Winter greenhouse gas fluxes

19 Pages·2013·7.01 MB·English

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Biogeosciences,10,3185–3203,2013 O O
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www.biogeosciences.net/10/3185/2013/ e Biogeosciencese
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doi:10.5194/bg-10-3185-2013 Biogeosciences A A
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©Author(s)2013. CCAttribution3.0License. e e
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p Climate p
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A of the Past A
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Winter greenhouse gas fluxes (CO , CH and N O) from a subalpine
2 4 2
O O
grassland p Earth System p
Earth System e e
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A Dynamics A
Dynamicsc c
L.Merbold1,C.Steinlin2,andF.Hagedorn3 ce ce
s Discussionss
s s
1ETHZurich,DepartmentofEnvironmentalSystemsScience,InstituteofAgriculturalSciences,GrasslandSciencesGroup,
Universita¨tsstrasse2,8092Zurich,Switzerland
Geoscientific Geoscientific
2ETHZurich,DepartmentofChemistryandAppliedBiosciences,InstituteforChemicalandBioengineering, O O
p p
SafetyandEnvironmentalTechnologyGroup,Wolfgang-Pauli-Strasse10,8093Zurich,SIwnistzterrulamndentation en Instrumentation en
3SwissFederalInstituteforForest,SnowandLandscapeResearch(WSL),Zuercherstrasse11M1,e8t9h0o3dBsir maenndsdo Acrf, Methods and Ac
c c
Switzerland Data Systemsess Data Systemsess
Correspondenceto:L.Merbold([email protected]),C.Steinlin([email protected]) Discussions
O GeoscientificO
Received:16November2012–PublishedinBiogeosciencesDiscuss.:8January2013 p p
Geoscientifice e
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Revised:15April2013–Accepted:17April2013–Published:13May2013 A Model Development A
Model Developmentcc cc
e e
s Discussionss
s s
Abstract. Although greenhouse gas emissions during 550±540gCO m−2 estimatedbytheeddycovarianceap-
2
winter contribute significantly to annual balances, their proach and 543±247gCO m−2, −0.4±0.01gCH m−2
quantification is still highly uncertain in snow-covered and0.11±0.1gN OmH−2ydde2rrivoeldobgyyth eagnraddi eOpnttechn4ique. Hydrology and Op
2 e e
ecosystems. Here, carbon dioxide (CO2), methane (CH4) TotalseasonalgreenhousEegaarstehm iSssyiosnstefrmomn Athegrassland Earth Systemn A
andnitrousoxide(N2O)fluxesweremeasuredatasubalpine were between 574±276 andSc58ie1n±c5e69sgcceCO2eq.m−2, Sciencescce
managed grassland in Switzerland using concentration with N2O contributing 5% to the overall budssget and CH4 ss
gradients within the snowpack (CO , CH , N O) and reducing the budget by 0.1%. Cumulative budgets of CO Discussions
2 4 2 2
the eddy covariance method (CO ) during the winter were smaller than emissions reported for other subalpine
2 O O
2010/2011.Ourobjectiveswere(1)toidentifythetemporal meadows in the Swiss Alps and the RockypeMountains. Ocean Sciencepe
n n
and spatial variation of greenhouse gases (GHGs) and Further investigationsOoncteheaGnH SGceixechnacngee Aof grasslands A
their drivers, and (2) to estimate the GHG budget of the in winter are needed in order to (1) deepencceour currently Discussions cce
s s
site during this specific season (1 December–31 March, limited knowledge on the environmental drisvers of each s
121 days). Mean winter fluxes (December–March) based GHG, (2) to thoroughly constrain annual balances, and (3)
on the gradient method were 0.77±0.54µmolm−2s−1 to project possible changes in GHG flux maOgnitude with O
for CO2 (1.19±1.05µmolm−2s−1 measured by eddy expectedshorterandwarmerwinterperiods. pen Solid Earthpen
covariance), −0.14±0.09nmolm−2s−1 for CH and Solid Earth A A
0.23±0.23nmolm−2s−1 for N2O, respectively. In4 com- cces Discussions cces
parison with the CO fluxes measured by eddy covariance, s s
2
thegradienttechniqueunderestimatedtheeffluxesby50%. 1 Introduction
While CO and CH fluxes decreased with the progressing O O
2 4 p p
winterseason,N2Ofluxesdidnotfollowaseasonalpattern. Identifying the sources and sinks of greenenhouse gases The Cryosphereen
The major variables correlating with the fluxes of CO2 and (GHGs) in terrestrialTehcoesy Cstermysohsaspbheecormee Accan important Discussions Acc
CH weresoiltemperatureandsnowwaterequivalent,which globalresearchfocus.MeasurementnetworksseuchasGHG- e
4 s s
s s
isbasedonsnowheightandsnowdensity.N Ofluxeswere EuropeorFLUXNETdeliverfundamentaldatatoinvestigate
2
onlyexplainedpoorlybyanyofthemeasuredenvironmental biogeochemical processes at the ecosystem scale (Aubinet
variables. Spatial variability across the valley floor was et al., 2000; Baldocchi et al., 2001). Much of the research
smallest for CO and largest for N O. During the winter to date has focused on the biosphere–atmosphere exchange
2 2
season 2010/2011, greenhouse gas fluxes ranged between ofcarbondioxide(CO2)andmorerecentlyalsoonmethane
(CH ) and nitrous oxide (N O) in most of the major global
4 2
PublishedbyCopernicusPublicationsonbehalfoftheEuropeanGeosciencesUnion.
