chapter 3 2000 econ bot paper.pdf

CHAPTER 3

The Commercial Market for Medicinal Plants and Plant Parts

___________________________________________________________________

Economic Botany 54(3) pp. 310–327. 2000q 2000 by The New York Botanical Garden Press, Bronx, NY 10458-5126 U.S.A.

UNRAVELING THE COMMERCIAL MARKET FOR MEDICINAL

PLANTS AND PLANT PARTS ON THE WITWATERSRAND,SOUTH AFRICA1

VIVIENNE L. WILLIAMS, KEVIN BALKWILL, AND EDWARD T. F. WITKOWSKI

Williams, Vivienne L., Kevin Balkwill, and Edward T. F. Witkowski (Department of Ani-mal, Plant and Environmental Sciences, University of the Witwatersrand, Private Bag 3, WITS2050, Gauteng, South Africa). UNRAVELING THE COMMERCIAL MARKET FOR MEDICINAL PLANTS

AND PLANT PARTS ON THE WITWATERSRAND, SOUTH AFRICA. Economic Botany 54(3):310–327,2000. To unravel the market for commercial medicinal plants on the Witwatersrand in SouthAfrica, a semiquantitative approach was taken. A stratified random sample of 50 herb-traderswas surveyed, and an inventory of all plants and parts sold was compiled. Research participantswere questioned on the scarcity and popularity of the plants traded, as well as suppliers andorigins. The rarefaction method established that the sample size was adequate. The diversityof the sample was determined using ecological indices of diversity, and found to be compar-atively high. In addition, Spearman rank correlations, chi-squared and Fisher’s exact proba-bility tests were used to assess the probability of certain taxa being used. At least 46% of thetaxa traded showed a higher than expected probability of being utilized, and taxa tended to beharvested from the largest families proximate to the markets. About 511 species are traded inthe region, and there is a low dominance in the use of species. Ethnic and floristic diversityare influential in deciding the trading patterns that have emerged.

DECOUVRIR LE MARCHE DES PLANTES MEDICINALES ET DES PARTIES DE PLANTES DANS LA REGION

DU WITWATERSRAND, EN AFRIQUE DU SUD. Pour decouvrir le marche commercial des plantesmedicinales et des parties de plantes, nous avons utilise une approche semiquantitative. Unechantillon pris au hasard, de 50 commerces base sur une connaissance corporative de cemonde specifique, et un inventaire de toutes les varietes de plantes offertes a la vente dans cesechopes a ete effectuee. Les participants, furent questionnes sur la rarete et la popularite desplantes a l’etalage, ainsi que sur l’origine et les fournisseurs de ces memes plantes. La methodebasee sur la rarefaction indiqua que la taille de l’echantillonage etait adequat. La diversitedes echantillons fut determine en utilisant les indices ecologiques, de diversite et se revela, encomparaison, important. De plus, la correlation lineaire de Spearman, le test x2, et les tests deprobabilite exacte de Fisher furent utilises pout evaluer la probabilite de certaine taxa utilisee.Au moins 46% de la taxa vendue, montre une probabilite superieure a la moyenne d’etreutilisee, et la taxa tend a etre recoltee parmi les familles de plantes situees dans la vicinite deslieux de vente. 511 especes sont a la vente dans la region, et il n’y a pas de dominanceparticuliere sur certaines especes. La presence de plusieurs groupes ethniques et la diversitevegetale influence les habitudes commerciales qui constituent la base de l’etude.

Key Words: ethnobotany; medicinal plants; survey; trade; diversity; biome; harvesting; SouthAfrica.

The trend towards increased commercializa-tion of medicinal plants in South Africa has re-sulted in overharvesting and, in some cases,near-extinction of some valued indigenous plantspecies. Several factors have stimulated the rise,including: a rapidly growing and urbanizingBlack population, an estimated 80% of whom

1 Received 20 January 1999; accepted 24 December1999.

consult traditional healers (Cunningham 1988);the affordability, accessibility, and acceptabilityof traditional medicine over western medicine;and a high rate of unemployment and low levelof formal education, especially in rural areas.Together, the factors have resulted in the com-mercial exploitation of economically valuableplants by commercial gatherers to obtain an in-come (Cunningham 1988). The unemploymentrate is high, in part, because job opportunities in

Chapter 3; Pg. 2

2000] 311WILLIAMS ET AL.: WITWATERSRAND

the formal business sector and in the rural sub-sistence economy have failed to keep pace withthe growing number of new job-seekers (Hunt-ley, Siegfried, and Sunter 1989).

The harvesting of medicinal plants was for-merly the domain of trained traditional medicalpractitioners, renowned for their skills as herb-alists and diviners (Cunningham 1991a). Strictcustomary conservation practices were respect-ed, which regulated plant collection times andquantities. With the advent of urbanization andthe consequent commercialization of traditionalhealth care, however, the demand for medicinalherbs has increased. As a result, harvesting hasbecome the domain of untrained, and often in-different, commercial gatherers with no other in-come sources. Harvesting and the provision ofmedicinal plants to meet the urban demand hasthus become an environmentally destructive ac-tivity.

There is an ecological context within whichpeople interact with plants that goes beyond thequery of ‘‘What is the name of this plant andwhat is it used for?’’ (Peters 1996). Some studiesin South Africa have focused on recording thecustomary knowledge and uses of indigenousplants by various communities (e.g., Hutchings1989, Hutchings and van Staden 1994), whileignoring their economic significance, the extentof commercial harvesting, and the potential im-pact harvesting has on regional species diversity.There are exceptions, for example, Cunningham(1988), Mander (1997), and Mander, Quinn, andMander (1997). A question that should be askedis: ‘‘What are the long-term impacts of the ac-tions of the people who use the local flora?’’(Peters 1996).

