Soil vital signs: A new Soil Quality Index (SQI) for assessing forest

United StatesDepartmentof Agriculture

Soil Vital Signs: A New Soil Quality Index (SQI) for

Assessing Forest Soil Health

Michael C. Amacher, Katherine P. O’Neill, and Charles H. Perry

Rocky MountainResearch Station

May 2007Forest Service Research Paper

RMRS-RP-65WWW

Amacher, Michael C.; O’Neil, Katherine P.; Perry, Charles H. 2007. Soil vital signs: A new Soil Quality Index (SQI) for assessing forest soil health. Res. Pap. RMRS-RP-65WWW. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 12 p.

Abstract __________________________________________ The Forest Inventory and Analysis (FIA) program measures a number of chemical and physical properties of soils to address specific questions about forest soil quality or health. We developed a new index of forest soil health, the soil quality index (SQI), that integrates 19 measured physical and chemical properties of forest soils into a single number that serves as the soil’s “vital sign” of overall soil quality. Regional and soil depth differences in SQI values due to differences in soil properties were observed. The SQI is a new tool for establishing baselines and detecting forest health trends.

Keywords: forest soil health, Forest Inventory and Analysis, soil indicator database, soil quality index

The Authors Michael C. Amacher is a research soil scientist with the Forest and Woodland Program Area at the Forestry Sciences Laboratory in Logan, UT. He holds a B.S. and a M.S. in chemistry and a Ph.D. in soil chemistry, all from The Pennsylvania State University. He joined the Rocky Mountain Research Station in 1989. He studies the effects of natural and human-caused disturbances on soil properties and develops methods for restoring disturbed ecosystems. He is also the western soil indicator advi-sor for FIA.

Katherine P. O’Neill is a former research soil scientist with the Forest Inventory and Analysis Work Unit at the North Central Research Station in St. Paul, MN. She holds a B.S. in geology from the College of William and Mary and a Ph.D. in biogeochemistry and ecosystem ecology from Duke University. She joined the North Central Research Station in 2001 where her research focused on the effects of disturbance on soil carbon and nutrient cycling and on developing techniques for monitoring changes in forest soil properties. She also served as the eastern soil indicator advisor for FIA from 2001 to 2003.

Charles H. (Hobie) Perry is a research soil scientist with the Forest Inventory and Analysis unit at the Northern Research Station in St. Paul, MN. He holds a B.A. in philosophy from the University of Michigan and an M.S. and a Ph.D. in forestry from the University of Minnesota. He joined the North Central Research Station in 2004. His research focuses on estimation of the soils component of carbon stocks and methods of generalizing and summarizing FIA data across varying spatial scales. He is the eastern soil indicator advisor for FIA.

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�USDA Forest Service Res. Pap. RMRS-RP-65WWW. 2007

Introduction

NumerousphysicalandchemicalpropertiesofsoilsaremeasuredaspartoftheFIAforesthealthindicatorsprogramtoevaluatethestatusof,andtodetect,trendsinforestsoilquality.Unlessaparticularindicatorofforesthealthisstronglyrelatedtoaspecificsoilproperty,theindividualphysicalandchemicalpropertiesareoftenoflittlevaluetoscientiststryingtoassessoverallforesthealth.Typically,individualbiologicalindicatorsofforeststandhealth(forexample,diebackorproductivity)arecorrelatedwitharangeofsoilphysicalandchemicalpropertiesinanattempttoidentifywhichpropertyorpropertiesareassociatedwithforesthealth.Variableswithstatisticallysignificantpositiveornegativecorrelationsareusedtodevelopmultivariateregressionequationstoexplainorpredictforesthealthasafunctionofmeasuredsoilproperties.Becausethisapproachispredominantlysitespecific,itisoflittleuseasaroutineassessmenttool.Also,manysoilpropertiesareassociatedwitheachother(forexample,lowpHassociatedwithlownutrientlevels)suchthatusingasingle“dependent”variableinisolationmaynotprovideacompleteandaccurateassessmentofforesthealth. ToassistecologistsandFIAanalystsinassessingthepotentialimpactsofchangesinsoilpropertiesonforesthealth,itwouldbedesirabletodevelopasoilqualityindex(SQI)thatintegratesthemeasuredsoilphysicalandchemicalpropertiesintoasingleparameterthatcouldbeusedasanindicatorofoverallforestsoilquality.Thus,inconcept,thisindexwouldserveasameasureofthesoil’s“vitalsign.” Theuseofindexestomeasuretrendsiswellestablished.PerhapsthemostwellknownexampleisuseoftheDow-JonesIndustrialAverageasanindicatorofstockmarketactivityandeconomichealth.Theuseofindexvaluestointegrateorsum-marizesoilpropertiesisnotanewconcept.Othershavesuggestedanddevelopedsuchindexesforagriculturalsystems(forexample,DoranandParkin1996),butasimilarindexasanindicatorofforestsoilhealthislacking.Thedevelopmentandapplicationofasoilqualityindextoanationallyconsistentforestsoilmonitoringprogramwouldprovide amechanism for evaluatingchanges in soil propertiesacrossthelandscape. Here,wedevelopandpresentanSQIthatintegrates19soilphysicalandchemicalpropertiesmeasuredintheFIAprogramintoasinglenumberthatcanbeusedtomonitorchangesinforestsoilpropertieswithtime.TheSQImayalsohavesomepotentialasanindicatorofincreasedordecreasedriskofforestdecline,butthiswilldependonitsaccuracytopredictsoilrelatedforesthealthstatusandtrends,

