Biogeosciences, 13, 4439–4459, 2016
www.biogeosciences.ne /13/4439/2016/
doi:10.5194/bg-13-4439-2016
© Au ho (s) 2016. CC A ibu ion 3.0 License.
Unde es ima ion o bo eal soil ca bon s ocks by ma hema ical
soil ca bon models linked o soil nu ien s a us
Bo is ˇ
Tupek1, Ca ina A. O iz2, Shoji Hashimo o3, Johan S endahl2, Jonas Dahlg en4, E ik Ka l un2, and
Aleksi Leh onen1
1Na u al Resou ces Ins i u e Finland, P.O. Box 18, 01301 Van aa, Finland
2Swedish Uni e si y o Ag icul u al Sciences, P.O. Box 7014, 75007 Uppsala, Sweden
3Fo es y and Fo es P oduc s Resea ch Ins i u e, Tsukuba, Iba aki 305-8687, Japan
4Swedish Uni e si y o Ag icul u al Sciences, Skogsma ksg änd, 90183 Umeå, Sweden
Co espondence o: Bo is ˇ
Tupek ([email p o ec ed]), Aleksi Leh onen (aleksi.leh onen@luke. i)
Recei ed: 21 Decembe 2015 – Published in Biogeosciences Discuss.: 18 Janua y 2016
Re ised: 6 July 2016 – Accep ed: 7 July 2016 – Published: 10 Augus 2016
Abs ac . Inaccu a e es ima e o he la ges e es ial ca bon
pool, soil o ganic ca bon (SOC) s ock, is he majo sou ce
o unce ain y in simula ing eedback o clima e wa ming on
ecosys em–a mosphe e ca bon dioxide exchange by p ocess-
based ecosys em and soil ca bon models. Al hough he mod-
els need o simpli y complex en i onmen al p ocesses o soil
ca bon seques a ion, in a la ge mosaic o en i onmen s a
missing key d i e could lead o a modeling bias in p edic-
ions o SOC s ock change.
We aimed o e alua e SOC s ock es ima es o p ocess-
based models (Yasso07, Q, and CENTURY soil sub-model
4) agains a massi e Swedish o es soil in en o y da a se
(3230 samples) o ganized by a ecu si e pa i ioning me hod
in o dis inc soil g oups wi h unde lying SOC s ock de elop-
men linked o physicochemical condi ions.
Fo wo- hi ds o measu emen s all models p edic ed ac-
cu a e SOC s ock le els ega dless o he de ail o inpu da a,
e.g., whe he hey igno ed o included soil p ope ies. How-
e e , in e ile si es wi h high N deposi ion, high ca ion ex-
change capaci y, o mode a ely inc eased soil wa e con en ,
Yasso07 and Q models unde es ima ed SOC s ocks. In com-
pa ison o Yasso07 and Q, accoun ing o he si e-speci ic
soil cha ac e is ics (e. g. clay con en and opsoil mine al N)
by CENTURY imp o ed SOC s ock es ima es o si es wi h
high clay con en , bu no o si es wi h high N deposi ion.
Ou analysis sugges ed ha he soils wi h poo ly p edic ed
SOC s ocks, as cha ac e ized by he high nu ien s a us and
well-so ed pa en ma e ial, indeed ha e had o he p edomi-
nan d i e s o SOC s abiliza ion lacking in he models, p e-
sumably he myco hizal o ganic up ake and o gano-mine al
s abiliza ion p ocesses. Ou esul s imply ha he ole o soil
nu ien s a us as egula o o o ganic ma e mine aliza ion
has o be e-e alua ed, since co ec SOC s ocks a e decisi e
o p edic ing u u e SOC change and soil CO2e lux.
1 In oduc ion
In spi e o he his o ical ne ca bon sink o bo eal soils,
500Pg o ca bon since he las ice age (Rapalee e al., 1998;
DeLuca and Bois enue, 2012; Scha lemann e al., 2014),
bo eal soils could become a ne sou ce o ca bon dioxide
o he a mosphe e as a esul o long- e m clima e wa m-
ing (Ki schbaum, 2000; Amundson, 2001). They ha e he
po en ial o elease la ge quan i ies o ca bon han all an-
h opogenic ca bon emissions combined (337Pg; Boden
e al., 2010). In o de o p ese e he soil ca bon pool and
o u ilize he soil ca bon seques a ion po en ial o mi iga e
an h opogenic CO2emissions, mi iga ion s a egies o cli-
ma e o cing aim o imp o e soil o ganic ma e managemen
(Schlesinge , 1999; Smi h, 2005; Wiesmeie e al., 2014).
Suppo ing soil managemen decisions equi es an ac-
cu a e quan i ica ion o spa ially a iable soil o ganic ca -
bon (SOC) s ock and SOC s ock changes (Scha lemann
e al., 2014). The ini ial le el o SOC s ock is essen ial in
o de o es ima e SOC s ock changes (Palosuo e al., 2012;
Todd-B own e al., 2014), especially when es ima ing ca bon
emissions due o land-use change, e.g., a o es a ion o g ass-
Published by Cope nicus Publica ions on behal o he Eu opean Geosciences Union.
4440 B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y
lands (Be h ong e al., 2009). P ocess-o ien ed soil ca bon
models like CENTURY, Ro h-C, Biome-BCG, ORCHIDEE,
JSBACH, ROMUL, Yasso07, and Q a e impo an ools o
p edic ing SOC s ock change, bu he e a e also isks o poo
p edic ions (Todd-B own e al., 2013; DeLuca and Bois -
enue, 2012). The models need u he alida ion and im-
p o emen as hey show poo spa ial ag eemen on ine scale
and mode a e ag eemen on egional scale agains SOC s ock
da a (Todd-B own e al., 2013; O iz e al., 2013). Despi e he
po en ially quan i a i e impo ance o CO2emissions he ex-
pec ed change will be small in ela ion o he SOC s ock.
The e o e, he unce ain y o measu emen s and/o model
es ima es could p e en conclusions on SOC s ock changes
(Palosuo e al., 2012; O iz e al., 2013; Leh onen and Heikki-
nen, 2015) especially o he soils wi h he la ges SOC
s ocks, which a e he mos sensi i e o ca bon loss. Beside
la ge unce ain ies, he poo ag eemen be ween he modeled
and measu ed SOC s ocks (Todd-B own e al., 2013) could
also indica e missing bio ic o abio ic d i e s o long- e m
ca bon s o age (Schmid e al., 2011; A e ill e al., 2014).
Fo example, igno ing he essen ial ole o soil nu ien
a ailabili y in ecosys em ca bon use e iciency (Fe nández-
Ma ínez e al., 2014) could lead o missing impo an con-
ols o plan li e p oduc ion and soil o ganic ma e s abi-
liza ion mechanisms. Soil nu ien s a us is linked o he mo-
bili y o nu ien s in he wa e solu ion (Husson e al., 2013),
p oduc ion, quali y and mic obial decomposi ion o plan li -
e (O win e al., 2011), and o ma ion o he soil o ganic
ma e (SOM). The SOM a ec s soil nu ien s a us by e-
cycling o mac onu ien s (Husson e al., 2013), and wa e
e en ion and wa e a ailabili y (Rawls e al., 2003).
In spi e o s a e o he a soil ca bon modeling based on
he amoun and quali y o plan li e “ ecalci ance”, a ec ed
by clima e and/o soil p ope ies as in he Yasso07, Q, and
CENTURY models, hese ypes o p ocess-based models do
no include mechanisms o SOM s abiliza ion by (a) he o -
ganic nu ien up ake by myco hizal ungi; (b) humic o -
ganic ca bon in e ac ions wi h sil -clay mine als; and (c) he
inaccessibili y o deep soil ca bon and ca bon in soil agg e-
ga es o soil bio a (O win e al., 211; Sollins e al., 1996;
To n e al., 1997; Six e al., 2002; Fan e al., 2008; Dun-
gai e al., 2012; Clemen e e al., 2011). Al hough he models
do no con ain a o emen ioned mechanisms and con ols o
changes in SOM s abiliza ion p ocesses, hey ha e been pa-
ame e ized using a wide a ie y o da a se s and can ea
soil bio ic, physicochemical, and en i onmen al changes im-
plici ly. The Yasso07 model (Tuomi e al., 2009, 2011) is an
ad anced o es soil ca bon model and i is used o Kyo o
p o ocol epo ing o changes in soil ca bon amoun s o he
Uni ed Na ions F amewo k Con en ion on Clima e Change
(UNFCCC) by Eu opean coun ies, e.g., Aus ia, Finland,
No way, and Swi ze land. The Q model (Åg en e al., 2007)
is a mechanis ic li e decomposi ion model de eloped in
Sweden and used, e.g., o compa e esul s p oduced wi h
Swedish na ional in en o y da a (S endahl e al., 2010; O iz
e al., 2011) and also wi h o he models a na ional o global
scales (O iz e al., 2013; Yu o a e al., 2010). The CEN-
TURY model (Pa on e al., 1987, 1994; Adai e al., 2008)
is one o he mos widely applied models and i is used o
soil ca bon epo ing o he UNFCCC by Canada, Japan, and
USA. Al hough indi idual pa ame e s and unc ions a y,
ma hema ical models such as Yasso07, Q, and CENTURY
ha e simila s uc u es. Fo example, hese models a e d i en
by he decomposi ion a es o li e inpu and SOM. Decom-
posing li e and SOM is di ided in o pools based on li e
quali y, and i s ans e om one pool o ano he is, apa
om model unc ions and pa ame e s, a ec ed by empe -
a u e (Q), and/o wa e (Yasso07), and/o soil ex u e and
s uc u e (CENTURY). The Q model does no include ex-
plici mois u e unc ions, whe eas p ecipi a ion a ec s de-
composi ion o he Yasso07 and CENTURY models (Tuomi
e al., 2009; Adai e al., 2008). On he o he hand, he mod-
els do no explici ly o by de aul include mechanisms ha
educe decomposi ion by excessi e p ecipi a ion/mois u e
(Falloon e al., 2011).
We hypo hesized ha (1) soil ca bon es ima es o he
Yasso07, Q, and CENTURY models would de ia e o soils
whe e SOC s abiliza ion p ocesses no implici ly accoun ed
by he models a e p edominan , (2) he Yasso07 and Q mod-
els igno ing soil p ope ies would ail on he nu ien - ich
si es o he sou hwes e n coas o Sweden and on occasion-
ally paludi ied clay and sil soils, and (3) he CENTURY
model ou pe o ms he Yasso07 and Q models due o ac
ha i includes soil p ope ies as inpu a iables.
