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ContentslistsavailableatScienceDirect

Ecological

Indicators

j o ur na l h o me p a g e :w w w . e l s e v i e r . c o m / l o c a t e / e c o l i n d

A

quantitative

framework

for

assessing

spatial

flows

of

ecosystem

services

H.M.

Serna-Chavez

a,∗

,

C.J.E.

Schulp

b

,

P.M.

van

Bodegom

c

,

W.

Bouten

a

,

P.H.

Verburg

b

,

M.D.

Davidson

a

aInstituteforBiodiversityandEcosystemDynamics,UniversityofAmsterdam,P.O.Box94248,1090GEAmsterdam,TheNetherlands bInstituteforEnvironmentalStudies,VUUniversityAmsterdam,DeBoelelaan1085,1081HVAmsterdam,TheNetherlands cDepartmentofEcologicalScience,VUUniversityAmsterdam,DeBoelelaan1085,1081HVAmsterdam,TheNetherlands

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received26June2013

Receivedinrevisedform25October2013 Accepted25November2013

Keywords:

Ecosystemservices Serviceprovidingareas Servicebenefitingareas Spatialecosystemserviceflows Quantitativeframework

Benefitsthroughspatialserviceflows

a

b

s

t

r

a

c

t

Spatialdisconnectionsbetweenlocationswhereecosystemservicesareproducedandwheretheyare usedarecommon.Todatemostecosystemserviceassessmentshavereliedonstaticindicatorsof pro-visionandoftendonotincorporaterelationswiththecorrespondingbeneficiariesorbenefitingareas. Moststudiesimplicitlyassumespatialandtemporalconnectionsbetweenecosystemserviceprovision andbeneficiaries,whiletheactualconnections,i.e.,ecosystemserviceflows,arepoorlyunderstood.In thispaper,wepresentagenericframeworktoanalyzethespatialconnectionsbetweentheecosystem serviceprovisioningandbenefitingareas.Weintroduceanindicatorthatshowstheproportionof ben-efitingareassupportedbyspatialecosystemserviceflowsfromprovisioningareas.Weillustratethe applicationoftheframeworkandindicatorbyusingglobalmapsofprovisioningandbenefittingareas forpollinationservices.Wealsoillustrateourframeworkandindicatorusingwaterprovisionandclimate regulationservices,astheyportrayimportantdifferencesinspatiotemporalscaleandprocessofservice flow.Wealsodescribethepossibleapplicationoftheframeworkforotherservicesandotherscalesof assessment.Wehighlighthow,dependingontheecosystemservicebeingstudied,thespatialservice flowsbetweenprovisioningandbenefitingareascanlimitservicedelivery,therebyreducingthelocal valueofecosystemservicesupply.

© 2014 The Authors. Published by Elsevier Ltd.

1. Introduction

Ecosystemservicescomprise‘theecosystemsconditionsor pro-cessesutilized,activelyorpassively,toproducehumanwell-being’

(MA, 2005;Fisher etal., 2009).The strictcouplingin the

defi-nitionofecosystemservicestohumanutilizationhasimportant consequences. First, there is a considerable differencebetween ‘potential’and‘actual’ serviceprovision,sinceecosystem condi-tionsandprocessesonlybecomeservicesoncetheyareactually usedor consumedby humanbeneficiaries(Fisher etal., 2009). Second,theremaybespatialdissimilaritiesbetweenareaswhere

Correspondingauthorat:P.O.Box94248,1090GEAmsterdam,TheNetherlands.

Tel.:+310205257379.

E-mailaddresses:h.m.sernachavez@uva.nl(H.M.Serna-Chavez),

nynke.schulp@vu.nl(C.J.E.Schulp),p.m.van.bodegom@vu.nl

(P.M.vanBodegom),w.bouten@uva.nl(W.Bouten),peter.verburg@vu.nl

(P.H.Verburg),m.d.davidson@uva.nl(M.D.Davidson).

servicesareproducedandwheretheyaretobeused.Thisimplies thatmostecosystemservicesare‘delivered’fromprovisioningto benefitingareasthrougheitherbiophysicaloranthropogenic pro-cesses.Howtheproductionconnectswithhumanbeneficiariesis acrucialfeatureoftheecosystemserviceconcept:theflowof ser-vicesinspaceandtime.Todate,theuseoftheterm‘ecosystem serviceflow’hasbeenambiguous,referringeithertogeneralservice provisionortothepathofdeliveryfromprovidingtobenefiting areas(e.g.,Chanetal.,2006;Fisheretal.,2011;Bagstadetal.,2013). Wedefineecosystemserviceflowsasthespatialandtemporal con-nectionsbetweenprovisioningandbenefitingareas.Thisdefinition centersecosystemserviceflowsasmeansforactualservice

provi-sion(e.g.,Reyersetal.,2010;Fisheretal.,2011;Turneretal.,2012)

and,hence,complementstheviewofserviceprovisionto bene-ficiaries.Informationonwhenandwherebenefitsareenjoyedis requiredfordesigningandapplyingeconomicinstruments,such aspayments forecosystemservices(Wunder,2007;Guariguata

andBalvanera,2009).Forinstance,thecharacterizationof

ecosys-temserviceflowsiscrucialtoidentifykeyplayersintheefforts tomitigateclimatechangeimpactsthroughReducingEmissions

fromDeforestationandForestDegradationmechanisms(REDD+,

1470-160X© 2014 The Authors. Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.ecolind.2013.11.024

Open access under CC BY license.