Soil Vital Signs: A New Soil Quality Index (SQI) for

Assessing Forest Soil HealthMichael C. Amacher, Katherine P. O’Neill, and Charles H. Perry

2USDA Forest Service Res. Pap. RMRS-RP-65WWW. 2007

anassessmentwhichhasyet tobemade.TheSQImayalsobeanindicatorofthepotentialforsoilqualitytochangebecauseoftheinfluenceofenvironmentalstressors(forexample,atmosphericdeposition,changesinglobalcycles,andsoforth).

Methods

AbriefdescriptionofthedevelopmentofthesoilindicatorandtheFIAplotnetwork isgiven inO’Neill andothers (2005a,b).Three forest floorand twomineral soil core samples are collected fromeachFIAPhase3plot.At eachforestfloorsamplelocation,thecompleteforestfloor(litter+humuslayers)iscollectedfroma30.5-cmdiametersamplingframeandsenttooneoftheregionalFIAlaboratoriesfordeterminationsofsampleweight,watercontent,andtotalcarbonandnitrogen.Twomineralsoilcores(0to10cmand10to20cm)arecollectedfromonesamplinglocationusinganimpact-drivensoilcoringtool.Analysisofthemineralsoilcoresincludessampleweight,bulkdensity,watercontent,coarsefragmentcontent,waterandsaltpH,carbon(total,organic,andinorganicC),totalnitrogen(N),1MNH4Clexchangeablecations(sodium[Na],potassium[K],magnesium[Mg],calcium[Ca],aluminum[Al]),1MNH4Clextractabletraceelements(manganese[Mn],iron[Fe],nickel[Ni],copper[Cu],zinc[Zn],cadmium[Cd],lead[Pb]),1MNH4Clextractablesulfur(S),andBray1orOlsenextractablephosphorus(P).DetailsoftheFIAplotlayout,soilsam-pling,andsoilanalysismethodsarepresentedelsewhere(Amacherandothers2003;O’Neillandothers2005a,b;USDAForestService2005).Inthisreport,wefocussolelyonthedevelopmentoftheSQIfromthemeasuredsoilpropertiesofthemineralsoilcores,givesomeexamplesofcalculatedSQIsusingapartialFIAsoilsdatabase,andproviderecommendationsonitsapplicationtoFIAdata.Becauseonlyafewpropertiesaremeasuredontheforestfloorsamples,theyarenotusedtocalculateSQIs. Mineralsoilpropertythresholdlevels,interpretations,andassociatedsoilindexvaluesarelistedintable1.TherationaleforthethresholdlevelsselectedisgivenintheAppendix.Theindividualindexvaluesforall themineralsoilpropertiesmeasuredonanFIAplotaresummedtogiveatotalSQI:

TotalSQI=∑individualsoilpropertyindexvalues

ThemaximumvalueofthetotalSQIis26ifall19soilpropertiesaremeasured.ThetotalSQIisthenexpressedasapercentageofthemaximumpossiblevalueofthetotalSQIforthesoilpropertiesthataremeasured:

SQI,%=(totalSQI/maximumpossibletotalSQIforpropertiesmeasured)x100

Thus,missingpropertiesdonotcontributetotheindex.However,werecommendthatSQIsbasedononlyafewofthe19measuredsoilpropertiesnotbeincludedinanydataanalysissincethesevaluescouldprovideadistortedassessmentofsoilqualitybecausetheyarebasedontoofewmeasuredproperties.


