Surveillance of habitats and plant diversity indicators across a regional gradient in the Iberian Peninsula

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ContentslistsavailableatSciVerseScienceDirect

Ecological

Indicators

jo u rn a l h o m e pa 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

Surveillance

of

habitats

and

plant

diversity

indicators

across

a

regional

gradient

in

the

Iberian

Peninsula

M. Ortega

a,∗

_,

_C.

_Guerra

b,c

_,

_J.P.

_Honrado

d

_,

_M.J.

_Metzger

e

_,

_R.G.H.

_Bunce

f,g

_,

_R.H.G.

_Jongman

g

a_Department_of_Ecology,_Facultad_de_Ciencias_Biológicas,_Universidad_Complutense_de_Madrid,_José_Antonio_Novais_n◦_2,_Ciudad_{Universitaria,}₂₈₀₄₀_Madrid,_Spain

b_Instituto_Politécnico_de_Viana_do_Castelo_–_Escola_Superior_Agrária,_4990-706_Ponte_de_Lima,_Portugal c_Institute_of_{Mediterranean}_Agricultural_and_{Environmental}_Sciences,_Campus_da_Mitra,_Évora,_Portugal

d_CIBIO-Centro_de_Investigac¸_ão_em_{Biodiversidade}_e_Recursos_Genéticos_&_Faculdade_de_Ciências,_Universidade_do_Porto,_Rua_do_Campo_Alegre,_s/n,_4169-007_Porto,_Portugal e_Centre_for_the_Study_of_{Environmental}_Change_and_{Sustainability}_(CECS),_School_of_Geosciences,_University_of_Edinburgh,_Drummond_Street,_Edinburgh_EH8_9XP,_United_Kingdom f_Estonian_University_of_Life_Sciences,_51014,_Estonia

g_Alterra,_Wageningen_UR,_P.O._Box_47,₆₇₀₀_AA,_Wageningen,_The_Netherlands

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received28September2012 Accepted3December2012

Keywords: Fieldsurvey Monitoring Observationnetworks Samplingefﬁciency Speciesandhabitatindicators

a

b

s

t

r

a

c

t

LocatedinthewestoftheMediterraneanandwithhighenvironmentalheterogeneity,theIberian Penin-sularepresentsachallengingregionfordesigningandimplementingobservationsystemsforlandscape, habitatandspeciesdiversityindicators.WithintheframeworkofaprojectdesignedtosetupaEuropean BiodiversityObservationNetwork(EBONE),astandardizedprotocolforfieldsurveywasusedinpilot siteslocatedacrossamajorgradientinPortugalandSpain.Resultsarepresentedandcomparedtoassess theefficiencyofthemethodindetectingpatternsalongthisgradient.Thesesitesrepresentdifferent typesofIberianlandscapesselectedusingastratifiedrandomprocedureimplementedintheMadrid province(Spain)andinthenorthofPortugal.Speciesandhabitatrichnessanddiversity(aswellastheir components)arecomparedintheirrelationtoenvironmentalgradientsandsurveyarea.Resultsfrom spatialanalysesoflandscapeheterogeneityarealsopresentedanddiscussedinrelationtoappropriate indicators.Theimplicationsforsettingupcost-efficientobservationschemesthatcapturethekey indi-catorseffectivelyarediscussed.Perspectivesforintegrationwithcomplementarymonitoringschemes targetedatkeyspecies,habitatandlandscapeindicatorsarealsodiscussedinordertooptimizethepower andefficiencyoftheseobservationnetworks.

1. Introduction

Inaneraofglobalenvironmentalchange,theneedfor accu-rateestimatesofbiodiversitylossaroundtheworldhasbecome acoreobjectiveinordertomeettheinternationalconservation goalsfor2020(EuropeanCommission,2011).Previousestimates totacklethe2010targetshavebeenbasedonlocalmeasuresand ontheuseoftheStreamliningEuropeanBiodiversityIndicators (SEBI).Howeveralackofharmonizationhasbeennotedinthe sur-veysbehindseveralestimates(Bunceetal.,2008;Lengyeletal., 2008;Schmeller,2008).Therefore,sofaronlypartialestimateshave beenobtainedwhichsuggestthatrapidbiodiversitylossisactually

∗_{Corresponding}_author._Tel.:₊₃₄₉₁₃₉₄₄₄_21;_fax:₊₃₄₉₁₃₉₄₅₀_81.

E-mailaddresses:martao02@pdi.ucm.es(M.Ortega),carlosguerra@esa.ipvc.pt (C.Guerra),jhonrado@fc.up.pt(J.P.Honrado),marc.metzger@ed.ac.uk

(M.J.Metzger),bob.bunce@emu.ee(R.G.H.Bunce),rob.jongman@wur.nl (R.H.G.Jongman).

ongoing,buttheextentofthedeclineisunknown(Scholesetal., 2008;Butchartetal.,2010;Pereiraetal.,2010).

