spatial patterns of soil organic carbon in the contiguous united states

Spatial Patterns of Soil Organic Carbon in the Contiguous United StatesJeffrey S. Kern*

ABSTRACTSpatial patterns and total amounts of soil organic C (SOC) are

important data for studies of soil productivity, soil hydraulic proper-ties, and the cycling of C-based greenhouse gases. This study evaluatedseveral approaches for characterizing SOC to determine their relativemerits. The first approach entailed grouping data from a global pedonSOC database by type of ecosystem, resulting in a total of 78.0 Pg ofC (Pg = 1015 g) to 1-m depth for the contiguous USA. In a secondapproach, a pedon database was aggregated using soil taxonomy,resulting in a total for the contiguous USA of 80.7 ± 18.6 Pg of Cwhen the great group SOC was spatially distributed with Major LandResource Areas (MLRAs) using the 1982 National Resource Inventory(NRI) and the Soil Interpretation Record databases. The third ap-proach used pedon and spatial data from a global soil map groupedby soil unit that resulted in 84.5 Pg of C for the contiguous USA.Although the ecosystem and soil taxonomic approaches resulted insimilar totals, the taxonomic approaches are recommended becausethey gave more realistic results in areas of Histosols, shallow soils,and soils with high rock fragment content. The ecosystem approachdid not give reh'able spatial patterns and is only useful for verybroad-scale work where precisely georeferenced data are not needed.Grouping data by great group provided more information than group-ing by order or suborder. The approach based on soil taxonomy isvery useful because it is based on the NRI statistical framework andit allows stratification by other NRI items, such as land use andvegetation.

SOIL ORGANIC MATTER, which is approximately 56%SOC (Nelson and Sommers, 1982), is a major factor

in plant nutrition (Stevenson, 1982), soil structure, com-pactability (Soane, 1990), and water-holding capacity(De Jong et al., 1983). In addition, soil is the largestterrestrial pool of C (Post et al., 1990) and must beconsidered for evaluating the flux of greenhouse gasesManTech Environmental Technology Inc., USEPA Environmental Re-search Lab., 200 SW 35th St., Corvallis, OR 97333. The information in thisdocument has been funded wholly by the U.S. Environmental ProtectionAgency (EPA) under Contract 68-C8-0006 to ManTech EnvironmentalTechnology, Inc. It has been subjected to the agency's peer and administra-tive review, and it has been approved as an EPA document. Received 1May 1992. "Corresponding author.

Published in Soil Sci. Soc. Am. J. 58:439-455 (1994).

between the terrestrial biosphere and the atmosphere.Spatial databases of SOC are needed, especially thosethat model the impact of agricultural tillage on SOC(Kern and Johnson, 1993), assess the impact of erosionon SOC pools (Kern, 1992), and provide informationfor biogeochemical modeling (Running and Coughlan,1988; Running and Gower, 1991). The purpose of thisstudy was to evaluate methods to estimate the spatialdistribution and amount of SOC in the contiguous USAto assess the relative merits of the methods. This isimportant for selecting which method to use for a givenapplication.

The SOC content of soil in the USA has been studiedin many locations; however, there have been few regionalor U.S. national-scale assessments. Franzmeier et al.(1985) characterized the SOC in the north central USAbased on a regional soil map, with laboratory data frompublished reports, theses, and unpublished data fromsoil survey activities. The map unit composition wasdetermined from published soil surveys, soil surveys inprogress, other inventories, and the expert judgment ofthe Technical Committee on Soil Survey. The upper 0.2 mof mineral soil ranged from 1.0 to 10.7 kg C m~2; theupper 1 m ranged from 2.3 to 19.2 kg C m~2.

Parton et al. (1987, 1989) used the CENTURY modelto analyze controlling factors of SOC accumulation inGreat Plains grasslands and modeled the geographic dis-tribution of SOC in the upper 20 cm. They concludedthat SOC content can be predicted from soil temperature,soil moisture, soil texture, plant lignin content, and Ninputs and that cool, moist, fine-textured soils have thegreatest SOC content. Burke et al. (1989) found thathigh SOC content was associated with high precipitation,high clay content, and low air temperature in grasslandsAbbreviations: SOC, soil organic C; NRI, National Resource Inventory;CDIC, Carbon Dioxide Information Center; NSSL-PD, pedon databasefrom the National Soil Survey Laboratory; MLRAs, major land resourceareas; GRID, Global Resource Information Database; SCS, Soil Conserva-tion Service; UN, United Nations; FAO, Food and Agriculture Organiza-tion; UNESCO, United Nations Educational, Scientific, and Cultural Orga-nization; CV, coefficient of variation; EROS, Earth Resources ObservationSatellite.

440 SOIL SCI. SOC. AM. J., VOL. 58, MARCH-APRIL 1994

of the U.S. Central Plains. In southern Great PlainsMollisols, clay content and, to a lesser degree, annualprecipitation were found to be factors of SOC accumula-tion (Nichols, 1984). In frigid and cryic soils of Montana,texture was not significantly correlated with SOC butcorrelation was found with elevation and precipitation(Sims and Nielsen, 1986). In a literature review, Oades(1988) concluded that water regimes and temperaturecontrolled the turnover of C in soil and the mineralizationof SOC was retarded by high clay content and basesaturation.

A study of the SOC in a northern hardwood forestecosystem (consisting predominantly of Spodosols) foundan average 16 kg C m~2 to a depth of 1 m or lessincluding O horizons (Huntington et al., 1988). The SOCof Spodosols in Florida was found to be somewhat lowerat 4.9 to 12.6 kg C m"2 to 1-m depth (Stone et al., 1993).Armentano and Menges (1986) summarized informationabout Histosol SOC content, which ranged from 113 kgC m~2 to 1-m depth for most of the contiguous USA to145 kg C m~2 for the southeastern USA.

One widely cited approach (Adams et al., 1990; Pren-tice and Fung, 1990; Jenkinson et al., 1991) for estimat-ing global SOC is the study by Post et al. (1982), whichused a large ( — 2700 pedons) database of SOC fromthroughout the world. The SOC data were grouped byHoldridge life zone (Holdridge, 1947) to derive meanSOC content from the surface to 1-m depth, and globalSOC was calculated by multiplying the SOC estimates

by the land area of the life zone groups. The SOC contentof wetlands was assumed to be 72.3 kg C m~2, and bogsor Histosols were not differentiated. A similar approachwas used by Schlesinger (1984) in which data for 117pedons were aggregated by ecosystem type. Buringh(1984) estimated SOC using areal estimates of soil ordersfrom the USDA-SCS and data from 400 pedons. Bohn(1976; 1982) used preliminary data from the UN FAO/UNESCO soil map of the world (FAO, 1974-1978) toestimate global SOC. Kimble et al. (1990) used the SCSNational Soil Survey Laboratory pedon database groupedby soil order and global areal estimates of orders tocalculate SOC globally for mineral soil. Eswaran et al.(1993) estimated global SOC by using the same pedondatabase as Kimble et al. (1990) with some additionsincluding Histosols, grouping the pedons by suborder,and using revised areal estimates of suborders.

METHODS AND MATERIALSEcosystem Complex Approach

The first approach closely follows the methods used byPost et al. (1982) except that ecosystem complexes (Olson etal., 1985), rather than Holdridge life zones (Holdridge, 1947),were used as a geographic base (Fig. 1, Table 1). This approachwas used because, as discussed above, the Post et al. (1982)study had been widely cited and used. The mean SOC perunit area was calculated for each ecosystem complex from apedon database assuming that each pedon equally representedthe ecosystem that it occurred in. The area and location of

S o u r c e s O l s o n e t a l . , 1985, USDA S o i l C o n s e r v a t i o nZ i n k e e t a l . , 1984 S e r v i c e

U N F o o d a n dA g r i c u l t u r e O r g a n .

