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Ecological Engineering 37 (2011) 40–53
Contents lists available at ScienceDirect
Ecological Engineering
journa l homepage: www.e lsev ier .com/ locate /eco leng
ynamics of gaseous nitrogen and carbon fluxes in riparian alder forests
aido Soosaara, Ülo Mandera,∗, Martin Maddisona, Arno Kanala, Ain Kull a, Krista Lõhmusb,aak Truuc, Jürgen Augustind
Department of Geography, Institute of Ecology and Earth Sciences, University of Tartu, 46 Vanemuise St., 51014 Tartu, EstoniaDepartment of Botany, Institute of Ecology and Earth Sciences, University of Tartu, 40 Lai St., 51005 Tartu, EstoniaInstitute of Molecular and Cell Biology, University of Tartu, 23 Riia St., 51010 Tartu, EstoniaInstitute of Landscape Matter Dynamics, Leibniz-Centre for Agricultural Landscape and Land Use Research (ZALF), D-15374 Müncheberg, Germany
r t i c l e i n f o
rticle history:eceived 2 March 2010eceived in revised form 26 July 2010ccepted 26 July 2010
eywords:arbon dioxideenitrificationinitrogenlobal warming potentialethaneitrous oxide
a b s t r a c t
We studied greenhouse gas (GHG) fluxes in two differently loaded riparian Alnus incana-dominatedforests in agricultural landscapes of southern Estonia: a 33-year-old stand in Porijõgi, in which the uphillagricultural activities had been abandoned since the middle of the 1990s, and a 50-year-old stand inViiratsi, which still receives polluted lateral flow from uphill fields fertilized with pig slurry. In Pori-jõgi, closed-chamber based sampling lasted from October 2001 to October 2009, whereas in Viiratsithe sampling period was from November 2003 to October 2009. Both temporal and spatial variationsin all GHG gas fluxes were remarkable. Local differences in GHG fluxes between micro-sites (“Edge”,“Dry” and “Wet” in Porijõgi, and “Wet”, “Slope” and “Dry” in Viiratsi) were sometimes greater than thosebetween sites. Median values of GHG fluxes from both sites over the whole study period and all micrositesdid not differ significantly, being 45 and 42 mg CO2–C m−2 h−1, 8 and 0.5 �g CH4–C m−2 h−1, 1.0 and2.1 mg N2–N m−2 h−1, and 5 and 9 �g N2O–N m−2 h−1, in Porijõgi and Viiratsi, respectively. The N2:N2Oratio in Viiratsi (40–1200) was lower than in Porijõgi (10–7600). The median values-based estimation ofthe Global Warming Potential of CH4 and N2O was 19 and 185 kg CO2 equivalents (eq) ha−1 yr−1 in Porijõgiand −14 and 336 kg CO2 eq ha−1 yr−1 in Viiratsi, respectively. A significant Spearman rank correlation wasfound between the mean monthly air temperature and CO2, CH4 and N2 fluxes in Porijõgi, and N2O flux
in Viiratsi, and between the monthly precipitation and CH4 fluxes in both study sites. Higher groundwa-ter level significantly increases CH4 emission and decreases CO2 and N2O emission, whereas higher soiltemperature significantly increases N2O, CH4 and N2 emission values. In Porijõgi, GHG emissions did notdisplay any discernable trend, whereas in Viiratsi a significant increase in CO2, N2, and N2O emissionshas been found. This may be a result of the age of the grey alder stand, but may also be caused by thelong-term nutrient load of this riparian alder stand, which indicates a need for the management of similarer st
nasrs2
heavily loaded riparian ald
. Introduction
Riparian buffer zones, as the interface between terrestrial andquatic components of the landscape, are important ecotech-ological measures to control water quality in agriculturalatchments (Kuusemets and Mander, 1999) and provide otherandscape-ecological functions (Mander et al., 2005a). The water
urification effect of riparian ecosystems has been thoroughlytudied (Lowrance et al., 1983; Peterjohn and Correll, 1984;aycock and Pinay, 1993; Vought et al., 1994; Mander et al.,995, 1997a), yet their role as greenhouse gas (GHG) sources∗ Corresponding author. Tel.: +372 7 375816; fax: +372 7 375825.E-mail address: [email protected] (Ü. Mander).
pSNsfb1t
925-8574/$ – see front matter © 2010 Elsevier B.V. All rights reserved.oi:10.1016/j.ecoleng.2010.07.025
ands.© 2010 Elsevier B.V. All rights reserved.
eeds to be better understood (Groffman et al., 1991; Teiternd Mander, 2005; Mander et al., 2008). According to certaintudies, water purification efficiency may be less favorable iniparian zones, which function as hotspots of greenhouse gas emis-ions with high global warming potential (GWP; Groffman et al.,000).
Our literature study, which considered scientific peer-reviewedapers published in 1980–2009 and indexed by the ISI Web ofcience, shows that there are several investigations on CH4 and2O fluxes but only a very few studies that analyse CO2 emis-
ion in riparian ecosystems. The emission rate of CO2 can varyrom 20.6 kg CO2–C ha−1 yr−1 in semiarid sub-tropical riparianush and grassland vegetation (McLain and Martens, 2006) to1,400 kg CO2–C ha−1 yr−1 in a temperate riparian poplar planta-ion (Tufekcioglu et al., 2001; Table 1).
