EDDY COVARIANCE MEASUREMENTS OF CO 2 AND ENERGY FLUXES OF AN ALASKAN TUSSOCK TUNDRA ECOSYSTEM

686

Ecology, 80(2), 1999, pp. 686–701q 1999 by the Ecological Society of America

EDDY COVARIANCE MEASUREMENTS OF CO2 AND ENERGY FLUXES OFAN ALASKAN TUSSOCK TUNDRA ECOSYSTEM

GEORGE L. VOURLITIS1,3 AND WALTER C. OECHEL2

1Biology Program, California State University, San Marcos, California 92096 USA2Global Change Research Group, Department of Biology, San Diego State University, San Diego, California 91812 USA

Abstract. Eddy covariance was used to measure the net CO2 exchange and energybalance of a moist-tussock tundra ecosystem at Happy Valley, Alaska (69808.549 N,148850.479 W), during the 1994–1995 growing seasons (June–August). The system operatedfor 75–95% of the time, and energy balance closure was within 5%, indicating good systemperformance.

Daily rates of evapotranspiration (ET) were on average 1.5 mm/d, while seasonal ETranged between 100 and 150 mm. Daily ET was strongly correlated with daily fluctuationsin net radiation. However, the ‘‘omega factor’’ (an index of the relative importance ofmeteorological and physiological limitations to evapotranspiration) was generally ,0.5throughout June and early July, indicating that biological limitations to ET were relativelymore important than meteorological limitations during the first half of the growing season.The biological limitation to ET was presumably due to bryophyte desiccation and subsequentreductions in canopy water-vapor conductance, especially under conditions of high evap-orative demand.

The moist-tussock tundra ecosystem was a net sink for atmospheric CO2 of 23.3 and24.6 mol/m2 during the 1994 and 1995 growing seasons, respectively (negative flux depictsnet CO2 accumulation). Over diel (24-h) periods, 60–90% of the variation in net CO2

exchange was explained as a hyperbolic function of photosynthetic photon flux density(PPFD), while over seasonal time scales, model estimates of the estimated quantum yieldand maximum gross assimilation indicate that daily variations in net CO2 uptake weredriven more by the seasonal trend in ecosystem phenology than by meteorology. Approx-imately 70% of the variation in nighttime net CO2 exchange, an estimate of the whole-ecosystem respiration rate, was explained by variations in water-table depth and temperature.Although other environmental factors may be important, interannual differences in observednet CO2 exchange were almost completely explained by the interannual differences inestimated whole-ecosystem respiration.

Key words: arctic Alaska; climate change; CO2 flux; ecophysiology; eddy covariance; energybalance; Eriophorum vaginatum; tussock tundra.

INTRODUCTION

The carbon and energy balance of the circumarcticis of considerable interest due to the presumed sensi-tivity of arctic ecosystems to high-latitude warming andclimate change (Hinzman and Kane 1992, Oechel andBillings 1992, Shaver et al. 1992, Waelbroeck 1993)and the substantial soil carbon stocks in the active layerand upper permafrost (Miller et al. 1983, Billings 1987,Schlesinger 1991). Thermal profiles of permafrost andweather records indicate a temperature rise of 2–48Cthroughout northern Alaska and Canada over the lastfew decades (Lachenbruch and Marshall 1986, Beltra-mi and Mareshal 1991, Chapman and Walsh 1993,Oechel et al. 1993). These temperature increases mayhave already substantially altered arctic ecosystem hy-drology (Oechel et al. 1995, Kane 1996), while futureclimatic change will likely result in alterations in the

Manuscript received 21 July 1997; revised 2 March 1998;accepted 4 March 1998; final version received 20 April 1998.

3 E-mail: [email protected]

distribution and extent of snow cover, atmospheric H2Ovapor, cloudiness, and radiation balance (Gates et al.1992, Hinzman and Kane 1992, Kane et al. 1992, Man-abe and Stouffer 1993, Kettenberg et al. 1996). Theselocal changes in energy balance not only have the ca-pacity to affect regional climate (Kane 1996), but haveimplications for global climate as well, throughchanges in albedo from retreating snow and ice fields(Groisman et al. 1994) and alterations in the distri-bution of arctic and boreal forest vegetation (Bonan etal. 1992).

Arctic tundra ecosystems have historically been con-sidered sinks for atmospheric CO2 due to the presenceof permafrost and its control on ecosystem water bal-ance (Miller et al. 1983, Oechel and Billings 1992).However, recent plot-scale measurements indicate thatterrestrial tussock tundra ecosystems are net CO2

sources of on average 12 mol/m2 during the June–Au-gust growing season (Grulke et al. 1990, Oechel et al.1993, Oechel and Vourlitis 1995, Tenhunen et al. 1995;W. C. Oechel et al., unpublished data). The recent

March 1999 687CO2 AND ENERGY FLUX OF TUSSOCK TUNDRA

change in the direction of net CO2 exchange is attrib-uted to soil surface drying associated with the observedhigh-latitude warming (Oechel and Billings 1992,Oechel et al. 1993, 1995, Oechel and Vourlitis 1994,1995, Waelbroeck et al. 1997). An additional 2mol·m22·yr21 may be lost from lakes and streams (Klinget al. 1991), thus increasing the actual amount of Clost from arctic landscapes.

Arctic landscapes exhibit considerable spatial het-erogeneity in microtopography, water-table depth, soiltemperature, and plant species composition (Weller andHolmgren 1974, Stuart et al. 1982, Walker et al. 1989).The high spatial and temporal variance in these drivingvariables makes large-scale (e.g., hectare) estimates ofnet CO2 flux extrapolated from plot-scale measure-ments uncertain (Oechel and Vourlitis 1994, Weller etal. 1995, Baldocchi et al. 1996). Furthermore, the me-teorological and phenological controls on large-scalenet CO2 exchange and energy balance are also uncertainbecause a majority of the studies have a limited spatialand temporal extent (Oechel and Vourlitis 1994, Welleret al. 1995, Baldocchi et al. 1996). Because of theseuncertainties, eddy covariance measurements of netCO2 flux and energy balance were initiated in a varietyof Alaskan terrestrial arctic tundra ecosystems in con-junction with the NSF Land–Atmosphere–Ice–Inter-actions (NSF–ARCSS–LAII) flux study (Weller et al.1995). This paper summarizes the eddy covariancemeasurements of net CO2, H2O vapor, and energy fluxfrom a moist-tussock tundra ecosystem during the1994–1995 summer growing seasons. The objectivesof this research were to assess the inter- and intrasea-sonal variation in terrestrial CO2 and energy flux andto determine the possible meteorological and pheno-logical controls on net CO2 and energy exchange.

