universidade de aveiro · projeto europeu do fp7: “recare – preventing and remediating...

Universidade de Aveiro

2016

Departamento de Ambiente e

Ordenamento

Tiago van der Worp da Silva

The short-term effects of mulching on the soil-dwelling arthropod community after a wildfire Os efeitos no curto prazo da aplicação de mulch sobre a comunidade de artrópodes que vivem no solo após um incêndio florestal

Universidade de Aveiro 2016

Departamento de Ambiente e Ordenamento

Tiago van der Worp da Silva

The short-term effects of mulching on the soil-dwelling arthropod community after a wildfire Os efeitos no curto prazo da aplicação de mulch sobre a comunidade de artrópodes que vivem no solo após um incêndio florestal Dissertação apresentada à Universidade de Aveiro para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Engenharia do Ambiente, realizada sob a orientação científica da Doutora Filomena Maria Cardoso Pedrosa Ferreira, Professora Associada do Departamento de Ambiente e Ordenamento da Universidade de Aveiro e coorientação do Doutor Nelson Abrantes, investigador auxiliar do Centro de Estudos do Ambiente e do Mar (CESAM), Departamento de Ambiente e Ordenamento da Universidade de Aveiro, e Doutor Jan Jacob Keizer, Investigador Auxiliar do CESAM e Departamento de Ambiente e Ordenamento da Universidade de Aveiro.

Esta dissertação foi desenvolvida no âmbito do projeto europeu do FP7: “RECARE – Preventing and Remediating degradation of soils in Europe through Land Care” (no. 603498)

o júri

presidente Professora Doutora Maria Isabel Aparício Paulo Fernandes Capela

Professora associada do Departamento de Ambiente e Ordenamento

Professor Doutor Fernando José Mendes Gonçalves

Professor associado com agregação do Departamento de Biologia da Universidade de Aveiro

Professora Doutora Filomena Maria Cardoso Pedrosa Ferreira Martins

Professora associada do Departamento de Ambiente e Ordenamento da Universidade de Aveiro

agradecimentos

À orientação muito próxima e muito enriquecedora facultada pela Prof. Doutora Filomena Martins, pelo Doutor Nelson Abrantes e Doutor Jan Jacob Keizer. Ao Doutor Jan Jacob Keizer pela oportunidade dada em trabalhar e colaborar no seio de um grupo de investigação. Em especial ao João Puga por toda a disponibilidade, crítica, conselhos, constante apoio e partilha de conhecimento. À minha família por me proporcionar sempre o melhor e pelo apoio incondicional neste percurso. À Mariana pela presença sempre muito especial. A todas as amizades e aprendizagens que nutri durante este percurso e que levo para a vida.

keywords

mulching effects, wildfires, ground-dwelling arthropods

abstract

Forest fires are common events in the Mediterranean basin, but due to human action and climate change, these have been increasing, especially in Portugal. It is in this context that a larger number of studies have emerged in regard to the impacts of forest fires on ecosystems, with special focus on the effects on soil and mitigation strategies in the post-fire period. In this regard, the application of mulch is one of the mitigation strategies studied since it is considered inexpensive and effective in reducing erosion and loss of soil nutrients in the post-fire. Moreover, the impacts of organic coverages application on soil fauna are still poorly understood. This study aims to assess the effect of the application of various mulch densities in the soil on the invertebrate community in a eucalyptus plantation, immediately after the fire. The ground fauna covered in this study were soil arthropods, a large existing community regarded as reliable bio-indicators. The type of mulch used was chopped eucalyptus bark. The study area, located in North-Central region of Portugal, is characterized by eucalyptus plantations in a schist soil. This study was conducted in order to understand the extent of the effects that mulch could produce in a short period after a fire. In order to achieve adequate results, different areas with and without the application of mulch, at different densities were selected and monitored for 5 months after the fire. Sampling was carried out with pitfall traps and identification of the collected specimens was made at Order level. The results suggest differences between the monitoring months and absence of differences among the densities of mulch application, suggesting seasonality as influence factor on the total community abundance. Small differences in the community richness suggested that a low density of mulch provided a faster ecological succession. The application of mulch also raised the hypothesis that it may have introduced unwanted specimens into the ecosystem.

vii

palavras-chave

efeitos da aplicação de uma camada orgânica, incêndios florestais, artrópodes que vivem no solo

resumo

Os incêndios florestais são eventos comuns na bacia mediterrânica, mas devido à ação do homem e às alterações climáticas, estes têm vindo a aumentar em Portugal. É neste contexto que um maior número de estudos tem surgido, focando-se nos impactes dos incêndios florestais sobre os ecossistemas, e em especial sobre os seus efeitos no solo e em estratégias de mitigação no período pós-incêndio. Neste sentido, a aplicação de coberturas orgânicas sobre o solo é uma das estratégias de mitigação estudada, sendo considerada barata e eficaz na redução da erosão e perda de nutrientes no pós-incêndio. Por outro lado, o conhecimento dos impactes da aplicação de uma cobertura orgânica sobre a fauna presente no solo é ainda escasso. Este estudo pretende avaliar o efeito da aplicação de várias densidades de cobertura orgânica no solo sobre a comunidade de invertebrados do solo em eucaliptais, imediatamente após o incêndio, utilizando como cobertura orgânica raspas de casca de eucalipto. Os invertebrados do solo, formam uma comunidade muito diversa considerada como um bioindicador fiável. A área de estudo, situada na região Centro-Norte de Portugal, é caracterizada por plantações de eucalipto sobre um solo xistoso. A amostragem foi realizada com armadilhas de solo e a identificação dos espécimenes recolhidos foi feita até ao nível da Ordem. Os resultados obtidos sugerem diferenças entre os meses de monitorização e ausência de diferenças entre as densidades de aplicação e sem cobertura orgânica, sugerindo a sazonalidade como um fator de influência sobre a abundância total da comunidade. Pequenas diferenças na riqueza específica da comunidade sugeriram que uma baixa densidade de cobertura orgânica promoveu uma sucessão ecológica mais célere. A aplicação da cobertura orgânica levanta ainda a hipótese de esta ser uma fonte de introdução de espécies indesejadas no ecossistema.

viii

Tableofcontents

Acknowledgements

Abstract

ListofFigures

ListofTables

1.Introduction...................................................................................................................................1

1.1WildfiresandthePortuguesecontext..............................................................................1

1.2Wildfireimpactsandstudies............................................................................................2

1.3Ground-dwellingarthropods............................................................................................3

1.4Researchobjectives..........................................................................................................5

2.Materialsandmethods..................................................................................................................7

2.1 StudyareaandSites..........................................................................................................7

2.1.1Samplingmethodologyanddesign..........................................................................8

2.1.1.1Pitfalltraps............................................................................................................8

2.1.1.2Samplingdesign....................................................................................................9

2.2 Ground-dwellingarthropodscollectionandidentification.............................................11

2.3 Ecologicalfunction..........................................................................................................12

2.4 Environmentalvariables.................................................................................................13

2.5 Dataanalysis...................................................................................................................13

3.Results...........................................................................................................................................15

3.1 Environmentalvariablesanalysis....................................................................................15

3.2 Communityanalysis........................................................................................................15

3.2.1RichnessandAbundance........................................................................................15

3.2.1AbundanceandEnvironmentalvariables...............................................................23

3.2.2Diversity(H’)andEvenness(J’)...............................................................................23

ix

3.3 Ecologicalfunctionanalysis............................................................................................24

4.Discussion.....................................................................................................................................29

5.Conclusion....................................................................................................................................37

6.Finalconsiderations.....................................................................................................................39

References........................................................................................................................................41

x

Listoffigures

Figure1.MeanburntareaperyearontheMediterraneanclimatecountries(PORDATA,2016).....1

Figure2.Locationofthestudyfields,Burnt(black)andUnburnt(green)........................................7

Figure3.Pictureofanuncoveredpitfalltrapintheburntsite..........................................................8

Figure4.Samplingdesigndisplaypersamplingmonths.................................................................10

Figure7.Stereoscopicmagnifier......................................................................................................11

Figure5.Secondscreening,identifyingandcountingarthropodsatorderlevelperpitfalltrap....11

Figure6.Firstscreeningprocess,separatingtrappedarthropodsfromlitter.................................11

Figure8.Meanandstandarddeviationfortemperatureandprecipitationbetweenlate

September2015andJanuary2016..................................................................................................15

Figure9.Totalrichnessregardingsamplingmonthsandplots........................................................16

Figure10.Totalabundanceregardingsamplingmonthsandplots.................................................18

Figure11.Meanabundanceandrespectivestandarddeviationpersamplingmonthsandplots..18

Figure12.Relativeabundanceinpercentageperplotduringthesamplingmonths......................20

Figure13.TotalabundanceperorderinSeptember.......................................................................21

Figure14.TotalAbundanceperplotduringsamplingmonths........................................................22

Figure15.TotaldiversityandtotalevennessintheLT,HTandNTplotsduringsamplingmonths23

Figure16.EcologicalfunctiondistributioninSeptember................................................................24

Figure17.Ecologicalfunctionrelativeabundanceperplotduringsamplingmonths.....................25

Figure18.Ecologicalfunctiongroupstotalabundanceperplotduringsamplingmonths..............26

xi

Listoftables

Table1.Two-wayANOVAsummaryregardingmonthandplotwithtotalrichnesspertrap.

Significantstatisticalrelationsinboldtype......................................................................................17

Table2.AllPairwiseTukeymultiplecomparisontestwithinmonthsandtreatments....................17

Table3.Two-wayANOVAsummaryregardingmonthandplotwithtotalabundancepertrap.

Significantstatisticalrelationsinboldtype......................................................................................19

Table4.Pearsoncorrelationbetweenordersoneachsamplingmonth.........................................20

Table5.Pearsoncorrelationbetweentotalabundanceandabioticvariables................................23

Table6.Two-wayANOVAsummaryregardingmonthandtreatmentasfactorsanddiversityand

evennessindexeshasvariables.Significantstatisticalrelationsinboldtype..................................24

Table7.Tukey’smultiplecomparisonofmonthsregardingdiversity.............................................24

Table8.Pearsoncorrelationbetweenecologicalfunctiongroupsoneachsamplingmonth.........25

Table9.PearsoncorrelationbetweenecologicalfunctiongroupsoneachPlot.............................25

Table10.One-WayANOVAonfunctionalgroupsregardingsamplingmonths...............................27

Table11.Tukeymulti-comparisontestonmicrobialfeedersandomnivoresregardingdifferent

months.............................................................................................................................................27

Table12.One-WayANOVAonfunctionalgroupsregardingtreatments........................................27

The short-term effects ofmulching on the soil-dwelling arthropod community after awildfire

2016

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1. Introduction

1.1 WildfiresandthePortuguesecontext

Awildfire isanevent that takesplace in forestsetting influencedbyexisting fuels,climate-

weatherrelations,ignitionagentsandanthropologicactivities(Flannigan,Stocks,Turetsky&

Martínez-Mena, 2009), that ultimately produces effects on soil, hydrological regimes,

vegetation and fauna (Moreira, Catry, Silva & Rego, 2010). Wildfires are seen as major

ecologicaldisturbances,althoughthesehavealsobeenoneimportantenvironmentalchange

factor shaping the landscape in fire-prone ecosystems for millenniums, such has the

Mediterraneanbasin,California,SouthAfricaandSouthwestAustraliaregions(Pausas,Llovet,

Rodrigo&Vallego,2008).

Consideringthispremise,itisbelievedthattheglobalclimatechangescenariowillbeplaying

asignificantroleinincreasingchangesforfireperiodsandintensityregimesinthenearfuture

(Lavorel,Canadell,Rambal&Terradas,1998;Bento-Gonçalves,Vieira,Úbeda&Martin,2012).

Largertemperaturegapsbetweenseasonsaswellaslongerdryperiodsandlessprecipitation

willinfluencedirectlyfireseverityandoccurrence(Flanniganetal.,2013).

PortugalhasnotbeenanexceptionintheMediterraneanBasinareasinceitistheEuropean

countrywith the largest recordofwildfires andburnt area in the lastdecade (IPCC,2013)

(Figure1).Moreover,thisscenarioislikelytocontinueinthenearfuture(Bento-Gonçalveset

al.,2011).

Figure1.MeanburntareaperyearontheMediterraneanclimatecountries(PORDATA,2016)

Theserecordsareassociatednotonlywith theclimateregimecharacterisedbywetwinter

seasonsincontrastwithdryandhotsummerseasons,butalsoduetosocio-economicfactors

50 100 150 200 250 300

1980- 1984

1985- 1989

1990- 1994

1995- 1999

2000- 2004

2005- 2009

2010- 2014

MeanburntareainthousandsofhaPortugal Italy Greece France Spain


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(ICNF, 2013). These factors include: the extensive and intensive plantations of Eucalypt

registeredinPortugalthatstartedinthe80’s;theruralexodusthathasledtotheabandonment

of forest areas leaving them more exposed to this hazard; and the lack of efficient land

managementpoliciesthatwouldpreventit(Shakesby,2011;Shakesby&Doerr,2006;Keeley

etal.,2012).

1.2 Wildfireimpactsandstudies

Awildfireleadstomanyeffectsontheecosystemeitherdirectlyorindirectly,bychangingsoil

structurepropertiesthatlaterleadtochangesinhydrologicalandgeomorphologicalprocesses

andconsequentlychangesinthefaunaandfloraofanecosystem(Certini,2005).

Most of the recent studies undertaken in theMediterranean region have been focused on

physicalandchemicaleffectsonsoilduringthepost-fireseason(Neary,Ryan&DeBano,2005;

Keizeretal.,2008,Shakesby,2011)inordertocomprehendhowbettercopingstrategiescan

beimplementedinthepreandpostfireperiods.

Mostofthemitigationstrategiesarefocusedonreducingsoilerosionbywaterrunoffinthe

burntareas,suchas:seeding,constructionofphysicalbarriersalongtheslope,scarifyingand

ploughing,applicationofhydro-mulchandmulching.Thesetechniquesareappliedaccording

tothephysicalcharacteristicsoftheburntfield,suchastheslopeand/oravailableresources

suchasrockandlogs.Intheoverall,themosteffective,easytoapplyandlowcosttechniqueis

mulching(Ferreiraetal.,2015).

