Soils and climate change: potential impacts on carbon stocks and … · 2016. 7. 11. · Soils and...

Soils and climate change potential impacts on carbonstocks and greenhouse gas emissions and future researchfor Australian agriculture

J A BaldockAD I WheelerC N McKenzieB and A McBratenyC

ACSIRO Land and WaterSustainable Agriculture Flagship PMB 2 Glen Osmond SA 5064 AustraliaBCSIRO Land and Water Canberra ACT 2601 AustraliaCUniversity of Sydney Faculty of Agriculture Food and Natural Resources Sydney NSW 2006 AustraliaDCorresponding author Email jeffbaldockcsiroau

Abstract Organic carbon and nitrogen found in soils are subject to a range of biological processes capable of generatingor consuming greenhouse gases (CO2 N2O and CH4) In response to the strong impact that agricultural management canhave on the amount of organic carbon and nitrogen stored in soil and their rates of biological cycling soils have the potentialto reduce or enhance concentrations of greenhouse gases in the atmosphere Concern also exists over the potentialpositive feedback that a changing climate may have on rates of greenhouse gas emission from soil Climate projectionsfor most of the agricultural regions of Australia suggest a warmer and drier future with greater extremes relative to currentclimate Since emissions of greenhouse gases from soil derive from biological processes that are sensitive to soiltemperature and water content climate change may impact significantly on future emissions In this paper the potentialeffects of climate change and options for adaptation and mitigations will be considered followed by an assessment offuture research requirements The paper concludes by suggesting that the diversity of climate soil types and agriculturalpractices in place across Australia will make it difficult to define generic scenarios for greenhouse gas emissionsDevelopment of a robust modelling capability will be required to construct regional and national emission assessmentsand to define the potential outcomes of on-farm management decisions and policy decisions This model development willrequire comprehensivefield datasets to calibrate the models and validate model outputs Additionally improved spatial layersof model input variables collected on a regular basis will be required to optimise accounting at regional to national scales

Received 12 December 2011 accepted 20 March 2012 publishedonline 28 May 2012

Introduction

Soils contain large stores of organic carbon and nitrogen~1500ndash2400 Pg C (Eswaran et al 1995 Houghton 2005Jobbaacutegy and Jackson 2000 Lal 2004 Powlson 2005) and 190Pg N (Mackenzie 1998) depending on the soil depth overwhich the stores have been calculated These stores arecontinuously exposed to decomposition and a range ofadditional biologically mediated transformations that generateor consume all three major greenhouse gases (CO2 N2O andCH4) (Fig 1) Globally soils and their management thereforehave the potential to either enhance or reduce atmosphericconcentrations of greenhouse gases and the magnitude of anyassociated climate change Using respective estimates of 1500and 720 Pg for carbon contained in soil and the atmosphereand an atmospheric concentration of 390 ppm for CO2 (MaunaLoa Observatory December 2010) a 1 change in the amountof carbon stored in soils would equate approximately to an8 ppm change in atmospheric CO2 concentration providedall other components of the carbon cycle remained constantHowever given the potential mediating responses provided byphotosynthesis and oceanic exchange it is likely that the netchange brought about by a 1 change in carbon stored in soil

would be somewhat less than 8 ppm When this calculation iscoupled with the observation that initiating agriculturalproduction results in a 20ndash70 reduction in the amount ofcarbon stored in soils (Luo et al 2010b Sanderman et al2010) the way in which agricultural soils are managed has thepotential to either enhance or reduce atmospheric concentrationsof CO2 Additionally the impact of agricultural managementpractices on emissions of N2O and CH4 must be consideredgiven their high levels of radiative forcing relative to CO2

(310 and 21 times that of CO2 over a 100-year time framerespectively) Concern also exists over the potential positivefeedbacks that a changing climate may have on rates ofgreenhouse gas emission from soil in view of the strongimpact that climate can have on the biological processesleading to production and consumptionstorage of CO2 N2Oand CH4

This paper will examine the potential implications of climatechange on greenhouse gas emissions from Australian agriculturalsoils It will not examine soils under native ecosystems ormanaged native forests or plantations A short description ofthe projected changes in climate will be presented This will befollowed by an examination of the processes responsible for

Journal compilation CSIRO 2012 Open Access wwwpublishcsiroaujournalscp

CSIRO PUBLISHING

Crop amp Pasture Science 2012 63 269ndash283httpdxdoiorg101071CP11170

emission and consumptionstorage of each of the greenhousegases (CO2 N2O and CH4) in soil and how the predicted climatechanges are likely to impact Options for adapting to andmitigating climate change from a soils point of view will thenbe discussed followed by identification of knowledge gaps andfuture research priorities

Climate change predictions for Australia

Climate projections for most of the agricultural regions ofAustralia suggest a warmer and drier future with alterations to

the seasonality and greater extremes relative to 1980ndash1999average annual climatic conditions (Fig 2) Although thenorth-eastern portion of Australia and particularly central NewSouth Wales is predicted to have higher or unchanged rainfall insummer this is accompanied by projected increases in potentialevapotranspiration Such conditions are likely to result in anoverall pattern of drying with respect to the amount of wateravailable to grow crops and pastures The projected climaticchanges will undoubtedly affect the balance between emissionand storageconsumption of CO2 N2O and CH4 in Australiarsquos

(a)

(b)

Fig 1 Soil biological processes that influence (a) consumption of atmospheric greenhouse gases bysoil and (b) emissions of greenhouse gases from soil into the atmosphere

270 Crop amp Pasture Science J A Baldock et al

agricultural soils The direction and magnitude of changeswill be defined by the integrated effects across all processesinvolved in emission and consumption or storage of eachgreenhouse gas

Greenhouse gas emissions from soil and potentialimplications of climate change and agriculturalmanagement practices

Emissions of greenhouse gases from soil fluctuate bothtemporally and spatially due to variations in environmentalfactors and soil properties and quantification of multipleprocesses is often required to define net fluxes For examplenet CO2 emissions result from the balance between CO2 uptakethrough photosynthesis and CO2 release from respiration byplants animals and microbes Although measurements of netCO2 fluxes are possible they require sophisticated equipmentand data analysis and do not define the magnitude of individualcontributing processes An alternative is to quantify the changesin biological stocks of carbon including vegetation and soilacross space through time Given the diversity of vegetationtypes soil properties and climatic conditions existing acrossAustralia the stock change approach has been adopted tomeasure and predict changes in net CO2 emissions from

Australian soils For N2O and CH4 emissions from soil nostock change measurement is available thus measurement andprediction of fluxes provides the only approach to quantifyemissions of these gases

In this section processes influencing soil carbon stockchanges and net emissions of N2O and CH4 from agriculturalsoils will be identified potential impacts of climate change will bediscussed and options for mitigation of emissions will beconsidered Although each greenhouse gas will be examinedindividually dynamic links often exist with respect to emissionof these gases and the impact of any mitigation strategies on allthree gases must be considered For example if soil carbonstocks increase due to enhanced plant growth associated withadditional fertiliser nitrogen application the impact of fertilisernitrogen on net N2O and CH4 emissions must be considered in anywithin-farm-enterprise greenhouse gas account Additionallyit will be important to define and quantify any induceddeviations in off-farm emissions associated with managementchange to delineate the net benefit to atmospheric concentrationsof greenhouse gases In the example just considered (applicationof additional fertiliser nitrogen) any CO2 emissions associatedwith the production and transport of the additional fertilisernitrogen will need to be considered

Change in average annual temperature (degC)

2070(a)

50

Change in annual rainfall ()

(b)

40

(c)

Change in annual potential evapotranspiration ()16

2030 2050

03 06 10 15 20 25 30 40

ndash40 ndash20 ndash10 ndash5 ndash2 2 5 10 20

ndash4 ndash2 2 4 8 12

Fig 2 Projected changes in (a) mean annual temperature (b) annual rainfall and (c) annualpotential evapotranspiration for Australia relative to the 1980ndash1999 period using the 50thpercentile of projected changes under the medium future emissions profile (Source httpclimatechangeinaustraliacomau and CSIRO2007)

Soils and climate change potential impacts Crop amp Pasture Science 271

Soil organic carboncarbon dioxide

The amount of organic carbon contained in a soil is the directresult of the balance between carbon inputs and losses Organiccarbon is added to soil via deposition in and on the soil oforganic materials created by capturing CO2 through theprocess of photosynthesis (Fig 1a) Soil organic carbon (SOC)is returned to the atmosphere as CO2 via respiration that occursas soil organisms use organic materials as a source of energyand nutrients (Fig 1b) Any agricultural practices that alter ratesof carbon input to or loss from the soil will result in a changein the stock of SOC

A potential upper limit for carbon inputs to soil can be definedfor any given location by five factors

(1) amount of photosynthetically active radiation (PAR)available which is defined by global position and cloudcover

(2) fraction of PAR that can be absorbed by plants (typically afunction of leaf area and architecture)

(3) efficiency with which carbon is captured by photosynthesisper unit of PAR absorbed

(4) proportion of captured carbon lost to autotrophic respiration(5) proportion of captured carbon deposited on or in the soil

The summation of the first four factors provides an estimate ofthe potential net primary productivity (NPP) of an agriculturalsystem Other factors such as low availabilities of water andnutrients changes in temperature or low soil pH may constrainpotential NPP to lower values by limiting the efficiency of carboncapture (factors 2 and 3) or enhancing respiratory losses (factor 4)Agricultural breeding programs have been designed to reducethe magnitude of such limitations through genetic manipulationto allow crops and pastures to maximise NPP at any givenlocation Factor 5 also needs to be considered sinceagricultural systems are designed typically to maximise theallocation of captured carbon to products harvested andtransported off-farm As a result enhanced productivity asdefined by estimates of agricultural yield does not necessarilytranslate to increased inputs of carbon to soils and in fact may beoccurring at the expense of carbon inputs to soils if harvest indicesare increasing (for a summary of harvest indices for Australiancrops see Unkovich et al 2010)