We g ouped Swedish o es soil in en o y da a in o ho-
mogenous g oups wi h speci ic soil physicochemical con-
di ions using a eg ession ee and ecu si e pa i ioning
modeling me hods. A e ha we an he models un il hey
eached an equilib ium wi h a li e inpu ha was de i ed
om he Swedish o es in en o y. The ea e , we compa ed
he model es ima es agains da a by g oups ha we e ob-
ained om he eg ession ee model. In discussion we ad-
d ess he easons why he models de ia e and indica e di ec-
ions o u he imp o emen s.
2 Ma e ial and me hods
2.1 Measu emen s
We analyzed da a om he Swedish o es soil in en o y
(SFSI), which is a s a i ied na ional g id su ey o ege-
a ion and physicochemical p ope ies o soils (SLU, 2011;
Olsson e al., 2009). The soil da a dis inguished be ween
he o ganic, B (0–5cm o B ho izon), BC (45–55cm below
g ound su ace), and C (55–65cm om he op o he mine al
soil) ho izons (Olsson e al., 2009). All analysis was done
using R so wa e o s a is ical compu ing and g aphics (R
Co e Team, 2014). The soil da a we e iden ical o a da a se
used in S endahl e al. (2010). We es ic ed ou sample plo s
Biogeosciences, 13, 4439–4459, 2016 www.biogeosciences.ne /13/4439/2016/
B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y 4441
Table 1. Desc ip ion o he Swedish Fo es Soil In en o y (SFSI) da a educ ion o soil so ing o pa en ma e ial and humus ypes; SFSI
con e sion es ima e o soil classes o soil mois u e o nume ical ep esen a ion o soil wa e con en ; and SFSI con e sion es ima e o classes
o nume ical ep esen a ion o soil ex u e (sand, sil , and clay con en o sedimen s by Lindén (2002) and o ills by Albe A e be g’s
dis ibu ion o he di e en g ain size ac ions).
So ing pa en ma e ial Humus ype Mois u e
SFSI Reduced SFSI Reduced SFSI SFSI Nume ic
Bed ock Bed ock Mode No-pea Wa e Long- e m
Poo ly so ed sedimen s Unso ed Mo 1 No-pea le el (m) mois u e %
Tills Unso ed Mo 2 No-pea D y <2 10
Well-so ed sedimen s So ed Mull No-pea F esh 1–2 20
Mull-Mode Pea F esh-mois <1 30
Pea Pea Mois <0.5 50
Pea -Mo Pea
Tex u e
SFSI Nume ic
Sedimen s Tills
Sand % Sil % Clay % Sand % Sil % Clay %
Bed ock 0 0 0 0 0 0
Boulde 0 0 0 0 0 0
G a el 10 0 0 10 0 0
Coa se sand 40 5 0 40 5 0
Sand 80 10 0 45 10 0
Fine sand 70 25 5 55 15 0
Coa se sil 50 40 10 65 20 5
Fine sil 10 75 15 55 35 10
Clay 0 65 35 0 85 15
Pea 0 0 0 0 0 0
o mine ogenic soils since he Q, Yasso07, and CENTURY
models we e no de eloped o use on pea soils, and only o
plo s o o es land use wi h Swedish o es in en o y da a
(SFI). We also excluded samples wi h o al SOC s ock be-
low 2.8 and abo e 470.5 ( Cha−1), i.e., samples wi h SOC
s ock below 0.01 and abo e 99.9 pe cen ile. Measu emen
da a o igina ed om 1993 o 2002, which cons i u e a ull
in en o y, and om 2020 sample plo s loca ed a ound Swe-
den, and in o al i included 3230 samples. Fo each sample
plo he wea he (yea s 1961–2011) and N deposi ion (yea s
1999–2001) da a we e e ie ed om he nea es s a ions o
Swedish Me eo ological and Hyd ological Ins i u e (SMHI)
ne wo k (Fig. 1). The plo s, which we e linked by he closes
dis ance o he gi en wea he s a ion had he same wea he
and N deposi ion da a, and he numbe o soil samples pe
s a ion anged be ween 10 and 70. The mean o al SOC s ock
o samples co esponding o wea he s a ions anged om
40 o 200 ( Cha−1), and he SOC s ock le el dec eased om
sou he n o no he n Sweden (Fig. 1).
Each sample plo con ained ca ego ical da a om he ield
su ey on he so ing o soil pa en ma e ial, humus ype,
soil ex u e, and soil mois u e. In ou analysis we educed
ca ego ical classes by basing hem on he so ing o soil pa -
en ma e ial and humus ype (Table 1). We de e mined nu-
me ic alues o sil , clay, and sand con en om soil ex u e
ca ego ies by Albe A e be g’s dis ibu ion o he di e en
g ain size ac ions in ills and dis ibu ions o sedimen s by
Lindén (2002) (Table 1). We also de e mined nume ic al-
ues o olume ic soil wa e con en (SWC) om ca ego ical
ield da a classi ied acco ding o he dep h o he g ound wa-
e le el (WL; Table 1).
As is ypical o soil ca bon in en o ies, he a ia ion o
da a was la ge (Table 2). Fo example, he mean o al SOC
s ock o all samples was 93 ( Cha−1) while 1s and 99 h pe -
cen iles we e 17 and 309 (Table 2). The mean SOC s ock
was 33.3 and 66.8 ( Cha−1) o he humus ho izon and he
mine al soil. The mean alues o ca ion exchange capaci y
(CEC) (23.9mmolckg−1), he base sa u a ion (36.4%), and
he C/N a io (16.5) indica ed condi ions o medium e il-
i y, al hough he soils we e mos ly acidic (mean pH was 5.2).
The mean p e ailing soil wa e con en (22.3) was ypical o
he well-d ained o es soils. The mean annual empe a u es
anged om below 0 o abo e 8◦C, and annual p ecipi a-
ion a ied be ween 392 and 1154mm (Table 2). To al SOC
s ock o all he samples gene ally inc eased o pea and pea
like humus o ms, o well-so ed sedimen s, o soils wi h
high ac ion o sil and clay and wi h inc easing soil mois-
u e (Fig. S1 in he Supplemen ).
www.biogeosciences.ne /13/4439/2016/ Biogeosciences, 13, 4439–4459, 2016
4442 B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y
Table 2. Desc ip i e cha ac e is ics (mean, con idence in e al, 1s , 50 h, and 99 h pe cen ile) o selec ed a iables (n=3230 samples). The
alues o he bulk densi y, ca ion exchange capaci y, base sa u a ion, C /N a io, and pH a e shown only o BC soil ho izon ( ixed 45–50cm
dep h below he g ound su ace) due o he s ong co ela ion o he o al soil ca bon s ock. The soil was cu o a 1 m. The si e p oduc i i y
index (H100, m) is an app oxima ion o he si e e ili y exp essed as he heigh o ees a 100 yea s o age. S and and unde s o y biomass,
and li e inpu a e modeled alues o app oxima ed equilib ium condi ions based on obse a ions.
Mean CI 1s pe cen ile 50 h pe cen ile 99 h pe cen ile
To al soil ca bon s ock ( Cha−1) 93.24 1.95 17.02 79.68 308.68
Humus ca bon s ock ( Cha−1) 33.29 1.17 3.89 22.82 176.66
Mine al soil ca bon s ock ( Cha−1) 66.82 1.7 6.92 54.81 273.91
Dep h o humus (cm) 10.52 0.27 1 8 36
Dep h o soil (cm) 93.37 0.6 18 99 99
S oniness (%) 39.91 0.54 3.96 42.37 65.05
Bulk densi y o BC (gdm−3) 1267.1 5.5 790.55 1294.9 1522.13
Ca ion exchange capaci y o BC (mmolckg−1) 23.94 1.28 1.53 12.33 203.25
Base sa u a ion o BC (%) 36.44 1.02 4.33 25.73 100
C/N a io o BC 16.5 0.35 3.33 14.98 62.45
pH o BC 5.17 0.02 4.36 5.08 7.26
Sil con en (%) 19.98 0.57 0 15 85
Clay con en (%) 3.16 0.25 0 0 35
Sand con en (%) 51.25 0.63 0 55 80
Long- e m soil mois u e (%) 22.36 0.2 10 20 30
Mean ai empe a u e (◦C) 4.63 0.09 −0.44 5.34 8.47
To al p ecipi a ion (mm) 697.87 7.13 392.54 637.11 1154.55
Ni ogen deposi ion (kgNha−1y−1) 7.17 0.14 2.35 6.56 17.67
P oduc i i y class (H100, m) 23.61 0.21 12 23 36
To al s and biomass ( Cha−1) 56.02 1.39 1.34 51.14 156.52
To al unde s o y biomass ( Cha−1) 2.69 0.05 0.96 2.37 6.02
To al li e all inpu ( Cha−1) 3.17 0.03 1.65 3.07 5.28
2.1.1 Biomass and li e all es ima es
Fo he biomass and li e all es ima ion we adop ed a s an-
da d me hod o na ional g eenhouse gas in en o ies o es i-
ma ing soil ca bon s ock changes (S a is ics Finland, 2013).
In o de o model SOC s ocks o o es in equilib ium (no
SOC s ocks changes), we modi ied he me hod by es ima ing
he long- e m li e all o o es in equilib ium. Fo es s and
biomass was es ima ed by allome ic biomass unc ions o
s em wi h ba k, b anch, oliage, s ump, coa se oo s and ine
oo s applied o basic ee dimensions (b eas heigh diame-
e , o al heigh o ee, numbe o ees) o SFI s ands (Ma k-
lund, 1988; Pe e sson and S åhl, 2006; Repola, 2008; Leh o-
nen e al., 2016a). In o de o simula e “equilib ium” soil ca -
bon s ock, we es ima ed long- e m mean o es biomass, e-
e ed o as “equilib ium o es ” below.