Table 1—Soil quality index values and associated soil property threshold values and interpretations.

(continued)

> 500 High – excellent reserve 250 to 500 Moderate – adequate levels for most plants 1Mg (mg/kg)< 50 Low – possible deficiencies 0> 1000 High – excellent reserve, probably calcareous soil 2101 to 1000 Moderate – adequate levels for most plants 110 to 100 Low – possible deficiencies 0Ca (mg/kg)

< 10 Very low – severe Ca depletion, adverse effects more likely -1> 100 High – adverse effects more likely 011 to 100 Moderate – only Al sensitive plants likely to be affected 11 to 10 Low – adverse effects unlikely 2Al (mg/kg)

< 1 Very low – probably an alkaline soil 2> 100 High – possible adverse effects to Mn sensitive plants 011 to 100 Moderate – adverse effects or deficiencies less likely 11 to 10 Low - adverse effects unlikely, possible deficiencies 1Mn (mg/kg)

< 1 Very low – deficiencies more likely 0> 10 High – effects unknown 10.1 to 10 Moderate – effects unknown 1Fe (mg/kg)< 0.1 Low – possible deficiencies, possibly calcareous soil 0

> 5 High – possible toxicity to Ni sensitive plants, may indicateserpentine soils, mining areas, or industrial sources of Ni 0

0.1 to 5 Moderate – effects unknown 1Ni (mg/kg)

< 0.1 Low – adverse effects highly unlikely 1

> 1 High – possible toxicity to Cu sensitive plants, may indicatemining areas or industrial sources of Cu 0

0.1 to 1 Moderate – effects unknown, but adverse effects unlikely 1Cu (mg/kg)

< 0.1 Low – possible deficiencies in organic, calcareous, or sandy soils 0

Parameter Level Interpretation Index> 1.5 Possible adverse effects 0Bulk density (g/cm3) 1.5 Adverse effects unlikely 1> 50 Possible adverse effects 0Coarse fragments

(percent) 50 Adverse effects unlikely 1< 3.0 Severely acid – almost no plants can grow in this environment -1

3.01 to 4.0Strongly acid – only the most acid tolerant plants can grow in thispH range and then only if organic matter levels are high enoughto mitigate high levels of extractable Al and other metals

0

4.01 to 5.5 Moderately acid – growth of acid intolerant plants is affecteddepending on levels of extractable Al, Mn, and other metals 1

5.51 to 6.8 Slightly acid – optimum for many plant species, particularly moreacid tolerant species 2

6.81 to 7.2 Near neutral – optimum for many plant species except those thatprefer acid soils 2

7.21 to 7.5Slightly alkaline – optimum for many plant species except thosethat prefer acid soils, possible deficiencies of available P andsome metals (for example, Zn)

1

7.51 to 8.5 Moderately alkaline – preferred by plants adapted to this pHrange, possible P and metal deficiencies 1

Soil pH

> 8.5 Strongly alkaline – preferred by plants adapted to this pH range,possible B and other oxyanion toxicities 0

> 5 High – excellent buildup of organic C with all associated benefits 21 to 5 Moderate – adequate levels 1

< 1 Low – could indicate possible loss of organic C from erosion orother processes, particularly in temperate or colder areas 0

> 0.5 High – excellent reserve of nitrogen 20.1 to 0.5 Moderate – adequate levels 1< 0.1 Low – could indicate loss of organic N 0> 15 High – sodic soil with associated problems 0

15Adverse effects unlikely

1

> 500 High – excellent reserve 2100 to 500 Moderate – adequate levels for most plants 1K (mg/kg)< 100 Low – possible deficiencies 0

Exchangeable Napercentage(exchangeableNa/ECEC x 100)

Total nitrogen in mineralsoils (percent)

Total organic carbon inmineral soils (percent)


Table 1 (Continued)

> 10 High – possible toxicity to Zn sensitive plants, may indicatemining areas or industrial sources of Zn 0

1 to 10 Moderate – effects unknown, but adverse effects unlikely 1Zn (mg/kg)

< 1 Low – possible deficiencies in calcareous or sandy soils 0> 0.5 High – possible adverse effects 00.1 to 0.5 Moderate – effects unknown, but adverse effects less likely 1Cd (mg/kg)< 0.1 Low – adverse effects unlikely 1

> 1 High – adverse effects more likely, may indicate mining areas orindustrial sources of Pb 0

0.1 to 1 Moderate – effects unknown, but adverse effects less likely 1Pb (mg/kg)

