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Quantifying Resilience of Multiple Ecosystem Quantifying Resilience of Multiple Ecosystem

Services and Biodiversity in a Temperate Forest Services and Biodiversity in a Temperate Forest

Landscape Landscape

Elena Cantarello Bournemouth University

Adrian C. Newton Bournemouth University

Phillip A. Martin Bournemouth University

Paul M. Evans Bournemouth University

Arjan Gosal Bournemouth University

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Citation Details Citation Details Cantarello E, Newton AC, Martin PA, Evans PM, Gosal A, Lucash MS. (2017). Quantifying resilience of multiple ecosystem services and biodiversity in a temperate forest landscape. Ecology and Evolution. 00:1–15.

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Authors Authors Elena Cantarello, Adrian C. Newton, Phillip A. Martin, Paul M. Evans, Arjan Gosal, and Melissa S. Lucash

This article is available at PDXScholar: https://pdxscholar.library.pdx.edu/geog_fac/78

Ecology and Evolution. 2017;1–15.  | 1www.ecolevol.org

Received:9February2017  |  Revised:17August2017  |  Accepted:16September2017DOI: 10.1002/ece3.3491

O R I G I N A L A R T I C L E

Quantifying resilience of multiple ecosystem services and biodiversity in a temperate forest landscape

Elena Cantarello1  | Adrian C. Newton1 | Philip A. Martin1 | Paul M. Evans1 |  Arjan Gosal1 | Melissa S. Lucash2

ThisisanopenaccessarticleunderthetermsoftheCreativeCommonsAttributionLicense,whichpermitsuse,distributionandreproductioninanymedium,providedtheoriginalworkisproperlycited.©2017TheAuthors.Ecology and EvolutionpublishedbyJohnWiley&SonsLtd.

1DepartmentofLifeandEnvironmentalSciences,BournemouthUniversity,Poole,UK2DepartmentofEnvironmentalScienceandManagement,SRTCB1-04D,PortlandStateUniversity,Portland,OR,USA

CorrespondenceElenaCantarello,DepartmentofLifeandEnvironmentalSciences,BournemouthUniversity,Poole,UK.Email:ecantarello@bournemouth.ac.uk

Funding information ThisresearchisfundedbyNERCviatheBiodiversity&EcosystemServiceSustainability(BESS)program.Projectref.NE/K01322X/1.TheopinionsandviewsexpressedheredonotnecessarilyrepresentthoseofthemainBESSprogramanditsdirectorate.

AbstractResilienceisincreasinglybeingconsideredasanewparadigmofforestmanagementamongscientists,practitioners,andpolicymakers.However,metricsof resiliencetoenvironmentalchangearelacking.Facedwithnoveldisturbances,forestsmaybeableto sustain existing ecosystem services and biodiversity by exhibiting resilience, oralternativelytheseattributesmayundergoeitheralinearornonlineardecline.Herewe provideanovelquantitativeapproachforassessingforestresiliencethatfocusesonthreecomponentsofresilience,namelyresistance,recovery,andnetchange,usingaspatiallyexplicitmodelofforestdynamics.Underthepulsesetscenarios,weexploredtheresilienceofnineecosystemservicesandfourbiodiversitymeasuresfollowingaone-off disturbance applied to an increasing percentage of forest area. Under thepulse+presssetscenarios,thesixdisturbanceintensitiesexploredduringthepulsesetwerefollowedbyacontinuousdisturbance.Wedetectedthresholdsinnetchangeunderpulse+pressscenariosforthemajorityoftheecosystemservicesandbiodiver-sitymeasures,whichstartedtodeclinesharplywhendisturbanceaffected>40%ofthelandscape.Thresholdsinnetchangewerenotobservedunderthepulsescenarios,with theexceptionof timbervolumeandgroundfloraspecies richness.Thresholdsweremostpronouncedforabovegroundbiomass,timbervolumewithrespecttotheecosystemservices,andectomycorrhizalfungiandgroundfloraspeciesrichnesswithrespect to the biodiversitymeasures.Synthesis and applications. The approachpre-sentedhereillustrateshowthemultidimensionalityofstabilityresearchinecologycanbeaddressedandhowforestresiliencecanbeestimatedinpractice.Managersshouldadoptspecificmanagementactionstosupporteachofthethreecomponentsofresil-ienceseparately,asthesemayresponddifferentlytodisturbance.Inaddition,man-agementinterventionsaimingtodeliverresilienceshouldincorporateanassessmentofbothpulseandpressdisturbancestoensuredetectionofthresholdresponsestodisturbance,sothatappropriatemanagementinterventionscanbeidentified.

K E Y W O R D S

biodiversity,climatechangeimpacts,dieback,disturbance,ecosystemservices,forestcollapse,forestmanagement,grazing,LANDIS-II,multiplestressors,socio-ecologicalresilience

2  |     CANTARELLO ET AL.

1  | INTRODUCTION

Forests have evolved in the presence of natural disturbances, suchas drought, windstorms, wildfire, insect, and disease outbreaks(Greenberg&Collins,2015;Walker,1999).However, the increasingfrequency, extent, and severity of disturbances are altering forestcommunitiesoutsidetherangeswithinwhichtheyhaveevolvedandadapted(Usbecketal.,2010;Weed,Ayres,&Hicke,2013).Asaresultofthecurrenthighrateofglobalenvironmentalchange,theintensi-ficationofforestdisturbancesislikelytocontinue,whichmayinhibittheabilityofspeciestokeeppacethroughtheirevolutionaryadapta-tionprocesses(Trumbore,Brando,&Hartmann,2015).Asaresult,thefutureofglobalforests,theirassociatedbiodiversity,andtheprovisionofecosystemservicestohumansocietyareuncertain(Trumboreetal.,2015). These services include provisioning (e.g., timber), regulating(e.g.,carbonsequestration),supporting(e.g.,nutrientcycling),andcul-tural(e.g.,recreation)benefits(MEA2005).Whenexpressedinmone-taryunits,thesecombinedserviceshavebeenestimatedtobeworth5,264 and 3,013 international $/ha/year in tropical and temperateforests,respectively(deGrootetal.,2012).Forestsalsocontainmorethan80%ofterrestrialspecies,providinganimportantsourceofbio-diversityworldwide(FAO2012).Ifspeciesarenotabletoadapttotheintensifieddisturbancesthatarewidelyoccurring,themaintenanceofbiodiversityandthesustainableprovisioningofecosystemservicestosocietycouldbeundermined(Lindneretal.,2010).