Designing thescientiﬁc and institutional framework as well asthetoolstosupportsuchglobalassessmentis atthecoreof several initiativesat global and sub-global level e.g. GEO BON, Intergovernmental Science-Policy Platform on Biodiversity and EcosystemServices(IPBES) ortheEuropeanUnion(EU) funded European Biodiversity Network (EBONE) project (Halada et al., 2009;LarigauderieandMooney,2010;GEOBON,2011).The objec-tiveof thelatteris theprovisionofa sound scientiﬁcbasis for theproductionofstatisticalestimatesofstockandchangeofkey indicatorsthatcanthenbeinterpretedbypolicymakers respon-dingtoEUDirectivesregardingthreatenedecosystemsandspecies (Metzgeretal.,2010).Themainoutputwasthedevelopmentof asystemforestimatingpastchangebutalsoforforecastingand testingpolicyoptionsandsupportingthedesignofmitigating man-agementstrategiesforthreatenedecosystemsandspecies.Inthis context EBONEhasdeveloped a Europeansystemforrecording habitatsandassociateddatasuitableforinsiturecording(Bunce etal.,2011)whichalsoallowsexchangeandintegrationbetween

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existingnationalprojects.Theprotocolincludesthewholeland surfaceandisexchangeablewiththeFAO(FoodandAgriculture Organization)LandCoverClassiﬁcationSystem(DiGregorioand Jansen,2000).

Amongtherelevant achievements fromEBONE hasbeenan evaluation of the Environmental Stratification of Europe (EnS; Metzgeretal.,2005)asamethodforselectionofstratifiedsamples, throughastatisticalcomparisonwithnationalenvironmental clas-sificationssuchastheGreatBritainCountrysideSurvey(Firbank etal.,2003;SheailandBunce,2003),theSwedishNational Inven-toryofLandscapes(Esseenetal., 2006), theAustrianSurvey of AgriculturalLandscapes(Wrbkaetal.,1999)andtheSpanish Sur-veyofHabitats(Elena-Rossellóetal.,1997,2005).Ingeneral,the EnSwasfoundtobecomparablewithregionalstratificationsand toresolve bordereffects wheredivergentenvironmental condi-tionsarecombinedintodominantstrata(Ortegaetal.,2012).The test ofa Europe-widesamplingstrategy basedon theEnS and ofasurveyprotocolforhabitatsandspeciesbasedonlifeforms andgeneralhabitatcategories(GHCs)hasbeenachievedinEBONE (Bunce etal.,2008; Hazeuet al.,2011).Thisprotocolhasbeen testedinthefieldincontrastingenvironments,fromborealconifer foreststohotdeserts,butaformaltestonitseffectivenessinthe assessmentofspeciesandhabitatdiversitypatternsacrossamajor environmentalgradienthasnotyetbeencarriedout.Inaddition,its effectivenessinrecordingrelevantindicatorshasnotbeen deter-mined.

TheIberian Peninsulais animportant reservoir ofEuropean biodiversity (Morillo and Gomez-Campo, 2000), and is usually includedinthe“MediterraneanRegion”hotspotofglobal biodi-versity(Myersetal.,2000).However,thepeninsulaalsopresents challengesforsetting upanecologicalmonitoringprogram due to its high environmental and social-ecological heterogeneity (Rey-Benayas and Scheiner, 2002;Rescia etal., 2008).Previous assessment and monitoringprogrammes in Spain and Portugal have ranged from national forest inventories and land cover mappingtolandscapeinventoriesfrombothstructural(e.g. Elena-Rosselló et al., 1997, 2005 in Spain; and Caetano et al., 2008, inPortugal)andfunctional(e.g.Alcaraz-Seguraetal.,2009) per-spectives.However,due totheirspeciﬁcgoalstheseapproaches havenotbeenabletoidentifyhabitatandbiodiversityindicators withtheenoughdetail to supportregionalmanagement needs whilst meeting the requirements of national and international reporting,e.g.ontheapplicationoftheEUHabitatsDirectiveand theimplementationoftheNatura 2000network (Evans, 2006). Thereis thereforearequirementtotesta commonIberian sys-temforhabitatandbiodiversitymonitoringthatcancontributeto cross-bordermanagementandpolicy,aswellastointernational goals.

Thispaperthereforepresentsanddiscussesresultsofapilot surveyofhabitatsandbiodiversityacrossamajorenvironmental gradientintheIberianPeninsula,includingtestsitesinSpainand Portugal.Thepilotinvolvedtheselectionandsurveyof10siteswith landscapemosaicsintworegionsofthepeninsulawithcontrasting climates,vegetation,landusesandlandscapestructure.Dataon habitatandplantdiversitydatafromthose10sitewereusedto addressthefollowingthreeobjectives:(i)toassessthe effective-nessoftheEBONEprotocolinidentifyingindicatorsofhabitatsand plantbiodiversityatthelandscapescale;(ii)totestpossibleeffects ofsurveyareaontheeffectivenessoftheprotocol,andtodiscuss implicationsforimprovingtheefﬁciencyoftheapproach;and(iii) todescribeandanalysehabitatandbiodiversityindicatorsacrossa majorenvironmentalandsocial-ecologicalgradientintheIberian Peninsula(Metzgeretal.,2005,2010).Finally,guidelinesare pro-posedforthedesignandimplementationofanIberianmonitoring programforhabitatsandbiodiversity,asaregionalcontributionto apan-Europeanobservationnetwork.

2. Methods

2.1. Testregionsandsites

Thesamplingstrategyandfieldmethodologyforsurveillance ofhabitatsandplantspeciesrichnessusedwasdescribedbyBunce etal.(2008,2011).Themethodwastestedin10sitesacrossamajor environmentalgradientintheIberianPeninsula,fiveofwhichwere locatedinSpainandtheremainingfiveinPortugal.Thesesiteswere selectedwithintwocontrastingtestregions:theMadridprovince (NUTScodeES30)and theNorth ofPortugal(NUTScodePT11). Insideeachofthesetworegions,fiveINSPIRE1km2_grid_cells_were

selectedunderastratiﬁedrandomsamplingdesignbasedonthe EnS(Metzgeretal.,2005).Theunderlyingenvironmentalgradient discriminatingthesetof10sitesisrelatedtodecreasing tempera-turesandcontinentalinﬂuenceonthegradientfromthesouthern Mediterraneantowardsthenorthernandmountainous Mediter-raneanareasandfurtherintotheAtlantic(“Lusitanian”)zonein thenorth-westofthePeninsula(Fig.1).Thisclimaticgradienthas beensummarizedinthesystemusedforstratifyingtheallocation ofsamples(Metzgeretal.,2005).