G e o g r a p h i cP a t t e r n s

O l s o n E c o s y s t e m C o m p l e x e s llajor L a n d R e s o u r c e A r e a s S o i l M o p o f t h e War I d

M a p U n i tC o m p o s i t i o n

M a p C o m p o n e n tP r o p e r t i e s

O n e E c o s y s t e m p e rp o l y g o n

1 9 8 2 M o t i o n a l R e s o u r c e sI n v e n t o r y

A r e a e x t e n t o f c o m p o n e n t s

D e s c r i p t i v e L e g e n dA r e o I e x t e n t o f c o m p o n e n t s

r o c k f r o g m e n t ss o i l d e p t h

W o r l d i i d e S o i l O r g a n i cC and N D a t a b a s e

Z i n k e e t a l . , 19843700 p e d o n s u i e d w i t h :

s o i l C by * o I u m e

1982 S o i l I n t e r p r e t a t i o nR e c o r d D a t a b a s e

s o i l c l a s s i f i c a t i o ns o i l d e p t h

E x o m p I e P e d o nD e s c r i p t i o n s a n d D a t a2 5 5 p e d o n s u s e d w i t h :

s o i l Cb u l k d e n s i t y

S o i l S u r v e y L o b P e d o n D a t a b a s e2784 t o 3625 p e d o n s u s e d w i t h :

s o i l C b y w e i g h tb u l k d e n s i t y

Fig 1. Sources of input data for geographic databases of soil organic C.

KERN: SOIL ORGANIC CARBON SPATIAL PATTERNS 441

Table 1. Components of the soil organic C estimation approaches.Component Ecosystem approach Soil Taxonomy approach Soil map of the world approachSoil organic C

Digital map dataSpatial resolutionMinimum delineationMap unit composition

Rock fragmentsSoil depth

Bulk density

Pedon data, Zinke et al. (1984)4118 pedons global, 3700 usedEcosystem complexes, Olson et al. (1985)0.5° latitude/longitude= 360 x lO'ha1 ecosystem complex per unit

Included in calculations of pedonsIncluded in pedon calculations

Some measured, mostly estimated from ecosystem

Pedon data, SCS database2465 to 3625 pedons usedMajor Land Resource Areas, SCS (1981)1:7.5 million227 x 103 ha1982 National Resources Inventory

Texture modifier from NRISoil Interpretation Record for soil identi-

fied in NRIOnly measured data used

Pedon data255 pedons globalSoil map of the world1:5 million101 x 103 haIdentified dominant, associated

and inclusion soilsMap unit phaseMap unit phase

Some measured, mostly esti-mated from texture

each ecosystem complex was determined from a digital mapof ecosystem complexes. Global pedon data of SOC content(Zinke et al., 1984) were obtained from the CDIC. Thisdatabase contained information for 4118 pedons from a varietyof sources (2392 from North America), and the majority ofsamples were from the USA and central Eurasia. The datawere the basis of the Post et al. (1982) study with pedonsadded since that study. Many pedons are from work of thesenior compiler of the database, and the remainder come fromjournal articles, technical reports, theses, SCS Soil SurveyInvestigation Reports, and proceedings. Of the 4118 pedonswith SOC data, 3256 pedons (1990 from North America)had Holdridge classification and 3700 had Olson classification(2373 from North America). No information about soil classi-fication is included in the database. No quantification of dataquality is possible because of the wide variety of data sources.

The SOC determinations for the pedon database (Zinke etal., 1984) were made using a variety of methods includingwet combustion and loss on ignition, but the method for eachsample was not specified in the pedon database. Soil bulkdensity was measured using cores for 1800 of the 4118 pedons,and the remainder were estimated from regressions based ondepth, SOC content, and Olson ecosystem complex. The SOCcontent for each pedon was calculated by Zinke et al. (1984)on a volume basis to 1-m depth by multiplying mass SOC bybulk density and correcting for rock fragment content.

The geographic distribution of major world ecosystem com-plexes, as they existed in 1980 (Olson et al., 1985), wasobtained from the CDIC. The spatial resolution of the databaseis 0.5 by 0.5 ° latitude/longitude. The categories of ecosystemcomplexes in the spatial database were edited to agree withthe categories used in the pedon database. An advantage ofthe ecosystem complexes described by Olson et al. (1985) isthat, unlike the Holdridge system used by Post et al. (1982),it differentiates among bogs and other types of wetlands. TheHoldridge system (Holdridge, 1947) predicts plant formationsfrom climatic data and, thus, does not predict the extent ofwetlands, which is largely a function of landscape position.A map of the Olson ecosystem complexes of the contiguousUSA is presented in Fig. 2. The total SOC was calculated bysumming the mean of the pedon SOC content per unit areaaggregated by ecosystem complex times the area occupied.Water bodies were assigned zero SOC for all three approachesusing the perennial lakes, marshes, and reservoirs shown at1:2 million scale by the updated national atlas of the USA(U.S. Geological Survey, 1990).

Taxonomic Approach I: Soil TaxonomyThe Soil Taxonomy approach used the order, suborder, and

great group levels of classification (Soil Survey Staff, 1975)to aggregate pedon data. A national resource inventory was

used with a national land resources map to characterize thespatial distribution of soil taxonomic units (Fig. 1, Table 1).The SOC content of soil taxonomic units was calculated fromthe SCS pedon database from the NSSL-PD assuming thateach pedon equally represented the taxonomic unit. The SCSmaintains the NSSL-PD of soil samples analyzed at their labora-tories in Lincoln, NE, and Riverside, CA, as well as samplesanalyzed by the Agricultural Research Service (ARS) in Belts-ville, MD. Soil organic C was reported as percentage by weightdetermined by wet combustion with C^O?"2, and bulk densitywas determined using the clod method (Soil Survey Staff,1984). Data quality was enhanced by uniform methods amongthe laboratories and standardized sampling procedures, but noquantitative statement can be made about the data quality.

The database contained 15 789 pedons or sites sampled inthe contiguous USA at the time it was obtained, of which 6294pedons had SOC and measured bulk density data with eithergreat group classification or a series name that was not ataxadjunct. Of these 6294 pedons, 2258 listed the great groupclassification. The data for pedons lacking great group identifi-cation were merged by soil series with both the 1982 andcurrent SCS Soil Interpretation Record database to obtain theclassification (SCS, 1983). This data merge added great groupidentification for 3014 pedons or sites to yield a total of 5272pedons with potentially useful data.

Bulk density data were necessary to convert SOC measure-ments made on a weight basis to a volume basis. Only SCSdata with accompanying measured bulk density were usedbecause of the difficulty of estimating bulk density (Manriqueand Jones, 1991). Bulk density measured at 33 kPa moisturecontent was used because it more nearly represents field-moistconditions than that measured oven dry. In cases where oven-dry bulk density was available, but 33 kPa bulk density wasnot, the oven-dry bulk density was adjusted using the regressionequation based on NSSL-PD data:

p33 = (POD 0.880)+ 0.046(r2 = 0.89, n = 30 035 horizons)

where pas = bulk density at 33 kPa moisture, POD = bulkdensity oven dry.

The pedon dataset was analyzed by depth increments becauseit was recognized that many pedons were not sampled to 1-mdepth for each taxonomic unit. These depth increments wereadded together to construct an average SOC content to 1 m.The five depth intervals chosen were 0 to 8, 8 to 15, 15 to30, 30 to 70, and 70 to 100 cm. Soil organic C by volumewas calculated by multiplying SOC by weight, bulk density,and soil depth.

