The dirt on nitrogen, soil, and carbon—a step toward solving the enigma of soil N balance

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    Dr. J. K. Ladha

    IRRI Rice SeminarSeries

    Current position: Principal Soil Scientist, IRRI

    Editorial BoardSits in the editorial board of several international journals. Currently he is the

    regional editor ofBiology and Fertility of Soils.

    Education and training PhD from Banaras University, India (1976)Post Doctoral Fellow, University of Dundee (1977-78)Post Doctoral Fellow, IRRI (1980-82)

    Work experience Twenty eight years experience in international agriculture researchin agronomy/cropping systems, soil management, andsystem sustainability.

    Actively involved in research, training/teaching, project development, andteam leadership.

    Co-author of more than 179 research articles in international refereed journals,and editor of 13 books.

    Presented 81 invited papers in 31 countries.Supervised 30 M.S. and Ph.D. students and 40 Visiting Scientists from 12

    countries.

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    Dr. J. K. Ladha

    Research highlights International Agronomy Service Award (2011)

    International Soil Science Award (2010)

    International Plant Nutrition Institute Science Award (2009)

    Frosty Hill Fellow of the Cornell University (2008),

    CGIAR King Baudouin Team Award (2004)

    CGIAR Chairmans Excellence Science Team Award (2002)

    Young Scientist Award by the Indian National Academy of Sciences (1976)

    Fellow

    American Association for the Advancement of Science (2008)

    American Society of Agronomy (2004)

    Soil Science Society of America (2002)

    Indian Academy of Agriculture Science (1999).

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    Very Best Wishesfor a Happy 2012

    Foggy and

    Cold New

    Delhi

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    Synthetic nitrogen is good for thefather and bad for the sons- Dutch

    saying

    J.K. [email protected]

    The Dirt on Nitrogen, Soil andCarbon - A Step Toward Solving

    the Enigma of Soil N Balance

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    Synthetic N The Dirt

    Destroys soil carbon

    Undermines soil health

    Creates a kind of treadmill effect

    Bleeds the soil

    Not an ecological advantage but agravest liability

    Fertilized to death

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    OutlineKey Topics for TodaysDiscussion

    1. Role of Synthetic Nitrogen- Food production and Environment

    - SOM

    Equilibrium Concept

    Methods to Calculate Changes in SOC and SON

    Does the long-term use of synthetic fertilizer N

    lead to decline in SOM? Summary and Conclusion

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    Global, Long-Term (1961-2010),

    3 Major Cereals

    3 Land Use 3 Climate

    7

    Role of Synthetic N - Outline

    2. Construct Global N Balance byIntegrating 50 Years of NResearch Outputs

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    8

    0

    500

    1000

    1500

    2000

    2500

    1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

    Reducing hunger

    Improving nutrition

    Sparing naturalecosystem from

    conversion toagriculture

    R,W,MProduction(mt) Increased by 3 times in 40 years

    Source: (FAO, 2010)

    Global Rice, Wheat and MaizeProduction

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    -20

    -10

    0

    10

    20

    30

    40

    50

    60

    1960

    1965

    1970

    1975

    1980

    1985

    1990

    1995

    2000

    2005

    2010

    9

    Global N Consumption by Rice,Wheat, Maize

    Year

    Consumption

    (mt)

    Increased by 9 times in 40 years

    Source: unpublished

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    Region/ RENT

    a

    Crop Mean

    Africa

    Australia

    Europe

    America

    Asia

    Average

    Maize

    RiceWheat

    Average

    aRENT=recovery efficiency of fertilizer N based on total plant N (kg N

    taken kg

    -1

    N applied)

    Descriptive Statistics of N Recovery Efficiencyfor Cereals in Various Regions

    0.63

    0.46

    0.68

    0.52

    0.50

    0.55

    0.65

    0.460.57

    0.55

    Ladha et al, 2005

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    46 65% REN in first crop

    5.7 7.1% REN in five succeeding crops

    Summary

    20 40% REN in Rainfeds

    30 50% REN in Irrigated

    200 studies (with 500 800 datapoints) conducted across the globein a wide diversity of ecologies

    Source: Ladha et al 2005 Ad Agro

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    Humanactivities

    130-150(60%)?

    Accumulation of reactive N in

    AtmosphereSoilsGroundwaterLand vegetation

    OceansMarine sediments

    N2

    Unreactive Pool4 x 109 Tg

    Biotic90-130

    Biotic90-130

    Preindustrial Industrial

    Reactive Pool of N(N2 Fixation Tg/year)

    EnvironmentalChallenge

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    2050

    Global population 50% >

    Global grain demand 100% >

    Global fertilizer demand 50-70% >

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    Soil Organic Matter

    SOM is recognized as a major factor controlling thecapacity of soil resources to deliver agricultural andenvironmental servicesandsustain human societiesfromlocal (fertility maintenance) to global (mitigation ofatmospheric carbon emissions) scales.