3186 L.Merboldetal.: Wintergreenhousegasfluxesfromasubalpinegrassland
ecosystem types, including arctic ecosystems (Lohila et al., al.,2007).CH fluxesarecharacterizedbytwoantagonistic
4
2007; Schulze et al., 2010). In comparison, less focus has processes, methanogenesis and methanotrophy, both occur-
beenpaidtosubalpineoralpinegrasslands(Gilmanovetal., ringyearround(Bowdenetal.,1998;Nykanenetal.,2003;
2007; Soussana et al., 2007; Ammann et al., 2007), partic- PanikovandDedysh,2000;Zhuangetal.,2004;Zimovetal.,
ularly during winter (Brooks et al., 1997; Gilmanov et al., 1993)andareprimarilydependentontheaerobic/anaerobic
2004; Filippa et al., 2009; Liptzin et al., 2009; Merbold et conditionsofsoilsaswellasbiologicalfactorssuchasveg-
al.,2012).Forthefullgreenhousegasbalanceofecosystems, etationtype(LeMerandRoger,2001).Considerablecontri-
CH andN Ohavetobeincluded,whichmayoffsetpossi- butionsofCH fluxestoannualtracegasbalanceshavebeen
4 2 4
ble annual carbon sink capacities of terrestrial ecosystems shown for several “hot-spot” ecosystems such as wetlands
(Nykanen et al., 1995; Zimov et al., 1996, 1993; Sommer- and peatlands (Merbold et al., 2009; Corradi et al., 2005;
feldetal.,1996;Dise,1992;Bubieretal.,2002;Chenetal., Alm et al., 2007; Dise, 1992; Huang et al., 1997; Kroon et
2011a; Merbold et al., 2012; Oechel et al., 1997; Groffman al.,2010),whereasknownCH sinkscontributedonlylittle
4
et al., 2006; Schurmann et al., 2002; Yashiro et al., 2006; toannualGHGbalances(Chenetal.,2011a;Blankinshipet
Filippaetal.,2009).Globally,ricepaddies,wetlandsandru- al.,2008;Hartmannetal.,2011).
minant husbandry are the major CH sources. In contrast, EmissionsofN Oaremoredifficulttopredictduetothe
4 2
grassland soils and agricultural ecosystems are often con- limited understanding and interaction of the potential mi-
sidered as CH sinks (Blankinship et al., 2010; Chen et al., crobial source processes – nitrification, denitrification and
4
2011a;Dijkstraetal.,2011;Katoetal.,2011;Lietal.,2012; nitrifier denitrification (Brumme et al., 1999; Firestone and
Stiehl-Braunetal.,2011;Wuetal.,2010),whileagricultur- Davidson, 1989) – with an even more substantial lack of
allymanagedsoils,similartosoilsundernaturalvegetation, knowledgeregardingwinterprocesses.N Oemissionsfrom
2
areknownasconsiderableN Osources(Snyderetal.,2009; deeplyfrozensoilshavebeenfoundtomakeamajorcontri-
2
StehfestandBouwman,2006). butiontoannualfluxestimates(Wolfetal.,2010).Therea-
Complex processes drive the emissions of the three most son for the high N O fluxes is most likely suppressed con-
2
important greenhouse gases – CO , CH and N O – but sumption in the soil, rather than enhanced N O production
2 4, 2 2
a profound understanding of such processes exists only for (Goldbergetal.,2010).ForafenintheNetherlands,Kroon
CO .Forexample,theexchangeofCO betweentheecosys- etal.(2010)showedacontributionofwinterN Oemissions
2 2 2
temandtheatmosphereduringthegrowingseason–namely of up to 465% to the annual trace gas balances, while in
photosynthesis and respiration – is driven by light, water nineEuropeangrasslandsN Oemissionsduringwintercon-
2
availabilityandtemperature.However,thedominantprocess tributedtolessthan6%toannualbalances(Soussanaetal.,
during the dormant and often snow-covered periods, respi- 2007).
ration,islargelydrivenbysoiltemperature.Duetofreezing Measurement of GHG fluxes in winter is a logistical and
at the soil surface, soil-respired CO often originated from methodological challenge as many snow-covered sites have
2
deeper soil layers, while snow density and friction velocity pooraccessinwinterandcoldtemperaturesprovidedifficult
above the snow control the CO exchange with the atmo- workingconditionsforbothhumansandequipment.Primar-
2
sphere (Liptzin et al., 2009; Merbold et al., 2012; Lohila ily, there are four experimental approaches – surface cham-
et al., 2007; Mariko et al., 2000). Worldwide, only about bers,snowpackconcentrationgradientmeasurements(GM),
25 case studies have been conducted on winter respiration isotopictracersandeddycovariance(EC).Thecomparabil-
inhigh-latitudeand-altitudesystems(reviewedbyLiptzinet ityofthemethodsiscontroversialsinceeachmethodcovers
al.,2009inarecentspecialissueonwinterprocessesinBio- different spatial and temporal scales. Therefore, annual es-
geochemistry)withonlytwoofthemconductedintheAlps timates of winter GHG fluxes are often variable as a result
(Schindlbacher et al., 2007; Merbold et al. 2012). There is ofthemethodused(McDowelletal.,2000;Bjo¨rkmanetal.,
also only one single study that explicitly measured the spa- 2010a).Thegradientmethodhasbeendocumentedtounder-
tial variability of soil CO effluxes for different ecosystem estimate fluxes compared to the EC method (Suzuki et al.,
2
types during winter in Arctic Alaska (Jones et al., 1999). 2006) as well as compared to the chamber method (Mariko
CasestudiesshowedthatsoilCO effluxrangedbetween0.7 etal.,2000).Incontrast,Schindlbacheretal.(2007)observed
2
and770gCO -Cm−2duringthelongsnow-coveredseason, thatthechambermethodunderestimatedCO fluxesrelative
2 2
which corresponded to 10 to 40% of the annual effluxes in to the gradient method, and McDowell et al. (2000) found
arcticandsubalpineecosystems(Winstonetal.,1997;Clein nodifferencebetweenthechamberandthegradientmethod
andSchimel,1995;MellohandCrill,1996;Nykanenetal., atthreesitesintheRockyMountains.Tocompletethiscon-
1995; Aurela et al., 2002; Fahnestock et al., 1999; Jones et tradictory discussion, Lohila et al. (2007) measured signif-
al.,1999;Bjo¨rkmanetal.,2010b). icantly lower CO emissions rates by the eddy covariance
2
DrivingfactorsofCH andN Oemissionsaremuchless methodthanbythechambers.
4 2
understood than for CO , and detailed process knowledge Up to date only a few studies (<10) on subalpine grass-
2
remains sparse (Flechard et al., 2005; Kato et al., 2011; lands have investigated the exchange of the other green-
Kroon et al., 2010; Neftel et al., 2000, 2007; Soussana et house gases (CH and N O) during periods of snow-cover
4 2
Biogeosciences,10,3185–3203,2013 www.biogeosciences.net/10/3185/2013/
L.Merboldetal.: Wintergreenhousegasfluxesfromasubalpinegrassland 3187
Table1.Monthlymeansofthebasicmeteorologicalvariablesbe-
tweenNovember2010andApril2011.Thesoiltemperaturesensor a
wasinstalledat3cmdepth.