In most Australian agricultural systems the availability ofwater or nutrients represents a major limitation to achievingpotential NPP Therefore efforts to enhance inputs of carbonto soil shouldfirst focus on identifying soils where carbon captureper unit of available resource (water and nutrients) is notmaximised under the agricultural systems in use Then anassessment should be made as to whether alterations to currentmanagement practices can enhance resource use efficiency Forexample if water-use efficiency is being held back due to a lackof fertility or low pH application of appropriate levels offertiliser or agricultural lime may enhance productivity andinputs of carbon to the soil However if low water-useefficiency is resulting from the presence of high subsoilconcentrations of salt and boron it may not be possible toenhance productivity by simply altering management withinthe operating production system Under such conditionssignificant changes to the production system may be required

to achieve increased inputs of carbon to the soil (eg reducedextent or frequency of cropping reduced grazing intensity andintroduction of plant species with a greater tolerance to adversesoil conditions)

Plant residues enter the soil system through deposition onthe soil surface (shoot residues) or within the soil matrix (rootresidues exudates and root-associated mycorrhizal fungi) Themajority of residue carbon will be decomposed and respiredback to the atmosphere as CO2 with the balance resistingdecomposition as a result of its chemical recalcitranceassimilation into decomposer tissues or interactions with soilminerals However even the more biologically stable forms ofSOC are gradually decomposed and their carbon is returned tothe atmosphere Thus the retention of a small fraction ofresidue carbon as stabilised SOC is essential to replace theSOC continuously being lost at low rates by decomposition

The diversity of biological transformations and interactionswith soil minerals that occur as residue carbon enters soilmeans that SOC has a diverse composition and a range ofsusceptibilities to decomposition as demonstrated by D14Cmeasurements (eg Ladd et al 1981 Anderson and Paul1984 Swanston et al 2005) To gain further insight into SOCcomposition and cycling various methodologies based onvariations in chemical and physical properties have beendeveloped to allocate SOC to a series of lsquobiologicallysignificantrsquo fractions (Blair et al 1995 Golchin et al 1997Paul et al 2001 Six et al 2002 Skjemstad et al 2004)Skjemstad et al (2004) used a combination of physical andchemical properties to allocate SOC to the following threefractions

(1) particulate organic carbon (POC) organic carbon associatedwith particles gt50mm (excluding charcoal carbon)

(2) humus organic carbon (HUM) organic carbon associatedwith particles lt50mm (excluding charcoal carbon)

(3) resistant organic carbon (ROC) organic carbon found in thelt2 mm soil and having a poly-aromatic chemical structureconsistent with the structure of charcoal

Skjemstadet al (2004) went on to demonstrate that the RothC soilcarbon model (Jenkinson et al 1987) could be re-parameterisedusing these measureable fractions by substituting the RPMHUM and IOM model pools with the measured POC HUMand ROC fractions respectively and altering the decompositionrate constant assigned to the POC fraction Based on thesefindings the National Carbon Accounting System has adoptedthe use of a version of RothC modified to simulate the dynamicsof these measureable fractions This approach allows the modelto be initialised using measured values for the amounts of SOCand fractions rather than estimated values as typically used inother SOC models based on conceptual pools of carbon

Although estimates of SOC composition are not essential toallow carbon accounting an understanding of SOC compositionwill provide an assessment of the vulnerability of SOC stocks tosubsequent changes in management practice Vulnerability willincrease as the proportion of energy-rich and decomposable POCincreases and will decrease as the proportions of the more stableHUM and ROC fractions of SOC increase Accurate predictionof the impact of climate change on SOC stocks will require an


understanding of SOC composition and climatic responses to aseries of factors that influence the biological stability of differentforms of SOC and thus the magnitude of SOC loss (see Eqn 1below) (modified from Baldock 2007) Factors defining thebiological stability of SOC can be divided into two typesthose responsible for defining whether or not a particular formof SOC can be decomposed (biological capability) and thosedefining the rate of decomposition (biological capacity) Ofprimary importance to biological capability are

(1) chemical nature of SOC which defines the inherentbiochemical recalcitrance of the carbon-containingcompounds present

(2) genetic potential of decomposer organisms to create theenzymes required to degrade both plant residues and thevarious forms of SOC present

(3) mechanisms of physical protection that can alter molecularconformation through adsorption reactions isolate organicmolecules from enzyme attack through the creation of aphysical barrier or encapsulate pieces of plant residuecreating an environment less conducive to decomposition

Of importance to biological capacity are

(1) environmental properties that govern rates of biochemicalreactions including temperature and the availability ofoxygen water and nutrients

(2) duration of exposure to conditions conducive todecomposition

By crossing the two factors governing biological capacity(environmental properties duration of exposure) an index ofmicrobially active days can be constructed and used to provide anindication of the potential for SOC to decompose provided thecapability exists

Biologicalstabilityof SOC

frac14 f

Biologicalcapability

Biologicalcapacity

0BB

1CCA

frac14 f

Biochemical Genetic Mechanismsrecalcitrance potential of physical

protection

Environmental properties Durationinfluencing rates of of

biochemical reactions exposure

0BBBBBB

1CCCCCCA

eth1THORN

Most of the factors described in Eqn 1 particularlymechanisms of physical protection environmental propertiesand duration of exposure show strong spatial variability acrossthe Australian agricultural regions due to differences in soil claycontent and mineralogy and climate When such variability iscombined with spatial differences in plant productivity and theamount of residue deposited in and on soils it becomes apparentthat the potential for soils to capture and retain carbon willalso vary spatially Such variability is exemplified by the largedifferences noted in depth profiles of soil carbon for severalindicative Australian soils (Fig3) The practical implication ofthese observations is that the magnitude of SOC change inducedby agricultural management practices will vary across Australiarsquosagricultural regions Particular practices may work well in some

areas but not others For example where carbon storage resultsfrom a strong dependence on mechanisms of physical protectionit is unlikely that the same magnitudes of SOC change will benoted on a sandy Calcarosol a medium-textured Chromosol or ahigh clay content Vertosol

Projected increases in temperature and reductions in theavailability of water will undoubtedly influence stocks of SOCin Australia because of the controls that these parameters exert onrates of carbon capture and addition to soil as well as on rates ofdecomposition However the direction and magnitude of changesand the potential for feedbacks that may accentuate climatechange are still under debate Progressing the understanding ofclimate change effects on SOC requires an assessment of thepotential impacts that climate change will have on relativemagnitude of carbon inputs and losses from soil

Under dryland agriculture where water availability is thefirst dictator of potential carbon capture by plants a drier andwarmer climate is likely to reduce potential plant growth andthe inputs of carbon to soil Identification and implementationof agricultural management strategies that allow plants to accessand transpire a greater fraction of the rainfall received anddevelopment of new genetic material (species and varieties)with greater water-use efficiency (carbon capture per mm ofavailable water) will be required to ensure that inputs ofcarbon to soils are maintained Enhanced carbon capture byplants due to lsquoCO2 fertilisationrsquo associated with increasedatmospheric CO2 concentrations (Grace and Rayment 2000)may help to alleviate potential negative impacts of lower wateravailability on SOC levels Under irrigated agriculture wherewater requirements to maximise plant productivity can be metthe likely outcome of climate change would be enhancedproductivity unless temperatures increase to levels beyond thatat which plant growth is optimised Under both drylandconditions and irrigation the greenhouse gas costs associatedwith maintaining or enhancing productivity (eg petrol forirrigation pumps additional nitrogen fertiliser etc) will needto be quantified to define net benefits

Changes in climate will also affect the magnitude of SOCloss from agricultural systems It is widely accepted that dryingwill reduce rates of SOC decomposition however the effect of

0 1 0 1 2 0 1 2 3 0 2 4 6

Calcar

osol

Chrom

osol

Ferro

sol

Verto

sol

0

50

100

150

200

Soi

l dep

th (

cm)

Soil organic carbon content ( by weight)

Fig 3 Changes in soil carbon with depth for representative Australian soilprofiles (Modified from Spain et al 1983)


increasing temperature has been debated The majority ofevidence available suggests that increasing temperature willincrease rates of SOC decomposition (Powlson 2005)However by quantifying the turnover time of SOC atlocations exhibiting a 5308C range in annual temperatureGiardina and Ryan (2000) suggested that rates of SOCdecomposition were not sensitive to temperature In that workGiardina and Ryan (2000) expressed SOC as a single componentwith a single turnover time which was a significantoversimplification considering the diversity of differentmaterials contained in SOC and the range of locations fromwhich soils were collected Subsequent work completed usingthe same data (Knorr et al 2005) established that when SOCwas divided into several fractions having different rates ofdecay a positive sensitivity of SOC decomposition tovariations in temperature existed Knorr et al (2005) alsoshowed that the relative temperature sensitivity of SOCfractions increased as the stability of the SOC fraction againstbiological attack increased The implication of the analysis byKnorr et al (2005) is that an enhanced decomposition of SOCin a warming environment may have a positive feedback onatmospheric CO2 values An accurate manifestation of theinfluence of temperature alone on SOC decomposition is onlypossible if all other factors controlling accessibility of organiccarbon to decomposer enzymes remain non-limiting In a reviewDavidson and Janssens (2006) suggested that environmentalconstraints (eg availability of water or nutrients) may resultin low lsquoapparentrsquo temperature sensitivity of SOC decompositionby obscuring the intrinsic temperature sensitivity and that theenvironmental constraints themselves may also be sensitive totemperature Additional research is required to more accuratelydelineate the temperature response of the decomposition ofSOC and its component fractions

Many variations in land use and agricultural managementpractices exist across Australian agricultural regions Reviewsby Hutchinson et al (2007) Luo et al (2010b) and Sandermanet al (2010) have defined the magnitude of potential soil carbonchanges under a variety of management practices and regimesGoing forward options will undoubtedly be available to enhancethe input andor reduce the emission of carbon to most soils evenunder projected climate change scenarios The guiding principalwhen designing management regimes to maximise SOC stockswill be to maximise the capture of carbon given the resourcesavailable at any particular location The challenge will be todesign appropriate agricultural systems that meet thefinancialrequirements of the farm business (converting carbon capturedby photosynthesis into a product that can be sold) and enhancethe input and retention of organic carbon in soils