We adop ed an obse ed ac ion o pho osyn he ically ac-
i e abso bed adia ion ( APAR; Fig. A1 in Appendix A) as
a ela i e indica o o a si e’s capaci y o p oduce biomass
(minimum is 0, maximum is 1) by accoun ing o he o es
s and s uc u e, anging om he absen s and APAR =0 o
he closed canopy s and APAR =1, h ough i s majo ole
on limi ing o he po en ial g oss p ima y p oduc ion (Pel-
oniemi e al., 2015). The APAR was calcula ed based on
SFI measu emen s o basic ee dimensions as in Hä könen
e al. (2010) and o he main ee species (pine, sp uce, de-
ciduous) i was well co ela ed wi h he s and basal a ea (Ap-
pendix A).
The equilib ium o es APAR alues we e assumed o be
in a ange be ween he median and he maximum ac ion o
he obse ed s a e o es APAR o a gi en species, la i u-
dinal deg ee, and si e p oduc i i y index (Appendix A). We
selec ed equilib ium APAR as he 70 h pe cen ile ( APAR70)
ou o a ange om he 50 h o 95 h, because he modeled
soil ca bon dis ibu ions wi h a li e inpu om he APAR70
biomass ag eed bes wi h he measu ed soil ca bon dis i-
bu ions (Fig. S2). The APAR70 was he es ima ed 70 h pe -
cen ile o he obse ed ac ion o abso bed adia ion speci ic
o a gi en species, la i udinal deg ee, and si e p oduc i i y
index H100 (heigh o ees a 100 yea s o age; m; Fig. B1 in
Appendix B). The si e index H100, ha can be ansla ed o
a speci ic p oduc i i y (m3ha−1y −1), was o Swedish o -
es in en o y plo s de e mined based on heigh de elopmen
cu es and obse ed si e p ope ies by using he me hodol-
ogy o Hagglund and Lundma k (1977) (Swedish S a is ical
Yea book o Fo es y, 2014). Ins ead o modeling o equi-
lib ium biomasses o e e y ee s and componen sepa a ely
o he species, la i ude, and si e p oduc i i y index, we sim-
pli ied he biomass modeling i s by es ima ing only equilib-
Biogeosciences, 13, 4439–4459, 2016 www.biogeosciences.ne /13/4439/2016/
B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y 4443
10 15 20 25
56 58 60 62 64 66 68
68
●
34
and numbe o
Me eo.s a ion
nea es soil samples ( ha−1)
Soil ca bon
La i ude (°)
Longi ude (°)
50
100
150
Figu e 1. Geog aphical loca ions o me eo ological s a ions wi h
co esponding numbe o nea es soil samples (n, size o he ci cle)
and hei mean measu ed soil o ganic ca bon s ock ( Cha−1, colo
o he ci cle) ac oss Sweden.
ium o es s and s uc u e o he species, la i ude, and p o-
duc i i y ( APAR70, Table A1 in Appendix A) and secondly
by using APAR70 wi h APAR biomass models (Table B1 in
Appendix B) o es ima e he biomass componen s.
We modeled he equilib ium biomass by applying he i -
ed exponen ial unc ions be ween he obse ed s a e o es
biomass componen s (s em, b anch, oliage, s ump, coa se
oo s, ine oo s, es ima ed by ee s and measu emen s and
he allome ic biomass unc ions) and he obse ed ac ion
o abso bed adia ion ( APAR; Appendix B) o he es ima ed
APAR70 o he equilib ium o es . The unde s o y ege a-
ion o he equilib ium o es was es ima ed by applying ou
g ound ege a ion models (Appendix C) o he modeled equi-
lib ium o es cha ac e is ics, and plo -speci ic en i onmen-
al condi ions.
In o de o de i e he li e inpu s, he annual u no e
a e (TR), he ac ion o li ing biomass ha is shed on o
he g ound pe yea o biomass componen s, was applied
o he modeled biomass componen s o he equilib ium o -
es . The needle li e TR was a linea unc ion o la i ude
o pine and sp uce and a cons an o deciduous species
(Åg en e al., 2007). The TR o b anches and oo s we e om
Mukkonen and Leh onen (2004) and Leh onen e al. (2004)
and he TR o s ump and s em we e om Vi o (1955), Mälkö-
nen (1974, 1977) and Liski e al. (2006). Fo ee ine oo s,
we assumed he e was a di e ence be ween ee species and
be ween sou he n and no he n Sweden. Fo pine, sp uce,
and bi ch he TR ine oo s we e 0.811, 0.868, and 1.0, e-
spec i ely, as epo ed by Maidi (2001), Ku z e al. (1996),
and Liski e al. (2006). Kleja e al. (2008) and Leppälampi-
Kujansuu e al. (2014) epo ed di e en ine- oo TR o
sou he n (1 and 0.83) and no he n Finland (0.5). We in e po-
la ed TR acco ding o he mean annual empe a u e g adien
be ween TR o ine oo s in he sou h and he no h. The ine-
oo s TR o 0.811, 0.868, and 1.0 in he wa mes sou he n-
mos soil plo s we e hus educed down o 0.5 in he coldes
no he nmos soil plo s. The unde s o y TR was applied as in
Leh onen e al. (2016b).
The majo pa o he li e inpu o igina ed om he ee
s and biomass componen s, which we e modeled by he non-
linea unc ions wi h R2 alues close o 0.9 (Fig. B1, Ta-
bles A1 in Appendix A, and B1 in Appendix B). The linea
unde s o y ege a ion models had low R2 alues (Table C1
in Appendix C). Howe e , when he unde s o y models (Ap-
pendix C) we e applied only o plo s close o equilib ium o -
es , as in ou applica ion, he R2 alues o p edic ed and ob-
se ed unde s o y componen s we e la ge (Fig. S9). In com-
pa ison o majo unde s o y li e all o igina ing om ea-
sonably well-p edic ed dwa sh ubs and mosses (Figs. S9
and S10), he in luence o poo e unde s o y models ( o
he bs, g ass, and lichens) was small on p edic ions o he un-
de s o y li e and ma ginal on p edic ions o he o al o es
li e all (Fig. S10). The main imp o emen on he accu acy
o o al li e inpu was achie ed by a oiding he con ounding
e ec o managemen on obse ed o es s a e by modeling
he biomass/li e all es ima es ep esen ing he mean long-
e m condi ions (de ined by es ima ed equilib ium APAR70)
o small egions (de ined by deg ee o la i ude and p oduc-
i i y index o dominan species; Fig. A1 in Appendix A).
Thus he es ima es accu a ely e lec ed he long- e m spa ial
a iabili y in dominan species, nu ien s a us and clima e
(Fig. S11) and lacked highe spa ial and empo al p ecision;
as a emp s o high p ecision o he es ima es applied o he
pe iod o he las ew housand yea s would be unce ain due
o high a ia ion o ac o s a ec ing plo his o y.
2.1.2 Co ela ion analysis
O e all ou da a consis o 3230 soil samples and hei ca -
bon s ocks linked o soil physicochemical a iables, s and
and g ound ege a ion biomass and li e all componen s,
and nea es wea he s a ion en i onmen al a iables. We pe -
o med he Spea man’s ank co ela ion analysis be ween he
o al soil ca bon s ock and he o he soil a iables, si e, cli-
ma e, and ege a ion cha ac e is ics. As expec ed he o al
soil ca bon s ock mos s ongly co ela ed wi h he measu ed
www.biogeosciences.ne /13/4439/2016/ Biogeosciences, 13, 4439–4459, 2016

4444 B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y
CEC.BC < 17
CEC.BC < 7.9
pa en .ma e ial:
bed ock,unso d
CN.BC < 16
pa en .ma e ial:
unso d CEC.BC < 33
N.deposi ion < 9.9
Bound.H2O.C < 2.4
Humus:
no.pea
>= 17
>= 7.9
So ed
>= 16
So ed >= 33
>= 9.9
>= 2.4
Pea
65
n=959 30 % 82
n=909 28 % 130
n=136 4 % 86
n=335 10 % 126
n=182 6 % 104
n=296 9 % 137
n=180 6 % 269
n=8 0 % 144
n=142 4 % 203
n=83 3 %
Measu ed soil ca bon s ock ( C ha−1)
(a)
Ca bon low medium high medium high medium high ex a high ex a
Mois u e d y− esh esh mois − esh esh mois − esh esh esh esh esh mois − esh
Fe ili y low medium medium medium high low high high medium medium
Soil g oup 1 2 3 4 5 6 7 8 9 10
(b) n=959 n=909 n=136 n=335 n=182 n=296 n=180 n=8 n=142 n=83
Figu e 2. (a) Classi ica ion/ eg ession ee o he measu ed soil ca bon s ock ( Cha−1), soil physicochemical p ope ies, and si e en i-
onmen al cha ac e is ics; he ca ion exchange capaci y o BC ho izon (CEC.BC, (mmolckg−1)), he C/N a io (CN.BC), he ni ogen
deposi ion (N.deposi ion kgNha−1y−1), he highly bound soil wa e o C ho izon (bound.H2O.C, %), and soil class a iables as ype o
so ed o unso ed soil pa en ma e ial and humus ype. No e ha a iables used o calcula e he soil ca bon s ock (bulk densi y, ca bon
con en , dep h, and s oniness) we e excluded om he eg ession ee analysis. The alues in he lea es o he ee show o he dis inc en-
i onmen al condi ions mean soil ca bon s ock ( Cha−1), numbe and pe cen age o samples. (b) The in e p e a ion o 10 physicochemical
soil g oups o he eg ession ee model in o he le els o ca bon, soil mois u e, and e ili y oughly inc easing om le o igh .
a iables used o i s calcula ion, e.g., bulk densi y, dep h o
humus and mine al soil, ca bon con en , and s oniness. These
a iables we e excluded om u he eg ession ee analysis,
which aimed o g oup da a acco ding o he p ocesses o soil
ca bon s ock de elopmen .
2.1.3 Reg ession ees
In o de o o ganize SOC da a in o g oups acco ding o he
physicochemical soil a iables and o be e unde s and he
na u e o measu ed da a, we gene a ed eg ession ees o
SOC s ocks by using ecu si e pa i ioning (RPART; Th-
e neau and A kinson, 1997). RPART is based on de eloping
decision ules o p edic ing and c oss- alida ion o con inu-
ous ou pu o soil ca bon s ocks ( eg ession ee). The clas-
si ica ion ee was buil by inding a single a iable, which
bes spli s he da a in o wo g oups. Each sub-g oup was e-
cu si ely sepa a ed un il no imp o emen could be made o
he soil ca bon s ock es ima ed by using he spli -based e-
g ession model. The complex esul an eg ession ee model
was c oss- alida ed o a nes ed se o sub- ees by compu -
ing he es ima e o soil ca bon s ock o im back he ull ee.