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Agrawaletal.,2011).Additionally,thestudyofecosystemservice flowscouldhighlightconstraintsaswellasoptionstorestorethe deliveryofservicestobeneficiaries,whichisakeytargetofAction2 oftheEuropeanUnion’s2020BiodiversityStrategy,1anda

strate-gicgoalintheConventiononBiologicalDiversity’s2020targets (‘enhancingbenefitsfromecosystemservices’,Perringsetal.,2010). Todate,studiesonecosystemserviceflowsaresparseandrather conceptual(SilvestriandKershaw,2010;Bastianetal.,2012;Syrbe

andWalz,2012).Thetemporalfeaturesofecosystemserviceflows

haverarelybeenaddressed(e.g.,Braumanetal.,2007;Bastianetal., 2012)andourunderstandingofthespatialfeaturesofserviceflows reliesheavilyonbroadcategoriesofthespatialrelationsbetween provisioningand benefitingareas(Costanza,2008; Fisheretal., 2009).Forinstance,soilformationanderosionregulationare clas-sifiedasinsituservices,becauseproviding andbenefitingareas overlapcompletely.Forstormandfloodprotection,service deliv-erydependsonproximity(Braumanetal.,2007;Costanza,2008;

Fisheretal.,2009).Forclimateregulation,thedeliveryisglobal

andomnidirectional(Costanza,2008).Recently, SyrbeandWalz

(2012)defined “the intervening spacebetween non-contiguous

providingandbenefitingareasthatinfluenceprocessvariables”as serviceconnectingareas.Thisdefinitiononlyindirectlyaddresses thespatialfeatures ofserviceflows andwithoutquantification.

This leaves a challenge quantifying the connections between

ecosystems as service providers and the beneficiariesof those services.

Spatialassessments pairingprovisioningareas withthe cor-respondingbenefitingareascanprovideinsightsintotheroleof spatialflowsinthedeliveryofaparticularecosystemservice.

Cur-rentmappingofecosystem serviceshasmoreoftenfocused on

thepotential rather thanthe actualprovision (e.g., Chanet al.,

2006;Kienastetal.,2009;Haines-Youngetal.,2012).Owingto

themisrepresentation ofactualprovision and benefits,andthe useofdifferentinputdataandmethodologies,considerable dif-ferencesintheextentofecosystemserviceprovisionandbenefits arefoundamongstudies(Eigenbrod etal.,2010;Hollandetal., 2011).Theinclusion ofthedemandside, i.e.,thecorresponding benefitandbeneficiaries,isyettobecomeanintegralpartof assess-ments(e.g.,Burkhard etal., 2012; Schulpet al.,2014).Only in afew regional-scalestudieshave thespatialfeaturesof ecosys-temserviceflowsbeenillustratedandestimated,e.g.,indirectly, bymapping‘supply anddemand’(Fisheretal.,2011; Burkhard etal.,2012),anddirectlyby,e.g.,estimatingtheperceivedbenefits fromdifferentforestedareastoagivensettlement(Palomoetal., 2012).Atlargescalesthespatialconnectionsbetweenproviding andbenefitingareasforecosystemservicesrelatedtothetradein specificcommodities,suchaswood,fishandagriculturalgoods, havewellbeenstudied(HoekstraandHung,2005;Deutschetal.,

2007;Kastneretal.,2011).Themethodologiesusedtomapand

quantifytheflowofsuchcommodities,however,areonly applica-bleforservicesthataremarketableandtrackedbyinternational tradeagencies.

Aprominentstudythatexplicitlyusedthespatialconnections betweenprovidingandbenefitingareastoevaluatespatialservice flowsistheoneconductedbyTurneretal.(2012).Theyexamined howglobalecosystemservicevaluesarerealizedandconstructed spatialmodelsofflowtoestimatethepopulationabletocapture benefits.Theirstudymakesanimportantstepbyexplicitly model-ingspatialflowstoestimatethevalueofthedeliveredbenefits.This approach,however,isdifficulttoextendandgeneralizetoother applicationsgiventheiragglomerationofindividualspatialflows intocoarsecategories.

1http://ec.europa.eu/environment/nature/biodiversity/comm2006/2020.htm.

Fig.1.Frameworktoanalyzeandquantifyecosystemserviceflows.Redcircleswith

B,representbenefitingareas,whilebluecirclewithPrepresentsprovisioningareas.

Fistheflowareawithinwhichservicesfromprovisioningareacanpotentiallybe delivered;bf isthebenefitingareanotoverlappingwithPbutwithinF;bnisthe benefitingareanot-overlappingwiththeprovisioningareaandoutsideF;bpisthe benefitingareaoverlappingwiththeprovisioningarea.

Inthisarticle,weaimtoassessthespatialflowsofindividual ecosystemservicesbymappingprovisioningareasandthe corre-spondingbenefitingareasusingagenericframework.Following thisframework,wederiveanindicatorthatcharacterizestheextent towhichbenefitingareasdependonspatialflowsfromother loca-tions.Weillustratethisapproachbymapping,attheglobalscale,a numberofillustrativeecosystemservicesthatshowdistinctly dif-ferentrelationsbetweenprovisioningandbenefittingareas.Finally, wediscusshowtheframeworkcanbeappliedinothersettingsto studytheactualprovisionofecosystemservices.

2. Materialsandmethods

2.1. Agenericframeworktocharacterizeandquantifyspatial flowsofecosystemservices

The framework we use to analyze the spatial relationships

betweenecosystemserviceprovidingandbenefitingareasis illus-tratedinFig.1.Thebluecircle(P)representsaprovisioningarea, heredefinedasthespatialunitfromwhichecosystemservicesare sourced.Thegraycircle(F)representstheflow area,delineated byamaximumorthresholddistancefromtheouterperimeterof theprovisioningarea(P)withinwhichservicescanbe‘delivered’ tobeneficiaries.Redcircles(B)representbenefitingareas,defined asthosespatialunitsinwhichecosystemservicesareneededor readilyusedorconsumed.Thebenefitingareasarefurther charac-terizedas:bp,thebenefitingareaoverlappingwiththeprovisioning area;bf,benefitingareasnotoverlappingwiththeprovisioningarea butwithintheflowarea(F);andbn,thebenefitingareanot over-lappingwiththeprovisioningareaandoutsidetheflowarea(F). Anindicatorfortheimportanceofspatialflowsforbenefitsfrom ecosystemservices(Ben.flow)canbecalculatedastheratiobetween theproportionofbenefitingareaslocatedwithintheflowarea(bf) andthetotalbenefitingareas:

%Ben.flow=

bf bf+bp

×100
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Table1

Spatiallyexplicitdatausedtodelineateecosystemserviceprovisioningandbenefitingareas.