< 0.1 Low – adverse effects unlikely 1

> 100 High – may indicate gypsum soils, atmospheric deposition,mining areas, or industrial sources 0

1 to 100 Moderate – adverse effects unlikely 1S (mg/kg)

< 1 Low – possible deficiencies in some soils 0

> 30High – excellent reserve of available P for plants in acid soils,possible adverse effects to water quality from erosion of high Psoils

1

15 to 30 Moderate – adequate levels for plant growth 1

0.03 M NF4 + 0.025 MHCl (Bray 1) P (mg/kg)

< 15 Low – P deficiencies likely 0

> 30High – excellent reserve of available P in slightly acidic toalkaline soils, possible adverse effects to water quality fromerosion of high P soils

1

10 to 30 Moderate – adequate levels for plant growth 1

pH 8.5, 0.5 M NaHCO3(Olsen) P (mg/kg)

< 10 Low – P deficiencies likely 0

Parameter Level Interpretation Index

Results and Discussion AhistogramofthedistributionofSQIsforsoilsamplescollectedfromFIAbasegridplotsin2000through2004showsthatmostoftheplotsareclusteredaroundthemid-rangeofSQIvalues(fig.1).SQIsforeachregionofthecountryareplottedasseparatebarstoallowforregionalcomparisonsamongthedifferentrangesofSQIvalues.ThesouthtendedtohavemoreplotswithlowerSQIvalueswhereasthewesttendedtohavemoreplotsathigherSQIvalues.Thetwosoilcoredepths(0to10and10to20cm)areplottedseparately.BothsoilcoredepthstendtohavethesamerelativedistributioninSQIvalues.Oneoftheadvantagesofanindexforassessingforestsoilqualityisthattheindexvaluestendtofollowanormaldistributioneventhoughindividualsoilpropertiesthatareusedtocalculatetheindexareoftennon-normallydistributed. TherangeofobservedSQIvaluesareshownforeachregionofthecountryandeachsoilcoredepthinboxplots(fig.2).Minimum,mean,andmaximumvaluesforeachregionandsoilcoredeptharesummarizedintable2.ThesouthtendedtohavelowerSQIlevelsthanotherregionsofthecountry.Thisisaresponsetothefactthatlargeareasofmorehighlyweatheredsoilstendtobeconcentratedinthesouth.MorehighlyweatheredsoilstendtohavelowerorganiccarbonandnutrientcontentsandlowerpHlevelsandhigheracidity(asmeasuredbyexchangeableAllevels)thansoilsinlessintensivelyweatheredregionsofthecountry.TheSQIcalculationstakethisintoaccount.Otherconsiderationsbeingequal,theremaybeanincreasedriskofsoil-relatedforestdeclineonsoilswithlowerSQIlevels.


Figure 1—Histogram of SQI levels for the 0 to �0 cm (left) and �0 to 20 cm (right) soil cores from the 2000 to 200� FIA plots from the Northeast, North Central, South, Interior West, and Pacific West FIA regions of the United States.


Figure 2—Box plots of SQI levels for the 0 to �0 cm and �0 to 20 cm soil cores from the 2000 to 200� FIA plots from the Northeast, North Central, South, Interior West, and Pacific West FIA regions of the United States. The 25th and 75th percentiles are shown as a box around the median (solid line) and mean (dotted line), the �0th and 90th percentiles are shown as error bars, and the 5th and 95th percentiles and outlier data points are shown as circles.

Table 2—Minimum, mean, and maximum SQIs of FIA soil samples collected between 2000 and 200�.

Soil mineral Region layer (cm) N Minimum Mean Maximum -----------Percent----------Northeast (CT, MA, ME, NH, NJ, 0 to �0 �08� 25 55 �00