In February 1994, an investigation waslaunched to examine the commercial market formedicinal plants in the medicinal markets of theWitwatersrand, South Africa. Included in the ob-jectives of the study was the development ofmethods to quantify the regional herbal medi-cine trade. The herb-traders on the Witwaters-rand have been quantitatively and qualitativelycharacterized (Williams, Balkwill, and Witkows-ki 1997). This paper identifies the species beingtraded in the region, the plant parts harvested,the suppliers of the plants, and the sources ofsupply. In addition, the following questions wereasked: 1) was sampling adequate; 2) what is thediversity of the sample and is species use equi-

table; and 3) do certain taxa have a higher thanexpected probability of being utilized?

REGIONAL SETTING

The Witwatersrand is an extensively urban-ized complex running along an east-west axis ofapproximately 100 3 40 km from Nigel toRandfontein in the province of Gauteng, SouthAfrica (Fig. 1). Urban growth in the area islargely centered around the city of Johannes-burg, which is also at the center of an emergingnorth-south industrial axis (Dauskardt 1994).Traders in traditional medicine in the region canbe differentiated into two sectors, namely formalbusinesses and informal markets. The formalsector is represented by herb-traders, includingtraditional healers, trading from fixed licensedpremises called umuthi shops. At the time of thesurvey in 1994, there were approximately 166shops. The informal sector, is represented bytransient commercial gatherers, hawkers, andtraditional healers who sell medicinal plantsfrom the pavements and open markets. There areestimated to be more than 100 gatherers, 75%of which are women from the rural areas ofsouthern Africa.

METHODS

SELECTING RESEARCH PARTICIPANTS

The investigation focused on surveying theformal sector. Therefore research participantswere chosen from the 166 umuthi shops. Con-centrating on the formal sector permitted re-peated visits to the research participants. Obser-vations could be subsequently cross-checked ifnecessary—a difficult task with the transientcommercial gatherers. In order for the samplenot to be biased in favor of any one sociogeo-graphic group, a stratified random sample of 50research participants was selected. The partici-pants were proportionately representative of thegeographical distribution, ethnicity, and genderof the herb-traders on the Witwatersrand at thetime of the survey (Williams, Balkwill, and Wit-kowski 1997).

Prior to the commencement of the investiga-tion and the final selection of the research par-ticipants, it was important to establish a positionof credibility and trust with the herb-traders. Theobjectives, methods, and foreseeable implica-tions and consequences of the research were ex-plained to potential participants. The proposedsurvey did not anticipate compromising the in-

Chapter 3; Pg. 3

312 [VOL. 54ECONOMIC BOTANY

Fig. 1. Location of the study area, the Witwatersrand, in the province of Gauteng, South Africa.

tellectual property rights of the participants,hence no arrangement for equitable compensa-tion for information was negotiated. After thecompletion of the survey, however, gifts of in-formation, plants, and elephant dung (requestedby the herb-traders) were given in gratitude forthe participants’ cooperation.

SEMIQUANTITATIVE SURVEY

Between July and December 1994, a semi-quantitative survey of 50 umuthi shops was con-ducted. A complete checklist of all plants andtheir parts was compiled for each shop. Plantnames were recorded in the vernacular. There-after, the research participants were asked tonominate plants perceived as being popular andscarce. Questions relating to the suppliers of theplants (e.g., commercial gatherer or wholesaler)and their sources, i.e., the region from whichthey were harvested (if known), were also asked.Plant use was not directly relevant to the study,hence no participant was asked for the use ofany plant on the checklist—an issue that was

brought to their attention before the study com-menced.

SYNTHESIS

Species Identification

The scientific names for the plants recordedin each umuthi shop were determined using theextensive and reliable literature that exists forsouthern African plant names in Latin and thevernacular. A set of voucher specimens was pur-chased from one of the umuthi shops, and ispresently being incorporated into the traditionalmedicine collection at the Adler Museum of theHistory of Medicine, University of the Witwa-tersrand in Johannesburg. The external appear-ance and features of the plant parts sold underthe same name in different shops were consis-tent throughout the survey, and matched thevouchers in the reference collection at the AdlerMuseum, except where otherwise indicated.Thus, the scientific names allocated to the plantsare, for the most part, reliable. The method of

Chapter 3; Pg. 4


species identification is detailed in Williams,Balkwill, and Witkowski (in press).

DatabaseFollowing species identification, the data were

entered into a relational database designed in theprogram DATAEASE by modifying the herbar-ium management system of the C. E. Moss Her-barium. The botanical names of most species en-countered in the study had been entered previ-ously in that system. The data capture formatwas modified specifically for the entry of thesurvey records, and the data were entered underthe following fields for each species recorded inan umuthi shop: a) genus and species number(Genspec No., following Arnold and de Wet(1993)); b) genus and species; c) commonnames; d) language of the common name; e)traders’ opinion of scarcity; f) supplier code; g)source code; h) plant part; i) plant use (if vol-unteered by the herb-trader); j) additional infor-mation (e.g., price, description of the plant, orplant popularity); and k) trader information andcode. Herb-traders were given codes denotingthe region and order in which they were sur-veyed, for instance JB30 for Johannesburg Shop30. The number of records entered for the fiftyherb-traders totaled 6285—an average of 126species per umuthi shop.

Following data capture, a complete list of allplant families, genera, and species found to betraded could be extracted from the database. Inaddition, the number of records of each taxoncould be established to determine the most fre-quently or rarely recorded species. The numberof records or citations per taxon were used toquantitatively establish the adequacy of the sam-ple size and diversity of the sample using eco-logical indices of species diversity.