TheEnSidentifiesrelativelyhomogeneousregionsin Europe suitable for strategic random sampling of ecological resources (Metzgeretal.,2010).Itprovidesagenericclassificationthatcan beadaptedforaspecificobjective,whilstprovidingsuitablezones for environmental reporting (Hazeu et al., 2011).The EnS was createdusingtried-and-testedstatisticalclusteringprocedureson 20primaryphysicalenvironmentalvariables.Thesewere(1) cli-matevariablesfromtheClimaticResearchUnit(CRU)TS1.2dataset (Mitchell etal.,2004);(2)elevationdatafromtheUnitedStates GeologicalSurveyHYDRO1kdigitalterrainmodel;and(3) indi-catorsforoceanicityandnorthing.Principalcomponentsanalysis (PCA) was used to compress 88% of the variation of these 20 environmentalcharacteristicsintothreedimensions,whichwere subsequently clustered using theIterative Self-Organizing Data Analysis(ISODATA)clusteringroutine.Thescoresofeachgridcell alongthesethreePCAdimensionsthereforerepresentkey envi-ronmentalfeaturesinrelationtothemaingradientsacrossEurope (temperatureforPCA1,oceanicityforPCA2,andprecipitationfor PCA3;Metzgeretal.,2005).Theclassificationprocedurehasbeen describedindetailbyMetzgeretal.(2005).

TheEnScomprises84strata,aggregatedinto13environmental zones(EnZs)withadataresolutionof1km2_._The_Iberian

Penin-sula has six EnZs and four are included in the test areas. The SpanishtestregionwasintheMadridprovincewithanareaof 8.021km2_._Five_sites_were_randomly_selected_within_strata,_using

anarea-proportionalallocation,threeinthenumber1stratumof theMediterraneanSouthzone(MDS1)andtwointhenumber6 stratumoftheMediterraneanNorthzone(MDN6)oftheEnS.In Portugal,thetestregionwasinthenorthofthecountrywithanarea of21,278km2_._Five_sites_were_also_selected_randomly_within_strata,

inthesamearea-proportionalway,twointhenumber4stratum oftheLusitanianzone(LUS4),oneinthenumber1stratumofthe samezone(LUS1),oneinthenumber5stratumofthe Mediter-raneanMountainszone(MDM5),andﬁnallyoneinthenumber3 stratumoftheMediterraneanNorthzone(MDN3).Thedistribution ofthesitesinthesestrataandEnZsisshowninFig.1.Thissampling designtriestosimulateabasicnetworkNomenclatureofTerritorial UnitsforStatistics(NUTS)areathatcouldbeproposedtoinclude inapan-Europeanbiodiversityobservationnetwork.

NearMadrid,thegentlerelieftogetherwiththedry Mediter-ranean climate has produced a dominance of extensive land useswithlowspatialheterogeneityandcoarse-grainedlandscape mosaics.Therefore,intheﬁveSpanishsites1km2_grid_cells_(from

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Fig.1.RepresentationoftheselectedsamplingsiteswithintheclimaticgradientoftheEnvironmentalStratiﬁcationofEuropeaggregatedbyenvironmentalzones(Metzger etal.,2005).ThingreylinesindicateNUTS-IIregionsintheIberianPeninsula.ThicklinesindicatestudyregionsinnorthernPortugalandcentralSpain.(Forinterpretationof thereferencestocolorinthisﬁgurelegend,thereaderisreferredtothewebversionofthearticle.)

Conversely,intheNorthofPortugal,thecomplexphysiographyand terrain,withahumidAtlanticclimate,togetherwithalonghistory ofintensivelanduse,hasledtoﬁne-grainedlandscapes.Forthe ﬁvePortuguesesitesasurveyareaof0.25km2_was_therefore_used

(basedona0.5km×0.5kmgridcellresultingfroma disaggrega-tionoftheINSPIRE1km2_grid_cells)._This_cell_size_follows_previous

examplesundercomparableconditionselsewhere(Cooperetal., 2009;Rogersetal.,2012).Thisapproachallowedtheﬁeldsurvey beadaptedtothefeaturesofthetestlandscapeswhilstprovidingan opportunitytoaddressthepossibleconsequencesofthisprocedure ontheoveralleffectivenessofthemethod.

2.2. Fieldsurveysforhabitatsandplantdiversity

Ineachsite,allGHCswererecordedandmapped,including lin-earfeatures,followingtheEBONEprotocolasdescribedinBunce etal.(2011).ThebasisfortheGHCtypologyistheclassical classi-ficationofplantlifeformsdevisedbyRaunkiaerintheearly20th century.Theselifeforms(fromannualsandherbaceous perenni-als,totallshrubsandtrees)transcendthedescriptionofspecies. Theyarebasedonthescientifichypothesisthathabitatstructureis relatedtotheenvironment.Thesystemdefines160general habi-tatcategories(GHCs),asdescribedbyBunceetal.(2011).Variation withinagivenGHCisthenexpressedbyenvironmentalandglobal qualifiers,whicharecombinationsofsoilhumidity,nutrient sta-tus,acidityandotherhabitatcharacteristics.Importantadditional informationisgivenbyaddingcodesfrompredefinedlistsof quali-fiersdescribinghumanmanagementandothersitefeatures.Finally fulllistsofGHCsineachunitareadded,togetherwithinformation ondominantspecies.Inthisparticularstudy,thesevariationsare expressedasdiversityof“habitattypes”.