Zurich
Nov Dec Jan Feb Mar Apr
Meanairtemp.(◦C) −1.8 −7.3 −6.2 −3.7 −0.8 4.6
Meansoiltemp.(◦C) 1.4 0.2 −0.1 −0.3 −0.3 5.5
Meansnowheight(cm) 15 38 46 52 43 8
Monthlysnowfall(cm) 52 46 30 16 2 0
(Gilmanov et al., 2004; Liptzin et al., 2009; Lohila et al.,
2007; Wang et al., 2010; Schurmann et al., 2002; Filippa
et al., 2009); therefore, in this study we quantified all three
b
GHG fluxes from a subalpine grassland during winter in
Switzerland.Ourspecificobjectiveswere(i)tocomparedif-
ferent approaches for measuring GHG emissions; the in-
stantaneousgradientmethod,permanentautomaticallymon-
itoredgradientsandeddycovariance,(ii)toidentifythevari-
ables driving GHG emissions from the grassland and (iii)
placing the grassland CO fluxes in context with the sur-
2
rounding ecosystems, and (iv) to estimate the cumulative
emissions of CO , CH and N O from the ecosystem dur-
2 4 2
ingthesnow-coveredseason.
2 Materialandmethods
0 204060m
2.1 Studysite
c
Thegrasslandsiterepresentsatypicalmanagedhigh-altitude
grassland ecosystem in the Swiss Alps and is located in
the Dischma Valley near Davos, Canton of Graubu¨nden,
(46◦470N,9◦520E,1590ma.s.l.,Fig.1a)withconvenientac- 5 strea
stcaaneclstoesawrinibzniceluoidatvylebprayrnetydcapippicmiotawaeltleaiyornnlaaavisnnatsniDlua1aab5vli5loitsteydmaamiypnsoewru(aBnitntuestrneetiros.too1Dfn0a,2v221o.89sm◦9imC7s),yc.rhaT−ano1rd--, 2 1 B A 4 3 cross-country ski tmra c(Dkischmabach)
with maximum values recorded during the summer months
(July–September, MeteoSchweiz, 2011). During the winter
season 2010/2011, mean monthly air temperatures ranged E M
from−7.3◦CinDecemberto4.6◦CinApril.Snowcovered 10m
thesitefrom16Novemberuntilthe5April(Table1).
Fig.1.(a)and(b):locationoftheresearchsiteintheDischmaVal-
The vegetation at the grassland site consists of a species
leysouthofDavos,GR,Switzerland(copyrightwww.geo.admin.ch,
mixture of ryegrass (Lolium sp.), meadow foxtail (Alopecu-
swiss federal authorities, 2007, http://www.disclaimer.admin.ch/
rus pratensis), dandelion (Taraxacum officinale), white
terms and conditions.html).Panelbfurthershowsthefootprintcal-
clover (Trifolium repens) and buttercup (Ranunculus sp.).
culatedafterKljunetal.(2004)fortheeddycovariancetowerand
The subalpine grassland studied is considered moderately the transects (red dashed lines) of the spatial GHG flux measure-
managed with grazing of cattle in spring and two harvest ment campaign. (c) visualizes a scheme of the sampling setup in
eventsforfodderproductionduringsummer,eachbeingfol- the field. “M” is the location of the meteorological tower run by
lowedbymanureapplications.SoilsareacidicwithpHval- theSwissFederalInstituteforSnowandAvalancheResearchand
ues(CaCl )of4.1–4.6,havesoilorganiccarboncontentsof “E”referstothelocationoftheeddycovariancetowerandtheau-
2
8±1%intheuppermost5cmandcontain65–70%sandand tomaticprofilesamplingunits.Profiles1–5wereusedformanual
measurement,whereasAandBwereautomaticgradientmeasure-
10%clay.Thesurroundingecosystemsareaslopinggrass-
ments.Thedashedlinesarewalkingtrackstoapproachtheprofiles.
land,forestandafilledground.Foramoredetailedexplana-
(b)Reproducedwithpermissionofswisstopo(JA100120).
tionofthesiteseeSteinlin(2011)andMohnetal.(2013).
www.biogeosciences.net/10/3185/2013/ Biogeosciences,10,3185–3203,2013
3188 L.Merboldetal.: Wintergreenhousegasfluxesfromasubalpinegrassland
2.2 Greenhousegasfluxmeasurements ingofCO concentrationswereinstallednorthoftheECand
2
meteorologicaltowers(Fig.1c).
Gas flux measurements of CO2, CH4 and N2O were under- The gradient method is based on measured concentration
takenfromearlyDecember2010untilthebeginningofApril gradients and the diffusivity of gases across the snowpack
2011,coveringmostofthesnow-coveredperiodintheDis- (Hubbardetal.,2005).Thisapproachreliesontheassump-
chmaValley.Twodifferenttechniques–eddycovarianceand tion that the gas production is continuous, limited to the
manual gradient measurements – were used to derive inde- soil and that the gas does not bind or react with snow. We
pendentGHGfluxestimates.Inaddition,wetestedaperma- usedaone-dimensionalsteady-statediffusionmodel(Fick’s
nentautomaticmonitoringofCO2gradients. law of diffusion) for calculating GHG fluxes through the
An eddy covariance (EC) tower was set up at the end of snow(Eq.2),
November 2010 in the center of the grassland ecosystem
d
in the Dischma Valley (Fig. 1). The dominant wind direc- J =−D c, (2)
tionswereNWandSE,followingtheorientationoftheDis- dz
chma Valley. The EC tower approach was used for contin-
where J is the flux rate (µmolCO m−2s−1;
uous measurements of the turbulent fluxes of CO , water 2
2 nmolCH m2s−1 and nmolN Om2s−1) and D the
vapor, sensible heat and momentum (Aubinet et al., 2000; 4 2
diffusion coefficient of each GHG in the snow (m2s−1).