Adequacy of the Sample SizeIn ecological situations where sample sizes

(n) differ, rarefaction may be used to allow com-parisons of species numbers between commu-nities (Ludwig and Reynolds 1988). Rarefying asample computes the expected number of spe-cies [E(Sn)] at different sample sizes, i.e., E(Sn)at n 5 50, 100, or 1000, etc. Rarefaction helpsto determine how many species [E(Sn)] are like-ly to have been recorded (Krebs 1989) if thesample had consisted of n individuals (citationsof species). Therefore, rarefaction may be usedto evaluate sampling effort (Begossi 1996).

When more individuals are added to the sampleand E(Sn) does not increase, then sampling effortis said to be sufficient (Begossi 1996).

Sampling effort can be shown graphically ona rarefaction curve. The expected number ofspecies [E(Sn)] is plotted on the y-axis, and thenumber of citations per species (n) on the x-axis.A leveling off of the curve indicates that in-creasingly fewer new species are expected to beadded to the sample as more umuthi shops aresampled. The BASIC program RARE-FRAC.BAS (Ludwig and Reynolds 1988), wasused to compute E(Sn) at different sample sizes.

Assessing Species DiversityThree questions were asked: 1) what is the

species richness of the sample; 2) what is thediversity of the species sold in Witwatersrandumuthi shops; and 3) is there dominance in theuse of a few species? Diversity measures takeinto account two factors: taxon richness (i.e., thetotal number of taxa, S) and evenness (or ‘‘eq-uitability,’’ i.e., how equally abundant the taxaare in the sample). An index of species diversity(also called an index of heterogeneity) incorpo-rates both richness and evenness in a single val-ue and calculates the probability that two speciesdrawn at random from a sample belong to thesame species. If the probability is high, then thediversity of the sample is low. The seven eco-logical measures of species diversity used hereare: 1) species richness (S or N0); 2) Simpson’sindex of heterogeneity (l); 3) the Shannon-Wiener index (Hprime); 4) Hill’s diversitynumbers N1, N2, and N}; and 5) evennessmeasure Jprime. The Shannon-Wiener index isthe more widely known diversity measure, andis based on information theory. Hill’s diversitynumbers give a measure of the ‘‘effective num-ber of species present in a sample’’ (Ludwigand Reynolds 1988). N0 is the number of allspecies in the sample, N1 is the number ofabundant species in the sample, N2 is the num-ber of very abundant species, and N} is thenumber of most abundant species. The indicesof richness, heterogeneity, and evenness werecomputed using the BASIC program SPDIV-ERS.BAS (Ludwig and Reynolds 1988).

Assessing the Utilization of SpeciesExploring causation of species utilization rais-

es the following questions: 1) are taxa concen-trated in particular families and biomes, and 2)

Chapter 3; Pg. 5


Fig. 2. Rarefaction curve for the sample of Wit-watersrand umuthi shops, based on number of citationsper species. The curve shows the expected number ofspecies [E(Sn)] as a function of n 5 number of cita-tions/records of all species traded in 50 umuthi shops.

do certain taxa have a higher than expectedprobability of being used medicinally? Questionone was answered using Spearman’s rank cor-relation coefficients (rs) (Siegal 1956). The cor-relations tested the null hypothesis that the ranksof families from the survey were not statisticallydifferent from the ranks of corresponding fami-lies in the southern African flora and biomes.The families found to be traded medicinallywere correlated with: 1) 119 corresponding fam-ilies of southern African angiosperms, gymno-sperms, and pteridophytes, ranked by number ofspecies and infraspecific taxa (Gibbs Russell1985) (Appendix); and 2) corresponding fami-lies represented by more than 1% of the totalnumber of taxa in any one of the six southernAfrican biomes (Gibbs Russell 1987). The bi-omes analyzed were: Grassland, Savanna, De-sert, Nama-Karoo, Succulent Karoo, and Fynbos(Rutherford and Westfall 1986). The flora of theForest biome and a new biome described as ‘‘be-fore Thicket’’ in Low and Rebelo (1996) werenot included in the floristic analysis because datawere not available in Gibbs Russell (1987).

Question two was answered using Chi-squared (x2) 2 3 2 contingency tables and Fish-er’s exact probability test. The following nullhypothesis was tested: the frequency of speciesused medicinally per family would not be statis-tically different from the frequency of occur-rence of species in corresponding families in thesouthern African flora—i.e., that species use isproportional to what is available. The alternativehypothesis was that most families would showa significant difference in the observed frequen-cy. Therefore species use would not be propor-tional to availability, and could be due insteadto the size and the geographical availability offamilies in the southern African flora and bi-omes, and/or the presence of desirable pharma-cologically active chemicals in different plantfamilies. Chi-square tests were performed on allthe families. Where a minimum expected cellfrequency of ,5 was obtained, Fisher’s exactprobability test was executed instead.

RESULTS

ADEQUACY OF SAMPLE SIZE

The rarefaction curve for the sample of 511species and 6285 citations (Fig. 2) indicates thatsampling effort was sufficient. This is evidencedby the leveling off of the rarefaction curve to a

rate of one new species for every 100 speciesrecorded, or, approximately 1.3 new species forevery additional umuthi shop surveyed. Onewould not expect the curve to level off com-pletely, as this would infer that either all plantsconsidered to be medicinally useful have beensampled, or that every taxon sold on the Wit-watersrand had been sampled.

SPECIES PRESENT IN THE MARKET

Five hundred and eleven species, representing328 genera and 119 families (Appendix), wereidentified and recorded for sale in 50 Witwa-tersrand umuthi shops. A further 70 specimensfrom the sample remain unidentified. The largestfamilies in trade, by number of genera, are: Fa-baceae (28), Liliaceae sensu lato (23), Compos-itae (20), Euphorbiaceae (14), and Rubiaceae(13). Five families contain about 33% of thespecies and infraspecific taxa traded, namely:Liliaceae s.l. (57), Fabaceae (38), Compositae(34), Euphorbiaceae (28) and Amaryllidaceae(15). A study of the taxa traded commercially inSouth Africa reported similar trends (Mander,Quinn, and Mander 1997). The number of spe-cies in the 50 shops surveyed is shown in Fig.3. The average number of species per shop is126 6 65.9 (SD).