K. Soosaar et al. / Ecological Engineering 37 (2011) 40–53 41
Table 1Minimum and maximum observed emission of carbon dioxide, methane and nitrous oxide in riparian buffer zones.
References Country Ecosystem type Emission data in reference Annual emission(kg ha−1 yr−1)
Comments
Value Unit
Carbon dioxide (CO2)McLain andMartens,2006
USA Riparian bush(mesquite & grassland(sacaton + forbs)
235.6 �g C m−2 h−1 20.6 Averagevalue
Tufekciogluet al., 2001
USA Riparian buffer zone,poplars
1140 g C m−2 yr−1 11,400 Averagevalue
Methane (CH4)Hopfenspergeret al., 2009
USA Riparian northernhardwood forest
−1.4 to 3.6 mg C m−2 d−1 −5.3 to 13.3 Range
Altor andMitsch,2006
USA Created riparianmarshes, permanentlyinundated zone
42 g C m−2 yr−1 420 Annualaveragevalue
Nitrous oxide (N2O)Dhondt et Belgium Riparian mixed −0.5 to 0.4 mg N m−2 d−1 −1.8 to 1.5 Range
rCrlr
sgi(s2Heu2t(
(nbraGHhN2v222
srA1esi
iae
cnhsebMtNhp
r(a2hc2
catt(G
2
2
u
al., 2004 forest-grass vegetationSchipper etal., 1993
New Zealand Riparian grassland(intensively managed)
73
Methane flux varies from −5.3 kg CH4–C ha−1 yr−1 in a northerniparian hardwood forest (Hopfensperger et al., 2009) to 420 kgH4–C ha−1 yr−1 in the permanently inundated zone of a creatediparian marsh (Altor and Mitsch, 2006; Table 1). Pulsing hydro-ogical regime significantly decreases the methane emission fromiparian wetlands (Altor and Mitsch, 2006).
Nitrous oxide flux appears to be the greatest among the GHGtudied: from −1.8 kg N2O–N ha−1 yr−1 in riparian mixed forest-rass vegetation (Dhondt et al., 2004) to 6390 kg N2O–N ha−1 yr−1
n an intensively managed riparian grassland in New ZealandSchipper et al., 1993; Table 1). Riparian created marshes showedignificantly lower N2O emissions (Hernandez and Mitsch, 2006,007) than natural fens and grasslands (see Blicher-Mathiesen andoffmann, 1999; Burt et al., 1999; Van Beek et al., 2004; Oehlert al., 2007). Alder stands showed the highest N2O emission val-es of riparian forests (Teiter and Mander, 2005; Hefting et al.,006; Mander et al., 2008). The percentage of N2O flux of N inputo the riparian ecosystem varied from 0.02% in a riparian wetlandJacinthe et al., 1998) to 5.5% in a riparian forest (Jordan et al., 1998).
Denitrification, as the microbial reduction of nitrate–NNO3
−–N) to nitrite–N (NO2−–N) and further to the gaseous forms
itric oxide (NO), (nitrous oxide) N2O and N2 (Knowles, 1982), haseen found in numerous studies to be a significant process in Nemoval in riparian buffer zones (Groffman et al., 1991; Ambusnd Christensen, 1993; Hanson et al., 1994; Weller et al., 1994;old et al., 1998; Hefting and de Klein, 1998; Groffman et al., 2000;efting et al., 2003). In the majority of these studies, N2O fluxesave been measured, while only a few studies pay attention to2 emission (Watts and Seitzinger, 2000; Butterbach-Bahl et al.,002; Teiter and Mander, 2005). The N2–N emission from forestsary from 0.9 kg ha−1 yr−1 in a beech forest (Wolf and Brumme,003) and 7 ± 0.7 kg ha−1 yr−1 in a spruce forest (Kreutzer et al.,009) to 1200 kg ha−1 yr−1in riparian alder forests (Mander et al.,008).
Both denitrification and CH4 formation depend on the oxygentatus of the soil or sediment. As a result, the spatial and tempo-al variability of fluxes of both N2O (Robertson and Tiedje, 1984;
mbus and Christensen, 1993; Augustin et al., 1998; Gold et al.,998; Groffman et al., 1998; Jacinthe et al., 1998) and CH4 (Saarniot al., 1997; Willison et al., 1998) are high. Denitrification rates inoils are mainly influenced by carbon availability, NO3− availabil-ty, temperature and pH (Nommik, 1956; Knowles, 1982). Methane
Sttifi
mg N m−2 h−1 6390 Averagevalue
s produced in anoxic soils and sediments, while well-drained soilsct as a sink for atmospheric CH4 due to CH4 oxidation, throughither ammonia oxidizers or methanotrophs (Hanson et al., 1994).
Alders are typical tree species in riparian zones (known asommon species of symbiotic dinitrogen (N2) fixing bacteria (acti-obacteria) from the Frankia group (Rytter et al., 1989). Due toigh rates of N2 fixation, some authors have seen alder forests asources of water body pollution with excess nitrogen (N) (Binkleyt al., 1992). Several other studies consider riparian alder stands toe effective N removal ecosystems (Mander et al., 1995, 1997a,b;ander et al., 2008). This contradiction is mainly due to the posi-
ion of alder stands in the landscape: in riparian zones the excessis mainly denitrified, whereas in the more aerated conditions of
igher altitude locations (see Binkley et al., 1992), leaching takeslace.