METHODS

Site description

The Happy Valley research site (69808.549 N,148850.479 W) is located 135 km south of the ArcticOcean and 1.5 km west of the Trans-Alaska PipelineHaul Road on the North Slope of Alaska. Happy Valleyis characteristic of moist-tussock tundra dominated byEriophorum vaginatum L. (Auerbach and Walker1995). Inter-tussock microsites are dominated by non-tussock-forming sedges (Carex bigelowii Torr.) and de-ciduous and evergreen shrubs (e.g., Betula nana L. andVaccinium vitis-idaea L., respectively) (Auerbach andWalker 1995). This ecosystem type corresponds to 25–50% of the Alaskan arctic tundra (Hastings et al. 1989,Auerbach and Walker 1995), and ;20% of circumpolartundra (Miller et al. 1983). Soils are Histic PergelicCryaquepts with a 15–30 cm organic layer overlyingmineral soil (Marion and Oechel 1993). Mean annualtemperature is between 211.1 and 26.78C, while meansummer temperature (June–August) is ;118C (Oechel1989). Annual precipitation is on average 345 mm, with

60% falling as rain during the summer months (Kane1996).

Eddy covariance instrumentation

The eddy covariance systems were deployed between11 June and 30 August in 1994, and between 30 Mayand 6 September in 1995. Fluctuations in wind speedand temperature were measured at 10 Hz using a tri-axial sonic anemometer–thermometer (SWS-211/3K;Applied Technologies, Incorporated, Boulder, Colora-do) with a path length of 15 cm (Vourlitis and Oechel1997). The sensors were mounted at a height of 2.5 mabove ground level and aligned at an angle of 2708, aswind direction was out of the south-to-west and west-to-north quadrants 84–98% of the time.

Carbon dioxide and H2O vapor fluctuations weremeasured at 10 Hz using a closed-path infrared gasanalyzer equipped with a pressure transducer (LI-6262;LI-COR, Incorporated, Lincoln, Nebraska). Flow ratethrough the 3 mm diameter by 3 m long plastic inlettubing was measured using a rotameter, and maintainedat 9–10 L/min using either a carbon vane or diaphragmpump installed with a 12-V direct-current continuouspower supply to maintain a consistent pump speed andflow rate (Vourlitis and Oechel 1997). Sample air wasunder vacuum in the gas analyzer, and mechanical puls-es from the pump were dampened using a 2-L baffleattached between the vacuum pump and the gas ana-lyzer (Suyker and Verma 1993). The gas sample inletwas located 13 cm behind the vertical sample path ofthe sonic anemometer. In addition to the closed-pathanalyzer, an open-path CO2 and H2O vapor infrared gasanalyzer (Auble and Meyers 1992), mounted 25 cmbehind the vertical sample path of the sonic anemom-eter, was used during the 1995 field season for redun-dancy in the CO2 and H2O vapor measurements (Vour-litis and Oechel 1997). This sensor has a response timeof 10 Hz and a sensitivity of 6.8 mmol/m3 and 0.5mmol/m3 to CO2 and H2O vapor, respectively (Aubleand Meyers 1992). The CO2 and H2O vapor channelsof both analyzers were calibrated every other weekusing a 300 and 400 mmol/mol standard gas and a por-table dew-point generator (LI-610, LI-COR, Incorpo-rated), respectively. The drift in the CO2 and H2O vaporcalibration coefficients for both sensors over the grow-ing season was 60.1 mmol/m3 and 60.2 mol/m3, re-spectively.

Meteorological instrumentation

Meteorological conditions were measured every 60s between 11 June and 30 August and between 30 Mayand 6 September in 1994 and 1995, respectively, andstored as 30-min averages using a datalogger (CR 21X;Campbell Scientific, Incorporated, Ogden, Utah). Wet-and dry-bulb temperatures were measured at 25, 100,and 200 cm above ground level using ventilated psy-chrometers affixed with cross-calibrated type-t ther-mocouples. Soil temperatures were measured between

688 Ecology, Vol. 80, No. 2GEORGE L. VOURLITIS AND WALTER C. OECHEL

0 and 80 cm below the moss surface at 5-cm incrementsusing cross-calibrated type-t thermocouples. Net ra-diation (Rn) was measured at a height of 1 m using anet radiometer (Q-6; REBS, Seattle, Washington). Soilheat flux (G) was measured using two soil heat fluxplates (HFT-1; REBS) buried 2 cm below the mosssurface. Because of the high heat capacity of the mosslayer (Miller et al. 1984, Waelbroeck 1993), G wascorrected by adding heat flux in the moss layer abovethe heat flux plates (Fritschen and Gay 1979). Photo-synthetic photon flux density (PPFD) was measuredusing a quantum sensor (LI-190SB; LI-COR, Incor-porated). Summer precipitation (1 June–31 August)was measured in 1995 using a tipping-bucket rainfallgauge (2501; Sierra-Misco, Incorporated, Berkeley,California), while in 1994, precipitation data were frommeasurements made at Imnaviat Creek, Alaska (D. L.Kane et al., unpublished data) located about 50 kmsouth-south-east of the study site.

Water-table depth and depth to permafrost (referredto as active layer depth) were measured every 7–10days between 1 June and 31 August during both grow-ing seasons. Water-table depth was determined by mea-suring the height of the subsurface water, relative tothe soil surface, within 1.9 cm diameter by 90 cm deepperforated plastic water wells. The water wells wereinstalled in tussock (n 5 6), Carex (n 5 2), water-track(n 5 2), and shrub (n 5 2) dominated surface types,with the sampling proportional to the spatial extent ofthe surface types observed at the study site. Mean ac-tive layer depth per surface type was determined from5–10 subsamples taken adjacent to the water wells bydriving a steel rod into the soil until permafrost wasreached, and measuring the portion of the rod betweenthe permafrost layer and the soil surface.

Eddy covariance flux calculation and systemperformance

Raw CO2 and H2O vapor fluctuations were output asmean voltages and converted to densities by multiply-ing by the requisite calibration constants (Leuning andMoncrieff 1990). Net CO2, H2O vapor, and sensibleheat fluxes were computed following a coordinate ro-tation of the wind vectors, and fast response (10-Hz)fluxes were calculated and stored on a laptop computeras 30-min averages using a 200-s running mean anddigital recursive filtering technique (McMillen 1986,1988). Closed-path CO2 flux estimates were correctedfor the simultaneous flux of H2O vapor (Leuning andMoncrieff 1990, Suyker and Verma 1993). Open-pathflux estimates were corrected for the simultaneous fluc-tuations in both heat and H2O vapor (Webb et al. 1980),as the fluctuations in both CO2 and H2O vapor weremeasured in situ. Data that appeared to be affected byflow distortion created by the tower structure, deter-mined by wind direction and large order-of-magnitudedepartures in the scalar and turbulent variances, wereremoved from analysis.

Normalized cospectra for latent heat (Le) and CO2

fluxes were calculated using raw (10-Hz) data to de-termine the errors induced by sensor and data acqui-sition frequency response (Moore 1986). These anal-yses indicated that ;10% of the open-path CO2 and Le

flux, 10% of the closed-path CO2 flux, and 35% of theclosed-path Le flux were lost due to slow sensor and/or data acquisition response (Vourlitis and Oechel1997). After correcting for the flux loss (Moore 1986),the closed-and open-path measurements of net CO2 andH2O vapor flux were similar (Vourlitis and Oechel1997). Because the measurement bias among the sen-sors was minimal, net CO2 and Le fluxes for the 1995growing season represent an average of the open- andclosed-path measurements (Vourlitis and Oechel 1997).

