characterization of traditional healers in the mountain forest … · 2019-09-20 · b a s e...

BASE Biotechnol. Agron. Soc. Environ.201620(1),25-41

CharacterizationoftraditionalhealersinthemountainforestregionofKahuzi-Biega,South-Kivu,DRCongoChantalShalukoma(1,2),PierreDuez(3),JosephBigirimana(1),JanBogaert(4),CarolineStévigny(2),CélestinPongombo(5),MarjoleinVisser(1)(1)UniversitélibredeBruxelles.FacultyofSciences.ResearchUnitofLandscapeEcologyandPlantProductionSystems.CP264/2.BoulevardduTriomphe.BE-1050Brussels(Belgium).E-mail:[email protected],[email protected](2)UniversitélibredeBruxelles.FacultyofPharmacy.DepartmentofPharmacognosy,BromatologyandHumanNutrition.CP205/09.BoulevardduTriomphe.BE-1050Brussels(Belgium).(3)UniversitédeMons.FacultyofMedicineandPharmacy.DepartmentofTherapeuticChemistryandPharmacognosy.AvenueMaistriau,19.BE-7000Mons(Belgium).(4)UniversitédeLiège-GemblouxAgro-BioTech.UnitéBiodiversitéetPaysage.PassagedesDéportés,2.BE-5030Gembloux(Belgium).(5)UniversitédeLubumbashi.FacultyofVeterinaryMedicine.DepartmentofPharmacology,ToxicologyandTherapeutics.BP1825.Lubumbashi(DemocraticRepublicofCongo).

ReceivedonOctober15,2014;acceptedonDecember4,2015.

Description of the subject. Severalethnobotanicalstudieshavedemonstratedlinksbetweentraditionalmedicinepracticesandtheethnicityandgeographicallocationofhealers,whilemanyothershaveconcludedtheopposite.ThisstudydealswiththetypologyoftraditionalhealersinthemountainregionofKahuzi-Biega.Objectives.Thegoalistounderstandwhetherthetypologyoftraditionalhealersisrelatedtotheirinter-ethnicandinter-zonaldifferences,basedondiseasestreatedandplantsused.Method.Ethnobotanicalsurveyswereconductedusingthe“PSSVV”method.Thisinvolved88traditionalhealersrecognizedas“specialists”in33villagesadjacenttotheforestofKahuzi-Biega,inDRCongo.Multivariateanalysis(clustering,ordination,Manteltest,IndVal)wereappliedtoestablishtypologiesoftraditionalhealers.Results.Multivariateanalysesshowedthatethnicityandgeographicallocationdidnotexplainthepracticesandknowledgeofhealers.However,byusingtheIndValmethod,differenceswereobservedintheirdegreeofspecialization.Non-specializedhealers(70%)couldbedistinguishedfromspecializedhealers(30%).Twocleargroupsofspecialistsemerged;thosewhotreatbone traumaand thosewho treatobstetric-gynecologicalcomplaints.TheMantelcorrelation test revealedapositiveassociation(r =0.134,p <0.05)betweenthe“healers-plants”and“healers-diseases”matrices.Thisindicatesthathealerswhotreatsimilardiseasesusesimilarherbs.Bothtypologieshaveshowntheirpreferencesforforestspecies(81%),especiallytrees(51%).Conclusions.Thisexploratorystudysuggests that traditionalhealersarecharacterizedbasedontheirspecializations.Thisresulthelpsincreatingstrategiestopreservelocaltraditionalknowledgeandapplyittotheconservationofspecies.Keywords. Ethnobotany, forest resources, drug plants, indigenous knowledge, typology, human pathology, DemocraticRepublicofCongo.

Caractérisation des tradipraticiensde la région de forêt montagneuse de Kahuzi-Biega, sud-Kivu, RD CongoDescription du sujet.Plusieursétudesethnobotaniquesontdémontrédesliensentrelespratiquesdelamédecinetraditionnelleetl’identitéethniqueetgéographiquedestradipraticiens,denombreusesautresontmontrél’inverse.CetteétudeportesurlatypologiedestradipraticiensdelarégiondeforêtmontagneusedeKahuzi-Biega.Objectifs. L’objectifestdecomprendresilatypologiedesguérisseurstraditionnelsestliéeàleursdifférencesinter-ethniquesetinter-zonalessurbasedesmaladiestraitéesetdesplantesutilisées.Méthode.Laméthode«PEEVV»apermisdemenerdesenquêtesethnobotaniquesauprèsde88tradipraticiensde33villagesdelarégiondeKahuzi-BiegaenRDCongo.Lesanalysesmultivariées(classification,ordination,Mantel test, IndVal)ontpermisd’établirlatypologiedestradipraticiens.

26 Biotechnol. Agron. Soc. Environ. 201620(1),25-41 ShalukomaCh.,DuezP.,BigirimanaJ.etal.

1. INTRODUCTION

Throughout the world, traditional medicine isregarded as a precious heritage, particularly forcommunities in developing countries. Its importanceis well established on the African continent whereabout 80% of the populationmainly relies on herbsfor their primary health care (WHO, 2002). Despitelarge amounts of natural resources, people in theDemocraticRepublicofCongo(DRC)arestillmarkedbypovertyand insecurity(PNUD,2009).Theuseoftraditional medicine increased in the area since thestart of the armed conflict in Eastern DR Congo in1996 (Shalukoma, 2008). Indeed, in the province ofSouth-Kivuingeneral,accesstoamodernhealthcaresystem is limited.WhileWorld Health Organization(WHO) standards prescribe at least one doctor per10,000inhabitants, inSouth-Kivuthere isonedoctorper 27,699inhabitants (PNUD, 2009). However,the population’s demand for medicinal herbs exertsconsiderable pressure on vegetation, especially inprotectedareas(Mbayngoneetal.,2011).Lossofplantspeciesandbiodiversitycouldbeadirectconsequenceof the lack of regulation of the plants used intraditionalmedicineinmanyAfricancountries.Thus,ethnobotanicalstudiesareessentialforunderstandingneedsandhelpingdecision-makingwhenitcomestosustainableconservationoflocalflora.

Traditional medicine remains a complex field. Itis based on traditions, pragmatism and knowledge,transmittedorallywithoutbeingscientificallyproven.Over time, however, pharmacological and clinicalstudies have researched and shown the effectivenessofmanytraditionalpractices(Sofowora,2010).Fassin(1990) pointed out this complexity of traditionalmedicine. It is focused on disease but also involvesinstitutionsandplayersbeyondthescopeofthebodyandhealth.