Several studies consider CO2 emissions and sequestration iniparian wetlands (Mitsch and Gosselink, 1993) and buffer zonesBrumme et al., 1999; Gulledge and Schimel, 2000; Tufekcioglu etl., 2001; Larmola et al., 2003; Scott et al., 2004; Teiter and Mander,005; von Arnold et al., 2005) Depending on meteorological andydrological conditions, riparian ecosystems, especially wetlands,an be either sources or sinks of carbon (C) (Gulledge and Schimel,000).
The main objectives of this research were: (1) to quantify andompare N2O, N2, CH4 and CO2 emission rates in two riparian greylder (Alnus incana) forests of different input loading and age, usinghe closed-chamber method and the He–O method; (2) to analyserends in GHG emissions in these two riparian buffer zones; and3) to estimate the global warming potential (GWP) of the analyzedHGs.
. Materials and methods
.1. Study sites
The Porijõgi study area represents a grey alder stand. It is sit-ated in the moraine plain of southeast Estonia (Tartu County,
irvaku; 58◦13′N, 26◦47′E), in the riparian zone of a small river,he Porijõgi, which flows in a primeval valley where agricul-ural activities ceased in 1992. The landscape study transectn this valley crosses several plant communities: an abandonedeld (last cultivated in 1992) on Planosols and Podzoluvisols; an
42 K. Soosaar et al. / Ecological Engineering 37 (2011) 40–53
F ites ing
avplbos(
iui
(tafAay
TM
ig. 1. Study transects in complex riparian buffer zones in southern Estonia. Microsroundwater observation wells. Adapted from Kuusemets et al., 2001.
bandoned cultivated grassland (last mown in 1993) on Collu-ic Albeluvisol (dominated by Dactylis glomerata and Alopecurusratensis); an 11-m wide wet grassland on Gleysol (two paral-el communities, one dominated by Filipendula ulmaria, anothery Aegopodium podagraria), and a 20-m wide grey alder standn Thapto-Mollic (Endogleic) Gleysol. In the grey alder stand, 3ites: Edge, Wet and Dry were chosen for gas and soil analyses
Fig. 1).The Viiratsi study area (Viljandi County, 58◦20′N, 25◦39′20′′E)s situated in the Sakala uplands, consisting of moraine hills andndulated plains with a variety of glacial deposits. The transect
s located on the moraine plain in the vicinity of a pig farm
w(ets
able 2ain soil characteristics of riparian study sites.
Study sites andmicro-sites
Soil type Depth ofA-horizon(m)
Averagegroundwa-ter tabledepth (m)
pH K
Porijõgi Wet Thapto-mollic Gleysol 0.35 0–0.09 6.5Porijõgi Dry Thapto-mollic Endogleyic
Umbrisol0.25 0.20–0.95 6.3
Porijõgi Edge Thapto-mollic EndogleyicUmbrisol
0.27 0.10–0.95 6.3
Viiratsi Wet Mollic Gleysol (pachic,colluvic)
0.45 0–0.18 4.8
Viiratsi Slope Thapto-mollic EndogleyicUmbrisol
0.30 0.2–1.2 7.0
Viiratsi Dry Thapto-mollic EndogleyicUmbrisol
0.25 0.3–1.0 7.6
Porijõgi: I – edge, II – dry, III – wet; in Viiratsi: I – wet, II – slope, III – dry. 1–5(6) –
30,000–80,000 pigs during the study). Almost all of the slurry fromhe pig farm is spread on the neighbouring fields, and the wholerea is heavily impacted by the pig slurry. The transect crosses theollowing plant communities: a cultivated field on Planosols andlbeluvisols, where slurry is spread almost every growing season;n 11-m wide strip of grassland (Elytrigia repens-Urtica dioica) andoung alder (Alnus incana) trees on Colluvic Albeluvisol; a 12-m
ide wet patch (A. incana + Filipendula ulmaria) on Mollic Gleysolconsidered as the Wet microsite) and a 28-m wide grey alder for-st on Thapto-mollic Endogleyic Umbrisol. In the grey alder stand,wo additional microsites: slope and dry, were chosen for gas andoil analyses (Fig. 1).
CL of topsoil Ntot in topsoil (%) NH4+–N in
topsoil(mg 100g−1)
NO3−–N in
topsoil(mg 100g−1)
C in topsoil(%)
0.41 1.88 0.09 4.00.80 0.33 0.14 4.5
0.32 0.61 0.11 5.3
0.13 1.72 0.08 1.4
0.56 0.58 0.14 7.6
0.76 0.42 0.15 9.1
K. Soosaar et al. / Ecological Eng
Tab
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Nu
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load
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ics
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1990
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and
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2005
b).
