2011) were found between

the raw Betula nana chronology and seasonal mean

temperatures of June and July (JunJul, r = 0.53,

P < 0.05) and previous December and current year

Ja

n

Fe

b

Ma

r

Ap

r

Ma

y

Ju

n

Ju

l

Au

g

Se

p

Oct

No

v

De

c

0

20

40

60

80

100

120

0

20

40

60

80

100

120

19

91

19

93

19

95

19

97

19

99

20

01

20

03

20

05

20

07

20

09

20

11

(b)(a)

Sn

ow

de

pth

s (

cm

)

Fig. 4 Snow depths measured at Arctic Station (Disko Island, western Greenland) for the period 1991–2011 (a) mean monthly snow

depths (line with error bars indicating � 1 SD) and (b) maximum yearly snow depth.



January (pDecJan, r = 0.42, P < 0.05). The highest sig-

nificant positive correlations between radial growth

and winter temperatures were seen for the periods

1910–1930 and 1991–2011 dominated by winter warm-

ing (Fig. 6; Fig S13; Table S1). For the period 1910–

1930, correlations between Betula nana growth and air

temperatures were 0.49 (P < 0.05) and 0.56 (P < 0.05)

for pDec and current January compared to 0.45

(P < 0.05) for June and 0.55 (P < 0.05) for July. The

winter signal was even stronger for the last 20 years

with r = 0.61 (P < 0.05) and 0.69 (P < 0.05) for pDec

and current January, respectively, and dominated over

the summer signal (0.44 (P < 0.05) for June and 0.36

(P < 0.1) for July). Pearson’s correlation coefficients

obtained for the standardized Betula nana chronology

confirmed the overall significant and positive relation-

ship with both summer (JunJul) and winter (pDecJan)

for the period 1910–2011 (Fig. 6). The result was

approved by comparing different detrending methods

(Fig. S14). The positive and significant correlation coef-

ficients for both summer and winter periods were con-

firmed also by computing climate–growth

relationships between raw and detrended Betula nana

chronology and detrended air temperatures for the

period 1910–2011 (Fig. S15). Furthermore, a compari-

son of climate–growth response of different shrub

parts revealed that the importance of winter air tem-

peratures was seen for both below-ground and above-

ground plant growth (Fig. S16).

The positive long-term correlation between Betula

nana radial growth and air temperature established by

Pearson’s correlation coefficients was further examined

by calculating bootstrapped response coefficients

(BRC). The results confirmed that both summer and

winter air temperatures had a significant controlling

influence on Betula nana growth over a last century

(Fig. 7a). The highest BRC were obtained for average

monthly air temperature of previous December

(r = 0.228, P < 0.05), current June and July (r = 0.209

and r = 0.205 respectively, P < 0.05).

The century-long variability of climate–growth rela-

tionship reflected in the Betula nana growth rings was

assessed by performing moving correlation functions

(MCF) between the Betula nana chronology (raw series)

and air temperatures (Fig. 8a). The MCF applied for the

whole study period (i.e. last 100 years) indicated a pre-

dominantly positive correlation with previous Decem-

ber, current January and February, particularly in the

periods 1912–1951 and 1970–2011 (except for February).

For summer temperatures, the signal was predomi-

nantly positive for current June and July (Fig. 8a) and

revealed moderate seasonal variability of the signifi-

cance levels over time. The MCF revealed that the posi-

tive correlation between shrub radial growth and

winter temperatures (previous December and current

January) within last two decades has become so pro-

nounced that it is prevailing over the summer signal.

This was not the case of early study period (i.e. 1912–

1950), where the summer signal (mainly July) domi-

nated over the winter signal although both correlation

coefficients were significant (P < 0.05). Additionally,

the MCF indicated an increasing importance of

spring temperatures (March and April) during the

recent period (Fig. 8a).

October November December January February March April May June

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

Sea ice

No observations 1 - 25% 26 - 50% 51 - 75% 76 - 100%

Fig. 5 Daily observations of per cent sea ice cover as observed from Arctic Station (Disko Island, western Greenland) from 1991 to

2011.



Precipitation and other climatic variables

Positive and significant correlations were also observed

when using other measures such as growing degree-

days (pDec r = 0.67 and Aug r = 0.47, P < 0.05) and

thawing degree-days (pDec r = 0.72 and Aug r = 0.46,

P < 0.05) (Fig. S17 a,b). Long time series do not exist for

soil temperatures, but for the last 20 years (1991–2011),

significant positive correlations with winter and spring

soil temperatures at 60 cm depth were noted (Fig. S17c;

Table S2). The highest positive correlation was found

between Betula nana growth and April and May soil

temperatures.