Recent researchhas focusedonunderstanding the trajectoryofforestsystemresponsestodisturbances,includingtheroleofthresh-oldsandchanges inecological state (Allen,Breshears,&McDowell,2015).MillarandStephenson(2015)theorizedfourpatternsofforestresponsetocumulativedisturbances:Response(1)correspondstoaresilientforest,abletosustainexistingecosystemservicesandwherenothresholdsarereached;response(2)and(3)bothrepresentaforestcrossingathreshold,leadingtotheconversiontoanewforesttype.Under(2),theforestisstillabletosustainprimaryecosystemservices,whereasunder(3)thechangesaresubstantialenoughthatecosystemservice delivery declines. Response (4) corresponds to a forest thatfollowingthecrossingofathresholdtransformstoanonforesttype,losingforestfunctionanditscapacitytodelivermostforestecosystemservices.Giventhatdisturbancesarespatiallyexplicitprocessesplay-ingakeyroleinforestecosystemdynamics,landscapeapproachesarerequired todeterminewhether thereareabrupt thresholdsormoresubtle changes in these systems and to evaluate the trajectory offorest recovery (Seidl etal., 2011;Trumbore etal., 2015). Followingadisturbance,someforestfunctionssuchasphotosynthesisandtran-spirationcanrecoverwithinadecade,whereasitcantake>100yearsforbiomassandbiodiversity to recover (Martin,Newton,&Bullock,2013; Spake, Ezard,Martin,Newton,&Doncaster, 2015;Trumboreetal., 2015). If we can anticipate an approaching forest transition,guidancecanbeprovidedonhowmanagementcanbeadaptedsothatbiodiversityandecosystemservicedeliveryismaintained.

One response strategy to intensifieddisturbances is toenhanceecosystem resilience,which has been the focus of recent literature(Biggsetal.,2012),andenvironmentalpolicy(Newton,2016;Newton

&Cantarello,2015).Resilience is intuitivelyunderstoodas theabil-ityofanecosystemtowithstandortolerateaperturbation.However,theprecisedefinitionofresilienceinanecologicalcontexthasbeenthe focusof substantialdebate (Newton&Cantarello,2015).Manydifferent definitions have been proposed, including engineering re-silience (the time required for a system to return to an equilibriumpoint followingadisturbanceevent;Pimm,1984)andecological re-silience(theamountofdisturbancethatasystemcanabsorbbeforetransitioningtoanotherstablestate;Brand&Jax,2007).Promotingresilience through forestmanagement is particularly relevant in thecontextofintensifieddisturbances,becausethestochasticnatureofsuchdisturbancesmakesthemdifficulttopredict(Seidl,2014).Inad-dition,disturbancesdonotactinseparation,butcaninteractinwaysthat increase their impact. For example, warmer temperatures areexpectedtoamplifytheoccurrenceofpestspecies,andinteractionswithdroughtcanfurtheracceleratetreemortalityininsect-damagedtrees(Daleetal.,2001).

Despitetheemergingimportanceofresilienceasanewparadigmof forest ecosystem management among scientists, practitioners,andpolicymakers(Millar&Stephenson,2015;Newton&Cantarello,2015; Seidl, Spies, Peterson, Stephens, & Hicke, 2016), theoreticaldiscussionsofresilienceconceptsstillgreatlyoutpacetheirpracticalapplication (Biggsetal.,2012).Thiscanbeattributed toknowledgegaps regarding the underlying mechanisms, and the difficulties inmeasuringresilienceinwaysthatareappropriateforinformingman-agement (Biggsetal.,2012;Reyeretal.,2015).Recentresearchhasidentifiedsomeapproachesthatcanpotentiallybeusedtomeasureresilience. Methods include rapid assessment approaches (Nemecetal.,2014),thequantificationoffunctionaldiversityandresponsedi-versity(Angeleretal.,2014),discontinuityapproaches(Nash,Graham,Jennings,Wilson,&Bellwood,2016),andthresholdsanalysis(Standishetal., 2014).However,very fewstudieshaveproposedquantifiablemetrics,andeveninthesecases(Nashetal.,2016),theyare largelylimitedtofreshwaterandmarineecosystems.Potentialwaysforwardforterrestrialecosystemssuchasforestsincludeassessmentofdiffer-entelementsofresilience,suchasresistanceandrecovery (Newton& Cantarello, 2015; Nimmo, Mac Nally, Cunningham, Haslem, &Bennett,2015),whichshouldbestandardizedandcomparedacrosssystemsandfieldsofresearch(Hodgson,McDonald,&Hosken,2015).Measuresofresilienceshouldalsotake intoaccountthespatialandtemporal components of disturbances, which are rarely considered(Allenetal.,2016).

Hereweprovideanovelquantitativeassessmentapproachforas-sessingtheresilienceofforestecosystemsthataccountsforthespa-tiotemporalpatternsofdisturbancesandfocusesonthreemeasurableresiliencecomponents:resistance,recovery,andnetchange(Nimmoetal.,2015).Weexploretowhatextentaforestthatiscurrentlyun-dergoingdieback(Martin,Newton,Cantarello,&Evans,2015)willberesilienttofuturedisturbancesusingaspatiallydynamicmodelsup-portedbyempiricaldata,simulatingboth“pulse”(suddendisturbance)and“press”(sustaineddisturbance)dynamics,followingtheconceptualframeworkpresented inCollinsetal. (2011). Specifically,weaim toquantify(1)towhatextentforestecosystemservicesandbiodiversity

     |  3CANTARELLO ET AL.

areresistanttopulseandpressdisturbances;(2)towhatextentforestecosystemservicesandbiodiversityrecoverfrompulseandpressdis-turbances;(3)whetherperturbedforestecosystemservicesandbio-diversityareabletopersistovertime;and(4)whetherthereareanythresholdsobservedinlossofecosystemserviceprovisionandbiodi-versitywhendisturbanceintensifiesovertime.Specifically,wetestedthehypothesisthatallthreecomponentsofresiliencewerecorrelatedwitheachother.