Mulchingconsistsoncoveringthebaresoilsurfacewithabiomasslayerinorderthatinsmall

areas,micro-trapsaregenerated,asthesewillretainashesandstoresomeoftherunoffwater

intheperiodafterthefire.Thistechniqueconductsaverysignificantreductionofwaterrunoff

by50%thatconsequentlyproducesareductionofsoilerosionby90%(Ferreiraetal.,2015).

Thissametechniquehasalsobeenstudiedandappliedintheagriculturalcontext,providing

anincreaseinsoilmicrobialactivity,improvingnutrientbalance,moderatingsoiltemperature

andimprovingwaterinfiltrationandreducingsoilerosion(Gill,McSorley&Branham,2011;

Chalker-Scott,2007;Westerman&Bicudo,2005;Altieri&Nichols,2003).Theseadvantages

havealsobeenobservedinthepost-fireapplicationcontext(Ferreiraetal.,2015).

Mulching also occurs naturally in the ecosystem, especially in settings that had mid-low

severitywildfire events, onwhich leaves remain on trees and later fall in the soil surface,


2016

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working in the same way has the mulch application effects (Ferreira et al., 2015; Prats,

McDonald,Monteiro,Ferreira&Keizer,2012).Nonetheless,mulchapplicationdependsonthe

localavailabilityandpriceofthematerial(biomass)inordertobeafeasiblesolution.Many

materials have been proven to work effectively like straws, woodchips and hydro-mulch,

althoughforestresidualshavenotbeensubjectedtothesamescrutiny(Ferreiraetal.,2015).

In thatregard,studies inPortugalhave looked into forestresidueshasamulchingmaterial

consideringitsavailability,costandalsothedensityofitsapplication(Pratsetal.,2012).

Followingupthestudiesthatfocusontheeffectivenessofmulchinginthereductionofsoilloss

inburntareas,awarenesshasrisentoothereffectsthatthistechniquemightproduce,specially

to the soil-dwelling arthropod communities (Puga, 2016), which are widely affected by

wildfires(Elia,Lafortezza,Tarasco,Colangelo&Sanesi,2012).

1.3 Ground-dwellingarthropods

ThesoilisoneofthemostcomplexsystemsinEarth,althoughitsbiologicalsystemsareyetto

befullyexplored.It’sthelivingsurfaceforatleastoneormorestagesofalifecycleformany

animals,meaningthatmost,ifnotall,terrestrialorganismsdependdirectlyandindirectlyon

biologicalprocessesinthesoil(Storketal.,1992).

TheArthropodaphylumroughlyaccountsforthreequartersoftheEarth’sorganismshaving

themostdiversetaxaofinvertebratesandbeingpresentinbothwaterandlandecosystems.

Arthropods are characterized by segmented bodies, with bilateral symmetry and chitin

exoskeletons(McGavin,2010).

Theground-dwellingarthropodsaretheoneswhoinhabittheleaflitterinthesoilandrange

inmanydifferentformsandfunctionswhileactinghasdecomposers,playingaveryimportant

role onnutrient cycling and soil structuremaintenance and fertility; as prey andpredator,

regulatingpopulationsofotherorganismsandenhancingthefood-web;andalsoinenabling

floweringplantreproduction(García-Domíngez,Arevalo&Calvo,2010;Buddleetal.,2005;

Danks,1992;Kremenetal.,1993andWiggins,Marshall&Downes,1991).

Inanecologicalcommunity,theground-dwellingarthropodscanbeextremelysusceptibleto

shocksthatmayaltertheirlivingenvironmentsandthereforebeingregardedasbio-indicators

foraccessingecologicalchangesduetotheirhabitatrequirementsandpotentialsensitivityto


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changes and/or threats. Hence, arthropods have beenwidely studied as bio-indicators for

pollution,habitatdisturbanceandclimatechange(McGeoch,1998).

The threats that affect the integrity and resilience of this group in the Mediterranean

ecosystemsvariedfromhabitatfragmentation,humanexploitation,pestoutbreaks,invasion

ofexoticspecies,overgrazingandforestfires(Eliaetal.,2012;Penman,Beukers,Kavanagh&

Doherty, 2011). Forest fires conduct severe impacts on ecological communities directly,

throughmortalityinducedbyheatandsmoke(Gerson&Kelsey,1997),andindirectbyaltering

vegetation structure in the post-fire period (Whelan, 1995; Pickering, 1997).However, the

extentofseverityfromtheseimpactsisalsodependentonthefireseverity(Certini,2005).

Iffact,fewstudieshavebeenconductedtoassesstheresponseofthisgroupinthepost-fire

period. Nunes et al. (2006) found a decreasing tendency in ground beetle abundance in a

Mediterranean Pine forest, proving that the fire does alter the ecological community

composition.Although theshort-termresponseof insect communities to fire remains tobe

fullyexploredinMediterraneanforestecosystems,especiallywhenpost-fireeffectmitigation

techniquescometoaction.

Another study conducted by Puga (2016) focused on the effects of mulching on ground-

dwellingarthropods,butona laterstageof theecosystemrecovery,approximately5years

afterthefireevent.Inthisstudyitwasobservedahomogenouscommunityineithermulched

anduntreatedplots,suggestingthatatanearlierstageafterawildfire,thepresenceofmulch

can be of bigger influence on the re-establishment of the ground-dwelling arthropods, by

possiblypromotingafasterrecoveryonanearlystage.

Hence,thisstudyfollowsupthestudyundertookbyPuga(2016),byfocusingontheshort-

term impactofmulchingon there-establishmentofground-dwellingarthropods inaburnt

eucalyptplantationarea.


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1.4 Researchobjectives

Themainquestionsaddressedbythisstudywere:

1. How does the ground-dwelling arthropod community responds to fire-inducedecosystemalterationsinthefirstmonthafterthewild-fireevent:1.1. Whicharethemaintaxapresentduringthisperiod?

2. Howdotheabundanceanddiversityoftheground-dwellingarthropodcommunitychangewithtimesincethewildfireinthepresenceofmulchasopposedtowithoutit?2.1. Ismulchpromotingafasterrecovery?2.2. Ismulchpromotingspecifictaxaorecologicalfunctionlevels?2.3. How does a high and low mulch application density impact the re-

establishmentoftheground-dwellingarthropodcommunity?


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2. Materialsandmethods

2.1 StudyareaandSites

ThisstudywasconductedintwositesinthelocationofSemide,MunicipalityofMirandado

Corvo:oneburnt(40°09'57.8"N8°19'29.7"W)andoneunburnt(40°09'49.9"N8°19'44.7"W).

Theareasarelocatedinnorth-centralPortugal.

Figure2:Locationofthestudyfields,Burnt(black)andUnburnt(green).

BetweenAugust9thand10th,thisareawasfustigatedbyawildfirethatburntapproximately

715ha(Figure2).Thefireseveritywasrecordedbetweenmoderateandhigh,accordingtothe

soilseverityindexofVegaetal.(2013).

Regardingwildfirerecords,thestudysiteshadtwowildfiresbefore,in2000and2012.

TheareaischaracterizedbysteephillsthatconnectwiththeCeirariver.Thesoilsderivefrom

pre-OrdovicianschistsoftheHespericMassif(Pereira&FitzPatrick,1995)andareclassified

accordingtotheIUSS(2014)asacidicloamyEpilepticumbrisol.Soilsaretextureequilibrated,

pHrangesbetween4.6and4.8andarerichinsoilorganicmatter,approximately15-18%into

Alayer.Theclimateofthestudyareacanbecharacterizedashumidmeso-thermal(Köppen,


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Csb),withprolongeddryandwarmsummers.Meanannualtemperatureatthenearestclimate

station(CARAPINHAL(13H/09UG),SNIRH,2012) is12°C.Meanannualprecipitationat the

nearestrainfallstation(12km)is,onaverage,851mm(CARAPINHAL(13H/09UG),SNIRH,

2016).TheareasaredominatedbyEucalyptusglobulusLabillplantations.

Both sites are eucalypt plantations (burnt and unburnt) that present very similar

characteristics,distancing500metersawayfromeachother.Theburntandunburntsitesface

E-NEandEandhaveahillslopedegreeof27°and26°,respectively.Thesitesweresubjected

tothesametypeofsamplingofground-dwellingarthropods:thepitfalltrapmethod.

2.1.1 Samplingmethodologyanddesign

Immediatelyafterthefire,afieldsettingwascarried-outintheselectedburntslopetoassess

theeffectsofforestresiduemulchonrunoffandsoilerosion.Inthisfieldsetting,areastoassess

theeffectsof forestresiduemulchon theground-dwellingarthropodcommunitywerealso

installed.

2.1.1.1 Pitfalltraps

Pitfalltrappingisthemostcommonlyusedcollectionmethod

forsamplingsoilinvertebrates.Itisanefficientandlow-cost

technique to assess ground-dwelling fauna, despite its

disadvantages. It consists, basically, on a cylindrical shaped

container(inthiscasehalfofaplasticbottle)whichisdugin

thegroundwitharimatsurfacelevelthatultimatelywilltrap

mobileanimalsthatfallintoit.Mostofthetimes,itisslightly

coveredbyrockorsomethingsimilarinordertocamouflagethehole,toprotectthetrapfrom

sunlightandfromotherpredators(Figure3).

Thismethodprovides reasonableactivity-densityestimates forgroupssuchbeetles (Baars,

1979),spidersandants(Wang,Strazanac&Butler,2001).

Therearealsoinevitablybiasesinpitfallsamplingwhilecomparingdifferentgroupsofanimals

and different habitats. An invertebrate’s probability of being captured depends on the

structure of its habitat, such as the density of vegetation; activity of a certain taxa (higher

physiologicalactivityand/or largerareaof influence);animal size,bybeing too large tobe

Figure3.Pictureofanuncoveredpitfalltrapintheburntsite


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trappedortoosmallthatitisnotcollected;andalsofromfactorssuchhastemperatureand

rain,whichalteranimal’sbehaviour.Comparisonsbetweendifferentgroupsmust,therefore,

take into account variation in habitat structure and complexity, changes in ecological

conditionsovertimeandtheinnatedifferencesinspecies(Woodcock&Leather,2007,chap.

3;Spence&Niemela,1994).

Pitfall traps, while taking into consideration its limitations, are able to provide answers

regardingground-dwellingarthropod richness,which is thenumberofdifferent taxonomic

individuals identified; and abundance, which is the total number of collected individuals

disregarding its taxonomical aspects. Taxa richness and abundance combined can provide

informationaboutthechangesonthecommunitiesduringthesamplingperiodandevaluate

howtheyevolvethroughtime(Abbott&LeMaitre,2010).

Thetrapsusedinthisstudyhad8.5cmindiameterand12cmheightplasticbottombottles.

Thebottomofthebottlewasfilledbywater,alittlebitofethanol70%thatslowsdownthe

degradationofthecapturedanimalsandonedropofdetergentthatbreaksthesurfacetension

oftheliquidinordertopromotequickdrowning.

2.1.1.2 Samplingdesign

Atotalof12pitfalltrapswereinstalledatthetwostudysites,3ofwhichattheunburntsite

(UNB)and9attheburntsitetocomparethreedifferenttreatments:heavy-treatment(HT),

lowtreatment(LT)andnotreatment(NT),wheretreatmentstandsforthemulchapplication

atdifferentdensities.ThefieldinstallationwasperformedfromSeptemberuntillateOctober

(Figure4).Theappliedmulchmaterialwaschoppedeucalyptbark,whichisbelievedtobethe

bestfitasmulchmaterialsareregardedconsideringthesite’scharacteristics,availabilityon

siteandapplicationcost.Theunburntsiteactedasacontrollocationbeingareferenceofan

ecosystemwithverysimilarcharacteristicsthathasnotbeenchangedforatleast4years.

Pitfall sampling was performed for a period of seven days, repeated in the months of

September, October, November and January. The selection of sampling months had the

intentionoffollowingtheendofsummer,includingAutumn,whichisaseasonthatcomprises

manybiologicalevents(Gallinat,Primack&Wagner,2015),andearlyWinter.Thecollection

dayswere the25thof September, the14thofOctober, the25thofNovemberand the27thof

January.TheunburntsiteinstallationtookplaceonlyattheendofOctober,thus,itonlybegun

tobesampledfromNovemberon.


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AfterthefirstsamplingperiodofSeptember,whennotreatmenthadyetbeenapplied,theplots

attheburntsiteweremulched:onewithadensityofmulchmaterialof0.26kg.m-2andanother

with0.80kg.m-2;athirdplotremaineduntreated.Eachplotmeasures2metersinwidthand8

metersonlength,spacing10metersfromeachother,withthreepitfalls linearlyplacedand

equallyspacedalongtheslopeofthehill.Theunburntsitefollowedthesamesetting,buthad

onlyoneplot(Figure4).Thisdesignensuredthatafirstassessmenttotheground-dwelling

arthropodcommunitycouldbeexecutedrightafterthewildfireeventandalsoonlaterstages,

conductingtodatathatcouldclarifythequestionsraisedonthisstudyregardingtheuseof

mulch.

Figure4.Samplingdesigndisplaypersamplingmonths.


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2.2 Ground-dwellingarthropodscollectionandidentification

Beforethesamplingperiodtookplace,everypitfalltraphadtobere-set,inordertoguarantee

that the collection of arthropodswas only from that 7-day period. Re-setting consisted on

cleaningtheinteriorofthepitfallandintroducingwater,ethanolanddetergent,aslistedbefore

(Chapter2.2.1).Afterthe7-dayperiod,theinteriorofeachtrapwasfilteredbyasmallmesh

(±1mm)andthesamplesweretransferredintoarecipient,respectivelylabelled.Thefiltering

process allowed elimination of accumulated water in the pitfall trap during the sampling

period,beingaveryusefulstepduringwinter.However,micro-arthropods(smallerthanthe

mesh size) could have beenwasted in this process. Due to this limitation, theAcariorder

collectedisconsiderednottobefullyrepresentative.

Thesamplescollected inthe fieldwere lateranalysed inthe laboratory.Firstly,ascreening

fromdirtandanimals tookplace (Figure5).Secondly,a screeningatorder level fromeach

pitfall was made (Figure 6). The screening process was done with the assistance of a

stereoscopic magnifier (Figure 7), in order to easily identify the selected taxa. The

identificationprocessfollowedtaxonomickeysfromChinery(1993)andwasalsosupported

byBarrientos(1988).

Figure6.Secondscreening,identifyingandcountingarthropodsatorderlevelperpitfall

trap.

Figure7.Firstscreeningprocess,separatingtrappedarthropodsfromlitter.