Service Providingareas Benefitingareas

Data(units) Resolution Year Source Data(units) Resolution Year Source Pollination MODIS–continuous

vegetationcover(% herbaceousandtree cover) 0.092◦×0.092◦ 2000–2001 Hansenetal. (2003) Global distributionof agricultural crops dependingor benefitingfrom pollination 0.092◦×0.092◦ 2000 Lautenbach etal.(2012)

Globallandsystems map

0.092◦×0.092◦ 2000 Asselenand Verburg(2012) Waterprovision Long-termaverage

groundwaterrecharge rate(millionm3year−1)

0.5◦×0.5◦ 1958–2000 Gleesonetal. (2012) Annual groundwater abstractions (mil-lionm3year−1) 0.5◦×0.5◦ 2000 Gleesonetal. (2012)

Climateregulation Above-and below-groundcarbon density (Mgcarbonha−1) 0.5◦×0.5◦ 2000 Rueschand Gibbs(2008) Vulnerabilityof agricultural productionto climatechange (%changein total production) 0.5◦×0.5◦ 2000–2020 Wuetal. (2011)

Top-soilcarboncontent (Mgcarbonha−1) 0.5◦×0.52000 Hiedererand Köchy(2012) Netecosystem productivity (Mgcarbonha−1year−1) 0.5◦×0.52000 Sitchetal. (2003)

HighvaluesforBen.flowindicate:(1)ahighimportanceofthe spatialflowsforthedeliveryoftheservicetothebenefitingareas, and(2)alargerspatialsegregationbetweenprovisioningand ben-efitingareas.

We present the application of the framework and indicator

basedonlocal-scale flowsusingbiotic pollinationservices.The availableknowledgeonhabitatrequirementsandforagingranges ofpollinators(Kremen etal.,2007),aswellasthegeographical locationofcropsbenefitingfromthis service(Kleinetal.,2007;

Lautenbachetal.,2012),allowsacomprehensivedepictionoftheir

spatialflows.Themajorityofecosystemservices,however,show importantdifferencesintheirspatialcharacteristicsofprovision andflow.Thatiswhy,wealsopresenttheapplicationofour frame-workusingtwootherexamplesofecosystemserviceswherethe connectionsbetweenprovisioningandbenefittingareasare under-pinnedbydifferentprocessesandoperateatlargerscales.These additionalexamplesareonlymeantforillustration,forwhichwe selectedwater provisionandclimateregulationservices.Forall ecosystemservicesweuseglobalmapsofprovisionandbenefits

(Table1),delineatingtheflowareabasedoncurrentknowledge

(Table2),andmakingassumptionsmatchingglobalscaledata

avail-ability.AllanalyseswereconductedinArcGISv10.1.andRv2.15.2

(RDevelopmentCoreTeam,2011)software.

2.2. Local-scalespatialecosystemserviceflow:pollination

Providedtocroplandsbyunmanagedpollinators,pollination servicesrelyonthepresenceofsuitablehabitats(Kremenetal.,

2007;Lonsdorfetal.,2009).Theabundanceofpollinators,andlikely

theircontributiontoeffectivecroppollination,decreasesas isola-tionfromsuitablehabitatsincreases(Rickettsetal.,2008;Garibaldi etal.,2011).Tomapprovisioningareasataglobalscaleweused thepercentageofvegetationcoverinnaturalandsemi-naturalland covercategoriesaspotentialhabitatforunmanagedpollinators.We usedremotelysenseddataonherbaceousandtreecover(MODIS,

ContinuousVegetationCover; Hansenetal.,2003)within natu-ralandsemi-naturalgloballandsystemscategories(Asselenand

Verburg,2012).Theselandsystemcategoriesincludeddense

for-est,naturalgrassland, andmosaiccover offorestand grassland withextensivecroplandorwithfew livestock.Herbaceous and treecoverwithintheotherlandsystemcategorieswasassumed tobemoreintensivelymanagedand, hence,unlikely tocontain significantpollinator habitat.For thedense forestcategory, we onlyincludedforestedgesinthevicinityofagriculturalareasas partofpollinatorhabitat(Garibaldietal.,2011).Forestedgeswere selectedbyneighborhoodanalysis,removingthosecellsentirely surroundedbythesamelandsystemcategory.

Localcasestudieshavedeterminedthresholdsforhabitatcover thatenableoptimalpollinationtosurroundingcroplands(Kremen

etal.,2004;Rickettsetal.,2008).Becauseofdifferencesinspatial

scalesandtypesofdataused,suchthresholdscouldnotbereadily appliedtoourstudy.Therefore,wefirstassessedtherelationship betweentreeandherbaceouscoverandthecroplandcover occur-ringwithinadistanceof2km.The2kmthresholdwasusedsinceat greaterdistancesvisitationratesfromunmanagedpollinatorsare likelytobenegligible(Rickettsetal.,2008;Garibaldietal.,2011).

Thisassessmentshowedthat witha treeandherbaceous cover

of45%mostofthesurroundingcroplandareas(95%±5%)would occurwithinadistanceofapproximate2km(AppendixA).With theresults,werefinedtheglobalprovisioningareasofpollination servicesasthosewithtreeandherbaceouscover≥45%(hereafter ‘potentialpollinationhabitat’).

Areasbenefitingfrompollinationservicesweredefinedasthose globalareaswherecropsdependingorprofitingfrombiotic polli-nationareproduced.Thesebenefitingareasweredelineatedusing aglobalmapofthedistributionof60cropsdependingor profit-ing,tovaryingextents,frompollination(Lautenbachetal.,2012). Wethenevaluatedtheextentofthespatialoverlapbetweenthe

provision and benefit maps (bp). The spatial flow to

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Table2

Keyecosystemserviceprovisioningandbenefitingareas,andthespatiotemporalcharacteristicsofflowamongthem.