Energy balance closure was used to assess the per-formance of the eddy covariance flux system (Mc-Millen 1988). Under perfect closure, the sum of thesensible and latent heat flux terms (H 1 Le) measuredby eddy covariance is equal to the difference betweennet radiation and ground heat flux (Rn 2 G) measuredindependently from the meteorological sensors(McMillen 1988). Using least-squares linear regressionwith H 1 Le as the dependent variable and Rn 2 G asthe independent variable, the slope and intercept (61SE) in 1994 were 0.93 6 0.01 and 10.12 6 0.70 W/m2, respectively (r2 5 0.92, n 5 2642). In 1995, theslope was 0.96 6 0.01 and the intercept was 5.92 60.65 W/m2 (r2 5 0.91, n 5 3765). Thus at Rn 2 G of300 W/m2, which represents a maximum midday(1300–1400) value, the average underestimation in H1 Le was ,5%, indicating almost complete energy bal-ance closure and good performance of the eddy co-variance system.

Data analysis

Following notation and rationale of Ruimy et al.(1995), the instantaneous (30-min average) response ofwhole-ecosystem net CO2 flux (F ) to instantaneousvariations in PPFD (Q) was modeled using a rectan-gular hyperbola:

F 5 [(aQF`)/(aQ 1 F`)] 2 Rd (1)

where a 5 estimated quantum yield (mmol CO2/mmolPPFD), F` 5 estimated rate of gross CO2 assimilationat saturating PPFD (mmol·m22·s21), and Rd 5 the es-timated whole-ecosystem (plant 1 soil) dark respira-tion rate (actually referred to as R by Ruimy et al. 1995)which is the respiration rate at Q 5 0 (mmol·s22·s21).Model coefficients (a, F`, and Rd) were estimated bynonlinear least-squares regression (SYSTAT, Evanston,Illinois).

Although useful as an indication of the whole-eco-system respiratory kinetics, the term Rd estimated fromthe hyperbolic expression (Eq. 1) does not take intoaccount the effects of variable temperature and mois-ture on whole-ecosystem respiration (Ruimy et al.1995). To account for the effects of diel and seasonal


FIG. 1. The diel trend in net radiation (Rn), ground heatflux (G), sensible heat flux (H), and latent heat flux (Le) for15 July 1995.

variations in temperature and moisture on whole-eco-system respiration (R), a second approach was em-ployed where R was estimated from average nighttimenet CO2 exchange (Fn) measurements (Ruimy et al.1995) made at PPFD values below the light compen-sation point for whole-ecosystem net CO2 uptake (e.g.,PPFD , 50 mmol·m22·s21; Oechel et al. 1995) and un-der well-mixed atmospheric conditions (e.g., windspeed $ 2 m/s). The effects of average nighttime tem-perature (T ) and water-table depth (W ) on Fn wereassessed using a modified version of a phenomenolog-ical model described by Bunnell et al. (1977):

Fn 5 [(W/[W 1 a])(b/[b 1 W ])c 3 exp(dT ) (2)

where the coefficients of the model (a–d ) were esti-mated using nonlinear least-squares regression (SYS-TAT, Evanston, Illinois). This relationship was appliedto average daily temperature and water-table depth datato estimate the average daily whole-ecosystem (plant1 soil) respiration rate (R) for the 1994–1995 growingseasons. Because this estimate takes into account theeffects of variable temperature and water-table depth,R (Eq. 2) and the estimated dark respiration rate (Rd;Eq. 1) are not synonymous (Ruimy et al. 1995).

The Bunnell et al. (1977) model (Eq. 2) was initiallydeveloped to quantify the effects of soil water contentand temperature on microbial activity. However, fieldand laboratory studies indicate that variations in bothtemperature and moisture are important in controllingrates of whole-ecosystem respiration as well (Petersonand Billings 1975, Billings et al. 1977, 1982, Ober-bauer et al. 1991, 1992, Oechel et al. 1995, 1998a,Oechel and Vourlitis 1995, Johnson et al. 1996). Hence,the Bunnell et al. (1977) model (Eq. 2) should be ap-propriate for estimating R. Although the modified mod-el described here uses water-table depth instead of soilmoisture to characterize the soil water status (Bunnellet al. 1977), water-table depth is a useful surrogatesince soils with a higher water table (i.e., closer to thesoil surface) typically have a higher surface soil watercontent than soils with a lower (i.e., deeper) water table,and rates of O2 diffusion decline considerably at thewater table (Oberbauer et al. 1992).

Average midday (1000–1730) canopy conductance(gc) was estimated by inversion of the Penman-Mon-teith equation (Baldocchi et al. 1991). For Penman-Monteith, aerodynamic conductance was calculated as1/[u/(u*)2], where u 5 wind speed measured from thetri-axial sonic anemometer and u* 5 frictional velocitycalculated from eddy covariance measurements of mo-mentum flux (Baldocchi et al. 1991). The effects ofaverage midday (1000–1730) variations in the surface-to-air vapor pressure deficit (Do), calculated as a func-tion of the surface temperature estimated by inversionof the sensible heat flux equation (Baldocchi et al.1991, Grantz and Meinzer 1991), on average middayvariations in gc were assessed using nonlinear least-squares regression (SYSTAT, Evanston, Illinois). The

average midday (1000–1730) ‘‘omega factor’’ (V) (Jar-vis and McNaughton 1986) was calculated to assessthe relative importance of physiological and meteo-rological limitations to canopy evapotranspiration.

Daily evapotranspiration (ET) and CO2 flux totalswere calculated by integrating the 30-min average flux-es over the diel (24-h) period. Seasonal ET and CO2

flux totals were calculated by integrating the daily fluxtotals of ET and CO2 over an 81-d and 90-d period for1994 and 1995, respectively. A rectangular integralfunction was used for both daily and seasonal integra-tion schemes. In cases where data were missing, a linearinterpolation was used to estimate the CO2 and ET fluxduring the missing period.

RESULTS

Energy balance

The diel trend in net radiation (Rn) was symmetricalwith a midday peak between 1300 and 1500 local time(Fig. 1). Diel variations in sensible (H ), latent (Le), andground heat flux (G) were closely coupled to diel vari-ations in Rn (Fig. 1). Relatively more Rn was partitionedinto H at the beginning of the growing season (1–30June), as the Bowen ratio (ß 5 H/Le) was on average1.35–1.79 (Table 1). After 1 July, proportionally moreRn was partitioned into evaporative than to convectiveheating, and ß ranged from 0.5 to 0.9 between 1 Julyand 31 August in 1994 and 1995 (Table 1). On average,12–19% of Rn was partitioned into G, while H and Le

consumed nearly 38 and 45% of Rn, respectively, overboth growing seasons.