Figure5.Stereoscopicmagnifier


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Identificationwasonlydoneat theOrder level, considering the timeeffort and the levelof

expertiseneededtoidentifylowertaxonomiclevels.Nonetheless,theuseofhighertaxonomic

levelscanprovidegoodoutcomeswhen itcomes to thestudyofarthropodcommunities in

severalecosystems(Simão,Carretero,Amaral,Soares&Mateos,2015).Arthropodlarvaewere

notconsideredinthecommunityanalysis.

2.3 Ecologicalfunction

Fourecologicalfunctionswererecognisedforthetaxathathadbeenidentifiedinthevarious

samples:microbialfeeders,plantfeeders,predatorsandomnivores.Theselectionoftaxa,at

theorderlevel,foreachfunctionalgroupwasperformedconsideringthemorphologicfeatures

foundintheindividualsfromeachsampleandalsobasedonBarrientos(1988).

Forthegroupofpredators,orderssuchasAranaea,Chilopoda,OpilionesandPseudoscorpiones,

were automatically assumed considering the main morphology found in these orders.

Collembolawereconsideredasmicrobialfeeders(feedingfromfungianddeadorganicmatter).

Thysanura,IsopodaandHymenopterawereconsideredasomnivores.Hymenopteraindividuals

wereonlyantsandtherefore,thesewerealsofittedintotheomnivoregroup.

Coleoptera individualshadasub-samplingproceduretocharacterisetheircommunity,since

thisorderisoneofthemostdiversewhenitcomestoecologicalfunctions(Rainio&Niemela,

2003). Considering the large number of individuals in some samples, a sub-sampling was

adopted to classify the collected specimensperecological functionbasedonmorphological

characteristics.Onsampleswithaverylargernumberofindividuals,only10specimenswere

classified.

Acari individuals were not considered in the ecological function since it is not possible to

determinetheirfunctionwithoutidentificationatfamilylevel.Dipterawasalsoexcludedfrom

theseanalysessincethesamplingmethod(pitfalltrap)isnotadequateforthisorder.


2016

13

2.4 Environmentalvariables

Theenvironmentalvariablesconsideredinthisstudywererainfalllevelsandtemperature.

Theselectedenvironmentalvariableswerecollectedbyameteorologicalstationalsoinstalled

bytheESPTeam,neartothestudysites,onthe24thofSeptember.Inordertointerpretdata

provided by this station, which collected data on a 15-minute period, an average of

temperaturewascalculatedandthetotalprecipitationwassummedina10-dayperiod,having

atleast3valuesforeachmonth.The10-dayperiodwasselectedinordertoobtainvaluesthat

wouldmatchthenumberofsamplesinthefoursamplingmonths(3plotsx4months)andalso

considering the level of detail regarding environmental variables intended, which is

seasonality.

2.5 Dataanalysis

The results obtained by the collected samples, after being screened and sorted,were later

analysedstatisticallywithSPSS13.0andMicrosoftExcel2015.

Alltaxawereanalysedatorderlevel,asmentionedbefore,andthedataretrievedwasusedto

calculate ground-dwelling arthropod community’s structural parameters: total abundance,

total richness, Shannon-Weiner diversity index (H’) andPielou’s evenness index (J’). These

parameterswereorganizedbysamplingmonthsandperplots.Theindexeswerecalculated

fromtotalabundanceresultsataplotlevel,inwhichthetotalabundancewasthesumofthe3

pitfall-trapsinstalledoneachplot.

TheShannon-Weinerdiversityindex(H’)andthePielou’sevennessindex(J’)werecalculated

accordinglytothefollowingformulas.

𝐻´ = − 𝑝'𝑙𝑛 𝑝' *

'+,

• pi=fractionoftheentirepopulationfromorderi;

• T=numberofordersfound;

• ∑=sumfromorder1toorderT;


2016

14

𝐽. = 𝐻′

𝐻′012

where,𝐻′012 = − ,*𝑙𝑛*

'+,,*= ln 𝑇

• T=numberofordersfound;

These indexeswere calculated accordingly with the total abundance at plot level for each

samplingmonth.

Pearson’scorrelationswereperformedinordertocomprehendrelationsbetweenordersand

between ecological function groups through the sampling period and also between total

abundanceandtheenvironmentalvariables.Correlationswereconsideredsignificantona2-

tailedtest.

A two-wayANOVAwasused to test for significantdifferencesamong themonths (October,

NovemberandJanuary)aswellasbetweentreatments(NT,LTandHT)regardingthedistinct

community parameters analysed (total abundance, diversity and evenness). Specific

differencesbetweenfactorswereanalysedusingtheTukeymultiplecomparisontest.Inthe

caseoftheecologicalfunctionanalysis,aOne-wayANOVAtestwasusedperfactor(months

andtreatments).Normalityandhomogeneityofvariancesofthedatawereassessedusingthe

Shapiro–WilktestandtheLevenemediantest,respectively.Ifdataisnotstatisticallynormal,

aNaperianlogarithm(ln)wasappliedtoensureanormaldistribution.Allstatisticaltestswere

carriedoutusingaαof0.05.

Inthestatisticalanalysisprocedure,onlytotalabundancewasused.Totalrichnessatorder

levelinthisstudycontextdisplayedverysmalldifferencesthatleadtoinconclusivestatistical

results.TheUNBplotandthesamplingperformedinSeptemberwerenotconsideredonthe

statisticalanalysisregardingdifferentsamplingperiods,becauseinSeptembernomulchwas

presentonanyplotandtheUNBsitewasonlysampledinthelasttwomonthsofthisstudy

(NovemberandJanuary).Duetothesereasons,statisticalcomparisonregardingrichnesswas

notapplicable.AcariandDipterawerealsoexcludedfromthestatisticalanalyses,considering

thepitfallsamplinglimitationsconcerningthesetwoorders.


2016

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3. Results

3.1 Environmentalvariablesanalysis

In Figure 8, it is seen that regarding precipitation, the first big events took place only at late

DecemberandearlyJanuary.Beforethatperiod,smallprecipitationeventswereregistered,always

below 50mm in a 10-day period. Betweenmid-November andmid-December, there were few

precipitationevents.Meanwhile,averagetemperatureina10-dayperiodhadasteadydeclinefrom

lateSeptembertoearlyNovember.ThetemperaturehadamajordeclineduringNovember,from

15°Ctoa7°Caverage.Afterwards,temperatureroseuntilmid-December,reachingapeakat13°C.

Inthesameperiodthattemperaturereacheditslowest,precipitationwasalsoveryscarce.January

displaysameantemperaturearound9°C.

Figure8.MeanandstandarddeviationfortemperatureandprecipitationbetweenlateSeptember2015andJanuary

2016

3.2 Communityanalysis

3.2.1 RichnessandAbundance

Duringthe4samplingmonths,thatcomprisetwoseasons(AutumnandearlyWinter),2303

ground-dwellingarthropodswereretrievedbythepitfalltraps,representingintotal14orders

(Richness): Collembola, Coleoptera, Diptera, Hemiptera, Hymenoptera, Isopoda, Thysanura,

0

75

150

225

300

375

0

5

10

15

20

25

1-Sep-15 1-Oct-15 1-Nov-15 1-Dec-15 1-Jan-16TotalPrecipitatio

n[m

m]

Tempreature[°C]

TotalPrecipitation

AverageTemperature


2016

16

Chilopoda,Araneae,Acari,Diplopoda,Pseudoscorpiones,PsocopteraandOpiliones(Appendix1

and2).

Although 14 orderswere found, only amaximum of 12were identified on one single plot

duringthesamplingperiod.TakingintoaccounttheconditionsofthehabitatinSeptember,a

considerablenumberoftaxawasyetidentified,namely8to10orders.

TotalrichnessdifferencesbetweenSeptemberandJanuarywerenolargerthan5.Thishigher

differenceoccurred in theNTplot fromOctober toNovember.TheLTplot remainedquite

equal during the sampling period, with total richness of around 10, whereas the HT plot

registeredapeakfrom8to11betweenSeptemberandNovember.Afterthemulchapplication

that occurred inOctober, it is seen that only theHTplot had an increase in total richness,

whereastheLTremainedstableandtheNThadadecrease.Ontheotherhand,inNovember,

the NT and LT had a richness growth, more accentuated on the NT plot, whilst the HT

decreased.InJanuary,theLTandUNBhadadecreaseintotalrichness,HTremainedidentical

tothepreviousmonthandtheNTincreasedfrom11to12orders(Figure9).

Figure9.Totalrichnessregardingsamplingmonthsandplots

Nostatisticallysignificantdifferenceswerefoundbetweensamplingmonthsandtreatments

viaaTwo-wayANOVAtestregardingtotalrichness(Table1).Thetestpointsoutasignificant

interaction betweenmonths and plots (treatments) (Table 1). Significant differenceswere

foundfortreatmentinNovember,namelywiththeNTandtheHT,andonmonthsintheNT

4

5

6

7

8

9

10

11

12

13

14

September October November January

Totalnum

bero

fide

ntified

Orders

NT

LT

HT

UNB

Mulch Application


2016

17

plot,namelywithinNovemberandOctoberandalsowithinJanuaryandOctoberforthesame

plot(Table2).

Table1.Two-wayANOVAsummaryregardingmonthandplotwithtotalrichnesspertrap.Significantstatisticalrelationsinboldtype.

SourceofVariation DF SumofSquares MS F P

Month 2 7.185 3.593 1.830 0.189Treatment 2 6.741 3.370 1.717 0.208

MonthxTreatment 4 23.259 5.815 2.962 0.048Residual 18 35.333 1.963 Total 26 72.519 2.789 NormalityTest(Shapiro-Wilk):passed(p=0.083)

Table2.AllPairwiseTukeymultiplecomparisontestwithinmonthsandtreatments.

Factor1 Factor2 Comparison DiffofMeans p P<0.05Treatment October HTvs.NT 2.000 0.215 No

HTvs.LT 0.333 0.954 DoNotTest

LTvs.NT 1.667 0.334 DoNotTest

November NTvs.HT 3.333 0.024 Yes NTvs.LT 1.333 0.488 No LTvs.HT 2.000 0.215 No January NTvs.HT 2.000 0.215 No NTvs.LT 0.667 0.831 DoNotTest

LTvs.HT 1.333 0.488 DoNotTest

Month NT Novembervs.October 4.000 0.007 Yes Novembervs.January 1.000 0.663 No Januaryvs.October 3.000 0.044 Yes LT Novembervs.October 1.000 0.663 No Novembervs.January 0.333 0.954 DoNotTest

Januaryvs.October 0.667 0.831 DoNotTest

HT Octobervs.November 1.333 0.488 No Octobervs.January 1.000 0.663 DoNotTest

Januaryvs.November 0.333 0.954 DoNotTest

Lookingtotheabundancefoundduringthesamplingperiodsperplot,allofthesampledplots

follow a similar trend. Earlier, it seems that before the mulch application process, the

abundance in the sampledplotsdecreased.After this firstperiod, inNovember, abundance

increased, especially on the NT andHT plots. BetweenNovember and January, abundance

decreased,buttohigherlevelswhilecomparingwithOctober(Figure10).


2016

18

Regardingtotalabundancevariationsonthesamplingperiod,atrendisidentifiedwithinthe

differentplots.FromSeptembertoOctober,allplotsexperiencedadropintotalabundance

whichwaslaterfollowedbyanincreaseinallplotsinNovember.Onthelastmonth,January,

all plots had a decrease in total abundance, to levels a little higher than the registered in

September.

Figure10.Totalabundanceregardingsamplingmonthsandplots.

Inordertobetterinterpretthedataanalysedonthepreviousfigure,relativeabundancewas

calculatedbyobtainingmeanabundanceperplot,consideringabundancelevelsoutofsetsof

threepitfalltraps(Figure11).

Figure11.Meanabundanceandrespectivestandarddeviationpersamplingmonthsandplots.

Regardingthemeanabundanceperplot,thetreatedplots(LTandHT)displayhighervaluesof

relativeabundancewhilecomparingwiththeNTplotsandtheUNB.Adecreaseofproximately

0

50

100

150

200

250

300

350

400

450

500


Totalnum

bero

fcollectindividu

als

NT

LT

HT

UNB

MulchApplication

0

50

100

150

200

250

300

350


Abun

dance

UNB NT LT HT


2016

19

50%lessrelativeabundanceisidentifiedbetweenSeptemberandOctoberoneachplot.The

peakintotalabundanceidentifiedinFigure10isalsoseenonrelativeabundance,wherethe

NTandLTplotdisplaysimilarvalues.Ontheotherhand,relativeabundanceontheHTplotin

Novemberhadalargedisparityoftotalabundancebetweenpitfalltraps,sincethestandard

deviation is larger thanthemeanabundanceonthatplot. In January, there isan increasing

relativeabundancefromtheUNBplot,totheNT,LTandtheHTplot,between25and75.

ATwo-wayANOVAtestwasperformed,consideringthesamplingmonthsandthetreatments

asfactors(Table3)(Appendix2).

Table3.Two-wayANOVAsummaryregardingmonthandplotwithtotalabundancepertrap.Significantstatisticalrelationsinboldtype.

SourceofVariation df SumofSquares MS F P

Month 2 4.817 2.408 2.537 0.107Treatment 2 0.282 0.141 0.149 0.863

MonthxTreatment 4 2.484 0.621 0.654 0.632Residual 18 17.089 0.949 Total 26 24.671 0.949

NormalityTest(Shapiro-Wilk):passed(p=0.545)

Althoughthereisnotastatisticallysignificantdifference(p=0.107)betweenmonths,thereare

considerable differences in abundances. Regarding the abundances between treatments

(plots)therearenodifferences.Theinteractionbetweenmonthsandtreatmentswasalsonot

significant.

Regardingtaxadistributionalongthestudyarea(Figure12),Collembolaisthemostabundant

order,foundoneveryplotandincreasingalongeachsamplinginmostoftheplots,followedby

Hymenoptera andAcari. Contrary toCollembola,Hymenoptera individuals decrease steadily

fromSeptembertoJanuary.Dipteraarepresentinallplots,butinlargernumbersduringthe

monthsofNovemberandJanuary.Acariarealsopresentineveryplot,althoughtheyaremore

abundant in September and January in some plots. Araneae and Coleoptera are also

representedinallplots,althoughapatternisnotyetidentifiable.ItisalsoseenthatColeoptera

abundanceintheHTplotinNovemberisthemaincauseforthemarkedincreaseinabundance

foundearlierinFigure9and10.Regardingthelessrepresentedorders,Thysanurawasonly

foundintheUNBplotandDipluraonlypresentinthetreatedplots.