Innovations such as the introduction of tropical perennialspecies into previously annual pastures implementation ofrotational grazing and adoption of pasturendashcropping systemsare being reported to increase soil carbon values in someagricultural regions of Australia (Sanderman et al 2010)Further definition of the mechanisms and quantification ofrates of SOC change under these innovative systems arerequired Additionally the extent of soil carbon declineinduced by agricultural production prior to the introductionof alternative lsquoSOC friendlyrsquo management practices requiresconsideration Evidence is emerging to suggest that the

magnitude of measured SOC gains induced by the introductionof perennial pasture species into previously annual pasturesincreases as the extent of SOC decline under previousmanagement regimes increases (J Sanderman unpubl data)

The influence that increased SOC can have on a range ofsoil properties should also be considered Increases in SOC canbenefit a range of biological chemical and physical propertiesAmong the more important in terms of maintaining productivityin a changing climate is the enhancement that can occur to soilwater-holding capacity Availability of water will remain themajor factor limiting plant productivity across many ofAustraliarsquos agricultural regions under the predicted climatechange scenarios Enhancing the water-holding capacity of soilby increasing SOC may help maintain productivity as dryingoccurs

Nitrous oxide

Nitrous oxide is generated in soils as a byproduct of twonatural biological processes involved in transformations ofinorganic nitrogen nitrification (conversion of ammonium tonitrate) and denitrification (conversion of nitrate to N2O and N2

gases) (Fig 1a) Although microorganisms can reduce N2Oto N2 under anaerobic conditions rates of atmospheric N2Oconsumption by soil are suggested to be small (Freney et al1978)

Because nitrification and denitrification are biochemicalprocesses process rates will increase with increasingtemperature provided the appropriate form of inorganicnitrogen and other required materials (eg biologicallyavailable carbon for denitrification) are present and the soil issufficiently wet Chen et al (2010b) obtained near-exponentialincreases in N2O emission from soils as temperature increasedfrom 5 to 258C but also noted reduced rates of emission as thesoil dried from 60 to 40 water-filled pore space Dalal et al(2003) presented a generalised relationship showing thatrelative rates of N2O emission were negligible at water-filledpore space values lt40 were maximised between 60 and70 and were again negligible at values gt90 Increasingtemperature has also been shown to enhance the ratio of N2Onitrate from nitrification (Goodroad and Keeney 1984) andreduce N2ON2 ratios from denitrification (Keeney et al 1979Castaldi 2000) Under dryland agriculture the influence ofproposed climate changes will depend on the relativeresponses to temperature and drying It is suggested that forthe current warmer and wet tropical and subtropical regionsN2O emissions may increase while for the cooler and drierregions N2O emissions may decrease (all other factors beingconstant) However under irrigated systems where water contentlimitations are removed the higher temperatures associated withprojected climate change would enhance the emission of N2Ounless soil inorganic nitrogen levels are tightly controlled

The key to mitigating emissions of N2O from agricultural soilsis to minimise concentrations of inorganic nitrogen particularlygiven the non-linear increases in N2O emissions from soils inresponse to incremental fertiliser nitrogen additions (McSwineyand Robertson 2005) By limiting the amount of inorganic Navailable process rates of nitrification and denitrification andemissions of N2O will be reduced Options available for


reducing the concentration of inorganic nitrogen in soil and thusN2O emission include

(1) Better matching of fertiliser nitrogen applications to plantdemand as defined by growing season conditions Australiauses significant quantities of ammonium-based nitrogenfertilisers in agriculture Through the use of flexiblenitrogen fertiliser systems based on multiple smallapplications consistent with plant growth stage andgrowing season conditions a better matching betweenrates of nitrogen supply and plant demand can beachieved Adoption of such application strategies willreduce the potential for generating high inorganic nitrogenstatus and N2O emissions Under irrigated agriculture wherehigh rates of nitrogen fertiliser addition are common morefrequent irrigation or fertigation events that reduce theextent of soil saturation and inorganic nitrogenconcentrations will help mitigate N2O emissions Suchprocesses would be expected to have the added benefit ofenhancing nitrogen-use efficiency

(2) Increased reliance on biological nitrogenfixation to enhancesoil nitrogen status Building soil organic N status throughthe incorporation of legumes into pastures and croprotations can be used to enhance the availability ofnitrogen to subsequent crops (Chalk 1998 Peoples andBaldock 2001) Given that nitrogen mineralisation andplant growth are controlled by the same environmentalfactors the provision of plant-available nitrogen throughmineralisation of organic nitrogen is likely to be wellmatched temporally with plant demand However it isunlikely that provision of nitrogen through organicnitrogen mineralisation will optimise productivity Peakdemands for nitrogen by well-managed crops with nowater limitations will exceed the capacity of the soil tosupply nitrogen from mineralisation so additionalnitrogen is required to meet the shortfall (Angus 2001)Judicious use of nitrogen fertilisers will be required toensure that excess inorganic nitrogen levels do not resultand to optimise fertiliser nitrogen use efficiency andproductivity

(3) Alteration of animal diets to avoid an intake of excessnitrogen and excretion of high nitrogen content urine andfaeces Pastures often contain an excess of protein relative toanimal requirements (Whitehead 1995) Production ofpastures with a balanced legumenon-legume mixtureapplications of appropriate fertiliser nitrogen rates tomaintain optimal nitrogen status of non-legume pasturebiomass and supplementation of high nitrogen contentdiets with a low nitrogen content material (eg cropresidues) offer mechanisms by which the provision offood with appropriate nitrogen content to reduce thenitrogen content of urine and faeces can be achieved Suchstrategies can increase nitrogen-use efficiency (Kebreabet al2001) and thereby reduce urine nitrogen concentrations andsubsequent emissions of N2O (Mulligan et al 2004 Nielsenet al 2003)

(4) Application of inhibitors to reduce rates of formationand transformation of soil ammonium Urease activity andnitrification inhibitors are available commercially to alter

nitrogen transformations in soil Urease inhibitors slow thehydrolysis of urea in fertilisers or animal urine limitingthe accumulation of ammonium (Watson 2000) whereasnitrification inhibitors reduce the transformation ofammonium to nitrate (Luo et al 2010a) Reductions of upto 70 in N2O emissions have been noted due to theapplication of these inhibitors particularly through theapplication of nitrification inhibitors to urine-affectedpastures (Di and Cameron 2003 2006 Di et al 2007Smith et al 2008 Chen et al 2010b)

Methane

Methane can be produced by methanogens under anaerobic soilconditions and consumed through oxidation by methanotrophsunder aerobic soil conditions Fig 1 Significant CH4

production can occur in soils once redox potentials becomemore negative than ndash100 mV (Hou et al 2000) and 10-foldincreases in CH4 emission have been noted for each ndash50 mVdecrease in redox potential over the range ndash150 to ndash250 mV(Masscheleyn et al 1993) Such conditions are typicallyassociated with soils exposed to prolonged flooding (egunder rice cultivation) or saturated conditions Rates of CH4

emission from flooded soils are generally 10mg CH4 mndash2 hndash1

(Dalal et al 2008) Given the high dependence on redoxpotential soil properties influencing rates of oxygen diffusion(eg soil bulk density and pore size distribution) and oxygenconsumption (eg presence of decomposable C substrates) exertprimary control over rates of CH4 production (Conrad 2005)Bossio et al (1999) found 5-fold increases in CH4 emissionswhere rice straw was incorporated rather than being burnt overa 4-year period (92v 19 kg CH4 handash1) Management practices thatenhance the presence of electron acceptors such as Fe3+ (creationof transient oxic conditions through temporary drainage) orSO4

2ndash (application of gypsum or ammonium sulfate) canreduce CH4 emissions when soils are exposed to saturatedconditions such as occur under rice production (Corton et al2000 Wassmann et al 2000 Kumaraswamy et al 2001Le Mer and Roger 2001 Mosier et al 2004 Conrad 2005)Methane production increases with increasing temperaturewith an average optimum around 358C and an average Q10

temperature coefficient of 40 depending on a range ofenvironmental factors and amount of biologically availablesubstrate (Dalal et al 2008)

Dryland agricultural soils provide a net sink for CH4 due totheir predominant oxidative condition with mean consumptionrates generally 100mg CH4 mndash2 hndash1 (Dalal et al 2008)Temperature effects on CH4 consumption are much smallerthan those associated with CH4 production (Dunfield et al1993) however soil water content or water-filled pore spaceexerts strong control (Kessavalou et al 1998 Veldkamp et al2001) At low soil water contents CH4 consumption can belimited as sufficient water is required to initiate methanotrophicactivity Dalal et al (2008) presented a generalised relationshipshowing enhanced rates of methane consumption in progressingfrom 80 to 30 water-filled pore space Observations ofenhanced CH4 consumption with increasing headspace CH4

concentration suggest that rates of consumption are likelyCH4-limited under favourable environment conditions


possibly due to limits on rates of CH4 diffusion into soilConsumption of CH4 in arable soils is generally lower thanthat in pasture or forest soils under similar environmentalconditions and decreases in progression from temperate totropical regions (Dalal et al 2008)

Increased temperatures and drier conditions associated withprojected climate changes for Australia would be expected toaffect CH4 emissions from irrigated and dryland agriculturedifferently Under irrigated agriculture prolonged periods offlooding associated with increased temperature will have thepotential to enhance CH4 emissions particularly where cropresidues are retained Adequate water management strategiesto allow temporary oxic soil conditions will be essential tominimise CH4 emissions under such conditions The greatestpotential to consume CH4 is likely to exist where non-floodirrigation is practiced Through judicious control of soil watercontent rates of CH4 consumption can be optimised howeverwhether this can be achieved at the same time as optimisingplant productivity will require assessment Under drylandagricultural systems the lack of strong temperature effects onCH4 consumption suggests that projected reductions in theavailability of water will be most influential For soils thatcurrently experience prolonged wet periods enhanced CH4

consumption is likely to be associated with future climatescenarios provided that the soils do not dry to the extent thatthe activity of methanotrophs is limited Where methanotrophicactivity becomes limiting due to reduced water availability ratesof CH4 consumption may decline