OH, PA, RI, VT, WV) �0 to 20 �02� �5 �9 �00

North Central (IA, IL, IN, KS, MI, 0 to �0 857 25 66 �00

MN, MO, ND, NE, SD, WI) �0 to 20 8�� 20 56 �00

South (Al, AR, FL, GA, KY, LA, MS, 0 to �0 �757 20 5� 90

NC, OK, SC, TN, TX, VA) �0 to 20 �725 �5 �� 89

Interior West (AZ, CO, ID, MT, NM, 0 to �0 976 �0 66 �00

NV, UT, WY) �0 to 20 869 22 6� 90

Pacific West (CA, OR, WA) 0 to �0 566 �0 67 �00

�0 to 20 �97 �� 62 90


However,becauseriskofdeclineisdependentonsoilandforesttypeandtypeofdisturbance, these factorsmustbeconsidered inanyassessmentof soil-relatedforestdecline. The10to20cmsoilcorestendedtohavelowerSQIlevelsthanthe0to10cmsoilcores(fig.2,table2).The10to20cmsoilcorestendedtohavehigherbulkdensityandlowerorganiccarbonandnitrogenlevelsthanthe0to10cmsoilcores,whichwouldskewtheSQIlevelstolowernumbers. Manysoilpropertiestendtobecorrelatedwitheachother.SincetheSQIisbasedon19measuredsoilproperties,someofthesevariablesareexpectedtobeinter-related.Toassessthedegreeofassociationamongthemeasuredvariables,Pearsonproductmomentcorrelationcoefficientswerecalculatedandthehighestsignificantcorrelationcoefficientsarepresentedintable3. Thevariablesthatwereexpectedtobestronglyassociatedwerefoundtohavesignificantlyhighcorrelationcoefficients.Soilbulkdensityisinfluencedbysoilorganicmatter(SOM)levelsbecausehighamountsoflighterweightSOMwillresultinlowerbulkdensities.Totalorganiccarbon(TOC)andtotalNareindirectmeasuresof the amountofSOM.Thus, thenegative correlationbetweenbulkdensityandTOCortotalNisexpected.Similarly,thereisastrongpositivecor-relationbetweenTOCandtotalNbecausethesearemajorconstituentsofSOM.AstrongpositivecorrelationbetweensoilpHandexchangeableCaisexpectedbecausehighpHsoilstendtobecalcareousbecauseofthepresenceofcarbonatemineralshighinCa.AstrongnegativecorrelationbetweensoilpHandexchange-ableAlisalsoexpected,becauseexchangeableAlisthemajorsourceofacidityinstronglyacidsoils.ExchangesitesonclaymineralstendtohavemoreCaandMgthanotherelements,thusaccountingforthestrongpositiveassociationbetweenexchangeableCaandMg.ZincandCdaregroupIIBelementsintheperiodictableandhavesimilarchemistriesandreactionsinsoils.Thus,highlevelsofextractableZntendtobeaccompaniedbyhighlevelsofextractableCd. ThehighlyinterrelatedvariablessuchashighTOCandtotalN,lowbulkdensity,higherpH,lowexchangeableAl,andhighbasecationlevels(K,Mg,andCa)wouldtendtoyieldhighSQIlevels.

Table 3—Significantly high Pearson product moment correlation coefficients among the soil variables.

TOC1 Total N Ex2 Mg Ex Ca Ex Al Ex Cd

Bulk density –0.�80 –0.�� TOC 0.728 Water pH 0.�07 0.6�8 –0.5�� Ex K 0.�9� 0.�58 Ex Mg 0.59� Ex Ca –0.�0� Ex Zn 0.�2��TOC = total organic carbon2Ex = � M NH�Cl extractable


Recommendations for Interpreting and Using SQI Values

TheSQIwasdeveloped to integrate19measuredsoilphysicalandchemicalpropertiesintoasingleindexnumber,whichcanbeusedtoassesstrendsinfor-estsoilqualityandestablishbaselinelevelsfordifferentsoilandforesttypes.WeurgeFIAandFHManalystsandscientistsinterestedinforesthealthissuestobeginexploringanystatisticalassociationsbetweenSQIandmeasuresofforesthealth,including damage, dieback, crown transparency, biomass, productivity, speciesdiversity,lichens,andsoforth.IftheSQIisabletosuccessfullyquantifyincreasedriskofsoil-relatedforestdecline,thenweexpecttofinddeclineassociatedwithlowSQIlevels.Alackofassociation,however,mayindicatethatinaccuratethresholdvalueswereselected,othersoilpropertiesnotmeasuredintheFIAprogramarecontributingtoforestdecline,orthecausativeagentofdeclineisnotsoilsrelated.Moreaccuratethresholdlevelsandindexcomputationalalgorithmscanbedevel-opedonlythroughrepeatedandrigorousevaluationsoftheSQI. Followingadditional testingandrefinement,weanticipate thatcalculationofSQIvalueswillbedoneautomaticallyaspartoftheFIAsoildatabaseandmadereadilyavailabletootherscientists.Thedatabasecanbestratifiedbyecoregion,foresttype,soiltype,andsoforth.andappropriatepopulationestimatescanbecalculated.MapproductsshowingthespatialdistributionofSQIlevelscanthenbeprepared.Soilpropertythresholdlevelsandweightingfactorsmayneedtoberefinedfordifferentregionsofthecountrytotakeintoaccountdifferentsoilandforesttypes.ThiscouldimprovespatialresolutionofSQIswithinaregion.