2  | MATERIALS AND METHODS

2.1 | Study area

TheNewForestNational Park is located in southern England (UK;50°52′00″N 1°34′00″W) and extends over 57,100ha (Newton,2010).Itsexceptionalimportancefornatureconservationisreflectedinitsmanydesignations,rangingfromnational-scalelegislation(e.g.,SiteofSpecialScientific Interest—SSSI), toglobal-scaledesignations(Cantarello, Green, & Westerhoff, 2010). The Park is also one ofthemostvisited inBritainwithover13milliondayvisitseachyear(ForestryCommission2008).Thevegetationiscomposedofancientpasture-woodlands,lowlandheathland,valleymirecommunities,acidgrassland, the network of rivers and streams, and permanent andtemporaryponds.NowhereelseinlowlandEnglanddothesehabitatsoccurtogetherandatsuchalargescale(Cantarelloetal.,2010).TheuniquecharacteroftheNewForestisstronglydependentonitshis-toryasamedievalRoyalhuntingreserveandthelong-termsurvivalofatraditionalcommoningsystem,with largepopulationsofdeerandfree-roaminglivestock(principallyponiesandcattle)interactingwiththeprocessesofecologicalsuccession(Newton,Cantarello,Tejedor,&Myers, 2013). The New Forest has been remarkably resilient asa socio-ecological system having withstood profound political andsocioeconomicchanges in societyover the last900years (Newton,2011); however, some woodland elements of this system are cur-rentlyundergoingmajorchangesinstructureandcomposition(Martinetal.,2015).Possiblecausesofdiebackhavebeenattributedtotheco-occurrenceofmultiplestressors,suchasdroughtsandnovelpath-ogenicfungi(Martinetal.,2015).

Our research focused on the broadleaved woodlands of theNational Park,which are highly valued for their biodiversity, recre-ational opportunities and amenities (Newton, 2010), and managedwith thedualpurposesof (1) conservingandenhancing thenaturalbeauty,wildlife, and cultural heritage and (2) promoting opportuni-ties for theunderstandingandenjoymentof thespecialqualitiesofthe Park by the public, as set out by the EnvironmentalAct 1995.Managementdecisionmakingplaysacrucialpartinmeetingthedualstatutorypurposes.ThesewoodlandswereidentifiedbyselectingtheSSSImanagementunitswith>50%ofthebasalarearepresentedbybroadleavedspeciesandcomprised6,909ha(AppendixS1).Theyin-clude ancient pasture-woodlands originating in the18th century orearlier, shapedby thepresenceofgrazingand traditionalpollardingoftrees(Peterken,Spencer,&Field,1996),and“enclosed”woodlandsthathistoricallyhavebeenmanagedfortimberproductionandhave

at timesbeenprotectedby stock fences. In addition to their abilityto provide timber, today enclosed woodlands are increasingly rec-ognized for theirnatureconservationand recreationvalue (ForestryCommission2008).Thetreebiomass isdominatedbyQuercus robur (47%)andFagus sylvatica(33%),withanunderstoreyofIlex aquifolium (9%)andanadmixtureofBetula pendula (4.5%),Crataegus monogyna (1.3%), andTaxus baccata (0.9%).Details of the species characteris-ticsfoundinthebroadleavedwoodlandswerebasedonNewtonetal.(2013) (Table1).Themain soil types are surfacewater gleys (84%),groundwatergleys(9%),brownearths(7%),andpodzols(0.2%)basedontheNationalSoilResourcesInstitute(2007)andPyattetal.(2003).Thelocalclimateistemperateoceanicwithamean(±SD)annualpre-cipitation of 832±150mm andmean (±SD) annual temperature of10.17±0.64°Cbetween1957and2014(MetOffice2015).

2.2 | Study design

Twomainsetsofscenariosweredevelopedtoexploretheimpactof increasing disturbance on the provisioning of ecosystem ser-vices and biodiversity: “pulse” and “pulse+press” sets. Under thepulse set, forest dynamics following a one-off disturbance, suchasawindthroweventorpathogenattack,wereexploredusinganincreasing percentage area towhich the disturbancewas applied(0%,20%,40%,60%,80%,and100%).Thedisturbancecommencedafter5yearsofthesimulationand lastedfor1year,randomlyre-movingthedominanttreespecieswith>10cmdiameteratbreastheight(dbh).Underthepulse+pressset,thesixdisturbanceinten-sitiesexploredduringthepulsesetwerefollowedbyacontinuousdisturbance, simulating thecurrent levelsofbrowsingof treesbylivestockanddeer(Newtonetal.,2013).Intotal,12scenariosweresimulatedandeachscenariowas replicated three times,owing tothe stochasticnatureofdisturbanceevents.Due to the lowvari-ationbetweenthethreereplicatesforeachscenario,AGBofeachreplicatewas less than±5%of themeanof replicates at theendofthesimulation.Scenariosweredevelopedoveratimeframerel-evant to decisionmaking (100years; Forestry Commission 2016)andwererunata50-mresolution(orcellsize).

All scenarios were simulated using a spatially dynamic model(LANDIS-II v.6.0; Scheller etal., 2007), designed to simulate thespatiotemporal dynamics of forested landscapes through the incor-poration of a number of ecological processes including succession,disturbances, and seed dispersal (Scheller etal., 2007). Followingguidanceforapplicationofthemodel (Scheller&Lucash,2014),thelandscapewasdividedinto25ecoregionsonthebasisofelevationandsoiltype,basedonNewtonetal.(2013).Mortalityeventsweremod-eledusing theharvesting successionextension (BaseHarvestv2.2).Tree establishment, forest succession, and C andN dynamicsweremodeledusingtheCenturySuccessionExtension(v4.0;Schelleretal.,2012),whichisderivedfromtheoriginalCENTURYsoilmodel(Parton,Anderson,Cole,&Stewart,1983).Themodelwasparameterizedandcalibratedusingempiricaldatafromthesiteandthescientificlitera-ture.ProceduresforgatheringthemodelinputsandmodelcalibrationaredescribedinAppendixS2.