Site
Tota
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talp
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ph
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s
Gro
un
dw
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tco
nce
ntr
atio
ns
(mg
L−1)
Gro
un
dw
ater
outl
etco
nce
ntr
atio
ns
(mg
L−1)
Late
rali
nfl
ow(g
rou
nd
wat
er+
over
-la
nd
flow
)(k
gh
a−1yr
−1)
Late
ralo
utfl
ow(g
rou
nd
wat
er+
over
-la
nd
flow
)(k
gh
a−1yr
−1)
Gro
un
dw
ater
inle
tco
nce
ntr
atio
ns
(mg
L−1)
Gro
un
dw
ater
outl
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ntr
atio
ns
(mg
L−1)
Late
rali
nfl
ow(g
rou
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wat
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nd
flow
)(k
gh
a−1yr
−1)
Late
ralo
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rou
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wat
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ow)
(kg
ha−1
yr−1
)
Pori
jõgi
2.3
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25.6
13.2
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±0.
030.
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0.00
51.
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6V
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5.6
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52.
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4
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ineering 37 (2011) 40–53 43
The age of grey alders in Porijõgi is up to 33 years, whereas iniiratsi up to 50-year-old trees have reached their maximum age,nd many of them have died.
In both study areas, five soil samples of 50 cm3 were takent two depths (0–10 cm and 10–20 cm) from all micro-sites.ampling was carried out twice a year: in spring (May) andutumn (October). Soil pH value, organic matter (loss of igni-ion), Kjeldahl–N, NH4–N and NO3–N and lactate–soluble Poncentrations were analyzed in all soil samples using stan-ard methods (APHA, 1989). In wet microsites the groundwater
evel was higher than in other microsites. The Gleysol of theiiratsi Wet site has a significantly lower N and C concentra-
ion and lower pH value than other soils (Table 2). For a moreetailed description of soil parameters, see Kuusemets et al.2001).
The nutrient loading of the two different study areas dif-ers significantly. Due to intensive fertilization by pig slurry, thenflow concentrations of N and P in Viiratsi are about two timesigher than in the Porijõgi area of abandoned agricultural activ-
ties. Likewise, the estimated lateral N inflow (kg ha−1 yr−1) iniiratsi is twice as high as in Porijõgi, whereas the P inflow
oading is at about the same level (Table 3). In Viiratsi, fertil-zation of uphill fields with pig slurry still continues, while inorijõgi the agricultural activities in uphill fields ceased in the mid-990s.
.2. Gas sampling and analyses
The closed-chamber method (Hutchinson and Livingston, 1993)as used for the measurement of CO2, CH4 and N2O fluxes,
nd the He–O method (Butterbach-Bahl et al., 1997; Scholefieldt al., 1997; Mander et al., 2003, 2005b; Teiter and Mander,005) for the measurement of N2 emissions. Gas samplers (closedhambers with a cover made of PVC, height 50 cm, Ø 50 cm,olume 65 l, sealed with a water-filled ring on the soil sur-ace, painted white to avoid heating during application) werenstalled in five replicates at the following sites: in edge, wetnd dry positions in the Porijõgi riparian buffer zone and in wet,lope and dry positions in the Viiratsi study area (Fig. 1). Dur-ng each gas sampling session in each microsite, the depth ofhe groundwater table (cm) in observation wells (∅ 50 mm, 1.5 meep PVC pipes perforated and sealed in a lower 0.5 m part) andoil temperature was measured at 3 depths (0–10, 20–30 and0–40 cm).
Gas sampling was carried out according to the following sched-le: (1) in Porijõgi – once a month in October and November001, March, May to December 2002, January to March, July,ovember and December 2003, March 2004, April and May 2005,ovember and December 2006, April, June and August 2007,pril, May, July, August, October and November 2008, January
o October 2009; (2) in Viiratsi – once a month at the sameates as in Porijõgi, but starting in November 2003. At the endf the 1 hr measuring period, gas samples were taken fromhe enclosures of samplers with previously evacuated gas bot-les (100 ml; see Augustin et al., 1998). The soil temperature andedox potential and water depth in the sampling wells was mea-ured simultaneously, and the NH4–N and NO3–N concentrationn soil samples was analyzed using the Kjeldahl method (APHA,989).
Intact soil cores (diameter 6.8 cm, height 6 cm) for use with
he He–O method were taken from the topsoil (0–10 cm) at theas sampler sites each time gas sampling was completed. Soilamples were weighed, kept at low temperature (4 ◦C) and trans-orted to the laboratory of the Institute of Primary Productionnd Microbial Ecology of the Centre for Agricultural Landscape
44 K. Soosaar et al. / Ecological Engineering 37 (2011) 40–53
Table 4Annual and summer (May to October) precipitation and mean air temperature during winter months (December to February). Based on data from the Meteorology Stationof Tartu Observatory.
Year Yearly precipitation (mm) Summer (May to October) precipitation (mm) Mean air temperature in winter(December to February) (◦C)
2001 824 523 −2.32002 522 221 −4.02003 745 460 −7.82004 748 539 −4.02005 603 381 −3.02006 562 349 −6.52007 695 418 −2.92008 875 535 0.22009 805 514 −2.2
Fig. 2. Variation (average ± standard deviation) of CO2, CH4, N2 and N2O fluxes, and the N2:N2O ratio in the Porijõgi test site from October 2001 to October 2009. Data areaveraged over all sites within the test area.