The data were grouped by soil order, soil suborder, and greatgroup for separate data analyses. There were not a sufficientnumber of samples to go to a more detailed category than


1=1 Bogs and bog foods^3 Fonts or gross/scrub, cool^a Forms or gross scrub, form

Forns, grass/scrub, woods, warnI I II Forns, gross/scrub, foods, coolnun Forest, torn coniferOn Forest, cool deciduous

k \l Forest, iorm brood-leaved %ZM Soid/scrub/herbs or bore desertt\\\] Forest/ form complex, cool m-i Savanna and woodland, tropicolix A Forest/ form complex, warm H+H Scrub/iood/sovonno. Mediterranean£3^3 Grassland, miscellaneous K^XI Scrubland, subdesert /desert , hotE^ grassland, cool Scrublond. subdesert/desert, coolV7A Harsh, siampioods, littoral ES3 Taiga, northern or moritime/subolpine^^ Paddylonds and foods lili Taiga, main

WS Thorn/succulent foods, tropicalITOH TundraHUH Woods, hordfoods-coniters, cool

\K3 Woodland or scrubland, sparse

Fig. 2. Ecosystem complexes for the contiguous USA.

great group. Grouping the pedons by soil order resulted in3541, 3682, 3452, 2822, and 2505 pedons being used forthe five depth increments, respectively. When pedons weregrouped by suborder, the usable number of pedons was 3541,3681, 3449, 2819, and 2504. The results of the great groupanalysis were screened manually to eliminate outliers and bringthe CV to 80 or below. The 80% CV level was chosen becausepreliminary data analyses showed only a small number ofextreme values exceeded this level. The number of samplesused for the increments in the final analysis by great groupwere 3478, 3625, 3401, 2784, and 2465. There were fewersamples in the first depth increment than the second incrementbecause of the difficulty of obtaining bulk density measurementsfrom horizons near the soil surface.

The SOC content by great group was then geographicallydistributed using MLRAs as a map base, which are areas withsimilar patterns of soils, climate, water resources, and landuse that was published at a map scale of 1:7.5 million (SCS,1981). The areal extent of great groups in each MLRA wasdetermined using the 1982 NRI and the total area of eachMLRA. The MLRA map and 1982 NRI are known collectivelyas the National Soil Geographic Database (Reybold and TeS-

elle, 1989; Bliss, 1990). The dominant subgroups determinedfrom the 1982 NRI and the MLRA map are shown in Fig. 3.

The 1982 NRI is the most extensive inventory made in theUSA of soil, water, and related resources of nonfederallyowned land. The SCS coordinated data collection from 352 786primary sampling units, with three or less sampling pointseach, for the 1982 NRI. The data collected included soilcharacteristics, soil interpretations, land cover, land use, ero-sion, land management, conservation needs, and potential forconversion to farmland. There was a total of 841 860 samplingpoints in all counties of the USA (except for Alaska) and U.S.possessions in the Caribbean. Sites were selected to representthe MLRAs with a confidence limit of plus or minus onestandard deviation for attributes that comprise 10% of theMLRA (SCS, 1987). Thus, if corn (Zea mays L.) is producedon 10% of the area of a MLRA, then the theoretical confidencelimit is plus or minus one standard deviation. The analysesfor this study had a higher confidence limit because every(nonwater and nonurban) point of the database has soil as anattribute. The 1982 NRI is of limited use for characterizingwetlands because it does not contain information for millionsof acres that the NRI classified as water, but that might be


E3 A q u a l f s B X e r p l f sS Boro l f s HD Arg idsSUdolfs nmOrthidsSUsta l fs ^Fluvents

Or then tsPsammentsHemlstsSapr i s t s

A q u e p t sOchrep tsUmbreptsAquol ls

Bo ro l l sUdollsUsto l lsXero l l s

AquodsOrthodsAquu l t sUdul ts

U s t e r t s

Fig. 3. Dominant soils from Soil. Taxonomy approach.

wetlands (Goebel and Dorsh, 1986). Each NRI point that isnot water or urban land has data for the surface texture andcoarse fragment content. In these analyses, the nonfederal landwithin the MLRAs is assumed to represent the federal landas well. The expansion factor for each point indicates the areathat the point represents.

Every point in the NRI has a number that links it to theSoil Interpretation Record that includes taxonomic informationand estimated soil properties based on the expert judgment ofpersonnel involved in soil survey work. Organic matter con-tents from the Soil Interpretation Record are of limited usefor estimating SOC because they are estimates that may notbe based on laboratory data, they are expressed as a range,and only organic matter data for surface horizons were re-corded. The soil properties for this project obtained fromthe Soil Interpretation Record are depth to bedrock and thetaxonomic classification. A special version of the Soil Interpre-tation Record from 1982 has been developed by the SCS foruse with the 1982 NRI data.

Some classes in soil taxonomy have changed since 1982,and the 1982 version of soil taxonomy is used in this studyfor the NRI points. For example, many soils that formerlywere in the Andept suborder of Inceptisols are now consideredAndisols. There have also been changes in the Oxisol classifi-

cations, because currently the suborder Orthox is not definedand previously there were no Udox (Soil Survey Staff, 1975,1990).

Great groups identified in the 1982 NRI that were notrepresented in the NSSL-PD were assigned the SOC contentof similar great groups with data. Miscellaneous land areas,considered nonsoil, were identified in the 1982 NRI. Miscella-neous land areas that were assigned SOC contents of 0.2 kgC m~2 to the 1-m depth were alluvial land, badlands, gulliedland, gypsum land, lava flows, playas, rubble land, salt flats,and scoria. The remaining miscellaneous areas were assigneda SOC value of 0.

An approximation of minimum and maximum SOC wascalculated by adding or subtracting one-half of the incrementSOC standard deviation from the mean SOC before geographi-cal distribution. The reasoning was that estimates based onthe 1982 NRI have a theoretical confidence limit of plus orminus one standard deviation, thus estimates based on the typeof soil that has a very large sample size should have a somewhatmore narrow confidence limit. The standard deviation of theSOC content for each combination of great group and incrementcould not be calculated because in some cases there was onlyone sample. The average CV (standard deviation/mean X 100)for each increment was also calculated by soil order. All


A c r i s o l s E3 FluvisoisAndoso ls EEB GleysolsCombisols CD GreyzemsChernozems M Histosols

K a s t o n o z e m sLi thosolsLuvisolsPhaeozems

Planoso lsPodzo lsPodzo luv iso lsRegoso ls

So lone tzVer t i so lsX e r o s o l sY e r m o s o l s

Fig. 4. Dominant soils from the soil map of the world.

increments with missing standard deviations were then calcu-lated as the CV for that order multiplied by the SOC for theincrement, then divided by 100.

The SOC content for each depth increment by MLRA wascalculated by using the SOC content for that layer and addingor subtracting one-half of the standard deviation of the SOCto derive a minimum and maximum content. Water bodieswere assigned zero SOC using the perennial lakes, marshes,and reservoirs shown at 1:2 million scale by the updatednational atlas of the USA (U.S. Geological Survey, 1990).The SOC for each MLRA was calculated by

E SOCiayer x expansion factorE expansion factor

Taxonomic Approach II: Soil Map of the World

[2]

The FAO/UNESCO soil map of the world was chosen asa geographic layer because consistent data about the spatialdistribution was needed, not only for the USA but also globally.The soil map of the world is currently the most comprehensiveglobal-scale soil map available (Sombroek, 1989). The soilmap of the world was based on soil information available in

the 1960s to 1970s and is primarily a compilation of availablenational soil maps with additional field work by FAO staff.The soil map of the world, published at a scale of 1:5 million,was compiled from approximately 600 soil maps of differentscales and legends with 11000 other maps such as physiogra-phy, vegetation, climate, geology, and land use system, whichconstituted a system for correlating various taxonomic systems(FAO, 1974-1978). The texts that accompany the map sheetscontain information about map unit composition and generalproperties of the soil units.