4  |     CANTARELLO ET AL.

Threepropertiesof resiliencewere calculated, followingNimmoetal. (2015): resistance, recovery time, and net change. Resistancewasmeasuredasthemagnitudeofchangeofeachvariable(i.e.,eco-system service or biodiversitymeasure) caused by the disturbance,usingtheindexproposedbyOrwinandWardle(2004):

where D0isthedifferencebetweenthecontrolvariable(C)attimet0,andthedisturbedvariable(P)afteraone-offdisturbancehasoccurred(i.e.,endofyear5;Figure1a).Theindexwasboundedby0and+1,withavalueof+1showingmaximumresistanceandlowervaluesshowingless resistance. In thosecaseswhereD0>C0 (indicatingan increase

inthevalueofthevariable),theindexwassetto1toavoidtheindexgiving a negative value of resistance (Figure1b). Recovery timewasmeasuredasthetimetakenforeachvariabletoreturntothepredis-turbancevalue(Pimm,1984).Maximumrecoverytimewas100yearstocoincidewiththetimeframeofthescenarios,relevanttodecisionmaking(ForestryCommission2016).Inthosecaseswhereresistance(tl)wassetto1,recoverytimewasconsiderednonapplicableandthereforewasnotcalculated.Itisworthnotingthatrecoverytimeisreferredtoas“resilience”byGrimmandWissel(1997)andDonohueetal.(2016).Systemswithshorterrecoverytimesaremoreresilientthanthosewithlongerrecoverytime(Donohueetal.,2016).Netchangewasmeasuredbycomparingeachvariableattheendofthesimulationwiththepredis-turbancevalue,followingNimmoetal.(2015).

(1)resistance (tl)=1−2D0

C0+D0

TABLE  1 DetailsofthespeciescharacteristicsencounteredinthebroadleavedwoodlandsoftheNewForestNationalPark

00 Long Mat ShT FiT EffSD MaxSD VRP Min VRP Max VRP P- FiR

Acer campestre 200 10 3 1 80 120 1 10 120 None

Acer pseudoplatanus 150 12 4 1 120 400 1 10 100 None

Alnus glutinosa 250 12 3 1 120 200 1 10 200 None

Betula pendula 160 18 2 1 200 1,600 1 10 120 None

Carpinus betulus 250 20 4 1 90 130 1 10 150 None

Castanea sativa 300 35 3 1 300 700 1 10 250 None

Corylus avellana 80 10 4 1 300 700 1 10 80 None

Crataegus monogyna 150 4 2 1 300 700 1 10 100 None

Fagus sylvatica 500 55 5 1 300 700 1 10 300 None

Frangula alnus 80 3 2 2 300 700 1 10 30 None

Fraxinus excelsior 200 17 3 1 90 120 1 10 200 None

Ilex aquifolium 300 10 3 1 300 700 1 10 300 None

Malus sylvestris 130 8 2 1 300 700 1 10 100 None

Picea abies 300 40 2 1 100 120 0 0 0 None

Picea sitchensis 300 22 2 1 100 120 0 0 0 None

Pinus nigra 350 22 2 1 100 150 0 0 0 None

Pinus sylvestris 300 12 2 1 100 1,000 0 0 0 None

Populus alba 250 7 2 1 500 1,600 1 10 250 None

Prunus spinosa 60 4 2 1 300 700 1 10 60 None

Pseudotsuga menziesii 400 12 2 3 120 380 0 0 0 None

Quercus robur 500 60 2 1 300 700 1 10 400 None

Quercus rubra 200 22 4 3 300 700 0 0 0 None

Salix cinerea 90 35 2 1 1,000 1,600 1 10 70 None

Sorbus aria 150 6 2 1 300 700 0 0 0 None

Sorbus aucuparia 100 15 2 1 300 700 1 10 100 None

Sorbus torminalis 100 13 4 1 300 700 1 10 100 None

Taxus baccata 3,000 20 4 1 300 700 0 0 0 None

Tsuga heterophylla 400 15 2 1 120 160 0 0 0 None

Viburnum opulus 50 5 2 1 300 700 1 10 40 None

Long,longevity(years);Mat,ageofsexualmaturity(years);ShT,shadetolerance(1–5);FiT,firetolerance(1–5);EffSD,effectiveseeddispersaldistance(m);MaxSD,maximumseeddispersaldistance(m);VRP,vegetativereproductionprobability(0–1);MinVRP,minimumageofvegetativereproduction(years);MaxVRP,maximum age of vegetative reproduction (years); P-FiR, postfire regeneration form (none, resprouting, or serotiny). Valueswere based onNewtonetal.(2013).

     |  5CANTARELLO ET AL.