Tounravel thecomplexityof traditionalmedicinewhen compared with conventional medicine,anthropologists developed different typologies ofmedicine, depending on the knowledge they were

referring to. Dunn (1976) developed an interestingtypology that talkedaboutmedicineasbeing“local”(e.g.whichcanre-grouptraditionalAfricanpractices),“regional” (e.g. comprising Arabic, Chinese andIndianmedicines)and“cosmopolitan”(thosebasedonamodernunderstandingofbiology).ComparedwithDunn,Kleinman(1980)classified:–“popularmedicine”asbasedonthefamilycircleandneighborstowhomself-medicationisprimordial;

–“folkmedicine” as practiced by traditional healerswho are non-professionals, but specialists in theirfield;

–“professionalmedicine”,likeAyurvedaandUnaniinAsia.

Unlike popular traditional medicine, specializedtraditionalmedicineisusedforcertainspecifichealthissuesthatarechronicanddifficulttotreat(Shalukoma,2008).

Specialized traditional healers are recognized assuchbytheircommunities,duetotheircompetenceinthecareofagivencategoryofdiseases(Fassin,1990;Sofowora, 2010).Often, their knowledge is acquiredthroughapprenticeship,however, theyprotectcertainknowledgetheyconsidertoo“secrets”intheirpractices.This secrecy limits the transmission of knowledgebetweenhealers,evenalongbloodlines(Pfeifferetal.,2005;Kouakou,2013).Aparadoxwaspointedoutinliteratureondiscriminatory factorsamong traditionalhealers. Some ethnobotanical studies made the linkbetween traditionalmedicine and culture on the onehand(Phillipsetal.,1993;Reyes-Garciaetal.,2006;Signorineetal.,2009;Kasikaetal.,2015)andbetweentraditionalmedicineandgeographicallocationontheother(Pardo-de-Santayanaetal.,2007;Mutheeswaranetal.,2011).Moermanetal.(1996,1999)andHeinrichetal.(1998)pointedoutthatstudieswereoftenfocusedononeethnicgroup,onetaxonomicgrouporbotanicalgenus,and rarelyconsidered theuseofplantsacrosscultures.Pfeifferetal.(2005)arguedthattransmissionof knowledge is influenced by geographical origin,local culture and gender. Finally, Augereau (2008)

Résultats.L’origineethniqueetgéographiquen’expliquepaslesgroupementsdestradipraticiens.LaméthodeIndValamontréqueleurtypologieestbaséesurleurs«spécialités»:lestradipraticiensmodérémentspécialisés(70%)etlestradipraticienshautementspécialisés(30%).Decesderniers,deuxgroupessedistinguentnettement,ceuxquitraitentletraumatismedesosetceuxquitraitentlestroublesdesorganesreproducteurs.LacorrélationpositivedeMantel(r =0,134,p <0,05)entrelesmatrices«tradipraticiens-plantes»et«tradipraticiens-maladies»asuggéréqueles tradipraticiensquisoignent lesmêmesmaladiesutilisentengrandepartie lesmêmesplantesdans leurspratiquesmédicales.Lesdeuxtypologiesontmontréunepréférencepourlesespècesforestières(81%),enparticulierlesarbres(51%).Conclusions.Cetteétudeexploratoiresuggèrequelatypologiedestradipraticiensestbaséesurleursniveauxdespécialisationsetnonsurleursdifférencesethniquesetgéographiques.Cerésultatestutilepourpréserverlesconnaissanceslocalesetlesrendreutilespourlaconservationdesespèces.Mots-clés.Ethnobotanique,ressourceforestière,plantemédicinale,connaissance indigène, typologie,pathologiehumaine,RépubliqueDémocratiqueduCongo.

TraditionalhealersoftheKahuzi-Biegaregion,DRCongo 27

pointedoutthateachethnicgrouphasitsownmedicinedeferential to the local flora and environment, andestablishes itsownrulesregarding therecognitionofplantsproperties.

However,thereisalsoabodyofresearchshowingthat significant links between culture and medicinalpracticesdonotexist.Moermanetal.(1999)showeda remarkable trendof similarity in theuseofcertainmedicinalplants,regardlessofgeographical location,oftraditionalhealersinChiapas,NorthAmerica,KoreaandKashmir.Sopetal.(2012)demonstratedthat theuseofherbsasmedicinewasnotculturallyinfluencedamongtheFulani,SamoandMossigroupsinBurkinaFaso.

Thisstudyfocusesontheknowledgeandpracticesofspecialisttraditionalhealersfromfourethnicgroups,Batwa,Havu,ShiandTembo, located inKaleheandKabare territories, respectively, around themountainforestofKahuzi-Biega.Thisforestishometomanyfloraand fauna species, including theendangered lowlandgorilla (Gorilla berengeigraueri) and the threatenedeastern chimpanzee (Pan troglodytes schweinfurthii).It also possesses a very important ethno-medicinalpotential.An understanding of the local practices ofhealerswillhelpindefiningconservationprioritiesandimplementing long-term management strategies forspeciesinaforestregionheavilyburdenedbyhumanactivities(Sopetal.,2012).

Themainobjectiveof this study is tounderstandthefactorsstructuringthebasicorganizationofhealersthrough the traditional medicinal practices recordedinthearea, inorder topreservelocalknowledgeandmakeuseofitintheimplementationofstrategiesforsustainablespeciesconservation.Wehypothesizethatthe ethnic affiliations and geographical locations ofhealersaresignificantstructuringfactors.

2. MATERIALS AND METHODS

2.1. Study site

Surveys were conducted around themountain forest of Kahuzi-Biegain the province of South-Kivu, inEasternDRC(Figure 1).The600km2park, created in 1970 to protect thelowland gorillas, covers lowlandforest (600m-1,200m a.s.l.) andrainforestmountain(1,700m-3,308ma.s.l.), which are connected by anecological corridor (ICCN, 2009).The park, a world heritage site,has been endangered since 1997(ICCN, 2009) due to the humanpressure. The highland region of

the park is characterized bymountains. The climateis of the afromontane type,with amaximum annualprecipitationofup to1,900mm(Fischer,1993).Themain ethnic groups are Havu (Kalehe territory), Shi(KabareterritoryandKaleheterritory,Kalongeaxis),Tembo (Kalehe territory, Bunyakiri axis) and Batwa(locatedinbothlocalities).