Baldocchi,2003).Measurementheightwas1.5mabovethe
The concentration gradient d /d is the slope of the linear
snowpackwithregularadjustmentsfollowingsnowaccumu- c z
regression between the single concentration measurements
lation.Athree-dimensionalultrasonicanemometer(CSAT3,
in each profile (µmolm−4). D is estimated from porosity
CampbellScientific,Logan,USA)wasinstalledtomeasure
(f) and tortuosity (τ) of the medium and the diffusion
wind velocity, wind direction and temperature fluctuations.
coefficient in air (D , Eq. 3). diffusion) for calculating
CO andwatervaporconcentrationsweremeasuredwithan air
2
GHGfluxesthroughthesnow(Eq.2),
open-pathinfraredgasanalyzer(LI-7500,LI-CORInc.,Lin-
coln,Nebraska,USA)andboththeanemometerandgasan-
D=f ×τ×D (3)
air
alyzersampledataresolutionof20Hz.
DataprocessingfollowedCarboEuropestandards(Papale D has a value of 0.138×10−4m2s−1 for CO ,
air 2
etal.,2006;Mauderetal.,2008).Theverticalturbulentflux 0.195×10−4m2s−1 for CH and 0.144×10−4 m2s−1 for
4
(F) was calculated from the covariance of the fluctuations N O (Massman, 1998). Porosity (f) and tortuosity (τ) are
2
(30minaverages)oftheverticalwindvelocityandtheCO2 derivedfromsnowdensityfollowingEqs.(4)and(5),
concentration(c,µmol)(Eq.1)
ρ
f =1− , (4)
F =w0c0, (1) ρice
CO2
whereρ isthemeandensityofthesnowlayerandρ isthe
where the overbar denotes time averages. c0 was obtained densityofice(973kgm−3).Tortuosityisthencalcuiclaetedas
by subtracting the linear trend in CO2 concentration from afunctionofporosity(Eq.5).
eachhalf-hourinterval,andw0 representedtheverticalwind
speed.ApositivefluxsignindicatesanetlossofCO2 from τ =f13 (5)
theecosystem,whereasanegativesignindicatesnetuptake.
Flux processing included the necessary corrections for For weekly instantaneous measurements of the GHG fluxes
high-frequencydampinglosses(EugsterandSenn,1995)and using the gradient method, we sampled all gases across the
densityfluctuationsaccordingtoWebbetal.(1980).Inaddi- snowpack with a “ski pole”. The ski pole had 10cm in-
tion,fluxeswerefurthercorrectedwithaheatfluxcorrection terval depth markings along the pole to determine the in-
term due to instrument heating (Burba et al., 2008). A spe- sertion depth into the snow. The pole contained tubing in-
cific description of the modified correction for instruments sideandhadaperforatedtip,allowinggascollectionatany
thatarenotsetupverticallyisgiveninMerboldetal.(2012) snowdepth(Wetter,2009).Gasmeasurementsweremadeat
and Rogiers et al. (2008). After the application of the vari- 10cm increments either in the field via a portable gas ana-
ouscorrectionstotheprocessedfluxes,datawerefilteredfor lyzer directly connected to the ski pole or later in the lab-
clearly out-of-range values (±10 standard deviations, SD), oratory following gas sampling. A different hole was used
negative flux rates at night, and values below a u∗ (friction foreachsamplingdate.Gaswascollectedfromtheskipole
velocity)thresholdof0.1ms−1 toavoidanunderestimation usingadiaphragmgaspump(NMP015M,KNFNeuberger,
ofnighttimerespirationunderlowturbulence(Gouldenetal., Balterswil, Switzerland) to pull the air at a rate of approx-
1996). imately 0.4Lmin−1 through the infrared gas analyzer (LI-
GasconcentrationsofCO ,CH ,andN Oweremeasured 820,LI-CORInc.,Lincoln,Nebraska,USA)untilCO con-
2 4 2 2
infourprofilessurroundingtheECtoweronaweeklybasis. centrationsremainedconstant(usuallyafter30–60s).Inad-
Inaddition,twoautomaticprofileswithcontinuousmonitor- dition, gas samples were taken from the ski pole using a
Biogeosciences,10,3185–3203,2013 www.biogeosciences.net/10/3185/2013/
L.Merboldetal.: Wintergreenhousegasfluxesfromasubalpinegrassland 3189
60mLsyringe,whichwereimmediatelytransferredintopre- plesforCO ,CH andN Oanalysisweretakenat10,30and
2 4 2
evacuated 12mL vials (Labco Limited, Buckinghamshire, 50cmdepthatahorizontalresolutionof5m(Fig.1b).Snow
UK)withaneedle.InthesesamplesCO ,CH andN Ocon- densitymeasurements(explainedbelow)wereperformedev-
2 4 2
centrations were measured by gaschromatography (Agilent ery10m.
6890 gas chromatograph equipped with a flame ionization In addition, 150 CO concentration gradients were mea-
2
detector(FID)combinedwithamethanizertomeasureCO sured on a transversal cut across the different vegetation
2
and CH and an electron capture detector (ECD) to mea- types of the valley, in distances ranging from 0.2 to 5m on
4
sureN O,AgilentTechnologiesInc.,SantaClara,USA).For 24February(Fig.1b).Thesegradientsweremeasuredonsite
2
moregaschromatographydetailsseeHartmannetal.(2011). using the portable gas analyzer (LI-820, LI-COR Inc., Lin-
The permanent automatically monitored gas gradients coln,Nebraska,USA)connectedtotheskipoleinavertical
were set up to measure CO and Rn222 concentrations in resolutionof10cm.
2
situ and continuously within the snowpack at four dif- Statistical differences in ecosystem fluxes were analyzed
ferent heights. Closed loops of tubing (Synflex 1300 alu- usingananalysisofvariance(ANOVA).Spatialdataevalua-
miniumcoatedtubing,EatonIndustriesIIGmbH,Effretikon, tionandinterpolationwasachievedbyconventionalkriging
Switzerland), about 10m length in total, were installed for approachesinArcGIS(ArGISDesktop9.3.1,ESRIInc.)