The example pedons with laboratory data that accompanyall volumes of the soil map of the world (255 pedons) wereused to make SOC calculations grouped by soil unit (Fig. 1,Table 1). These pedons were presented as typical profiles, butit was cautioned that "one profile will not show the range ofsoil characteristics and climatic conditions within such broadunits" (FAO, 1974-1978). Thus, it was assumed that thesepedons represented broad modal soil characteristics. Missingmineral bulk density values were estimated, based on texture,from guidelines from the SCS (SCS, 1983). Organic horizonbulk density was assumed to be 0.15, which was derived byanalyzing NSSL-PD data for horizons of Histosols with >30%SOC by weight (75 measurements). The pedons were assumed


Table 2. Soil organic C content of ecosystem complexes that occur in North America.Soil organic C

Ecosystem complex

Bogs and bog woodsCool farms or grass/scrubFarm, grass, or scrub with woods, warmFarms, grass/scrub with woods, coolForest, tropical/sub broad-leaved humidForest, warm coniferForest, cool deciduousForest, cool coniferForest, warm broad-leavedForest/farm complex, coolForest/farm complex, warmGrassland, miscellaneousGrassland, coolHeath, moorlandMarsh, swampwoods, and littoralPaddylands and associated woodsRangelands, coldSand/scrub/herbs or bare desertSavanna and woodland, tropicalScrub, lowScrub/wood/savanna, MediterraneanScrubland, hot subdesert/desertScrubland, cool/cold semidesert/desertTaiga, midcontinental southernTaiga, northern or maritime/subalpineTaiga, mainThorn/succulent woods, tropicalTundra, woodedTundra, non-woodedWarm farms or grass/scrubWoodland, seasonally dry tropicalWoodland or scrubland, sparseWoodlands, warm semiaridWoods, warm broad-leaved conifer mixWoods, cool hardwoods-conifers mixed

Mean

113.210.410.713.310.713.615.015.815.95.98.48.7

12.414.923.414.624.73.16.03.77.52.56.2

12.312.917.02.1

16.618.19.6

11.27.8

10.210.312.9

Min.

—— kg C m-2 1-m depth"1 ——50.42.41.60.10.80.32.20.41.95.73.81.40.65.85.33.86.00.50.41.20.60.31.10.41.42.91.02.40.91.62.32.88.91.22.9

Max.

183.624.034.146.297.545.161.5

349.4101.8

6.011.537.492.345.8

124.046.033.310.331.27.7

50.05.8

10.3142.534.770.45.4

66.260.645.224.627.111.547.540.0

cvt%43607666935783

132119

448777076

136925085764888737598

11180888989954850138576

ntno.

4114253

3873471098038723

936531113112

156914

259155

1796

635

20416322633

7657

t Coefficient of variation.$ Number of samples.

to be free of coarse fragments and extend to 100-cm depthunless they were Lithosols or indicated by the phase correction.The method of SOC analysis is the Walkley-Black method(FAO, 1974-1978). Soil units with missing SOC were assignedSOC from similar soil units in 52 cases. Lithosols were assigneddepths of 10 cm, soil with bedrock within 100-cm depth wereassigned 85 cm, and stony soils were assumed to contain 40%rock.

The soil geography of the soil map of the world for theUSA (Fig. 4) was based on the SCS general soil map (FAO,1974-1978) at 1:7.5 million map scale that was apparentlyalso a source of soil data for the MLRA map (SCS, 1981).The soil map of the world at 1:5 million map scale has greaterdetail than the MLRA map and also has soil phases indicatedas map overprints. The map has been digitized and is availablefrom the Global Resource Information Database program ofthe United Nations Environment Programme. The digital soilmap of the world data used in this study were obtained fromthe EROS Data Center of the U.S. Geological Survey. Thelegend of the soil map of the world has >5000 map units,which consist of soil units or associations of soil units. Somemap units are composed of 100% of the dominant soil; how-ever, more commonly at this scale of mapping, there areassociated soils and inclusions. Associated soils cover at least20% of the map unit area, and inclusions cover <20%. Phasesof map units were used to indicate indurated layers, hardbedrock at shallow depth, stoniness, salinity, or alkalinity(FAO, 1974-1978). The FAO estimated the composition ofeach map unit using the methodology developed in the Agroeco-

logical Zones Project (FAO, 1978). Water bodies were as-signed zero SOC using the perennial lakes, marshes, andreservoirs shown at 1:2 million scale by the updated nationalatlas of the USA (U.S. Geological Survey, 1990).

RESULTS AND DISCUSSIONSoil Organic Carbon by Ecosystem Complexes

The results of the average SOC content of the ecosys-tem complexes that occur in North America are listedin Table 2, and the spatial distribution for the contiguousUSA is shown in Fig. 5. One sample for bogs had 349.4kg C m~2, which is much higher than any pedon, andwas removed from the database. Bogs and bog woodshad the greatest SOC content at 113.2 kg C m~2 andtropical thorn-succulent woods had the least at 2.1 kgC m"2. Forests, ranging from 10.9 to 15.9 kg C irr2,tended to have greater SOC than grasslands, with 8.4to 12.4 kg C nr2. The variability of the SOC contentwithin the ecosystem complexes, as indicated by theCV was large (Table 2). Marshes, swamps, and littoralregions had the greatest variability (136% CV) with arange of 5.3 to 124.0 kg C m~2. Cool conifer forestshad a range of 0.4 to 349.4 kg C m~2. The total SOCfor the contiguous USA based on this approach was 78.0Pg. The CV of many ecosystem complexes was >80,and some CV values were MOO, which indicates that


N

ki lometersI

0 900Albers coiic-tquol or«o

E3 0.1 to 4.0 Cm 4.1 to 8.0 EE3 8.1 to 12.0 Em 12.1 to 16.0 E

kg C3 16.1 to 20.0 m% 20.1 to 24.0 m3 24.1 to 28.0 m0 28.1 to 32.0 •

m ~ 2

1 32.1 to 36.0 11 36.1 to 40.0 i

40.1 to 44.0 I1 44.1 to 48.0

1 48.1 to 52.0i 52.1 to 56.0^ 56.1 to 113.2

Fig. 5. Soil organic C using ecosystem complexes to 1-m depth.

there are broad ranges of types of soil within the com-plexes. The minimum and maximum values were quitedifferent, in most cases, which suggests that ecosystemcomplexes are poor predictors of the amount of SOCcontent because of the great soil heterogeneity.

Soil Organic Carbon by Soil Taxonomy

The results for total SOC content and SOC densityfor depth intervals by soil order are listed in Table 3.Aridisols were the soil order with the lowest SOC, with

Table 3. Soil organic C (SOC) content by soil order.

Order

AlflsolsAridisolsEntisolsHistosolsInceptisolsMoUisolsOxisolsSpodosolsUltisolsVertisols

Totalsoct

kgm-2

7.05.66.9

84.311.712.111.516.77.0

10.3

0-8 cm

pihgm-2

2.11.271.68

10.873.092.752.673.852.151.99

CV§

%55686341565038416946

nlno.806385329

18404

10561867

36494

8-15 cm

Phgm-2

1.710.961.40

10.462.582.472.433.411.901.67

CV

%53565542655038476843

nno.78842433621

4341057

1992

402109

15-30 cm

Phg m"2

0.970.720.939.931.791.761.662.651.051.24

CV

%62566639715446517946

nno.68842830620

4439552089

387116

30-70 cm

Phgm"2

0.460.470.527.850.840.970.851.430.430.95

CV

%53628228986049787646

nno.60926324817

3597812161

36796

70-100 cm

Phgm-2

0.290.340.407.340.490.550.610.510.260.65

CV%58628535

1046359967753

nno.568199228

132916822169

34688

11-m depth.I Soil organic C density to 1-cm thickness.§ Coefficient of variation.1 Number of samples.

KERN: SOE, ORGANIC CARBON SPATIAL PATTERNS 447

5.6 kg C m~2 to the 1-m depth, and the greatest wereHistosols with 84.3 kg C nT2. The ranking of the SOCcontent of the soil orders was Aridisols < Entisols ~Ultisols = Alfisols < Vertisols < Oxisols < Inceptisols <Mollisols < Spodosols « Histosols. Histosols containednearly six times the SOC of Spodosols, which is thenext lowest order. Greater SOC density heterogeneitywas observed below 30-cm depth for most soils, asevidenced by higher CVs, and is due, in part, to smallersample sizes. Soil organic C content decreased withdepth for all soil orders.