Species Commonly TradedTable 1 lists the most frequently occurring

species in the umuthi shops surveyed. No spe-cies was present in more than 42 of the 50shops. Drimia spp. (bulbs) had the highest re-corded frequency of occurrence (82%). Of the

Chapter 3; Pg. 6


Fig. 3. The number of species identified in the 50umuthi shops surveyed, according to the race-group ofthe herb-trader. The mean number of species per shopis 126 6 65.9 (SD). The minimum and maximumnumber of species recorded in a shop was 10 and 294respectively.

511 species inventoried, 78 (15.3%) were re-corded once in a shop (Fig. 4), and 61 species(11.9%) were recorded twice. By contrast, 36species (7.0%) occurred in more than 33 of theshops surveyed.

Popular SpeciesHerb-traders derive a regular income from

those species perceived to be ‘‘popular’’—i.e.,in demand, frequently purchased by consumers,and regularly restocked by the traders. Table 2lists the species most commonly nominated aspopular and in demand. These plants have beendescribed as the so called bread-and-butter com-modities of the herb trade.

Scarce SpeciesTable 3 lists species most commonly nomi-

nated by #10% of the research participants as‘‘scarce,’’ i.e., becoming increasingly unavail-able and usually expensive. Drimia elata is pres-ently considered only seasonally scarce, whereasBowiea volubilis is a vulnerable species that hasbecome locally extinct in some regions ofKwaZulu-Natal (McKean 1993). Of the trees,Ocotea bullata is considered the most scarce andis threatened not only by excessive ring-barkingand the high price it demands in the umuthitrade, but also by forest destruction and the fur-niture industry (McKean 1993). The populationsof Warburgia salutaris are few and criticallysmall. Siphonochilus aethiopicus was unani-

mously viewed as the scarcest plant in trade—an opinion verified by the known distribution ofthe species in South Africa. The species is ex-tinct in the wild in KwaZulu-Natal, exceptwhere it appears to be cultivated around home-steads (Mander, Quinn, and Mander 1995).

TRADE IN PLANT PARTS

The plant parts most traded on the Witwaters-rand are roots (38.4%), followed by bark(25.6%), leaves/stems (13.5%), and bulbs(10.8%) (Table 4). Combined, the removal ofwhole plants, roots, and bulbs is 57.3%, com-pared to 17.1% for aerial parts other than bark.Therefore, the harvesting of almost two-thirds ofthe species for the Witwatersrand medicinalplant trade will almost always result in plantmortality. These results are similar to those re-ported by Cunningham (1988) for a survey ofthe trade in medicinal plants in Durban.

SUPPLIERS

The major suppliers of plants to the Witwa-tersrand are the commercial gatherers in the in-formal, open air markets (Table 5). Combined,the Faraday Street market in Johannesburg andthe markets of Durban in KwaZulu-Natal ac-count for 40.2% of the trade. Deliveries by gath-erers directly to umuthi shops account for 36.1%of the supply. The importance of gatherers assuppliers depends on the distance of the umuthishop to the nearest open market—the closer tothe open-markets the herb-traders are, the lessthey rely on door-to-door deliveries by gather-ers.

SOURCES OF SUPPLY

Species traded on the Witwatersrand aremainly harvested from the province of Kwa-Zulu-Natal (42.1%) (Table 6) followed by Gau-teng (15.2%), the Northern Province (7.2%),Swaziland (6.3%), and Mpumalanga (3.2%).The percentages were calculated as the meanpercentage of the species kept by herb-traderssaid to be harvested from the various regions.

Some regions for which percentage contribu-tion to the source profile is unexpectedly low(e.g., Eastern Cape), may be accounted for inthe 21.1% of unknown sources. In addition,some participants were uncertain of the origin ofthe plants purchased at the Faraday Street andDurban markets, but cited KwaZulu-Natal as aprobable source. A re-analysis of the data from

Chapter 3; Pg. 7


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Chapter 3; Pg. 8


Fig. 4. Relative frequencies of the 511 species re-corded for sale in 50 umuthi shops on the Witwaters-rand. There were 78 species recorded in only one umu-thi shop, 61 species recorded in two shops, 25 speciesrecorded in three shops, etc.

TABLE 2. SPECIES MOST COMMONLY NOMINATED AS ‘POPULAR’ AND IN DEMAND.

Species Common name Plant part

% Traderopinion ofpopularity

Eucomis autumnalis (Mill.) Chitt.Helichrysum spp.a

Drimia spp.b

Scilla natalensis Planch.Dianthus mooiensis F.N. Williamsc

uMathungaiMphephoSkanamainGuduzaTjanibeswe

bulbleaves/stembulbbulbwhole plant

1614141412

Warburgia salutaris (Bertol. f.) Choiv.Peucedanum magalismontanum Sondd

Elaeodendron transvaalensis (Burtt Davy) R.H. Archere

Gunnera perpensa L.Rapanea melanophloeos (L.) Mez.

isiBhahaiBhekaiNgwavumauGophouMaphipha

barkwhole plantbarkrootbark

88666

a Helichrysum cymosum (L.) D. Don, H. decorum DC., H. epaposum Bolus, H. gymnocomum DC., H. natalitium DC., H. nudifolium (L.) Less andH. odoratissimum (L.) Sweet.

b Generally Drimia elata Jacq. or D. robusta Bak.; sometimes Urginea altissima (L.f.) Bak., U. delagoensis Bak., U. macrocentra Bak. and U.sanguinea Schinz.

c In KwaZulu/Natal the species Dianthus zeyheri Sond. is used and is called iNingizimu.d In KwaZulu/Natal the species Scabiosa columbaria L. is used as iBheka.e Formerly Cassine transvaalensis (Archer and van Wyk 1998).

the Durban and Faraday Street markets revealedthat an additional 15.2% of plants could havebeen harvested from areas other than KwaZulu-Natal, as originally cited. Therefore the originsof 36.3% of the plants are potentially unknown.