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Fisher,R.F.1995.Soilorganicmatter:clueorconundrum.In:W.H.McFeeandJ.M.Kelly,editors.Carbonformsandfunctionsinforestsoils.Madison,WI:SoilScienceSocietyofAmerica:1-11.

Fisher,R.F.;Binkley,D.2000.EcologyandManagementofForestSoils.3rdedition.NewYork:JohnWileyandSons.489p.

Hargrove,W.L.;Thomas,G.W.1981.Effectoforganicmatteronexchangeablealuminumandplantgrowthinacidsoils.In:R.H.Dowdy,J.A.Ryan,V.V.Volk,andD.E.Baker,editors.Chemistryinthesoilenvironment.AmericanSocietyofAmericaSpecialPublicationNumber40.Madison,WI:AmericanSocietyofAgronomy:151-166.

Henderson,G.S.1995.Soilorganicmatter:alinkbetweenforestmanagementandproductivity.In:W.H.McFeeandJ.M.Kelly,editors.Carbonformsandfunctionsinforestsoils.Madison,WI:SoilScienceSocietyofAmerica:419-435.

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�0USDA Forest Service Res. Pap. RMRS-RP-65WWW. 2007

Bulk density—Soilbulkdensitymayindicatesoilcompactionbutisdependentonmanysoilfactorsincludingparticlesizedistribution,soilorganicmattercontent,andcoarse fragmentcontent.Generally,bulkdensity increaseswith increasingsandand rockcontentanddecreaseswith increasingorganicmattercontent.Amineralsoilwith“ideal”physicalpropertieshas50percentsolidsand50percentporespaceoccupyingagivenvolumeofspace.Atoptimalwatercontent,halftheporespaceisfilledwithwater.Suchasoilwillhaveabulkdensityof1.33g/cm3.Ingeneral,rootsgrowwellinsoilswithbulkdensitiesofupto1.4g/cm3androotpenetrationbeginstodeclinesignificantlyatbulkdensitiesabove1.7g/cm3(FisherandBinkley2000;Sutton1991).Weselected1.5g/cm3asthethresholdvalueforbulkdensity,abovewhichthereisanincreasingprobabilityofadverseeffectsfromsoilcompactionorhighrockcontent. Coarsefragments—Soilswithacoarsefragmentcontentof>50percenttohaveagreaterprobabilityofadverseeffectsfrominfiltrationrates thatare toohigh,waterstoragecapacitythatistoolow,moredifficultrootpenetration,andgreaterdifficultyinseedgerminationandseedlinggrowth.Highcoarsefragmentcontentshavebeenshowntolimitforestsoilproductivity(RodrigueandBurger2004). Soil pH—Althoughmanyplantspeciesareadaptedtoacidicoralkalinesoils,vegetationdiversitytendstodeclineatstronglyacid(pH<4)orstronglyalkaline(pH>8.5)pHlevels.Also,theavailabilityofmanyplantnutrients(forexample,P),non-essentialelements(forexample,Al,Cd,Pb),andessentialtraceelements(forexample,Mn,Fe,Cu,Zn)isstronglydependentonsoilpH(MillerandGardiner2001).Generally,metalcations(forexample,Mn,Fe,Ni,Cu,Zn,Cd,Pb)becomemoreavailableaspHdecreases,whileoxyanions(forexample,SO4)becomemoreavailableatalkalinepHlevels.Onlythemostacid-oralkaline-tolerantplantspe-ciescansurviveattheveryacidicoralkalineendsofthepHscale.SoilpHisalsostronglydependentonthechemicalweatheringenvironment.Soilsinhot,humidareas(forexample,southeasternUnitedStates)andevenmesic,wetterareas(forexample,NewEngland,mid-Atlantic,PacificNorthwest)tendtobemoreacidicthanthoseofmuchdrierareas(forexample,portionsofthesouthwesternandinteriorwesternUnitedStates).Vegetationcommunitiesinthoseareastendtobeadaptedtothesoilconditionsinwhichtheydeveloped.However,fewplantcommunitiesareadaptedtostronglyorseverelyacidsoils,particularlyifthoseconditionsde-velopedasaresultofacidicatmosphericdepositionmorerapidlythantheplantcommunitiescouldadapt. Organic carbon and nitrogen—Organicmatterisakeycomponentofsoilsbecauseofitsinfluenceonsoilphysicalandchemicalpropertiesandsoilbiota(Fisher1995).Soilorganicmatteriscomposedofmanyelements,butCandNaretwoofthemostimportant.TheorganicCandNcontentsofsoilsaretheresultofalltheinputsandoutputsandsoilformingprocesses,butgenerally,higherlevelsoforganicCandNarefoundincolderandwettersoils(forexample,borealforests,wetlands)whereorganicmattertendstoaccumulate.Lesseramountsare