2.2. Ethnobotanical surveys

An ethnobotanical survey was conducted between2010 and 2012 to collect data on traditional healers,pathologies treated and plants used. To ensure thereliabilityofdata,wedevelopedamethodologythatishelpful,butdemandingintermsofresourcesandtime.Thisso-called“PSSVV”studywasconductedinfoursteps (Figure 2): Pre-survey (PS), Survey (S), DataVerification (V) and Data Validation (V). The fieldinvestigationswereaffectedbytheprecarioussecuritysituation in the study region. The sampling wasexhaustivebecausethenumberofspecialisthealersintheregionislimited.Atotalof88recognizedhealerswas identified during pre-survey sessions. They allagreed to collaborate on the study.At their request,interviews were done individually. To motivaterespondents, the purpose of the study was largelyexplained.Acashgiftofappreciationwasgivenafterinterviews,generallyup to50USD, representing thevalueofagoatwithreferencetotheculture.Interviewscomprised questions relating to the identification ofhealers, the main diseases they treat and the plantsthey use to heal these diseases. The triangulationmethod, which enables the cross-checking of data(Guillemont,2006),wasused tocheck the reliabilityofdatacollectedindifferentlocalities.Datarelatingtodiseasesanddiagnosis(symptomsand/orphysiologicaleffects) were verified and, when necessary, clarifiedbyhealthagentsinhospitalsandlocalhealthcenters.

Figure 1. Study area:Kahuzi-BiegaNational Park—Zone d’étude : Parc National de Kahuzi-Biega.

0 20 40km

LegendKahuzi-BiegaBukavuRoadsLakeKivuBorderDRCStudyarea

N

MontKahuzi

MontBiegaTshivanga

Bukavu


Figure 2. Schematic presentation of the ethnobotanical method “PSSVV” used around the Kahuzi-Biega NationalPark—Présentation schématique de la méthode ethnobotanique « PEEVV » utilisée autour du Parc National de Kahuzi-Biega.

Goal:explorationofthestudyareaandcollectionofdataontraditionalhealersrecognizedasexpertsinthefield(identityandhomelocation)

1. Pre-survey (PS)

(2009)

2. Surveys (S)

(2010-2012)

3. Data verification (V) (2010-2012)

4. Data validation (V) (2010-2013)

Goal:checkconsistencyofdata

Goal:agreeonthenamesthatdesignatediseasesandplantsmentionedinvariouslocallanguages

Goal:collectofindividualethnobotanicaldatafromeachhealer

Target:localchiefs,civilsocietyorganizations(NGOs,primaryandsecondaryschools,churches),n=91healersidentified

Techniques:meetingsandopeninterviews

Targets:healersidentified,n=88;diseases,n=115listed,medicinalspecies,n=217listed

Tools:investigationrecords

Techniques:individualinterviewsuponrequestofhealers,n=88

Targets:a.healersthemselvesfromdifferentethnicgroupsanddifferentvillages;b.staffofthePark;c.localpeople,includingtheelderlyandwomen.Diseases,n=96;medicinalspecies,n=77.

Techniques:a.triangulationofdata;b.personalinterviews;c.identificationandcollectionofsamplesinnaturalenvironmentswithinsmallgroupsofhealers;n<10,uponourrequest.

Targets:stakeholdersinthestudyandotherexternalpersons;4plantnamingsessionswithmorethan20participantspersession.

Techniques:a.interviewstovalidatenamesandsymptomsofdiseases,n=96,byhelpofhealthworkersinhospitals;b.videoprojectiononidentifiedspeciesintheirnaturalenvironments,n=77;c.identificationofplantsinherbaria(DRCongoandBelgium)


“Diseases”werethenclassifiedintothedifferent“usecategories”accordingtoCook(1995).Incontrastwiththe very complexWHO system for the InternationalClassification of Diseases (ICD), this practicalcategorization serves to group diseases dependingonwhether they affect a given systemof the humanbody, allowing an easier understanding of healers’descriptionsoftreateddiseasesandsymptoms.Duringinterviewsconcerningherbs,acitationwasconsideredas a “use score” (Treyvaud-Amiguet et al., 2005).These“usescores”,oncerecordedfromhealers,wereverified with different sources and through differentchannels toensurecorrespondencewith listedplants,their scientific names and their vernacular names.Species mentioned in the various local languages,including Mashi, Kitembo, Kihavu, and sometimesKirega, had to be identified and collected duringforest excursions. Following Ichikawa et al. (2003),thecorrect identificationofspeciescanonlybedonein their natural environment. Forest excursionswereconductedwithsmallgroupsofhealers,dependingontheaffinitiesbetweenthem.Othervillagemembersandparktechnicalstaffwereconsultedonthenamesofcitedherbs. Slides of identified herbswere projectedwithdifferentgroupsofhealerstoconfirmandcompletethebotanicallist.Theidentificationofsampleswasdonein herbaria of the Centre de Recherche en SciencesNaturelles, CRSN/Lwiro (DRC) as well as in theHerbarium and Library of African Botany, BRLU/ULBandinMeiseHerbarium(Belgium).Thenamingsystem of the flora of Rwanda and from the lists offloweringplantsoftropicalAfricawasapplied(Lebrunet al., 2006). Formal and informal interviews withhealers,variousdiscussionswithallstudystakeholdersandexcursionsintotheforestweremadepossiblebythecollaborationestablishedduringthework.

2.3. Data analysis

Todeterminewhetherthereisasignificantdifferencebetweenhealersonthebasisofdiseasestreatedandplantsused, we performed cluster analysis and ordination,identifiedindicatorspeciesthroughtheIndValmethodandcarriedoutaChi2testbasedontheethnicityandgeographical location of healers. The analyses werebased on two distance matrices, a binary matrix of88healersx96diseasesandasemi-quantitativematrixof88healersx 77plants.For thebinarymatrix,datawererepresentedbyvalues“1”or“0,”dependingonwhether thehealer treated thediseaseornot.For thesecond matrix, the numbers at the intersection of aplantandahealerrepresentedthenumberoftimesoneand the same specieswasmentioned to treat one orseveraldiseases.Thementionsoforgansusedforeachspecieswerecollectedqualitativelyfordocumentationpurposes.

The survey information was summarized bymultivariate analysis using the software for ecology,PC-Ord 5.0 (McCune et al., 2002). In ecology,classification organizes community types dependingon their calculated similarities or dissimilaritieswithdistancemeasuresandordinationmethods,toimprovethe understanding of relations between species andenvironments (McCune et al., 2002). In this study,the relations concern healers with their plants usedand diseases treated. The groups were discriminatedby ascending hierarchical classification with theflexible-betaclusteringmethod(β=-0.25)associatedwith the Sørensen similarity index. Non-MetricMultidimensional Scaling (NMMS) was applied tobothmatrices,healersxdiseasesandhealersxplants.TheautopilotmodeoftheNMMSenabled50iterationsof real data to be compared with 50iterations ofrandom data to select the dimensionality.To find anacceptablesolution,200iterationswereperformedonthestabilitycriterionof0.00001,withtwodimensions.Indicatorspeciesandindicatordiseaseswereidentifiedforeachgroupofhealers,basedontheIndValmethod(Dufrêne et al., 1997) available in the softwarePC-Ord, 5.0 (McCune et al., 2002). In ecology, thisprocedure combines the relative abundance andrelativefrequenciesofspeciestoidentifyineachgrouptheindicatorspeciesandtheirvalues(0-100%).Inthisstudy, the statistical significance of these indicatorvaluesforeachspeciesordiseasewasevaluatedbyaMonteCarlomethodwith5,000randomizations,withathresholdα=0.05.Healergroupswerenamedbasedon their indicator speciesordiseaseswhichobtainedmaximum and significant indicator values. The toptwowereconsideredfordiseasesandthetopthreeforplants.