K. Soosaar et al. / Ecological Engineering 37 (2011) 40–53 45
(Conti
actu7mflwNmwfgflscpcsLtatIet(
2
savsft(t
2
s1
Kcm2
Fig. 2.
nd Land Use Research (ZALF) in Germany. At the lab, the soilores were introduced into special gas-tight incubation vessels. Inhese vessels, N2 was removed using 3 subsequent slight evac-ation/flushing cycles with an artificial gas mixture (21.3% O2,8.6% He, 337 ppm CO2, 374 ppb N2O, 1882 ppb CH4 and approxi-ately 5 ppm N2). This was followed by the establishment of a new
ow equilibrium by continuously flushing the vessel headspaceith the gas mixture at 10 ml/min for 12 h. For the start value,2 and the greenhouse gas concentration in the gas mixture waseasured. The gas concentrations in the incubation headspaceere measured (final value) after closing the incubation headspace
or 1 h to accumulate the emission of N2 and the greenhouseases. The final accumulation value minus the start continuousow value served as the basis for the calculation of the emis-ion rates. During the flushing, the redox potential of the soilores was regularly measured and regulated so that it was com-arable with the field conditions. The gas concentration in theollected air was determined by using the gas chromatographicystem (electron capture detector and flame ionization detector;oftfield et al., 1997) in the lab of the Institute of Primary Produc-ion and Microbial Ecology at the Centre for Agricultural Landscapend Land Use Research (ZALF) in Germany. Since October 2008
he gas concentrations were measured in the laboratory of thenstitute of Technology of the University of Tartu using the samequipment as at ZALF. The procedures used for the determina-ion of the emission rates of gases are described by Mander et al.2003).aMttt
nued ).
.3. Meteorological data
Meteorological analyses are based on air temperature, mea-ured hourly and calculated daily, as well as daily, monthly andnnual precipitation from the Meteorology Station of Tartu Obser-atory (58◦15′55′′ N, 26◦27′58′′E). The station is located near bothtudy areas. In the 2001–2009 period, monthly precipitation variedrom 522 to 875 mm. During the last two years of the inves-igations, 2008 and 2009, the mean air temperature in winterDecember–February) was higher than in previous study years, andhese years also had more precipitation (Table 4).
.4. Calculations and statistical analyses
The GWP of N2O and CH4 was calculated by converting the mea-ured flux values into CO2 equivalents (eq; 1 kg CH4 = 25 kg CO2 eq;kg N2O = 296 kg CO2 eq; IPCC, 2007).
The normality of variable distributions was checked using theolmogorov–Smirnov, Lilliefors, and Shapiro–Wilk’s tests. In mostases with the gas analyses, the distribution differed from the nor-al, and hence non-parametric tests were performed. Medians,
5 and 75% percentiles and non-outlier range values of variables
re presented. We used the Kruskal–Wallis ANOVA and Wilcoxonatched Pairs test to check the significance of differences betweenhe gas fluxes at different sites, and the Spearman Rank Correlationo analyse the relationship between GHG fluxes and environmen-al conditions. The Mann–Whitney U-test was used to check the
4 l Engi
dao
ypaya
mu
3
Fa
6 K. Soosaar et al. / Ecologica
ifference between gas fluxes in different periods. The statisticalnalysis was carried out using Statistica 7.1 (StatSoft Inc.). The levelf significance of ˛ = 0.05 was accepted in all cases.
In addition, the soft modeling approach called redundancy anal-
sis (RDA) was applied to relate gas emission data to environmentalarameters (Legendre and Legendre, 1998). The soil temperaturend depth of groundwater data were used in the redundancy anal-sis as explanatory variables, and the microsite was considered ascategorical variable. The forward selection option with 1000 per-3
p
ig. 3. Variation (average ± standard deviation) of CO2, CH4, N2 and N2O fluxes, and N2:veraged over all sites within the test area.
neering 37 (2011) 40–53
utation was applied for variable selection. RDA was implementedsing the CANOCO 4.52 program.
. Results
.1. Gaseous emissions
The emission of all GHG gases varied remarkably at both tem-oral and spatial scales. The values of carbon dioxide, methane,
N2O ratio in the Viiratsi test site from November 2003 to October 2009. Data are
K. Soosaar et al. / Ecological Engineering 37 (2011) 40–53 47
(Conti
dvC8ia−as
2flw
Fa
Fig. 3.
initrogen and nitrous oxide fluxes averaged over micrositesaried between 2 and 198 mg CO2–C m−2 h−1, −6 and 551 �gH4–C m−2 h−1, 0.1 and 4.7 mg N2–N m−2 h−1, and −0.6 and7 �g N2O–N m−2 h−1 in Porijõgi (Fig. 2). There was no trend
n average values of GHG fluxes in 2001–2009. In Viiratsi theverage values varied between 2 and 366 mg CO2–C m−2 h−1,38 and 234 �g CH4–C m−2 h−1, 0.4 and 4.7 mg N2–N m−2 h−1,nd 0.5 and 38 �g N2O–N m−2 h−1 respectively (Fig. 3). Emis-ions of CO2, N2, and N2O showed a significant increase in
wNNPa
ig. 4. Comparison of CO2, CH4 (A), N2 and N2O (B) fluxes in 2003–2007 (period with coldnd higher precipitation). I – 2003–2007, II – 2008–2009. * – significantly differing values
nued ).