Daily variations in evapotranspiration (ET) were sig-nificantly correlated with daily variations in averageRn (Spearman’s r 5 0.74, P , 0.001, n 5 57 in 1994,and r 5 0.69, P , 0.001, n 5 88 in 1995). Although


TABLE 1. Average midday (1000–1730) net radiation (Rn), ground heat flux (G), sensible heat flux (H ), latent heat flux (Ln),and the Bowen ratio (ß) calculated over 2-wk intervals. Data represent means 6 1 SD; n 5 number of days averaged duringeach 2-wk interval.

Dates n Rn (W/m2) G (W/m2) H (W/m2) Le (W/m2) ß (H/Le)

199416–30 June1–15 July

16–31 July1–15 August

16–31 August

13111514

7

246 6 85269 6 67258 6 73199 6 76101 6 29

41 6 1651 6 1147 6 1041 6 1122 6 10

113 6 4993 6 31

107 6 4963 6 4125 6 18

89 6 39124 6 35126 6 25

93 6 3345 6 20

1.35 6 0.530.76 6 0.230.87 6 0.440.62 6 0.370.51 6 0.27

19951–15 June

16–30 June1–15 July


16–31 August

131515161416

230 6 73238 6 98229 6 75221 6 60171 6 88171 6 60

22 6 1129 6 2432 6 2119 6 1319 6 1624 6 14

93 6 4498 6 4483 6 3793 6 4066 6 3776 6 35

77 6 3792 6 59

113 6 35111 6 29

91 6 3988 6 28

1.79 6 1.541.52 6 1.180.71 6 0.220.84 6 0.350.70 6 0.200.86 6 0.39

day-to-day variations in ET and Rn were large, ET in-creased substantially after mid-June to a seasonal peakof 2–2.4 mm/d in the first week of July (Fig. 2A, B).The early-season increase in ET coincided with an in-crease in Rn following snowmelt (Fig. 2C, D). After 1July, daily rates of ET decreased gradually to a late-August value of 0.4 and 1.0 mm/d in 1994 and 1995,respectively (Fig. 2A, B). The decrease in ET coincidedwith a decrease in average daily Rn, reaching a seasonalminimum of ;40–60 W/m2 at the end of August (Fig.2C, D).

Precipitation varied considerably over both intra-and interseasonal time scales. Total June precipitationin 1994 was ;27 mm compared to 157 mm observedin June 1995 (Fig. 2E, F). Precipitation increased witheach month in 1994, as July and August precipitationwas 52 and 58 cm, respectively (Fig. 2E). Much of theprecipitation in 1994 was light (e.g., 88% of all events,5 mm, 10% between 5 and 15 mm, 2% .15 mm)and precipitation events were distributed relativelyevenly throughout the growing season. In contrast, Julyand August precipitation in 1995 was 199 and 94 mm,respectively (Fig. 2F), and the precipitation events wereoften heavier than in 1994 (53% of all events ,5 mm,32% between 5 and 15 mm, 15% .15 mm).

Average midday (1000–1730) canopy conductance(gc) in 1995 increased as the growing season progressed(Fig. 3A). With the exception of a brief (e.g., 4-d)increase in gc, average midday values for gc were0.004–0.008 m/s between 1 June and 15 July (Fig. 3A).After 15 July, an apparent stepwise increase in averagegc was observed, and gc varied between 0.008 and 0.05m/s (Fig. 3A). Average midday variations in gc wereclosely coupled to average midday variations in thesurface-to-air vapor pressure deficit (Do ), and gc de-creased as a power function as Do increased (Fig. 4).As with gc, average midday values of the omega factor(V) were typically ,0.5 before 15 July (Fig. 3B), in-dicating that biological limitations to ET were slightlylarger than meteorological limitations. After 15 July,

V was .0.5 (Fig. 3B), indicating that meteorologicallimitations to ET were relatively more important thanbiological limitations.

Net CO2 exchange

The diel pattern of net CO2 exchange was qualita-tively similar over intra- and interseasonal time scales;however, the diel amplitude of net CO2 exchange variedsubstantially both within and between growing seasons(Fig. 5). Although day-to-day variability was large, netsource activity was strongest between 2200 and 0600h, while net sink activity peaked between 1000 and1500 h (Fig. 5). The magnitude of diel net CO2 ex-change ranged between 10.5 and 20.75 mmol·m22·s21

in early June of 1995 (negative values depict net CO2

uptake or sink activity) (Fig. 5A). At the end of June(Fig. 5B), the midday sink strength increased to nearly22 mmol·m22·s21 in 1995, while in 1994, the middaysink was on average 2–4 times lower (Fig. 5B). In earlyJuly (Fig. 5C), net influx for both growing seasons wascomparable up to the hour of 0800, when the ecosystemin 1994 began to exhibit a midday photosynthetic de-pression with only partial recovery at 1500. In 1995,no midday depression was evident, and thus, the eco-system accumulated on average 2.5 times more at-mospheric CO2 between 1200 and 1400 than in 1994(Fig. 5C). In late July (Fig. 5D), interannual differencesin net CO2 exchange were negligible, and the magni-tude of diel net CO2 exchange ranged between 1.5mmol·m22·s21 at night and 23.5 mmol·m22·s21 at noon.In early August (Fig. 5E), interannual differences innet CO2 exchange were again negligible, but comparedto late July, nighttime net source activity increased tonearly 2 mmol·m22·s21 and midday net accumulationdecreased to only 22 mmol·m22·s21. Further reductionsin midday net sink strength were observed in late Au-gust (Fig. 5F). Net sink activity in 1994 reached amaximum of 22 mmol·m22·s21 between 1000 and 1500h, and a substantial midday depression was evident(Fig. 5F). In 1995, net sink activity was restricted to


FIG. 2. The seasonal trend in daily integrated evapotranspiration (A and B), average daily net radiation (C and D), andtotal daily precipitation (E and F) in 1994 (left panels) and 1995 (right panels). The cross (3) symbols and dashed linesdepict the daily integrated and daily averaged values of evapotranspiration and net radiation, respectively, while the closedboxes and solid lines depict a 7-d running mean. Precipitation data for 1994 are from Kane et al. (unpublished data) measuredat Imnaviat Creek, located ;50 km south-southeast of Happy Valley, Alaska.

1000–1300 h, with a maximum net uptake of 20.5mmol·m22·s21 (Fig. 5F).

The diel variation in net CO2 exchange was largelydriven by diel variations in photosynthetic photon fluxdensity (PPFD). The net CO2 compensation point (i.e.,the PPFD level where net CO2 exchange is zero) was

on average (61 SD) 157 6 19 mmol·m22·s21 in 1994and 135 6 45 mmol·m22·s21 in 1995, with no obviousseasonal trend. At low to intermediate levels of PPFD(e.g., 200–400 mmol·m22·s21), net CO2 uptake in-creased linearly with PPFD, but as PPFD exceeded400–500 mmol·m22·s21, the relative increase in the rate


FIG. 3. (A) The seasonal trend in average midday (1000–1730) bulk canopy conductance (gc) and (B) the average mid-day ‘‘omega factor’’ (V), which is an index describing therelative importance of physiological versus meteorologicallimitations to canopy evapotranspiration (Jarvis and Mc-Naughton 1986), for 1995. The cross (3) symbols and dashedlines depict the average midday gc and V values, while theclosed boxes and solid lines depict a 7-d running mean.