Correlationsbetweendistancematricesofhealers-diseases(binary)andhealers-plants(abundance)werecalculatedusingaManteltest(Mantel,1967;McCuneetal.,2002)andtheSørensendistancemeasure.

3. RESULTS

3.1. Diversity of diseases treated as a basis for healers’ typology

A total of 96diseases grouped into 18categories(Appendix 1)werereportedtobetreatedbyspecializedhealers around the park.Themost important diseaseclasses were infectious (14%), digestive (14%) andgenitourinarydisorders(13%).

Threegroupsofhealerswereidentifiedfromclusteranalysis(Figure 3):group1wascorrelatedtothetwoNMMSordinationaxes,whilegroups2and3showeda better correlation with axis2 (Figure 3). The twoextractedaxesrepresent20%ofthetotalvariance,9%


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beingexplainedbyaxis2andtheremaining11%beingexpressedbyaxis3.

Indeed,thethreeidentifiedgroupsofhealerswerenotrelatedtotheirethnicaffiliation(x² =1.33;df=6;p>0.05)ortothegeographiclocationoftheirhomes(x² =1,86;df=6;p>0.05).Thedifferentiationofthesethreegroupsisinsteadexplainedbythespecializationofhealersinthetreatmentofthediseases,accordingtotheindicatorvalueanalysis(Table 1).

Group1 contains healers moderately specialized(HMS). They are recognized specialists but treat awiderangeofdiseases(51%ofdiseasestreated;zeroindicatordisease).

Group2 consists of healers highly specialized inobstetrics and gynecology (SOG), treating about 25%of diseases, mainly sexual impotence (IV [indicator value]=38.8%),uterineprolapse(IV=37.6%),gastriculcer(IV=31.3%)andthreatenedabortion(IV=28.0%).

Group3 consists of healers highly specializedin bone trauma (SBT). The SBT cares for 24% ofdiseases,mainlycomprisingfontanelanomalies(IV=21.2%)andfractures(IV=92.2%).

3.2. Diversity of medicinal plant species as the basis for identifying typology of healers

A total of 77medicinal species was recorded fromthe healers involved in the study. These speciesrepresented 72genera and 41botanical families(Appendix 2). TheAsteraceae family was the mostimportant,with10generaand13species,representing17%of the totaldiversity.Among themorphologicaltypesidentifiedinthepracticesofhealers,treeswerethemost used (51%), followedbyherbaceousplants(22%),shrubs(21%)andvines(6%)(Figure 4).Withabout 81% of the species being extracted from the

Kahuzi-Biega, this forestwas theharvesting locationmost frequented by healers. The remaining plantswere collected from fallows (17%) and fields (2%).Among themedicinal species cited,Prunus africanaandAutranella congolensis are listed as endangeredspecies,duetotheirheavyexploitationfortimberandbarkformedicinalpurposes(IUCN,2015).However,notindicatorspeciesofanygroup.

Four groups of healers were identified from thecluster analysis of the 88healersx 77plants matrix(Figure 5).The twoextractedaxes represent24%ofthetotalvariance,11%beingexplainedbyaxis2,andtheremaining13%beingexpressedbyaxis3.

Again,therelationshipofthesegroupswithethnicaffiliation(x2 =6.62;df=9;p>0.05)aswellaswithgeographic location (x2= 6.82; df= 9; p> 0. 05) ofhealerswas insignificant. Instead, thespeciesharvestsiteseemedtodifferbetweenthesegroupsofhealers.

Group1compriseshealersusingcultivatedmulti-use species (UCMUS). The indicator species ofthis group areAloe barbadensisMill. (IV= 28.6%),Baissea multifloraA.DC. (IV=14.7%) andPlantagopalmataHook.f. (IV= 19.2%).The first two specieshave multiple uses in traditional medicine and arewidelyaccessible.Plantago palmataiscultivatedandsometimesusedasanornamentalplant.

Group2 comprises healers using forest multi-use species (UFMUS). It is indicated by 11species

Table 1. Indicator diseases for discriminated groupsof healers — Maladies indicatrices des groupes de tradipraticiens.Group Indicator

diseasesIndicatorvalue(%)

p

HMS - 0 0SOG Sexualimpotence 38.8 0.001

Uterineprolapse 37.6 0.003Threatenedabortion 28.0 0.006

SBT Fontanelle 21.2 0.013Fracture 92.2 0.001

HMS:healersmoderatelyspecialized—tradipraticiens moyennement spécialisés;SOG:specialistsofobstetricsandgynecology—tradipraticiens spécialistes des troubles obstétriques et gynécologiques;SBT:specialistsofbonetrauma—tradipraticiens spécialistes des traumatismes des os.

Figure 4.ProportionsofmorphologicaltypesofmedicinalspeciesusedbydiscriminatedgroupsofhealersaroundthePark—Proportions des types morphologiques des espèces médicinales utilisées par les groupes de tradipraticiens dans le Parc.

UCMUS:healersusingcultivatedmultipleusesspecies—tradipraticiens utilisant des espèces cultivées à usages multiples;UFMUS:healersusingforestmultipleusesspecies—tradipraticiens utilisant des espèces forestières à usages multiples;USMO:healersusingspeciesofmixedorigins—tradipraticiens utilisant des espèces d’origine mixte;USFS:healersusingspeciesfromsecondaryforests—tradipraticiens utilisant des espèces de forêts secondaires.

1009080706050403020100

%

Vines

Herbs

ShrubsTrees

UCMUS UFMUS USMO USFS


Figu

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spèc

es d

’ori

gine

mix

te (U

SMO

);

grou

pe 4

roug

e : t

radi

prat

icie

ns u

tilis

ant p

rinc

ipal

emen

t des

esp

èces

des

forê

ts se

cond

aire

s (U

SFS)

.

Distance(objectivefunction)

Inform

ationremaining

(%)

040

8

0

Axis2

80 40 0

Axis3

1 2 3 4


(Table 2) most of which are forest species (62%)including Carapa grandiflora Sprague (IV= 26.2%),Piper capense L.f. (IV = 21.9%) and Anisopappus africanus(Hook.f.)Oliv.&Hiern(IV=21.4%).