When building he eg ession ee models, we excluded
a iables such as bulk densi y, ca bon con en s o soil lay-
e s, soil dep h, and s oniness, since hese measu ed a iables
we e used o de e mining he o al soil ca bon s ock. The
selec ed a iables o he RPART da a mining we e based
on he co ela ions analysis (see Sec . 2.1.2), he p ocesses
o soil o ganic ma e o ma ion (e.g., Husson e al., 2013)
and decomposi ion, and ep esen ed he soil ca ego ical a i-
ables (so ing o pa en ma e ial, soil ex u e, long- e m soil
mois u e, and humus o m), soil physicochemical a iables
Biogeosciences, 13, 4439–4459, 2016 www.biogeosciences.ne /13/4439/2016/
B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y 4445
(sand, clay, and sil con en , long- e m soil mois u e, highly
bound wa e , C /N a io, pH, CEC o o ganic, B, BC, and C
ho izons), clima ic a iables (annual mean ai empe a u e,
annual p ecipi a ion sum), and s and and si e cha ac e is ics
( ee species co e age o pine, sp uce and deciduous, o al
olia li e inpu , p oduc i i y class and N deposi ion). Al e -
na i ely, we also an eg ession and classi ica ion analysis by
excluding all measu ed soil a iables because soil a iables
a e o en una ailable o landscape le el modeling.
The eg ession ee model sepa a ed he measu ed o-
al SOC s ocks ( Cha−1) in o 10 g oups. The ca ion ex-
change capaci y o he BC ho izon (CEC, mmolckg−1) di-
ided all he samples in o wo- hi ds o lowe SOC s ock
g oups (means be ween 65 and 130 Cha−1) and one- hi d o
la ge g oups (means be ween 86 and 269 Cha−1; Fig. 2a).
The g oup o he smalles SOC s ock consis ed o 959 sam-
ples compa ed o eigh samples o he g oup wi h he la ges
SOC s ocks. We acknowledge ha his is a small dis inc
g oup based only on eigh obse a ions. Howe e , we did
no ha e any easons o exclude hese da a poin s as ou lie s.
These obse a ions indica ed highly e ile condi ions (high
N deposi ion, he la ges H100 among g oups (31m), second
la ges li e inpu , he highes empe a u e and p ecipi a ion
on well-d ained soil) (Fig. 2, Table S1 in he Supplemen ).
Two- hi ds o samples wi h smalle SOC s ocks we e sub-
di ided by CEC and he ype so ing o soil pa en ma e ial
(so ed o unso ed). One- hi d o samples wi h la ge SOC
s ocks was subdi ided by he C /N a io, CEC, N deposi ion
among o he s. Roughly gene alized, g oups om le o igh
o om 1 o 10 o med a g adien in le els o SOC s ock,
mois u e, nu ien s a us, and p oduc ion (Fig. 2, Table S1).
The al e na i e eg ession ee model was buil wi h a i-
ables o he han soil p ope ies. The eg ession ee wi h he
annual mean ai empe a u e, he annual p ecipi a ion sum
and he pe cen age o pine ees in he s and, and he ni-
ogen deposi ion sepa a ed measu ed SOC s ocks ( Cha−1)
in o i e g oups (Fig. S3). Colde g oups wi h smalle SOC
s ocks (wi h means 67 and 85) had less li e inpu (below
3 Cha−1) and a low si e p oduc i i y index (H100 <20 m;
Table S2).
2.2 Soil ca bon s ock modeling
The Q model (Rol and Åg en, 1999) is a con inuous mech-
anis ic li e decomposi ion model desc ibing change o soil
o ganic ma e o e ime. The decomposi ion a e o he
b anch, s em, needle, ine oo , and woody li e ac ions
is con olled by he empe a u e, li e quali y, mic obial
g ow h, and li e in asion a e. The model has been cali-
b a ed o se en clima ic egions o Sweden in o de o ac-
coun o Swedish empe a u e and p ecipi a ion g adien s
(O iz e al., 2011; Table 3). The Q model was applied in
se e al s udies o SOC s ock and change es ima ion in Swe-
den (e.g., S endahl e al., 2010; O iz e al., 2013; Åg en
e al., 2007). The Q model was un o se en Swedish cli-
ma ic egions (O iz e al., 2011). The mean egional pa ame-
e iza ion om he calib a ion o he 2011 Q model was used
o he plo simula ions. Thus, he simula ions in each e-
gion ep esen a ia ions in clima e and li e inpu and no
pa ame e a ia ions. The equilib ium soil ca bon s ocks a e
es ima ed in he model using he equa ion o equilib ium
soil ca bon s ock, which is de i ed om he decomposi ion
unc ions wi h cons an amoun s and quali y o li e inpu .
The Yasso07 model (Tuomi e al., 2009, 2011) is one o he
mos widely applied SOC models. The model was calib a ed
based on almos 10 000 measu emen s o li e decomposi-
ion om Eu ope, No h and Sou h Ame ica (Table 3). The
equi ed annual inpu s o li e all, i s size and chemical com-
posi ion, empe a u e, and p ecipi a ion de e mine he de-
composi ion and seques a ion a es o soil o ganic ma e .
Yasso07 es ima es SOC s ock o a dep h o 1 m (o ganic and
mine al laye s), change o SOC s ock, and he e o ophic soil
espi a ion. Species-speci ic chemical composi ion o di e -
en li e compa men s o Yasso07 we e used acco ding o
Liski e al. (2009). The ini ial soil o ganic ma e o Yasso07
was ze o. The simula ed soil ca bon s ock co esponding o
equilib ium be ween he li e inpu and decomposi ion was
achie ed by a Yasso07 spin-up un o 10 000 yea s. Yasso07
uns used li e inpu s o he equilib ium o es biomasses
(see Sec . 2.1.1) and clima e a iables (annual ai empe a-
u e, mon hly empe a u e ampli ude, and annual p ecipi a-
ion). The global pa ame e alues o decomposi ion a es,
low a es, and o he dependencies o he Yasso07 soil ca -
bon model we e adop ed om Tuomi e al. (2011) and he
es ima es o Yasso07 SOC s ocks we e used in compa ison
wi h measu emen s and o he models. We did no use he
SOC s ocks simula ed wi h he mo e ecen Yasso07 pa am-
e e s based on he li e decomposi ion da a om he No dic
coun ies (Ran aka i e al., 2012), because he SOC s ocks
simula ed wi h he global pa ame e alues p oduced a be e
i wi h SFSI measu emen s.
The CENTURY ma hema ical model o iginally de el-
oped o g assland sys ems (Pa on e al., 1987, 1992) has
been since modi ied o a ious ecosys ems including bo eal
o es s (Nalde and Wein, 2006). The CENTURY is also one
o he mos widely applied models. The soil o ganic ma -
e in he model consis s o ac i e, slow, and passi e pools,
which ha e di e en TR (Table 3). The decomposi ion a es
a e modi ied by empe a u e and mois u e, and in addi ion
he decomposi ion a es o he slow and passi e pools ely
on lignin o N and C o N a ios, while he ac i e pool de-
composi ion a e elies on soil ex u e. The model simula es
soil o ganic ma e o a dep h o 20cm. The model simu-
la es plan p oduc ion and pools o li ing biomass, while TR
o biomass pools de e mine he li e all inpu s o soil. To
compa e he pe o mance o he soil sub-model wi h o he
soil ca bon dynamics models, Q and Yasso07, we only used
he CENTURY soil sub-model. We used he same li e all
inpu s as used by he Q and Yasso07 simula ions, which
we e es ima ed by ou li e all modeling (see Sec . 2.1.1).
www.biogeosciences.ne /13/4439/2016/ Biogeosciences, 13, 4439–4459, 2016
4446 B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y
Table 3. Desc ip ion o models and da a inpu s ele an o his s udy.
Model Yasso07 Q CENTURY 4.0 soil submodel
Time s ep Yea Yea Mon h
Pa ame e iza ion Global Scandina ian Combined global wi h si e speci ic
Ca bon pools Labile (acid -, wa e -, and e hanol- sol-
uble and non-soluble), ecalci an (hu-
mus)
Coho s ( oliage, s ems, b anches,
coa se oo s, ine oo s, “g ass”), soil
o ganic
Li e (su ace s uc u al and
me abolic, belowg ound s . and
me .), su ace mic obial, soil
o ganic ma e (ac i e, slow and
passi e)
Biomass Biomass componen s es ima ed by allome ic biomass unc ions and p o ided s and da a o li e inpu es ima ion
Li e amoun Annual o mon hly ac ions o biomass componen s (species speci ic, same o al li e inpu s o all models)
Li e quali y Li e a u e-based solubili ies Es ima ed coho s quali ies C/N a ios and lignin /N a ios
Tempe a u e ai Annual mean, mon hly ampli ude Annual mean Max and min mon hly mean
P ecipi a ion Annual o al – Mon hly o al
Soil p ope ies – – Bulk densi y, sand, sil , and clay con en
Soil dep h (m) 1 – 0.2
The li e inpu s e lec ed N deposi ion and si e p oduc i i y
(Fig. S11). Fo CENTURY we adop ed gene al pa ame e s
om he pa ame e ile “ ee.100”, pa ame e s o si e “AND
H_J_ANDREWS” o coni e s, and si e “CWT Cowee a” o
deciduous ees. The N dynamics in CENTURY sub-model
included uning si e-speci ic pa ame e s o opsoil mine al N
ela i e o N deposi ion (Th oop e al., 2004) and educ ion
o C/N a io o he li e all up o 15% o mos p oduc i e
si es (Me ilä e al., 2014). We also accoun ed o si e-speci ic
soil d ainage by a ying i s pa ame e be ween 1 and 0.6 el-
a i e o long- e m soil wa e con en anging be ween 10 and
50% (Raich e al., 2000). The CENTURY SOC s ocks sim-
ula ion we e un wi h equilib ium o es li e inpu s, si e-
speci ic C/N a ios o li e all, si e-speci ic soil pa ame e s
(speci ic bulk densi y, sand, sil , and clay con en , mine al N
in opsoil, and d ainage) and clima e a iables (mon hly ai
empe a u e, and mon hly p ecipi a ion). In o de o accoun
o he deep soil ca bon (Jobbágy and Jackson, 2000), we
scaled CENTURY es ima es ep esen ing he opsoil ho izon
by adding 40% o es ima ed si e-speci ic SOC s ock. The
simula ed equilib ium SOC s ocks we e es ima ed by a spin-
up un o 5000 yea s. The numbe o yea s o each equi-
lib ium (equilib ium be ween he li e inpu and decomposi-
ion) was sough empi ically on 100 andom si es, and di e s
om Yasso07 and Q models.