Table 4 lists the SOC results for the suborders repre-sented in the database. Alfisol suborders had the SOCcontent trend of Udalfs « Ustalfs < Xeralfs < Aqualfs< Boralfs. The Argid and Orthid suborders of Aridisolshad nearly equal SOC content. The suborders of Entisolshad considerable variation, with a low of 4.9 kg C m~2

for the sandy Psamments and 10.5 kg C m~2 for wetAquents. Arents had consistently high SOC densitythroughout the profile, resulting in high total SOC content(but there was only one pedon represented). Sapristswere the only suborder of Histosols represented in the

data, with SOC of 86.9 kg C nr2. The Inceptisol subor-ders showed the trend Ochrepts < Tropepts < Aquepts~ Andepts. Aquepts and Andepts had a great deal ofvariability in SOC density for the lower horizons. Allsuborders of Mollisols had SOC content >10 kg C m~2

with the trend Ustolls < Xerolls < Borolls < Albolls <Udolls < Aquolls. Oxisols were not well representedin the database because they are not extensive in thecontiguous USA. Oxisols were not identified in the 1982NRI for the contiguous USA but are included here forcomparison. The trend for Oxisol suborders were Or-thoxs < Torroxs < Ustoxs < Udoxs. Spodosol subordersdisplayed a different trend than many others because theaquic suborder had less SOC than the orthic. The Aquodshad relatively high SOC density in the upper solum, butthe amount decreased more sharply with depth than inthe Orthods. The majority of the Ultisol samples wereUdults, which had considerably lower SOC content thanthe other suborders. The trend for Ultisol suborders wasUdults < Aquults < Ustults « Xerults < Humults. Thetrend for Vertisol suborders was Xererts < Uderts <Torrerts < Usterts.

Table 4. Soil organic C (SOC) content by soil suborder.

Suborder

AqualfsBoralfsUdalfsUstalfsXeralfsArgidsOrthidsAquentsArentsFluventsOrthentsPsammentsSapristsAndeptsAqueptsOchreptsTropeptsUmbreptsAlbollsAquollsBorollsUdollsUstollsXerollsOrthoxsTorroxsUdoxsUstoxsAquodsOrthodsAquultsHumultsUdultsUstultsXerultsTorrertsUdertsUstertsXererts

Totalsoct

kgm-2

7.98.26.36.57.35.55.9

10.514.47.46.14.9

86.918.513.59.0

13.318.613.715.713.414110.010.58.8

10.612.911.510.917.210.412.66.1

11.211.410.09.3

11.98.5

0-8 cm

Pthgm-2

2.172.891.971.362.371.21.362.231.891.461.71.65

10.873.573.692.573.454.573.443.593.272.842.082.622.221.852.892.864.123.823.313.611.832.664.592.262.352.001.55

CV§

%4945507056627346

NA#51686941634852434155464432465874

NA34213542604862544724324566

nlno.16676

34485

135230155371

9914151184849

244184516

123185198301231

41767

603025

29559

12213724

8-15 cm

Phgnr2

2.051.991.661.141.610.901.042.022.151.391.321.17

10.453.103.262.082.724.283.363.492.802.781.872.101.241.852.782.593.103.443.053.451.602.393.051.651.731.811.39

CV

%4754475756555646NA50574843785954484158474433425282

NA31214247804056464130333961

n

no.16285

32489

128249175381

9715347205254

269184115

125197192288239

31969

833328

32669

15224428

15-30 cm

Phgm-2

1.181.190.860.801.010.710.741.491.650.950.850.68

10.212.512.021.391.973.152.142.661.922.181.421.451.281.852.031.421.142.741.481.880.931.691.501.281.021.451.04

CV

%5955595166536063

NA66555539757353694735525235415638

NA40558548

1354760584828514157

nno.11876

27995

120256172341

10112446185658

27318381498

203119288232

41875

832923

32168

19214729

30-70 cm

Phgnr2

0.520.480.390.570.470.460.500.831.320.580.430.338.091.620.920.591.031.320.941.171.061.200.860.820.740.950.970.780.801.510.560.820.360.960.640.920.781.110.82

CV

%4754515252616399

NA6355552580

12458

1146222557146436717

NA39667575

1315450532835594045

nno.10570

24877

10916697311

819441164250

22115311281

164105239180

317

106

532726

30158

13204221

70-100 cm

Phgm-2

0.330.290.250.380.300.340.320.601.230.500.300.157.771.080.550.350.540.670.550.600.590.620.510.520.450.430.570.720.190.540.400.420.220.350.270.500.540.830.51

CV

%4653595366655683

NA7159612781

12468

1057050607057547055

NA35676093994665404932644064

nno.11068

2297388

12178301

878129123040

18312261272

129100217151

41796

633022

28077

14193718

11-m depth.t Soil organic C density to 1-cm thickness.§ Coefficient of variation.5 Number of samples.it Not applicable.

448 SOIL SCI. SOC. AM. J.( VOL. 58, MARCH-APRIL 1994

Table 5. Soil organic C (SOC) content of selected great groups.

Great group

OchraqualfsNatraqualfsEutroborallsHapludalfeNstrudfllfsHaplustalfsHaploxeralfsNatrixeralfsDurixeralfs

HaplargidsCamborthidsDurorthidsGypsiorthidsPaleorthids

HydraquentsHaplaquentsCryaquentsFluvaquentsXerofluventsUstifluventsUdifluventsCryofluventsTorrifluventsUdorthentsXerorthentsCryorthentsUstorthentsTorriorthentsCryopsammentsXeropsammentsUdipsammentsUstipsammentsTorripsamments

BorosapristsMedisaprists

Totalsoct

kgm-2

8.55.88.76.96.06.57.87.14.4

5.26.55.24.43.2

28.89.99.89.19.18.78.26.96.38.06.96.65.75.66.45.45.34.32.8

97.280.1

0-8 cm

Pihgm"2

2.371.693.142.081.451.342.582.291.30

1.171.641.000.821.04

2.171.74.052.211.951.571.541.931.232.411.983.321.471.272.591.322.021.171.13

10.7510.91

CV§

%

453242491771524863

6376526768

NA57

NA46495143NA5536306446626454615546

3344

"1no.

1061437

2282

49848

15

12251165

19

121

33129

321

45201013217610118

145

414

8-15 cm

phgm'2

2.201.522.031.791.421.211.791.410.89

0.891.080.790.811.16

2.171.632.352.031.681.341.591.521.182.151.461.271.291.091.211.061.451.060.49

9.4310.89

CV

%

423461452058502834

5455576158

NA53

NA48535740NA5137473755593243505123

4144

n

no.Alfisols

1051137

2162

57788

15Aridisols

14160161017

Entisols121

34139

291

45231013258299

10133

Histosols6

14

15-30 cm

Phgm"2

1.280.711.180.970.610.841.090.920.61

0.720.780.620.710.63

3.541.241.621.361.140.931.120.680.831.341.050.780.740.790.930.930.870.620.30

10.939.85

CV

%

55456053

NA#52673941

5556506089

3654

NA59546254NA7628394145632637436027

3841

n

no.

711034

1841

56748

16

14356151119

221

291210261

52128

122072

569

148

612

30-70 cm

Phgm"2

0.550.420.500.430.410.550.500.500.40

0.420.540.470.380.40

3.500.950.640.630.760.790.620.680.500.490.470.270.380.460.370.420.260.350.19

9.237.40

CV

%

46394947NA59524356

58536644NA

3842NA55498153NA6428644349565048206341

2125

n

no.

659

33165

14271

513

8336960

221

26116

17NA47779

1556886

105

610

70-100 cm

Phgm"2

0.350.240.340.290.450.370.290.320.10

0.290.360.360.210.23

2.090.600.600.480.570.670.561.100.420.230.290.270.350.290.210.190.120.110.14

9.596.48

CV

%

44535055NA57666328

555247399

2863NA56718378NA5947405856628350722952

1820

n

no.