Group3consistsofhealersusingspeciesofmixedorigins(USMO).TheindicatorspeciesofthisgroupareTragia brevipesPax(IV=35.4%),Syzygium cordatumHochst. ex Krauss (IV= 27.0%), Ensete ventricosum(Welw.) Cheesman (IV= 21.2%), Hibiscus noldeaeBakerf.(IV=20.2%),Zanthoxylum lemairei(DeWild.)(IV =17.8%)andKirkia acuminataOliv.(IV=15.8%).Halfofallthespeciesusedbythisgrouparewildandtheremainderisruderal.

Group4 consists of healers using secondary forestplant species (USFS). Two indicator species aresecondaryforestspecies:Maesa lanceolataForssk.(IV=31.8%),Trema orientalis(L.)Blume(IV=37.1%)andDrymaria cordata (L.)Willd.exSchult.(IV=41.0%).

3.3. Consistency between typologies of healers identified from diseases treated and medicinal plants used

The Mantel test revealed a significant correlationbetween the two typologies of healers based ondiseasestreatedandmedicinalspeciesused(r=0.134,p<0.05).

The superposition of typologies indicated thatmost healers using multi-use species (UCMUS andUFMUS)werehealersmoderatelyspecialized(HMS).A large proportion of healers specializing in bonetrauma (about 64%ofSBT) corresponded to healersexploiting secondary forest plant species (USFS).About 27% of healers specializing in obstetrics andgynecology(SOG)wereexploitersofspeciesofmixedorigins(USMO).

Table 2.Indicatorspeciesoffourgroupsofhealers—Espèces indicatrices de quatre groupes de tradipraticiens.Group Indicator species Indicator value (%) pUCMUS Aloe barbadensisMill. 28.6 0.002

Plantago palmataHook.f. 19.2 0.033Baissea multifloraA.DC. 14.7 0.049

UFMUS Carapa grandifloraSprague 26.2 0.003Bidens pilosaL. 23.9 0.012Ageratum conyzoidesL. 22.1 0.004Piper capenseL.f. 21.9 0.016Anisopappus africanus(Hook.f.)Oliv.&Hiern 21.4 0.004Parinari excelsaSabine 18.5 0.016Clerodendrum welwitschiiGurke 17.9 0.006Entandrophragma excelsum (Dawe&Sprague)Sprague 17.9 0.020Myrianthus holstii Engl. 17.9 0.010Alchornea hirtellaBenth. 14.3 0.036Begonia meyeri-johannisEngl. 17,3 0.020

USMO Tragia brevipesPax 35.4 0.001Syzygium cordatumHochst.exKrauss 27.0 0.007Ensete ventricosum(Welw.)Cheesman 21.2 0.011Hibiscus noldeaeBakerf. 20.2 0.028Zanthoxylum lemairei (DeWild.)P.G.Waterman 17.8 0.016Kirkia acuminataOliv. 15.8 0.022

USFS Drymaria cordata(L.)Willd.exSchult. 41.0 0.001Maesa lanceolataForssk. 31.8 0.002Trema orientalis(L.)Blume 37.1 0.001

UCMUS,UFMUS,USMO,USFS:seefigure 4—voir figure 4.


4. DISCUSSION

Rather than ethnicity or geographic factor, healersweredifferentiatedaccordingtotheirdegreeandtypeof specialization. The plants they use are correlatedwithdiseasestheyarespecializedin.

4.1. Diversity of diseases treated and the typology of traditional healers

Thisstudyrevealedtheexistenceoftwocategoriesofhealers around themountain forest ofKahuzi-Biega:healers moderately specialized and healers highlyspecialized. The first category represents a largemajorityofhealers(70%),whilethesecondrepresentsaminority(30%).Mostmoderatelyspecializedhealershave an expertise that encompasses many kinds ofdiseases, while healers highly specialized generallyfocusononlyonegroupofdiseasesorona specificmodeof traditional practices. IndistrictsofAbidjan,Manouan et al. (2010) found a similar pattern of ahighproportionofnon-specializedhealers(79%)andalowproportionofspecialists.AccordingtoKouakou(2013),manyhealersoftenlengthentheirlistofskillsin order to be considered useful and honorable intheir communities. However, the financial benefitsof theprofession also encouragepeoplewith limitedknowledgetomasqueradeashealers.Accordingly,itisthereforeimportant,withthehelpofthecommitmentoflocalcommunities,todifferentiaterealhealersfromthoseparticularlymotivatedbymoneyandpower.Thisneedformoneymightalsoencouragethemtobecomemore specialized in some category of diseases. Theresult is that theywill not be so good at diagnosingand treating thevarietyofdiseasesprevalent in theircommunities.

4.2. Diversity of medicinal plant species and typology of traditional healers

InKahuzi-Biegaregion,theuseoftreesbyhealersisa reality compared with other morphological types.ThistrendwasreportedinotherregionsinAfrica,e.g. in Zinguinchor in Senegal (Diatta et al., 2013), forhealersinSouthOmo,Ethiopia(Tolossaetal.,2013)and in Limpopo province, South Africa (Potgieteretal.,2012).Thisisexplainedbythefactthatwoodyspecies generally present a higher concentration ofsecondarymetabolites,notablyalkaloidsorsaponins,compared with herbaceous species (Hladick et al.,1997).According toBitsindou(1996), thesignificantuse of bark in traditional medicine is linked to itsoften important role in the biosynthesis and storageof secondary metabolites, but also for its ease ofcollection and/or preservation, compared with otherpartslikeroots,leavesorlatex.

Healersprefercollectingplantsfromtheforest,evenwhensomespeciesareavailableinvillages.Asimilarattitude was reported in Madagascar by Rasoanaivo(2005),whofoundthatplantshaveahighcontentofactive ingredients as a result of growing in naturalhabitats.Collinsetal.(2006)alsonotedthatinTimor-Lestecultures,healerspreferspeciesfromtheforest.The trend is similar in Morocco, where medicinalspeciesfromforestshaveahigherculturalvaluethanthosecollectedinthevillage(Mehdiouietal.,2007).Inothercountrieswhereforestsareuncommon,suchas Burkina Faso, healers prefer to collect medicinalplantspeciesingalleryforests(Olivieretal.,2012).

4.3. Consistency of typologies of traditional healers based on diseases treated and plants used

Amongthefourethnicgroupsstudiedaroundtheforestof Kahuzi-Biega, the findings of this study suggestthatmedicinal practices are not influenced by eitherthe ethnic group or geographical location of healers.Healersoftenusealmostthesamespeciestotreatthesame identified diseases. A similar observation wasmade in Beni and Lubero territories, where Kasikaet al. (2015) found that specialist healers showedthe convergence of use of species against recurrentdiseases among Bantus and Pygmies groups. Thismaybeexplainedbytheirexpertknowledgeofusefulplants.Also,geographicalproximitycanenablesimilaraccesstothewholebiodiversityinthearea,includinglow forest and mountain rainforest. According toSaslis-Lagoudakis et al. (2014), the distribution andavailability of plant species are controlled by localenvironmentalconditionssothatdifferencesincultureand language represent no predispositions to thedifferencesinpracticesandusesofmedicinalplants.