As a concluding note to this section on soil carbon storageand greenhouse gas emissions it is important to recognise thatwhen a change in management practice is applied to increasesoil carbon storage or reduce N2O and CH4 emissions the neteffect of the practice change on the total greenhouse gas emissionwill require consideration This consideration may also requirea quantification of off-farm emissions As an example if soilcarbon values are increased by enhanced crop productivitythrough the application of additional nitrogen fertiliseremissions of CO2 during the production and transport of thefertiliser and potential enhanced emissions of N2O will have tobe considered to define the net benefit associated with increasingsoil carbon

Current research priorities

In this section current research priorities required to define therole of soils in the mitigation of greenhouse gas emissionsand removal of CO2 from the atmosphere will be identifiedand discussed Priorities common to all three greenhouse gaseswill be identified first followed by those specific to soil carbonand then N2O and CH4

All greenhouse gases

The diversity of climate soil types and agricultural practices inplace across Australia will make it difficult to define and applygeneric greenhouse gas emissions factors with confidenceparticularly where accurate estimates are desired for thediverse range of agricultural enterprises Research will need tofocus on the development and implementation of measurement

technologies as well as the improvement of current simulationmodelling capabilities Debate exists as to whether the focusshould be on measurement or modelling however both will beneeded and with appropriate coordination the two approachescan be used to inform and enhance the value of each otherWhile appropriate measurement technologies can be used toretrospectively define carbon stock changes or alterations tonet greenhouse gas emissions they cannot be used to guidechanges in land use and management practice throughforecasting potential outcomes Definition of potentialoutcomes of on-farm management and policy decisions onlocal regional and national greenhouse gas emissions willrequire a robust modelling capability However appropriatemodel development will require comprehensive field datasetsto define baseline soil conditions and to calibrate and validatemodel outputs Establishing efficient (accurate rapid cost-effective) measurement technologies will be essential tofacilitate the acquisition of appropriate datasets Suchmeasurement technologies need be designed to provide datathat are consistent with those required by the simulationmodels and to allow temporal measurements of carbon stocksor N2O and CH4 emissions for calibration and validation ofmodels

As Australia enters into carbon-trading systems simplymeasuring or predicting a carbon stock change or changes innet greenhouse gas emissions will not be good enough Theuncertainty associated with such values will be required andwill need to include that associated with the measurementtechnology applied model predictions (if used) and thespatial variability associated with the variable of interest (egsoil carbon content) and all other variables required to completecalculations (eg bulk density in the case of soil carbon stocks)Where possible it is recommended that this uncertainty beexpressed as a cumulative probability distribution (Snedecorand Cochran 1989) to allow land managers potential buyersof carbon credits andfinancial institutions to assess the level ofrisk associated with carbon transactions

As an example consider the situation where an estimate isdesired for the potential outcome on soil carbon of adopting a10 increase in the proportion of pastures grown in rotation withcrops across an agricultural region A measurement campaignwould be used to define the current frequency distribution ofsoil carbon in farm paddocks across the region (Fig 4a) Thisdistribution would form the input to a soil carbon simulationmodel set up to model both the current business-as-usualsituation as well as the changed management regime into thefuture Through repeated sampling of the initial baseline soilcarbon frequency distribution a cumulative probabilitydistribution (Fig 4b) or a relative frequency distribution(Fig 4c) of the estimated change in soil carbon stocks couldbe derived The example presented suggests that 60 of thetime a net change in soil carbon of 10 Mg C handash1 would beexpected after 10 years or an average value of 8 3 Mg C handash1Subsequent measurements at some point in the future shouldbe conducted to assess the predictive capabilities of the modeland used to facilitate model alteration where poor agreementbetween model predictions and future measurements areobtained Under such a scheme the combination ofmeasurement and modelling allows current assessment


predictions of future outcomes assessment of these outcomesand possible recalibration of models if required AlthoughFig 4 is based on soil carbon change a similar approach couldbe applied to estimate the effect of management regimes on netemissions of N2O or CH4 A possible exception to this would bethe use of an initial frequency distribution which would muchmore difficult and expensive to collect for N2O and CH4

emissions


Future research directions for SOC will need to be structuredaround optimising the efficiency of soil carbon stockmeasurements and improving the capability of soil carbonmodels to accurately predict the impact of changes in land useand management practice Approaches to optimise soil carbonsampling will first be examined followed by a consideration ofthe duration required between measurements and an assessmentof progress against development of rapid and cost-effectivemethods for measuring soil carbon and its composition

Measuring soil carbon stocks can be costly particularly wheresubstantial variations in soil landscape and environmentalproperties exist Approaches that use existing spatial datasetsto optimise sample placement and minimise the number ofsampling locations are required Stratified simple randomsampling introduces a non-random element into sampling designby portioning the sample space into more homogeneous

subgroups before the application of a random sample to eachstratum This approach can reduce sampling error by decreasingthe variance of sample estimates within each stratum andtherefore yield SOC data with smaller uncertainties (see forexample de Gruijter et al 2006)

In order to obtain information on the spatial distribution ofSOC required to optimise soil sampling numerous spatial datalayers for variables that exhibit some degree of relation toSOC levels (ie soil type land use normalised differencevegetation index terrain attributes) can be used However inthe case of SOC these relationships can be non-linear as well assubject to threshold conditions indicating that variables alterin importance depending on the complex non-linear interplayof several factors at the site of interest (eg see Buiet al 2009)As a result monothetic division where included variablesare treated as both necessary and sufficient to classify SOCdistribution may not be particularly advantageous whenused for stratification For instance stratification of a singleattribute (such as soil type) may not reflect enough of thecontrolling factors on SOC levels to produce statisticallyworthwhile groupings As more variables are introduced tothe classification such as terrain attributes or vegetation covergroupings may become less disparate and increasingly disjointedthereby reducing stratification effectiveness This is in part dueto the decreasing ratio of signal to noise which may outweigh thebenefits of including additional attributes in this manner in thefirstplace

2) Define model parameters for the business as usual and alternative management scenarios

SOC

Fre

quen

cydi

strib

utio

n

σi = 8

Measured values

Nor

mal

ised

cum

ulat

ive

prob

abili

ty d

istr

ibut

ion

10

06

Modelled values

Fre

quen

cydi

strib

utio

n

i = 8i

microi = 40

(a)

SOC change after 10 years(Mg SOC handash1 in 0ndash30 cm soil)


(Mg SOC kgndash1 in 0ndash30 cm soil)

microp= 8

σp = 3

1) Define the frequency distribution of initial soil carbon stocks

3) Repeatedly sample the frequency distribution of soil carbon values and use these values to initialise and run the soil carbon simulation model for both the business as usual and modified practice scenarios

4) Calculate the magnitude of the difference in soil carbon stocks between the two management scenarios for each model run and build either a cumulative probability distribution (b) or frequency distribution (c) of the change

(b)

(c)

Fig 4 A strategy for combining measurement and modelling to provide an estimate of the level of risk associated with acquiring a particular increasein soil carbon through the adoption of a defined management scenario (a) Frequency distribution of soil carbon stocks across a region as defined by themeasurements performed on collected samples with a mean ofmi and standard deviation of si (b) cumulative probability distribution of SOC change asdefined by model output and (c) frequency distribution of soil carbon change with a mean ofmp and standard deviation ofsp (Note all values presentedare fictitious)


One solution to this problem is to employ a polytheticapproach to conceptual division Polythetic approaches toclassifying dissimilarity use a broad set of criteria (that areneither necessarily explicit nor sufficient) to provide theinformation to be stratified An example of this approach is topredict the spatial distribution of SOC from a combination oflegacy SOC data and continuous environmental variables Thisallows stratification of the sampling space in a way thatincorporates the best available information while minimisingthe introduction of variable noise Once a continuousprediction of SOC has been obtained spatial stratification canbe applied either proportionally or optimally Proportionalallocation uses arbitrary incremental steps in predicted SOClevels to determine strata whereas optimal allocation canstratify on the basis of the frequency distribution As optimalallocation allows the statistical structure of the (predicted)target variable to be taken into account it is considered anadvantageous approach Proportional or optimal allocation canalso be applied at the random sampling step rather than thestratification step

In general stratified sampling schemes can provide betterestimates of the mean with fewer samples compared with a simplerandom design for a single survey When multiple surveys areconducted through time (ie for monitoring purposes)stratification has the added benefit of allowing theincorporation of new informationobservations into the designas it becomes available and therefore increases in efficacy withtime

An example of the polythetic approach to obtainingexhaustive spatial information of SOC distribution for an areaof ~5000 km2 is given in Fig 5a This spatial prediction was

constructed at a resolution of 250 m by combining depth-harmonised legacy profile information with environmentalattributes using a machine learning approach (I Wheelerunpubl data) This layer can then be stratified using optimalallocation to account for the variability of the predicteddistribution into six strata showing internal similarity (Fig5b)from which random samples can then be drawn