2016

20

Figure12.Relativeabundanceinpercentageperplotduringthesamplingmonths.

StatisticalsignificantcorrelationsbetweenordersaredisplayedonTable4.Atabledisplaying

allresultsregardingthePearsoncorrelationtestisfoundonAppendix3.

Table4.Pearsoncorrelationbetweenordersoneachsamplingmonth.

Month OrderPair N PearsonCorrelation Sig.(2-tailed)

OctoberAraneae&Hymenoptera 3 1 0.011*

Collembola&Pseudoscorpionidea 3 0.997 0.048*November Coleoptera&Hymenoptera 3 0.997 0.05*January Acari&Coleoptera 3 -0.997 0.046*

*Correlationissignificantatthe0.05level(2-tailed).

InOctober,statisticallysignificantresultsarefoundregardingacorrelationbetweenAraneae

andHymenopteraandbetweenCollembolaandPseudoscorpionidea(Table2).Bothcorrelation

coefficientspointtowardsariseintotalabundancebetweenthepairsoforders.TheCollembola

andPseudoscorpionideacorrelationmaybeduetoa trophicrelation.OnNovemberthere is

alsoasignificantcorrelationbetweenColeopteraandHymenoptera,althoughecologicallyitis

adoubtable result considering theColeoptera total abundanceon theHTplot inNovember

(Figure12).

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

NT LT HT UNB NT LT HT UNB NT LT HT

October November January

Relativ

eAb

undance

Thysanura

Psocoptera

Pseudoscorpiones

Orthoptera

Opilionidea

Isopoda

Hymenoptera

Hemiptera

Diptera

Diplopoda

Collembola

Coleoptera

Chilopoda

Araneae

Acarina


2016

21

Figure13.TotalabundanceperorderinSeptember

ThetotalabundanceofordersinSeptembercorrespondstotheindividualstrappedinatotal

ofninepitfalls(distributedover3plots,seeFigure4)(Figure13).Atotalof518individuals

were collected in September. It is seen thatHymenoptera is the largest represented order,

followed by Collembola, Acari andAraneae. Richness, considering all plots together in this

month,is11outof14.

Figure14 shows thedistributionof themainordersperplotoneachsamplingmonth.The

“Others”representthetaxathatislessabundant(<50identifiedindividualsduringthewhole

sampling period), namely Diplopoda, Pseudoscorpiones, Psocoptera, Opiliones, Orthoptera,

Hemiptera,Isopoda,ThysanuraandChilopoda.Althoughtheseareinalowernumber,theyare

stillrelevantregardingecologicalfunctioninthepost-fireperiod.

0 50 100 150 200 250

HymenopteraCollembola

AcarinaAraneae

ColeopteraDipteraIsopoda

PseudoscorpionidaChilopoda,Opiliones,Hemiptera

TotalabundanceinSeptember


2016

22

Figure14.TotalAbundanceperplotduringsamplingmonths.

TotalabundancefollowsasdescribedonFigure9,showinghowmucheachtaxacontributes

andhoweachtaxaevolvesduringthesamplingperiod.Octoberwasthemonthwiththelowest

abundancewhereasNovemberdisplaysthemaximumtotalabundance.

CollembolashowsasteadyriseinabundanceontheHTplotofalmostfourtimesasmorefrom

September to January.On the other plots, therewas also amarked increase inCollembola,

notedfromOctobertoNovemberintheNTplot,andalsoontheLTplot,althoughnotasmuch

while comparingwith other plots. On theHT plot, there is a very high total abundance of

ColeopteraduringNovember,onemonthaftertheapplicationofmulch.Thiswasalsodisplayed

inthepreviousfigures.TheUNBplot,despitedisplayingalowertotalabundanceasotherplots,

200 individuals inNovember and 100 in January, it shows amore evenly distributed total

abundanceperOrder.

050

100150200250300350400450

Totalabu

ndance

NTPlot

050100150200250300350400450

LTPlot

050

100150200250300350400450

HTPlot

050100150200250300350400450

November January

Totalabu

ndance

UNBPlot


2016

23

3.2.1 AbundanceandEnvironmentalvariables

Table5showsthattemperatureandtotalabundancearenotsignificantlycorrelatedbythe

Pearsoncorrelationtest,yetthep-valueisclosetobesignificant.However,evennotsignificant,

thetotalabundancedecreaseswithdecreasingtemperature.

Table5.Pearsoncorrelationbetweentotalabundanceandabioticvariables.

VariablePair N PearsonCorrelation Sig.(2-tailed)Temperature&Totalabundance 3 -.638 0.065Rainfall&Totalabundance 3 -.232 0.548

3.2.2 Diversity(H’)andEvenness(J’)

Regarding diversity (H’) and evenness (J’) indexes there is a decreasing trend in both

throughoutthesamplingperiods(Figure15).Nonetheless,theHTandNTplotsshowsteeper

decreasesinbothdiversityandevennessindifferentperiods:NovemberontheNTplotand

JanuaryontheHTplot.

Figure15.TotaldiversityandtotalevennessintheLT,HTandNTplotsduringsamplingmonths

The Two-way ANOVA test pointed-out significant differences in diversity betweenmonths

(Table 6), namely from October through January (Table 7). No differences were observed

betweendifferenttreatments(Table6).TheTwo-wayANOVAtestdidnotprovidesignificant

differencesregardingevennessindifferentmonthsandplots(Table6).

0,0

0,2

0,4

0,6

0,8

1,0

0,0

0,4

0,8

1,2

1,6

2,0

LTPlot

DiversityIndex(H') Evenness Index(J)

0,0

0,2

0,4

0,6

0,8

1,0

0,0

0,4

0,8

1,2

1,6

2,0

Even

ness

HTPlot

0,0

0,2

0,4

0,6

0,8

1,0

0,0

0,4

0,8

1,2

1,6

2,0

Diversity

NTPlot


2016

24

Table6.Two-wayANOVAsummaryregardingmonthandtreatmentasfactorsanddiversityandevennessindexeshasvariables.Significantstatisticalrelationsinboldtype.

Variable SourceofVariation DF SS MS F P

Diversity* Month 2 0.249 0.125 7.779 0.042 Treatment 2 0.0574 0.0287 1.793 0.278 Residual 4 0.0641 0.0160 Total 8 0.371 0.0463

Evenness** Month 2 0.0604 0.0302 3.389 0.138 Treatment 2 0.00777 0.00389 0.437 0.674 Residual 4 0.0356 0.00891 Total 8 0.104 0.0130

*NormalityTest(Shapiro-Wilk):Passed(p=0.427)**NormalityTest(Shapiro-Wilk):Passed(p=0.242)

Table7.Tukey’smultiplecomparisonofmonthsregardingdiversity.

Comparison DiffofMeans p p<0.050

Octobervs.January 0.369 0.050 -Octobervs.November 0.0357 0.938 NoNovembervs.January 0.334 0.067 No

3.3 Ecologicalfunctionanalysis

AssignmentofordersperecologicalfunctiongrouparefoundonAppendix4.

In September, most of the taxa found were omnivore,

followedbymicrobial feeders, predators and, at last, by

very few plant feeders (Figure 16). After the treatment

wasapplied,omnivoresdecreasedandmicrobialfeeders

andplant feeders increased, fromOctobertoNovember.

InNovember,thetotalabundanceofomnivoresstandsout

ontheUNBplot,representingabout50%ofthesampled

individuals.InJanuary,about80%ofthecommunityisa

microbialfeederonallplots(Figure17). Figure16.EcologicalfunctiondistributioninSeptember

MicrobialFeeders33%

PlantFeeders1%

Omnivores51%

Predators15%


2016

25

Figure17.Ecologicalfunctionrelativeabundanceperplotduringsamplingmonths

Table8&9displaytheresultsofthePearsoncorrelationsbetweenecologicalfunctiongroups.

AllcorrelationtestresultsarefoundinAppendixes5&6.Whenthemonthsareconsidered,

there is a significant correlation between plant feeders and predators. When plots are

concerned,moresignificantcorrelationswerefound.Thecorrelationshavethepredatorgroup

incommon.OntheNTplotastrongincreasingtrendbetweenmicrobialfeedersandpredators

wasfound.OntheLTplot,therewasadecreaseofmicrobialandplantfeedersrelatedwithan

increaseinthenumberofpredators.

Table8.Pearsoncorrelationbetweenecologicalfunctiongroupsoneachsamplingmonth.

Month GroupPair N PearsonCorrelation Sig.(2-tailed)January PlantFeeders&Predators 3 1.000* 0.007

*Correlationissignificantatthe0.01level(2-tailed)

Table9.PearsoncorrelationbetweenecologicalfunctiongroupsoneachPlot.

Plot GroupPair N PearsonCorrelation Sig.(2-tailed)NT MicrobialFeeders&Predators 3 0.999 0.024

LTMicrobialFeeders&Predators 3 -1.000* 0.007PlantFeeders&Predators 3 -0.997 0.046

*Correlationissignificantatthe0.01level(2-tailed)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

NT LT HT UNB NT LT HT UNB NT LT HT

October November January

Predators

Omnivores

PlantFeeders

MicrobialFeeders


2016

26

Figure18complementsthestatisticalcorrelationsshownearlier.Onthetreatedplots,LTand

HT, the ecological function groups followed an identical trend. Omnivores and predators

decreased, microbial feeders and plant feeders increased, reaching a peak in November,

although at a different scale. Abundance per ecological function groups present also very

similarnumberof individuals.PlantfeedersontheHTrosesteeplyinNovemberduetothe

highnumberofColeoptera.

Figure18.Ecologicalfunctiongroupstotalabundanceperplotduringsamplingmonths.

ThegreatmajorityofindividualsfoundinSeptemberintheNTplotareomnivores.InOctober,

most of the groups decreased, but the microbial feeders had a slight increase. The slight

increasewas followedbya steep increase inNovember, from15 to160 individuals,whilst

other groups had a very small increase, of about 10 individuals. Ultimately, in January,

omnivores andmicrobial feeders decreased in total abundance, while predators and plant

feedersmaintainedtheirtotalabundancerelativelytoNovember(Figure19).

A One-Way ANOVA was performed to assess significant differences in ecological function

groupsregardingdifferentfactors:monthsandtreatments(Table10and12).

0

30

60

90

120

150

180HT

0

30

60

90

120

150

180LT

0

30

60

90

120

150

180NT


2016

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Table10.One-WayANOVAonfunctionalgroupsregardingsamplingmonths.

EcologicalFunction Sumof

Squares df MeanSquare F P

MicrobialFeedersBetweenGroups 13152.889 2 6576.444 12.333 0.007WithinGroups 3199.333 6 533.222

Total 16352.222 8

PlantFeeders

BetweenGroups 7698.667 2 3849.333 1.609 0.276WithinGroups 14355.333 6 2392.556

Total 22054 8

Omnivores

BetweenGroups 1510.889 2 755.444 24.545 0.001WithinGroups 184.667 6 30.778

Total 1695.556 8

Predators

BetweenGroups 10.889 2 5.444 0.212 0.815WithinGroups 154 6 25.667

Total 164.889 8

Table11.Tukeymulti-comparisontestonmicrobialfeedersandomnivoresregardingdifferentmonths

DependentVariable MonthPairs DiffofMeans p p<0.005

MicrobialFeeders

OctobervsNovember -92.66667 0.006 Yes

OctobervsJanuary -58.00000 0.050 -

NovembervsJanuary 34.66667 0.236 No

Omnivores

OctobervsNovember -17.66667 0.019 Yes

OctobervsJanuary 14.00000 0.049 Yes

NovembervsJanuary 31.66667 0.001 Yes

Table12.One-WayANOVAonfunctionalgroupsregardingtreatments.

EcologicalFunction SumofSquares df Mean

Square F P

MicrobialFeedersBetweenGroups 118.222 2 59.111 0.022 0.978WithinGroups 16234 6 2705.667

Total 16352.222 8

PlantFeedersBetweenGroups 4418 2 2209 0.752 0.511WithinGroups 17636 6 2939.333

Total 22054 8

OmnivoresBetweenGroups 66.889 2 33.444 0.123 0.886WithinGroups 1628.667 6 271.444

Total 1695.556 8

PredatorsBetweenGroups 80.222 2 40.111 2.843 0.135WithinGroups 84.667 6 14.111

Total 164.889 8


2016

28

Statisticaldifferenceswere foundonlywhenconsideringthemonthsasa factor(Table10).

Within the different months, microbial feeders and omnivores had statistically significant

differences. These differences were statistically significant between all months in both

ecological groups, except between November and January on the microbial feeders group

(Table11).Asfarasplotsareconcerned,nosignificantdifferenceswerefoundbetweenthe

ecologicalfunctiongroups(Table12).


2016

29

4. Discussion

Wildfiresconductmanydirectandindirectimpactsonecosystems(Bowmanetal.,2013).One

oftheindirectimpactsproducedbywildfiresisthealterationofthegrown-dwellingarthropod

community(Eliaetal.,2012),akeyelementonsoilquality(Stork&Eggleton,1992).Although

some studies report a cause-effect relation between fire and insects (Bowman & Murphy,

2010), few studies are clear on this matter, regarding the ground-dwelling arthropod

community’sresponsetowildfire.Thesestudiesalsodonotprovidehomogeneousoutcomes

regardingthecommunityresponseandresilience(Eliaetal.,2012).Infact,wildfireeventsare

shapedbymanydifferentvariablesthatconsequentlywillimpactontheextentofseverityof

post-fireevents(Certini,2005).

Thewildfireactsdirectlyasamortalityagentona firststage,bycremationand lethalheat

exposuretothelessmobilearborealandotherfoliage-feedingarthropods(New,2014).Soil

microandmacro-faunaaremoresusceptibledependingon the fire severity impact,mostly

relatedwithheat intensity and exposure (Certini, 2005).On a second stage, right after the

wildfireevent,awindowofopportunityopenstothemorefireresistantandmobilegroups,

namelysaproxylicinsectsandthesoil-dwellingzoophagosandsaprophagous(Moretti,Duelli

&Obrist2006).Thesegroups,withhighertolerancetofireandmoremobile,willalsobepart

ofthere-colonizationprocessoftheareaafterafire,sinceaburntsiteprovideswellsuited

habitat fortheiractivitiesandecologicalroles.Generally,predatorsarethemostnegatively

affected by fire and detrivores are more abundant in fire prone sites (Engstrom, 2010).