Ecosystemservice Areasofecosystemservice Flow (Human)Benefits

Provision Benefits Spatiotemporalscale Processallowing Pollination Naturaland

semi-natural habitats •Grassland •Shrubs •Heathland •Forestpatches •Forestedges Agriculturalareas dependentonor profitingfrombiotic pollination

Rapidandlocal(range restricted)

-Foragingrangesof pollinatorspecies -Pollentransportationand deposition

-Abundanceand effectivenessofpollinating organisms

-Direct:increasedand/or realizedcropyield -Indirect:intermediaryin otherservices,e.g., reproductionofplants involvedinclimate regulation

Waterprovisionforirrigation Locationof groundwater basinsandtheir annualrecharge Agriculturalareas dependenton groundwaterirrigation Basin-wide.Water availabilityis precipitation-dependent (seasonality) -Infrastructurefor extraction,distributionand irrigation

-Basinrechargerate, whichdependson:

•Soilinfiltrationcapacity •Topography

-Cropyield -Monetary

Climateregulation Primarily,tropical (incl.peatforests) andborealforest (hotspots) Various Here:tropical, sub-tropicaland mid-latitude agriculturalareas vulnerabletochanges inprecipitationand temperature Globalnon-excludable, andlong-term (decades) Local-to-regional,and rapid(days,months)

-Vegetationandsoil interactionswiththe atmosphere,suchas:

•Photosynthesis •Soilandplant evapotranspiration,soil heterotrophicrespiration •Albedo

•Plantaerosolproduction •Heathexchange -Globalatmospheric mixing

-Avoidedorameliorated:

•Decreasedcropyieldsin tropical,sub-tropicaland mid-latitudes

•Decreasedwater availability

•Increaseinvector-borne exposureandwater-borne diseases

•Increasedfloodrisk •Increasedmortalityform heatstress

pollinatorhabitatareas2kmineverydirectionandre-evaluating theextentofspatialoverlapwithcroplandareas(bf).

2.3. Large-scaleecosystemserviceflows

2.3.1. Groundwaterprovision

Toillustratetheanalysisandquantification ofregional-scale ecosystemserviceflows,wemappedgroundwaterrecharge(i.e., provision)andabstraction(i.e.,benefit)forcropirrigation follow-ingourframework(Fig.1).Astheaimofthisparticularexample isnotanexhaustivequantificationofserviceprovisionandflow, we didnotaccount for othertechnical solutionsthat influence theavailabilityofwaterforirrigation,suchasrainharvestingor theuseof reclaimedwastewater.Forgroundwaterprovisioning andbenefitingareasweusedglobalmapsoflong-termrecharge andabstractionsforirrigation(inmillionm3year−1;Gleesonetal.,

2012),respectively.Asthesedataarequantitativeandofthesame

entity,we estimatedto whatextent groundwaterrechargecan

meetabstractionsforirrigation.Weassumedthatspatialflowsof availablegroundwatertoareasofabstractionsoccuronlywithin basins,becausetransportofgroundwaterisconstrainedtowithin basinsandtothepresenceofinfrastructureforextractionand dis-tribution.Onlymajorgroundwaterbasins,whicharethosewith amappedrechargerate>2mmyear−1 (BGRandUNESCO,2008), weretakenintoconsideration.

Foreachglobalgroundwaterbasin,weanalyzedtheextentto which abstractionsare covered byavailable recharge.Thiswas calculatedas thebasin-widedifferencebetweentheaverageof abstractionsandrecharge,whichrepresentsthetotalofbp+bf.By doingthis,allrechargeisallocatedtoabstractionsregardlessthe locationofwhereboth occurred.Toillustratetheapplicationof ourframeworkforregionalflowsinmoredetail,wecalculatedthe amountofabstractionsforirrigationthatcanbecoveredby spa-tialflowsofgroundwater(bfandBen.flow)inthreebasins,i.e.,the greatplains(US),Ganges(India)andnorthChinabasin.Theselected groundwaterbasinsillustratethreedifferentcaseswherebfdiffers

inmagnitudetomeetabstractionsforirrigation.Foreachbasin, weusedtheaverageofrechargeandabstractionstocalculatethe extenttowhich(1)rechargemeets‘on-the-spot’(i.e.,withinthe samegrid-cell)abstractions(bp),and(2)theremainingrecharge availabletoflowwithinthebasin(bf).Thesetwoestimateswere thenusedtocalculatetheBen.flowforeachofthethreebasins.

2.3.2. Climateregulation

The provision of climate regulation includes

biogeochemi-cal(e.g.,carbonsequestration)andbiophysicalmechanisms(e.g., evaporative cooling) (Foley et al., 2003; Chapin et al., 2008).

As quantifications of the biophysical mechanisms are scarce

(Anderson-Teixeiraetal.,2012),weonlyaccountedforthestored

andsequesteredcarboninvegetationandtopsoilasrepresentative ofaclimateregulationservice.Forthispurpose,aglobalcarbon densitymap (Mgha−1)wasconstructedbyaddingtheamounts ofcarbonstoredinlivingvegetation(above-andbelow-ground;

RueschandGibbs,2008)andintopsoil(0–30cmdepth;Hiederer

and Köchy,2012).From outputof theLPJ-DynamicGlobal

Veg-etationmodel(Sitch etal., 2003), we selectedareaswitha net ecosystemproductivity(NEP,inMgha−1year−1)greaterthanzero, i.e.,netadditionstotheterrestrialcarbonpool.Areaswithinthe top25% quartileofthecarbon densitymap wereoverlaidwith thenetsinksfromtheNEPmaptodelineatehotspotsofprovision. Thishotspotsmapwasusedasprovisioningareasofclimate reg-ulationandrepresents(1)areasofhighabove-andbelow-ground carbondensity,(2)netcarbonsinks,and(3)theareaswhereboth overlapped.