FIG. 4. The relationship between average midday (1000–1730) bulk canopy conductance (gc) and average midday sur-face to air vapor pressure deficit (Do) for 1995. The linerepresents a power function fit to the data using nonlinearleast-squares regression.

of net CO2 uptake per unit PPFD began to decline (Fig.6).

The net CO2 flux vs. PPFD relationship described bythe rectangular hyperbolic model (see Methods: Dataanalysis) explained between 60 and 90% of the vari-ation in diel net CO2 exchange (Table 2). The modelcoefficients, estimated quantum yield (a), maximumgross CO2 assimilation at saturating PPFD (F`), anddark respiration rate (Rd) varied substantially both with-in and between growing seasons (Table 2). In 1994,mean a (6 1 SD) increased from a late-June value of0.01 6 0.003 mmol CO2/mmol PPFD to a late-July peakof 0.026 6 0.007 mmol CO2/mmol PPFD, and decreasedonly marginally thereafter (Table 2). By contrast, a in1995 increased from 0.018 6 0.006 mmol CO2/mmolPPFD in early June to a peak of 0.031 mmol CO2/mmolPPFD in early July, and decreased to a seasonal min-imum value in late August (Table 2). Similarly, meanF` (61 SD) in 1994 was 2.38 6 0.04 mmol·m22·s21

between 16 and 30 June in 1994, with the seasonal

peak (7.92 6 2.91 mmol·m22·s21) in late August (Table2). In 1995, F` was nearly 4 mmol·m22·s21 in early June,reached a seasonal peak of 9 mmol·m22·s21 in late July,and decreased to 3.75 mmol·m22·s21 in late August (Ta-ble 2). Early-season (16–30 June) Rd was 0.8 6 0.21mmol·m22·s21 in 1994 and 1.3 6 0.9 mmol·m22·s21 in1995 (Table 2). Estimated Rd peaked at ;2.2mmol·m22·s21 in July for both growing seasons, anddecreased throughout August (Table 2).

The seasonal pattern of net CO2 exchange was qual-itatively similar to the diel pattern (Fig. 7A, B). The1995 data indicate that the moist-tussock tundra eco-system was a small net source following snowmelt inearly June (Fig. 7B). Net sink activity increased rapidlybetween mid-June and early July during both years,with a peak net sink of on average 20.14 mol·m22·d21

occurring around 15 July (Fig. 7A, B). Sink strengthdecreased rapidly after mid-July, and in early to mid-August the ecosystem was a small net source of onaverage 0.02 mol·m22·d21 (Fig. 7A, B). The net dailysource activity increased to as much as 0.06mol·m22·d21 as the growing season came to a close.The seasonal pattern of average daily PPFD (Fig. 7C,D) was qualitatively similar to the seasonal pattern inaverage daily net radiation (Fig. 2C, D). Average dailyPPFD was typically highest throughout the month ofJune, followed by a gradual decrease as the growingseason progressed.

The simple phenomenological model (Eq. 2) relatingnighttime net CO2 flux (Fn) to variations in averagenighttime air temperature and water-table depth ex-plained between 67 and 71% of the variation in Fn

during 1994 and 1995, respectively, and ;65% of the


FIG. 5. The average diel trend in net CO2 flux between 16 June and 31 August 1994 and between 1 June and 31 August1995. Each point represents an instantaneous average of net CO2 flux (61 SD) calculated over a 2-wk interval. Positive valuesindicate net loss of CO2 to the atmosphere, while negative values indicate net uptake of atmospheric CO2 by the ecosystem.

variation in Fn averaged for both growing seasons (Ta-ble 3). The absolute rate of Fn increased as water-tabledepth increased, and the largest relative increase oc-curred at water-table depths of 0–15 cm (Fig. 8). Aswater-table depth increased, Fn at any given tempera-ture was larger than at lower water-table depths; how-ever, the relative increase in Fn declined as water-tabledepth increased from 15 to 30 cm (Fig. 8).

Assuming that Fn is indicative of whole-ecosystemrespiration (R) (Ruimy et al. 1995), the phenomeno-logical models developed for a given year (Table 3)were applied to the average daily air temperature andwater-table depth data to provide an estimate of averagedaily R for each growing season (Fig. 9). Estimated Rin 1994 was lowest in early June, but increased steadily

to a seasonal peak of ;3.8 mmol·m22·s21 in early Au-gust (Fig. 9A). Similarly, estimated R in 1995 increasedfrom a seasonal minimum of ,1 mmol·m22·s21 in earlyJune to a seasonal peak of ;3.4 mmol·m22·s21 in mid-July (Fig. 9A). Before 20 July, estimated R was onlyslightly higher in 1995 compared to 1994, in spite ofthe lower water table (Fig. 9B) and generally highertemperatures observed in 1995 (Fig. 9C). After 20 July,estimated R was substantially larger in 1994 comparedto 1995, due to the combination of lower water-tabledepth (Fig. 9B) and higher average daily air temper-atures (Fig. 9C).

Seasonal summaryThe moist-tussock tundra ecosystem was a sink for

atmospheric CO2 during both growing seasons. Assum-


FIG. 6. The relationship between diel net CO2 exchangeand photosynthetic photon flux density (PPFD) for 1994 and1995 between 1 and 7 July. Each point represents an instan-taneous average of net CO2 flux and PPFD calculated between1 and 7 July. The lines represent rectangular hyperbolic func-tions fit to the data using nonlinear least-squares regression(see Eq. 1; Methods: Data analysis).

TABLE 2. Coefficients and goodness of fit (R2) estimates for the rectangular hyperbolic model of diurnal net CO2 flux as afunction of the diurnal fluctuations in photosynthetic photon flux density (PPFD) (Eq. 1; Methods: Data analysis) calculatedover 2-wk intervals. Data represent means 6 1 SD; n 5 number of days averaged over each 2-wk interval.