Indirectly,thewildfiretransformingeffectsonthehabitatsetting,byremovingvegetationand

litter,will alsopromotedifferentoutcomes.Thearthropod community compositionwill be

dependentonecologicalprocesseslikestarvation,predationorimmigration(Engstrom,2010).

Starvationwillberelatedwiththeavailabilityoffoodtosurviveinassociationwiththelossof

vegetation,which isavital source forherbivorearthropods (Haddadetal.,2009).This can

ultimatelylimitotherfood-webrelations,suchhaspredation.Outcomesfromtheseprocesses

willdeterminethepopulationviabilityinthepost-firecontext(Engstrom,2010).Ultimately,

arthropodabundanceandrichnessvariationsareusuallyrelatedwiththeverydistinctclimate

factorsfromtheMediterranean-typeecosystems,suchhastemperature,rainfallanddaylength

(Simãoetal.,2015).

Inthesensethatmostofthebiomass(vegetationandlitterlayer)islostduringawildfire,the

application of mulch, in the form of chopped eucalyptus bark, is an amendment to the

transformedhabitat.Thiswillverylikelyhavesomeecologicalvalue,sinceagreatamountof


2016

30

biomass (2.6ton to 8ton/ha considering each treatment type regarding the mulching

application)isaddedtoanecosystemthatlostagreatamount.Italsohasbeenwitnessedthat

applicationofforestresidualshasamulchingagentalsoincreasestheorganicmattercontent

inthesoil(Pratsetal.,2014),whichecologicallycanhaveapositiveeffect.Ontheotherhand,

erosioncanalsodictatehowfastanecosystemcanrecoverafterawildfire,consideringthat

erosionratesandrunoffinmono-specificplantationsofeucalyptarehigh(Pratsetal.,2015).

Theseeffectspromotethelossofnutrientscontainedinplantbiomassandsoilorganiclayers,

especiallyafterrainfallevents(Machadoetal.,2015),whichinthiscontextcanbevitaltothe

lifecyclesofmanyground-dwellingarthropods.Hence,theapplicationofmulchcontributesin

thereductionoferosion,whichcanalso,potentially,benefit theground-dwellingarthropod

community.

Onthisstudycontext,itisnecessarytotakeintoaccountoneofthemaincharacteristicsfrom

theburntarea,whichisthesoiluseinthisarea.Theareahasbeenwidelyusedhasaeucalypt

plantation.BremerandFarley(2010)statedthatbiodiversityineucalyptusplantationsislow

and,ifmanagementpracticesandfirehistoryareadded(Oliver,MacNally&York,2000),the

conjugationofbothoftenresultsonalowerbiodiversity.

FocusingontheresultsofSeptember,regardingtotalabundance,oneofthemostrelevantfact

isthatHymenoptera,exclusivelyants,wasthemostabundantordercollected,weighingabout

50%ofthetotalabundance(518individuals,in9pitfalltraps).Matsudaetal.(2011)considers

ant’sresistanttofire,sinceonlyabout2%ofthepopulationofamatureantcolonyisactiveat

surfaceleveland,therefore,exposedtofirehazards.Antsarealsoknowntobeinthelineof

thefirstorganismstocolonisedisturbedareas,forinstancebyfire,duetotheirgeneralistand

opportunistbehaviour,exploitingspaceandresourcesefficiently(Antunes,Curado,Castro&

Gonçalves,2009).ItshouldalsobetakenintoaccountthatinPortugalantsseemtothrivein

eucalyptusplantationecosystems(Zina,Garcia,Valente,Branco&Franco,2015).

Other orders, namely Collembola and Acari, each representing about 20% of the total

abundance and Araneae that represents about 10%, mostly characterize the community

immediatelyafterthewildfireevent.Collembola isaverycommonorderpresentonthesoil

thatfeedsmostlyonfungianddecayingplants(Neher,Weicht&Barbercheck,2012;Anslan,

Bahram&Tederoso,2016)andactingalsoaspreytospidersandbeetles.Itisalsoexpectedto

someextent,dependingontheseverityofthewildfire,thatcollembolansprofitfromtheeffects

producedby awildfire. In fact, there is an increaseofplantmatterdecay, considering that

coarsewoodydebrisleftoversfromthefirethatcontributeinregeneratingmicrobialactivity


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andinputofnitrogenandphosphorustothesoil(Marañón-Jiménez&Castro,2013;Brais,Sadi,

Bergeron&Grenier,2005).AcarifollowupCollembolahasoneofthemostcommonordersin

forest soils. Acari are highly diverse and regulate litter decomposition and nutrient

mineralizationrates(Camann,Gillette,Lamoncha&Mori,2008). Inthisstudy, it isbelieved

that the population of Acari sampled is mainly predators, due to their overall size and

morphologicfeaturesseenduringthescreeningprocess(Koehler,1999).Thesizeconditionin

Acariwasimposedbythemeshmeasureusedinthesamplingprocess(Chapter2.3),onwhich

Acariindividualssmallerthan1mmcouldhavebeenwashedaway.Addingup,pittfalltrapping

is also not the most adequate sampling method for sampling the full extent of Acari

biodiversity. TheAraneae are predators widely represented in forest ecosystems and also

adapted to forest fires (Buddle,Spence&Langor,2000).Araneae isexpectedonapost-fire

contextatsomelevelsincemostspiderscanrapidlyre-colonizevia long-distancedispersal,

likeballooning,andshort-distancedispersal,mainlyfromunburnedforestpatches(Buddleet

al.,2000).

Regarding ecological function groups in September, the community sampled was 51% of

omnivores,33%ofmicrobialfeedersand15%predators.Theseresultstranslatetheobtained

valuesregardingabundance,whereHymenopterawasthemostrepresentedorder.Only1%of

thesampledindividualswereclassifiedasplantfeeders,whichindicatestosomeextentthe

absenceofvegetationtofeedintherecentlyburntarea.

The second sampling took place in October, after the mulch application. Total abundance

decreasedinallplots.However,theplotwiththelargestdensityofmulchrichnessrosefrom8

to11orders.Althoughtherewasageneraldecreaseoftotalabundanceinthearea,theplot

withahighdensityofmulchmaterialattractedalargerdiversity(orderrichness)ofground-

dwellingarthropods.Infact,theLTplotregisteredasimilarlevelofrichness(10)andtheNT

plothadadecreasefrom9to7.Thisobservationmaybeduetothefactthatthemulchedareas

may provide more opportunities to survival to more groups, such as shelter and food

resources.Nonetheless,assumptionsraisedbyanalysingtotalrichnessinthisstudycaseneed

tobecarefullyconsidered.Inonehand,pitfalltrappingpresentsaflawatthislevel,inthesense

that there is a chance that orders with a very low total abundance were not sampled by

causality.Ontheotherhand,thelevelofdetailfromacommunityprovidedatataxonomiclevel

suchasOrdermaynotbeenoughtopointoutdifferencesbetweentreatments.

The fact that there was a decrease in abundance while comparing with the results from

September,mayberelatedwiththerainfallandtemperatureregisteredduringOctober.Inlate


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September and early October, very little precipitation occurred, less than 50mm and

temperatureremainedstableatameanofapproximately17°C.Infact,thelackofrainfallona

post-firecontextcanrepresentadualeffect:lowerosionfromrunoff,sincethereisnotenough

rainfallandlowvegetationgrowth,inthesensethatrainfallmostlyimprovessoilmoistureand

nutrientavailabilitythatlaterpromotevegetationgrowth,whichalargenumberofarthropods

relyon(Certini,2005).Ultimately,theseepigeicfactorsshapeseasonality,whichisakeyfactor

influencingarthropoddiversityandabundance(Shakir&Ahmed,2014).

Summing up, October’s unusual meteorological conditions seemed to delay the overall

recoveryprocessoftheecosystemdespitethemulchapplicationissuggestingaslighthigher

totalabundanceandrichnessofground-dwellingarthropodsinthemulchedplots.

InNovember,themostrelevantobservationwastheabundancegrowthnotedinallplots.The

plotsthatregisteredthelargestgrowthweretheHTandNT,from77to429andfrom44to

283individuals,presentingabout6timesmorespecimenswhilecomparingtoOctober.Infact,

consideringthatthetotalabundancegrowthtookplaceineverysampledplot,thissuggests

that seasonality is playing an important role on shaping the ground-dwelling arthropod

community. This observationhas also some support by the statistical analyses, despite the

differences not being entirely significant. Differences were only closer to be significant

regardingdifferentmonthsandonlynotedbetweenOctoberandNovember. Ifweconsider

temperatureandrainfallbeforethesamplingcampaign,itisseenasteepdecreaseofthemean

temperature,apotentialtriggerthatmarkstheendofSummerandthebeginningofAutumn

(Gallinat et al., 2015). When we include functional groups to this assumption, the most

represented group in November are themicrobial feeders. This suggests that possibly the

ecosystem conditions during late October through late November have promoted the

development of fungi and consequently an increase in organic matter decomposition, a

commonecosystemfeatureinAutumnseason(Almagro,López,Querejeta&Martínez-Mena,

2009).Mostof the totalabundanceregistered isdueto themicrobial feeders,which in this

studyonlycompriseCollembola.OtherfunctionalgroupstotalabundanceroseinNovember,

althoughvery little.Differenceswereonly statistically significant formicrobial feeders and

omnivoresbetweendifferentmonths.Consideringtheincreaseofmicrobialfeeders,andthe

total abundance values regarding the population of predators, omnivores and other plant

feeders,itseemsthatthesepopulationsmayhaverespondedtothesechanges,consideringthe

trophicinteractionswithinthesegroups.ThePearsoncorrelationtestunveilsasignificantand

astrongcorrelationbetweenplantfeedersandpredatorsinJanuaryandbetweenmicrobial

feedersandplantfeederswithpredatorsintheUNBandNTplots.Exceptionally,ontheHT


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plot,theplantfeedersincreasedmuchmoreitsabundanceincomparisonwithothergroups.

ThisobservationisrelatedwiththehighnumberofColeopteracollectedfromapitfallatthe

HTplotandthefurthersub-samplingperformedinthelaboratory.Duringthissub-sampling,

itwaspossibletovisualisethatthelargestnumberoftheseColeopteraindividuals,classified

asplantfeeders,hadmorphologicalfeaturesthatsuggestedthatthesefedonwoodyremains.

Infact,theforestresidualappliedtotheplotsurfacecouldhavelodgedthiskindofarthropods

initslarvaestage.Abioticand/orclimactericconditionssuchastemperature,rainfalloreven

seasonality could have triggered a rapid development of these Coleoptera morphospecies

(Wermelinger&Seifert,1999).ThedevelopmentoffungiintheareaduringNovembercould

also possibly been promoted by the growth of vegetation, by resprouting and by the

developmentofshrubs(Rincón&Pueyo,2010)aswellasbythealreadystatedseasonality.

Atthisstageofsampling,mulchimpactsontheground-dwellingcommunityarenotyetvery

clear, ifweonly take intoaccount totalabundanceatorder levelandecologicalgroups.No

statisticalsignificantresultswerefoundbetweendifferenttreatmentsfortotalabundanceand

ecologicalfunctiongroups.Whencomparingrichnessbetweenplots,itisseenanincreasein

total richness on the NT and LT plots, whereas the HT total richness decreased. This

observation,takingintoaccounttheconsiderationsabovementioned,suggeststhatmulchcan

becontributingtoacertaindegreeofinhibitionintherecoveryofthehabitat,inthesensethat

themulchlayercandismissthegrowthofsomefungiandplants,byeithercreatingaphysical

barrier,blockinglightandevenchemicalcontrolthroughtheleachingofallelopathicchemicals

present inwood (Chalker-Scott, 2007). This assumption can be relatedwith the density of

application,meaningthata largerdensitynormally impliesverylittleexposureoftheother

lowerlayers,whichmayinhibitplantdevelopment,whereasalessdenseapplicationallows

much more heterogeneity of ground cover. This heterogeneity can provide room for the

developmentoffungiandplants,increasingthevarietyofecologicalnichesinthearea(Menta,

2012).Consideringthescaleoftheareawhereground-dwellingarthropodsremainactive,itis

implicitthatamorediversecommunitycanbefoundduetothelargerdiversityofecological

nichesavailable,shapedbyplantrichness(Haddadetal.,2009).Theseassumptionsseemto

beassociatedtoobservedrichnessvariation,consideringagrowthontotalrichnessfrom7to

11taxaontheNTplot,alessaccentuatedincreaseontheLTfrom10to12taxa,thatcontrast

withadecreasefrom11to8taxaontheHTplot.Unfortunately,theUNBwassampledfrom

November on, and therefore, it is not possible to build comparisons taking into account

previousmonths.


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The last sampled month, January, presents a decrease of abundance when comparing to

November.Winter season conditions only arrived in late December, bringing large rainfall

events followedby lowmean temperatures. Total abundance and season changes between

months, specifically temperature changes were statistical significant, asmentioned before.

Likewise,theUNBplotalsosuggeststhesame,adecreaseofabundancealsobetweenthetwo

sampling periods fromNovember and January.When comparing total abundancewith the

otherplots,abundanceintheUNBplotisrelativelylower.ThissuggeststhattheUNBplot,since

itdidnothaveafirerecently, itdidnotundergothesamephysicalandchemicalconditions

imposedbythewildfireintheburntsite.Additionally,UNBhadarecordofawildfirein2012

and, besides themulch absence, it seems to present amore advanced and stable stage of

ecologicalrecovery,similartoresultsobtainedbyPuga(2016).

Regardingrichness,theNThaditsrichnessraisedfrom11to12,theLTandUNBdroppedfrom

12to10and10to9respectively,andtheHTremainedat8.Takingintoaccounttheresults

foundintheprevioussamplingmonths,alltheplotspresentlowerrichness,inJanuary,when

comparing to the previous months. Nevertheless, the NT plot presents the highest total

richnessrecordinJanuary,consideringallsamplingmonths.ItseemsthattheNTplot,sinceit

didnothadmulchapplied,tookmoretimetoperforminitialecologicalsuccessionsordidnot

hadthenecessaryavailabilityofresourcestopromoteafasterrecovery,unliketheHTandLT,

whereastherichnesspeak inthetreatedplotswasreachedinOctober(HT)andNovember

(LT).TheHTplotdisplayslessrichnesscomparingtotheUNBplot,pointingoutthatalarger

densityofmulchdoesnotpromoteground-dwellingarthropodsdiversity.Ontheotherhand,

supportingtheabovestatedobservation,theLTplotpresentshigherrichness.Oncemore,the

total richnessrelatedassumptionsmust take intoaccount the fact thatorder level richness

might not provide a reliable answer, as above-mentioned. In addition, the field design, the

distancesbetweentraps,aswellasthenumberoftrapsusedandtheoverallareaofeachplot

mightnothavebeenenoughtotracesignificantdifferencesinthecommunitywithindifferent

treatments.