Climateregulationserviceshaveawiderangeofindirectand directbenefits,beyondoff-settinganthropogeniccarbonemissions. For illustration purposes, and because of a lack of global-scale mapsofmultiplebenefitsfromclimateregulation,weonly con-sideredagriculturalproductionasabeneficiary.Weusedamap

of agricultural production vulnerable to changes in

tempera-tureandprecipitationunderabusiness-as-usualclimatechange scenario (Wu et al., 2011). This map shows projected changes

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Fig.2. Pollinationserviceflowfrompotentialhabitattocropland.(A)Spatialsimilaritiesbetweenprovisioningandbenefitingareas(24.7%,bp),whichentailsthatwithin overlappingcellsthepotentialhabitatcovercanenablepollinationserviceflowstothesurroundingcroplands.(B)Theincreaseinspatialsimilarities(31%,bp+bf)by

accountingfortheflowareaforunmanagedpollinatorstoadjacent,non-overlapping,croplandareas.About68%oftheareaswithcropsprofitingordependingonbiotic pollinationareoutsidetheflowareas(bn).

in total production of wheat, rice, soybeans and maize for the 2000–2020period(asa percentage changeintotal production; (Wuetal.,2011).Theseagriculturalareasrepresentthe produc-tionoffourofthetop-tenglobalagriculturalcommodities(FAO stats:http://faostat3.fao.org/home),whichwillbenefitindirectly

fromthebiogeochemicalmechanismsofclimateregulation.We

onlyselectedareaswhereadecreaseinagriculturalproductionis projected.Toassesstheproportionofbenefitingareasdepending onspatialflowsofclimateregulationservices,weestimatedthe overlapbetweenprovisioninghotspotsandbenefitingareas(bp). Theflowarea(F)forthedeliveryofindirectbenefitsthrough car-bonsequestrationandstoragecanbeconsideredglobal(Table2), thusallareasthatdonotoverlapwithprovisioninghotspots(bp), arewithinflowarea(bf).Itisimportanttonote,however,thatin thiscasetheserviceflowisindirectandthatimpactsofclimate regulationmaybespatiallydependent.

3. Results

3.1. Local-scalepollinationserviceflows

Oftheglobalcroplandareasthatwouldbenefitfrom pollina-tion,24.7%overlapwiththeprovisioningareas(bp).Fortheseareas, thepollinationserviceflowswould occurwithintheareaitself

(‘Potentialserviceflow’inFig.2A).Additionally,another7.7%(bf)is supportedbypollinationserviceflow(Fig.2B).Thislastdelineation ofserviceflowsassumesthattheconnectivityanddistributionof habitatwithintheprovisioninggridcells is sufficienttoenable flowstoadjacentopenlandcoverwithlittleornopollinator habi-tat.Overall,thisanalysisindicatesthat32%oftheglobalpollination servicesdeliveredtocroplandscanberealized(bp+bf).Abouta quarterofthisglobalserviceswouldberealizedthroughspatial flows(Ben.flow=24%).Thisleavesabout68%oftheglobal agricul-turalareasoutsidetheflowareaofunmanagedpollinators(bnin

Fig.1).Theregionswherepollinationflowsfrompotential habi-tatareunlikelyarethelarge-scale,homogeneous,croplandcover in,e.g.,MidwestUSA,andEastAsia(Fig.2B). Theseareaslikely relyonartificialserviceprovisionbyusing,e.g.,domesticatedbee colonies.

3.2. Largescalespatialflows 3.2.1. Groundwaterserviceflows

A global map illustrating the range of differences between groundwaterabstractionsforirrigationandrecharge(bp+bf)and for all major groundwater basins in the world is presented in

Fig.3A.GroundwaterbasinsinthearidregionsofnorthernMexico, SaudiArabiaandIrandisplaynegativewaterbalances,duetotheir

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Fig.3. Large-scaleecosystemserviceflows.(A)Groundwaterprovisionforirrigation.Netbasin-widebalanceafteraverageabstractionsforirrigationweresubtractedfrom theaveragerecharge(millionm3year−1).Resultsaccountforbpandbp,asallrechargeisallocatedtoabstractionsregardlesstheirlocation.Temperateandmid-latitude

regionsshowgreaterdemandsonserviceflowstofulfilltheabstractionsforirrigation.Boxesdelineatetheselectedbasinsfordetailedanalysisofbenefitsthroughspatial serviceflows(inTable3)(B)Globalclimateregulationservice.Spatialconnectionsbetweenvulnerableagriculturalareasandhotspotsforclimateregulationservices.Overlap isconsiderable,with21%ofglobalagriculturalareasoverlappingwithhotspotsofprovision(bp),whiletheremaining79%areas(bf)relyonspatialflows.

lowrechargeratesandlargeabstractions.Groundwaterbasinsin theCongoandAmazonregionsdisplayhighpositivenet

ground-water balances due to their high natural recharge and scarce

abstractions.

DetailedexamplesofthecalculationofBen.flowindicatorare givenforthreebasins(Table3).Thesebasinsdifferintheamount ofabstractionscovered byoverlapping recharge,and byspatial flowsofrecharge.Thegroundwaterabstractionsthatarecovered with‘on-the-spot’recharge(bp)rangedfrom7%to82%,whilethe remainingrechargethatwouldbeabletocoveradditional abstrac-tions(bf)rangedfrom2%to21%.Ben.flowrangedfrom10%to75%. Inallcases,agroundwaterdeficitremained.

Table3

Ben.flowindicatoranditscomponentsforthreeillustrativegroundwaterbasins. NomenclatureafterframeworkinFig.1.

Basin bp bf %Ben.flow

USAhigh-plains 8% 2% 20%

UpperGanges 82% 9% 10%

NorthChina 7% 21% 75%

bp:theamountofabstractioncoveredby‘on-the-spot’recharge.

bp:theamountofabstractioncoveredspatialflowsofrecharge.