CO and Rn222 concentration measurements. The closed
2
loops included 1m section of an air permeable, hydropho- 2.3 Environmentalvariables
bic,polypropylenetube(AccurelPPV8/2)(Gutetal.,1998)
to sample the air within the snowpack over the course of Environmental data including air temperature and rela-
the winter season. The first sampling depth was installed at tive humidity (3m height, Rotronic Hydroclip MP100A,
the beginning of the winter season between the soil and the ROTRONICAG,Bassersdorf,Switzerland),soiltemperature
first snow layer. The following tube layers were set up on (3cmdepth,107-LCampbellScientificInc.USA),soilwater
topofthesnowpack,preferablyafteraperiodofsnowcom- content (10cm depth, 10HS soil moisture sensor, Decagon
paction and before severe snowfall events. We favored flex- DevicesInc.,Hopkins,Nebraska,USA),snowheight(SR50-
ibletubesascomparedtorigid“snowtowers”usedinother L, Campbell Scientific Inc. USA), wind speed and direc-
winter studies (e.g., Filippa et al., 2009; Seok et al., 2009) tion (3.4m height, 05103 RM Young Windmonitor, Camp-
becausethelatterarelikelytoalterthebuild-upofanundis- bellScientificInc.USA),snowsurfacetemperature(AlpuG
turbed snow structure. For the actual gas measurement, air IR,AlpuGGmbH,Davos,Switzerland)andglobalradiation
was flushed through the tubes and sampled at a 10min in- (SP-110, Apogee Instruments Inc., Logan, UT, USA) were
terval using a self-made profile unit consisting of a switch- collectedas10minaveragesatanearbymeteorologicalsta-
ing unit, the gas analyzer (LI-840, LI-COR Inc., Lincoln, tion run by the Institute of Snow and Avalanche Research
Nebraska, USA)and a Radon analyzer (Alpha Guard, Gen- (SLF). Measurements of snow density were conducted in
itron Instruments, Frankfurt a.M., Germany) incorporating combination with the manual GHG gradient measurements
a pulse-counting ionization chamber (alpha spectroscopy). by weighing snow samples (100cm3) directly in the field.
Theradonanalyzerwascapableofmeasuringconcentrations These measurements were done in a 10cm vertical resolu-
between2and2×106Bqm−3.Radon(222Rn)fluxwasmea- tionwith2–3replicatesperdepth.
suredtodeterminediffusionpropertiesinthesnowpack.This
method was successfully applied to measure soil diffusivity 2.4 CalculationofseasonalGHGbalances
byLehmannetal.(2000)sinceradonisofgeologicalorigin
and is produced continuously in the α-decay chain of ura- Gaps in eddy covariance CO fluxes were filled using a
2
niumandthoriuminallnaturalsoils.Furthermore,radonisa marginal distribution sampling (MDS) procedure according
noblegasandshowsnochemicalormicrobialreactioninthe toReichsteinetal.(2005)inordertoreceiveacompletesea-
soil,snoworair.SincethecantonofGrisons,andspecifically sonaldataset.Gap-filled30minfluxaverageswerethereafter
the region of Davos, has been identified as a region of high integrated.
radonbyDeflorin(2004),wedecidedtouse222Rnasanat- Gradienttechniquebasedseasonalfluxestimateswerede-
uraltracerforthespecificsnowdiffusionpropertiesneeded rivedbyaveragingtheweeklyrepeatedprofilemeasurements
forthequantificationofotherGHGfluxesusingthegradient and relating the flux values to a set of environmental vari-
approach. To quantify the actual 222Rn flux, we measured ables(airtemperature(T ),soiltemperature(T ),soilmois-
a s
the increase in 222Rn with time in chambers placed on the ture (2), snow height (h ), snow density (% ), snow water
s s
soilsurfaceinsnowpitseveryweek. equivalent(h )andwindspeed(WS)).Snowwaterequiv-
SWE
To determine the transversal and longitudinal variabil- alentwascalculatedbytheproductofsnowdepthandrela-
ity across the grassland, 33 profiles along two transects tive snow density with respect to the density of liquid wa-
(transversal length 50m, longitudinal 90m) were sampled ter. Therefore, h represents a measure for the mass of
SWE
manuallyusingtheski-polemethodduringanintensivefield the snowpack and includes a time component since snow
campaignon23and24February2011.Ateachlocationsam- accumulates over the course of the season. The identified
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3190 L.Merboldetal.: Wintergreenhousegasfluxesfromasubalpinegrassland
20 10
a e
e [°C] 10 -1m s] 8
Air temperatur -100 Wind speed [ 46
-20 2
-30/1.0 0/70
b f
60
perature [°C] 00..05 height [cm] 345000
m w
oil te Sno 20
S -0.5 10
0
-1.0 0.6
-3m] 0.44 c g
3m 0.5
nt [ 0.42 -3m]
onte y [g 0.4
etric water c 00..3480 Snow densit 00..23
m
olu 0.1
V 0.36
1200 0.0/18
d h
16
1000 m]
-2W m] 800 ent [c 1124
obal radiation [ 460000 w water equival 1680
Gl 200 Sno 4
2
0 0
1.11.10 1.12.10 1.1.11 1.2.11 1.3.11 1.4.11 1.5.11 1.11.10 1.12.10 1.1.11 1.2.11 1.3.11 1.4.11 1.5.11
Date Date
Fig.2.EnvironmentalvariablesbetweenNovember2010andApril2011,(a)airtemperature,(b)soiltemperature,(c)soilwatercontent,
(d)radiation,(e)windspeed,(f)snowheight,(g)snowdensity±SDand(h)snowwaterequivalent.Dataare30minaveragesexceptfor(g),
whichisbasedon4measurementspersamplingdate.Thegreyshadedarearepresentsthetimeofcontinuoussnowcover.
functionalrelationsonaweeklybasiswerethenusedtoex- 3 Results
trapolatefluxvaluesforeachdayofthesnow-coveredseason
andthereafterintegrated. 3.1 Weatherandsnowcondition
Seasonal budgets were calculated for the time
period when actual measurements were available
Therewascontinuoussnowcoveratthestudysitefrommid-
(1December2010–31March2011) representing 85%
November until the beginning of April during the winter
ofthesnow-coveredperiodduringthewinter2010/2011.