3 Resul s
The dis ibu ions o Yasso07, Q, and CENTURY model es-
ima es o o al SOC s ocks ( Cha−1) we e in ag eemen
o wo- hi ds o he measu ed da a wi h lowe SOC s ock
(Fig. 3, dis ibu ions o g oups 1, 2, and 4). The emain-
ing one- hi d o SOC da a we e unde es ima ed by models.
This one- hi d o da a we e sepa a ed in o se en physico-
chemical soil g oups (means o g oups anging om 104 o
excep ionally la ge 269 Cha−1, see Fig. 3, dis ibu ions o
g oups 3, and 5–10). The linea eg ession o mean le els o
all 10 physicochemical soil g oups (weigh ed by he numbe
o samples in each g oup) be ween he modeled and mea-
su ed SOC s ocks showed smalle unde es ima ion o CEN-
TURY compa ed o Yasso07 and Q models (Fig. 4). The
weigh ed oo mean squa e e o (RMSE) was 27.5 ( Cha−1)
o CENTURY and 31.6 and 38.8 o Yasso07 and Q, espec-
i ely. The p opo ion o explained a iance was la ge o Q
( 2=0.58) han o Yasso07 and CENTURY ( 2=0.42 and
0.32; Fig. 4). The de ia ion o he dis ibu ions o CENTURY
SOC s ocks, simula ed using soil bulk densi y, sand, sil , and
clay con en , we e lowe han hose o Yasso07 and Q es i-
ma es o 10 physicochemical soil g oups (Fig. 3). Accoun -
ing o si e-speci ic soil ex u e (clay, sil , and sand con en )
and s uc u e (bulk densi y) by he CENTURY model im-
p o ed SOC s ock es ima es o e ile si es wi h high clay
con en , bu no o si es wi h high N deposi ion. Va ying
CENTURY pa ame e s o si e-speci ic opsoil mine al ni o-
gen and C/N a io o he li e all showed ha his impac on
SOC s ocks es ima es was small in compa ison o sensi i i y
o SOC s ock es ima es o li e all (Fig. S12). The applica-
ion o si e-speci ic d ainage on ou mos ly well-d ained soils
showed mino impac on es ima ed CENTURY SOC s ocks.
As expec ed, he models clea ly showed less a ia ion han
he measu emen s. The shi o he mean alues om he cen-
e o dis ibu ion, he wid h o con idence in e als o means,
and he wid h o he ails o dis ibu ions we e clea ly la ge
o he measu emen s han o he modeled es ima es (Fig. 3).
The modeled dis ibu ions ag eed o he poo –medium e -
ili y soils wi h low and medium measu ed SOC s ocks, low
and medium CEC, unso ed pa en ma e ial, low empe a-
u es, and low p oduc ion (g oups 1, 2, and 4; Figs. 2, 3,
Table S1). Disag eemen be ween modeled and measu ed
SOC s ock dis ibu ions we e o med on e ile soils wi h
so ed pa en ma e ial (g oups 3 and 5), soils wi h highe
wa e con en (g oups 3, 5, and 10), whe e ni ogen depo-
si ion was la ge (g oups 7 and 8), and whe e CEC was me-
dian o la ge (Figs. 2, 3). The la ges de ia ion be ween he
Biogeosciences, 13, 4439–4459, 2016 www.biogeosciences.ne /13/4439/2016/
B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y 4447
0 100 200 300
Measu emen s
Yasso07
CENTURY
Q
0 100 200 300
n=959 n=909 n=136 n=335 n=182 n=296 n=180 n=8 n=142 n=83
12345678910
Soil ca bon s ock ha ( −1)
Soil g oups
Figu e 3. Bean plo o dis ibu ions o he soil ca bon ( Cha−1) measu emen s (g ay ill) and es ima es o 10 physicochemical g oups. The
ull and dashed ho izon al lines ep esen he g oup means and hei con idence in e als. The nis he numbe o samples. Fo desc ip ion o
g oup le els o SOC s ocks, mois u e, and e ili y see Fig. 2 and Table S1.
measu ed and modeled dis ibu ions was ound o he ela-
i ely small physicochemical g oups o soils (3%) ypical o
highly bound wa e and pea humus ypes (g oups 8 and 10;
Figs. 2, 3). The dis ibu ions o measu ed o al SOC s ocks
( Cha−1) gene ally inc eased o he g oups wi h highe nu-
ien s a us (Figs. 3, S4). The dis ibu ions o SOC s ocks
in mine al soil we e la ge han hose in humus ho izon, and
dis ibu ions o mine al SOC s ocks inc eased wi h e ili y
sligh ly mo e han dis ibu ions o SOC s ocks in humus ho i-
zon (Fig. S4).
A e excluding all he soil physicochemical cha ac e is-
ics om he ecu si e pa i ioning, he SOC s ock dis ibu-
ions o i e g oup eg ession ee models (Fig. S3, Table S2)
we e in ag eemen be ween he measu emen s and model es-
ima es o h ee g oups (77% o samples) and de ia ed o
wo g oups (23%; Fig. S5). The modeled SOC s ock dis-
ibu ions ag eed wi h measu emen s o all models on si es
wi h low annual empe a u es <3 ◦C in no he n si es (low-
C.cold.pine, low-C.cold.o he ) and o wa me condi ions in
middle Sweden on si es wi h low ni ogen deposi ion and me-
dian SOC s ocks (Fig. S5). Howe e , he models unde es i-
ma ed SOC s ocks on si es wi h high (>10 kgNha−1y−1) N
deposi ion (21% o samples) and on si es wi h wa m and d y
clima e (2% o samples; Fig. S5).
The a ia ion o densi y unc ions o modeled SOC s ocks
o 10 physicochemical g oups (Fig. 3) was simila o he
a ia ion o he o al annual plan li e inpu ( Cha−1;
Fig. S6) indica ing ha li e all was he main d i e o SOC
accumula ion in he models . The mean le els o annual plan
li e inpu and mean SOC s ocks o 10 soil g oups we e
mo e s ongly co ela ed o Yasso07 and Q models (wi h
2 alues 0.86 and 0.96, espec i ely) han o CENTURY
( 2=0.52). Al hough, models pe o med easonably well
o he la ges soil g oups o nu ien and p oduc ion le els
(Figs. 3 and 4), none o he models was able o p edic a i-
a ion o indi idual samples (Fig. S7). The model es ima es
we e well co ela ed be ween Yasso07 and CENTURY wi h
2 anging om 45 o 73% o indi idual samples o 10 soil
g oups, whe eas he co ela ions o es ima es be ween Q and
he o he wo models we e lowe (Fig. S8).
4 Discussion
4.1 SOC s ock dis ibu ions linked o mechanisms o
SOM s abiliza ion
I has been sugges ed ha p ocess-based soil ca bon mod-
els wi h he cu en o mula ion lacking majo soil en i on-
men al and biological con ols o decomposi ion would ail
o condi ions whe e hese con ols p edomina e (Schmid
e al., 2011; A e ill e al., 2014). E en so, he e ec o he
soil p ope ies on SOC s ocks, e.g., soil nu ien s a us in
he widely used models such as Yasso07, Q, and CENTURY,
ha e no p e iously been quan i a i ely e alua ed. We ound
ha in compa ison wi h Swedish o es soil in en o y da a,
he models based on he amoun and quali y o inhe en s uc-
u al p ope ies o plan li e (Q, Yasso07, and CENTURY)
p oduced accu a e SOC s ock es ima es o wo- hi ds o
no he n bo eal o es soils in Sweden. Two- hi ds o he
dis ibu ions o SOC s ocks measu emen s o SFSI ag eed
wi h dis ibu ions o SOC s ock es ima es o he Q, Yasso07,
and CENTURY soil ca bon models (Fig. 3, dis ibu ions o
g oups 1, 2, and 4). Howe e , he SOC s ocks unde es ima-
ion by hese models o one- hi d o he da a (Fig. 3, dis i-
www.biogeosciences.ne /13/4439/2016/ Biogeosciences, 13, 4439–4459, 2016
4454 B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y
Appendix B: Models o o es d y weigh biomass wi h
APAR
We i ed species-speci ic exponen ial eg ession models
be ween he biomass componen s (s em, b anch, oliage,
s ump, coa se oo s, ine oo s, all in kgha−1) o obse ed
s a e o es and he obse ed ac ion o abso bed adia ion
( APAR) (s a is ics o he eg ession models in Table B1 in
Appendix B). The biomass componen s de i ed wi h allo-
me ic models (measu ed) and hose de i ed wi h APAR
models (modeled) showed s ong co ela ions (Fig. B1 in
Appendix B). In o de o model he long- e m mean o es
biomass “equilib ium o es biomass” we applied he APAR
biomass models o he modeled APAR70 alues.
Table B1. Pa ame e es ima es and hei s anda d e o s o he co-
e icien s o he d y weigh biomass (kgha−1) models wi h he ac-
ion o abso bed adia ion (y=ab APAR ) o Sco s pine, No way
sp uce, and deciduous s ands.
y=ab APAR Species a±SE b±SE adj.R2
B anch pine 610±21 122±6 0.92
sp uce 877±35 54±2 0.92
deciduous 290±26 156±16 0.89
Fine oo pine 422±13 21 ±1 0.84
sp uce 317±14 15±1 0.80
deciduous 453±28 14±1 0.82
Foliage pine 361±24 86±8 0.71
sp uce 766±40 33±2 0.83
deciduous 141±28 71±16 0.56
Roo pine 703 ±26 183 ±10 0.92
sp uce 629±32 113±7 0.90
deciduous 359±33 150±16 0.89
S em and ba k pine 1793±84 254 ±17 0.89
sp uce 974±72 229±19 0.86
deciduous 972±98 161±18 0.88
S ump pine 232±10 214±13 0.89
sp uce 171±10 129±9 0.88
deciduous 80±8 216±25 0.87
p < 0.001 o all pa ame e s.