Diversity(H’)andEvenness(J’)indexessupportmostoftheobservationsdiscussedabove.A

decreasingtrendindiversityandevennessisvisiblefrommonthtomonth,whichsupportsthe

ideathatseasonalityisshapingthecommunity.Thisdecreasingtendencyisalsosupportedby

astatisticallysignificantdifferenceinvariancesbetweenmonths,namelyOctoberandJanuary.

Therearealsosomevisibleyetsmalldifferenceswithindifferenttreatments,wherethemost

importantoneisfoundonJanuaryattheHTplot,whichhasalowerdiversityandevenness

when comparingwith LT andNT. This observation is in linewith the theory that a higher


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densityofmulchcouldpossiblyreducethenumberanddiversityofecologicalniches.When

comparingthetreated(LTandHT)anduntreatedplots(NT)withtheUNBplot,aslightlylarger

diversityisfoundontheUNBplotregardingdiversityandevenness.Thisobservationisrelated

bythewildfirehistoryandseemstoshowafurtherstageofre-establishmentofthecommunity

in the UNB plot. Once more, these indexes are calculated with total richness values and,

therefore,shouldbeinterpretedconsideringthealreadystatedlimitations.

Taking into account the main orders found during the 4 sampling months, Collembola,

Coleoptera,Diptera,Hymenoptera,AraneaeandAcari,therearesomeobservationsthatarise.

Collembolaistheordercontributingthemostontotalabundanceinallplots,especiallyfrom

Novemberon.Thisfollowsupwithwhatwasalsoobservedregardingtheecologicalfunction

groups.Dipterawereonly found, in a considerablenumber inNovember.Thisorder isnot

suitedtothepitfallsamplingsincethisordercanbeattractedbythesolutionoranimalremains

presentonthetrapstolayeggs.Hymenopterashowaninverseevolutionwhilecomparingwith

Collembola.The population ofHymenoptera decreased from September until January. This

steadydecreaseseemstoberelatedwithseasonality,regardingthetemperaturedropandhow

theactivityofantsisrelatedwithtemperature(Cerda,Retana&Cros,1998).AraneaeandAcari

displayalargerabundanceintheLTplot,whichmightberelatedwiththelargernumberof

nichesthattheLTplotoffers.


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5. Conclusion

Hymenopterawas the most represented order in September, right after the wildfire. This

findingwasexpected,consideringthatantscanusuallysurvivetoawildfireeventduetotheir

burrowing capabilities.Hymenoptera total abundance gradually decreasedduring sampling

months,mostlikelyduetoseasonality.

Althoughdifferenceswithintreatmentandsamplingmonthswereexpected,onlyseasonality

seemedtobethedriverofabundancevariationsinthisstudycontext.Statisticalresultssuggest

seasonalityasbeinga factorshapingthetotalabundanceof theground-dwellingarthropod

community,aswellasthedecreasingtendencyindiversity(H’)andevenness(J’)fromOctober

through January. Slight differences were found on community total richness during the

samplingmonths,althoughnotsignificant.

These non-significant differencesmay be relatedwith the level of taxonomic identification

usedinthisstudy.Familylevelcouldhaveunveiledbetterinterpretationsregardingecological

groups and potential relations between mulch material and certain families, yet, the time

available toproceedwith thisstudywas limitedandtherefore, itwasnotpossible toreach

Familylevel.

A lower density of mulch application seemed to provide faster response regarding the

invertebrate community, and therefore a faster recovery.A largerdensity ofmulch, on the

otherhand,didnotseemtoproduceanidenticaloutput,sincetotalrichnesswaslowerand

totalabundancehigherwhencomparingwithalowdensityofmulchandnomulchedareas.

Inageneralperspective,mulchingseemednottopromoteaspecificorder,sincenoevidence

was found regarding significant differences between orders within different treatments.

Nonetheless,anuncommonobservationofhundredsofindividualsofaColeopteraspecieslead

to the assumption that the application of mulch may have introduced organisms in the

ecosystem.


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6. Finalconsiderations

Literaturesuggeststhatanaccuratemeasureoffireseveritycanprovidemoreevidenceregarding

ground-dwelling arthropod re-establishment after a wildfire (Malmström, 2010). This

interpretationcouldallowabetterunderstandingonhowground-dwellingarthropodcommunity

response isdrivenafterawildfireandhowfardoesmulch impactspositivelydependingon the

wildfireseverity.EnvironmentalfactorssuchaspH,nutrientavailability,qualityoforganicmatter

are related with the fire severity in a post-fire context (Certini, 2005) and are also important

indicators to support ground-dwelling community parameters. Hence, fire severity accurate

assessmentcanbeveryusefulinthisstudycontext.

Forestresidualsasamulchingagentshouldbealsoreviewedinthesensethat itcancarryalien

speciesintotheecosystem,presentingapotentialthreat.

Someoftheresultsobtainedinthisstudyraisedthehypothesisthatmulchcouldhavecontributed

positively immediately on the re-establishment of ground-dwelling arthropods, although

statistically,nosignificantresultswereachieved.Inordertoreachabetterunderstandingabout

the extent of the impacts of mulch on ground-dwelling fauna, future studies should consider

identificationatfamilylevel,largersamplingplotsandtrapswithlargerdistanceintervalswithin

samplingplots.

Addinganunburntplotwith similar characteristics in this typeof studies canbe veryuseful to

comprehendhow theecological successionproceeds after thewildfire, in the sense that itwill

providecontrastingcommunityparameterswhilecomparingwithanecosystemthathadawildfire.


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References

Abbott,I.,&LeMaitre,D.(2010).Monitoringtheimpactofclimatechangeonbiodiversity:Thechallenge of megadiverse Mediterranean climate ecosystems. Austral Ecology, 35(4),406–422.http://doi.org/10.1111/j.1442-9993.2009.02053.x

Almagro,M.,López,J.,Querejeta,J.I.,&Martínez-Mena,M.(2009).TemperaturedependenceofsoilCO2effluxisstronglymodulatedbyseasonalpatternsofmoistureavailabilityinaMediterranean ecosystem. Soil Biology and Biochemistry, 41(3), 594–605.http://doi.org/10.1016/j.soilbio.2008.12.021

Altieri,M.A.,&Nicholls,C.I.(2003).Soilfertilitymanagementandinsectpests:Harmonizingsoil and plant health in agroecosystems. Soil and Tillage Research, 72(2), 203–211.http://doi.org/10.1016/S0167-1987(03)00089-8

Anslan, S., Bahram, M., & Tedersoo, L. (2016). Temporal changes in fungal communitiesassociated with guts and appendages of Collembola as based on culturing and high-throughput sequencing. Soil Biology and Biochemistry, 96, 152–159.http://doi.org/10.1016/j.soilbio.2016.02.006

Antunes, S. C., Curado,N., Castro, B. B., &Gonçalves, F. (2009). Short-term recovery of soilfunctional parameters and edaphic macro-arthropod community after a forest fire.Journal of Soils and Sediments, 9(3), 267–278. http://doi.org/10.1007/s11368-009-0076-y

Baars,M.A. (1979).Catches inpitfall traps inrelation tomeandensitiesofcarabidbeetles.Oecologia.41,25-46.

Barrientos, J.A.(1988).BasesparauncursoprácticodeEntomología.ImprentaJuvenil,S.A.Barcelona.Spain.pp.754.

Bento-Gonçalves, A., Vieira, A., Ferreira-Leite, F., Martins, J., Silva, D., Soares, V., 2011.ADAPTACLIMA—adaptationto theeffects fromclimatechange in theAVE. In:Bento-Gonçalves,A.,Vieira,A.(Eds.),Proceedingsofthe3rdInternationalMeetingofFireEffectsonSoilProperties.UniversityofMinho,15–19March,Guimarães,Portugal,pp.175–180.

Bento-Gonçalves,A.,Vieira,A.,Úbeda,X.,&Martin,D.(2012).Fireandsoils:Keyconceptsandrecentadvances.Geoderma,191,3–13.http://doi.org/10.1016/j.geoderma.2012.01.004

Bowman,D.M.J.S.,&Murphy,B.P.(2010).Fireandbiodiversity.ConservationBiologyforAll,163–180.http://doi.org/10.1093/acprof:oso/9780199554232.003.0010

Bowman,DM.J.S.,Balch,J.K.,Artaxo,P.,Bond,W.J.,Carlson,M.J.,Cochrane,M.A.,D’Antonio,C.M.,Defries,R.S.,Doyle,J.C.,Harrison,S.P.,Johnston,F.H.,Keeley,J.E.,Krawchuk,M.A.,Kull,C.A.,Marston,J.B.,Moritz,M.A.,Prentice,I.C.,Roos,C.I.,Scott,A.C.,Swetnam,T.W.,vanderWerf,G.R.,Pyne,S.J.(2013).FireintheEarthSystem.Science.324,481-484.

Brais,S.,Sadi,F.,Bergeron,Y.,&Grenier,Y.(2005).Coarsewoodydebrisdynamicsinapost-firejackpinechronosequenceanditsrelationwithsiteproductivity.ForestEcologyandManagement,220(1-3),216–226.http://doi.org/10.1016/j.foreco.2005.08.013


2016

42

Bremer,L.L.,&Farley,K.A. (2010).Doesplantation forestry restorebiodiversityorcreategreendeserts?Asynthesisoftheeffectsofland-usetransitionsonplantspeciesrichness.Biodiversity and Conservation, 19(14), 3893–3915. http://doi.org/10.1007/s10531-010-9936-4

Buddle, C. M., Spence, J. R., & Langor, D. W. (2000). Succession of boreal forest spiderassemblages following wildfire and harvesting. Ecography, 23(4), 424–436.http://doi.org/10.1034/j.1600-0587.2000.230405.x

Buddle, C.M., Beguin, J., Bolduc, E., Mercado, A., Sackett, T.E., Selby, R.D., Varady-Szabo, H.,Zeran,R.M., 2005.The impor-tanceanduseof taxon sampling curves for comparativebiodi-versityresearchwithforestarthropodassemblages.Can.Entomol.137,120–127.

Camann,M.A.,Gillette,N.E.,Lamoncha,K.L.,&Mori,S.R.(2008).ResponseofforestsoilAcaritoprescribedfirefollowingstandstructuremanipulationinthesouthernCascadeRange.Canadian Journal of Forest Research-Revue Canadienne De Recherche Forestiere, 38,956–968.http://doi.org/10.1139/x07-241

Certini,G.(2005).Effectsoffireonpropertiesofforestsoils:areview.Oecologia,143(1),1–10.http://doi.org/10.1007/s00442-004-1788-8

Cerda,X.,Retana, J.,&Cros, S. (1998). Critical thermal inMediterranean limits ant species:betweenmortalityriskandforagingperformance.FunctionalEcology,12(1),45–55.

Chalker-Scott,L.(2007).Impactofmulchesonlandscapeplantsandtheenvironment-areview.Journal of Environmental Horticulture, 25(December), 239–249. Retrieved fromhttp://www.gufc.org/wp-content/uploads/2010/12/Mulchreviewarticle(2).pdf

Chinery,M.(1993),CollinsFieldGuidetotheInsectsofBritainandNorthernEurope.London:HarperCollins.

Danks,H.V.(1992).Longlifecyclesininsects.Can.Ent.124(1):167-187

Elia,M.,Lafortezza,R.,Tarasco,E.,Colangelo,G.,&Sanesi,G.(2012).ThespatialandtemporaleffectsoffireoninsectabundanceinMediterraneanforestecosystems.ForestEcologyandManagement,263,262–267.http://doi.org/10.1016/j.foreco.2011.09.034

Engstrom,R.T.(2010).First-orderfireeffectsonanimals:Reviewandrecommendations.FireEcology,6(1),115–130.http://doi.org/10.4996/fireecology.0601115

Ferreira,A. J.D.,Alegre,S.P.,Coelho,C.O.A.,Shakesby,R.A.,Páscoa,F.M.,Ferreira,C.S.S.,Ritsema, C. (2015). Strategies to prevent forest fires and techniques to reversedegradation processes in burned areas. Catena, 128, 224–237.http://doi.org/10.1016/j.catena.2014.09.002

Ferreira,V.,Larrañaga,A.,Gulis,V.,Basaguren,A.,Elosegi,A.,Graça,M.A.S.,&Pozo,J.(2015).Theeffectsofeucalyptplantationsonplantlitterdecompositionandmacroinvertebratecommunities in Iberian streams. Forest Ecology and Management, 335, 129–138.http://doi.org/10.1016/j.foreco.2014.09.013


2016

43

Flannigan,M.,Stocks,B.,Turetsky,M.,&Wotton,M.(2009).Impactsofclimatechangeonfireactivityand firemanagement in thecircumboreal forest.GlobalChangeBiology,15(3),549–560.http://doi.org/10.1111/j.1365-2486.2008.01660.x

Flannigan,M.,Cantin,A.S.,DeGroot,W.J.,Wotton,M.,Newbery,A.,&Gowman,L.M.(2013).Globalwildlandfireseasonseverityinthe21stcentury.ForestEcologyandManagement,294,54–61.http://doi.org/10.1016/j.foreco.2012.10.022

Gallinat,A.S.,Primack,R.B.,&Wagner,D.L.(2015).Autumn,theneglectedseasoninclimatechange research. Trends in Ecology and Evolution, 30(3), 169–176.http://doi.org/10.1016/j.tree.2015.01.004

Garcia-Dominguez, C., Arevalo, J. R., & Calvo, L. (2010). Short-term effects of low-intensityprescribed fire on ground-dwelling invertebrates in a Canarian pine forest. ForestSystems,19(1),112–120.Retrievedfrom<GotoISI>://WOS:000277869800011

Gerson,E.A.,Kelsey,R.G.,1997.AttractionanddirectmortalityofPandoramoths,Coloradiapandora(Lepidoptera:Saturniide),bynocturnalfire.ForestEcol.Manag.98,71–75

Gill,H.K.,McSorley,R.,Branham,M.(2011).Effectoforganicmulchesonsoilsurfaceinsectsandotherarthropods.FloridaEntomologist.94(2),226-232.