4.4. Implications of traditional healer typologies for species conservation

Traditional medicine practitioners, moderately orhighlyspecialized,areoftenconsultedbylocalpeoplefor healthcare.They all use drugs fromplants and alargeproportionoftheseplantsareobtainedfromwildsources and particularly from the forest. Thus, theycan negatively impact species when plant collectionmethods do not respect sustainable harvestingrequirements.AccordingtoRichter(2015),mechanicalinjuriescausedbyhumanstotreesleftunharvested,inthe long term, usually reduceswoodquality becauseinjuriesoftenleadtofungalinfectionwithsubsequentwooddiscolorationanddecay.During theharvestingof plant parts, in most cases, wounds and injuriescan further increase the vulnerability of species bypreventingrecovery,whiletheforestsareintheprocessof disappearing.Traditional practitioners also have a


positiveroletoplayasoneofthestakeholdersintheconservation of plant diversity. Their contribution isdemonstrated and recognized through the practiceof cultivating medicinal plant species (Cunningham,1993).As long as a plant is known and successfullyused by healers, it will be harvested. This suggestshighlightingbestpracticesandknowledgeoftraditionalhealersbasedontheirspecialties.Activeinvolvementinex situconservationeffortsisanalternativetoprotectawidevarietyofplantspecies.Providingsupportforplantingmedicinal species in community gardens orincorporatingthemintocropfieldsconstitutessomeofthepathwaysforpreservingwildwoodyspecies.

5. CONCLUSIONS

Thisstudyrevealstheimportanceofknowingthebasisoftheorganizationoftraditionalpractitionersinordertobetterunderstand localized traditionalmedicine. IthasrevealedthatintheKahuzi-Biegahighlandregion,traditional medicine is not influenced by the ethnicaffiliation or geographical location of healers.Basedondiseasesandplantsused, this traditionalmedicineis mainly dependent on the healer’s specialization.The study also suggests that traditional healers canbe characterized on the basis of the type of theirknowledge;ashealersmoderatelyorhighlyspecialized.Healers moderately specialized use several plants totreat a great number of diseases and healers highlyspecialized use particular plants to treat a limitedgroupofdiseases.Twocleargroupsofhealershighlyspecializedemerge: thosewhotreatbonetraumaandthose who treat obstetric-gynecological complaints.Bothtypologieshaveassociatedpreferencesforforestspecies,especiallytrees.

The fact that (i) neither ethnic origin norgeographical location could structure the group oftraditional healers and that (ii) plant use and diseasespecialization were correlated suggests we shouldconsider them as one community sharing a commonsetofpracticesandasinglebodyofknowledge.Thisresult begs thequestion: towhat degreeof ethnicorgeographical distance can knowledge be shared? Inotherwords,fromwhichpointdothesefactorscomeinto play.This exploratory study also raises context-specificquestions,suchaswhynootherspecializationshave been encountered, how knowledge is sharedbetween ethnic groups and different localities and ifspecificpracticescanbelinkedtotheendangermentofspecificspecies,suchasendemicforesttrees.

Acknowledgements

WethankCTBforthegrantthatsupportedourPhDstudies.WealsothankICCN/KBNPandhispartnersGIZ,USFWS,

WCSandtheVanBuurenFoundationforthematerialandfinancial support for field work. We are grateful for thecollaboration of colleagues at PNKB, CRSN/Lwiro andMEISE.Mostofall,wethankthepopulationlivingaroundtheforestofKBNPwhoagreedtocollaborateandsharetheirtremendousethnobotanicalknowledge.

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Appendix 1. Listofdiseases—Liste des maladies.Classe Disease Vernacular name Group Indicator value

(%)p*

Infectiousdisorders Amoebiasis Eamibe 1 22.5 0.0751Oralcandidiasis Chaminyagu 2 4.2 0.9640Cholera Mukunguru 2 6.7 0.3173Immunodeficiency Muzirho 3 6.4 0.5145Fever Ihoma 1 1.6 10.0000Gastroenteritis Kadurha 1 4.8 0.7628Hepatitis Budiku 3 8.7 0.3824Helminthiasis Nzokay’omunda 1 8.1 0.4084Jaundice Ensiko 1 1.6 10.0000Leprosy Bibenzi 2 20.0 0.0060*Gingivitis Ndwalay’ekanwa 1 1.6 10.0000Taeniasis Tegu 3 9.1 0.1461Tuberculosis Chigoholoch’ikulu 2 6.7 0.2933

Circulatorydisorders Elephantiasis Birimbo 3 9.1 0.1251Bloodpressure Ndwalayomurhima 3 5.0 0.6316

Digestivedisorders Tonsillitis Bilimi 2 6.7 0.3253Appendicitis Pandisi 1 1.6 10.0000Painfulbloatingoftheabdomen Mukungulo 1 3.2 10.0000Constipation Kurhanya 1 1.6 10.0000Diarrhea Mushole 2 18.2 0.0561Bloodydiarrhea Kunyaomuko 3 11.9 0.1942Hypergastritis Lurholerolukulu 1 5.7 0.6797Hypogastritis Lurholerolurho 1 3.2 10.0000Ulcergastritis Lurholerolwechihulu 2 31.3 0.0040*Hemorrhoids Kukunuka 2 11.9 0.1181Discherniation Omugongo 3 5.9 0.5716Toothaches Ndwalay’aminu 2 5.4 0.4885PainfulBloodydiarrhea Mukunguru 3 4.6 0.6907

Genito-urinarydisorders Adnexitis Mwanamimba 1 4.8 0.7588Gonorrhea Chikagasi 1 3.2 10.0000Cystitis Buganga 2 11.9 0.1061Persistentdysmenorrhea Ndwalag’Omukogw’omwezi 1 1.6 10.0000Frigidity Kumasha 1 1.6 10.0000Sexualdysfunction Kurahashaobuhya 2 38.8 0.0010*Hydrocele Mishiha 3 6.7 0.2132Prostate porositati 1 1.6 10.0000Uterineprolapse Ibanzi 2 37.6 0.0030*Maleinfertility Kugumbakwechilume 1 1.6 10.0000Femaleinfertility Kugumbakwechikazi 3 5.6 0.6176Itchyvaginitis Chilondatumbu 2 10.7 0.1612

Inflammatorydiseases Burns Kuhyan’omuliro 1 6.5 0.4875Nephritis Nfiko 1 1.6 10.0000

./..