Apart from the sale of nonindigenous speciesgrown and harvested in southern Africa, e.g.,Cinnamomum camphora, species imported fromIndia are present in the market. Asian herb-trad-ers usually import the plants as substitutes forscarce indigenous species or as new medicines.The plants are redistributed through wholesalersand other herb-traders until they reach the Wit-watersrand markets. There are approximately 11

imported species on the market at present, in-cluding: jikantambo (a seed capsule), mlomo-mnandi and dumaphanzi (both roots). The sci-entific names for these species are not known.

SPECIES RICHNESS, HETEROGENEITY, AND

EVENNESS

The richness, heterogeneity, and evenness ofspecies sold on the Witwatersrand are compara-tively high (Table 7). The Shannon index (Jprime5 0.932) suggests that there is a relatively highevenness in the distribution of species in thesample, i.e., that there is a low dominance.Simpson’s index (l) for the Witwatersrand con-firmed that the diversity of the sample was high.The probability of two records drawn at randombelonging to the same species is low (l 5 3.443 1023). Hill’s diversity numbers for the effec-tive number of species in the sample corroborateJprime. Of the 511 species inventoried, the num-ber of abundant species (N1) in the sample is335; the number of very abundant species (N2)is 291.

UTILIZATION OF SPECIES

The rank correlation between the plant fami-lies used medicinally on the Witwatersrand andthe southern African flora is significant (P ,0.001; rs 5 0.652) (Table 8). The results suggestthat taxa harvested and used medicinally are as-sociated with the largest southern African floralfamilies. Rank correlations with families in six

Chapter 3; Pg. 9


TABLE 3. SPECIES NOMINATED AS SCARCE BY 10% OR MORE OF THE RESEARCH PARTICIPANTS.

Species Common name Plant part

% Traderopinion of

scarcity

Siphonochilus aethiopicus (Schweinf.) B.L. BurttEucomis autumnalis (Mill.) Chitt.Bowiea volubilis Harv. ex Hook. f.Drimia spp.a

Ocotea bullata (Burch.) E. Mey.

isiPhepethouMathungaiGibisileSkanamauNukani

rootbulbbulbbulbbark

6636262424

Synaptolepis kirkii Oliv.Brackenridgea zanguebarica Oliv.Stangeria eriopus (Kuntze) Baill.Cinnamomum camphora (L.) J. Preslb

unconfirmed speciesc

uVuma, whitemutavhasindiimFingouRoselinabangalala

rootroottuberbarkroot

2220181414

Warburgia salutaris (Bertol. f.) Choiv.unconfirmed speciesScilla natalensis Planch.Alepidea amatymbica Eckl. & Zeyh.Pappea capensis Eckl. & Zeyh.

isiBhahauSilepheinGuduzaiKhatazouVuma, red

barkrootbulbrootroot

1212121010

a Generally Drimia elata Jacq. or D. robusta Bak.; sometimes Urginea altissima (L.f.) Bak., U. delagoensis Bak., U. macrocentra Bak. and U.sanguinea Schinz.

b Exotic.c Identification uncertain, but one of several species is used, including: Corchorus asplenifolius Burch., Eriosema salignum E. Mey., Gymnosporia

buxifolia (L.) Szyszyl., Hippocratea longipetiolata Oliv., Rhynchosia sp., Salacia krausii (Harv.) Harv. (M. Mander, pers. com.) and Tragia meyeriana.f Including Hypoxis colchicifolia Bak.

TABLE 5. SUPPLIERS OF MEDICINAL PLANTS TO

THE WITWATERSRAND HERB-TRADERS.

Suppliers% Supplying

the trade*

Commercial gatherers deliveringdirectly to shops

Faraday Street market gatherersHerb-traders gathering own plantsDurban market gatherersWholesalersFarmersMai Mai BazaarUnknown

36.131.214.5

9.04.52.90.21.6

* Calculated from the total number of citations (n 5 6285).

TABLE 4. THE NUMBER AND PERCENTAGE OF

PLANTS FOR WHICH PARTICULAR PLANT PARTS ARE

TRADED.

Plant partNumberof plants

Percentageof plants

Roots (incl. ligno-tubers)BarkLeaves and stemsBulbsWhole plantFruitSeedsFlowers

227148

78614312

63

39.325.613.510.6

7.52.11.00.5

southern African biomes indicate that taxa usedmedicinally on the Witwatersrand have more incommon with the Savanna (P 5 0.048, rs 50.45) (Table 8) than the other biomes. The re-sults suggest a tendency for species to be har-vested from the biomes proximate to the markets(Fig. 6) and from taxa common in biomes in theregions from which the commercial gatherersharvest (Table 6) and with which they are fa-miliar.

Seventy-two (61%) of the plant families in-vestigated exhibited significant differences in theobserved proportion of species used per family

when compared to the southern African flora.Species utilization, therefore, is not proportionalto availability for these families. Only 46 fami-lies (39%) showed no significant differences intheir observed frequencies. Species utilization,therefore, is hypothesized to be proportional totheir availability. The families can be subdividedinto four groups depending on the statistical sig-nificance of the x2 and Fisher’s exact probabilitytests (Fig. 5, Tables 9, 10). The rank of the fam-ilies in the proximate biomes of the Savanna andGrassland are included in the comparison be-

Chapter 3; Pg. 10


TABLE 6. REGIONAL SOURCES OF PLANTS HAR-VESTED FOR THE TRADE, BASED ON THE MEAN PER-CENTAGE OF SPECIES HARVESTED PER REGION PER

HERB-TRADER.