Linear mixed models (LMMs) were fitted to estimate the rela-tionshipsbetweenresistance,recoverytime,andnetchangeandthedegree of disturbance for each ecosystem service and biodiversitymeasure.Toimprovemodelsperformanceandinterpretabilityofco-efficients, thedegreeofdisturbancewasstandardizedpriortoanal-ysisusing themethods inSchielzeth (2010).Models fitted includednull (M = B0+Re), linear (M=B0+D B1+Re), and quadratic terms(M=B0+D B1+D B2

2+Re),withscenarioreplicatesasarandomef-fect(whereMisthemetricofinterest,B0isthemodelintercept,Disthedegreeofdisturbance,B1 andB2 areparameters relating to theslope, andRe is a randomeffect that identifies thedifferentmodelreplicates).ModelselectionwasperformedbycomparingmodelsAICc,withthebestmodelhavingthelowestAICc.ThecoefficientsandthenatureofthebestmodelswererecordedalongwithR2valuesfollow-ingthemethodsofNakagawaandSchielzeth(2013).Avariablewasconsideredtoshowathresholdifthebestmodelincludedaquadraticterm,indicatinganonlinearrelationship,anditsmarginalR2valuewas>0.9.Thesecriteriawerebasedonwhatweconsidered tobegoodpractice, but it should be noted that use of different criteriamighthave yielded different results. A paired Wilcoxon signed rank test

wasusedtotestdifferencesbetweenthepulseandthepulse+pressvalues of resistance, recovery time, and net change. Spearman cor-relationanalysesbetweenresistance,recoverytime,andnetchangewere performed for each of the variables. All analyses were con-ductedinR3.2.2.(RCoreTeam,2015),usingthelme4package(Bates,Mächler,Bolker,&Walker,2014)formixedmodels,andtheqdapTools(Goodrich,Kurkiewicz,Muller,&Rinker,2015)forcorrelations.

2.3 | Ecosystem services and biodiversity data sets

Nineecosystemservicesandfourbiodiversitymeasureswereselected,basedontheirimportanceinforestecosystems:abovegroundbiomass(Mg/ha),aestheticvalue,commerciallyharvestedfungirichness,netni-trogen(N)mineralizationabsorbedtoionicresins[(μgNO3

−+NH4+)/

capsule)], recreation value, soil nitrogen stock (MgN/ha), soil respi-ration rate (μmolsm2/s), timber volume (m3/ha), total carbon stock(MgC/ha), and species richness of ectomycorrhizal fungi (ECM),groundflora,epiphyticlichens,andtrees(Figure2).

Abovegroundbiomass,totalCstock,andsoilNstockwerecal-culated from theCentury Extension of LANDIS-II.Timbervolume

F IGURE  1  (a)Exampleoftheresistance(RS),recoverytime(RT),andnetchange(NC)ofaresponsevariabletoapulseandpressdisturbance.Theblackupperlinerepresentsthecontrolvariable(C)andtheredlinerepresentstheperturbedvariable(P);(b)ChangesinRSwithchangesinD0 (i.e.,C0–Pl),whenC0isfixedat40.AdaptedfromShadeetal.(2012)andOrwinandWardle(2004)

(a) (b)

F IGURE  2 Diagramsynthesizingthe13variablesselected(outsidecircles)andthestudydesignemployedtomeasuretheirresilience(insidegraph).Forexplanationofgraphlabels,seeFigure1.Forfulldescriptionofthestudydesign,seetext

6  |     CANTARELLO ET AL.

wascalculatedbymultiplyingtheabovegroundbiomassofthespe-cies importantfortimberproduction (i.e.,Quercus roburandFagus sylvatica)fortheirrespectivenominalspecificgravity(Jenkinsetal.,2011).

Net N mineralization, soil respiration rate, species richness ofcommerciallyharvestedandectomycorrhizalfungi,groundflora,and

epiphytic lichensweremeasured in the field along twelve replicategradients of temperate forest dieback, from intact forest to grass-land. Recreation and aesthetic values were measured by conduct-ingaquestionnairesurveyof200visitorsdistributedequallyacrossten car parkswithin the SSSI New Forest boundary (seeAppendixS3). For eachof thesevariables, LMMswere fitted toestimate the

F IGURE  3 Ecosystemservicesandbiodiversitymeasuresofdifferentdegreesofdisturbancesimulatedbypulseandpulse+presssetscenariosovera100-yeartimespan.Valuesrepresentlandscapelevelmeansweightedbyecoregions(incolor)andstandarddeviations(ingray)acrossthreereplicates.(a)Aes,aestheticvalue;CHF,commerciallyharvestedfungirichness;NMnetNmineralization;(b)Rec,recreationvalue;SN,soilnitrogenstock;SRR,soilrespirationrate;TVol,timbervolume;TC,totalcarbonstock;(c)ECM,ectomycorrhizalfungirichness;GF,groundflorarichness;EL,epiphyticlichenrichness;andTrees,treespeciesrichness.Notethatforillustrativepurposes,onlyfourofthe12scenariosarepresentedhere.Thefirsttwocolumnsillustratetheleastandthemostsevereofthepulsesetscenarios(0%and100%pulsedisturbance),whereasthelasttwocolumnsillustratetheleastandthemostsevereofthepulse+pressscenarios(pressonlyand100%pulsedisturbancecombinedwithpress).Seetextforafulldescriptionofthescenarios

     |  7CANTARELLO ET AL.

relationshipsbetweenabovegroundbiomass(AGB)andthevariables.Avalueforeachofthe50-mcellsassociatedwithbroadleavedwood-landswasthenderivedfromthemodel-averagedcoefficientsofthe

LMMsfitted.Recreationandaestheticvalues,whichwereassessedonascoreof1-5,weretransformedtoproportionsbydividingallval-uesby5andperformingalogittransform,basedonWartonandHui

F IGURE  3  (Continued)

8  |     CANTARELLO ET AL.

(2011).Forvariablesofspeciesrichness,aPoissonerrorstructurewasused,whileGaussianerrorswereusedforallothervariables.FurtherinformationabouttheLMMsfittedispresentedinAppendixS4.

3  | RESULTS

3.1 | Ecosystem services and biodiversity spatial and temporal variation

All of the ecosystem services and biodiversity measures stud-ied varied spatially between ecoregions. Most variables (10/13)

demonstrated a suddendecrease after thepulsedisturbancewasapplied and started to increase back to a predisturbance valuewithtime.Conversely,netNmineralizationandgroundflorarich-nessdisplayedanincreaseafterthepulsedisturbancewasapplied,whereastreespeciesrichnessdemonstratedlittlechangewithtime(Figure3).

3.2 | Resistance

The majority of the ecosystem services studied (8/9) showed alinear decline in resistancewith increasing disturbance intensity.

F IGURE  3  (Continued)

     |  9CANTARELLO ET AL.