Vegetation plots to estimate plant diversity in GHCs were selectedrandomlywithineachGHC,followingthreecriteria:(i)one

vegetationplotperGHCorlinearelementcategoryandper envi-ronmentalqualiﬁerordominantspecies;(ii)novegetationplotsin urban,waterbodiestoodeeptosampleordangerousterrain;(iii) ifthereweremorethanoneelementofacertainGHC,thanselect randomlyoneofthemandselectalsorandomlythelocationofthe plotinsidetheGHCavoidingedgeeffectwithabufferofatleast 3m(Bunceet al.,2011).Thesizeand shapeofvegetationplots areshowninTable1.Vascularplantswereusedasafocalgroup sincetheyareconsideredassuitableindicatorsofbiodiversityand arerelativelyrapidtosurveyandidentify.Also,asprimary pro-ducerstheyplayacriticalroleinsupplyingecosystemgoodsand services,andarethesinglemostimportantgroupoforganismsin shapinghabitatsforotherspecies(Lughadhaetal.,2005;Pereira andCooper,2006).Fieldworkforhabitatrecordingandvegetation plotsextendedfortwoorthreevisitspersitedependingonthe spatialheterogeneityandspeciesdiversity.

2.3. Dataanalysis

Withthecollecteddata,threetypeofanalysiswerecarriedout. First, forthelandscapespatialanalysis,landscapemetrics were calculatedtosummarizespatialpatternsofhabitatsandmain land-scapetraitsofeachsurveyedgridcell.ThenumberofGHCs,number ofpatches,meanpatchsize,patchdensityandGHCShannon diver-sitywere calculatedat landscapelevel. Together,thesemetrics coverseveralkeyfeaturesoflandscapeheterogeneity,from com-positiontoconﬁguration.Inordertocomparelandscapemetrics across sites, each Spanish site was divided into four zones of 0.25km2_._The_number_of_Corine_Land_Cover_Map_level₃_classes

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Table1

Vegetationplotscharacteristics(adaptedfromBunceetal.,2011).

Code Name Where Size No.persite

X Arealplots Centroidatrandompointsinpolygons 10m×10m Variable

L Linearsplots Centroidatrandomalonglinearfeatures 10m×1m Variable

Plantspeciesrichnessanalyseswerealsoperformed,usingall vegetationplotscollectedduringthesurveytotestfordifferences intherelativesizeofbiodiversitypools(andtheiradditivealpha andbetacomponents)foreachsiteandenvironmentalstrataas wellas toassess therelative effectiveness of theimplemented samplingstrategies.Thisanalysiswasaimedtoaddressthe pos-sibleareaeffectsontheeffectivenessoftheﬁeldprotocol.Finally, anEnS-basedevaluationwasdonebyplottingandcomparingthe contrastsbetweensitesinthedifferentenvironmentalstrata.

Theeffectivenessofthefieldsurveystocapturethepatterns of species diversity was assessed through randomized species accumulationcurves, orsample-based rarefactioncurves inthe terminologyofGotelliandColwell(2001),usingEstimateSv8.2.0 (Colwell,2009).Thesecurvesarecalculatedwith95%confidence intervals,usingthemathematicalapproachproposedbyColwell etal.(2004),andtheirasymptoticshapeisconsideredindicative of survey effectiveness (Magurran, 2004). Specifically,thetotal numberofspecieswasusedineach ofthepooledsamplesasa preferentialestimatortoestablishthecomparisonsbetweensites. Asrichnessestimationoption,EstimateScomputestheasymptotic function most commonly used, theMichaelis–Menten function (Colwell and Coddington, 1994)and Bootstrap incidence-based estimatorofspeciesrichness(SmithandvanBelle,1984)between others.Inthisworktheseestimatorswereusedbecausethey rep-resentedthemaximum andtheminimumpredictionof species richness.Theyarethereforeindicativeofeffectiveness,evenifthey arebasedinpredictionsofspeciesnotpresentinanysample.

3. Results

3.1. Habitatpatternsacrosstestregionsandenvironmentalstrata

ThemeannumberofGHCspersitewassigniﬁcantlyhigherin thePortuguesesitesthanintheSpanishsites(Mann–WhitneyU test=2.61,p<0.01;Table2).ThePortuguesesitesshowahigher spatial heterogeneity and complexity, expressed as higher val-ues for GHC Shannon diversity (Mann–Whitney U test=1.98, p<0.05),highernumberofpatches(Mann–WhitneyUtest=2.61, p<0.01), higher patch density (Mann–Whitney U test=2.61, p<0.01)andconsequentlylowermeanpatchsize(Mann–Whitney Utest=−2.61,p<0.01).