Province or country Percentage

KwaZulu/NatalGautengNorthern ProvinceSwazilandMpumalanga

42.115.2

7.26.33.2

North WestLesothoFree StateEastern CapeIndia

2.00.80.70.60.4

BotswanaWestern CapeNorthern CapeMozambiqueUnknown

0.30.050.030.02

21.1

TABLE 8. RESULTS OF THE SPEARMAN RANK COR-RELATION (rs) BETWEEN: 1) 119 FAMILIES USED ME-DICINALLY AND CORRESPONDING FAMILIES OF

SOUTHERN AFRICAN FLORA; AND 2) FAMILIES OF

MEDICINAL FLORA AND FAMILIES THAT REPRESENT

MORE THAN 1% OF THE TOTAL NUMBER OF TAXA

IN A PARTICULAR BIOME.

Level ofcorrelation

Correlationcoefficient (rs) P n

Southern AfricaSavannaGrasslandSucculent KarooFynbosNama-KarooDesert

0.6520.4470.3730.3590.3490.3170.085

,0.0010.0480.1040.1390.1190.1210.697

119202018212222

TABLE 7. COMPARISONS OF SPECIES RICHNESS, HETEROGENEITY AND EVENNESS FOR THE WITWATERS-RAND, AND SELECTED STUDIES1

Index/measure

Witwatersrandn 5 50 herb-traders

6285 citations

Tongan 5 50 informants

2037 citations

Mexicon 5 106 informants

2727 citations

Perun 5 29 informants

1383 citations

Species Richness# Species (S or N)

Indices of HeterogeneityShannon-Wiener (H9)2

Evenness IndexShannon (J9)

511

5.81

0.93

105

4.49

0.97

335

5.16

0.89

472

5.95

0.97

1 Source: Begossi (1996).2 Loge.

cause they can partially explain under- and over-utilization of certain taxa.

Group I families (Table 9) showed no signif-icant differences in the observed frequency ofoccurrence of species per family. Therefore, thenumber of species used is proportional to thenumber of species available. Most of the fami-lies, especially the Fabaceae, showed similarlyhigh rankings in the sample and the Savanna andGrassland biomes. Group II families (Table 9)exhibited significant differences in their ob-served frequencies, however the proportion ofspecies utilized per family was either higher thanexpected (e.g., Euphorbiaceae and Liliaceae s.l.)or lower than expected (e.g., Poaceae and Me-sembryanthemaceae). The rank of most of the

families in Savanna and Grassland was relative-ly high, except for Mesembryanthemaceae,which is represented by few species in the Sa-vanna biome (Gibbs Russell 1987).

Group III families (Table 10) demonstrate sig-nificant differences in their observed frequenciesand there are proportionately more species uti-lized per family than expected. In addition, thefamilies are either not ranked in the Savanna andGrassland (i.e., the families are represented byless than 1% of the total number of taxa in thebiome) or, they are ranked very low, e.g., Ana-cardiaceae. Group IV families (Table 10) exhibitsignificant differences in their observed frequen-cies of occurrence and the number of speciesused are proportional to their availability. Thefamilies are either not ranked or they are absentfrom the Savanna and Grassland.

Chapter 3; Pg. 11


Fig. 5. The 119 families used medicinally on theWitwatersrand can be divided into 4 groups, dependingon whether there is a statistically significant under- orover-utilisation or not, and on the statistical test used.H 5 proportionately more species used per family; L5 proportionately fewer species used per family; N.D.5 not determined.

TABLE 9. COMPARISON1 OF THE OBSERVED FREQUENCIES OF SPECIES IN SELECTED FAMILIES OF THE SUR-VEY DATA WITH SOUTHERN AFRICAN FLORA—GROUPS I AND II. THE RANK OF THE FAMILIES IN THE

SAVANNA, GRASSLAND AND SAMPLE ARE INCLUDED IN THE COMPARISON.

Family x2 P

No. of species in family

Survey(n 5

4952 spp.)

S. Africa(n 5

22,604 spp.)

Family rank

Savanna3 Grassland4 Survey5

GROUP IFabaceaeLamiaceaeOrchidaceaeRutaceae

0.0190.002

,0.0010.005

NSNSNSNS

385

106

1802257480306

21114NR

398

NR

214

913

GROUP IIAsclepiadaceaeCampanulaceaeCompositaeEuphorbiaceaeIridaceae

3.1673.3105.875

19.8818.397

* L* L* L*** H*** L

111

3428

8

892273

2417526

1024

9NR

38

17

7NR

11210

818

34

11Liliaceae sensu latoMesembryanthemaceaePoaceaeProteaceaeRubiaceaeScrophulariaceae

33.83451.371

9.7032.947

12.2876.315

*** H*** L** L* L*** H* L

57363

143

11422684

955392236568

5NR

1NR

410

413

2NR11

6

1161316

716

1 The x2 test was applicable to all the families listed in the table because expected cell frequencies were .5.2 5 Total no. spp. was 511, but the angiosperms were analysed separately from the gymnosperms and pteridophytes (total no. of species 5 16).3 Highest rank given for a family 5 21.4 Highest rank given for a family 5 23.5 Highest rank given for a family 5 18.x2 5 chi-square, NS 5 not significant, * 5 P , 0.05, ** 5 P , 0.01, *** 5 P , 0.001, NR 5 no rank available for the family, H 5 proportionately

more species used per family than expected, L 5 proportionately fewer species used per family than expected.