OnlynetNmineralizationratewasresistanttodisturbance.TimbervolumeandAGBdemonstratedsteeperdeclines,whereasdeclinesinsoilnitrogenstockandrespirationratewerelessrapid.Halfofthebiodiversitymeasures (2/4)showeda lineardecline in resist-ance with increasing disturbance intensity, while the other halfwereresistantovertime.Overall,resistancemeasuresdidnotdif-fer between pulse and pulse+press sets of scenarios (Figure4,AppendixS5).

3.3 | Recovery

All of the ecosystem service and biodiversity measures showedan increase in recovery time with increasing disturbance intensity.Recovery time increased relatively rapidly for timber volume andrichness of commercially harvested fungi, and relatively slowly forepiphyticlichensrichnessandrecreationvalue.Recoverytimeforsoilnitrogenstockandtimbervolumedidnotdifferbetweenpulseandpulse+press scenarios. For all of the other ecosystem service andbiodiversitymeasures,valuesdivergedbetweenthetwosetsofsce-nariosafterdisturbancewasappliedto>20%ofthelandscape.Inall

butonecase,ecosystemserviceandbiodiversitymeasuresdidnotre-covertopredisturbancevaluesathighdisturbancelevels>60%),evenafter100years(Figure5;AppendixS5).

3.4 | Net change

Under the pulse set, the majority of the ecosystem services andbiodiversitymeasures (10/13) demonstrated an ability to recovertopredisturbancevaluesafter100years.GroundflorarichnessandnetNmineralizationshowedanincreaseinnetchangewithdistur-banceintensity,whereastimbervolumeshowedadecrease.Underthepulse+press set,net changeexhibiteda threshold response inthemajorityofthecases(11/13).Inninecases,netchangestartedto decline sharply when disturbancewas applied to >40% of thelandscape, whereas in two cases net change showed a quadraticincrease with disturbance intensity. Soil nitrogen stock and treespecies richnesswere bestmodeled by nullmodels.Overall,withtheexceptionofsoilnitrogenstock,allofthenetchangemeasuresdiffered between pulse and pulse+press scenario sets (Figure6;AppendixS5).

F IGURE  4 Ecosystemservicesandbiodiversityresistancealonganincreasingdegreeofdisturbancesimulatedbypulseandpulse–presssetscenariosover100years.Valuesrepresentlandscapelevelmeansandstandarddeviationsacrossthreereplicates.SeeSection2.2formoredetails.AGB,abovegroundbiomass;Aes,aestheticvalue;CHF,commerciallyharvestedfungirichness;NMnetNmineralization;Rec,recreationvalue;SN,soilnitrogenstock;SRR,soilrespirationrate;TVol,timbervolume;TC,totalcarbonstock;ECM,ectomycorrhizalfungirichness;GF,groundflorarichness;EL,epiphyticlichenrichness;Trees,treespeciesrichness

10  |     CANTARELLO ET AL.

3.5 | Relationship between resistance, recovery, and net change

Underthepulsescenarios,allofthenonresistantecosystemser-vicesandbiodiversitymeasures(10/13)demonstratedanegativecorrelationbetweenresistanceandrecoverytime.Onlyinthecaseof timber volume, resistance and recovery timewere correlatedwithnetchange(positivelyandnegatively,respectively).Similarlytothepulsescenarios,underthepulse+pressscenarios,10of13of the measures demonstrated a negative correlation betweenresistanceandrecoverytime.Resistancewasalsopositivelycor-relatedwithnetchangein11of13cases.Recoverytimewasneg-ativelycorrelatedwithnetchangeinnineof13cases(AppendicesS5andS6).

4  | DISCUSSION

Despitetheemergenceoffosteringresilienceasanewparadigmofforestecosystemmanagement(Millar&Stephenson,2015;Newton&Cantarello, 2015; Seidl etal., 2016), quantifiablemetrics of resil-iencetochangingdisturbanceregimesareseverelylacking.Ourstudyprovides a quantitative assessment approach for forest ecosystemsthatfocusesonthreemeasurableelementsofresilience,namelyre-sistance,recovery,andnetchange,andexploresthespatiotemporalpatternsofdifferentdisturbanceintensities.Ourapproachtakesthe“multidimensionality” of stability concepts into account, which hastwodimensions:(1)severalstabilitypropertiesneedtobeassessedinparalleltoprovideacomprehensiveunderstandingofthemechanismsunderpinningasystem(Donohueetal.,2016;Grimm&Wissel,1997;

F IGURE  5 Ecosystemservicesandbiodiversityrecoverytimealonganincreasingdegreeofdisturbancesimulatedbypulseandpulse+presssetscenariosover100years.Valuesrepresentlandscapelevelmeansandstandarddeviationsacrossthreereplicates.Notethatvaluesonthereferencelineindicatearecoverytime>100years.RecoverytimeforNM,GF,andTreesisomittedasnotapplicable.SeeSection2.2formoredetails.Forexplanationofplotlabels,seeFigure4

     |  11CANTARELLO ET AL.

Pimm,1984);(2)thereisaneedtoexploretheresponseofsystemstodifferenttypesofdisturbance,observedatdifferentspatialandtem-poralscales,forseveralstatevariablesandreferencedynamics.Thishasbeendubbed“ecologicalchecklist”byGrimmandWissel(1997).Themoststrikingresultofourstudywasthedetectionofthresholdsinnetchangeunderapulse+pressscenarioforthemajorityoftheecosystem services and biodiversitymeasures. In our specific case,net change started to decline sharply when disturbance affected>40%ofthelandscape.Thresholdsinnetchangewerenotobservedunderthepulsescenarios,withtheexceptionoftimbervolumeandgroundfloraspeciesrichness.ThresholdsweremostpronouncedforAGBandtimbervolumewithrespecttotheecosystemservices,andECMandgroundfloraspeciesrichnesswithrespecttothebiodiver-sitymeasures.