Haddad,N.M.,Crutsinger,G.M.,Gross,K.,Haarstad,J.,Knops,J.M.H.,&Tilman,D.(2009).Plantspecieslossdecreasesarthropoddiversityandshiftstrophicstructure.EcologyLetters,12(10),1029–1039.http://doi.org/10.1111/j.1461-0248.2009.01356.x

ICNF(InstitutodeConservaçaodaNaturezaedaFloresta)(2013).IFN6-A� reasdosusosdosolo e das especies florestais de Portugal continental em 1995, 2005 e 2010: 34.http://www.icnf.pt/portal/florestas/ifn/resource/ficheiros/ifn/ifn6-resprelimv11/view.

IPCC (Intergovernmental Panel onClimateChange) (2013): Summary for Policymakers. In:ClimateChange2013:ThePhysicalScienceBasis.ContributionofWorkingGroupItotheFifthAssessmentReportoftheIntergovernmentalPanelonClimateChange[Stocker,T.F.,D.Qin,G.-K.Plattner,M.Tignor,S.K.Allen,J.Boschung,A.Nauels,Y.Xia,V.BexandP.M.Midgley(eds.)].CambridgeUniversityPress,Cambridge,UnitedKingdomandNewYork,NY,USA.

Keeley,J.E.,W.J.Bond,R.A.Bradstock,J.G.Pausas,P.W.Rundel.(2012).'Fireinmediterraneanecosystems: ecology, evolution and management'. Cambridge University Press,Cambridge,U.K.528p.

Keizer,J.J.,Doerr,S.H.,Malvar,M.C.,Prats,S.A.,Ferreira,R.S.V,Oñate,M.G.,Coelho,C.O.A,etal.(2008). ‘Temporalvariation in topsoilwaterrepellency in tworecentlyburnteucalyptstandsinnorth-centralPortugal.’Catena,74(3):192–204.

Koehler,H.H.(1999).Predatorymites(Gamasina,Mesostigmata).Agriculture,EcosystemsandEnvironment,74(1-3),395–410.http://doi.org/10.1016/S0167-8809(99)00045-6


2016

44

Kremen,C.,Colwell,R.K.,Erwin,T.L.,Murphy,D.D.,Noss,R.F.,Sanjayan,M.A.,1993.Terrestrialarthropodassemblages:theiruseinconservationplanning.ConservationBiol.7(4),796–808.

Lavorel,S.,Canadell,J.,Rambal,S.eTerradas,J.(1998).‘Mediterraneanterrestrialecosystems:researchprioritiesonglobalchangeeffects.’GlobalEcology&BiogeographyLetters,7:157–166.

Machado, A. I., Serpa, D., Ferreira, R. V., Rodrıguez-Blanco, M. L., Pinto, R., Nunes, M. I.,Cerqueira,M.A.,Keizer, J. J.(2015).Cationexportbyoverlandflowinarecentlyburntforestarea innorth-centralPortugal. Scienceof theTotalEnvironment.524-525,201-212.

Malmström, A. (2010). The importance of measuring fire severity-Evidence frommicroarthropod studies. Forest Ecology and Management, 260(1), 62–70.http://doi.org/10.1016/j.foreco.2010.04.001

Marañón-Jiménez,S.,&Castro,J.(2013).Effectofdecomposingpost-firecoarsewoodydebrisonsoilfertilityandnutrientavailabilityinaMediterraneanecosystem.Biogeochemistry,112(1-3),519–535.http://doi.org/10.1007/s10533-012-9744-x

Matsuda,T.,Turschak,G.,Brehme,C.,Rochester,C.,Mitrovich,M.,Fisher,R.(2011).Effectsoflarge-scalewildfires on ground foraging ants (Hymenoptera: Formicidae) in SouthernCalifornia.EnvironmentalEntomology.40(2),204-216.

McGavin,G.C.,2010.Insects.DorlingKindersleyLtd.

McGeochM.1998.Theselection,testingandapplicationofterrestrialinsectsasbioindicators.BiologicalReviews73:181–201.

Menta, C. (2012). Soil FaunaDiversity – Function, Soil Degradation, Biological Indices, SoilRestoration. Biodiversity Conservation and Utilization in a Diverse World, 284.http://doi.org/http://dx.doi.org/10.5772/51091

Moreira,F.,Catry,F.X.,Silva,J.S.,Rego,F.(2010).Ecologiadofogoegestãodeáreasardidas.IsaPress.

Moretti, M., Duelli, P., Obrist, M. K. (2006). Biodiversity and resilience of arthropodcommunitiesafterfiredisturbanceintemperateforests.Oecologia.149,312-327.

Neary,D.G.,Ryan,K.C.,DeBano,L.F.,2005.Wildlandfireinecosystems:effectsoffireonsoilsandwater.Gen.Tech.Rep.RMRS-GTR-42-vol.4.U.S.DepartmentofAgricul-ture,ForestService,RockyMountainResearchStation,Ogden,UT.

Neher,D.A.,Weicht,T.R.,&Barbercheck,M.E.(2012).Linkinginvertebratecommunitiestodecompositionrateandnitrogenavailabilityinpineforestsoils.AppliedSoilEcology,54,14–23.http://doi.org/10.1016/j.apsoil.2011.12.001

New, T. R. (2014). Insects, fire and conservation. Insects, Fire and Conservation.http://doi.org/10.1007/978-3-319-08096-3


2016

45

Nunes, L., Silva, I., Pité, M., Rego, F., Leather, S., Serrano, A., 2006. Carabid (Coleoptera)community changes followingprescribedburningand thepotentialuseof carabids asindicatorsspeciestoevaluatetheeffectsoffiremanagementinMediterraneanregions.SilvaLusitana14,85–100.

Oliver,I.,MacNally,R.,&York,A.(2000).Identifyingperformanceindicatorsoftheeffectsofforest management on ground-active arthropod biodiversity using hierarchicalpartitioning and partial canonical correspondence analysis. Forest Ecology andManagement,139(1-3),21–40.http://doi.org/10.1016/S0378-1127(99)00343-6

Pausas, J.G., Llovet, J., Rodrigo, A., Vallejo, R. (2008). Are wildfires a disaster in theMediterraneanbasin?–Areview.InternationalJournalofWildlandFire.17,713–723.

Pickering,D.L.,1997.Theinfluenceoffireonwestcoastgrasslandsandconcernsaboutitsuseasamanagement tool:acasestudyof theOregonsilverspotbutterflySpeyeriazereneHippolyta (Lepidoptera, Nymphalidae), in: Proceedings of the ‘‘1st conference on fireeffects on rare and endangered species and habitats’’ (Greenlee, Jason M ed). Coeurd’Alene(ID,USA)13-16November1995.

Penman,T.D.,Beukers,M.,Kavanagh,R.P.,Doherty,M.,2011.Arelong-unburnteucalyptforestpatchesimportantfortheconservationofplantspeciesdiversity?Appl.Veg.Sc.14,172–180.

Pereira,V.andFitzPatrick,E.A.(1995).Cambisolsandrelatedsoilsinnorth-centralPortugal:theirgenesisandclassification.Geoderma66,185-212.

Prats,S.A.,MacDonald,L.H.,Monteiro,M.,Ferreira,A.J.D.,Coelho,C.O.a,&Keizer,J.J.(2012).Effectivenessofforestresiduemulchinginreducingpost-firerunoffanderosioninapineand a eucalypt plantation in north-central Portugal. Geoderma, 191, 115–124.http://doi.org/10.1016/j.geoderma.2012.02.009

Prats,S.A.,Wagenbrenner,J.W.,Martins,M.M.a,&Keizer,J.J.(2014).Scaleeffectsonpost-firerunoffandsoilerosionandtheirmitigationwithforestresiduemulching.ScienceoftheTotalEnvironment,16,14631.http://doi.org/10.1016/j.scitotenv.2016.04.064

Prats, S. A., Wagenbrenner, J. W., Martins, M. A. S., Cortizo, M. M., & Keizer, J. J. (2015).Hydrologic Implications of Post-Fire Mulching Across Different Spatial Scales. LandDegradationandDevelopment.http://doi.org/10.1002/ldr.2422

Puga, J. (2016). Mulching influence on the reestablishment of ground-dwelling arthropodcommunitiesafterawildfire(Masterdissertation).

Rainio, J., &Niemelä, J. K. (2003). Ground beetles (Coleoptera: Carabidae) as bioindicators.BiodiversityandConservation,12,487–506.http://doi.org/10.1023/A:1022412617568,

Rincón,A.,&Pueyo,J.J.(2010).Effectoffireseverityandsiteslopeondiversityandstructureof the ectomycorrhizal fungal community associatedwith post-fire regenerated Pinuspinaster Ait. seedlings. Forest Ecology and Management, 260(3), 361–369.http://doi.org/10.1016/j.foreco.2010.04.028


2016

46

Shakesby,R.A.,&Doerr,S.H.(2006).Wildfireasahydrologicalandgeomorphologicalagent.Earth-ScienceReviews,74(3-4),269–307.http://doi.org/10.1016/j.earscirev.2005.10.006

Shakesby, R.A., 2011. Post-wildfire soil erosion in the Mediterranean: review and futureresearchdirections.Earth-ScienceReviews105,71–100.

Shakir, M. M., & Ahmed, S. (2014). Seasonal abundance of soil arthropods in relation tometeorologicalandedaphicfactorsintheagroecosystemsofFaisalabad,Punjab,Pakistan.InternationalJournalofBiometeorology,605–616.http://doi.org/10.1007/s00484-014-0874-9

Simão,F.C.P.,Carretero,M.A.,doAmaral,M.J.A.,Soares,A.M.V.daM.,&Mateos,E.(2015).CompositionandseasonalvariationofepigeicarthropodsinfieldmarginsofNWPortugal.TurkishJournalofZoology,39(3),404–411.http://doi.org/10.3906/zoo-1401-69

SNIRH:ServiçoNacionaldeInformaçaosobreRecursosHıdricos.(2015).http://www.snirh.pt.(LastaccessedinJanuary2016)

Spence, J. R., Niemela, J. K. (1994). Sampling carabid assemblages with pitfall traps: themadnessandthemethod.TheCanadianEntomologist.126(3),881-894.

Stork,N.E.,&Eggleton,P.(1992).Invertebratesasdeterminantsandindicatorsofsoilquality.American Journal of Alternative Agriculture, 7(1-2), 38.http://doi.org/10.1017/S0889189300004446

VegaJA,FontúrbelMT,MerinoA,FernándezC,FerreiroA,JiménezE.2013b.Testingtheabilityofvisualindicatorsofsoilburnseveritytoreflectchangesinsoilchemicalandmicrobialproperties in pine forests and shrubland. Plant and Soil 369:73–91. DOI:10.1007/s11104-012-1532-9.

Wang, C., Strazanac, J., Butler, L. (2001). A comparison of pitfall traps with bait traps forstudyingleaflitterantcommunities.JournalofEconomicEntomology.94,761-765.

Wermelinger,B.,&Seifert,M.(1999).Temperature-dependentreproductionofthesprucebarkbeetle Ips typographus, and analysis of the potentacial population growth. EcologicalEntomology,24(1),103–110.http://doi.org/10.1046/j.1365-2311.1999.00175.x

Westerman,P.W.,Bicudo,J.R.(2005).Managementconsiderationsfororganicwasteuseinagriculture.BiosourceTechnology.96,215-221.

Whelan,R.J.,1995.TheEcologyofFire.CambridgeUniversityPress,Cambridge

Wiggins, G.B.,Marshall S.A., Downes, J.A. (1991). The importance of research collections ofterrestrialarthropods.AbriefpreparedbytheBiologicalSurveyofCanada(TerrestrialArthropods).BulletinoftheEntomologicalSocietyofCanada23(2),supplement16pp.

Woodcock,B.A.,Leather,S.R(2007).InsectSamplinginForestEcosystems.Retrievedfromhttp://onlinelibrary.wiley.com/doi/10.1002/9780470750513.ch3/references


2016

47

Zina,V.,Garcia,A.,Valente,C.,Branco,M.,&Franco,J.C.(2015).Antspecies(Hymenoptera,

Formicidae)associatedtoeucalyptusplantationsinPortugal.Iberomyrmex,7(March2016),

11–16.


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Appendixes

Appendix1.Totalabundanceperorderoneachpitfalltrapandsamplingdate.

SamplingDate

Order Total Acari

Araneae

Chilop.

Coleop.

Collem.

Diplop.

Diptera

Hemip.

Hyme.

Isop

Opilio.

Orthop.

Pseudoscor.

Psocop.

Thysan.

Unindentifyed

NTPF1

25/09/15 4 2 3 1 1 16 2 1 1 2 31

14/10/15 1 2 4 5 2 12

25/11/15 9 1 13 117 12 17 2 1 2 1 175

27/01/16 10 7 52 8 1 1 1 1 7 81

NTPF2

25/09/15 9 4 7 4 16 3 40

14/10/15 2 2 10 5 1 8 20

25/11/15 10 4 1 5 23 12 7 1 7 63

27/01/16 10 2 35 1 2 1 4 51

NTPF3

25/09/15 6 4 1 3 25 1 39

14/10/15 1 2 2 1 6 1 12

25/11/15 5 2 1 2 27 5 1 2 1 45

27/01/16 3 1 1 2 8 2 2 1 1 14 21

LTPF1

25/09/15 52 4 5 3 2 1 27 1 1 3 96

14/10/15 8 6 7 1 8 1 4 10 35

25/11/15 27 2 8 44 1 14 26 1 2 44 125

27/01/16 12 2 8 1 3 1 21 27

LTPF2

25/09/15 2 16 1 3 16 1 38

14/10/15 11 2 1 47 9 1 3 1 74

25/11/15 16 3 8 73 4 2 3 1 110

27/01/16 44 1 4 40 2 1 2 2 14 96LTPF3

25/09/15 15 7 67 1 36 1 3 127

14/10/15 2 15 1 6 1 1 25

25/11/15 4 1 5 1 2 2 13

27/01/16 17 7 2 47 1 1 2 22 77

HTPF1

25/09/15 5 6 10 1 24 2 1 48

14/10/15 1 35 1 1 4 4 1 2 47

25/11/15 1 7 1 6 9

27/01/16 3 1 3 35 10 1 6 53

HTPF2

25/09/15 3 2 8 1 25 1 40

14/10/15 3 1 2 3 1 6 1 1 18

25/11/15 2 4 22 1 3 17 49

27/01/16 10 98 3 2 1 4 114

HTPF3

25/09/15 2 9 3 7 1 35 2 4 59

14/10/15 2 1 1 3 5 12

25/11/15 6 4 203 84 46 25 3 25 371


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27/01/16 14 1 6 73 1 1 2 96

UNBPF1

14/10/15 0

25/11/15 3 6 3 4 14 1 4 31

27/01/16 24 1 1 22 3 2 1 2 1 2 57

UNBPF2

14/10/15 0

25/11/15 2 3 13 29 29 22 2 2 16 102

27/01/16 4 4 14 2 1 5 25

UNBPF3

14/10/15 0

25/11/15 3 8 15 5 22 1 3 54

27/01/16 2 3 2 1 5 8


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Appendix2.SampleresultstransformationwiththeNaperianLogarithm.