3.2.2. Climateregulationserviceflow

The areas delineated as hotspots of provision of climate regulation services mainly comprise tropical and boreal forest areas(Provisioninghotspotsin Fig.3B).These forestedareasare recognizedasimportantbiophysicalandbiogeochemicalhotspots ofglobalclimateregulation(HouseandBrovkin,2005).The ben-efitingagriculturalareasshowimportantclustersincentraland EasternEurope,ChinaandtheUSA.Decreasesintotalproduction upto88%areexpectedintheseregionsuponclimatechange(Wu

etal.,2011).

Thespatialdisconnectionsbetweenprovisioningandbenefiting areasareconsiderable,withonly21%ofbenefitingareas overlap-pingwithprovisioningareas(bp,Fig.3B).Asagriculturegenerally doesnotprovideclimateregulationservices,thisoverlapislikely duetotheinclusionofaprojectedincreaseintotalsownareaswhen evaluatingfuturevulnerabilityofagriculturalproduction(Wuetal., 2011).Inthisexampleallbenefitingareasarewithintheflowarea (bp+bf=100%),giventhenon-rivalandnon-excludable character-isticofprovisionandflow(Costanza,2008).Oftheglobalbenefiting areas,79%ofthebenefitswouldberealizedthroughspatialservice flows(Ben.flow).

Thespatialflowsofclimateregulationservicesarebywayof global atmospheric connections,which entailnotransport lim-itations. Giventhetime neededfor atmosphericmixing (Meehl

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etal.,2007;Bastianetal.,2012),theglobalbenefitsthroughcarbon sequestrationandstoragebyecosystemsarelaggedintime.This iswhytheindirectglobalbenefitsfromclimateregulationservices aresegregatednotonlyinspacebutalsointime.

4. Discussion

4.1. Aframeworkforecosystemserviceflows

Weintroducedandillustratedaframeworktocharacterizeand analyzeecosystemserviceflowsbetweenprovisioningand bene-fittingareas.Weusedpollinationservicesandtwoothercasesto illustratekeyvariationsin theextentandlocation ofbenefiting areasaswellasinspatialflows(Table2).Fortheseexampleswe usedglobal-scaledatatodelineateecosystemserviceprovisioning andbenefitingareas,usingsimplifiedrepresentationsof ecosys-temservice‘supply’and ‘demand’thatfit availabledataat this scale.Weusedpollinationservicestopresenttheassessmentof spatialflowsfollowingourframework(Fig.2).Bycomplementing theassessment ofpollinationserviceflowswiththeillustration

of water provisionand climateregulation flows,we were able

toshow how depending on the service analyzed, provisioning

andbenefitingareascanhaveintrinsicallydifferentcharacteristics, whichimpliesthatspatialflowsarerequiredtoenjoybenefitsfrom mostecosystemservices.Thespatialinformationneededto delin-eateprovisioningand benefitingareasfollowingourframework isreadilyavailableformostecosystemservices,whichallowsthe extensionofthestudyonspatialflows.InTable4weoutlinethe applicationoftheframeworktodifferentecosystemservices.

Thegenericframeworkwepresentbuildson,andextends,the fewstudiesthathaveexplicitlyillustratedorevaluatedthespatial overlapbetweenecosystemserviceprovisionandbenefitsat land-scape(e.g.,SyrbeandWalz,2012),regional(e.g.,Fisheretal.,2011;

Palomoetal.,2012),continental(e.g.,Maesetal.,2011)orglobal

scale(e.g.,Turneretal.,2012).Theframeworkisaparsimonious approachtostudythespatialconnectionsbetweenprovisioning andbenefitingareas,andcanbereadilyusedforthemajorityof ser-vicesgivencurrentdataavailability.TheBen.flowindicatorprovides asimplemeasuretoidentifytheproportionofareawhere bene-fitsaredependentonspatialflows.ThecalculationoftheBen.flow indicatordependsonthedelineationofaflowarea(FinFig.1).This delineationofflowareaallowstheidentificationofthoseareasthat dependonspatialserviceflowstoenjoybenefitsandisafirststep towardthecharacterizationandquantificationofspatialflowsand actualecosystemserviceprovision.Theanalysesherepresented highlighthow theflow area(F)is characteristicofeach ecosys-temservice,and canbeunderpinnedby theforaging rangesof mobileorganisms(asinpollination),basinareaandinfrastructure (asinwaterforirrigation),orbiophysicalprocesses(asinclimate regulation).

Intheanalysisoflocal-scaleflows,unmanagedpollinatorsliving insuitablenaturalandsemi-naturalhabitatsprovidepollination servicestonearbycroplands.Giventhespatialsegregationbetween habitatandcropland(Kremenetal.,2007),benefitingareasare,by definition,completelydependentonpollinationserviceflowsfrom adjacenthabitats.Thestudyofserviceflows,therefore,requires accountingforathresholddistancefromprovidingareasto iden-tifythecropareasthatcanbenefitfrompollinationservices(sensu FinFig.1).Forpollination,suchinformationisavailablefromfield studies(Rickettsetal.,2008;Garibaldietal.,2011).Here,weused suchthresholddistancetoestimatethepercentageofbenefiting areasthatarecoveredbyspatialflows.Thedistinctionbetween serviceflowsthatwouldoccurinareaswherebothprovisionand benefitingareascanbefound(bp),andflowsbetweenadjacent pro-visionandbenefitingareas(bf)butwithintheflowarea(F)showed

howmorethanhalftheglobalcroplandareasthatwouldbenefit frompollinationareoutsidetheflowareafrompotentialhabitats (Fig.2).Thesefeaturesofspatialflowalsohighlightthe possibil-itiesfor improvingdeliverytobenefiting areas:by restoringor re-distributinghabitatcoveranditsconnectivity,orrelocatingthe benefitingcroplandareas.