Whencomparingtheresultsattheenvironmentalstratumlevel, dissimilaritiesbetweenstratawerealsofound,althoughalarger numberofsamplingsiteswouldbeneededtoobtainastronger statisticalrepresentation.Thesurveyedsitesshowedthatthe Lusi-tanianstratawerecharacterizedbyatendencytohavealarger numberofGHCsandahigherspatialheterogeneityand complex-ity,with more patches and a small mean patchsize (Table2). Fromalandscapeperspective,thisindicatesagradientof complex-ityfromstratawithcomplex,ﬁne-grainedmosaics(Lusitanian)to morehomogeneouslandscapes(MediterraneanSouth)withlarger patchesandfewerGHCs.

ThenumberoflandcoverclassesdetectedfromtheCorineLand Cover(CLC)2006datasetforthesamesiteswas,asexpected, signif-icantlylowerinthetworegionsthanthenumberofGHCsbecause themaphasaminimummappableareaof25haaswellasfewer classes(Wilcoxonmatchedpairs test=2.80,p<0.01)andin this casenodifferenceswerefoundbetweenregions(Mann–Whitney Utest=0.52,p=0.60;Table2).

3.2. EffectivenessoftheEBONEﬁeldprotocolinthetestregions andstrata

Intotal,262specieswererecordedintheﬁveSpanishsites(from 33plots),comparedwith284speciesrecordedinthePortuguese sites(from47plots),withatotalof470speciesrecordedinthe 80plotsfromall10sites(Fig.2(a)).Thecomparisonofthespecies accumulationcurvesfortheﬁvesitesintheMadridprovincewith thevalues of two estimators (Bootstrap and Michaelis–Menten richnessestimatedfor33plotswere300and352species, respec-tively) suggest that the surveys captured plant diversity with effectivenessbetween87%(usingBootstrapestimation)and74% (usingMichaelis–Mentenestimation). ForPortuguese sites, sur-vey effectiveness rangedbetween 82% and 59% (Bootstrap and Michaelis–Mentenrichnessestimatedfor47plotswere345and 481species,respectively).A visualcomparisonof species accu-mulationcurvesbetweenSpanishandPortuguesesitesrevealed amoreasymptoticshapeofSpanishcurvescomparedwiththeir Portuguesecounterparts,highlightingthehigherheterogeneityof thelatterlandscapes.

Thecomparisonofspecies accumulationcurves per environ-mentalstratumindicatedthatthetwoLusitanianstratashowed atendencytoaccumulatespeciesslowerthantheMediterranean strata(Fig.2(b))aconsequenceofthehighermeanspecies rich-nessofMediterraneanplots(seebelow).Themeaneffectiveness ofsurveyperstratuminMadridwas85.5±0.5%and64.5±4.5%, andinPortugalitwasof81±2%and47±10%(usingBootstrapand Michaelis–Mentenestimation,respectively).

3.3. Plantdiversitypatternsacrosstheregionalenvironmental gradient

AlphaspeciesrichnessperplotandspeciesrichnessoftheGHC hostingthehighestnumberofspeciespersiteexhibited signifi-cantcorrelationswiththethreefirstaxesofthePCAoftheEnS strata(Fig.3(a)–(c);seeSection2.1).Thefirstaxisreflectsa tem-peraturegradientandwaspositivelycorrelatedwithbothvariables (R2₌_0.45,_F₌_6.62,_p_<_0.05_and_R2₌_0.43,_F₌_5.91,_p_<_0.05),

there-foreincreasingtemperaturestendtopromotespeciesrichnessper plot.Thesecondand thirdaxes,thatreﬂectoceanicity and pre-cipitationgradientsrespectively,werenegativelycorrelatedwith both species richness variables (R2₌_0.73, _F₌_21.14,_p_<_0.01 _and

R2₌_0.78,_F₌_28.28,_p_<_0.001_for_second_axis_and_R2₌_0.62,_F₌_12.83,

p<0.01andR2₌_0.67, _F₌_16.13_p_<_0.01_for_third _axis),_indicating

thatseasonalbufferingbyproximitytotheoceanandincreaseof precipitationarerelatedtolowerplantspeciesrichnessattheplot level.

Whilstthepatternofgammarichnesspersitecouldbe inﬂu-encedbythedifferentsizesofsampleunits(0.25km2_in_Portugal,

against1km2_in_Madrid),_the_same_does_not_apply_to_alpha_richness,

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Table2

NumberofGHCs,numberofCorineLandCover2006(CLC)level3classes,numberofpatches,meanpatchsize,patchdensityandGHCShannondiversityforthe10surveyed sites.The10sitesareidentiﬁedbytheirenvironmentalstratumoftheEnS(Metzgeretal.,2005).Inordertocomparelandscapemetricsacrosssites,theSpanishsites weredividedintofoursquaresof0.25km2_,_and_means_are_shown_for_each_site._LUS,_Lusitanian_zone;_MDM,_{Mediterranean}_Mountains;_MDN,_{Mediterranean}_North;_MDS, MediterraneanSouth.