Where an assessment of management impacts on SOC valuesis desired it is important to consider the duration over which adefined management strategy has been implemented and whatthe implications of prior management may have been In a recentsurvey of Australian peer-reviewed journal papers Sandermanet al (2010) noted that changes in soil carbon obtainedthrough the adoption of lsquocarbon friendlyrsquo management relativeto more intensive management strategies ranged from 01 to 05Mg C handash1 yearndash1 over the 0ndash15 cm soil layer At a rate of changeof 05 Mg C handash1 yearndash1 it would take 3ndash45 years to detect achange in soil carbon content equivalent to 01 of the total0ndash15 cm soil mass depending on bulk density (Fig6) If higherrates of carbon accumulation can be achieved this time willdecrease (eg for an increase of 20 Mg C handash1 yearndash1075ndash113 years would be required) The implication of thisobservation is that unless a management practice inducessignificant increases in soil carbon (gt03 Mg C handash1 yearndash1 forthe 0ndash15 cm layer orgt06 Mg C handash1 yearndash1 for the 0ndash30 cm layer)it will take gt5 years to detect changes equivalent to 01 ofthe soil mass Another implication is that the potential fordetecting a change in soil carbon will increase as the thicknessof the soil layer decreases Given that carbon tends to accumulateto a greater extent near the soil surface where an assessment ofchanges in SOC stocks for the 0ndash30 cm layer are required a

Emerald Hill Emerald Hill

Gunnedah

gt04

0ndash100 cmSOC

04ndash06

06ndash08

08ndash10

10ndash12

12ndash14

14ndash16

16ndash18

18ndash20

gt20

1

2

3

4

5

6

Carroll CarrollGunnedah

Ourlewis

Breeza

OurlewisMullaley Mullaley

Tambar Springs Tambar Springs

Premer

Bundella

Premer

Bundella

Blackville

Yanaman

Blackville

Yanaman

Spring Ridge Spring RidgeCaroona

Pine Ridge

Caroona

Pine Ridge

Breeza

0 5 10 20 Kilometers 0 5 10 20 Kilometers

(a) (b)

Fig 5 (a) Average percentage soil organic carbon in the top 100 cm at resolution of 250 m across the Namoi Valley andLiverpool Plains in New South Wales and (b) optimal allocation of six strata to the predicted surface (I Wheeler unpubl data)


greater capability to detect change would exist where this layer isbroken up into 0ndash10 10ndash20 and 20ndash30 cm layers

Given the annual variations that exist in climate and otherfactors controlling crop and pasture productivity (eg diseaselate sowing inadequate nutrition etc) inter-annual variabilityin rates of soil carbon capture will undoubtedly exist To dealwith these issues effectively time-averaged trends calculatedby performing multiple measurements of soil carbon stocksover appropriate time scales will be required One approach todeal with this issue at a national level and build Australiarsquoscapability to both document and predict future impacts ofland use and management on soil carbon storage would beto establish a national soil carbon monitoring system Themonitoring system would require sampling locationspositioned throughout Australiarsquos agricultural regions Soilat each monitoring location would have to be repeatedlysampled through time Such data if combined with accuratedocumentation of the agricultural management practicesemployed by the land owner would allow the impact of landmanagement to be defined at regional levels and will providea robust national soil carbon dataset for optimisation of themodel included in the national carbon accounting systemthrough validation of model predictions and recalibrationwhere required

A related issue that requires consideration is how to samplenew and innovative farming systems in a statistically robustmanner One approach would be to compare measurements ofsoil carbon stocks obtained from such systems to frequencydistributions obtained for soil under the dominant practices inthe same agricultural region Where new systems produce soilcarbon stocks that are gt95th percentile of these distributionsstrong evidence would exist to suggest an enhanced accumulationof soil carbon However care must be taken to ensure that themeasured values of soil carbon are reflective of the imposedmanagement and not dominated by prior practices

Given the variable run-down of soil carbon that has occurreddue to the implementation of agriculture across Australia (Luoet al 2010b Sanderman et al 2010) and the length of timerequired for soil carbon to attain a value indicative of any newmanagement strategy the sampling of soils under new andinnovative practices too early is more likely to result in theacquisition of soil carbon data that are reflective of prior ratherthan current management practices Application of both repeatedsampling through time and modelling to define potentialtrajectories and final outcomes would provide the bestapproach but would also require time to complete theassessment Development of alternative approaches wouldhelp to identify practices with the potential to enhance soilcarbon and mitigate emissions

Measurements of SOC have traditionally focussed onquantification of the total amount of organic carbon present insoil through sample collection followed by laboratory analysisThe costs of this exercise compounded with spatial andtemporal variations in soil carbon often mean that the numberof samples collected and analysed limits the usefulness ofacquired results The quest should continue for rapid and cost-effective analytical methodologies for both laboratory andfieldsituations Analytical technologies have recently emerged thatextend the nature of data generated beyond that provided byconventional dry combustion analyses including laser-inducedspectroscopy (Herrmann et al 2005 Bai and Houlton 2009)inelastic neutron scattering (Rawluket al 2001 Li et al 2005)and near- and mid-infrared spectroscopies (Gerberet al 2010Ma and Ryan 2010) Research should be directed towardsthe possible extension of these technologies to field-basedapproaches capable of accounting for spatial variability InAustralia the use of mid-infrared spectroscopy combined withpartial least-squares analysis (MIRPLS) has been shown toallow rapid and cost-effective predictions of not only the totalorganic carbon content of soils but also the allocation of thiscarbon to component fractions with a defined confidence (Janiket al 2007) It has also been demonstrated that these fractionscould be substituted for the conceptual pools to produce avariant of the RothC soil carbon simulation model capable ofmodelling the dynamics of both total soil organic carbon andits component fractions (Skjemstad et al 2004) Extension ofthese measurement and modelling capabilities across a greaterrange of soils and agricultural systems is warranted Thedefinition of upper limits of soil carbon capture and storagewill be critical to allow estimates of soil carbon sequestrationpotential to be realised

Nitrous oxide and methane

Quantification of N2O and CH4 emissions from soil reliescompletely on the measurement of net gas fluxes because nostock change measurements such as those applicable to CO2

emissions are possible Various field-based methodologiesexist to estimate fluxes of non-CO2 greenhouse gases(Denmead et al 2010) Measurements of net fluxes of N2Oand CH4 integrated over time are obtained using eithermicrometeorological techniques (eg Phillips et al 2007Macdonald et al 2011) or ground-based monitoring chambersthat collect continuous data (eg Bartonet al 2008 2010 2011

500ndash15 cm soil bulk density = 100




30

20

10

000 05

Annual change in soil organic carbon (Mg Chayear)

Year

s re

quire

d to

ach

eive

a c

hang

e in

SO

C o

f0

1 o

f soi

l mas

s

10 15 20

Fig 6 Duration required to detect a change in the soil carbon content of the0ndash30 cm layer that would be equivalent to 01 of soil mass for annual valuesof soil carbon increase ranging from 01 to 20 Mg C handash1 yearndash1


Scheer et al 2011 Wang et al 2011) Although both of thesecontinuous monitoring approaches can provide estimates offluxes integrated over time they each have relative strengthsand weaknesses Micrometeorological techniques do notdisturb the soil or cause alterations to soil or plant processesand they provide an estimatedflux integrated over relatively largedistances (100 times the height) compared with the typical sizeof continuous monitoring chambers However whererelationships between the magnitude of N2O or CH4 flux andsoil properties (eg water) are sought obtaining appropriatespatially averaged values applicable to the entire fetch area ofmicrometeorological equipment will be difficult Use ofdatalogging equipment to monitor soil conditions directlyunder the chambers may provide a more appropriate approachfor such studies

Although non-continuous measurements using staticchambers have been used to examine relative differences inN2O and CH4 emission between treatments (Allen et al 20092010 Huang et al 2011) and spatial variations in N2O emissions(Turner et al 2008) integrating such values to provideaccurate estimates of emissions through time and space is notpossible given the magnitude of diurnalfluctuations (Macdonaldet al 2011) the high dependence of emission rates on soilproperties that vary significantly through time (Dalal et al2003) and the potential episodic nature of emission events(Chen et al 2010a)

Given the expense and technical requirements to maintaincontinuous monitoring systems routine estimation of N2O andCH4 emissions from individual landholdings and the formationof a national emission accounting system cannot be based onmeasurement alone Satisfying the requirements for accountingsystems will rely on the use of emissions factors andor thedevelopment of modelling capabilities However derivation ofappropriate emission factors and models will require continueduse of monitoring technologies to quantify emissions atrepresentative locations and provide data to constructcalibrate and validate simulation models

The current Australian national Nitrous Oxide ResearchProgram (NORP) is collecting valuable data that will becritical to model development however the number of siteswhere monitoring of N2O and CH4 emissions is occurring islimited given the diversity of Australiarsquos climate soils andagricultural systems Such experimental measurementprograms will need to be continued and extended to additionalagricultural regions and as new agricultural managementpractices are developed Questions that require considerationto help guide the acquisition of N2O and CH4 emissions dataand model development include

(1) How can the limited number of continuous monitoringsystems be optimally located within the diverse mix ofclimates soil types and agricultural practices acrossAustralia

(2) What are the relative responses of N2O and CH4 emissions tosoil temperature and water content do the responses interactand do they vary significantly between soil types

(3) How will changes in soil bulk density and pore sizedistribution that are induced by compaction or reducedtillage impact on net fluxes of N2O and CH4

(4) Will calibration of current models be adequate to deal withpotential climate change

(5) At present a much greater emphasis is being placed onmonitoring the net emissions of N2O should moreemphasis be placed on the additional acquisition of netCH4 emission data for soils

Summary

Soils contain significant stocks of carbon and nitrogenBiochemical processes associated with carbon and nitrogencycling can lead to both the consumption and emission ofthe three major greenhouse gases (CO2 N2O and CH4) Theseprocesses are strongly influenced by temperature and soilwater content (balance between rainfall and potentialevapotranspiration) Thus the predicted hotter and drierclimatic conditions associated with climate change projectionswill impact on net greenhouse gas emissions from soilhowever the direction and extent of influence require furtherconsideration Guiding principles exist to help developagricultural management strategies capable of enhancing soilcarbon stocks or reducing net N2O and CH4 emissions