No correlation was found between Betula nana

growth and winter precipitation in the period 1910–

2011 (Fig. S18), whereas a negative correlation between

(a)

(b)

(c)

(d)

(e)

Fig. 6 Pearson’s correlation coefficients between Betula nana ring-width chronology (black = undetrended; grey = detrended) and

monthly air temperature, including two seasonal averages for winter (previous December and current January) and summer (current

June and July), derived from Arctic Station (Disko Island, western Greenland) for (a) 1910–2011, (b) 1910–1930, (c) 1931–1960, (d) 1961–

1990 and (e) 1991–2011. Significance levels (P < 0.05) are indicated by horizontal dashed lines.



July precipitation and Betula nana ring-width growth

was observed (r = �0.22, P < 0.05). Based on average

monthly precipitation, the BRC revealed a significant

negative correlation between current and previous July

precipitation (r = �0.215 and r = �0.172 respectively,

P < 0.05) and Betula nana radial growth for the century-

long period (Fig. 7b). Results of MCF revealed weaken-

ing of this signal within the last years, as well as indi-

cated an increasing positive importance of May

precipitation (Fig. 8b).

For the period 1991–2011, a negative but not signifi-

cant correlation between Betula nana radial growth and

average monthly snow depths was obtained for the

winter months as well as current April. (pDec-Feb

r = �0.41 and Apr r = �0.41, P < 0.06). A remarkable

shift in the amount of snow was noticed within the last

20 years from a period with thick snow depths (1991–

1996) and a positive effect on Betula nana radial growth

to a recent period (1997–2011) with very shallow snow

depth and no significant growth response towards

snow depths (Fig. S19).

The influence of sea ice on shrub growth for the last

20 years was assessed using measurements of sea ice

cover from Arctic Station (Fig. 5). The analysis

revealed a highly significant negative correlation

between winter and spring sea ice extent and Betula

nana radial growth, which was the highest for January

(r = �0.70, P < 0.001) and May (r = �0.62, P < 0.01)

(Fig. S20).

Discussion

Chronology quality

Although limited amount of very old Betula nana indi-

viduals were available at the study site, a detailed

serial sectioning and crossdating analyses at the shrub

level enabled the elaboration of a robust ring-width

chronology that was characterized by high common

signal. This is often hard to obtain dealing with shrub

species which often reproduce vegetatively and form

multiply branches and adventitious roots. Neverthe-

less, we found wedging and missing rings to be a com-

mon phenomenon in our Betula nana individuals.

Three of 15 shrubs were lacking from four to 23 annual

rings at the stem base and, respectively, in the root

part of the same individual. This phenomenon has

recently been described for Betula nana from Abisko

(Wilmking et al., 2012) and thus emphasizes the impor-

tance of using the serial sectioning method when deal-

ing with Betula nana radial growth measurements. This

study reveals that smaller amount of sampled material,

combined with a multistep intraplant crossdating,

allows better understanding of shrub annual growth

performance and significantly enhances dating quality.

From 1923 to 2011, the expressed population signal

(EPS) was above 0.85, which is generally considered as

the acceptable threshold for a reliable chronology (Wig-

ley et al., 1984), confirming the robustness of the chro-

nology. However, before 1923 (i.e. form 1910–1923), the

EPS varied between 0.75 and 0.85. We tested the reli-

ability of this early part of the chronology (i.e. repre-

sented by a minimum of three shrubs growth series) by

independently comparing climate–growth correlations

for the periods 1910–1930 and 1920–1930 and found

that both seasonal summer and winter signals were

indicated for both periods (Fig. S21 and Table S1).

The ring-width chronology for Betula nana was used

for climate–growth analyses for the period 1910–2011.