Biogeosciences, 13, 4439–4459, 2016 www.biogeosciences.ne /13/4439/2016/

B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y 4455
0 50 100 150
0 50 100 150
S em+ba k
Modeled ( C ha−1)
Measu ed ( C ha−1)
2 = 0.95
0 10 20 30
0 10 20 30
B anch
Modeled ( C ha−1)
Measu ed ( C ha−1)
2 = 0.97
0 5 10 15
0 5 10 15
Foliage
Modeled ( C ha−1)
Measu ed ( C ha−1)
2 = 0.94
0 5 10 15
0 5 10 15
S ump
Modeled ( C ha−1)
Measu ed C ha ( −1)
2 = 0.96
0 10 30 50
0 10 20 30 40 50
Roo
Modeled ( C ha−1)
Measu ed C ha ( −1)
2 = 0.97
01234
0 1 2 3 4
Fine oo
Modeled ( C ha−1)
Measu ed ( C ha−1)
2 = 0.96
Figu e B1. Sca e plo s (n=3698 in each panel) o he d y weigh ee biomass componen s ( Cha−1) be ween “modeled” (es ima ed based
on ac ion o abso bed adia ion, APAR, and ou APAR models) and “measu ed” (es ima ed based on basic ee dimensions and allome ic
biomass models). The 2 alues ep esen he coe icien o de e mina ion indica ing how close he modeled alues i he measu ed alues.
www.biogeosciences.ne /13/4439/2016/ Biogeosciences, 13, 4439–4459, 2016
4456 B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y
Appendix C: Models o unde s o y ege a ion
We used Swedish o es in en o y g ound ege a ion co -
e age (%) da a isually moni o ed be ween 1993 and 2002
on 2440 plo s a ound Sweden wi h al oge he 4472 obse a-
ions sepa a ely o species o o es loo ege a ion o hei
classes (Table S3). In o de o de i e he g ound ege a ion
biomass and o apply he co e age/biomass con e sion unc-
ions (Leh onen e al., 2016), we g ouped he species co -
e age obse a ions in o i e unc ional ypes (dwa sh ubs,
he bs, g asses, moss, and lichen; Table S3). The applied
co e age/biomass con e sion unc ions es ima ed sepa a ely
he abo e- and below-g ound biomass componen s o dwa
sh ubs, he bs, and g asses, and o al biomass o moss, and
lichen.
Excep he unde s o y co e age, he o es in en o y da a
also con ained basic ee dimensions (diame e and heigh
o ees) and s and a iables (species dominance, age, basal
a ea, si e p oduc i i y class indica ed by he heigh o la ges
ess a 100 yea s o s ands age), and also we linked he plo s
by hei closes p oximi y o SMHI wea he s a ions wi h
wea he da a (ai empe a u e, p ecipi a ion) and loca ion a -
ibu es o he wea he s a ions (la i ude, longi ude, al i ude).
Table C1. Pa ame e es ima es and hei s anda d e o s o he coe icien s o he o es unde s o y ege a ion d y weigh biomass (kgha−1)
models (Eq. C1) o unc ional ypes (1 – dwa sh ubs, 2 – he bs, 3 – g asses, 4 – mosses, and 5 – lichens) wi h in e cep (a) and n– numbe
o p edic o s (b1 – age (yea s), b2 – basal a ea (m2ha−1), b3 – annual ai empe a u e (◦C), b4 – la i ude (◦), b5 – H100 (heigh o ees a
100 yea s o age, m), b6 – H100 o sp uce ees (m), b7 – H100 o pine ees (m), b8 – pine dominance (0/1), and b9 – sp uce dominance
(0/1)). Fo he la in names o species included in o unde s o y unc ional ypes see Table S3.
Wa±Eb1±SE b2±SE b3±SE b4±SE b5±SE b6±SE b7±SE b8±SE b9±SE adj.R2
Abo e 1 24.28 ±0.32 0.13 ±0.01 -0.43 ±0.02 7.13±0.33 0.29
g ound 2 −82.13 ±6.8 −0.1 ±0.1a1.23 ±0.1 0.77±0.03 0.12
3 4.07±0.30 −0.16 ±0.01 0.27 ±0.01 −1.36 ±0.15 0.21
4 32.9±0.62 −0.78 ±0.04 0.48 ±0.06 3.66 ±0.3 5.76 ±0.29 0.22
5 19.91±0.57 −0.13 ±0.01 −0.45 ±0.02 6.31 ±0.29 0.25
o al 43.68±0.29 0.12 ±0.01 −0.41 ±0.01 6.34 ±0.3 0.30
Below 1 −256.3±3.5 0.1±0.01 −0.35±0.02 5.05±0.06 8.56 ±0.35 0.75
g ound 2 −89.34 ±7.85 −0.03 ±0.1b1.4 ±0.12 0.78±0.04 −4.97 ±0.27 0.19
3 5.97±0.37 −0.19 ±0.01 0.32 ±0.01 −1.78 ±0.19 0.21
o al −251.9±3.3 −0.2 ±0.01 5.15 ±0.05 0.7
To al −222.7 ±4.0 0.12 ±0.01 −0.44±0.02 4.9 ±0.07 0.67
p < 0.001 o all pa ame e s excep o ap=0.44, and bp=0.84.
We buil linea models o d y weigh biomass o unde s o y
ege a ion (kgha−1) in a wo le el selec ion o he p edic o s
om s and, wea he and loca ion a iables. Fi s , we selec ed
he p edic o s in o linea models by using R package “Mass”
and i s s epwise model selec ion by exac Akaike’s in o ma-
ion c i e ion (AIC; Venables and Ripley, 2002). Second, we
e ined he model by using “ elaimpo” R package es ima ing
use ulness (G ömping, 2006), o ela i e impo ance o each
o he p edic o s in he model, and by selec ing only p edic-
o s wi h ela i e impo ance ≥0.1. The gene al o m o he
models was
yi=a+b1x1+...+bnxn+ε, (C1)
whe e yiis he unde s o y d y weigh biomass (kgha−1), x1
... xna e he p edic o s, a,b1... bna e pa ame e s o he
i h unde s o y unc ional ype (Table C1 in Appendix C), and
εis he esidual e o . S a is ics o he models a e shown in
Table C1 in Appendix C. Sca e plo s be ween he measu ed
co e age de i ed biomass and modeled d y weigh biomass
(kgha−1) o he unc ional ypes o g ound ege a ion o he
o es s in hei obse ed s a e close o he es ima ed equilib-
ium a e shown on Fig. S9.
Biogeosciences, 13, 4439–4459, 2016 www.biogeosciences.ne /13/4439/2016/
B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y 4457
The Supplemen ela ed o his a icle is a ailable online
a doi:10.5194/bg-13-4439-2016-supplemen .
Acknowledgemen s. We hank he Finnish Minis y o En i on-
men and he Finnish Minis y o Ag icul u e and Fo es y o
unding his wo k h ough he Me la p ojec 7509 “Imp o ing soil
ca bon es ima ion o g eenhouse gas in en o y”, and Academy o
Finland o unding he mobili y p ojec s 276300 and 276602. We
would like o hank he edi o and he e iewe s o hei aluable
commen s imp o ing he manusc ip .
Edi ed by: A. V. Elisee
Re iewed by: h ee anonymous e e ees
Re e ences
Adai , E. C., Pa on, W. J., Del G osso, S. J., Sil e , W. L., Ha mon,
M. E., Hall, S. A., Bu ke, I. C., and Ha , S. C.: Simple h ee-pool
model accu a ely desc ibes pa e ns o long- e m li e decompo-
si ion in di e se clima es, Global Change Biol., 14, 2636–2660,
2008.
Åg en, G. I., Bosa a, E., and Magill, A. H.: Combining heo y and
expe imen o unde s and e ec s o ino ganic ni ogen on li e
decomposi ion, Oecologia, 128, 94–98, 2001.
Åg en, G. I. and Hy önen, R.: Changes in ca bon s o es in Swedish
o es soils due o inc eased biomass ha es and inc eased em-
pe a u es analysed wi h a semi-empi ical model, Fo es Ecol.
Manage., 174, 25–37, 2003.
Åg en, G., Hy önen, R., and Nilsson, T.: A e Swedish o es soils
sinks o sou ces o CO2—model analyses based on o es in en-
o y da a, Biogeochemis y, 82, 217–227, 2007.
Amundson, R.: The ca bon budge in soils, Annu. Re . Ea h Plane .
Sci., 29, 535–562, 2001.
A e ill, C., Tu ne , B. L., and Finzi, A. C.: Myco hiza-media ed
compe i ion be ween plan s and decompose s d i es soil ca bon
s o age, Na u e, 505, 543–545, 2014.
Be h ong, S. T., Jobbágy, E. G., and Jackson, R. B.: A global me a-
analysis o soil exchangeable ca ions, pH, ca bon, and ni ogen
wi h a o es a ion, Ecol. Appl., 19, 2228–2241, 2009.
Boden, T. A., Ma land, G., and And es, R. J.: Global, e-
gional, and na ional ossil- uel CO2emissions, Ca bon Diox-
ide In o ma ion Analysis Cen e , Oak Ridge Na ional Labo-
a o y, US Depa men o Ene gy, Oak Ridge, Tenn., USA,
doi:10.3334/CDIAC/00001_V2010, 2010.
Cas ellano, M. J., Muelle , K. E., Olk, D. C., Sawye , J. E., and Six,
J.: In eg a ing Plan Li e Quali y, Soil O ganic Ma e S abiliza-
ion and he Ca bon Sa u a ion Concep , Glob. Change Biol., 21,
3200–3209, doi:10.1111/gcb.12982, 2015.
Cla holm, M. and Skyllbe g, U.: T ansloca ion o me als by ees
and ungi egula es pH, soil o ganic ma e u no e and ni ogen
a ailabili y in acidic o es soils, Soil Biol. Biochem., 63, 142–
153, 2013.
Clemen e, J. S., Simpson, A. J., and Simpson, M. J.: Associa ion o
speci ic o ganic ma e compounds in size ac ions o soils un-
de di e en en i onmen al con ols, O g. Geochem., 42, 1169–
1180, 2011.