    Soilorganic

    matteras a

    pool of

    nutrients

    component oforgano-claycomplexes

    pool ofcarbon

    pool of

    energy

    soil chemical

    status

    soil waterstatus

    soil physicalstatus

    soil biological

    status

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    SOM Equilibrium Gain and Loss Balance

    Time (Years)

    SOC orSON

    Loss

    Gain

    Originalequilibrium

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    Gain (input) and Loss (output)Pathways of SOC and SON

    Photosynthesis (C)

    Biological NFixation

    Synthetic N

    Organics (C & N)

    Decomposition/

    Mineralization/Respiration

    CO2, CH4

    Denitrification/Leaching/

    Volatilization

    N2, N2O, NO, NO3, NH3

    Gain Loss

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    Major Factors Affecting SOMEquilibrium

    Cropping pattern/intensity

    Tillage

    Climate

    Organic fertilization Synthetic N fertilization

    Soil water content

    Organic fertilization Synthetic N fertilization

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    Synthetic Fertilizer N

    Question:Does the long-term use of synthetic fertilizer Nlead to decline in SOM?

    View # 1

    Augmenting SOM by promoting plant growththereby increasing amount of litter to soil.

    View # 2Enhancing loss of SOM by accelerating its rateof oxidation or decay.

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    Knowledge Gaps

    Piece mill effort

    Lack of consistency in data analysis

    Inadequate statistics

    No global scenario

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    Ecological processes are oftenslow and it is only through long-

    term experiments they can befirstly detected and secondly

    understood.

    T.R.E. Southwood, University ofOxford (1994)

    Long-Term Experiment: A Treasure

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    Worldwide Coverage of 114 LTEs

    Tropical (20)

    Sub-tropical (42)

    Temperate (52)

    3000 0 3000

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    Data Set

    All experiments included a cereal-based croprotation

    At least one rate of synthetic fertilizer N (oftenwith P and K) plus a corresponding treatmentwithout the application of N (i.e.,N+P+Kversus +N+P+K) within a study

    Use similar soil depth at t=0 and t=1

    114 LTEs from 100 sites globally

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    Data Set : Sub - Groups

    Climate (CL)

    Land Use (LU)

    Fertilizer Type (FT)

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    Data Set

    Duration and number of C and N datapoints

    Duration (year) SOC SON

    10 172 103

    11-30 543 311

    31-50 85 84

    >51 117 82Total 917 580

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    Statistical Analysis

    Standardization allowed the elimination of

    differences due to sampling of soils atdifferent depths and the associated bulkdensities among the studies.

    All the data (primary and derived) were

    analyzed using the SAS mixed modelprocedure (SAS Institute, 2001) and meta-analysis Meta-Win software (Rosenberg etal., 2000).

    All the gravimetric and volumetric datawere converted to a percentage changeover time.

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    t = 0

    Time

    SO

    CorSONContent

    t = 1

    mgNkg-1

    1000

    800

    600- F (Nct1)

    + F (Nft1)

    No change

    Methods to Calculate Changes in SOC andSON

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    Methods to Calculate Changes in SOC andSON

    Nft1 - Nft0

    Nft0X 100 = - 20%

    1 A)=

    t = 0 Time

    SOCorSONC

    ontent

    t = 1

    + F

    + F (Nft1)

    - 20 %

    h d l l h i d

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    Methods to Calculate Changes in SOC andSON

    t = 0 Time

    SOC

    orSONContent

    t = 1

    2) = ((Nft1 / Nct1) -1)) x 100 = + 33

    (Nft1)

    + F

    (Nct1)- F

    + 33%

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    3) = ((Nft1/ Nft0) - (Nct1 / Nct0) x 100 = + 20 %

    Methods to Calculate Changes in SOC andSON

    t = 0 Time

    SOC

    orSONContent

    t = 1

    (Nct1)

    Nct0 (Nft1)

    Nft0

    + 20 %

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    Estimation of Responses of FertilizerN Input to SOC and SON

    Three ways:

    (1) Time Response (TR)

    (2) N-Fertilizer Response (NR)

    (3) Time by N-fertilizer Response

    (TNR)

    (1) Time Response (TR)

    % difference in SOC and SON contentfollowing the application fertilizer betweentime (t) = 0 and t = 1