Dates n a (mmol/mmol) F` (mmol·m22·s21) Rd (mmol·m22·s21) R2

199416–30 June1–15 July


16–31 August

12111514

7

0.010 6 0.0030.025 6 0.0130.026 6 0.0070.020 6 0.0090.020 6 0.005

2.38 6 0.045.78 6 1.727.25 6 2.796.72 6 2.857.92 6 2.91

0.83 6 0.212.02 6 0.672.13 6 0.411.99 6 0.521.77 6 0.37

0.80 6 0.110.80 6 0.180.84 6 0.100.82 6 0.110.80 6 0.11

19951–15 June

16–30 June1–15 July


16–31 August

713131513

8

0.018 6 0.0060.024 6 0.0200.031 6 0.0130.024 6 0.0110.016 6 0.0070.009 6 0.005

3.92 6 1.155.40 6 2.188.58 6 3.508.99 6 5.745.26 6 3.273.76 6 3.61

1.18 6 0.261.33 6 0.882.24 6 0.871.93 6 0.991.34 6 0.600.92 6 0.35

0.84 6 0.080.78 6 0.130.80 6 0.100.90 6 0.070.72 6 0.230.60 6 0.12

Notes: Coefficients refer to the estimated quantum yield (a), maximum rate of gross ecosystem assimilation at saturatingPPFD (F`), and the estimated rate of respiration at PPFD 5 0 (dark respiration rate, Rd). Coefficients and R2 values weredetermined using nonlinear least-squares regression.

ing an 81-d season in 1994 (11 June–31 August), theecosystem was a net CO2 sink of 23.3 mol/m2 (Table4). Similarly, the ecosystem was a net sink of 24.6mol/m2 during the 90-d (1 June–31 August) 1995 grow-ing season (Table 4). Average daily rates of net CO2

flux in 1994 were 20.51 mmol·m22·s21 (with a rangeof 21.76–0.78 mmol·m22·s21), compared to 20.58mmol·m22·s21 (22.00–0.73 mmol·m22·s21) in 1995 (Ta-ble 4). Estimated seasonal respiration (integrated overa 81- and 90-d growing season for 1994 and 1995,respectively) was 15.5 mol/m2 in 1994 and 13.5 mol/m2 in 1995 (Table 4). Average daily estimated respi-

ration rates were 2.33 mmol·m22·s21 (0.79–3.77mmol·m22·s21) in 1994 and 1.75 mmol·m22·s21 in 1995(0.17–3.37 mmol·m22·s21) (Table 4).

Seasonal evapotranspiration (ET) was 103 and 149mm in 1994 and 1995, respectively, while average dailyET was on average 1.54 mm/d during both growingseasons (Table 4). Total seasonal rainfall in 1995 wasnearly 3.5 times higher than in 1994 (474 vs. 138 mmfor 1995 and 1994, respectively), and 1994 was warmerthan 1995 based on cumulative thaw degree-days (airtemperature sum of average daily temperatures .08C)and average daily temperature (Table 4). Average dailyPPFD was on average 377 mmol·m22·s21 during bothgrowing seasons, however, maximum average dailyPPFD was 122 mmol·m22·s21 higher in 1994 than in1995 (Table 4). The warmer temperature observed in1994 did not lead to deeper active layer depth, as bothaverage and maximum active layer depth in 1995 were20–35% deeper than in 1994 (Table 4). The higherrainfall observed in 1995 resulted in only a slightlyhigher water table in 1995 (average difference 5 2.3cm), however, the maximum water-table depth in 1995was nearly 50% of that observed in 1994 (Table 4).

DISCUSSION

Meteorological and physiological controls onevapotranspiration

Evapotranspiration (ET) rates varied substantiallyover the course of each growing season, due to in partto meteorological and biological limitations to water-vapor flux. The observed positive correlation betweennet radiation (Rn) and ET is well known (Monteith1973, Jarvis 1976, Jarvis and McNaughton 1986). Inaddition to supplying the energy required for convert-ing liquid water to water vapor, increases in Rn resultin a steeper surface-to-air vapor pressure deficit (Do),which increases the atmospheric demand for water va-por and thus the rate of ET when surface water is non-


FIG. 7. The seasonal trend in daily integrated net CO2 flux (A and B) and average daily photosynthetic photon flux density(PPFD) (C and D) measured during the 1994 (left panels) and 1995 (right panels) growing seasons. The cross (3) symbolsand dashed lines depict the daily integrated value of net CO2 flux, and the average daily values of PPFD, while the closedboxes and solid lines depict a 7-d running mean.

TABLE 3. Coefficients and goodness of fit (R2) statistics ofthe phenomenological model relating nighttime net CO2

flux (Fn) to variations in average nighttime air temperatureand water-table depth (Eq. 2; Methods: Data analysis).

Season n a b c d R2

19941995

3441

301.06132.49

40.9021.47

26.7716.15

0.04250.0629

0.670.71

Mean 75 123.19 16.22 17.36 0.0506 0.65

Notes: Coefficients and R2 values were estimated using non-linear least-squares regression (model after Bunnell et al.[1977]).

limiting (Monteith 1973). As surface water decreases,surface evaporation rates also decline, and the contri-bution of vascular and nonvascular plant transpirationbecomes relatively more important in constrainingrates of ET (Slatyer 1967, Monteith 1973, Jarvis 1976,Jarvis and McNaughton 1986). If plants are water lim-ited, stomatal conductance to water loss (gs) declinesas Do increases, leading to reductions in leaf and whole-plant transpiration rates (Slatyer 1967, Monteith 1973,Jarvis 1976, Jarvis and Mansfield 1981, Schulze and

Hall 1982, Jarvis and McNaughton 1986, Grantz andMeinzer 1991). Although bulk canopy conductance (gc)may not be synonymous with gs (Baldocchi et al. 1991),the reduction in gc to increased evaporative demand(e.g., Do) observed here is qualitatively similar to thatobserved for gs at the leaf scale (Slatyer 1967, Schulzeand Hall 1982, Grantz and Meinzer 1991), implyingthat biological limitations to water-vapor flux were im-portant in constraining rates of ET under conditions ofhigh evaporative demand.

The biological limitation to ET may have been duein part to limitations to bryophyte transpiration. Anestimated 65–85% of ET is derived from moss surfaces(Miller et al. 1976, Stuart et al. 1982), and althoughthe relative contribution of bryophyte transpiration toET is unknown, transpiration rates of bryophytes canbe high due to the small resistance to water loss (Oecheland Sveinbjornsson 1978). Furthermore, leaf resistanceto water loss increases exponentially as tissue watercontent decreases, and since bryophytes rapidly des-iccate between rainfall or dewfall events, the bryophytesurface represents a potentially large resistance to ET


FIG. 8. The response surface of average nighttime net CO2

efflux (Fn; z-axis) as a function of average nighttime air tem-perature (y-axis) and water-table depth (x-axis) for 1994 and1995 combined (R2 5 0.65, n 5 75; see Table 3). Data aredisplayed as closed circles, and the response surface wascalculated using Eq. 2 (see Methods: Data analysis).

under dry surface conditions (Oechel and Sveinbjorns-son 1978). Paradoxically, seasonal variations in V (Fig.3) and the Bowen ratio (ß; Table 1) indicate that thelargest potential biological limitation to ET occurredin June, when a substantial surface-water pool is cre-ated from melting snow (Kane et al. 1990, Kane 1996)and the water table was highest (Fig. 9B). However,pooling of meltwater following snowmelt (e.g., earlyJune) was never observed, and since the majority ofthe summer precipitation during 1994–1995 fell be-tween July and August, it is conceivable that the sur-face moss layer was relatively dry in June.