Appendix: Rationale for Soil Property Threshold Levels Listed in Table 1

��USDA Forest Service Res. Pap. RMRS-RP-65WWW. 2007

foundinmoreintensivelyweatheredsoilssuchasthoseinthesoutheasternUnitedStatesandinhotter,drierareasofthecountrysuchasthedesertsouthwestwherebiomassproductionismorelimitedandorganicmatterbreakdownisrapidbecauseofwarmertemperatures.Variousdisturbancesandlandmanagementpracticescanresultindecreasedsoilorganicmatterlevels(Henderson1995;Schlesinger1997).Soilswithtotalorganiccarbon(TOC)andtotalNcontentsoflessthan1percentand0.1percent,respectively,areatagreaterriskofdeclineifsoilerosionand/orotherdisturbancesthataccelerateorganicmatterlosscontinuetoresultinanetlossofsoilorganicmatter,particularlyinareaswherenearbyundisturbed,nativesoilsarefoundtohavehigherlevelsofTOCandtotalN(USDA-NRCS-SQI2003). Exchangeable cations (Na, K, Mg, Ca, Al)—Generally,exchangeableCain-creaseswithincreasingpH,whilehighexchangeableAllevelsarefoundinsoilswithapHbelow5.2.HighexchangeableAllevelsaredeleterioustoplantgrowth,butthiscanbemitigatedsomewhatbyhighorganicmatterlevels(HargroveandThomas1981).HighorganicmatterlevelscancomplexexchangeableAlfrommineralsoilweathering,thusdecreasingAltoxicitytoterrestrialplantsandaquaticbiota.SoilswithverylowpH,loworganicmatter,highexchangeableAl,andse-verelydepletedCahavethegreatestriskofbeingassociatedwithforestdecline.Calciumdepletionhasbeenidentifiedasa threat tosustainableproductivityofsoutheastern forested watersheds (Huntington and others 2000). ExchangeableNapercentage(ESP)iscomputedbydividingtheexchangeableNaconcentration(cmolc/kg)bytheeffectivecationexchangecapacity(ECEC)(cmolc/kg)multipliedby100.SoilswithanESPof>15percentareclassifiedassodicorsaline/sodicsoilsdependingonthesaltcontentofthesoilsasmeasuredbytheelectricalcon-ductivityofasaturatedsoilextract(Richards1954).SuchsoilsarefoundinmorearidicareasoftheUnitedStatesandaremorelikelytoexhibitadverseeffects(forexample,decreasedinfiltration)associatedwithtoohighNalevelsthansoilswithanESP<15percent.Plantsgrowinginsoilswithverylowlevelsofexchange-ableKandMg(<100and50mg/kg,respectively)haveagreaterprobabilityofexhibitingdeficiencysymptomsthanplantsgrowinginsoilswithhigherlevelsoftheseelements. Exchangeable metals (Mn, Fe, Ni, Cu, Zn, Cd, Pb)—Manganese,Fe,Cu,andZnareessentialtraceelements.Deficiencysymptomsaremorelikelyexhibitedatverylowlevelsofthesetraceelements,particularlyincalcareousandsandysoils,andinthecaseofCu,insoilshighinorganicmatter(MillerandGardiner2001).However,toxicitytoplantsmaybefoundatveryhighlevelsofthesetraceelements.Theexchangeablefractionofthesetracemetalsisthemostplantavailableforminsoilsnexttowater-solubleforms.Generally,exchangeablemetalsextractedby1MNH4ClincreasewithdecreasingsoilpH,providedtheyhaven’tbeenleachedfrom the soil profile. High levels of exchangeable Ni would only be found insomeserpentine-derivedsoils,miningareas,downwindofNismelters,orinareasreceivingNi-containingindustrialwastes(Kabata-Pendias2001).HighlevelsofexchangeableCu,Zn,Cd,andPbmaybefoundinmineralizedorminingareas,downwindofsmelters,orinareasreceivingmetal-containingindustrialwastesandinsomecases,agriculturalwasteproductsandfertilizers(Kabata-Pendias2001).SoilsadjacenttoroadsmayalsocontainelevatedlevelsofZn,Cd,andPb.Threshold