season 2010/2011 (Fig. 2). Air temperature varied strongly
over the course of the season, reaching lowest values of
−20◦C on 27 December and 20 January. In March 2011
temperature started to rise rapidly (Fig. 2a). Soil tempera-
tures decreased at the beginning of the winter season and
stayed mostly stable around 0◦C until complete snowmelt
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L.Merboldetal.: Wintergreenhousegasfluxesfromasubalpinegrassland 3191
at the beginning of April 2011 (Fig. 2b). Soil water con- 5
a
tent fluctuated only slightly during the peak winter period
and increased with the beginning of snowmelt in March 4
(Fig. 2c). Global radiation decreased until mid-December
and rose continuously thereafter due to extended hours of -2-1m s] 3
daylight(Fig.2d).Windspeedfluctuatedgenerallybetween ol
0.1–4ms−1 withmaximaof8ms−1 observedduringsingle x [µm 2
days in November 2010 and March 2011 (Fig. 2e). Snow u
accumulated rapidly with the regular snowfall events until CO fl2 1
11 December. Maximum snow height (63cm) was reached
27 February (Fig. 2f) and was below the long-term average 0
of89±30cm(T.Jonas;unpublisheddata).Snowdensityre-
mainedstableataround0.25gm−3 overmostoftheseason -1/0.2
and reached maximum values of 0.45gm−3 only in the be- b
ginningofApril(Fig.2g).Icelayerswithinthesnowpackde-
0.0
velopedduetoshorttemperaturechangesduringthemonths
ofDecemberandJanuaryandtheassociatedfreeze–thawcy- -1s]
clesofthesnow(Fig.2a).Snowwaterequivalentwasshown -2m -0.2
to be lowest at the beginning of the season and highest at mol
n
the end with reduced snow height and higher snow density ux [ -0.4
(Fig.2h). H fl4
C
-0.6
3.2 Temporalvariationofgreenhousegasfluxes
-0.8/1.6
Concentrations of CO showed a decrease from the soil to c
2
1.4
thesnowsurfacewithsignificantlinearrelationshipsbetween
concentrationsandsnowdepths(notshown).FluxesofCO 1.2
2
calculated from the gradient measurements showed largest -1s] 1.0
erifofldux(Friagt.e3saa,t2t.h3e±be2g.2inµnminoglaCnOd2emnd2os−ft1hiensDnoecwe-mcobveerr2e0d1p0e)-. -2ol m 0.8
m
DecreasingCO fluxesweremeasuredduringthepeakwin- n 0.6
2 x [
t0e.r02peµrmioodlC(JOan2umar2ys/−Fe1bornua2ry32F0e1b1ru),arrye.acThhienrgeaaftmeri,naimndumwiothf NO flu2 00..24
the beginning of snowmelt, CO fluxes started to increase
2
(0.51±0.23µmolCO m−2s−1 in March and April) along 0.0
2
with high concentrations of CO2 at the soil–snow interface -0.2
(Fig.3a).Incomparisontothegradientapproach,CO fluxes 1.11.10 1.12.10 1.1.11 1.2.11 1.3.11 1.4.11 Average
2
measured by the eddy covariance method provided a bet- Date
ter temporal resolution, showing a much larger variation
Fig.3.FluxestimatesfromthegradientandECmeasurementsfor
(Fig.4a–c).ECfluxeswerecommonlylargerthanthevalues
(a)CO2(whitecircles),(b)CH4(greycircles)and(c)N2O(black
derivedfromthegradients(Table2).Forthemainwinterpe-
circles)duringthe2010/2011winterseasonintheDischmaValley.
riod (December–March), CO2 fluxes measured by EC were Modeledgradientfluxesareindicatedasorangecircles.Gap-filled
twiceashighasthegradientmeasurements(Table2,Fig.3a). ECofCO2±uncertainty(Reichstein etal.,2005)arehighlighted
TheCO fluxeswerecharacterizedbyacontinuousbuttem- in blue (a). Average seasonal flux estimates are given at the right
2
porallydecliningreleaseofCO untilsnowmeltattheendof side of each figure. The grey shaded area represents the time of
2
March(Fig.4a–c).Withtheappearanceofthefirstsnow-free continuous snow cover. Error bars for the gradient-derived fluxes
patcheswithintheECfootprintinApril2011netecosystem areshown±SD.
exchange(NEE)ratesdroppedbelowzeroindicatingphoto-
syntheticactivity(Fig.4aandb).
CH was taken up continuously by the grassland dur- son and fluctuated slightly below zero in March and April
4
ing the winter 2010/2011 (Fig. 3b). The largest uptake (−0.09±0.08nmolCH m2s−1,Fig.3b).
4
rates were recorded on 8 December with rates as nega- Emission of N O varied largely during the win-
2
tive as −0.62nmolCH m2s−1. Fluxes of CH towards the ter season 2010/2011 (Fig. 3c) with peaks up to
4 4
ecosystem decreased over the course of the winter sea- 1.63nmolN Om2s−1 on 15 February. In comparison, the
2
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3192 L.Merboldetal.: Wintergreenhousegasfluxesfromasubalpinegrassland
Table 2. Monthly averaged (measured and gap-filled) and overall mean of CO2, CH4 and N2O flux data ±SD derived by the gradient
approachandtheeddycovariancemethod.
CO2fluxes CH4fluxes(nmolm−2s−1) N2Ofluxes(nmolm−2s−1)
(µmolm−2s−1)
Gradient(meas.) Gradient(mod.) EC(meas.) EC(GF) Measured Modeled Measured Modeled
Nov na na na 1.81±0.96 na na na na
December 1.36±0.68 1.76±0.56 1.53±2.05 1.57±0.99 −0.22±0.10 −0.27±0.04 0.12±0.10 0.14±0.09
Jan 0.56±0.16 1.17±0.33 1.07±1.53 1.23±0.88 −0.15±0.05 −0.22±0.03 0.16±0.11 0.14±0.1
Feb 0.41±0.31 0.82±0.17 1.01±1.69 0.95±1.15 −0.11±0.09 −0.18±0.03 0.44±0.38 0.37±0.31
Mar 0.62±0.23 0.88±0.4 1.33±1.74 1.00±1.03 −0.08±0.07 −0.19±0.04 0.30±0.22 0.31±0.2
Apr 0.29±0.26 na 0.66±2.28 1.12±1.35 −0.11±0.9 na 0.02±0.07 na
Winterseason 0.77 ±0.54 1.18 ±0.54 1.24 ±1.75 1.19 ±1.05 −0.14 ±0.09 −0.22 ±0.05 0.23 ±0.23 0.24 ±0.21
(Dec–Mar)
averageN Ofluxfromtheecosystemwassignificantlylower the N O fluxes on aseasonal basis by linearly interpolating
2 2
(0.23±0.23nmolN Om2s−1,Fig.3c). theweeklymeasuredfluxes(Fig.3c).