NorthPortugal CentralSpain

Alturasdo Barroso

Medrões Vitorino Ousilhão Morais Sum(mean) Colmenar Venturada Mostoles Loeches Pozuelo Sum(mean)

LUS1 LUS4 LUS4 MDM5 MDN3 MDN6 MDN6 MDS1 MDS1 MDS1

GHCnumber 23.00 14.00 33.00 14.00 11.00 (19.00) 4.75 6.75 4.75 5.50 4.25 (5.20)

CLCnumber 1.00 2.00 3.00 4.00 3.00 (2.60) 1.50 3.25 2.25 1.50 2.25 (2.15)

Patchnumber 39.00 46.00 74.00 31.00 21.00 211(42.2) 6.50 10.00 6.00 8.75 4.75 81(7.20)

Meanpatchsize(ha) 0.64 0.50 0.35 0.81 1.19 (0.69) 5.69 4.74 4.49 3.51 5.42 (4.77)

Patchdensity(ha) 1.56 1.84 2.96 1.24 0.84 (1.69) 0.26 0.40 0.10 0.35 0.19 (0.26)

GHCShannondiversity 1.73 0.84 2.59 1.35 1.71 (1.64) 0.68 1.21 0.94 1.09 0.81 (0.95)

0 50 100 150 200 250 300 350 400 450 500

1 5 9 13 17 21 25 29 33 37 41 45

Plots

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Central Spain North Portugal

Michaelis-Menten Central Spain Michaelis-Menten North Portugal Bootstrap Central Spain Bootstrap North Portugal

a)

b)

0 50 100 150 200 250

1 5 9 13 17 21

Plots

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MDS1 MDN6 MDM5 MDN3 LUS4 LUS1

Fig.2.Randomizedaccumulationcurvesforplantspeciesrichnessinthesetof10sites.(a)NumberofspeciesasafunctionofthenumberofplotsforSpanishandPortuguese regions;a95%conﬁdenceintervalisindicatedineachcurve;maximumrichnessestimatedwithBootstrapandMichaelis–Mentenwas300and352species,respectively,for CentralSpain,and345and481species,respectively,forNorthernPortugal.(b)Numberofspeciesasafunctionofthenumberofplotsperenvironmentalstratum.

FocusingonthemostspeciesrichGHCineachsite,therewasa tendencyforspeciesrichnesstoexhibitvariationsalongthesame environmentalgradients(Fig.3(a)–(c)).However,notalwaysthe GHCwiththemostspecieswastheoneoccupyingalargerarea inthecorrespondingsite(Table3).IntheSpanishsites,themost speciesrichGHC(54speciesin10m2₎_was_a_linear_plot_of_tall_scrub

dominatedbyQuercusilex.Thishabitatwasintheedgesof foot-pathsthatcrossa similarGHCbutwithsomedifferencesinits life-formcomposition.ThelatterGHCwastheonecoveringthe largestareainthatsite(“Pozuelo”;Table3),whichislocatedinthe

MDS1environmentalstratum,thedriestofall10sites,onasandy soil and with somecattle grazing but almostsemi-abandoned. Amongareal plots(100m2_), _the_GHC_hosting_the_highest

num-berofplantspecieswasascrubpatchcomposedofevergreentall shrubs,locatedalsointheMDS1environmentalstratum.Inmore humidenvironments,suchasthosepresentintheMDN6stratum, the mostspecies rich GHCwas similarbut contained 20% less speciesthaninMDS1.InPortugal,thenumberofspeciespresentin themostdiverseGHCwassmallerthaninSpain(Mann–Whitney Utest=1.98,p<0.05)(Table3).Overall,theGHCwiththemost

Table3

RelationsbetweenGHCsandplantspeciesrichnessforthe10surveyedsites:GHCoccupyingmostarea,GHChostingmostplantspecies,andspeciesrichnessofthelatter. The10sitesareidentiﬁedbytheirenvironmentalstratumoftheEnS(Metzgeretal.,2005).LUS,LusitanianZone;MDM,MediterraneanMountains;MDN,Mediterranean North;MDS,MediterraneanSouth.CHE/LHE,CaespitoseHemicryptophytes/LeafyHemicryptophytes;CRO,herbaceouscrop;FPH/EVR,ForestPhanerophytesEvergreen;STR, herbaceousstrip;LSC,lineofscrub;LTR,lineoftrees;MPH/EVR,MidPhanerophytesEvergreen;TPH/EVR,TallPhanerophytesEvergreen;THE,Therophytes;WOC,woody crop.

NorthPortugal CentralSpain

Alturasdo Barroso

Medrões Vitorino Ousilhão Morais Mean Colmenar Venturada Mostoles Loeches Pozuelo Mean

LUS1 LUS4 LUS4 MDM5 MDN3 MDN6 MDN6 MDS1 MDS1 MDS1

GHCoccupyingmostarea CHE/LHE WOC/SPA CRO CHE/LHE FPH/EVR THE FPH/EVR CRO CRO MPH/EVR

GHChostingmostplantspecies LTR WOC/CHE HST WOC THE TPH/EVR FPH/EVR MPH/EVR MPH/EVR LSC SpeciesrichnessoftheGHC

hostingmostspecies

26 17 25 43 33 26.6 41 39 48 37 54 43.8

Meanalphaspeciesrichnessplot 14 9 12 23 16 32 27 30 21 42

Linealplotsnumber 3 1 3 2 1 2 2 3 3 1

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Fig.3.Patternsandenvironmentalcorrelationsofplantspeciesrichnesscomponentsinthe10surveyedsites.(a–c)Variationofmeanalpharichnessperplotandofspecies richnessofthemostdiversehabitatagainsttheﬁrst(a),second(b)andthird(c)axesoftheEnSPCA.(d)Total(gamma)speciesrichnessanditsbetaadditivecomponent (absoluteandrelativevalues)persite.The10sitesareidentiﬁedbytheirenvironmentalstratumoftheEnS(Metzgeretal.,2005).LUS,LusitanianZone;MDM,Mediterranean Mountains;MDN,MediterraneanNorth;MDS,MediterraneanSouth.

specieswas anold chestnut(Castaneasativa) grove(actually a woodycropinGHCterms),with43speciesin100m2₍_Table₃_),

recordedinthe“Ousilhão”site(MDM5stratum).Linearelements suchasherbaceousstripsandlinesoftreeswerealsoamongthe GHCshostingthemostspeciespersite(Table3).