Application of bootstrapped resampling confirmed the

significance of the obtained response coefficients

between Betula nana shrubs growth and both summer

and winter temperatures over the last century. More-

over using MCF, it was possible to investigate changes

in the significance levels of shrub sensitivity to summer

guArpAnuJp

—0.2

—0.1

0.0

0.1

0.2

0.3

—0.3

—0.2

—0.1

0.0

0.1

0.2

0.3

(a)

(b)

Re

sp

on

se

co

eff

icie

nts

Re

sp

on

se

co

eff

icie

nts

pJul pAug

pSep pOct

pNovpDec

Jan Feb

Mar May Jun

Jul Sep

guArpAnuJp pJul

pAugpSep

pOct pNov

pDec Jan

Feb Mar May

JunJul Sep

Fig. 7 Bootstrapped response coefficients (BRC) between the

Betula nana chronology (raw series) from Disko Island and (a)

average monthly air temperatures for the period 1910–2011 and

(b) average monthly precipitation rates for the period 1910–2010

computed from previous June to current September. Previous

year months are given in lowercase letters and current year

ones in uppercase letters. Significant coefficients (P < 0.05) are

marked by dark grey bars, and the lines represent the 95% confi-

dence intervals.



and winter temperatures over time. This helped to

reveal a rather low-frequency variability of the winter

signal primarily associated with the periods dominated

by warm winters previously identified (i.e. 1910–1930

and after 1991), whereas sensitivity of Betula nana radial

growth to summer temperatures seemed to be more

stable over time.

Climate change and Betula nana radial growth

The Betula nana ring-width chronology was combined

with one of the longest temperature records available

in Greenland to investigate the effects of air tempera-

tures on its radial growth over a century-long time

scale. Overall, we found a strong correlation between

(a)

(b)

Fig. 8 Moving correlation functions (MCF) relating the Betula nana chronology (raw series) from Disko Island, western Greenland to

(a) average monthly air temperatures for the period (1910–2011) and (b) average monthly precipitation rates (from previous November

to current September). The moving correlation was computed using a 30-year moving window, offset by 1 year. Significant correlations

(P < 0.05) are marked by asterisks.



Betula nana radial growth and winter temperatures as

well as summer temperatures. This relationship was

indicated for both below-ground and above-ground

shrub radial growth (Fig. S16) as was well confirmed in

all of the three different time series detrending methods

applied (Fig. S14 and S15). Comprehensive and thor-

oughly tested climate–growth relationship analyses

revealed that during the last century Betula nana radial

growth has primarily been driven by temperatures dur-

ing summer (June and July) and prior winter (previous

December) (Fig. 6–8). These results are in contrast to a

Betula nana study from north-eastern Siberia, which

revealed only a significant correlation between growth

and early summer air temperatures (Blok et al., 2011).

In addition to winter air temperatures, we also found

significant and positive correlations between Betula

nana radial growth with respect to both growing

degree-days (GDD) and thawing degree-days (TDD)

(Fig. S17 a,b).

The meteorological measurements from Arctic Sta-

tion show, as expected, a strong correlation between air

temperatures and soil temperatures with a tendency of

mild winters increasing winter and spring soil tempera-

tures (Fig. S5). Results reveal a significant negative cor-

relation between air temperatures and sea ice which

highlights a possible linkage between mild winters and

less sea ice or vice versa (Bhatt et al., 2010). Further-

more, we found a highly significant negative correla-

tion between sea ice extent and plant growth (r = �0.70

for January) (Fig. S20). This indicates a possible link

between warm winters, that is, expressed in the lack of

sea ice with an increased Betula nana growth on a local

scale which is in good agreement with investigations

by Bhatt et al. (2010), showing a linkage between sea ice

concentrations and tundra productivity in the High

Arctic. Recently, late-spring tundra productivity (i.e.

alder and willow) and temperatures were also found to

be largely linked to declining sea ice extent adjacent to

north-western Eurasian tundra (Macias-Fauria et al.,

2012).

Betula nana is considered as an early flowering spe-

cies (Molau et al., 2005) for which growth depends

much on early summer thermal conditions, which was

confirmed in this study by a significant correlation with

June air temperatures (Figs 6 and 7) and spring soil

temperatures (Fig. S17c). Mild winters may thereby

have a direct positive effect on Betula nana growth. The

current understanding of winter conditions positively

affecting growth is closely linked to the snow cover

reducing the chances for frost damage, warming up the

soil, and thereby increasing the mineralization and

release of nutrients (Schimel et al., 2004; Inouye, 2008;

Morgner et al., 2010). Over the whole period from 1991

to 2011, we found a weak negative correlation between

growth and the snow depths measured at Arctic Station

for the winter months as well as for April (Fig. S19).

