ISOTOPE FRACTIONATION FACTORS
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ISOTOPE FRACTIONATION FACTORS ASSOCIATED WITH SOIL DENITRIFICATION. Dominika Lewicka-Szczebak 1 ,2 , Reinhard Well 2 , Laura Cardenas 3 , Peter Matthews 4 , Roland Bol 3 , Lena Rohe 1 1 Thünen-Institut, Germany, 2 Uni versity of Wroclaw, Poland

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ISOTOPE FRACTIONATION FACTORS

ASSOCIATED WITH SOIL DENITRIFICATION

  • Dominika Lewicka-Szczebak1,2 , Reinhard Well2,

  • Laura Cardenas3, Peter Matthews4, Roland Bol3,

  • Lena Rohe1

  • 1 Thünen-Institut, Germany, 2University of Wroclaw, Poland

  • 3 Rothamsted Research,UK, 4University of Plymouth, UK,

  • 5 Agrosphere Institute, Germany


Introduction ISOTOPE FRACTIONATION FACTORS

DENITRIFICATION PROCESSES

N2O production

N2O reduction

β

α- position

N2O reduction

SP= α-β

N

N

O

N

N

N2

preferredconsumption of bondswith

14Nand16O

ε

N2O

N

O

N2O production

N

N

O

ε

NO

ε

differentiationwithinthemolecule

O

O

N

O

ε

H

H

NO2-

exchange

of O-isotopes

withsoilwater

ε

changeinSP

(SitePreference)

NO3-

N

N

O

β

α- position

O

ε

O

H

H

N

O

O

sum of ε → NIE – Net IsotopeEffects → ƞ

of 3 independent factors:

δ15N, δ18O, SP

N

N

N

N

N

enrichment in 15N

e.g. ƞ 15N: -45 - -13‰

O

O

O

enrichment in 18O


Introduction OBJECTIVES OF MODELING APROACH

Determination of Net IsotopeEffects of productionand reduction

Comparison of NIEs for differentreaction dynamics and different experimental conditions

Development of a method to calculate reduction contribution based on isotopomers data


Introduction RAYLEIGH EQUATIONS

δS- isotopicsignature of substrateinparticular point of thereaction

δ S0 - isotopicsignature of substrateprior to initiation of thereaction

f - remainingunreactedfraction

ƞP-S- Net IsotopeEffect (NIE) betweenproduct and substrate

(Mariotti et al., 1981)

δ15N

N2O production

δS

NO32-

δP

η

N2O

δS0=0‰

η

remaining nitrate


Introduction RAYLEIGH EQUATIONS

δS- isotopicsignature of substrateinparticular point of thereaction

δ S0 - isotopicsignature of substrateprior to initiation of thereaction

f - remainingunreactedfraction

ƞP-S- Net IsotopeEffect (NIE) betweenproduct and substrate

(Mariotti et al., 1981)

δ15N

N2O production

+ reduction

δS

NO32-

δP

η

N2O

δS0=0‰

η

fred=0.8

fred=0.5

δS0

fred=0.2

remaining nitrate


Methods EXPERIMENTS DESIGN 1

known reduction

only N2O production

8 variants, 1 water saturation:75 WFPS

C2H2 addition

reduction inhibition

no C2H2

reduction occurs

gas samples

each 2/4/12h

  • GC-analyses N2O

  • isotopomers analysis (15N, 18O, SP in N2O)

  • 15N (N2), 15N (N2O) analysis

soil samples

beginning / end

  • NO3- content

  • δ15N, δ18O of NO3-


Methods / Results MODELING STRATEGY 1

only N2O production

+ known N2O reduction

INPUTS

INPUTS

N2O emission

NO3- consumption

δ15N, δ18O of NO3-

δ15N, δ18O, SP of N2O

f

unconsumed NO3-

N2O emission

NO3- consumption

δ15N, δ18O of NO3-

ƞP-S of N2O production

δ15N, δ18O, SP of N2O

15N (N2), 15N (N2O)

δS0

N2O before reduction

δS, δS0

δS

f

unreduced fraction

OUTPUTS

ƞP-Sof N2Oproduction

OUTPUTS

ƞP-Sof N2Oreduction

fast rate reaction


Methods EXPERIMENTS DESIGN 2

on-line GC-analyses

1.5h time step

known reduction

amendment

addition

samples for isotopomers analysis

once a day

‘DENIS’ incubation system

3 water saturations: 100 WFPS, 94 WFPS, 85 WFPS


Methods / Results MODELING STRATEGY 2

known N2O reduction

INPUTS

found by itinerations to reachthebest fit betweenmodeled and measuredvalues

(Rock et al., 2011)