Cools, N., Ves e dal, L., De Vos, B., Vanguelo a, E., and Hansen,
K.: T ee species is he majo ac o explaining C: N a ios in Eu-
opean o es soils, Fo es Ecol. Manage., 311, 3–16, 2014.
Co u o, M. F., Wallens ein, M. D., Boo , C. M., Dene , K., and
Paul, E.: The Mic obial E iciency-Ma ix S abiliza ion (MEMS)
amewo k in eg a es plan li e decomposi ion wi h soil o ganic
ma e s abiliza ion: do labile plan inpu s o m s able soil o -
ganic ma e ?, Glob. Change Biol., 19, 988–995, 2013.
Deluca, T. H. and Bois enue, C.: Bo eal o es soil ca bon: dis i-
bu ion, unc ion and modelling, Fo es y, 85, 161–184, 2012.
Dungai , J. A. J., Hopkins, D. W., G ego y, A. S., and Whi mo e, A.
P.: Soil o ganic ma e u no e is go e ned by accessibili y no
ecalci ance, Glob. Change Biol., 18, 1781–1796, 2012.
Falloon, P., Jones, C. D., Ades, M., and Paul, K.: Di ec soil mois-
u e con ols o u u e global soil ca bon changes: An impo -
an sou ce o unce ain y, Global Biogeochem. Cy., 25, GB3010,
doi:10.1029/2010GB003938, 2011.
Fan, Z., Ne , J. C., Ha den, J. W., and Wickland, K. P.: Bo-
eal soil ca bon dynamics unde a changing clima e: A model
in e sion app oach, J. Geophys. Res.-Biogeo., 113, G04016,
doi:10.1029/2008JG000723, 2008.
Fe nández-Ma ínez, M., Vicca, S., Janssens, I. A., Sa dans, J.,
Luyssae , S., Campioli, M., Chapin III, F. S., Ciais, P., Malhi,
Y., Obe s eine , M., Papale, D., Piao, S. L., Reichs ein, M., Roda,
F., and Penuelas, J.: Nu ien a ailabili y as he key egula o o
global o es ca bon balance, Na u e Clima e Change, 4, 471–
476, 2014.
F anklin, O., Högbe g, P., Ekblad, A., and Åg en, G. I.: Pine o -
es loo ca bon accumula ion in esponse o N and PK addi-
ions: bomb 14C modelling and espi a ion s udies, Ecosys ems,
6, 644–658, 2003.
G ömping, U.: Rela i e impo ance o linea eg ession in R: he
package elaimpo, J. S a . So w., 17, 1–27, 2006.
Hagglund, B. and Lundma k, J.: Si e index es ima ion by means o
si e p ope ies, Sco s pine and No way sp uce in Sweden, S ud.
Fo . Suec., 138, 38, 1977.
Hä könen, S., Pulkkinen, M., Duu sma, R., and Mäkelä, A.: Es i-
ma ing annual GPP, NPP and s em g ow h in Finland using sum-
ma y models, Fo . Ecol. Manage., 259, 524–533, 2010.
Husson, O.: Redox po en ial (Eh) and pH as d i e s o
soil/plan /mic oo ganism sys ems: a ansdisciplina y o e iew
poin ing o in eg a i e oppo uni ies o ag onomy, Plan Soil,
362, 389–417, 2013.
Jobbágy, E. G. and Jackson, R. B.: The e ical dis ibu ion o soil
o ganic ca bon and i s ela ion o clima e and ege a ion, Ecol.
Appl., 10, 423–436, 2000.
Kamme , A. and Hagedo n, F.: Mine alisa ion, leaching and s a-
bilisa ion o 13C-labelled lea and wig li e in a beech o -
es soil, Biogeosciences, 8, 2195–2208, doi:10.5194/bg-8-2195-
2011, 2011.
Ki schbaum, M. U. F.: Will Changes in Soil O ganic Ca bon Ac as
a Posi i e o Nega i e Feedback on Global Wa ming?, Biogeo-
chemis y, 48, 21–51, 2000.
Kleja, D. B., S ensson, M., Majdi, H., Jansson, P., Lang all, O.,
Be gk is , B., Johansson, M., Weslien, P., T uusb, L., and Lin-
d o h, A.: Pools and luxes o ca bon in h ee No way sp uce
ecosys ems along a clima ic g adien in Sweden, Biogeochem-
is y, 89, 7–25, 2008.
www.biogeosciences.ne /13/4439/2016/ Biogeosciences, 13, 4439–4459, 2016
4458 B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y
Ku z, W. A., Beukema, S. J., and Apps, M. J.: Es ima ion o oo
biomass and dynamics o he ca bon budge model o he C ana-
dian o es sec o , Can. J. Fo es Res., 26, 1973–1979, 1996.
Leh onen, A. and Heikkinen, J.: Unce ain y o upland soil ca bon
sink es ima e o Finland, Can. J. Fo es Res., 45, 1–13, 2015.
Leh onen, A., Sie änen, R., Mäkelä, A., Mäkipää, R., Ko honen, K.
T. and Hokkanen, T.: Po en ial li e all o Sco s pine b anches in
sou he n Finland, Ecol. Modell., 180, 305–315, 2004.
Leh onen, A., Linkosalo, T., Pel oniemi, M., Sie änen, R., Mäkipää,
R., Tamminen, P., Salemaa, M., Nieminen, T., Tupek, B., Heikki-
nen, J., and Koma o , A.: Soil ca bon s ock es ima es in a na-
ionwide in en o y: e alua ing pe o mance o he ROMUL and
Yasso07 models, Geosci. Model De . Discuss., in e iew, 2016a.
Leh onen, A., Pal iainen, M., Ojanen, P., Kalliokoski, T., Nöjd, P.,
Kukkola, M., Pen ilä, T., Mäkipää, R., Leppälammi-Kujansuu,
J. and Helmisaa i, H.: Modelling ine oo biomass o bo eal ee
s ands using si e and s and a iables, Fo es Ecol. Manag., 359,
361–369, doi:10.1016/j. o eco.2015.06.023, 2016b.
Leppälammi-Kujansuu, J., A o, L., Salemaa, M., Hansson, K.,
Kleja, D. B., and Helmisaa i, H.: Fine oo longe i y and ca bon
inpu in o soil om below-and abo eg ound li e in clima ically
con as ing o es s, Fo es Ecol. Manage., 326, 79–90, 2014.
Lindén, A., G.: Swedish Geological Su ey epo , pp. 10, a ail-
able a : h p:// esou ce.sgu.se/p oduk e /ae/ae118-besk i ning.
pd (las access: 3 Augus 2016), 2002.
Liski, J., Tuomi, M., and Rasinmäki, J.: Yasso07 use -in e ace
manual, Finnish En i onmen Ins i u e, Helsinki, 2009.
Liski, J., Leh onen, A., Palosuo, T., Pel oniemi, M., Egge s, T.,
Muukkonen, P., and Mäkipää, R.: Ca bon accumula ion in Fin-
land’s o es s 1922–2004–an es ima e ob ained by combina ion
o o es in en o y da a wi h modelling o biomass, li e and soil,
Ann. Fo es Sci., 63, 687–697, 2006.
Majdi, H.: Changes in ine oo p oduc ion and longe i y in ela ion
o wa e and nu ien a ailabili y in a No way sp uce s and in
no he n Sweden, T ee Physiol., 21, 1057–1061, 2001.
Malkonen, E.: Annual p ima y p oduc ion and nu ien cycle in a
bi ch s and, Commun. Ins . Fo . Fenn., 91, 1–35, 1977.
Manzoni, S., Taylo , P., Rich e , A., Po po a o, A., and Åg en, G. I.:
En i onmen al and s oichiome ic con ols on mic obial ca bon
use e iciency in soils, New Phy ol., 196, 79–91, 2012.
Ma klund, L.: , Biomassa unk ione ö all, g an och bö k i S e ige,
Biomass unc ions o pine, sp uce and bi ch in Sweden, Swedish
Uni e si y o Ag icul u al Sciences, Depa men o Fo es Su -
ey, Repo 45, ISSN 0348–0496, 1988.
McCo mack, M. L., C is ield, E., Raczka, B., Schnekenbu ge , F.,
Eissens a , D. M., and Smi hwick, E. A.: Sensi i i y o ou eco-
logical models o adjus men s in ine oo u no e a e, Ecol.
Model., 297, 107–117, 2015.
Me he ell, A. K.: Cen u y: Soil O ganic Ma e Model En i on-
men : Technical Documen a ion: Ag oecosys em Ve sion 4.0,
Colo ado S a e Uni e si y, 1993.
Me ilä, P., Mus ajä i, K., Helmisaa i, H., Hilli, S., Lind oos, A.,
Nieminen, T. M., Nöjd, P., Rau io, P., Salemaa, M., and Ukon-
maanaho, L.: Abo e-and below-g ound N s ocks in coni e ous
bo eal o es s in Finland: Implica ions o sus ainabili y o mo e
in ensi e biomass u iliza ion, Fo . Ecol. Manage., 311, 17–28,
2014.
Muukkonen, P. and Leh onen, A.: Needle and b anch biomass
u no e a es o No way sp uce (Picea abies), Can. J. Fo es
Res., 34, 2517–2527, 2004.
Nalde , I. A. and Wein, R. W.: A model o he in es iga ion o
long- e m ca bon dynamics in bo eal o es s o wes e n Canada:
I. Model de elopmen and alida ion, Ecol. Model., 192, 37–66,
2006.
Olsson, M. T., E landsson, M., Lundin, L., Nilsson, T., Nilsson, Å.,
and S endahl, J.: O ganic ca bon s ocks in Swedish Podzol soils
in ela ion o soil hyd ology and o he si e cha ac e is ics, Sil a
Fennica, 43, 209–222, 2009.
O iz, C., Ka l un, E., S endahl, J., Gä denäs, A. I., and Åg en, G.
I.: Modelling soil ca bon de elopmen in Swedish coni e ous o -
es soils—An unce ain y analysis o pa ame e s and model es i-
ma es using he GLUE me hod, Ecol. Model., 222, 3020–3032,
2011.