The guiding principal to enhance carbon capture in soilsunder any climate-change scenario will be to maximise carboninputs Where the ability of a soil to protect organic carbonagainst decomposition is not saturated andor whereinefficiencies in resource use (water and nutrients) can beimproved by altered management to allow plants to captureadditional atmospheric CO2 the potential exists to increaseSOC and enhance soil resilience and productivity Thispotential will vary from location to location as a function ofsoil type (clay content depth bulk density etc) environmentalconditions (amount of available water and nutrients temperatureetc) and past management regimes (how much carbon has beenlost due to past management) Tailoring management solutionsthat optimise SOC at a defined location will be required

To reduce N2O emissions the guiding principal is to reduceconcentrations of the inorganic nitrogen Inorganic nitrogenserves as the substrate for the two main processes responsiblefor N2O emissionsmdashnitrification and denitrification However indeveloping practices to reduce inorganic nitrogen concentrationsin soil it is important to ensure that croppasture nitrogenrequirements are still met Development of flexible nitrogen-application strategies is required to allow a better matching offertiliser additions to crop demand as defined by seasonalclimatic conditions Methane emissions from soils can beminimised by maintaining the soil in an oxic state for as longas possible

Going forward the delivery of cost-effective measurementtechnologies coupled to adequately developed computersimulation models will be required Such a combination willproduce the required capabilities to develop managementpractices that can accumulate soil carbon and minimise theemissions of N2O and CH4 and underpin a national carbonaccounting system Development and support of a soil-monitoring program into the future is essential to ensureadequate coverage of all of Australiarsquos agricultural regions andallow an assessment of the impacts of variations in climate soiland agricultural production systems


Acknowledgments

Dr Baldock acknowledges financial support from the Department ofClimate Change and Energy Efficiency the Department of AgricultureFisheries and Forestry and the Grains Research and DevelopmentCorporation who have all funded projects that have led to the developmentof the ideas presented within this paper

References

Allen DE Mendham DS Bhupinderpal S Cowie A Wang W Dalal RCRaison RJ (2009) Nitrous oxide and methane emissions from soil arereduced following afforestation of pasture lands in three contrastingclimatic zones Australian Journal of Soil Research 47 443ndash458

Allen DE Kingston G Rennenberg H Dalal RC Schmidt S (2010) Effect ofnitrogen fertilizer management and waterlogging on nitrous oxideemission from subtropical sugarcane soils Agriculture Ecosystems ampEnvironment 136 209ndash217 doi101016jagee200911002

Anderson DW Paul EA (1984) Organo-mineral complexes and their studyby radiocarbon dating Soil Science Society of America Journal 48298ndash301 doi102136sssaj198403615995004800020014x

Angus JF (2001) Nitrogen supply and demand in Australian agricultureAustralian Journal of Experimental Agriculture 41 277ndash288doi101071EA00141

Bai E Houlton BZ (2009) Coupled isotopic and process-based modeling ofgaseous nitrogen losses from tropical rain forestsGlobal BiogeochemicalCycles 23 Art No GB2011 doi1010292008gb003361

Baldock JA (2007) Composition and cycling of organic carbon in soil InlsquoSoil biology Volume 10 Nutrient cycling in terrestrial ecosystemsrsquo (EdsP Marschner Z Rengel) (Springer-Verlag Berlin)

Barton L Kiese R Gatter D Butterbach-Bahl K Buck R Hinz C Murphy DV(2008) Nitrous oxide emissions from a cropped soil in a semi-arid climateGlobal Change Biology 14 177ndash192

Barton L Murphy DV Kiese R Butterbach-Bahl K (2010) Soil nitrousoxide and methane fluxes are low from a bioenergy crop (canola) grownin a semi-arid climate Global Change Biology ndash Bioenergy 2 1ndash15doi101111j1757-1707201001034x

Barton L Butterbach-Bahl K Kiese R Murphy DV (2011) Nitrous oxidefluxes from a grain-legume crop (narrow-leafed lupin) grown in asemiarid climate Global Change Biology 17 1153ndash1166 doi101111j1365-2486201002260x

Blair GJ Lefory RDB Lisle L (1995) Soil carbon fractions based on theirdegree of oxidation and the development of a carbon managementindex for agricultural systems Australian Journal of AgriculturalResearch 46 1459ndash1466 doi101071AR9951459

Bossio DA Horwath WR Mutters RG Van Kessel C (1999) Methane pooland flux dynamics in a rice field following straw incorporation SoilBiology amp Biochemistry 31 1313ndash1322 doi101016S0038-0717(99)00050-4

Bui E Henderson B Viergever K (2009) Using knowledge discoverywith data mining from the Australian Soil Resource InformationSystem database to inform soil carbon mapping in Australia GlobalBiogeochemical Cycles 23 Art No GB2011 doi1010292009GB003506

Castaldi S (2000) Responses of nitrous oxide dinitrogen and carbon dioxideproduction and oxygen consumption to temperature in forest andagricutlural light-textured soils determined by model experimentBiology and Fertility of Soils 32 67ndash72 doi101007s003740000218

Chalk PM (1998) Dynamics of biologically fixed N in legume-cerealrotations a review Australian Journal of Agricultural Research 49303ndash316 doi101071A97013

Chen D Li Y Kelly K Eckard R (2010a) Simulation of N2O emissions froman irrigated dairy pasture treated with urea and urine in SoutheasternAustralia Agriculture Ecosystems amp Environment 136 333ndash342doi101016jagee200912007

Chen D Suter HC Islam A Edis R (2010b) Influence of nitrification inhibitorson nitrification and nitrous oxide (N2O) emission from a clay loam soilfertilized with urea Soil Biology amp Biochemistry 42 660ndash664doi101016jsoilbio200912014

Conrad R (2005) Quantification of methanogenic pathways using stablecarbon isotopic signatures a review and a proposal OrganicGeochemistry 36 739ndash752 doi101016jorggeochem200409006

Corton TM Bajita JB Grospe FS Pamplona RR Asis CAJ WassmannR Lantin RS Buendia LV (2000) Methane emission from irrigatedand intensively managed rice fields in Central Luzon (Philippines)Nutrient Cycling in Agroecosystems 58 37ndash53 doi101023A1009826131741

CSIRO (2007) Climate Change in Australia Technical Report Available atwwwclimatechangeinaustraliagovautechnical_reportphp

Dalal RC Wang W Robertson GP Parton WJ (2003) Nitrous oxideemission from Australian agricultural lands and mitigation options areview Australian Journal of Soil Research 41 165ndash195 doi101071SR02064

Dalal RC Allen DE Livesley SJ Richards G (2008) Magnitude andbiophysical regulators of methane emission and consumption in theAustralian agricultural forest and submerged landscapes a reviewPlant and Soil 309 43ndash76 doi101007s11104-007-9446-7

Davidson EA Janssens IA (2006) Temperature sensitivity of soil carbondecomposition and feedbacks to climate changeNature 440 165ndash173doi101038nature04514

de Gruijter J Brus D Bierkens M Knotters M (2006)lsquoSampling for naturalresource monitoringrsquo (Springer Berlin)

Denmead OT Macdonald BCT Bryant G Naylor T Wilson S Griffith DWTWang WJ Salter B White I Moody PW (2010) Emissions of methane andnitrous oxide from Australian sugarcane soilsAgricultural and ForestMeteorology 150 748ndash756 doi101016jagrformet200906018

Di HJ Cameron KC (2003) Mitigation of nitrous oxide emissions in spray-irrigated grazed grassland by treating the soil with dicyandiamide anitrification inhibitor Soil Use and Management 19 284ndash290doi101079SUM2003207

Di HJ Cameron KC (2006) Nitrous oxide emissions from two dairy pasturesoils as affected by different rates of afine particle suspension nitrificationinhibitor dicyandiamide Biology and Fertility of Soils 42 472ndash480doi101007s00374-005-0038-5

Di HJ Cameron KC Sherlock RR (2007) Comparison of the effectivenessof a nitrification inhibitor dicyandiamide in reducing nitrous oxideemissions in four different soils under different climatic andmanagement conditions Soil Use and Management 23 1ndash9doi101111j1475-2743200600057x

Dunfield P Knowles R Dumont R Moore TR (1993) Methane productionand consumption in temperate and subarctic peat soils response totemperature and pH Soil Biology amp Biochemistry 25 321ndash326doi1010160038-0717(93)90130-4

Eswaran H Van den Berg E Reich P Kimble JM (1995) Global soil Cresources In lsquoSoils and global changersquo (Eds R Lal JM Kimble E LevineBA Stewart) pp 27ndash43 (Lewis Publishers Boca Raton FL)

Freney JR Denmead OT Simpson JR (1978) Soil as a source or sink foratmospheric nitrous oxideNature 273 530ndash532 doi101038273530a0

Gerber S Hedin LO Oppenheimer M Pacala SW Shevliakova E (2010)Nitrogen cycling and feedbacks in a global dynamic land modelGlobal Biogeochemical Cycles 24 Art No GB1001 doi1010292008GB003336

Giardina CP Ryan MG (2000) Evidence that decomposition rates oforganic matter in mineral soil do not vary with temperatureNature404 858ndash861 doi10103835009076

Golchin A Baldock JA Oades JM (1997) A model linking organic matterdecomposition chemistry and aggregate dynamics InlsquoSoil processes andthe carbon cyclersquo (Eds R Lal JM Kimble RF Follett BA Stewart)pp 245ndash266 (CRC Press Boca Raton FL)


Goodroad LL Keeney DR (1984) Nitrous oxide proudction in aerobic soilsunder varying pH temperature and water content Soil Biology ampBiochemistry 16 39ndash43 doi1010160038-0717(84)90123-8

Grace J Rayment M (2000) Respiration in the balanceNature 404 819ndash820doi10103835009170

Herrmann A Witter E Katterer T (2005) A method to assess whetherlsquopreferential usersquo occurs after 15N ammonium addition implication forthe 15N isotope dilution technique Soil Biology amp Biochemistry 37183ndash186 doi101016jsoilbio200406008