Appendix 1 (continued 1). Listofdiseases—Liste des maladies.Classe Disease Vernacular name Group Indicator value (%) p*

Inflammatorydiseases SciaticNerve Ihasha 3 9.1 0.1251

Rheumatism Kugogombaemisi 1 4.1 0.8859Woundsandinjuries Woundsandinjuries Chihuluchikulu 3 15.7 0.0641

Woundsulcer Lukero 1 3.2 10.0000Metabolicdisorders Diabete Chisukari 1 6.5 0.4394Muscledisorders Lowbackpain Omugongo 3 9.1 0.1221

Sprain Kuteguka 1 3.2 10.0000Fracture Buvune 3 92.2 0.0010*

Nervedisorders Headache Irhwekuluma 3 13.4 0.0931Epilepsy Lungungu 1 3.4 0.9630Madness Isirhe 1 9.1 0.6096Migraineheadaches Fumba 2 20.2 0.0340*

Poisoning Poisoning Oboge 1 10.6 0.3423Snakebite Kajokajoka 2 4.5 0.7157

Disordersofpregnancy Dystocia Ukurhagwisa 3 4.8 0.6226Voluntaryterminationofpregnancy Kukulaizimi 3 9.1 0.1221Threatenedabortion Lumomyo 2 28.0 0.0060*Hypogalactia Kukumbwa 1 9.7 0.3564Fontanel Lukunga 3 21.2 0.0130*Fetaldeath Chibolwe 2 6.7 0.2933

Respiratorydisorders Anginas Bigoga 1 3.2 10.0000Asthma Obuhema 1 3.2 10.0000Coryza Kufuneka 1 1.6 10.0000Cough Chikoholo 2 4.5 10.0000Painofchest Kashiha 3 6.7 0.3263Pneumonia Mwijimbwe 1 3.2 10.0000Sinusitis Muzerezi 2 6.7 0.2933

Sensorydisorders Cataracts Nshongo 1 4.8 0.6396Conjunctivitis Ndwalayamasu 1 6.5 0.4384

Skinandsubcutaneousdisorders

Abscess Muhama 1 8.1 0.4124Dermatosis Kuyaga 1 8.1 0.4284Furunculosis Mahurehure 3 6.7 0.3063Cyst Muziha 2 5.4 0.4795Fungus Lubenja 3 8.0 0.1361Panari Mududu 3 6.7 0.3073Psoriasis Pessé 2 5.4 0.4625

Abnormalbloodorgans Anemia Kubulaomuko 2 3.9 10.0000Splenomegaly Lusingu 3 4.9 0.6697TumorBreast Chimokomoko,

Mpanga1 3.2 10.0000

Cancerunidentifiedseat Kafinjo 1 1.6 10.0000Nutritionaldisorders Anorexia Kurhahashakulya 2 6.7 0.3173

Emaciation Njorwe 1 1.6 10.0000./..


Appendix 2. Florallist—Liste floristique.

Family Species Vernacular name Group Indicator value

p* Morpho-logicaltype

Habitat

Alangiaceae Alangium chinense(Lour.)Harms

Mulemera 1 3.3 10.000 tree forest

Apocynaceae Baissea multifloraA.DC. Mpango 1 14.7 0.049* shrub forestApocynaceae Pleiocarpa pycnantha

(K.Schum.)StapfKintangondo 2 3.9 0.672 tree forest

Apocynaceae Tabernaemontana johnstonii (Stapf)Pichon

Muberebere 3 16.6 0.076 tree forest

Araliaceae Polyscias fulva(Hiern)Harms Ntongi 1 2.2 0.988 tree forestAsclepiadaceae Periploca linearifoliaQuart.-

Dill.&A.Rich.Kanondonondo 2 1.8 10.000 vine ruderal

Asteraceae Mikania cordata(Burm.f.)B.L.Rob.

Muhombiamashaka

1 12.5 0.163 herb forest

Asteraceae Ageratum conyzoides(L.)L. Kahyola 2 22.1 0.004* herb fallowAsteraceae Alchornea hirtellaBenth. Lulerhalerha 2 14.3 0.036* shrub forestAsteraceae Anisopappus africanus

(Hook.f.)Oliv.&HiernNyamwasamuza 2 21.4 0.004* herb fallow

Asteraceae Bidens pilosaL. Kashisha 2 23.9 0.012* herb fallowAsteraceae Conyza aegyptiaca (L.)

Dryand.exAitonNyambuba 2 5.7 0.647 herb fallow

Asteraceae Lactuca attenuataStebbins Luvunanga 2 9.3 0.130 herb forestAsteraceae Vernonia amygdalinaDelile Mwibirizi 2 3.6 0.645 tree ruderalAsteraceae Vernonia hochstetteriSch.Bip.

exHochst.Ivumovumo 2 10.1 0.141 shrub forest

Asteraceae Vernonia kirungaeR.E.Fr. Ivumo 2 7.3 0.305 shrub forestAsteraceae Alchornea cordifolia

(Schumach.&Thonn.)Müll.Arg.

Lungusu 3 4.1 0.469 shrub forest

./..

Appendix 1 (continued 2). Listofdiseases—Liste des maladies.Classe Disease Vernacular name Group Indicator value (%) p*

Nutritionaldisorders Malnutrition Obwaki 1 3.2 10.0000Poorlydefinedsyndromes Epistaxis Muledu 1 1.6 10.0000

Vertigo Chizunguzungu 1 3.2 10.0000Culturalsyndromes Kivubo Chivubo 1 3.2 10.0000

Iseke Iseke 1 1.6 10.0000Kunde Kunde 2 6.7 0.2903Curses Mugereko 1 1.6 10.0000Evilspirit Mudorho 1 4.8 0.7618Mpivu Mpivu 1 1.6 10.0000Mulonge Mulonge 1 6.5 0.5075Mukinje Mukinje 1 1.6 10.0000

*:indicatorspeciesofthegroupe(Indvalmethod)—espèce indicatrice du groupe (méthode Indval);meaningofthegroups—signification des groupes:seefigure 5—voir figure 5.


Appendix 2 (continued 1). Florallist—Liste floristique.