003–2009. Likewise, when comparing GHG fluxes in both areasor the periods 2003–2007 (the period with colder winters andong-term average precipitation) and 2008–2009 (the period
ith warmer winters and higher precipitation; see Table 4),
e can see that in Viiratsi, the median values of CO2, N2, and2O emission increased during the latter period (Fig. 4). The2:N2O ratio in Viiratsi (40–1200; Fig. 3) was lower than inorijõgi (10–7600; Fig. 2), and no trend was found in bothreas.er winters and long-term average precipitation) and 2008–2009 (warmer winters(p < 0.05; Mann–Whitney U-test).
48 K. Soosaar et al. / Ecological Engineering 37 (2011) 40–53
Fig. 5. Comparison of CO2, CH4, N2 and N2O fluxes in Porijõgi and Viiratsi study sites. Data represent fluxes from all sites within the test area. No significant differences inGHG fluxes between two study areas have been found (Wilcoxon Matched Pairs test).
Table 5Wilcoxon Matched Pairs test p-values of differences in CH4 (upper part) and CO2 (lower part) emissions between the microsites in the study areas.
Methane
PE PD PW VW VS VD
PE 0.0001** 0.0001** 0.002** 0.001** 0.148PD 0.002** 0.001** 0.011** 0.0001** 0.001**
PW 0.0001** 0.001** 0.438 0.0001** 0.0001**
VW 0.039* 0.088 0.501 0.002** 0.003**
VS 0.070 0.408 0.070 0.039* 0.001**
VD 0.030* 0.002** 0.001** 0.001** 0.010*
Carbondioxide
P – Porijõgi: E – edge, D – dry, W – wet; V – Viiratsi: W – wet, S – slope, D – dry.* Significant at p < 0.05 level.
** Significant at p < 0.01 level.
Table 6Wilcoxon Matched Pairs test p-values of differences in N2O (upper part) and N2 (lower part) emissions between the microsites in the study areas.
Nitrous oxide
PE PD PW VW VS VD
PE 0.056 0.001** 0.098 0.148 0.001**
PD 0.002** 0.002** 0.918 0.148 0.001**
PW 0.163 0.001** 0.070 0.0001** 0.001**
VW 0.002** 0.002** 0.123 0.326 0.002**
VS 0.225 0.052 0.002** 0.178 0.001**
VD 0.002** 0.076 0.015* 0.005** 0.001**
Dinitrogen
P – Porijõgi: E – edge, D – dry, W – wet; V – Viiratsi: W – wet, S – slope, D – dry.* Significant at p < 0.05 level.
** Significant at p < 0.01 level.
K. Soosaar et al. / Ecological Eng
Fig. 6. The relation between the depth of groundwater and methane flux (A) andbVl
oiPsTaiw
edtate
l(s(
rmmN0rtc
ttpVawwvdjm
TSs
TSp
etween the soil temperature and carbon dioxide emission (B) in both Porijõgi andiiratsi study areas. The dashed line indicates that in the case of groundwater depth
ower than 0.2 m, most of the CH4 is oxidized.
A comparison of median values of CO2, CH4, N2 and N2O fluxesver all microsites in Porijõgi and Viiratsi did not reveal any signif-cant differences between the two study areas (Wilcoxon Matchedairs test; Fig. 5). On the other hand, most of the GHG fluxes differignificantly between the individual microsites (Tables 5 and 6).
he wet microsites in both study areas were relatively similarnd differed from all other microsites. Also, the Slope micrositen Viiratsi differed from most of the others (except for the Viiratsiet microsite) in terms of CO2 emission (Table 5).
3
a
able 7pearman rank correlation between the fluxes of CO2, CH4, N2, N2O, depth of the grountudy sites.
CO2 CH4
CH4 −0.24*
N2 0.43** 0.33**
N2O 0.29** −0.27**
Water level 0.28** −0.41**
Soil temperature 0.24* 0.27**
* p < 0.05.** p < 0.01.
able 8pearman rank correlation between the fluxes of CO2, CH4, N2, N2O, monthly precipitatiart) study sites for the period 2008–2009.
Viiratsi
CO2 CH4 N2
CO2 0.38 0.39*
CH4 0.61** 0.34N2 0.27 0.21N2O 0.39* 0.42** 0.06Precipitation 0.16 0.36* 0.00Air temperature 0.85** 0.58** 0.54**
Porijõgi
* p < 0.05.** p < 0.01.
ineering 37 (2011) 40–53 49
Among environmental factors determining the intensity of GHGmissions are soil moisture (referred to as the groundwater levelepth) and soil temperature. This seems to be most relevant inerms of gaseous carbon fluxes (Fig. 6). Considering the Porijõgind Viiratsi data together, we found that in the case of groundwa-er level deeper than 20 cm from the surface, no significant CH4mission appears.
The depth of the groundwater level was also significantly corre-ated with the flux of CO2 (Spearman rank correlation r = 0.28), N2r = 0.24) and N2O (r = 0.52). The soil temperature showed positiveignificant correlations with GHG fluxes, except for N2O emissionTable 7).