The relatively large interannual variation in evapo-transpiration (103 and 150 mm for 1994 and 1995,respectively; see Table 4) may be due to the fact thata portion of the 1994 seasonal ET was not accountedfor, and/or the higher precipitation observed during1995 led directly to higher rates of ET. Unfortunately,it is impossible to eliminate either possibility with theinformation available. Given the same average radia-tion regime (see Tables 1 and 4), it is likely that thehigher precipitation observed in 1995 led directly tohigher seasonal ET. However, the 3.5-fold higher pre-cipitation in 1995 failed to result in a proportional in-crease in ET. Although seasonal ET is generally higherduring wet years, the distribution of precipitationevents is critical for determining the fraction of pre-cipitation in runoff and ET (Kane 1996). Infrequentand/or heavy precipitation events (such as those ob-served in 1995) are conducive to higher runoff, whilefrequent and/or light precipitation events (e.g. 1994)are conducive to higher rates of ET (Kane 1996). It isinteresting to note that a greater proportion of precip-itation was consumed by ET in 1994 (;75%) comparedto only 32% in 1995. Therefore, although seasonal ET

was higher in 1995, proportionally more precipitationmust have been exported as runoff or stored as soilwater (as observed by the higher water table in August;see Fig. 9B).

Meteorological and physiological controls of netCO2 exchange

Diel variations in net CO2 exchange were largelycontrolled by diel variations in photosynthetic photonflux density (PPFD). The response of net CO2 flux tovariations in PPFD followed a rectangular hyperbolicfunction, a result that has been reported in leaf-scaleobservations of photosynthesis in arctic vascular plants(Tieszen 1973, Limbach et al. 1982), bryophytes(Oechel and Sveinbjornsson 1978, Sveinbjornsson andSonesson 1996), and in plot-scale studies of arctic andsubarctic tundra ecosystems (Whiting 1994, Oechel etal. 1995).

The coefficients of the hyperbolic model (see Meth-ods: Data analysis) have a firm physiological basis(Thornley 1976, Bjorkman 1981, Larcher 1995), andthus are useful for interpreting the seasonal variationsin ecosystem photosynthetic capacity. At low light in-tensities, net photosynthesis increases linearly with ab-sorbed PPFD (Bjorkman 1981, Larcher 1995). Theslope of this portion of the net assimilation vs. incidentPPFD curve is the apparent quantum yield (a), or thephotosynthetic efficiency, which varies as a functionof leaf (and/or ecosystem) chlorophyll content and pho-tosynthetically active leaf area (Bjorkman 1981, Tera-shima and Saeki 1985, Evans et al. 1993, Larcher1995). At high light intensities, net CO2 assimilationis relatively more limited by enzymatic processes in-volved in CO2 fixation; thus, the maximum rate of grossCO2 assimilation under saturating light (F`) is indic-ative of the development and capacity of the CO2 fix-ation apparatus, such as the amount and activity ofRuBP carboxylase (RUBISCO) and/or the developmentof sinks for assimilated CO2 (Bjorkman 1981, Larcher1995).

The seasonal variations in a and F` were approxi-mately normally distributed over the 1995 growing sea-son, with a seasonal peak in early July; in 1994, a andF` reached a seasonal peak later in the growing season(see Table 2). Covariance in the seasonal variations ofa and F` is expected if one assumes close couplingbetween light absorption and photosynthetic capacity,as both the light-harvesting and CO2-fixation compo-nents are costly to synthesize and involve the allocationof limiting resources (e.g., N) for the production ofbiomass, leaf area, chlorophyll, and RUBISCO (Larch-er 1995). The observed seasonal trends in a and F` aresimilar to the seasonal trends observed for spectral re-flectance (G. L. Vourlitis et al., unpublished manu-script; W. C. Oechel et al., unpublished manuscript; W.Boynton and A. S. Hope, unpublished data) and leafarea development (Tieszen 1972, 1975, Murray andMiller 1982) of Alaskan arctic tundra ecosystems.


FIG. 9. (A) Estimated average daily whole-ecosystem res-piration rate calculated from the phenomenological model(see Methods: Data analysis), (B) average water-table depth,and (C) average daily ambient temperature for 1994 and 1995.Data for water-table depth are means 6 1 SE (n 5 12 waterwells).

Thus, the rate and pattern of seasonal green-leaf andbiomass development represent important controls onthe photosynthetic efficiency and capacity of moist-tussock tundra ecosystems during the short arctic grow-ing season.

Diel and seasonal variations in temperature and soilwater content play an important role in net CO2 ex-change (Tieszen 1973, Limbach et al. 1982, Billings etal. 1982, Oberbauer et al. 1991, 1992, Oechel et al.1995). Diel variations in temperature are thought to

affect net photosynthesis minimally, because arcticplants have a broad range in the temperature optimumfor photosynthesis (Tieszen 1973, Limbach et al. 1982),and in the case of arctic bryophytes, a capacity to ac-climate the photosynthetic temperature optimum tochanges in mean temperature (Oechel and Sveinbjorns-son 1978, Sveinbjornsson and Sonesson 1996). Vari-ations in temperature, however, affect the rate of bothplant and microbial respiration, and respiration ratesoften respond exponentially to increases in temperature(Peterson and Billings 1975, Billings et al. 1977, Bun-nell et al. 1977, Ruimy et al. 1995). Variations in soilwater content also affect the rate of microbial respi-ration (Billings et al. 1982, Funk et al. 1994, Oecheland Vourlitis 1995, Johnson et al. 1996, Oechel et al.1998a), and the shape of the microbial response curveto variations in soil water content is often observed tobe an optimum function (Bunnell et al. 1977).

Although whole-ecosystem respiration (R) cannot bedirectly quantified using eddy covariance techniques,the observed nighttime net CO2 flux (Fn) is a usefulsurrogate (Ruimy et al. 1995). The phenomenologicalmodel utilized in this study (Eq. 2; see Methods: Dataanalysis) indicates that Fn increases exponentially withtemperature and decreases as water-table depth ap-proaches the soil surface. Both the absolute rate andthe temperature sensitivity of Fn increased as water-table depth increased, and the largest relative increaseoccurred as water-table depth increased up to 15 cmbelow the soil surface (Fig. 8). These results are con-sistent with the field and laboratory studies describedabove, and suggest that mechanisms important for con-trolling plot-scale R (e.g., Peterson and Billings 1975,Billings et al. 1982, Oberbauer et al. 1991, 1992, Oech-el et al. 1995) are qualitatively similar to those con-trolling hectare-scale Fn. These results also indicatethat the extrapolation of Fn to provide estimates of Ris appropriate, even though Fn may not be strictly syn-onymous with R during daytime periods (Ruimy et al.1995).

The two methods for estimating whole-ecosystemrespiration (Rd from Eq. 1, and R inferred from Fn cal-culated using Eq. 2) provided substantially differentestimates of ecosystem respiration. Dark respiration (Rd

5 R when PPFD 5 0) is affected by both temperatureand biomass because it contains microbial and plantmaintenance components (Ruimy et al. 1995); however,it does not account for daytime variations in R that inpart are affected by variations in temperature (Ruimyet al. 1995). The estimate of R calculated from therelationship of Fn as a function of water-table depthand temperature (Eq. 2) also contains a microbial andplant respiratory component; however, this estimate at-tempts to account for the diel temperature- and mois-ture-induced variations in microbial and plant respi-ration (Ruimy et al. 1995). Therefore, R and Rd are notstrictly synonymous(see Table 2 and Fig. 9), and sincevariations in temperature and moisture are known to


TABLE 4. Seasonal summary of physiological and meteorological characteristics of the HappyValley, Alaska, moist-tussock tundra ecosystem during the 1994 and 1995 growing season(1 June–31 August). Negative CO2 flux indicates that the ecosystem was a net sink foratmospheric CO2.