668

35142

1415758

6732572

220

26126

211

478S3

145144684

57

InceptisolsDystrandeptsHydrandeptsEutrandeptsCryandeptsVitrandeptsAndaqueptsHalaqueptsHumitropeptsHaplumbreptsXerumbreptsFragiumbreptsCryumbrepts

ArgialbollsNatralbollsCalciaquollsHaplaquollsArgiaquollsNatraquollsHaploborollsArgiborollsCalciborollsNatriborollsHapludollsArgiudollsNatrustollsCalciustollsHaplustollsArgiustollsHaploxerollsArgixerollsNatrixerolls

27.727.618.013.28.7

32.56.2

34.920.118.813.411.0

14.09.2

20.415.514.78.3

12.711.510.99.9

14.613.812.210.610.39.7

10.610.46.9

4.735.725.242.712.364.002.544.984.575.213.683.67

3.532.134.663.453.373.493.033.002.232.912.822.853.092.062.102.012.602.692.27

52446447527978183652

537

54NA3948396853401938362934564545595940

1732

1114624

281025

151

1774273

424687

741221231

10513489986

5.025.595.102.341.414.151.014.594.314.793.683.40

3.461.914.583.383.362.212.642.452.342.822.782.782.531.971.871.832.052.142.14

54426245536663243652

545

57NA3749395947452852363036494439564943

1632

1218643

25925

Mollisols141

1776274

465596

74117

93194

13691996

3.824.503.632.011.163.560.674.013.512.762.552.34

2.201.373.172.702.431.23.72.59.76.29.17.21.91.58.42.38

1.471.390.59

552652545360813134716

79

34NA4352494753412653383333394538594958

1932

1318644

23825

131

1757194

545996

51676

3590

13091933

2.452.310.8010.732.920.373.741.491.320.890.52

0.960.701.761.141.070.351.020.890.860.671.241.180.970.950.880.840.830.810.51

576

NA777690593060484468

21NA455439456851

'4759553346395238627663

18318

11342

19723

111

1150163

4047106

51537

2573

1118060

5

1.641.050.540.810.413.160.342.240.740.640.190.05

0.560.430.590.620.600.250.590.500.490.350.730.540.430.480.570.460.550.490.24

5932

NA7074NA35

NA6653NANA

51NA8460362272665256624535396447696481

133158121

20411

1117

49132

333874

39596

1973

10168514


Table 5. (cont.)

Great group

HaplorthoxsAcrorthoxsTorroxsHapludoxsKandiudoxsAcrudoxsEutrustoxs

HaplaquodsCryorthodsHaplorthodsFragiorthods

UmbraquultsPalehumultsHaplohumultsTropohumultsPaleudultsKandhapludultsKandiudultsHaplustultsHaploxerults

TorrertsChromudertsPelludertsPellustertsChromustertsPelloxerertsChromoxererts

Totalsoct

kgm-2

10.08.4

10.614.112.010.211.5

7.922.615.515.3

34.014.812.311.45.54.94.3

11.211.4

10.010.39.0

12.311.711.56.8

0-8 cm

Pthg m~2

3.152.121.852.713.183.022.86

3.523.903.982.44

8.523.843.435.841.621.681.232.664.59

2.262.192.392.081.961.831.39

CV§

%

58NANA4626NA21

31562969

453253

NA5156485447

24223234514482

nlno.

2114216

319365

25

191

78323159

n6

1312259

15

8-15 cm

Phgm"2

1.722.001.852.912.523.022.59

2.733.783.302.58

9.543.153.591.931.421.361.162.393.05

1.652.131.471.861.791.801.16

CV

%

50NANA404

NA21

51524329

343041NA5647424641

30232640403775

nno.

Oxisols2015216

Spodosols6

29513

Ultisols35

221

80332969

Vertisols157

1314301018

15-30 cm

Phg m"2

1.081.901.852.331.831.621.42

0.543.102.543.19

6.162.291.761.990.860.690.661.691.50

1.281.171.001.491.431.460.84

CV

%

31NANA487

NA55

19623427

625246NA5848475848

28336049362667

n

no.

3114217

228532

35

171

79312668

197

1217309

20

30-70 cm

Phg m~2

0.740.730.951.100.920.550.78

0.462.381.241.46

2.021.210.800.280.330.300.270.960.64

0.920.870.761.141.091.100.65

CV

%

25NANA4112

NA66

59647426

836140954753485328

35317040402251

nno.

211421

10

312374

34

202

73252758

136

1315278

13

70-100 cm

Phgm"2

0.580.320.430.690.440.350.72

0.190.900.450.34

1.080.430.410.460.230.130.160.350.27

0.500.630.520.860.800.750.36

CV

%

4766

NA2512

NA67

56857853

874449NA5455644049

32367535434362

nno.

2214219

315426

32

191

70212877

145

1314237

1111-m depth.$ Soil organic C density to 1-cm thickness.§ Coefficient of variation.1 Number of samples (0 for estimated values).# Not applicable.

The SOC for selected great groups arranged by soilorder is shown in Table 5. In a few cases, the depthincrement SOC density was estimated based on the valuesof surrounding increments, hi which case zero was en-tered for a number of samples. When the most centraltype of each Alfisol suborder was chosen, the trend wasHaploxeralfs < Haplustalfs < Hapludalfs < Ochraqualfs< Eutroboralfs. Alfisol great groups with indications ofan arid environment, such as Natraqualfs, Natrudalfs,Natrixeralfs, and Durixeralfs, had relatively low totalSOC content. The range of total SOC content for mostAridisol great groups (Table 5) was 5.2 (Durorthids andHaplargids) to 6.5 kg C m~2 (Camborthids). Paleorthidand Gypsiorthid SOC contents were particularly low, at3.2 and 4.4 kg C nr2.

The SOC content of Entisols is listed hi Table 5.Hydraquents, clayey soils of tidal marshes (Soil SurveyStaff, 1975), had the greatest SOC of all the Entisolgreat groups. The other aquic Entisols (Haplaquents,Cryaquents, and Fluvaquents) had moderately high SOCcontent. The arid Entisol great groups (Torrifluvents,Torriorthents, and Torripsamments) had lower SOC con-tent than did great groups with the same suborders. Thecold great groups, Cryofluvents and Cryorthents, hadsomewhat low SOC content, but the SOC was relatively

high for the cold, coarse-textured Cryopsamments. Greatgroups with xeric moisture regimes (Xerofluvents, Xer-orthents, and Xeropsamments) had moderately high SOCcontents. Great groups with ustic moisture regimes (Ust-orthents and Ustipsamments) had relatively low SOCexcept for the alluvial Ustifluvents. Udorthents, withudic moisture regimes had high SOC content, whereasother udic great groups (Udifluvents and Udipsamments)had moderate SOC compared with the same suborders.

There were only 18 samples to characterize Histosolgreat groups (Table 5), and they were all in the samesuborder. Borosaprists had lower SOC content than Med-isaprists, although they had similar SOC densities hi theupper 30 cm. Inceptisols showed a wide variation inSOC content by great group (Table 5). Inceptisol greatgroups influenced by volcanic parent material (Dystran-depts, Hydrandepts, Eutrandepts, and Cryandepts) hadhigh SOC content, except for the coarse-textured Vitran-depts. Andaquepts, which have both andic and hydricproperties, had particularly high SOC content. The salt-affected Halaquepts had the lowest SOC content of theaquic great groups. Of the Tropepts, the tropical Incepti-sols, only the Humitropepts great group had exceptionallyhigh SOC content. Great groups with umbric epipedons,which by definition have organic matter accumulations,


had high SOC content (Haplumbrepts and Xerumbrepts)except for soils with fragipans and cryic temperatures(Fragiumbrepts and Cryumbrepts).

The haplic great groups of Mollisols (Table 5) showedthe following trend: Haplustolls « Haploxerolls <Haploborolls < Hapludolls < Haplaquolls. Mollisol greatgroups with argillic horizon development had the follow-ing trend: Argiustolls < Argixerolls < Argiborolls <Argiudolls « Argialbolls < Argiaquolls. Sodium-affected Mollisols ranked Natrixerolls < Natraquolls <Natrialbolls < Natriborolls < Natrustolls. The trend forcalcareous Mollisols was Calciustolls < Calciborolls <Calciaquolls < Calcixerolls.