Toillustratethecharacterizationofspatialflowsthatoperate atlargerscalesfollowingthesameframework,weusedexamples ofwaterprovisionandclimateregulationbecausetheyrepresent differentprocessesunderpinningprovisionandflow.Inthesetwo cases,ecosystem serviceflow is establishedthrough hydrologi-calprocesseswithingroundwaterbasinsand,indirectly,through theclimatesystem,respectively.Theirrigationinfrastructurewill affectthedistanceanddirection(sensuF)thatavailablerecharge follows tomeet abstractions. For our illustrative examples,we assumedthattheinstalledinfrastructureisabletodeliverservices throughoutthebasintoestimatebp+bfforeachglobal groundwa-terbasin(Fig.3A)andBen.flowindicatorinthreecases(Table3). For theindirectbenefitsfromclimateregulationservices,there areknownspatialandtemporalsegregationsbetween provision-ing and benefiting areas (Fig. 3B). In this case, the perceived

benefits through carbon sequestration and storage cannot be

attributedtoaparticularprovisioningarea(P),becauseoftheflows throughtheglobalclimatesystem,whichmakes the differenti-ation ofbenefiting areasintobp or bfnot crucial. Ontheother hand,for thedirect benefitsof climateregulation through bio-physical mechanisms,suchas evaporative cooling (Foley et al., 2003),theneighboringprovisioningareas(P)arelikelythemain contributors. The direct, smaller-scale, flowsof climate regula-tionserviceswerenotincludedinouranalysis,becauseageneral maximumor thresholddistanceof a flow area(F)is noteasily derived.

Inthisstudyweintegratedallbenefitingareastoanalyzespatial serviceflows.Aspresented,theframeworkcanalsobeappliedto studythebenefitingareasindividually,whichwillthenhighlight thosethatrelymoreonspatialflowstobenefitfromecosystem services.Thischaracterizationwouldconsiderthebenefitingareas equally, regardless any difference in size or distancefrom the outerperimeterofprovisioningorflowareas.Thedifferentiation betweenbenefitingareaswouldbeattributedtothedifferencesin overlapwithprovisioningareas(bp),withtheflowarea(bf)and, hence,intheBen.flowindicator.

Theframeworkmayalsobeextendedtotheprovisionof multi-pleservices,withknowntrade-offsandsynergies.Suchapplication wouldrelyonthepossibilitytodelineatea‘common’flow area andtheidentificationofbeneficiaries.Inspiteofthedifferences betweenecosystemservices,somedosharekeycharacteristicsin theirprovisionandspatialflow.Forinstance,thecharacteristicsof provisioning,benefitingandflowareasforpollinationservicesare similartothoseforbiologicalcontrol(ThiesandTscharntke,1999;

Ruschetal.,2013),whichfacilitatestheanalyzesofbothservices

withourframework.

4.2. Caveatsandfutureresearchneeds

A proper characterization and quantification of ecosystem

serviceflowsrequirestheidentificationofthespatiotemporal fea-turesin provisionandflow,aswellasthequantificationofthe processesinvolved.Ourframeworkandindicatorcanserveasfirst approximationtoevaluatetheimportanceofspatialserviceflow (asinFig.2)andtoquantifythedeliveredbenefits(asinTable3). Theillustrationsinthispaperbasedonglobaldatadid,however, notexplicitlyaddresstheindividualflowpathsbetween provision-ingandbenefittingareas.The‘ServicePathAttributionNetwork’ (SPAN)frameworkfromthe‘ArtificialIntelligenceforEcosystem Services’project(ARES;Villaetal.,2009;Bagstadetal.,2013),helps

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Table4

Illustrationofframeworktoevaluatespatialserviceflowstobeneficiaries.NomenclatureofspatialserviceflowframeworkafterFig.1.

Ecosystemservices F bf bp bn pa

Pollinationandbiologicalcontrol

P

bpbf

B

F

bn

Relativetothe homeandforaging rangeofthemobile organism(s) providingthe service Adjacent (non-overlapping) croplandareas, dependentonor benefitingfrom theseservices

Areaswithboth suitablehabitatfor providingagents andbenefiting cropland Dependentor benefiting croplandareas outsidethe flowarea Areasof suitable, naturaland semi-natural, habitat

Waterprovisionforirrigation

B

P

P

B

bp

P

F bf b f

Basinarea Areaswithwater abstractionsandno orlittlewater availability—rel.to naturalrecharge rates

Areaswithboth water availability—rel.to recharge—and abstractions None,withina particularbasin Areasthat experience natural groundwater recharge

Moderationofextremeeventsanderosionprevention

P

bp

B

bf bf

B

F

Areasbetweenthe extremeeventand thebenefiting areas,e.g.,for erosionprevention, uplandvegetated areasasthereisa slope-dependent relationship Areasof settlementsor infrastructure vulnerableto extremeevents

Areaswithboth provisionand benefiting settlementsor infrastructure Dependson degradation processes considered Area,naturalor semi-natural, thatbuffers extremeevents orpreventssoil erosion,e.g. wetlands, floodplainsand reservoirscan bufferfloods Provisionoffoodandrawmaterials

B

B

B

B

P

P

B

bp bf F bf bf bf Delineatedby anthropogenic processesof storage, commercialtrade, aswellasdemand

Areaswherethe exported productionis delivered Domestic consumptionor use Demandingor necessityareas thatcannot import Total production Climateregulation

P

B

bp

B

bf bf F

Global Areasthatdonot overlapwith provisioning—high carbondensityor carbonsink—areas

Areasthatboth provideandbenefit fromclimate regulation

None Areaswithhigh carbondensity andnetcarbon sequestration rates

connectingbiophysicalmeasuresofserviceprovisionwithhuman useandconsumption,byconnectingbothspatiallocations.SPAN alsoincludesmodelsofspatialflowandallowsanapproximationon theuncertaintyofserviceprovisionandvalueofbenefits(Silvestri

andKershaw,2010;LogsdonandChaubey,2013).Thisapproach,

explainedinBagstadetal.(2013)remainsdata-and knowledge-intensive,whichstronglylimitsitsapplicabilityatlargescalesand formanyecosystemservicesandareaswhererelevantdataisnot available.