However, our data showed a clear shift within the per-

iod 1991–2011 from a period with thick snow depths

(1991–1996) having a positive effect on Betula nana

radial growth, to a period with very shallow snow

depths (1997–2011) and no significant growth response

towards snow (Fig. S19). At Arctic Station, both snow

depths and the duration of the snow cover have

decreased markedly over the last 20 years and the

results suggest that snow depths are getting too small

to effectively decouple the soil thermal regime from air

temperatures (Fig. S7). Nevertheless, winter and spring

soil temperatures have been increasing significantly

(Fig. S8) which suggests that the recent increase in Betu-

la nana growth is not directly controlled by snow but is

rather a direct effect of warmer winter and spring air

temperatures causing the snow to melt earlier and

allowing the soil to drain and warm faster. Further-

more, it seems that the negative effects linked with

early snowmelt, such as frost damage, are overcome by

positive effects, such as increased growing season

length and greater amount of growing degree-days,

which previously has been shown to enhance Arctic

shrub growth in snow manipulation studies (Wipf

et al., 2006).

No snow data exist for the study area before 1991,

and hence, it is not possible to get a 100 year perspec-

tive on the effect of site-specific snow conditions on

Betula nana growth. Instead, modelled precipitation

data from 1910 to 2010 were used showing a significant

negative correlation between July precipitation and

Betula nana ring-width growth but no correlation with

winter precipitation (Fig. 7b; 8b; S18). This does not

necessarily exclude an effect on winter precipitation on

shrub growth on a local scale. It is well known that

snow–shrub growth relations are highly heterogeneous

and complex (Sturm et al., 2001, 2005a,b; Liston et al.,

2002; Wipf & Rixen, 2010; Rumpf et al., 2014) and often

limited by inaccurate snow cover measurements over a

vast and diverse shrub cover. Using modelled regional

precipitation data to represent site-specific condition is

difficult, especially in Arctic areas where local precipi-

tation patterns, wind, topography and aspect, as well

as density of shrub cover may have a great influence on

snow depths.

An indirect effect of warmer winters positively

linked with Betula nana growth might be associated

with soil nutrient availability. Milder winters (i.e.

warmer and characterized by lower snow depths and

earlier onset of the snowmelt) might largely contrib-

ute to higher nutrient availability for shrub growth,

including nitrogen availability resulting from both

higher biogeochemical cycle and litter decomposition



in the warmer dormant season. Numerous studies on

shrub growth responses to elevated temperature

(mainly through open-top chambers, OTCs) or nutri-

ent availability have revealed a significant increase in

deciduous shrub growth resulting from both higher

dormant and growing season temperature (Henry &

Molau, 1997; Elmendorf et al., 2012a). Particularly, Be-

tula nana growth has been shown to be highly pro-

moted by nutrient addition (Chapin et al., 1995;

Shaver et al., 2001; Bret-Harte et al., 2008). These com-

monly conducted primary growth studies on tundra

shrubs revealed the importance of winter conditions

on tundra plant performance (Wipf & Rixen, 2010;

Rayback et al., 2011).

Implications and conclusions

Compared to previous investigations, this study

shows a strong winter relationship with secondary

growth at a unique high resolution over more than

100 years including both below-ground and above-

ground shrub parts. Thus, the developed ring-width

chronology provides a unique retrospective view of

more than 100 years of Betula nana growth in western

Greenland and shows that both summer and winter

conditions have had strong positive effect on radial

growth during the warming periods of the last cen-

tury. Hence, our results strongly suggest that not only

summer but also winter biological processes play a

crucial role in the current ‘greening’ of the Arctic tun-

dra and that the Betula nana increase in growth may

continue if the current winter warming in the region

continue as predicted by climate models (Elberling

et al., 2010) (Fig. 1).

Warm winters may have an indirect effect on temper-

atures of the following summer making it difficult to

differentiate between summer and winter effects. There

was no correlation revealed between winter air temper-

atures and the following summer temperatures in the

study area for the period 1991–2011, whereas winter

temperatures correlated significantly with summer

temperatures for the period 1910–1930 (Fig. S22 & Table

S3). This correlation indicates that the importance of

winter conditions for plant growth may be overlooked

in periods that are characterized by warmer winters fol-

lowed by a warmer summer.

The obtained ‘winter dependence’ between Betula

nana ring-width growth and temperature cannot be

treated as a direct growth trigger but rather as a sign of

a complex relationship in the tundra ecosystem and

shrubs growing under recent Arctic climate shift associ-

ated in many sites with warmer and shorter winters

(Cooper, 2014). Future investigations are needed as fol-

lows: (i) to verify if the observations for Betula nana are

valid for other tundra plant species, as well as Betula

species from other locations (ii) to quantify the combi-

nation of biogeochemical processes which can explain

the positive effect of warmer winters and its positive

feedbacks for shrub growth.