Hou AX Chen GX Wang ZP Van Cleempu TO Patrick WHJ (2000)Methane and nitrous oxide emissions from a rice field in relation tosoil redox and microbiological processesSoil Science Society of AmericaJournal 64 2180ndash2186 doi102136sssaj20006462180x

Houghton RA (2005) The contemporary carbon cycle InlsquoBiogeochemistryrsquo(Ed WH Schlesinger) pp 473ndash513 (Elsevier Science Amsterdam)

Huang X Grace P Mengersen K Weier K (2011) Spatio-temporal variationin soil derived nitrous oxide emissions under sugarcaneThe Science ofthe Total Environment 409 4572ndash4578 doi101016jscitotenv201107044

Hutchinson JJ Campbell CA Desjardins RL (2007) Some perspectives oncarbon sequestration in agricultureAgricultural and Forest Meteorology142 288ndash302 doi101016jagrformet200603030

Janik LJ Skjemstad JO Shepherd KD Spouncer LR (2007) The predictionof soil carbon fractions using mid-infrared-partial least square analysisAustralian Journal of Soil Research 45 73ndash81 doi101071SR06083

Jenkinson DS Hart PBS Rayner JH Parry LC (1987) Modelling theturnover of organic matter in long-term experiments at RothamstedIntecol Bulletin 15 1ndash8

Jobbaacutegy EG Jackson RB (2000) The vertical distribution of soil organiccarbon and its relation to climate and vegetationEcological Applications10 423ndash436 doi1018901051-0761(2000)010[0423TVDOSO]20CO2

Kebreab E France J Beever DE Castillo AR (2001) Nitrogen pollution bydairy cows and its mitigation by dietary manipulationNutrient Cyclingin Agroecosystems 60 275ndash285 doi101023A1012668109662

Keeney DR Fillery IR Marx GP (1979) Effect of temperature on thegaseous nitrogen products of denitrification in a silt loam soil SoilScience Society of America Journal 43 1124ndash1128 doi102136sssaj197903615995004300060012x

Kessavalou A Mosier AR Doran JW Drijber RA Lyon DJ Heinemeyer O(1998) Fluxes of carbon dioxide nitrous oxide and methane ingrass sod and winter wheatndashfallow tillage management Journal ofEnvironmental Quality 27 1094ndash1104 doi102134jeq199800472425002700050015x

Knorr W Prentice IC House JI Holland EA (2005) Long-term sensitivity ofsoil carbon turnover to warming Nature 433 298ndash301 doi101038nature03226

Kumaraswamy S Ramakrishnan B Sethunathan N (2001) Methaneproduction and oxidation in an anoxic rice soil as influenced byinorganic redox species Journal of Environmental Quality 302195ndash2201 doi102134jeq20012195

Ladd JN Oades JM Amato M (1981) Microbial biomass formed from14C 15N-labelled plant material decomposing in soils in the fieldSoil Biology amp Biochemistry 13 119ndash126 doi1010160038-0717(81)90007-9

Lal R (2004) Soil carbon sequestration to mitigate climate changeGeoderma123 1ndash22 doi101016jgeoderma200401032

Le Mer J Roger P (2001) Production oxidation emission and consumptionof methane by soils a review European Journal of Soil Biology 3725ndash50 doi101016S1164-5563(01)01067-6

Li CS Frolking S Butterbach-Bahl K (2005) Carbon sequestration in arablesoils is likely to increase nitrous oxide emissions offsetting reductionsin climate radiative forcingClimatic Change 72 321ndash338 doi101007s10584-005-6791-5

Luo J de Klein CAM Ledgard SF Saggar S (2010a) Management optionsto reduce nitrous oxide emissions from intensively grazed pasturesa review Agriculture Ecosystems amp Environment 136 282ndash291doi101016jagee200912003

Luo Z Wang E Sun OJ (2010b) Soil carbon change and its responsesto agricultural practices in Australian agro-ecosystems a reviewand synthesis Geoderma 155 211ndash223 doi101016jgeoderma200912012

Ma JF Ryan PR (2010) Understanding how plants cope with acid soilsFunctional Plant Biology 37 iiindashvi doi101071FPv37n4_FO

Macdonald BCT Denmead OT White I Byrant G (2011) Gaseous nitrogenlosses from coastal acid sulfate soils a short-term studyPedosphere 21197ndash206 doi101016S1002-0160(11)60118-5

Mackenzie FT (1998) lsquoOur changing planet an introduction to earth systemscience and global environmental changersquo 2nd edn (Prentice Hall UpperSaddle River NJ)

Masscheleyn PH DeLaune RD Patrick WHJ (1993) Methane and nitrousoxide emissions from laboratory measurements of rice soil suspensioneffect of soil oxidation-reduction status Chemosphere 26 251ndash260doi1010160045-6535(93)90426-6

McSwiney CP Robertson GP (2005) Nonlinear response of N2O flux toincremental fertilizer addition in a continuous maize (Zea mays L)cropping system Global Change Biology 11 1712ndash1719 doi101111j1365-2486200501040x

Mosier A Wassmann R Verchot L King J Palm C (2004) Methane andnitrogen oxide fluxes in tropical agricultural soils sources sinks andmechanisms Environment Development and Sustainability 6 11ndash49doi101023BENVI000000362743162ae

Mulligan FJ Dillon P Callan JJ Rath M OrsquoMara FP (2004) Supplementaryconcentrate type affects nitrogen excretion of grazing dairy cowsJournal of Dairy Science 87 3451ndash3460 doi103168jdsS0022-0302(04)73480-3

Nielsen NM Kristensen T Noslashrgaard P Hansen H (2003) The effect oflow protein supplementation to dairy cows grazing clover grass duringhalf of the day Livestock Production Science81 293ndash306 doi101016S0301-6226(02)00229-4

Paul EA Collins HP Leavitt SW (2001) Dynamics of resistant soil carbonof Midwestern agricultural soils measured by naturally occurring14Cabundance Geoderma 104 239ndash256 doi101016S0016-7061(01)00083-0

Peoples MB Baldock JA (2001) Nitrogen dynamics of pasturesnitrogen fixation inputs the impact of legumes on soil nitrogenfertility and the contributions of fixed nitrogen to Australian farmingsystems Australian Journal of Experimental Agriculture 41 327ndash346doi101071EA99139

Phillips FA Leuning R Baigenta R Kelly KB Denmead OT (2007)Nitrous oxide flux measurements from an intensively managedirrigated pasture using micrometeorological techniques Agriculturaland Forest Meteorology 143 92ndash105 doi101016jagrformet200611011

Powlson D (2005) Climatology will soil amplify climate changeNature433 204ndash205 doi101038433204a

Rawluk CDL Grant CA Racz GJ (2001) Ammonia volatilization from soilsfertilized with urea and varying rates of urease inhibitor NBPTCanadianJournal of Soil Science 81 239ndash246 doi104141S00-052

Sanderman J Farquharson R Baldock JA (2010) Soil Carbon SequestrationPotential A review for Australian agriculture CSIRO SustainableAgriculture Flagship Report prepared for Department of ClimateChange and Energy Efficiency Available at wwwcsiroauresourcesSoil-Carbon-Sequestration-Potential-Reporthtml

ScheerC Grace PR RowlingsDW Kimber S Van Zwieten L (2011) Effect ofbiocharamendmenton thesoilndashatmosphere exchangeofgreenhouse gasesfrom an intensive subtropical pasture in northern New South WalesAustralia Plant and Soil 345 47ndash58 doi101007s11104-011-0759-1


Six J Callewaert P Lenders S De Gryze S Morris SJ Gregorich EG Paul EAPaustian K (2002) Measuring and understanding carbon storage inafforested soils by physical fractionation Soil Science Society ofAmerica Journal 66 1981ndash1987 doi102136sssaj20021981

Skjemstad JO Spouncer LR Cowie B Swift RS (2004) Calibration of theRothamsted organic carbon turnover model (RothC ver 263) usingmeasurable soil organic carbon poolsAustralian Journal of Soil Research42 79ndash88 doi101071SR03013

Smith LC de Klein CAM Catto WD (2008) Effect of dicyandiamide appliedin a granular form on nitrous oxide emissions from a grazed dairy pasturein Southland New Zealand New Zealand Journal of AgriculturalResearch 51 387ndash396 doi10108000288230809510469

Snedecor GW Cochran WG (1989)lsquoStatistical methodsrsquo 8th edn (Iowa StateUniversity Press Ames IA)

Spain AV Isbell RF Probert ME (1983) Soil organic matter InlsquoSoils anAustralian viewpointrsquo pp 551ndash563 (CSIRO MelbourneAcademicPress London)

Swanston CW Torn MS Hanson PJ Southon JR Garten CT Hanlon EMGanio L (2005) Initial characterization of processes of soil carbonstabilization using forest stand-level radiocarbon enrichmentGeoderma 128 52ndash62 doi101016jgeoderma200412015

Turner DA Chen D Galbally IE Leuning R Edis RB Li Y Kelly K PhillipsF (2008) Spatial variability of nitrous oxide emissions from an Australianirrigated dairy pasture Plant and Soil 309 77ndash88 doi101007s11104-008-9639-8

Unkovich M Baldock J Forbes M (2010) Variability in harvest index ofgrain crops and potential significance for carbon accounting examplesfrom Australian agriculture Advances in Agronomy 105 173ndash219doi101016S0065-2113(10)05005-4

Veldkamp E Weitz AM Keller M (2001) Management effects on methanefluxes in humid tropical pasture soils Soil Biology amp Biochemistry 331493ndash1499 doi101016S0038-0717(01)00060-8

Wang W Dalal RC Reeves SH Butterbach-Bahl K Kiese R (2011)Greenhouse gas fluxes from an Australian subtropical cropland underlong-term contrasting management regimesGlobal Change Biology 173089ndash3101 doi101111j1365-2486201102458x

Wassmann R Neue HU Lantin RS Makarim K Chareonsilp N Buendia LVRennenberg H (2000) Characterization of methane emissions fromrice fields in Asia II differences among irrigated rainfed anddeepwater rice Nutrient Cycling in Agroecosystems 58 13ndash22doi101023A1009822030832