�2USDA Forest Service Res. Pap. RMRS-RP-65WWW. 2007

valuesforexchangeableMn,Fe,Ni,Cu,Zn,Cd,andPbwereselectedbasedontherangeanddistributionofvalueswithintheFIAsoildatasetbecausethereisinsufficientinformationrelatingvegetationresponseto1MNH4Clexchangeablemetallevels. Exchangeable S—Thedominant formofS in1MNH4Cl extracts is as-sumedtobesulfate(SO4).Sulfateishighlymobileinmostsoils.Highlevelsofexchangeablesulfatewouldlikelyonlybefoundinacidsoilscontainingmetaloxidemineralsthatcansorbthesulfate,metalsulfidemineralareas,gyp-siferoussoilsinmorearidicregions,andacidicsoilsreceivinglargeamountsof high-S atmospheric deposition downwind from coal-fired power plants.VolcaniceruptionsandashparticlesfromforestfirescanalsoaddsignificantamountsofStosoils.SulfurdeficiencieswouldbeexpectedonlyinsoilswithverylowlevelsofavailableS,suchassandysoilsandsomecalcareousandloworganicmattersoils(MillerandGardiner2001).ThresholdvaluesforSwereselectedbasedontherangeanddistributionofexchangeableSvaluesintheFIAsoildatabase. Extractable P—Soil P availability to plants is strongly dependent on theformsofPinsoilswhosesolubilityiscontrolledbysoilpH.Inacidsoils,mostplant-availablePisassociatedwithFeandAloxidesandisbestextractedwiththeBray1extractant(0.03MNH4F+0.025MHCl).TheBray1extractantisapplicabletosoilswithapHbelow6.8,butnottonear-neutraloralkalinesoilsbecausetheacidintheextractbeginstodissolveCaphosphates.TheseCaphos-phatesusuallyreleaseonlysmallamountsofPforplantuptakeunlesstheybegintodissolveundermoreacidconditions.Generally,deficiencysymptomsarenotexhibitedbyplantsgrowinginsoilswithBray1levelsabove15mg/kg(SoilandPlantAnalysisCouncil1999).Inalkalinesoils,mostsoilPisassociatedwithCa,eithersorbedtocarbonatemineralsorexistingasvariousCaphosphateminer-als,themostcommonofwhichisapatite.TheOlsen(pH8.5,0.5MNaHCO3)extractantwasdevelopedtomeasureplant-availablePinalkalinesoils,butitalsoworksinmanyacidsoils.ThebicarbonateionsreleasePsorbedtomanymineralsurfacesthatisplantavailablewithoutdissolvingtheotherwiseplant-unavailablePinCaphosphates.PlantsgrowinginsoilswithOlsen-extractablePlevelsabove10mg/kggenerallywillnotshowaresponsetoaddedP(SoilandPlantAnalysisCouncil1999).Becausewaterquality,asmeasuredbyalgalgrowth,isstronglydependentonlevelsandformsofPinreceivingwaters,soilswithveryhighlevelsofextractablePmayhaveadeleteriouseffectonwaterqualityifsuchsoilsaresubjectedtoerosionandthesoilparticlesendupinreceivingwaters.

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The Rocky Mountain Research Station develops scientific information and technology to improve management, protection, and use of the forests and rangelands. Research is designed to meet the needs of National Forest managers, Federal and State agencies, public and private organizations, academic institutions, industry, and individuals.

Studies accelerate solutions to problems involving ecosystems, range, forests, water, recreation, fire, resource inventory, land reclamation, community sustainability, forest engineering technology, multiple use economics, wildlife and fish habitat, and forest insects and diseases. Studies are conducted cooperatively, and applications may be found worldwide.

Research LocationsFlagstaff, Arizona Reno, NevadaFort Collins, Colorado* Albuquerque, New MexicoBoise, Idaho Rapid City, South DakotaMoscow, Idaho Logan, UtahBozeman, Montana Ogden, UtahMissoula, Montana Provo, Utah

*Station Headquarters, Natural Resources Research Center,2150 Centre Avenue, Building A, Fort Collins, CO 80526

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Documents

Soil vital signs: A new Soil Quality Index (SQI) for assessing forest