4. Discussion

4.1. EffectivenessoftheEBONEprotocolinthesurveyofhabitats, speciesandindicatorsoflandscapeheterogeneity

Designing observation networks for the assessment of land cover,habitatsandbiodiversitygloballywillrequiretheanalysisof theperformanceofsuchnetworksattheirseveralhierarchical lev-elsandoftheirresponsestochangesofscale(Manderetal.,2003). Overall,themethodusedinthisstudy(Bunceetal.,2008,2011)was foundtobesuccessfulinthesurveyofindicatorsrelatedtohabitats andplantspeciesrichnessinlandscapemosaicsdifferingin compo-sitionandspatialheterogeneity(cf.Table2).Themethodwasable tocapturethehighheterogeneityofspeciescompositionacross habitattypesthat characterizesIberian rurallandscapes(Rescia etal.,2008).Furthermore,themethodwaseffectiveincapturing therichnessofplantspeciespresentinthesamplesasderivedfrom accumulationcurves(cf.Fig.2).Finally,thehigherspeciesrichness thatcharacterizesMediterraneanhabitatsandlandscapes(Myers etal.,2000)wasalsoconﬁrmed,evenalthoughtheAtlanticsites usuallycontainedmoreGHCsandhabitattypes(cf.Tables2and3 andFig.2).

Comparableresults have beenobtained in theGreat Britain CountrysideSurveysincethe1970s(Firbank etal.,2003;Sheail

andBunce,2003).However,furtherdatafromotherregionsare requiredtoconfirmtheseconclusionsandtoconverttheminto policyrecommendations.Althoughwithdifferentsamplingareas, resultingfromanadaptationtolocalconditionsandcostefficiency, theresultsindicatethatinMediterraneanandLusitanian environ-mentsthesamehabitatmappingprotocolandvegetationsampling designworkswithcomparableeffectivenessintheestimationof biodiversityindicators.Themoremoderateasymptoticshapeof accumulationcurves forPortuguese test sites(see Fig.2)likely resultsfromtheirhigherdispersionacrossenvironmentalzones andstrata(seeSection2.1;Metzgeretal.,2005).Overall,theresults thereforeindicatethattheEBONEmethodology,supportedbya statisticallyrobustenvironmentalstratificationandsuitable sta-tisticalanalysis,canabsorbdifferencesinsamplingareaswithout significantlossesofeffectivenessandwithgainsofcost-efficiency. The landscape mosaics described in the field methodology beingtestedwereingeneralagreementwiththeprevious knowl-edge of each site, with thecharacteristic landscape features of each environmentalstratum reflecting interactions with social-ecologicalfactorsandtheunderlyingclimaticgradient(seeSection 2.1;Rey-Benayasand Scheiner,2002;Metzgeretal.,2010).The Portuguesesiteswereconfirmedasfine-grain(“small-scale”) land-scapes (Lomba et al., 2010, 2012), with mean patch size well belowone hectare(cf.Table 2)andwitha dominanceofcrops and grasslands, with various proportions of forest. The Span-ishsiteswerealsoconfirmedas coarse-grainmosaics(“mid-to large-scalelandscapes”),withmeanpatchsizeoverfivehectares andwithadominanceofextensivelandusee.g.annualpasture and woody crops together with open woodlands of evergreen

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area was nearly three times higher in Portugal than in Spain. However,theCorineLandcoverClassiﬁcationwasnotableto cap-turethedifferences betweenIberian regions (cf.Table2), once again highlighting the effectiveness of the methodology being tested.

4.2. Improvedefﬁciencyofsurveillanceandmonitoringandarea effects

The key resultsdiscussed in theprevious section yield two mainimplications.First,theLusitaniansitesoftheNorthernIberian Peninsulaowetheirhighspeciesdiversitytothehighspatial het-erogeneity,expressedinhighdiversityofhabitattypesandinthe highlevelsofinter-habitatdifferencesinspeciescomposition(i.e. thebetaadditivecomponentofspeciesrichness).Conversely,the Mediterraneansitessupporthighspeciesrichnessmostlydueto highvalues of species richness per habitat type (i.e. the alpha additivecomponentofspeciesrichness;cf.Fig.3).IntheIberian Peninsula,highspeciesandlandusediversityhavebeen associ-atedwithforestcovermeasuredatcoarsescale(50km×50km) byLoboetal.(2001).Oceanicityandotherclimaticvariableshave alsobeenrelatedtospeciesrichnessinthesamesensebythese authors.Rey-BenayasandScheiner,2002havealsorelatedlocal andregionalpatternsofplantspeciesrichnesstoenvironmental gradientsandheterogeneityatseveralscalesintheIberian Penin-sula.