2
3.3 Drivingfactorsofgreenhousegasfluxes 3.4 SpatialvariabilityofCO ,CH andN Ofluxesin
2 4 2
thegrassland
The weekly measured CO effluxes using the gradient ap-
2
proach correlated most closely with snow water equivalent During the intensive measurement campaign, CO
2
(hSWE, r2=0.8, Fig. 5d) and with soil temperature at 3cm fluxes ranged between 0.09µmolCO2m−2s−1 and
depth(r2=0.78,Fig.5b).Nosignificantrelationshipexisted 1.14µmolCO m2s−1. We observed similar variation
2
with air temperature, wind speed, snow density and snow in CO fluxes along the transversal cut of the grassland
2
height. Measurements from April were discarded from this and along the longitudinal cut of the valley (Fig. 6a).
analysisduetotheabsenceofcontinuoussnowcoveronthe Coefficientsofvariationwere75%forthewholegrassland,
grasslandandalteredCO2gradients.Inordertoderivecumu- 76% for the transversal and 72% for the longitudinal
lativesumsofCO2emissionsforthesnow-coveredperiodin transect. Our spatial measurement campaign showed that
2010/2011,weusedtheobservedrelationshipbetweenhSWE the average CO2 effluxes along the longitudinal transect
andCO2fluxtointerpolateweeklygapsinthedata(Fig.3a). (main wind direction) and the transversal cut were in the
This relationship explained 80% of the variability in flux same order of magnitude as those that were monitored
fromtheecosystem(Fig.5d): throughout the peak winter (0.36±0.24µmolm2s−1 vs.
0.54±0.23µmolm2s−1, January–March). By comparison,
F =7.88e(−0.17hSWE) (6)
CO2 eddy covariance fluxes showed considerably higher fluxes
(1.14±1.65to1.06±1.02µmolm2s−1,January–March).
Similartotheprofilemeasurements,CO fluxesmeasuredby
2
Fluxes of CH were significantly below zero
eddycovariance(EC)werecorrelatedwithh explaining 4
SWE (−0.06±0.06nmolCH m2s−1, one sample t test, Fig. 6b)
38%ofthevariation(Fig.5c).Inaddition,soiltemperature 4
along the two transects. Maximum uptake rates were
at3cmdepthshowedaweakerbutstillsignificantrelation-
ship with CO emissions (r2=0.32). Other environmental −0.16nmolCH4m2s−1. Single points of CH4 efflux
2
were located across the grassland with values up to
variablesdidnotcorrelatewithEC-basedfluxes(notshown).
0.10nmolCH m−2s−1 (Fig. 6b). Fluxes of CH along the
CH flux variability was also explained by snow water 4 4
4
equivalent (r2=0.57), resulting in decreasing uptake rates transversal and longitudinal cut through the grassland did
not differ significantly (Fig. 6b). Coefficients of variation
withincreasingvaluesofh (Figs.3band5e).Therefore,
SWE
wereslightlyhigherthanthevaluesreportedforCO fluxes
therelationshipbetweenCH fluxandh wasusedtocal- 2
4 SWE
(110%wholegrassland,103%and101%forthetransversal
culateseasonalsumsofCH uptake(Eq.7).
4
andthelongitudinaltransects,respectively).
FCH4 =0.02hSWE−0.45 (7) 0.0N32±O0.07flnumxeoslN Oacmro2sss−1 (thFeig. 6gcr)a.ssHlaonwdevera,vearasgiegd-
2
IncontrasttotheCO andCH fluxes,noneofthemeteoro- nificantly larger efflux of N O (0.33nmolN Om2s−1) was
2 4 2 2
logicalvariablesmeasuredwereabletoexplainthevariabil- measuredatoneprofile(at75m)alongthelongitudinaltran-
ity in N O flux. Relating N O fluxes to soil water content sect(Fig.6c).Onlyfewlocationsonthegrasslandwerechar-
2 2
(10cm depth) as done in previous studies did not result in acterizedbyN Ouptake(−0.03±0.008nmolN Om2s−1).
2 2
sufficientexplanatorypower(notshown)andneitherdidthe The coefficients of spatial variation were highest for N O
2
correlation with h (Fig. 5f). Therefore, we extrapolated in relation to CO and CH , with values up to 256% on
SWE 2 4
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L.Merboldetal.: Wintergreenhousegasfluxesfromasubalpinegrassland 3193
12 tem (Figs. 7 and 8) and smallest from the filled ground
a and the grassland slope (0.31±0.16µmolCO m2s−1).
10 2
Intermediate fluxes of CO occurred from the forest
-2-1m s] 8 (0.41±0.22µmolCO2m2s−12)(Figs.7and8).Snowheight
ol 6 was largest in the open areas (filled ground, grassland and
m
x [µ 4 grasslandslope)andlowestintheforest(Fig.7).
u
O fl2 2 3.6 Automaticgradientmeasurements
C
ed 0
sur BesidesmonitoringGHGsduringwinterintheDischmaVal-
a -2
e
M ley,weaimedattestinganin-housedevelopmentofanauto-
-4
maticgradientmeasurementtechniqueforacontinuousmon-
-6/12 itoring of 222Rn and CO concentrations within the snow-
b 2
10 pack. Although we chose long tube lengths (10m) to avoid
heating of the air passing the infrared gas analyzer, we ob-
-2-1ol m s] 68 sseurrveemdeincteccahmanpnaieglsna(rFoiugn.d9t)h.eAtusbainrgesautltth,etheendcoonfttihneuomueslay-
m
x [µ 4 measured CO2 gradient was much smaller than the instan-
CO flu2 2 tsahnoewonu)s.mFuarntuhaelrlydemveelaospumreedntonineculusdininggthaectsivkeipcoooleli(ndgaotafnthoet
ed 0 aircirculatinginthetubesisneeded.