1994 1995

Seasonal totalsNet CO2 flux (mol/m2)†Estimated respiration (mol/m2)†,‡Thaw degree-days (8C)Total evapotranspiration (mm)Total precipitation (mm)§

23.315.5

945103138

24.613.5

820149474

Mean daily (minimum, maximum) valuesNet CO2 flux (mmol·m22·s21)Estimated respiration (mmol·m22·s21)‡Evapotranspiration (mm/d)Soil surface temperature (8C)\Air temperature (8C)\Daily PPFD (mmol·m22·s21)Active layer depth (cm)Water-table depth (cm)

20.51 (21.76, 0.78)2.33 (0.79, 3.77)1.51 (0.19, 3.06)

11.0 (21.7, 21.0)11.6 (22.8, 20.4)

396 (83, 793)23.0 (7.3, 37.7)16.0 (9.5, 27.2)

20.58 (22.00, 0.73)1.75 (0.17, 3.37)1.56 (0.29, 2.91)

10.7 (0.8, 20.5)9.7 (21.7, 18.7)

358 (83, 671)31.2 (7.0, 45.0)13.7 (4.7, 18.3)

† The seasonal integration period was 81 d (11 June–31 August) and 90 d (1 June–31 August)for 1994 and 1995, respectively.

‡ Respiration was estimated using Eq. 2 (see Methods: Data analysis).§ Data for 1994 are from Imnaviat Creek (D. L. Kane et al., unpublished data), located 50

km south-southeast from the study site.\ Soil surface temperature was measured between 0 and 2 cm below the surface moss layer.

Air temperature was measured at 2 m above ground level.

be important in controlling rates of diel and daily R,the R estimated from Fn is probably more indicative ofthe actual R than Rd.

Although there were undoubtedly additional impor-tant factors controlling interannual variations in netCO2 flux that were not quantified during this study (e.g.,nutrient availability), the observed interannual differ-ences in net CO2 flux were almost completely explainedby the interannual differences in estimated R. Whenintegrated over a comparable period of time (e.g., 81d between 11 June and 31 August), the estimated sea-sonal R in 1995 was 20% lower than the estimatedseasonal R in 1994 (12.6 mol/m2 in 1995 vs. 15.5 mol/m2 in 1994), while the observed seasonally integratednet CO2 sink in 1995 was 23% higher than in 1994(24.3 mol/m2 in 1995 vs. 23.3 mol/m2 in 1994).

Comparison to other studies

Average daily rates of evapotranspiration (ET) ob-served at Happy Valley during the 1994–1995 growingseasons (Table 4) are comparable to those reported inthe literature. Seasonal ET for other arctic and subarcticmoist-tussock tundra ecosystems is reported to varybetween 92 and 242 mm (Stuart et al. 1982, Kane etal. 1990, Fitzjarrald and Moore 1992), and our estimateof 149 mm per season for 1995 is nearly identical tothe 142 mm per season reported for Imnaviat Creek,Alaska (Kane et al. 1990), located 50 km south-south-east of Happy Valley.

Earlier estimates of terrestrial net C balance basedon harvest measurements indicate that Alaskan moist-tussock tundra ecosystems were net sinks of 21.9mol·m22·yr21 during the early to mid-1970s (Miller et

al. 1983), comparable to the estimates reported here.However, results obtained from recent plot-scale fluxmeasurements of moist-tussock tundra ecosystems atToolik Lake, Alaska (1983–1993) and Happy Valley(1990–1991), indicate that these ecosystems were netsources of on average 12 mol/m2 during the summergrowing season (Grulke et al. 1990, Oechel et al. 1993,Oechel and Vourlitis 1995, Tenhunen et al. 1995; W.C. Oechel et al., unpublished data). The discrepancybetween the eddy covariance estimates reported hereand the recent plot-scale estimates showing a net sea-sonal source are probably not due to methodologicaldifferences in net CO2 flux sampling, because net CO2

flux estimates of arctic tundra ecosystems derived fromsimultaneous chamber and eddy covariance measure-ments are quite similar (Fan et al. 1992, Whiting et al.1992, Oechel et al. 1995, 1998b).

When the long-term (e.g., 25-yr) net CO2 flux andmeteorological record are assessed, the pattern thatemerges is one of sink activity during the cool, wet1970s, net source activity during the warm, dry 1980s,and a gradual return to sink activity during the warmand comparatively dry 1990s (W. C. Oechel et al., un-published data). The return to sink activity may be duein part to interannual differences in soil water contentand temperature, or longer term adjustment of ecosys-tem physiology, plant community composition, andbiogeochemical processes following climate change(Oechel and Billings 1992, Shaver et al. 1992, Oecheland Vourlitis 1994, Chapin et al. 1995, Jonasson 1996,Nadelhoffer et al. 1996, Rastetter et al. 1996, Wael-broeck et al. 1997). These patterns reflect terrestrial netCO2 exchange only, and when CO2 and dissolved C


losses from lakes and streams are taken into account,the net sink strength of tundra landscapes will be re-duced (Kling et al. 1991).

ACKNOWLEDGMENTS

This research was supported by the National Science Foun-dation, Arctic Systems Science, Land–Atmosphere–Ice–In-teractions Program (OPP-9216109). Logistic support wasprovided by personnel from the Polar Ice Coring Office ofthe University of Alaska, Fairbanks (1994) and the Universityof Nebraska, Lincoln (1995); the Institute of Arctic Biology,University of Alaska, Fairbanks; and the Piquniq Manage-ment Corporation and the North Slope Borough. G. Vourlitisthanks the Achievement Rewards for College Scientists(ARCS) Foundation for three years of financial and moralsupport. The authors thank the Alaska Department of NaturalResources for allowing us to conduct this research at HappyValley. Field assistance from Melissa Vourlitis, Steve Has-tings, Pablo Bryant, Richard Ault, and Rommel Zulueta ofSan Diego State University (SDSU), and technical expertisefrom Timothy Crawford, Tilden Meyers, and Robert Mc-Millen (NOAA-ATDD) are gratefully acknowledged. The au-thors thank Tagir Gilmanov, Viktor Nosov, Tom Ebert, andAllen Hope of SDSU, Kyaw Tha Paw U (University of Cal-ifornia, Davis), and three anonymous reviewers for review ofearlier versions of this manuscript.

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EDDY COVARIANCE MEASUREMENTS OF CO 2 AND ENERGY FLUXES OF AN ALASKAN TUSSOCK TUNDRA ECOSYSTEM