Althoughsurveyingmoresiteswouldbenecessarytoconfirm theresults,thepresent datasuggestthat highspecies diversity isassociatedwiththeextentofforestcoverand environmental gradientsatfinerscales.Forestareasoftencontainmorediverse assemblagesofspecies(Margalef,1974;ScheinerandRey-Benayas, 1994),butedgesareoftenasimportant.TheEBONEprotocol(Bunce etal., 2008,2011)recognizesarealand linear featuresof land-scapes asstructural elementsofhighimportancefor landscape functionality.Insomeofthesites,linearelementscontainedmore plantspeciesthanthenopenlandscape(Table3).Thefunctional importanceof linearfeatures ascorridorsfor individuals, seeds andgenesiswellknown(SaundersandHobbs,1991),andasis theirimportanceforbiodiversityinMediterraneanareas(García DelBarrioetal.,2006).Inotherenvironments,linearfeaturessuch ashedgerowssharemanyspecieswiththenearbywoodland habi-tats(McCollinetal.,2000)andalsocontain“weedyplants”that invade theneighbouring woods(Honnayet al.,2002).Riparian zonesarealsoknownfortheirrichnessandfortheinvasive capac-ityoftheirspecies(Planty-Tabacchietal.,1996).Inaddition,many oftheinteractionsbetweenthevariouscommunitiesofthe land-scapearereflectedinthecontactzonesbetweenthem.Themost dynamic zonefor “speciesflow”isreportedtobewhere linear elementsproviderefuges for plantspecies ofenclosed habitats (FaganandCosner,1999).InmanynorthernEuropeanagricultural landscapes,fieldmarginscomprisethemajorityofsemi-natural habitats(MarshallandMoonen,2002).Inareasofintensivefarming themajorityofnativespeciesarefoundinsmallwoodlandpatches (Dumortieretal.,2002;Lombaetal.,2010,2011)andinhedgerows aroundfields(Wagneretal.,2000).

The secondmajor implication of the resultsrelatesto cost-efﬁciencyofhabitatandbiodiversitymonitoringinthecontextofan IberiancontributionforEuropeanorglobalobservationnetworks. Inthecoarse-grainlandscapesofMediterraneanSpain,asin south-ernEnglandandelsewhere,ecologicalheterogeneityisexpressed atmediumtolargespatialscales.1km2_survey_areas_are_therefore

needed,asdiscussedinFirbanketal.(2003),tocapture ecolog-icalheterogeneityandbiologicaldiversity.Fortheselandscapes, the1km2 _sample_area_proposed_by_the_EBONE_method_has_been

tested acrossEuropeand elsewhere (Bunce et al.,2011). How-ever,insmall-scalelandscapesoftheLusitanianzoneandmany

mountainfarmlandareas,thespatialheterogeneityofabiotic con-ditions,habitattypesand speciesdiversityis expressedatﬁner scalesandacrosssmallerspatialunits(e.g.Lombaetal.,2012).The resultsfromthePortuguesesitesprovideevidencethatundersuch conditions0.25km2_areas_are_suitable_to_obtain_robust_estimates_of

ecologicaldiversity.Smallersampleunitsreducesurveyeffortand contributetohighercost-efﬁciencybyincreasingthetotalnumber ofsamplesandthefrequencyofcampaigns.

4.3. Perspectivesforamulti-purposeIberianbiodiversity observationnetwork

Besidesservingnationalandregionalmanagementneeds,the designofanIberianBiodiversityObservationNetwork(BON)based on the EBONEframework could have positive implications for reportingoninternationalindicatorsandontheimplementation ofconservationpolicy.TheIberianBONshouldbeimplementedin thecontextofthe“RegionalBONs”proposedintheGEOBON strate-gicimplementationplan(GEOBON,2010)andwouldrepresentan importantcontributionfromIberiancountriestosupportthe repor-tingoninternationalindicatorse.g.thoseestablishedinthecontext oftheConventiononBiologicalDiversity(CBD;MaceandBaillie, 2007)andthoseproposedforreportingintheEuropeancontext (SEBI;EEA,2007).Anotherkeycontributionwouldbeforreporting ontheimplementationoftheEUHabitatsandBirdsDirectivesin SpainandPortugal,evenifcomplementarysurveyswouldhaveto beconductedtocapturerarespeciesandhabitattypes.Thedatato becollectedwouldalsoboostimportantresearchonbiodiversity responsestomultipleenvironmentalpressuresanddrivers,from climatechangeandinvasiveexoticspecies(e.g.Vicenteetal.,2011) tolandusechangeorenvironmentalpolicy,byprovidingﬁelddata formodelcalibrationandscenarioanalysis(e.g.Pereiraetal.,2010; Lombaetal.,2012).

Inthiscontext,notonlyabiodiversityandhabitatsmonitoring networkwillbeneﬁtfromtheimplementedstandardized proto-col,butalsoothernationallyand/orregionally basedsurveys.A structuredsamplingprogramasdescribedabovecouldprovidethe necessaryinformationonindicatorsrelatedtohabitatsandspecies whichcouldleadtothedevelopmentofpoliciesforconservation, butitcouldalsoprovidedatavaluableforassessingthenational implementationofEuropeanDirectives,e.g.theWaterFramework Directive,orfor integrationwithdatafromagro-environmental surveys, e.g. the Land Use/Cover Area frame statistical Survey (LUCAS)andrelatedsetsofindicators(e.g.IRENA;EEA,2005)

The implementation of an Iberian BON could also beneﬁt from comparable initiatives by being able to integrate results fromothersurveysrelatedtoenvironmentalassessment.Suchan integrated developmentframeworkwould necessarily leadtoa standardizationofcollectionproceduresandopenopportunities forcost-efﬁciencyandintegratedenvironmentalanalysis.Although there aresome importantchallenges toconsider (data integra-tion, different reference systems, different representations and semantics,differentontologies,etc.;e.g.Henryetal.,2008),this integrationof systems andthe harmonizationofprocesses and toolscouldrepresenta landmarkforenvironmentalmonitoring effortsinthePeninsulaandelsewhere.

Acknowledgements

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