DISCUSSION

ADEQUACY OF SAMPLING

The sampling strategy chosen for the surveyand the stratified random sample of 50 herb-traders selected, constituted an adequate andrepresentative sample of the herb-traders on theWitwatersrand at the time of the survey. The re-sults obtained from the rarefaction method in-dicate that the results of the survey are not anartifact of a small and inadequate sample size orunrepresentative research participants.

The inventory interview process was appro-priate for establishing the suppliers of the plantsin stock and the sources of supply. However, itwas not entirely suitable for eliciting an ade-quate response from participants on the per-ceived scarcity and popularity of the plants trad-ed. For the most part, the participants’ opinionswere based on plants in the shop during the in-terview. Therefore, potentially scarce speciesthat were not in stock were overlooked. Thus theresults in Tables 2 and 3 underestimate the per-

Chapter 3; Pg. 12


TABLE 10. SELECTED1 COMPARISON OF FREQUENCIES OF SPECIES IN FAMILIES OF THE SURVEY DATA AND

SOUTHERN AFRICAN FLORA—GROUP III FAMILIES. THE RANK OF THE FAMILIES IN THE SAVANNA, GRASS-LAND AND SAMPLE ARE INCLUDED IN THE COMPARISON.

FamilyFishers exactprobability

No. of species in family

Survey(n 5 495 spp.2)

S. Africa(n 5 22,604 spp.)

Family rank

Savanna3 Grassland4 Survey5

GROUP IIIAmaryllidaceaeAnacardiaceaeApiaceaeApocynaceaeCapparaceae

***H***H***H***H***H

155995

205120221

4163

NR20NRNRNR

162018NRNR

514101014

CarophyllaceaeCelastraceaeCombretaceaeEbenaceaeFlacourtiaceaeLauraceaeLoganiaceae

***H***H***H***H***H***H***H

613

77656

66594951261324

NRNRNRNRNRNRNR

NRNRNRNRNRNRNR

137

1212131413

MeliaceaePolygalaceaeRhamnaceaeRutaceaeSapotaceaeSolanaceaeThymelaeaceae

***H***H***H***H***H***H

**H

5956675

17210203306

1498

199

NRNRNRNRNRNRNR

NRNRNRNRNR22NR

14101413131214

1 The x2 test was not applicable to the families listed in this table because expected cell frequencies were ,5, therefore Fishers exact probabilitytest was used. Only families with .5 spp. were included in the table.

2 5 Total no. spp. was 495, but the angiosperms were analysed separately from the gymnosperms and pteridophytes (total no. of species 5 16).3 Highest rank given for a family 5 21.4 Highest rank given for a family 5 23.5 Highest rank given for a family 5 18.NR 5 no rank available for the family, ** 5 P , 0.01, *** 5 P , 0.001, H 5 proportionately more species used per family than expected.

centage of traders that would regard species asbeing scarce or popular. On average, each traderonly mentioned five scarce or popular speciesand because there is a large number of speciesin trade, it is a good indication of potential pop-ularity even if only 16% of the herb-tradersnominated a particular species as being popular.Ideally, a checklist of all plants cited as scarceand popular should be returned to all partici-pants to more decisively establish the trends intrader opinion.

SPECIES PRESENT IN THE MARKET

A starting point for unraveling and under-standing the commercial market for medicinalplants on the Witwatersrand is knowing whatspecies are traded commercially. Many morespecies are used than have been identified in thisstudy. However, knowing what taxa are sold, theextent to which they are traded, and the per-ceived scarcity and popularity of these plants are

starting points for conservation action and eval-uating potentially threatened species. In addi-tion, the number of species traded can be an in-dicator of the size of the regional market and thediversity of the supply and demand. On the Wit-watersrand, the diversity of demand is largely aresult of the ethnic diversity of the traditionalhealers, consumers, and commercial gatherers.

In addition to reflecting the ethnic diversity ofthe consumers near a market, the demand, pop-ularity, and presence of species can reflect re-gional differences in the health needs of usersand the distribution of the plants. Historical eth-nic differences in utilization are evident on theWitwatersrand. Brackenridgea zanguebaricabark, for example, is better known to the Vendapeople of the Northern Province than to Zulusfrom KwaZulu-Natal (KZN). Dianthus mooien-sis, widespread in the Gauteng grasslands andpopular in the Witwatersrand markets, is largely

Chapter 3; Pg. 13


unknown in the KZN markets. A related species,Dianthus zeyheri, is used instead.

The number of species traded can reflect re-gional market variations. Cunningham’s (1988)survey, for example, indicated that more than400 species are sold commercially in the urbanmarkets of KZN. Hutchings (1996), however,identified 1032 species used by Zulus in KZN.Therefore, not all species used have commercialvalue. A survey by Mander, Quinn, and Mander(1997) indicated that about 550 species are like-ly to be traded in South Africa—a further 200species are infrequently traded, if at all. On theWitwatersrand, approximately 78 of the 511 spe-cies identified are likely to be commercially lessimportant because they were recorded in onlyone umuthi shop, and the national commercialtrade is unlikely to be extensive for these spe-cies. Speculative harvesting by commercialgatherers may be a reason for their appearancein the market.

Despite the response of research participantsto the perceived scarcity and popularity of theplants in trade, species in Tables 2 and 3 can beseen as ‘‘indicator’’ species. The knowledge ofresource users provides valuable insight into thescarcity of medicinal plants (Cunningham 1988).This qualitative knowledge has been gainedfrom years of harvesting, buying, and sellingplants, and can be tested against current knowl-edge of population size and rarity (Cunningham1988). There is a realistic concern that plants inTable 3 are indicators of species that are cur-rently scarce and threatened (e.g., Warburgiasalutaris), or will become scarce and threatenedin the future (e.g., Helichrysum spp.). Continuedremoval of large quantities of these plants tosupply the herb-trader’s demands might not besustainable.