Mon

th

Plot TrapNumber TotalAbundance ln(TotalAbundance)

Octob

er

NT

Trap1 12 2.4849

Trap2 20 2.9957

Trap3 12 2.4849

LT

Trap1 35 3.5553

Trap2 74 4.3041

Trap3 25 3.2189

HT

Trap1 47 3.8501

Trap2 18 2.8904

Trap3 12 2.4849

Nov

embe

r

NT

Trap1 175 5.1648

Trap2 63 4.1431

Trap3 45 3.8067

LT

Trap1 125 4.8283

Trap2 110 4.7005

Trap3 13 2.5649

HT

Trap1 9 2.1972

Trap2 49 3.8918

Trap3 371 5.9162

Janu

ary

NT

Trap1 81 4.3944

Trap2 51 3.9318

Trap3 21 3.0445

LT

Trap1 27 3.2958

Trap2 96 4.5643

Trap3 77 4.3438

HT

Trap1 53 3.9703

Trap2 114 4.7362

Trap3 96 4.5643


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Appendix3.Pearsoncorrelationtestresultsregardingorders. Araneae

Chilopoda

Coleoptera

Collembola

Diplopoda

Diptera

Hem

iptera

Hym

enopte

ra

Isopoda

Opilionidea

Orthoptera

Pseudoscor

piones

Psocoptera

October

Acarina

PearsonCorrelation

0,971

.a -0,59 0,943

.a -0,08

2

.a 0,975 .a .a .a 0,915

-1,000**

Sig.(2-tailed) 0,153

. 0,598

0,216

. 0,948

. 0,142 . . . 0,265

.

N 3 1 3 3 0 3 1 3 2 1 0 3 2

Araneae

PearsonCorrelation .a -0,38

1

0,836

.a -0,31

7

.a 1,000*

.a .a .a 0,792

-1,000**

Sig.(2-tailed) . 0,751

0,369

. 0,795

. 0,011 . . . 0,418

.

N 1 3 3 0 3 1 3 2 1 0 3 2

Chilopo

da

PearsonCorrelation .a .a .a .a .a .a .a .a .a .a .a

Sig.(2-tailed) . . . . . . . . . . .

N 1 1 0 1 1 1 1 0 0 1 1

Coleoptera PearsonCorrelation -

0,826

.a -0,75

6

.a -0,397

.a .a .a -0,86

6

.a


. 0,454

. 0,74 . . . 0,333

.

N 3 0 3 1 3 2 1 0 3 2

Collembola PearsonCorrelation .a 0,25

5.a 0,846 .a .a .a ,997* -

1,000**


. 0,358 . . . 0,048

.

N 0 3 1 3 2 1 0 3 2

Diplopo

da

PearsonCorrelation .a .a .a .a .a .a .a .a

Sig.(2-tailed) . . . . . . . .

N 0 0 0 0 0 0 0 0

Diptera

PearsonCorrelation .a -0,3 .a .a .a 0,327

1,000**

Sig.(2-tailed) . 0,806 . . . 0,788

.

N 1 3 2 1 0 3 2

Hem

ipte

ra

PearsonCorrelation .a .a .a .a .a .a

Sig.(2-tailed) . . . . . .

N 1 1 0 0 1 1

Hym

enopte

ra

PearsonCorrelation .a .a .a 0,803

-1,000**

Sig.(2-tailed) . . . 0,407

.

N 2 1 0 3 2

Isopoda

PearsonCorrelation .a .a .a .a

Sig.(2-tailed) . . . .

N 1 0 2 2

Opilioni

dea

PearsonCorrelation .a .a .a

Sig.(2-tailed) . . .

N 0 1 1


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Orthopt

era

PearsonCorrelation .a .a

Sig.(2-tailed) . .

N 0 0Pseudoscor

piones

PearsonCorrelation -1,000**

Sig.(2-tailed) .

N 2

Novem

ber

Acarina

PearsonCorrelation

-0,90

6

-1,000**

-0,82

7

0,07 .a -0,89

9

.a -0,781

-1,000**

.a .a -0,90

6

-1,000**


. 0,38 0,956

. 0,289

. 0,429 . . . 0,278

.

N 3 2 3 3 2 3 0 3 2 1 1 3 2

Araneae

PearsonCorrelation 1,000**

0,512

0,359

.a 0,629

.a 0,444 1,000**

.a .a 1,000**

1,000**


0,766

. 0,567

. 0,707 . . . 0 .

N 2 3 3 2 3 0 3 2 1 1 3 2

Chilopoda PearsonCorrelation 1,00

0**1,000**

.a 1,000**

.a -1,000**

1,000**

.a .a 1,000**

1,000**

Sig.(2-tailed) . . . . . . . . . . .

N 2 2 1 2 0 2 2 1 1 2 2

Coleoptera PearsonCorrelation -

0,618

.a 0,99 .a ,997* 1,000**

.a .a 0,512

1,000**


. 0,091

. 0,05 . . . 0,658

.

N 3 2 3 0 3 2 1 1 3 2

Collembol

a

PearsonCorrelation .a -0,5 .a -0,677

1,000**

.a .a 0,359

1,000**


. 0,526 . . . 0,766

.

N 2 3 0 3 2 1 1 3 2

Diplopo

da


Sig.(2-tailed) . . . . . . . .

N 2 0 2 1 1 0 2 1

Diptera

PearsonCorrelation .a 0,976 1,000**

.a .a 0,629

1,000**

Sig.(2-tailed) . 0,14 . . . 0,567

.

N 0 3 2 1 1 3 2

Hem

ipte

ra

PearsonCorrelation .a .a .a .a .a .a

Sig.(2-tailed) . . . . . .

N 0 0 0 0 0 0

Hym

enopte

ra


.a .a 0,444

-1,000**

Sig.(2-tailed) . . . 0,707

.

N 2 1 1 3 2

Isopoda

PearsonCorrelation .a .a 1,000**

1,000**


N 1 1 2 2

O p i l i o n i d e aPearsonCorrelation .a .a .a


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53


N 0 1 1Orthopt

era


Sig.(2-tailed) . .

N 1 1

Pseudosc

orpionesPearsonCorrelation 1,000

**Sig.(2-tailed) .

N 2

January

Acarina

PearsonCorrelation

0,983

.a -,997*

-0,43

6

.a -0,95

1

1,000**

-0,561

1,000**

.a .a .a .a


. 0,046

0,713

. 0,2 . 0,621 . . . . .

N 3 1 3 3 1 3 2 3 2 1 0 2 3

Araneae

PearsonCorrelation .a -0,99

3

-0,59

6

.a -0,99

2

1,000**

-0,397

-1,000**

.a .a .a .a


0,593

. 0,081

. 0,74 . . . . .

N 1 3 3 1 3 2 3 2 1 0 2 3

Chilopo

da

PearsonCorrelation .a .a .a .a .a .a .a .a .a .a .a

Sig.(2-tailed) . . . . . . . . . . .

N 1 1 0 1 1 1 1 1 0 1 1

Coleoptera PearsonCorrelation 0,5 .a 0,97

1-1,000**

0,5 .a .a .a .a .a


. 0,154

. 0,667 . . . . .

N 3 1 3 2 3 2 1 0 2 3

Collembol

a

PearsonCorrelation .a 0,693

.a -0,5 1,000**

.a .a .a .a


. 0,667 . . . . .

N 1 3 2 3 2 1 0 2 3

Diplopo

da


Sig.(2-tailed) . . . . . . . .

N 1 1 1 0 0 0 1 1

Diptera


0,277 1,000**

.a .a .a .a

Sig.(2-tailed) . 0,821 . . . . .

N 2 3 2 1 0 2 3

Hem

iptera


.a .a .a .a .a

Sig.(2-tailed) . . . . . .

N 2 1 1 0 2 2

Hym

enopte

ra


.a .a .a .a

Sig.(2-tailed) . . . . .

N 2 1 0 2 3

Isop odaPearsonCorrelation .a .a .a .a



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54

N 1 0 1 2

Opilionidea PearsonCorrelation .a .a .a


N 0 1 1

Orthopt

era


Sig.(2-tailed) . .

N 0 0

Pseudoscor

piones

PearsonCorrelation .a

Sig.(2-tailed) .

N 2

**Correlationissignificantatthe0.01level(2-tailed).*Correlationissignificantatthe0.05level(2-tailed).“a”

Cannotbecomputedbecauseatleastoneofthevariablesisconstant.


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Appendix4.Totalabundanceandecologicalfunctionforeachpitfallandsamplingdate.

Order

Collembola

Hemiptera

Psocoptera

Coleoptera

Thysanura

Isopoda

Coleoptera

Hymenoptera

Chilopoda

Pseudoscorpionida

Coleoptera

Aranea

Opiliones

EcologicalFunction

MicrobialFeeders

PlantFeeders

PlantFeeders

PlantFeeders

Omnivores

Omnivores

Omnivores

Omnivores

Predators

Predators

Predators

Predators

Predators

LTPF1

25/09/15 10 24 2 6 14/10/15 35 1 1 4 4 25/11/15 7 1 27/01/16 35 3 1 1

LTPF2

25/09/15 8 25 1 2 14/10/15 3 1 1 1 6 2 1 25/11/15 22 2 2 17 2 27/01/16 98 1 2

LTPF3

25/09/15 7 2 3 35 9 14/10/15 1 1 5 25/11/15 84 162 25 3 41 4 27/01/16 73 1 6 1

NTPF1

25/09/15 1 1 2 2 16 1 2 14/10/15 4 2 5 25/11/15 117 1 9 2 1 17 1 2 27/01/16 52 1 1 1 1

NTPF2

25/09/15 7 16 4 14/10/15 10 5 1 2 25/11/15 23 4 1 1 7 1 4 27/01/16 35 1 2 2

NTPF3

25/09/15 3 1 25 4 14/10/15 2 2 6 25/11/15 27 2 2 5 1 1 2 27/01/16 8 2 2 1 1 1 1

HTPF1

25/09/15 3 1 1 5 27 1 4 14/10/15 7 1 8 4 6 25/11/15 44 8 1 26 2 2 27/01/16 8 3 1 2

HTPF2

25/09/15 3 16 1 16 14/10/15 47 9 3 1 2 125/11/15 73 1 7 2 1 3 327/01/16 40 2 2 1 3 1


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HTPF3

25/09/15 67 1 36 7 114/10/15 15 1 6 25/11/15 5 1 2 27/01/16 47 1 2 1 2 7

UNBPF114/10/15 25/11/15 3 5 1 1 14 27/01/16 22 1 1 2 1 1 2

UNBPF2

14/10/15 25/11/15 29 7 3 22 2 3 227/01/16 14 1 4

UNBPF3

14/10/15 25/11/15 15 1 22 8 27/01/16 3 1


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Appendix5.Pearsoncorrelationresultsregardingfunctionalgroupswithinmonths.

Date PlantFeeders Omnivores PredatorsOctober

MicrobialFeeders

PearsonCorrelation -0,902 0,945 0,99Sig.(2-tailed) 0,285 0,212 0,091

N 3 3 3PlantFeeders PearsonCorrelation -0,993 -0,954

Sig.(2-tailed) 0,073 0,194N 3 3

Omnivores PearsonCorrelation 0,982Sig.(2-tailed) 0,121

N 3

Novem

ber

MicrobialFeeders

PearsonCorrelation -0,624 -0,457 0,984Sig.(2-tailed) 0,571 0,698 0,113

N 3 3 3PlantFeeders PearsonCorrelation 0,98 -0,752

Sig.(2-tailed) 0,127 0,458N 3 3

Omnivores PearsonCorrelation -0,607Sig.(2-tailed) 0,585

N 3

January

MicrobialFeeders

PearsonCorrelation -0,896 0,993 -0,891Sig.(2-tailed) 0,293 0,073 0,3

N 3 3PlantFeeders PearsonCorrelation -0,941 1,000**

Sig.(2-tailed) 0,219 0,007N 3 3

Omnivores PearsonCorrelation -0,937Sig.(2-tailed) 0,227

N 3**Correlationissignificantatthe0.01level(2-tailed).


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Appendix6.Pearsoncorrelationtestresultsregardingfunctionalgroupswithintreatments.

Treatments PlantFeeders Omnivores Predators

NT

MicrobialFeedersPearsonCorrelation 0,914 0,556 ,999*

Sig.(2-tailed) 0,266 0,625 0,024

N 3 3 3

PlantFeeders

PearsonCorrelation 0,846 0,898

Sig.(2-tailed) 0,359 0,29N 3 3

OmnivoresPearsonCorrelation 0,525


N 3

LT

MicrobialFeeders

PearsonCorrelation 0,997 0,242 -1,000**

Sig.(2-tailed) 0,053 0,844 0,007N 3 3 3

PlantFeedersPearsonCorrelation 0,161 -,997*

Sig.(2-tailed) 0,897 0,046

N 3 3

Omnivores

PearsonCorrelation -0,231

Sig.(2-tailed) 0,851N 3

HT

MicrobialFeedersPearsonCorrelation 0,538 0,384 -0,181

Sig.(2-tailed) 0,638 0,749 0,884

N 3 3 3

PlantFeeders

PearsonCorrelation 0,985 0,732

Sig.(2-tailed) 0,111 0,478N 3 3

OmnivoresPearsonCorrelation 0,839

Sig.(2-tailed) 0,367N 3

*Correlationissignificantatthe0.05level(2-tailed).**Correlationissignificantatthe0.01level(2-tailed).

universidade de aveiro · projeto europeu do fp7: “recare – preventing and remediating...

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