Habitat

Asteraceae Dichrocephala integrifolia (L.f.)Kuntze

Chitundambuga 3 12.1 0.2710 herb fallow

Asteraceae Crassocephalum bumbense S.Moore

Chifubula 4 9.9 0.1850 herb forest

Basellaceae Basella albaL. Ndelama 1 13.7 0.0640 herb forestBegoniaceae Begonia meyeri-johannis Engl. Kahulula 2 17.3 0.0200* herb forestBurseraceae Canarium schweinfurtii Engl. Bwaga 1 7.4 0.3280 tree forestCaryophyllaceae Drymaria cordataWilld.ex

Schult.Bwahulo 4 41.0 0.0010* herb ruderal

Chrysobalanaceae Parinari excelsaSabine. Mwinga 2 18.5 0.0160* tree forestClusiaceae Harungana montanaSpirlet Kadwamuko 1 12.4 0.2200 shrub forestClusiaceae Symphonia globuliferaL.f. Muzimba 1 3.3 1.0000 tree forestClusiaceae Lebrunia bushaeiStaner Bushahi 2 7.1 0.1620 tree forestConvolvulaceae Ipomoea involucrataP.Beauv. Kadwamonka 1 10.0 0.1210 herb forestCyatheaceae Cyathea mannianaHook. Bishembegere 1 3.5 0.7420 shrub forestEuphorbiaceae Macaranga kilimandscharica

PaxLushasha 2 4.9 0.3140 tree forest

Euphorbiaceae Neoboutonia macrocalyxPax Chibirabira 2 8.2 0.1990 tree forestEuphorbiaceae Tragia brevipesPax Ishusha 3 35.4 0.0010* shrub ruderalEuphorbiaceae Neoboutonia africanaMüll.

Arg.Kitubutubu 4 5.2 0.5880 tree forest

Fabaceae Piptadeniastrum africanum(Hook.f.)Brenan

Libuyu 1 3.3 10.0000 tree forest

Fabaceae Millettia psilopetala Harms Nshungurhi 2 8.7 0.1300 tree forestFabaceae Newtonia buchananii(Baker)

G.C.C.Gilbert&BoutiqueLukundu 2 1.8 10.0000 tree forest

Fabaceae Albizia gummifera(J.F.Gmel.)C.A.Sm.

Mushebere 3 3.3 0.6690 tree forest

Fabaceae Erythrophleum guineenseG.Don

Chikubwekubwe 3 2.9 0.9130 tree forest

Labiataceae Clerodendrum welwitschiiGürke

Nfubya 2 17.9 0.0060* shrub forest

Lamiaceae Pycnostachys erici-rosenii R.E.Fr.

Mwizunguluka 2 7.2 0.3650 shrub forest

Lauraceae Persea americanaMill. Ivocati 2 9.5 0.2890 tree cultivatedLobeliaceae Lobelia giberroaHemsl. Mwirumbu 3 5.4 0.3910 shrub forestMalvaceae Hibiscus noldeaeBakerf. Mukerashungwe 3 20.2 0.0280* herb forestMeliaceae Carapa grandifloraSprague Bugwerhe 2 26.2 0.0030* tree forestMeliaceae Entandrophragma excelsum

(Dawe&Sprague)SpragueLibuyu 2 17.9 0.0200* tree forest

Moraceae Ficus oreodryadumMildbr. Mulehe 2 8.2 0.2030 tree forestMoraceae Ficus thonningiiBlume Kahura 2 3.6 0.6930 tree forestMoraceae Milicia excelsa(Welw.)

C.C.BergMuvula 2 1.8 10.0000 tree forest

./..


Appendix 2 (continued 2). Florallist—Liste floristique.



Habitat

Moringaceae Moringa oleiferaLam. Muringa 3 5.3 0.4470 tree cultivatedMusaceae Ensete ventricosum(Welw.)

CheesmanChirembo 3 21.2 0.0110* herb forest

Myrsinaceae Embelia schimperiVatke Kashalulabahivi 1 5.5 0.5850 vine forestMyrsinaceae Rapanea melanophloeos(L.)

MezChishorhe 1 3.3 1.0000 tree forest

Myrsinaceae Maesa lanceolata Forssk. Mparhi 4 31.8 0.0020* tree forestMyrtaceae Syzygium guineense(Willd.)

DC.Chikobarhi 2 7.1 0.1470 tree forest

Myrtaceae Syzygium cordatumHochst.exKrauss

Mugorhe 3 27.0 0.0070* tree forest

Olacaceae Strombosia scheffleriEngl. Busika 3 4.1 0.5610 tree forestOleaceae Jasminum abyssinicumHochst.

exDC.Kafufula 2 3.6 0.6590 vine forest

Phyllanthaceae Bridelia micrantha(Hochst.)Baill.

Mujimbu 2 8.1 0.2520 tree forest

Piperaceae Piper capenseL.f. Muborobondo 2 21.9 0.0160* shrub forestPlantaginaceae Plantago palmataHook.f. Chibarama 1 19.2 0.0330* herb ruderalPolygonaceae Rumex bequaertiiDeWild. Muberanaga 1 7.8 0.3050 herb forestRhamnaceae Gouania longispicataEngl. Muvurha 2 8.4 0.2670 vine forestRosaceae Prunus africana(Hook.f.)

KalkmanMuhumbahumba 4 12.7 0.0500 tree forest

Rubiaceae Galiniera coffeoidesDelile Chintindi 2 7.1 0.1460 shrub forestRubiaceae Rubia cordifolia L. Lukerabatuzi 2 7.1 0.1510 herb forestRubiaceae Tricalysia niamniamensis

Schweinf.exHiernNkongo 2 10.7 0.1040 shrub forest

Rubiaceae Coffea kivuensisLebrun Akahwa 3 6.2 0.3710 shrub forestRubiaceae Hallea rubrostipulata

(K.Schum.)J.-F.LeroyMuzibaziba 3 3.5 0.8610 tree forest

Rutaceae Zanthoxylum macrophyllum Nutt.

Kashabumbu 2 9.0 0.2310 tree forest

Rutaceae Zanthoxylum lemairei(DeWild.)P.G.Waterman

Kashabumbu 3 17.8 0.0160* tree forest

Sapotaceae Autranella congolensis(DeWild.)A.Chev.

Mulungu 2 7.1 0.1550 tree forest

Simaroubaceae Kirkia acuminataOliv. Mulumear-hashonwako

3 15.8 0.0220* tree forest

Tiliaceae Triumfetta cordifoliaA.Rich. Chahunga 2 7.1 0.1460 shrub forestUlmaceae Trema orientalis(L.)Blume Mushakushaku 4 37.1 0.0010* tree forestUrticaceae Urera hypselodendron(Hochst.

exA.Rich.)Wedd..Mushebere 1 11.0 0.0950 vine forest

Urticaceae Myrianthus holstii Engl. Bwamba 2 17.9 0.0100* tree forestXanthorrhoeaceae Aloe barbadensisMill. Chigaka 1 28.6 0.0020* herb cultivated*:indicatorspeciesofthegroupe(Indvalmethod)—espèce indicatrice du groupe (méthode Indval);meaningofthegroups—signification des groupes:seefigure 5—voir figure 5.

characterization of traditional healers in the mountain forest … · 2019-09-20 · b a s e...

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