Threshold responses to environmental change are currently thefocus ofmajor scientific interest and societal concern (Mace,Hails,Cryle,Harlow,&Clarke,2015;Oliveretal.,2015;Steffenetal.,2015),aswhenathresholdiscrossed,asmallperturbationmayleadtomajorecologicalchange.However,theevidenceforsuchthresholdsinter-restrial ecosystems is currently limited. Our results indicate that ifthetemperateforestexaminedherecontinuestobesubjectedtothebrowsingintensitythatitexperiencesatpresent,nomajorchangesin

ecosystem service provision and biodiversity are forecast (responsetypeiofMillar&Stephenson,2015).However,whenbrowsingiscom-binedwithapulsedisturbancethatcauses treemortality, suchasawindthroweventorpathogenattack,theforestdisplaysathresholdresponse.Ifpulseandpressdisturbancesareappliedto≤40%ofthearea,theforestisstillabletosustainprimaryecosystemservices(re-sponsestype2),whereaswhenthesedisturbancesaffect>40%oftheforestarea,recoveryandnetchangeinbothbiodiversityandecosys-temservicesissignificantlyaltered(responsetype3).

Themechanismsunderlyingecologicalthresholdsareunclear,butimplytheexistenceofpositivefeedbacksbetweenvariablesinfluenc-ingthesystem(Schefferetal.,2012).Thethresholdsidentifiedinthisstudymay be attributable to positive feedbacks between the pulseandpressdisturbances.WhilethepulsedisturbancereducesAGB,thepressdisturbancelimitstreerecruitment,whichcouldaccelerateade-cline in future treegrowth.Manywood-pastureshabitats inEuropesufferfromregenerationfailure,primarilybecauseofhighherbivorepressure(Bergmeier,Petermann,&Schröder,2010).Ifthelossoflargetreesisnotcompensatedbyregenerationandbrowsingintensitiesre-mainhigh,theresultwillbeconversionofwoodlandtoopenpastures,aprocessthatwehavedocumentedinourstudysiteinsomelocations(Martin etal., 2015).Results from long-termmonitoringdata inour

F IGURE  6 Ecosystemservicesandbiodiversitynetchangealonganincreasingdegreeofdisturbancesimulatedbypulseandpulse+presssetscenariosovera100-yeartimespan.Valuesrepresentlandscapelevelmeansandstandarddeviationsacrossthreereplicates.SeeSection2.2formoredetails.Forexplanationofplotlabels,seeFigure4

12  |     CANTARELLO ET AL.

siteshowedthatoveraperiodof50years,basalareadeclinedby33%andjuveniletreedensitieswerereducedby~70%(Martinetal.,2015).ThethresholdinAGBobservedherewaslesspronouncedthanintim-bervolume,asthespeciesimportantfortimberproductioncoincidedwiththedominantspeciesthatwereextirpatedbythedisturbances.As disturbance intensifies, relatively shade-tolerant dominant treespeciesarereplacedbypioneerspecies(Newton,2010),allowingAGBto recovermorequickly compared to timbervolume.The thresholdobservedinECMrichnesscouldbeattributabletothedeclineintreerootdensityassociatedwiththelossofAGBandsupportsthefindingsofTreuetal.(2014)whoshowedECMrichnessdecliningalongagra-dientoftreemortality.ECMrichnessisfoundtobedependentontreerootdensity, leafarea,andasufficientsupplyofcarbohydrate fromthetreehost(Yarwood,Myrold,&Hogberg,2009)andcandecreasefollowingtreeharvestingandinsectattacks(Teste,Lieffers,&Strelkov,2012;Treuetal.,2014).InthepresenceofanECMrichnessdecline,treespeciesmaysuffersignificantreductioningrowthandregenera-tion,resultinginapositivefeedbackbetweenECMandAGBdecline(Simardetal.,2012).Thethresholds ingroundflorarichnesscanbeexplainedbywell-knownpatternsof successional changes in forestecosystems(Bormann&Likens,1979).Forexample,Zenner,Kabrick,Jensen, Peck, and Grabner (2006) demonstrated that ground florarichnessincreasedproportionallyalongagradientofharvestintensity,inaccordancewiththeresultsfoundinourstudy.

The current study presents a few issues that should be borneinmindwhen interpreting the results obtained.With regard to theecosystemservicesandbiodiversitymeasuresexplored,totalcarbonstock, soilnitrogenstock,and treespecies richnesswerecalculatedfromtheCenturyExtensionofLANDIS-II,whichcommontoalleco-logicalmodelsissubjecttoanumberoflimitationsandassumptions(Appendix S2).AGBwas used as indicator for the remaining of theecosystemservicesandbiodiversitymeasures.ThiswasbasedondatacollectedduringpreviousresearchundertakenbyRef.Evansetal.(inpress)andGosal(2016)whomeasuredarangeofecosystemservicesandbiodiversitymetricsalongagradientofwoodlanddieback,usingbasalareaasameasureof foreststructure.BasalareaandAGBareamong the indicatorscommonly found tobe significantly related tobiodiversity and ecosystem services (Cantarello & Newton, 2008;Harrisonetal.,2014).However,inourstudy,someoftheecosystemservices(namelyaestheticandrecreationvalue,netNmineralization,andsoilrespirationrate)showedalowmarginalR2inthelinearmixedmodelsfitted(AppendixS4),andtherefore,theresultsforthesemea-suresneedtobeconsideredwithcaution.Furtherresearchisrequiredtoexaminetheresilienceofthesemeasures.

Further,itshouldbenotedthatthereareotherissuestoconsiderwheninterpretingtheresultsobtained.Here,wequantifiedresiliencethroughthethreemetricsofresistance,recovery,andnetchange.Thisrepresentsanadvanceoveradoptingaone-dimensionalperspectivetoassessingresilience,whichasnotedbyDonohueetal. (2016)hasbeenafeatureofmanypreviousstudies.,However,othercomponentsof resilience couldhavebeen adopted, such as asymptotic stability,variability and persistence (Pimm, 1984), or robustness (Donohueetal.,2016).