The SOC contents of the Oxisol great group are pre-sented in Table 5. The greatest SOC content was forHapludoxs, but the lowest SOC content was for Haplor-thox, which has nearly the same definition in the olderversion of Soil Taxonomy. The SOC trend for the Oxisolswas Acrorthoxs < Haplorthoxs < Acrudoxs < Torroxs< Eutrustoxs < Kandiudoxs < Hapludoxs.

The Spodosol great groups (Table 5) all had relativelyhigh SOC content with the exception of the Haplaquods.The Cryorthods had considerably greater SOC than didthe other great groups. The Spodosols, in general, didnot have a marked decrease in SOC density hi the 30-to 70-cm increment, as was seen in many other greatgroups, apparently because of illuviation of organicmatter.

The great groups of Ultisols had quite a bit of variationin SOC content (Table 5). The poorly drained Um-braquults, which by definition have organic matter accu-mulations, had nearly three times the SOC content ofother great groups. The heavily weathered great groups(Paleudults, Kandhaphludults, and Kandiudults) all hadlow SOC contents of 5.5 kg C m~2 or less. The greatgroups that are defined by high SOC accumulationsshowed the trend Palehumults > Haplohumults > Tropo-humults. Haplustults and Haploxerults had nearly thesame SOC content as the humult great groups.

The SOC of the great groups of Vertisols is listed inTable 5. Chromusterts and Pellusterts, with ustic mois-ture regimes, had the highest SOC content. The Torrertsfrom arid climates, as well as the Chromuderts andPelluderts from humid regions, had similar SOC content.For the Xererts, Pelloxererts had nearly as much SOCcontent as Usterts but the Chromoxererts had half.

The CV of the SOC density estimates by soil order wasanalyzed to assign theoretical SOC standard deviations toincrements with only one sample. The CVs tended tobe <50 with an average of 45, 42, 46, 46, and 51 fordepth intervals of 0 to 8, 8 to 15, 15 to 30, 30 to 70,and 70 to 100 cm, respectively.

There was too much variation hi the kinds of soilsgrouped into soil orders, with the possible exception ofHistosols, to make them very useful for predicting SOCcontent. Grouping data by suborders provided a betterestimate than by orders because suborders give moreindications of climate, drainage, and coarse textures,which are important factors for SOC accumulation. Soilorganic C by great group provided even more detailabout soil-forming factors that affect SOC accumulation.

Great group classification provided only a limited indica-tion of soil texture (very sandy and some very clayeysoils) and temperature, which is included in family levelclassification. There was an insufficient number of pedonsto do these analyses at a family level of classification.

The tendency for soils from arid climates to have lowSOC content (<6 kg C m~2) is illustrated by the resultsfor great groups such as Torripsamments, Gypsiorthids,Haplargids, Naturargids, Torriorthents, and Paleargids.Coarse-textured soils had low SOC as shown by theTorrispamments, Ustipsamments, Quartzipsamments,Xeropsamments, and Udipsamments. Some highlyweathered soils have low SOC contents, such as thekandic great groups with their low-activity clays.

The influence of the soil moisture regimes varied fromorder to order. The general tendency for wet (aquic)and cold (boric and cryic) groupings to have greaterSOC was fairly consistent. Aquods, an exception, didnot have high amounts of SOC in their subsoils, whichmay be a function of the impedance to illuviation ofhumus by the poor drainage. Within similar great groups,udic groups tended to be greater than xeric and usticbut the relation of these two groups varied. In haplicAlfisols, xeric was less than ustic, but ustic was lessthan xeric hi haplic, argic, and calcic great groups ofMollisols. Great groups with the formative elementsumbr, hum, and umb tend to have higher SOC than othersimilar great groups. Soils with volcanic material tendto have high SOC content.

The Histosols stand out because they are, by definition,composed almost entirely of organic material. There arenot enough data for Histosol great groups to indicatewith certainty if Borosaprists consistently have moreSOC than Medisaprists.

Spatially distributing the great group SOC for thecontiguous USA results in a mean of 80.7 Pg of C; thespatial patterns are shown hi Fig. 6. The maximumSOC, as calculated by adding one-half of the standarddeviations of the increment SOC densities, is 99.3 Pg,and the minimum, by subtracting one-half of the SOCstandard deviations, resulted hi 62.1 Pg of C. The spatialpatterns of SOC as characterized by the Soil Taxonomyapproach (Fig. 6) showed the greatest SOC content hiareas of extensive Histosols and poorly drained soilssuch as in the northern Midwest, coastal Southeast andLouisiana, and southern Florida. The northcentral Mid-west, with its extensive Mollisols, had relatively highSOC content. The northern Northeast had high SOCcontent because of the extensive distribution of Spodo-sols. The western Pacific Northwest also had relativelyhigh amounts of SOC, probably because of high amountsof precipitation and cool temperatures.

Soil Organic Carbon from the Soil Map of the WorldThe SOC content of the soil units from the soil map

of the world are presented hi Table 6. The groupingswith the lowest amount of SOC were the arid Xerosolsand Yermosols. The Yermosols, which are the most aridgrouping, were extremely low hi SOC content, but therewas only one representative pedon of each. The Histo-


kilometer!

0 900Alters coiic-iquol or««

E3 0.1 to 6.0E2 6.1 to 7.5ES! 7.6 to 9.0m 9.1 to 10.5

kgM 10.6 to 12.0^ 12.1 to 13.5EJ 13.6 to 15.0S3 15.1 to 16.5

C m" 2

ra 16.6 to 18.0 Wm 18.1 to 19.5 i• 19.6 to 21.0 IHDD 21.1 to 22.5

M 22.5 to 25.01 25.1 to 35.0I 35.1 to 57.6

Fig. 6. Soil organic C using Soil Taxonomy to 1-m depth.

sols, with up to 99.2 kg C m~2, had considerably moreSOC than any other grouping.

All groupings showed considerable variation, but gen-erally the tendency was for higher values for Humic,Gelic, and Gleyic soils. Acrisols tended to have lowSOC content. The Andosols, with the exception of Vitric,had high SOC content. The coarse-textured Arenosolsall tended to have low SOC content. The soils withdark surface horizons (Chernozems, Kastanozems, andPhaoezems) tended to have high SOC content. The poorlydrained Gleysols had moderate to high SOC content.Spatial application of the soil unit SOC contents resultedin 84.5 Pg of C for the contiguous USA (Fig. 7).

The soil units with the lowest SOC content were thearid Yermosols, which were much less than comparableAridisol great groups. The sandy Arenosols had lowSOC content, which is comparable to similar psammentgreat groups. Soil units from dry climates (Xerosols,Solonchaks, and Solonetz) tended to have low SOC con-tent except for soil units with mollic prefixes. ChromicVertisols had low SOC content, which is similar to the

great group Chromoxerts, but other chromic Vertisolgreat groups (Chromouderts and Chromousterts) hadtwice the SOC content of the soil map of the worldvalues.

The Luvisol SOC contents were comparable to Alfisolgreat groups with the exception of the much higherAlbic Luvisols. The great group Eutroboralf is similarin morphology to Albic Luvisols but had 8.7 kg C m"2

compared with 21.7 kg C m""2 for Albic Luvisols. Therewas not much difference among Kastanozems andPhaoezems (12-15 kg C m~2), which were comparableto the similar great groups of Ustoll and Udoll suborders.The Chernozem SOC content was slightly higher thancomparable Boroll great groups. The Podzols had asimilar range to the Spodosol great groups with theexception of the Gleyic Podzol, which was relativelyhigh.

The spatial distribution of SOC for the contiguousUSA from the soil map of the world data (Fig. 7) wassimilar to the mean Soil Taxonomy approach (Fig. 6)except that the soil map of the world data indicated


Table 6. Soil organic C to 1-m depth calculated from the soil mapof the world.