Tohelpimprovingtheanalysisofspatialflowswesuggest build-ingfutureextensionsfollowing landscapemetrics.Forinstance,

landscape proximity and connectivity metrics can help assess

whichbenefiting areasrelyonwhich provisioningareasfor the delivery of services, given a defined distance from provision-ingareas(F).Thelattercanalsohelpassessingthepermeability andresistancetoservicedelivery,assuchcomplementary

land-scape metrics can consider the constraints posed by defined

anthropogenic or natural barriers within a given spatial flow

area.

Coupledtothespatialserviceflowsthatcanbeassessedwith ourframework,therearekeytemporalfeaturesofserviceprovision andflow.Todate,explicitrecognitionoftemporalfeaturesof provi-sionandflowisonlyslowlyemerging(Braumanetal.,2007;Bastian etal.,2012),andsuchfeaturesareyettobeintegratedinecosystem

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serviceassessments(Brownet al.,2005;Kochet al.,2009).The integrationof temporalfeatures intoassessmentsis notreadily supportedbyavailableframeworksgivenalsothevastdifferences intemporalfeaturesamongecosystemservices(Rodriguezetal., 2006).Someunderstandingonthetemporal features, however, maybeobtainedfromtheprocessesdeterminingtheserviceflows, asanalyzedinourframework.Forinstance,local-to-regional

ben-efits of climate regulation, as influenced by water and energy

exchangesbetweenvegetationandatmosphere,areexperienced

rapidly,withindaystomonthsbasis(Pielkeetal.,1998).Onthe otherhand,theglobalindirectbenefitsthroughthemodulation ofatmosphericconcentrationsofgreenhousegasesaresegregated fromprovisionintime,giventhetimerequiredforatmospheric mixing(Pielkeetal.,1998;Meehletal.,2007).Toillustratethis,we highlighttheimportanceofthedelineatedprovisioninghotspots (Fig.3B),basedonaverageNEP,aspast,presentandfutureservice providers.Thehotspotsarepastserviceproviders,fortheprocesses thatleadtohighcarbondensitiesinlivingvegetationandsoils; present,forthecontinuationofsequestrationandthestabilityof currentcarbonstocks;andfuture,sincethelong-termstabilityof theterrestrialcarbonpool,andfluxesofenergyand greenhouse-gasescanmitigate,orameliorate,someoftheexpectedimpacts ofglobalclimatechange.Acknowledgingaswellasaccountingfor thesetemporalfeaturesofclimateregulationservices,aswellas foranyotherecosystemservice,iskeytoassesstheactualbenefits fromecosystems.Table2describesthetemporalcharacteristicsof flowfortheecosystemservicesdiscussedinthepaper.

Thedeliveryofecosystemservicesandthelinksbetween pro-visioningandbenefittingareasasquantifiedinourframeworkalso hasacriticalsocio-ecologicaldimension.Therefore,itrepresents

akey componenttomake theecosystemserviceconcept

oper-ational(Kremenand Ostfeld,2005;Nicholson etal.,2009).This isillustratedin astudyonecosystemserviceflowsprovidedby

Palomoet al.(2012).Theyidentifiedand estimatedtheamount

ofecosystemservicesperceivedassuchbythelocalpopulation surroundinga nationalprotected areaand otherforestedareas. Theyexplicitly used theconcept of ecosystem service flowsto illustratetheextenttowhich benefiting areasenjoyedservices fromneighboringanddistantprovidingareas.Inthiscase

account-ing for ecosystems service flows helped to support thedesign

ofbetter management approaches,evaluation of trade-offs and informeddecision-makingbydeterminingwheretheservicesfrom aprovisioningareaarebeingdeliveredtoparticular

beneficiar-ies(GuariguataandBalvanera,2009;SilvestriandKershaw,2010;

Crossman et al., 2013).We envision that the quantification of

ecosystemserviceflows,asprovidedbyourframework,mayaid supportingdecisionmakinginsimilarsettingselsewhere.

5. Conclusions

Theanalysesinthis paperhighlight howthespatial charac-teristicsoftheflow betweenprovisioningand benefittingareas arespecifictoeachservice.Thestudyofecosystemserviceflows requiresguidelinesforassessmentsthatareappropriateforall ser-vicesaswellasallspatialscales.Thegenericframeworkforanalysis ofspatialflowsofecosystemservices,aspresentedinthispaper, canbeafirstbasis tosupportsuchassessments.Understanding thespatiotemporalcharacteristicsofproduction,flowanddelivery tobeneficiaries,andaccountingtheprocessespinpointingthem, arecrucial to make theecosystem service conceptoperational. Ourframework mayaidtheevaluationof optionstorestoreor improvethedeliveryofbenefitsnowandinthefaceofglobal envi-ronmentaland land-usechange.Thestudyofecosystemservice flowsiskeyinassessmentsaimingtodesigneconomicinstruments basedonactualserviceprovision,andforthecharacterizationand

managementofgeopoliticaldisparitiesbetweenserviceproviders andbeneficiaries.

Acknowledgements

Wethanktwoanonymousreviewersfortheirhelpfulcomments onanearlierversiononthismanuscript.WealsothankWu Wen-binforfacilitatingdata.H.M.S.C.andM.D.thanktheNetherlands OrganizationforScientificResearch(NWO)forprovidingfunding (InnovationalResearchIncentivesScheme,VIDI).P.V.wouldliketo thanktheFP7projectOPERAsforfinancialsupport.C.J.E.S. acknowl-edgesERA-NETBiodiversaprojectCONNECTforfinancialsupport. WearegratefultoNigelHarleforbrushinguptheEnglishinthis manuscript.

AppendixA. Supplementarydata

Supplementarymaterial relatedto this articlecanbe found, in the online version, at http://dx.doi.org/10.1016/j.ecolind.

2013.11.024.

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