OUTPUTS

(Well & Flessa, 2009)

pool2 – high reductionratio

produced SP range:

from -10‰ (bacteria) to 36‰ (fungi)

minimalvalue of δ18O

ca. 10 ‰

(Ostrom & Ostrom, 2011)

(Snider et al., 2011)


Methods / Results IMPROVED MODELING STRATEGY 2

INPUTS

OUTPUTS

OUTPUTS

INPUTS

pool2 – high reductionratio

I wyniki – że zależy od tempa procesu, mniejsze/większe – różne poole


ResultsFIT OF MEASURED AND MODELED DATA

SAT/sat

δ15N

UNSAT/sat

HALFSAT/sat


DiscussionCONTROLLING FACTORS

15N NIE of production

increasing reactions rates –

– smaller fractionation factors

increasing production rate

smaller difference between product and substrate

increasing soil moisture–

– smaller fractionation factors

ε - FRACTIONATION FACTORS

K - PROCESS RATES

increasing

water content

enzymatic

reaction

diffusion into cell

enzyme

activity

diffusion

diffusion

out of cell

100% WFPS

94% WFPS

85% WFPS

75% WFPS

(Farquar et al., 1982;

Ostrom & Ostrom, 2011; Well et al., acc.)


DiscussionCONTROLLING FACTORS

15N NIE of reduction

increasing substrate availability –

– higher fractionation factors

increasing reduction ratio

higher difference between product and substrate

decreasing soil moisture–

– higher fractionation factors

ε - FRACTIONATION FACTORS

K - PROCESS RATES

enzymatic

reaction

diffusion into cell

enzyme

activity

diffusion

diffusion

out of cell

unreduced fraction

increasing substrate availability

(Jinuntuya-Nortman et al., 2008, Ostrom & Ostrom, 2011)


DiscussionCONTROLLING FACTORS

produced 18O

increasingreactionsrates–

–higherδvalues

– lowerequilibriumwithsoilwater ?

100% WFPS

94% WFPS

85% WFPS

75% WFPS


Conclusions

  • Wide range of Net Isotope Effects associated with denitrification N2O production and reductionƞ15N: -43 - -18‰ ƞ15N: -9 - -1‰δ18O: 10 - 40‰ ƞ18O: -20 - -4‰ ƞSP: -10 - 1‰ ƞSP: -12 - -2‰

  • The magnitude of isotope effects is controlled by several factorshigher NIEs when lower reactions rates, higher substrate availability, more efficient substrate transportation (e.g. lower soil moisture)

  • Modelling aproach provides promising results for future development of a method to calculate reduction contribution based on isotopomers data

-45 - -13‰

-9 - -5‰

11 - 24‰

-20 - -13‰

-10 - 10‰

-8 - -3‰

*

*

*previous literature data (Well & Flessa, 2009; Ostrom & Ostrom, 2011)


N

N

N

N

O

N

N

N

N

O

N

N

N

N

O

N

N

N

N

O

N

N

N

N

O

N

N

N

N

O

N

N

N

N

O

N

N

N

N

O

N

N

N

N

O

N

N

N

N

O

N

N

N

N

O

N

N

N

N

O

THANK YOU FOR YOUR ATTENTION

  • This research was funded by the UK Biotechnology and Biological Sciences Research Council (BBSRC) with competitive grants BB/E001580/1 and BB/E001793/1 and by Deutsche Forschungsgemeinschaft (DFG) WE-1904-4.

  • The first authoris suppored by the Foundation for Polish Science.

  • DominikaLewicka-Szczebak


MethodsMODEL CONSTRUCTION

amendment

pool1 emission terminated

POOL1 – fast production,

low reduction

POOL2 – slow production,

high reduction

(Bergstermann et al., 2011)


ResultsFIT OF MEASURED AND MODELED DATA

SAT/sat

SP

UNSAT/sat

HALFSAT/sat


ResultsFIT OF MEASURED AND MODELED DATA

SAT/sat

δ18O

HALFSAT/sat

UNSAT/sat


N2-free

atmosphere

N

N

N

N

O

O

H

H

O

NO3-

N

O

O


N

N

N

N

O

N

N

O

C

glucose

15NO3-

O

N

O

O

O

N

C

glucose

O

O

NO3-

O

15NO3-

N

O

O

O

N

O

O

NO3-


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