Despitethese limitations,ourresultshaveanumberof implica-tionsformanagement.CurrentforestmanagementintheUKisguidedbynationalandregionalforestrypolicies(ForestryCommission2010;EuropeanUnion, 2015), aswell as specificmanagement objectivesforindividualsites(ForestryCommission2016).InsitessuchastheNewForest, inwhichmany species are dependent on themainte-nanceofearlysuccessionalcommunities,sustainingadisturbancere-gimecanbecriticaltoconservingbiodiversityvalue(Newton,2010).However,ourresultsindicatedthatwhencurrentbrowsingintensitiesarecombinedwithapulsedisturbance,suchasawindthroweventorpathogenattack,thresholdseffectscanoccur,leadingtoacceleratedlossofecosystemservicesandbiodiversity.Today,thereisincreasingconcernthatmanyecosystemservicesprovidedbyforestsinEuropewillbeaffectednegativelyincomingdecades,owingtotheincreasedincidenceofwindthrow,barkbeetle,andwildfires(Seidl,Schelhaas,Rammer,&Verkerk,2014).Emergingdiseasesincludingacuteoakde-cline,askdieback,chestnutblight,Dutchelmdisease,pinewilt,andJapanese larchdiseasearealsocausing increasing treemortality inmanypartsoftheworldincludingtheUK(Boyd,Freer-Smith,Gilligan,&Godfray,2013;Pautasso,Aas,Queloz,&Holdenrieder,2013).Thecurrentresultshighlighthowsuchdifferentperturbationscanpoten-tiallyinteract,leadingtothelossofbothbiodiversityandecosystemservices.

Managers could potentially use measurements of resilience,and identificationofthresholdsofresponsetodisturbance,tode-velop interventions specifically intended to increase forest resil-ience. Inthecasestudyexaminedhere,specificrecommendationstoenhanceresilience intheshort–mediumtermcould include: (1)protecting tree regeneration from high herbivore pressure,whichlimitsrecruitmentoftrees,and(2)limitingthecurrentmanagementpracticeof tree cutting andheathlandburningoutside thewood-landunitssothattreesmightcolonizenearbygrasslandandheath-landandadapttothenewenvironmentalconditions.However,thiswould mean accepting woodlands collapse in some parts of thelandscapeandexpandinotherareas,whichcouldresultinpotentialnegative impacts on biodiversity and ecosystem service provisionatthe landscapescale.Forexample,nativeancientwoodlandsarehighlyvaluedfortheirbiodiversity,andtheirlosscouldhaveimpli-cations formany species of conservation interest that dependonthem (Bergmeier etal., 2010; Plieninger etal., 2015). Biodiversityloss also has the potential to alter ecosystem functioning (Duffy,2009). Other recommendations to increase forest resilience havebeenproposedincludingplantingresilienttreespeciesthattolerateavarietyofclimatesand theselectionanduseofclones resistantto pests and diseases (Fares, Mugnozza, Corona, & Palahi, 2015;ForestryCommission2015).However,asnotedbyNewton(2016),these recommendations would undermine current efforts to haltbiodiversityloss.Forexample,treespeciesdiversificationcoulden-danger theexceptional biodiversityvalueof ancientnativewood-lands (Bruun, Heilmann-Clausen, & Ejrnaes, 2015). Managementpractices that preserve natural ecosystem processes are likely tobemore effective in supporting forest biodiversity and resilience(Jonsson,Pe’er,&Svoboda,2015).

     |  13CANTARELLO ET AL.

These results also have implications for how resilience is bestmeasured.Here,followingGrimmandWissel(1997)andNimmoetal.(2015), we assessed resilience as three independent components.However,wealsoexaminedwhetherthesedifferentcomponentswerecorrelatedwitheachother,totestwhethertheycouldpotentiallybecombinedintoasinglemeasureorindexofresilience.Inmostcasesunder the pulse+press scenarios, resistance and net change werepositivelycorrelated,whereasresistanceandrecoverywerenegativelycorrelated.Howeverunderthepulsescenarios,resistanceandrecov-eryweregenerallynotcorrelatedwithnetchange.Thisindicatesthatthesedifferentcomponentsshouldbedifferentiatedinanalysisofre-silience,astheymayresponddifferentlytodisturbance.Considerationofallthreecomponentsunderacombinedsinglemeasureofresiliencecouldthereforeobscureimportantecologicalchangesoccurringinfor-ests.Resilienceisincreasinglybeingincorporatedintomanyenviron-mentalmanagementpoliciesatnationalandglobalscales,despitethecurrentmeasurementdifficulty,whichincreasestheriskofitsmisuse(Newton,2016).Suchriskscouldpotentiallybeaddressedusingthekindsofmeasurementapproachesdescribedhereandbydevelopingspecificmanagementresponsestosupporteachofthethreeresiliencecomponentsindividually.

ACKNOWLEDGMENTS

WewouldliketothankMartinDymond,ChrisMoody,andLisaMalterfortheirhelpinthefieldandlaboratory,andMatthewWilkinsonandElenaVanguelovaatForestResearchfordiscussionsoncarbonmeasurements.

CONFLICT OF INTEREST

Nonedeclared.

AUTHORS’ CONTRIBUTION

A.C.N.andE.Cconceivedanddesigned thestudy.P.M.E.,E.C., andA.Gcollectedfielddata.E.Cparameterized,calibrated,andrunmodelwithcontributionfromM.S.L.E.C.andP.A.Manalyzedthedata.E.C.andA.C.N.wrotethemanuscriptwithcontributionsfromallauthors.

DATA ACCESSIBILITY

RawdataareintheprocessofbeingarchivedbyTheEnvironmentalInformationDataCentre(EIDC):http://eidc.ceh.ac.uk/

ORCID

Elena Cantarello http://orcid.org/0000-0001-7529-2018

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How to cite this article:CantarelloE,NewtonAC,MartinPA,EvansPM,GosalA,LucashMS.Quantifyingresilienceofmultipleecosystemservicesandbiodiversityinatemperateforestlandscape.Ecol Evol. 2017;00:1–15. https://doi.org/10.1002/ece3.3491