For the period 2008–2009, we also found a significant cor-elation between GHG fluxes, monthly precipitation (mm) andean monthly air temperature (◦C; Table 8). In Porijõgi, the meanonthly air temperature significantly correlates with CO2, CH4 and2 emission (Spearman rank correlation coefficient values are 0.85,.58 and 0.54, respectively), whereas in Viiratsi, no significant cor-elation was found between GHG fluxes and mean monthly airemperature. The monthly precipitation value correlates signifi-antly with the CH4 fluxes in both study areas (Table 8).
RDA analysis with forward selection procedure indicated thathe variation in GHG fluxes is related to various environmen-al parameters at studied sites (Fig. 7a and b). Environmentalarameters explained 36.7 and 49.4% of GHG flux variation iniiratsi and Porijõgi, respectively. In the case of Viiratsi, the vari-tion in GHG fluxes is best explained by microsite type (P < 0.01),hile in the case of Porijõgi, soil temperature (P < 0.01) togetherith microsite type (P < 0.01) contributes significantly to the
ariation in gas emission values. In addition, the model poorlyescribed the variation in CO2 flux in Viiratsi and N2O flux in Pori-
õgi. At both sites, higher CH4 fluxes were associated with weticrosites.
.2. Global warming potential
The GWP of N2O in the studied riparian buffer zones was rel-tively high: 336 kg CO2 equivalents (eq) ha−1 yr−1 in Viiratsi and
dwater level (m), and topsoil (0–10 cm) temperature in both Porijõgi and Viiratsi
N2 N2O Water level
−0.020.24* 0.52**
0.25* 0.15 0.24*
on and mean monthly air temperature in Viiratsi (upper part) and Porijõgi (lower
N2O Precipitation Air temperature
0.29 0.33 0.120.12 0.41* 0.170.72** −0.17 0.41
0.31 0.400.20 0.320.28 0.12
50 K. Soosaar et al. / Ecological Engineering 37 (2011) 40–53
F spectv are int
1ecItwet
4
4
aTNa
cfhNNfh
Fsf2
ahgam
asbji
sTilttTae
ig. 7. Ordination diagrams based on a redundancy analysis of GHG flux data with reariables are indicated by solid arrows, and explanatory environmental variablesriangles. Abbreviations: GWD – depth of groundwater, Temp – temperature.
85 kg CO2 eq ha−1 yr−1 in Porijõgi (Fig. 8). In both areas the differ-nces in N2O fluxes between the microsites were insignificant. Theontribution of methane emission from grey alder stands was low.n Porijõgi the median value of CH4 flux was more influenced byhe Wet microsite, making the total GWP 19 kg CO2 eq ha−1 yr−1,hereas in Viiratsi the GWP value was negative (−14 kg CO2
q ha−1 yr−1) N, which was the influence of well oxidized soils inhe slope and dry microsites (Fig. 8).
. Discussion
.1. Gaseous emissions
Our results of investigations carried out in two riparian greylder forests demonstrate some coherence with the literature data.he median values of cumulative annual fluxes of CO2–C, CH4–C,2–N, and N2O–N are 4100, 0.9, 153 and 0.4 kg ha−1 yr−1 in Porijõgind 3862, −0.4, 184 and 0.7 kg ha−1 yr−1 in Viiratsi, respectively.
Dinitrogen emission has been found to be the most importantomponent of N retention within the Porijõgi riparian grey alderorest. The estimated N2–N emission for 1994–1995 was 51.2 kg N
a−1 yr−1 (Lõhmus et al., 2002), for 2001–2003 even 700–1200 kgha−1 yr−1 (Mander et al., 2008), and has been estimated at 184 kgha−1 yr−1 for the period 2001–2009. The intensive N2 emissionrom both Porijõgi and Viiratsi study sites may be related to theigh microbial activity in alder forests (Hart et al., 1997; Dilly et
ig. 8. Global warming potential (GWP) of methane and nitrous oxide of the twotudy sites based on median values of measured fluxes. Coefficients of radiativeorcing: 1 kg CH4 = 25 kg CO2 equivalents; 1 kg N2O = 296 kg CO2 equivalents (IPCC,007).
tlpsm
4
GaHeCtiewtmc
to environmental variables for the Porijõgi (a) and Viiratsi (b) locations. Dependentdicated by dashed arrows. The qualitative variable microsite type is indicated by
l., 2000; Lõhmus et al., 2002), which could be assumed to lead toigher denitrification activity. High emission rates of N2 in youngerrey alder stands are most likely related to changes in microbialctivity during the succession from a pioneer grey alder stand to aore stable mixed forest community (see Mander et al., 2008).The continuously high nutrient loading has probably been
nother reason beside the high age for increasing GHG emis-ions from the soil in Viiratsi. Likewise, the different relationshipetween CO2 and N2, and N2 and N2O emissions in Viiratsi and Pori-
õgi hints at altered carbon availability in the denitrification processn the highly loaded Viiratsi buffer zone (Table 8 and Fig. 9).
The CH4 oxidation capacity in alder forests has been found to beignificantly lower than in other forests (Reay et al., 2001, 2005).his explains the higher CH4 emission values in Wet micrositesn both riparian study areas. On the other side, aerated topsoil ateast 20 cm deep above the groundwater level can oxidise most ofhe CH4 flux (Fig. 6). Seasonal fluctuations of CH4 fluxes depend onhe depth of water table and soil temperature (Table 7 and Fig. 6).herefore, higher precipitation and soil temperature values whichre expected due to climate warming might increase the methanemission from wetter locations in the riparian zone.