We conclude that winter processes are as important

as summer processes in controlling the Betula nana

radial growth. This includes a positive growth

response to winter air temperatures during the past

century, especially during the periods from 1910–1930

to 1990–2011 that were dominated by significant win-

ter warming. For the last two decades, we found a

strong positive growth response to the amount of

thawing and growing degree-days as well as towards

winter and spring soil temperatures. In addition, we

found a strong negative growth response to the sea ice

extent indicating a possible link between warm win-

ters, lack of sea ice and increased Betula nana growth.

Snow depths have been decreasing markedly from

1990 to 2011 lowering the insulating effect of the snow

pack and causing winter and spring soil temperatures

to be closer related to air temperatures. Despite of this,

both winter and spring soil temperatures have been

increasing significantly during this period and there-

fore, the recent increase in Betula nana growth seems

to be triggered directly by warmer winter and spring

air temperatures. As far as we know, this study pro-

vides the most robust documentation for that winter

processes on a century-long time scale are as impor-

tant as summer processes in controlling and enhancing

the overall, that is, below- and above-ground radial

growth pattern of one of the dominating shrub species

in the Arctic.

Acknowledgements

We gratefully acknowledge financial support from the DanishNational Research Foundation (CENPERM DNRF100) as well assupport from the European Union Seventh Framework Pro-gramme [FP7/2007–2013] under grant agreement no 262693[INTERACT]. Thanks are extended to ASIAQ for providing cli-matic data and to the staff at Arctic Station for taking dailyobservations and providing assistance: O. Frimer, M. Rasch, P.Funch, S. Bernstein, C. Schander, B.J. Graae, R. Ejrnæs, H. Suls-br€uck and O.M. Tervo, as well as technical assistance by U. Tho-mas. Finally, we would like to thank reviewers’ for very helpfuland constructive suggestions.

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Supporting Information

Additional Supporting Information may be found in the online version of this article:

Figure S1. Location of the Arctic Station 2 km east of Qeqertarsuaq at Disko Island in western Greenland.Figure S2. An example of serial sectioning of Betula nana individual collected near Arctic Station on Disko Island.Figure S3. Duration (A) and onset (B) of the snow free period (SFP) at Arctic Station.Figure S4. (A) mean annual soil temperatures at 0.05 m (black), 0.60 m (blue) and 1.70 m (grey) at Arctic Station.Figure S5. Correlation between seasonal air temperatures and soil temperatures at Arctic Station.Figure S6. Correlation between seasonal air temperatures and soil temperatures at Arctic Station.Figure S7. The upper red line shows a 14 days running average of the soil temperature.Figure S8. Soil temperatures (A) and snow depts (B) measured at Arctic Station.Figure S9. (A) correlation between monthly air temperatures measured at Arctic Station.Figure S10. Annual precipitation rates for the period 1901-2010 derived from the NOAA precipitation model.Figure S11. Correlation between monthly precipitation rates from 1991-2010.Figure S12. (A) Betula nana ring-width chronology for southern Disko Island (western Greenland).Figure S13. Betula nana ring-width chronology for southern Disko Island (western Greenland).Figure S14. Pearson’s correlation coefficients between raw (black bars) and standardized (grey bars) Betula nana chronologies.Figure S15. Pearson’s correlation coefficients between standardized Betula nana chronologies.Figure S16. Correlation between Betula nana ring-width (1910–2011).Figure S17. Pearson’s correlation coefficients between Betula nana ring-width chronology for Arctic Station (Disko Island, westernGreenland).Figure S18. Pearson’s correlation coefficients between Betula nana ring-width chronology for Arctic Station (Disko Island, westernGreenland).Figure S19. Correlations between Betula nana ring-width chronology for southern Disko Island.Figure S20. Pearson’s correlation coefficients between Betula nana tree-ring width chronology.Figure S21. Pearson’s correlation coefficients between Betula nana ring-width chronology.Figure S22. Relationships between mean monthly air temperatures for previous December and current January and current Juneand July derived from Arctic Station.Table S1. Significance (P-values) resulting from Pearson’s correlations between Betula nana ring-width chronology and meanmonthly air temperatures for Arctic Station.Table S2. Significance (P-values) resulting from correlations between Betula nana ring-width chronology and mean monthly soiltemperatures (°C) for Arctic Station.Table S3. Correlation coefficients and significance (P-values) resulting from correlations between curremt June and July.



http://dx.doi.org/10.1111/ecog.01335

winter warming as an important co-driver for betula nana growth in western greenland during the...

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