    TR = [(Nft1 Nft0) / Nft0] x 100

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    Estimation of Responses of FertilizerN Input to SOC and SON

    (2) N-Fertilizer Response (NR)

    % difference of the final values of soil N and Cbetween fertilized and zero-N treatments

    NR = (Nft1 -fertilized / Nft1-Control -1) x 100

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    Estimation of Responses of FertilizerN Input to SOC and SON

    (3) Time by N-fertilizer Response (TNR)

    % difference between the change in SOC and

    SON in N-fertilized treatments compared withthe change in the zero N

    TNR = [(Nft1 -fertilized / Nft0 -fertilized) - (Nft1-

    control / Nft0-control)] x 100

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    Estimation of Responses of FertilizerN Input to SOC and SON

    TR TNR

    Assesses the impact

    of whole system(tillage, residuemanagement,erosion, fertilizermanagement etc)

    Specifically

    assesses the impactof an N-fertilizeramendment

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    Final (t = 1) Concentration of SOC and SON (g kg-1) -Primary Data from 114 LTEs (Mixed Model Analysis)

    Fertilizer (FT) SOC SON

    Control (zero N) 13.7b 1.3bSynthetic N 12.9b 1.3b

    Organic N 17.7a 2.0a

    Integrated (organic +synthetic N)

    8.8c 1.1b Land Use (LU) SOC SON

    Flooded 18.0a 2.2aFlooded dryland 7.8c 1.2b

    Dryland 14.0b 1.3b

    Climate (CL) SOC SON

    Tropical 8.2c 1.0b

    Sub-tropical 13.8b 1.6a

    Temperate 16.9a 1.4a

    Organic N 17.7a 2.0a

    Temperate 16.9a 1.4a

    Flooded 18.0a 2.2a

    TR d TNR f SOC d SON i Mi d M d l

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    TR and TNR of SOC and SON using Mixed Modeland Meta Analysis

    Mixed model

    Mixed model

    Meta-analysis

    Meta-analysis

    TNR

    - std error

    TR TNR

    - 95% confidence interval

    - std error- 95% confidenceinterval

    TR

    %

    ChangeinSOC

    -20

    -10

    0

    10

    20

    30

    40

    50

    60

    Zero-N Synthetic-N Organic-N Organic+synthetic-N

    %

    ChangeinSOC

    -20

    -10

    0

    10

    20

    30

    40

    50

    60

    Zero-N Synthetic-N Organic-N Organic+synthetic-N

    %C

    hangein

    SON

    -20

    -10

    0

    10

    2030

    40

    50

    60

    Zero-N Synthetic-N Organic-N Organic+

    synthetic-N

    %C

    hangeinSON

    -20

    -10

    0

    10

    2030

    40

    50

    60

    Zero-N Synthetic-N Organic-N Organic+synthetic-N

    P t Ch i TNR f SOC ith L

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    Percent Change in TNR ofSOCwith Long-Term Synthetic N Application

    Flooded(95%CI)

    Flooded dryland(95%CI)

    Dryland (95%CI)

    TNR 7 (3-11) 17 (12-22) 7 (5-8)

    Tropical(95%CI)

    Humid sub-tropical

    (95%CI)

    Temperate(95%CI)

    TNR 16 (12-20) 11 (9-14) 3 (1-4)

    SOC (g kg

    -1

    ) 15.2 (13-18) 6.3 (6-9) 12.7 (12-13)

    SOC (g kg-1) 6.7 (6-7) 11.4 (10-12) 15.9 (15-17)6.7 (6-7)

    17 (12-22)

    16 (12-20)

    6.3 (6-9)

    Land Use

    Climate

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    Summary and Conclusion

    Overall, SOM content generally declined over

    time but synthetic-N led to slower decrease,and not a further additional decrease

    SOM decreased in a crop rotation fluctuatingbetween flooding and drying than in

    continuous dryland or flooded systems Flooded rice soils accumulates high SOC and

    SON because of lower residue decompositionand higher BNF

    TNR approach is accurate to determine theimpact of long-term application of synthetic Non SOM

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    Summary and Conclusion

    Undoubtedly, the primary function ofsynthetic N in producing food forgrowing population is vital but its role

    on long-term consequences on thesystem sustainability is equallyimportant as SOM plays multiplefunctions in maintaining soil quality and

    ecosystem services

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    Key PublicationsLadha, Dawe, Ventura, Singh, Watanabe, SSAJ 2000Ladha, Pathak, Krupnik, Six, van Kessel, Ad Agro 2005Ladha, Reddy, Padre and van Kessel, JEQ 2011Ladha et al, unpublished

    Acknowledgement