O iz, C. A., Liski, J., Gä denäs, A. I., Leh onen, A., Lundblad, M.,
S endahl, J., Åg en, G. I., and Ka l un, E.: Soil o ganic ca bon
s ock changes in Swedish o es soils – A compa ison o unce -
ain ies and hei sou ces h ough a na ional in en o y and wo
simula ion models, Ecol. Model., 251, 221–231, 2013.
O win, K. H., Ki schbaum, M. U., S John, M. G., and Dickie, I. A.:
O ganic nu ien up ake by myco hizal ungi enhances ecosys-
em ca bon s o age: a model-based assessmen , Ecol. Le ., 14,
493–502, 2011.
Palosuo, T., Foe eid, B., S ensson, M., Shu pali, N., Leh onen, A.,
He bs , M., Linkosalo, T., O iz, C., Rampazzo Todo o ic, G.,
Ma cinkonis, S., Li, C., and Jandl, R.: A mul i-model compa ison
o soil ca bon assessmen o a coni e ous o es s and, En i on.
Modell. So w., 35, 38–49, 2012.
Pa on, W. J., Schimel, D. S., Cole, C. V., and Ojima, D. S.: Analysis
o Fac o s Con olling Soil O ganic Ma e Le els in G ea Plains
G asslands, 51, 1173–1179, 1987.
Pa on, W., Ojima, D., and Schimel, D.: En i onmen al change in
g asslands: Assessmen using models, Clima e Change, 28, 111–
141, 1994.
Pa on, W.J., McKeown, R., Ki chne , V., and Ojima,D.: CEN-
TURY Use s’ Manual, Na u al Resou ce Ecology Labo a o y,
Colo ado S a e Uni e si y, F . Collins., 1992.
Pel oniemi, M., Pulkkinen, M., Au ela, M., Pumpanen, J., Kola i,
P. and Mäkelä, A.: A semi-empi ical model o bo eal- o es
g oss p ima y p oduc ion, e apo anspi a ion, and soil wa e –
calib a ion and sensi i i y analysis, Bo eal En i on. Res., 20,
2015.
Pe e sson, H. and S åhl, G.: Func ions o below-g ound biomass
o Pinus syl es is, Picea abies, Be ula pendula and Be ula
pubescens in Sweden, Scand., J. Fo . Res., 21, 84–93, 2006.
Raich, J. W., Pa on, W. J., Russell, A. E., San o d J , R. L., and Vi-
ousek, P. M.: Analysis o ac o s egula ing ecosys emde elop-
men on Mauna Loa using he Cen u y model, Biogeochemis y,
51, 161–191, 2000.
Ran aka i, M., Leh onen, A., Linkosalo, T., Tuomi, M., Tammi-
nen, P., Heikkinen, J., Liski, J., Mäkipää, R., Il esniemi, H., and
Sie änen, R.: The Yasso07 soil ca bon model–Tes ing agains e-
pea ed soil ca bon in en o y, Fo es Ecol. Manage., 286, 137–
147, 2012.
Rapalee, G., T umbo e, S. E., Da idson, E. A., Ha den, J. W., and
Veldhuis, H.: Soil Ca bon s ocks and hei a es o accumula ion
Biogeosciences, 13, 4439–4459, 2016 www.biogeosciences.ne /13/4439/2016/
B. ˇ
Tupek e al.: Unde es ima ion o modeled SOC s ocks linked o soil e ili y 4459
and loss in a bo eal o es landscape, Global Biogeochem. Cy.,
12, 687–701, 1998.
Repola, J.: Biomass equa ions o bi ch in Finland, Sil a Fenn., 42,
605–624, 2008.
Rawls, W. J., Pachepsky, Y. A., Ri chie, J. C., Sobecki, T. M., and
Bloodwo h, H.: E ec o soil o ganic ca bon on soil wa e e-
en ion, Geode ma, 116, 61–76, 2003.
Rol , C. and Åg en, G. I.: P edic ing e ec s o di e en ha es ing
in ensi ies wi h a model o ni ogen limi ed o es g ow h, Ecol.
Model., 118, 193–211, 1999.
R Co e Team R: A language and en i onmen o s a is ical com-
pu ing. R Founda ion o S a is ical Compu ing, Vienna, Aus-
ia, a ailable a : h p://www.R-p ojec .o g/ (las access: 3 Au-
gus 2016), 2014.
Scha lemann, J. P., Tanne , E. V., Hiede e , R., and Kapos, V.:
Global soil ca bon: unde s anding and managing he la ges e -
es ial ca bon pool, Ca bon Managemen , 5, 81–91, 2014.
Schlesinge , W. H.: Ca bon Seques a ion in Soils, Science, 284,
2095–2095, 1999.
Schmid , M. W. I., To n, M. S., Abi en, S., Di ma , T., Guggen-
be ge , G., Janssens, I. A., Klebe , M., Kogel-Knabne , I.,
Lehmann, J., Manning, D. A. C., Nannipie i, P., Rasse, D. P.,
Weine , S., and T umbo e, S. E.: Pe sis ence o soil o ganic ma -
e as an ecosys em p ope y, Na u e, 478, 49–56, 2011.
Six, J., Conan , R. T., Paul, E. A., and Paus ian, K.: S abiliza ion
mechanisms o soil o ganic ma e : Implica ions o C-sa u a ion
o soils, Plan Soil, 241, 155–176, 2002.
SLU: Ma kin o, a ailable a : h p://www-ma kin o.slu.se/eng/
index.h ml (las access: 3 Augus 2016), 2011.
Smi h, P.: An o e iew o he pe manence o soil o ganic ca bon
s ocks: in luence o di ec human-induced, indi ec and na u al
e ec s, Eu . J. Soil Sci., 56, 673–680, 2005.
Sollins, P., Homann, P., and Caldwell, B. A.: S abiliza ion and
des abiliza ion o soil o ganic ma e : mechanisms and con ols,
Geode ma, 74, 65–105, 1996.
S a is ics Finland: G eenhouse gas emissions in Finland 1990–
2011, in: Na ional In en o y Repo o he UNFCCC Sec e a ia ,
Minis y o he En i onmen , Helsinki, Finland, 285–286, 2013.
S endahl, J., Johansson, M., E iksson, E., Nilsson, Å., and Lang-
all, O.: Soil o ganic ca bon in Swedish sp uce and pine
o es s—di e ences in s ock le els and egional pa e ns, Sil a
Fenn., 44, 5–21, 2010.
Swedish S a is ical Yea book o Fo es y: O icial S a is ics o Swe-
den, 370 pp., Skogss y elsen, 2014.
S ensson, M., Jansson, P., and Kleja, D. B.: Modelling soil C se-
ques a ion in sp uce o es ecosys ems along a Swedish ansec
based on cu en condi ions, Biogeochemis y, 89, 95–119, 2008.
The neau, T. M. and A kinson, E. J.: An in oduc ion o ecu si e
pa i ioning using he RPART ou ines, 1997.
Th oop, H. L., Holland, E. A., Pa on, W. J., Ojima, D. S., and
Keough, C. A.: E ec s o ni ogen deposi ion and insec he -
bi o y on pa e ns o ecosys em le el ca bon and ni ogen dy-
namics: esul s om he CENTURY model, Glob. Change Biol.,
10, 1092–1105, 2004.
Todd-B own, K. E. O., Rande son, J. T., Hopkins, F., A o a, V., Ha-
jima, T., Jones, C., She liako a, E., Tjipu a, J., Volodin, E., Wu,
T., Zhang, Q., and Allison, S. D.: Changes in soil o ganic ca bon
s o age p edic ed by Ea h sys em models du ing he 21s cen-
u y, Biogeosciences, 11, 2341–2356, doi:10.5194/bg-11-2341-
2014, 2014.
Todd-B own, K. E. O., Rande son, J. T., Pos , W. M., Ho man, F.
M., Ta nocai, C., Schuu , E. A. G., and Allison, S. D.: Causes
o a ia ion in soil ca bon simula ions om CMIP5 Ea h sys em
models and compa ison wi h obse a ions, Biogeosciences, 10,
1717–1736, doi:10.5194/bg-10-1717-2013, 2013.
To n, M. S., T umbo e, S. E., Chadwick, O. A., Vi ousek, P. M., and
Hend icks, D. M.: Mine al con ol o soil o ganic ca bon s o age
and u no e , Na u e, 389, 170–173, 1997.
Tuomi, M., Rasinmäki, J., Repo, A., Vanhala, P., and Liski, J.: Soil
ca bon model Yasso07 g aphical use in e ace, En i on. Modell.
So w., 26, 1358–1362, 2011.
Tuomi, M., Thum, T., Jä inen, H., F onzek, S., Be g, B., Ha mon,
M., T o ymow, J. A., Se an o, S., and Liski, J.: Lea li e de-
composi ion – Es ima es o global a iabili y based on Yasso07
model, Ecol. Model., 220, 3362–3371, 2009.
Vi o, P.: In es iga ions on o es li e , Val ioneu os on Ki jap,
1955.
Wiesmeie , M., Hübne , R., Spö lein, P., Geuß, U., Hangen, E.,
Reischl, A., Schilling, B., on Lü zow, M., and Kögel-Knabne ,
I.: Ca bon seques a ion po en ial o soils in sou heas Ge many
de i ed om s able soil o ganic ca bon sa u a ion, Glob. Change
Biol., 20, 653–665, 2014.
Xia, M., Talhelm, A. F. and P egi ze , K. S.: Fine oo s a e he
dominan sou ce o ecalci an plan li e in suga maple-
domina ed no he n ha dwood o es s, New Phy ol., 208, 715–
726, doi:10.1111/nph.13494, 2015.
Yu o a, A. Y., Volodin, E. M., Ag en, G. I., Che o , O. G., and
Koma o , A. S.: E ec s o a ia ions in simula ed changes in
soil ca bon con en s and dynamics on u u e clima e p ojec ions,
Glob. Change Biol., 16, 823–835, 2010.
Venables, W. N. and Ripley, B. D.: Mode n applied s a is ics wi h
S-PLUS, Sp inge Science & Business Media, 2013.
Zandonadi, D. B., San os, M. P., Busa o, J. G., Pe es, L. E. P. ,and
Façanha, A. R.: Plan physiology as a ec ed by humi ied o ganic
ma e , Theo e ical and Expe imen al Plan Physiology, 25, 13–
25, 2013.
www.biogeosciences.ne /13/4439/2016/ Biogeosciences, 13, 4439–4459, 2016