RDA analysis results indicated that microsite type is one ofhe key factors explaining GHG flux variation within the studiedocations. In addition to the depth of groundwater, microsite typerobably incorporates some other key factors that contribute tooil biological activity, for instance soil chemical parameters andicrobial community composition.
.2. Global warming potential
Carbon dioxide constitutes the largest proportion of the totalWP of riparian alder forests, showing median values of 4168nd 3862 kg CO2 eq ha−1 yr−1 in Porijõgi and Viiratsi, respectively.owever, some studies on C sequestration in wetlands and for-st ecosystems (Butnor et al., 2003) indicate that about 50% of theO2 released during soil respiration will be assimilated by treeshrough photosynthesis in the vegetation period. Our earlier stud-es show that in the growing season, more than 80% of the CO2
mitted is assimilated by vegetation (Lõhmus et al., 2002). Even ife consider that about 25% of annual CO2 emissions happen duringhe cold period when vegetation is dormant, the long-term esti-ations of C budget in soil under grey alder plantation show a
lear sequestration, and the soil C concentration in these stands
K. Soosaar et al. / Ecological Engineering 37 (2011) 40–53 51
N2 an
cns
(mrCasictfha
i1l(rEoaercf
5
agsaC
ir
woli
meu
ssrccto
A
0RSE7SS
R
Fig. 9. The relationship between CO2 and N2 emission (upper part) and
learly increases (Uri et al., 2003). Therefore, in this study we didot count the share of CO2 in the total GWP of riparian aldertands.
Estimation of the GWP of CH4 and N2O over a long time period100–500 years) allows us speculate that due to the short adjust-
ent time for CH4 in the atmosphere (8.4 years; IPCC, 2007), theadiative forcing of CH4 will fall relative to CO2 (Whiting andhanton, 2001). Nitrous oxide, with its atmospheric lifespan ofbout 120 years and GWP value of 296, however, has a moreignificant impact. Our data show a minor CH4 emission from ripar-an alder forests. Likewise, the N2O emission was relatively lowompared to emissions from constructed wetlands for wastewaterreatment (Teiter and Mander, 2005). However, the high radiativeorcing value of N2O makes its share in total GWP remarkable, beingighest in the Viiratsi study area, with high nutrient input fromdjacent fields (336 kg CO2–C eq ha−1 yr−1; Fig. 8).
The lowering of the water table in wetlands and riparian zoness another well-known reason for N2O emission (Martikainen et al.,993). This is also supported by our results: deeper groundwater
evel significantly (Spearman r = 0.52) increases the N2O emissionTable 7). The planned increase in fertilization intensity and theeconstruction of abandoned drainage systems in several Easternuropean countries after the political and socio-economic changesf the 1990 s (Grimvall et al., 2000; Mander et al., 2000; Stålnacke etl., 2003) may change the N balance of riparian ecosystems. How-ver, its dynamics and especially the change in gaseous N fluxes areelatively unpredictable. Therefore further investigations shouldoncentrate on the factors that regulate N2O and N2 emission ratesrom riparian buffer zones.
. Conclusions
According to the literature data, alder stands have been reported
s highest N2O and N2 emitters among riparian forests whereas theaseous carbon emissions have been found less significant. In ourtudy, all the gas emissions showed a big variability in both spacend time. The median values of cumulative annual fluxes of CO2–C,H4–C, N2–N, and N2O–N are 4100, 0.9, 153 and 0.4 kg ha−1 yr−1A
A
d N2O fluxes (lower part) in the Porijõgi (A) and Viiratsi (B) study areas.
n Porijõgi and 3862, −0.4, 184, and 0.7 kg ha−1 yr−1 in Viiratsi,espectively.
Riparian grey alder forests are effective buffering ecosystemsith relatively high GWP due to high carbon dioxide and nitrous
xide emission. The higher water table in riparian forests benefitsower GWP because of decreasing CO2 and N2O emissions; increas-ng CH4 emission plays a less significant role.
Results of the RDA analysis suggest that further analysis oficrobial community composition, which may be a main factor
xplaining variation of GHG emission among microsites, should bendertaken.
Increasing trends in CO2, N2, and N2O emissions in the Viiratsitudy area may be a result of the age (>50 years) of the grey aldertand, but may also be caused by the long-term nutrient load of thisiparian alder stand. This indicates that the buffering capacity ofontinuously loaded riparian buffers will decrease over time, whichalls for the careful management of these riparian forests, such ashe selective cutting of older trees and the planting of younger treesn the border with adjacent fields.
cknowledgements
This study was supported by EU 5 FP RTD project EVK1-2000-0728 “PRocess Based Integrated Management of Constructed andiverine Wetlands for Optimal Control of Wastewater at CatchmentcalE” (PRIMROSE), Norway and EEA financed research projectE0012, Estonian Science Foundation projects No. 5247, 7459,527, and 7548 and Target Funding Projects No. 0182534s03,F0180127s08 and SF0180052s07 of the Ministry of Education andcience of Estonia.
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