Soil unit

AcrisolsGleyicFerricOrthicHumic

AndosolsVitricOchricHumicMollic

ArenosolsCambicFerralicLuvicAlbic

CambisolsCalcicEutricVerticFerralicChromicDystricHumicGleyicGelic

ChernozemsLuvicCalcicHaplic

FerralsolsXanthicAcricOrthicHumicRhodic

FluvisolsCalcaricDystricThiomicEutric

GleysolsDystricEutricCalcaricHumicGelicMollicOrthic

HistosolsEutricDystricGelic

KastanozemsHaplicCalcicLuvic

LuvisolsFerricCalcicPlinthicOrthicChromicGleyicAlbic

NitosolsDystricEutric

SoilCmean

kg C m-2

5.57.09.6

16.5

18.024.126.427.4

3.05.16.17.5

8.310.311.913.313.814.114.318.823.1

17.218.422.8

7.79.3

12.916.016.8

6.817.218.020.2

12.112.112.313.722.527.624.6

82.086.799.2

12.412.715.2

5.57.57.8Q 3O. J

10.212.921.7

9.19.2

cvt%

13382733

404

3823

321981

171911551111304330

13634

2328392530

30

4131

4121

3463

3

1716

372823

3316-214142

435

"tno

3366

4252

3221

452234322

233

22433

5124

4713212

361

543

4214741

33

SoilCSoil unit mean CVt nj

(cont.)Phaeozems

Haplic 12.4 16 5Luvic 13.8 35 3Gleyic 15.0 11 2Calcaric 15.2 - 1

PodzolsOrthic 13.7 82 3Humic 17.1 46 4Gleyic 19.0 46 3Placic 19.0 27 2Leptic 21.9 27 2

PodzoluvisolsGleyic 6.5 43 2Dystric 7.9 - 1Eutric 9.4 18 3Rankers 5.9 - 1

RegosolsDystric 5.2 - 1Eutric 6.3 11 3Calcaric 6.8 - 1Gelic 19.9 19 2

Rendizinas 15.7 32 3oOlODCnftKS

Gleyic 4.9 72 2Takyric 5.6 66 2Orthic 6.3 42 2Mollic 10.5 - 1

SolonetzOrthic 5.8 34 5Mollic 10.4 30 3Gleyic 12.9 - 1

V rfi 1vertisoisChromic 5.3 49 6PeUic 11.5 38 4

XerosolsHaplic 6.4 19 4Luvic 6.5 12 2Calcic 6.6 26 3

YermosolsGypsic 2.1 - 1Calcic 2.2 53 4Luvic 2.2 - 1Takyric 3.5 - i

Total 255

t Coefficient of variation.$ Number of samples.

greater SOC content in the northern Rockies, northernAppalachia, and mountainous parts of the West, andlower SOC was indicated in the upper Great Lakes andmuch of Southwest. The northern Rockies and Utah haveconsiderable federal land, and the 1982 NRI data maynot adequately describe these regions.

CONCLUSIONSSoil organic C can be sufficiently characterized on

very broad scales using ecosystem zones for aggregation;however, there are limitations to this approach for moredetailed work because this approach does not accountfor local variations hi parent materials (organic materials,coarse fragment content, and mineralogy) and soil depth.There was a great deal of heterogeneity of soil within


ki lometers

0 900Albers conic-tquol or«o

E3 0.1E2 6.1E3 7.6S 9.1

totototo

6.07.59.010.5

m 10^ 12H 13m 15

.6 to

.1 to

.6 to

.1 to

kg (12.0 i13.5 E15.0 i16.5 i

: m'21 16.6^ 18.11 19.6I 21.1

totototo

18.0 &19.5 I21.0 B22.5

% 22.51 25.1i 35.1

tototo

25.035.086.7

Fig. 7. Soil organic C using the soil map of the world to 1-m depth.

ecosystem complexes, which makes this method of dataaggregation of limited use. The SOC content based onecosystems of the contiguous USA (78.0 Pg of C) waswithin one-half of the SOC standard deviation. Thus, atthat scale, this method was useful, but the spatial patternsmight not be useful for more detailed studies. The ecosys-tem approach might be useful for global studies whereit is not combined with other georeferenced data andwhere only a large region total is needed. The unreliabil-ity of the spatial patterns of SOC make this approachof limited use hi studies where georeferenced data, suchas climate or land use, are used. The pedon data onwhich the ecosystem complex approach is based containonly one value for SOC from 0- to 1-m depth, whichlimits its use when some other depth increment is needed.The pedon data for the other approaches can be subsetat any depth to be used for applications such as SOCloss from erosion (Kern, 1992) or changes in surfaceSOC from tillage (Kern and Johnson, 1993).

Soil classification is a much better framework fordata aggregation than is ecosystem complex. The soil

classification systems do not have narrow limits of SOCin their criteria, but soils with similar classification oftenhave similar factors that affect SOC accumulation. Soilorders and suborders were not very effective for aggregat-ing pedon data. Great groups were a better frameworkand were a good compromise for level of detail becauseaggregation at a more specific level, such as subgroup orfamily, would require extremely large pedon databases.

The SOC content of the contiguous USA using thesoil map of the world (84.5 Pg of C) came very close tothe mean SOC content as calculated by the Soil Taxonomyapproach (80.7 Pg of C). This similarity may be due,in part, to the common origin of the map data. Thetwo approaches yielded very similar SOC per unit areaestimates for similar types of soils. The spatial detail ofthe soil map of the world was slightly greater than thatof the Soil Taxonomy approach (MLRAs), which is anadvantage for some applications. An advantage of theSoil Taxonomy approach is that it is possible to estimateupper and lower limits using assumptions about the NRIdata. The Soil Taxonomy approach may be less reliable


in areas of extensive federal land because the 1982 NRIexcludes federal land. This limitation may be minimizedif nonfederal land studied in the MLRAs was similar tofederal land. The Soil Taxonomy approach has manyadvantages because of additional data contained in the1982 NRI, such as land use. This is illustrated by astudy of the impact of conservation tillage on SOC (Kernand Johnson, 1993) where cropland SOC was estimatedby using points from the NRI that were cropland andoverlaying these points with a map of the areal extentof planted cropland. The 1982 NRI provides a greaternumber of map unit components than does the soil mapof the world, which is very useful for applications wherethe maximum or minimum values, rather than meanvalues, are critical. The SCS data approach providesa wealth of auxiliary information, such as land use,vegetation, and erosion from the 1982 NRI, which canbe used for data aggregation.

Improved statistical confidence will require largernumbers of sampled pedons to be included in the analy-ses. It would l>e very useful if existing databases, suchas the Zinke et al. (1984) dataset, could be updated byincluding the soil classification for samples that havealready been analyzed for SOC content. There are aconsiderable number of pedons or sites in the NSSL-PDwith missing series classification. The land use of pedonssampled should also be identified. There is not a lackof SOC measurements by weight, but there is a shortageof accompany big bulk density measurements. Measure-ment of bulk density in Histosols can be problematic,but it makes an enormous difference in the SOC estimatesby volume.

Better information about how the sampled pedons rep-resent the taxonomic unit used to aggregate the data isneeded. In this study, each pedon was assumed to equallyrepresent ecosystem complexes or taxonomic units, butthis was probably not the case. Information about whetherthe pedon is typical or atypical would enable differentweighting. Similarly, better locational data would permitfurther aggregating data by river basin, county, or othersubarea.

ACKNOWLEDGMENTSThis research was aided by the generous help of many

agencies. The USDA-SCS was very helpful in providing dataand advice. Henry Mount, of the Quality Assurance Staff,Lincoln, NE, helped with the acquisition of the Soil Interpreta-tion database. Benny R. Brasher and Steven L. Baird, of theNational Soil Survey Laboratory, Lincoln, NE, were veryhelpful in the acquisition and use of laboratory characterizationdatabase. Harvey Terpstra, of the Statistical Laboratory, IowaState University, provided the Soil Interpretation database andhelp with its use. Norm Bliss at the U.S. EROS Data Centerprovided the digital data for the United Nations soil map ofthe world, as well as helpful advice about linking together theNational Soil Geographic Database and the 1982 NationalResources Inventory.

spatial patterns of soil organic carbon in the contiguous united states

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