Watson CJ (2000) Urease activity and inhibitionmdashprinciples and practice InlsquoProceedings of the International Fertilizer Society No 454rsquo LondonUK (Ed CJ Watson) p 40 (International Fertiliser Society)

Whitehead DC (1995) lsquoGrassland nitrogenrsquo (CAB InternationalWallingford UK)


wwwpublishcsiroaujournalscp

emission and consumptionstorage of each of the greenhousegases (CO2 N2O and CH4) in soil and how the predicted climatechanges are likely to impact Options for adapting to andmitigating climate change from a soils point of view will thenbe discussed followed by identification of knowledge gaps andfuture research priorities

Climate change predictions for Australia

Climate projections for most of the agricultural regions ofAustralia suggest a warmer and drier future with alterations to

the seasonality and greater extremes relative to 1980ndash1999average annual climatic conditions (Fig 2) Although thenorth-eastern portion of Australia and particularly central NewSouth Wales is predicted to have higher or unchanged rainfall insummer this is accompanied by projected increases in potentialevapotranspiration Such conditions are likely to result in anoverall pattern of drying with respect to the amount of wateravailable to grow crops and pastures The projected climaticchanges will undoubtedly affect the balance between emissionand storageconsumption of CO2 N2O and CH4 in Australiarsquos

(a)

(b)

Fig 1 Soil biological processes that influence (a) consumption of atmospheric greenhouse gases bysoil and (b) emissions of greenhouse gases from soil into the atmosphere








2070(a)

50


(b)

40

(c)


2030 2050

03 06 10 15 20 25 30 40
































frac14 f


Biologicalcapacity

0BB

1CCA

frac14 f


protection



0BBBBBB

1CCCCCCA

eth1THORN






0 1 0 1 2 0 1 2 3 0 2 4 6

Calcar

osol

Chrom

osol

Ferro

sol

Verto

sol

0

50

100

150

200

Soi

l dep

th (

cm)









Nitrous oxide












Methane























emissions







SOC

Fre

quen

cydi

strib

utio

n

σi = 8

Measured values

Nor

mal

ised

cum

ulat

ive

prob

abili

ty d

istr

ibut

ion

10

06

Modelled values

Fre

quen

cydi

strib

utio

n

i = 8i

microi = 40

(a)




microp= 8

σp = 3




(b)

(c)









Gunnedah

gt04

0ndash100 cmSOC

04ndash06

06ndash08

08ndash10

10ndash12

12ndash14

14ndash16

16ndash18

18ndash20

gt20

1

2

3

4

5

6


Ourlewis

Breeza



Premer

Bundella

Premer

Bundella

Blackville

Yanaman

Blackville

Yanaman


Pine Ridge

Caroona

Pine Ridge

Breeza


(a) (b)















30

20

10

000 05


Year

s re

quire

d to

ach

eive

a c

hang

e in

SO

C o

f0

1 o

f soi

l mas

s

10 15 20












Summary






Acknowledgments


References





























































































2070(a)

50


(b)

40

(c)


2030 2050

03 06 10 15 20 25 30 40
































frac14 f


Biologicalcapacity

0BB

1CCA

frac14 f


protection



0BBBBBB

1CCCCCCA

eth1THORN






0 1 0 1 2 0 1 2 3 0 2 4 6

Calcar

osol

Chrom

osol

Ferro

sol

Verto

sol

0

50

100

150

200

Soi

l dep

th (

cm)









Nitrous oxide












Methane























emissions







SOC

Fre

quen

cydi

strib

utio

n

σi = 8

Measured values

Nor

mal

ised

cum

ulat

ive

prob

abili

ty d

istr

ibut

ion

10

06

Modelled values

Fre

quen

cydi

strib

utio

n

i = 8i

microi = 40

(a)




microp= 8

σp = 3




(b)

(c)









Gunnedah

gt04

0ndash100 cmSOC

04ndash06

06ndash08

08ndash10

10ndash12

12ndash14

14ndash16

16ndash18

18ndash20

gt20

1

2

3

4

5

6


Ourlewis

Breeza



Premer

Bundella

Premer

Bundella

Blackville

Yanaman

Blackville

Yanaman


Pine Ridge

Caroona

Pine Ridge

Breeza


(a) (b)















30

20

10

000 05


Year

s re

quire

d to

ach

eive

a c

hang

e in

SO

C o

f0

1 o

f soi

l mas

s

10 15 20












Summary






Acknowledgments


References


















































































































frac14 f


Biologicalcapacity

0BB

1CCA

frac14 f


protection



0BBBBBB

1CCCCCCA

eth1THORN






0 1 0 1 2 0 1 2 3 0 2 4 6

Calcar

osol

Chrom

osol

Ferro

sol

Verto

sol

0

50

100

150

200

Soi

l dep

th (

cm)









Nitrous oxide












Methane























emissions







SOC

Fre

quen

cydi

strib

utio

n

σi = 8

Measured values

Nor

mal

ised

cum

ulat

ive

prob

abili

ty d

istr

ibut

ion

10

06

Modelled values

Fre

quen

cydi

strib

utio

n

i = 8i

microi = 40

(a)




microp= 8

σp = 3




(b)

(c)









Gunnedah

gt04

0ndash100 cmSOC

04ndash06

06ndash08

08ndash10

10ndash12

12ndash14

14ndash16

16ndash18

18ndash20

gt20

1

2

3

4

5

6


Ourlewis

Breeza



Premer

Bundella

Premer

Bundella

Blackville

Yanaman

Blackville

Yanaman


Pine Ridge

Caroona

Pine Ridge

Breeza


(a) (b)















30

20

10

000 05


Year

s re

quire

d to

ach

eive

a c

hang

e in

SO

C o

f0

1 o

f soi

l mas

s

10 15 20












Summary






Acknowledgments


References




























































































Nitrous oxide












Methane























emissions







SOC

Fre

quen

cydi

strib

utio

n

σi = 8

Measured values

Nor

mal

ised

cum

ulat

ive

prob

abili

ty d

istr

ibut

ion

10

06

Modelled values

Fre

quen

cydi

strib

utio

n

i = 8i

microi = 40

(a)




microp= 8

σp = 3




(b)

(c)









Gunnedah

gt04

0ndash100 cmSOC

04ndash06

06ndash08

08ndash10

10ndash12

12ndash14

14ndash16

16ndash18

18ndash20

gt20

1

2

3

4

5

6


Ourlewis

Breeza



Premer

Bundella

Premer

Bundella

Blackville

Yanaman

Blackville

Yanaman


Pine Ridge

Caroona

Pine Ridge

Breeza


(a) (b)















30

20

10

000 05


Year

s re

quire

d to

ach

eive

a c

hang

e in

SO

C o

f0

1 o

f soi

l mas

s

10 15 20












Summary






Acknowledgments


References





























































































Methane























emissions







SOC

Fre

quen

cydi

strib

utio

n

σi = 8

Measured values

Nor

mal

ised

cum

ulat

ive

prob

abili

ty d

istr

ibut

ion

10

06

Modelled values

Fre

quen

cydi

strib

utio

n

i = 8i

microi = 40

(a)




microp= 8

σp = 3




(b)

(c)









Gunnedah

gt04

0ndash100 cmSOC

04ndash06

06ndash08

08ndash10

10ndash12

12ndash14

14ndash16

16ndash18

18ndash20

gt20

1

2

3

4

5

6


Ourlewis

Breeza



Premer

Bundella

Premer

Bundella

Blackville

Yanaman

Blackville

Yanaman


Pine Ridge

Caroona

Pine Ridge

Breeza


(a) (b)















30

20

10

000 05


Year

s re

quire

d to

ach

eive

a c

hang

e in

SO

C o

f0

1 o

f soi

l mas

s

10 15 20












Summary






Acknowledgments


References




































































































emissions







SOC

Fre

quen

cydi

strib

utio

n

σi = 8

Measured values

Nor

mal

ised

cum

ulat

ive

prob

abili

ty d

istr

ibut

ion

10

06

Modelled values

Fre

quen

cydi

strib

utio

n

i = 8i

microi = 40

(a)




microp= 8

σp = 3




(b)

(c)









Gunnedah

gt04

0ndash100 cmSOC

04ndash06

06ndash08

08ndash10

10ndash12

12ndash14

14ndash16

16ndash18

18ndash20

gt20

1

2

3

4

5

6


Ourlewis

Breeza



Premer

Bundella

Premer

Bundella

Blackville

Yanaman

Blackville

Yanaman


Pine Ridge

Caroona

Pine Ridge

Breeza


(a) (b)















30

20

10

000 05


Year

s re

quire

d to

ach

eive

a c

hang

e in

SO

C o

f0

1 o

f soi

l mas

s

10 15 20












Summary






Acknowledgments


References





























































































Gunnedah

gt04

0ndash100 cmSOC

04ndash06

06ndash08

08ndash10

10ndash12

12ndash14

14ndash16

16ndash18

18ndash20

gt20

1

2

3

4

5

6


Ourlewis

Breeza



Premer

Bundella

Premer

Bundella

Blackville

Yanaman

Blackville

Yanaman


Pine Ridge

Caroona

Pine Ridge

Breeza


(a) (b)















30

20

10

000 05


Year

s re

quire

d to

ach

eive

a c

hang

e in

SO

C o

f0

1 o

f soi

l mas

s

10 15 20












Summary






Acknowledgments


References



































































































30

20

10

000 05


Year

s re

quire

d to

ach

eive

a c

hang

e in

SO

C o

f0

1 o

f soi

l mas

s

10 15 20












Summary






Acknowledgments


References
































































































Summary






Acknowledgments


References























































































Acknowledgments


References























































































Soils and climate change: potential impacts on carbon stocks and … · 2016. 7. 11. · Soils and...

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Transcript of Soils and climate change: potential impacts on carbon stocks and … · 2016. 7. 11. · Soils and...