pfill -2
a
G
3.7 SeasonalGHGbudget
-4
-6/12
-1s] c Seasonal budgets derived by the gradient measurements
-2m 10 of CO2, CH4 and N2O during the period of 1 Decem-
mol 8 ber until 31 March (121 days) were 543±247gCO2m−2,
ux [µ 6 −0.4±0.01gCH4m−2 and 0.11±0.1gN2Om−2, respec-
CO fl2 4 tsilvigehlyt.lyCulamrguelrat(iv5e50em±i5ss4i0ongsCfOorCmO−22)mtehaasnurtehdebvyalEuCeswcearle-
d 2
pfille 2 culated from the concentration gradients. The ecosystem’s
d ga 0 global warming potential (GWP) during the winter season
ge 2010/2011(winterdefinedasthesnow-coveredtimeperiod)
a -2
er was 547–574gCO -eq., using the range of values derived
v 2
aily a -4 fromtheECandgradientapproaches(Table3).N2Ofluxes
D -6 contributed5%totheseasonalGHGbudgetandCH4fluxes
1.11.10 1.12.10 1.1.11 1.2.11 1.3.11 1.4.11 1.5.11
reducedtheGHGbudgetofthegrasslandsiteby0.1%.
Date
Fig. 4. CO2 fluxes based on eddy covariance measurements in
the Dischma Valley from mid-November 2010 until April 2011: 4 Discussion
(a) measured 30min averages (white circles), (b) gap-filled
30min averages and (blue circles) (c) gap-filled daily aver- Thegradientmethodhasbeenmostfrequentlyappliedtoin-
ages±uncertainty (blue circles) calculated using standard proce- vestigatewinterCO2 emissionsduringpreviousstudies(van
dures(fordetailsseeReichsteinetal.,2005).Thegreyshadedarea Bochoveetal.,2000;Wolfetal.,2011;Wetter,2009).How-
representsthetimeofcontinuoussnowcover. ever, its accuracy is highly uncertain due to the difficulties
in validating gas diffusivity across snowpacks and compar-
isons with chamber and eddy covariance approaches have
the grassland, 165% for the transversal and 254% for the yieldedcontradictingresults(Bjo¨rkmanetal.,2010a;Suzuki
longitudinalcut. etal.,2006;Schindlbacheretal.,2007).Ourcomparisonof
the gradient approach with CO effluxes estimated by the
2
3.5 SpatialvariationofCO fluxesacrossvegetation EC method indicated a 50% underestimation by the gradi-
2
types ent method during the main winter period (January–March)
andstrongerdeviationsduringsnowmelt(Fig.3a).
The mean CO fluxes differed considerably among Onepotentialbiasforourconclusioncouldbethediffer-
2
the ecosystems, with the largest emissions of entspatialscalescapturedbythetwomethodologies.While
0.85±0.38µmolCO m2s−1 from the grassland ecosys- the gradient method enables the quantification of emissions
2
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3194 L.Merboldetal.: Wintergreenhousegasfluxesfromasubalpinegrassland
5
a r2 = 0.32 b r2 = 0.78
y = 1.29*0.89x y = 0.87*e2.56x
4
-1s]
-2m 3
ol
m
µ
x [ 2
u
CO fl2 1
0
-1
-1.0 -0.5 0.0 0.5 -1.0/1.0 -0.5 0.0 0.5 1.0
Soil temperature [°C]
5
c r2 = 0.38 d r2 = 0.80
y = 3.91*-0.10x y = -7.88*e-0.17x
4
-1s]
-2ol m 3
m
µ
x [ 2
u
O fl2
C 1
0
-1/0.4 1.6
e f
1.4
-2-1m s] 0.0 11..02 -2-1ol m s]
H flux [nmol 4-0.2 000...468 NO flux [nm2
C
-0.4 0.2
r2 = 0.57
y = 0.02x - 0.45 0.0
-0.6 -0.2
0 5 10 15 20/0 5 10 15 20
Snow water equivalent [cm] Snow water equivalent [cm]
Fig. 5. Response functions of CO2, (eddy covariance a, c and gradient based b, d) CH4 (e), and N2O (f) to soil temperature and snow
water equivalent. While CO2 and CH4 fluxes could be explained well, N2O fluxes could not be explained by any of the meteorological
variables measured. Red dots indicate measurements in April, which were excluded from the analysis, since the snow cover at site was
alreadynoncontinuousatthistimeoftheyear.Dashedlinesindicatethe95%confidenceintervals.
attheplotscale(Hubbardetal.,2005),eddycovariancein- suggesting that wind pumping played a minor role in this
tegrates flux measurements over a whole ecosystem (foot- study.
printarea)andcancoverseveralhectaresofland(Baldocchi Inaddition,nonlinearitiesoftheconcentrationgradientof-
andMeyers,1998).Theunderlyingapproachofthegradient ten caused by ice layers have been shown to generate prob-
methodistheestimationof gasdiffusivityacrossthesnow- lems when calculating CO fluxes. Mast et al. (1998) sug-
2
pack by measurements of snow density assuming steady- gested choosing a linear part of the gradient with constant
state conditions (Eq. 2). Therefore, it seems likely that the snowdensity,whereasSchindlbacheretal.(2007)proposed
estimated fluxes include a high uncertainty. Effects such as including sections of the gradient above an ice layer only.
pressurepumpingmayleadtoadvectivemovementofsnow More complex approaches were recommended by Monson
air and consequently increased CO efflux (Colbeck, 1997; et al. (2006b). In our study we observed few nonlinearities,
2
SturmandJohnson,1991).Recently,BowlingandMassman whichcouldnotberelatedtoaspecificicelayer.Therefore,
(2011)wereabletoidentifyan8–11%contributionofpres- the entire concentration gradient was chosen for flux calcu-
surepumpingtoawinterCO budgetinNiwotRidge,USA. lation.
2
However, the quantification of such effects remains a chal- The estimation of porosity and tortuosity contributes the
lenge (Mast et al., 1998). We did not observe a relationship largestuncertaintiesforGHGfluxcalculationwhenapplying
between CO flux and wind speed (not shown) at our site, thegradientmethod(Monsonetal.,2006b;Seoketal.,2009;
2
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