TRADE IN PLANT PARTS

There is a clear relationship between the plantpart being harvested, the impact on the plant,and the degree of disturbance to the population(Cunningham 1988). The removal of wholeplants, bulbs, roots, and bark has a more im-mediate and damaging effect than the harvestingof leaves and fruit (Cunningham 1988). Har-vesting roots or whole plants usually results inplant mortality. If the entire root is removed be-fore the plant has gone to seed, it effectivelyends the possibility of future growth and regen-eration of that individual (Sheldon, Balick, and

Laird 1997). The damage caused by partial re-moval of the roots drastically reduces water up-take and increases the susceptibility to fungaldiseases, which can lead to mortality. Bark col-lection is not always detrimental to trees, butring-barking potentially inhibits long-termgrowth and/or reproductive fitness. Dependingon the resilience of a species to persistent andextensive bark-removal, mortality is possible.The harvesting of aerial parts does not alwaysresult in mortality because leaves and fruit areconsidered renewable (Sheldon, Balick, andLaird 1997). In general, harvesting may causemortality, inhibit growth, and extend the timetaken to reach critical life stages, or have nodiscernible adverse consequences. Plant produc-tivity and sustainable utilization are contingenton the severity of harvesting practices.

SUPPLIERS AND SOURCES

The demand for traditional medicines in urbanareas has led to the development of a substantialnetwork of rural commercial gatherers, herb-traders, traditional healers, and consumers.Plants harvested from wild populations in ruraland urban areas are transported nationally andfrom abroad into the city for resale and con-sumption. Prior to the establishment of the Far-aday Street market circa 1992, commercial gath-erers sold plants directly to umuthi shops. Far-aday subsequently expanded from about 10 to1001 gatherers and this has significantlychanged the supplier profile. Most noticeablehas been the decline in the number of gatherersdelivering directly to umuthi shops and a cor-responding increase in the number of tradershaving to travel to the markets. One result hasbeen to increase the herb-traders’ costs.

A small percentage of research participants,mostly traditional healers, harvest some of theplants they sell. What they don’t gather them-selves, they purchase from the commercial gath-erers. A few Asian traders surveyed regularlydrove to the traditional medicine markets inDurban in KZN (about 570 kilometers away) tobuy plants. They thought Durban markets had abetter range and larger volume of plants avail-able and were less dangerous to visit.

The cultural diversity of the Witwatersrand’sconsumers, traditional healers, commercial gath-erers, and traders is partly responsible for thelocalities that plants are harvested from. Peopleliving in the metropolis have ethnic ties to cer-

Chapter 3; Pg. 14


Fig. 6. Distribution of southern African biomes. Adapted from Rutherford and Westfall (1994), Low andRebelo (1997). Study area marked with an arrow (see Fig. 6.).

tain provinces in South Africa, e.g., Zulus toKZN. Therefore, the demand created by ethnicdiversity stimulates commercial harvesting fromlocalities with medicinal plants known to the re-source user. Despite the prevalence of other eth-nic groups in the Witwatersrand (e.g., Sotho etal.), Zulu traditional medicines harvested inKZN predominate in the market.

SPECIES DIVERSITY

The large floristic diversity of plants tradedcommercially on the Witwatersrand is probablydue to 1) the richness and diversity of the south-ern African flora; 2) the regional ethnic diver-sity; and 3) the wide geographical area fromwhich the plants are harvested (Table 9). Thehigh equitability, or low dominance, in the useof species may be ascribed to: 1) the high rich-ness of the taxa traded and 2) the number ofspecies used medicinally, compared to the num-ber with commercial value. In KZN, about 40%of the taxa used are traded commercially. A mar-ket has, therefore, developed over time for asuite of plants with commercial value. On theWitwatersrand, an estimated 335 species (N1–66% of the sample) constitute a large core groupof plants that are traded regularly.

A study of the diversity of species utilization

in South America and Asia (Begossi 1996),showed that utilization diversity in Tonga, forexample, was low—despite an adequate samplesize (Table 8). The evenness of use for Tongawas higher than for the current study. Peru, bycontrast, demonstrated high levels of richness,heterogeneity, and evenness (472; 5.95; and 0.97respectively) despite a small sample size. Mex-ico, on the other hand, showed lower values forthe diversity of species use and a higher domi-nance (Jprime 5 0.89). High diversity of plantuse in Mexico and Peru was ascribed to highdiversity of the vegetation in the study sites (Be-gossi 1996). In Tonga low diversity was proba-bly a representation of the island nation’s lowfloristic diversity.

PROBABILITY OF SPECIES UTILIZATION

There is a positive association between plantssold commercially and the size and distributionof southern African floral families. Larger fam-ilies occurring in biomes proximate to the mar-ket and the geographical sources of supply havea greater probability of being harvested.

Taxa in the Savanna have a greater probabilityof being utilized for several reasons. First, thebiome is the largest in southern Africa south of228S, occupying about 46% of the total area

Chapter 3; Pg. 15


(Low and Rebelo 1996) (Fig. 6). Second, taxaharvested in the Savanna account for about 48%of the cited sources. And third, it appears thatresource users, commercial gatherers, and theirantecedents historically inhabited the biome—hence the disproportionate use of species eventoday. Parts of woody plants (e.g., roots andbark), not geophytes and grasses common toGrassland, predominate in the market, thus theplant parts most commonly harvested (Table 4)corroborate evidence that Savanna is highlytraded.

Taxa in Grassland have a lower than expectedprobability of being utilized considering thestudy area is at its geographic center (Low andRebelo 1996). Taxa harvested in Grassland ac-count for about 31% of the cited sources. How-ever, the biome shares 60% of its taxa with Sa-vanna (Gibbs Russell 1987) and only coversabout 17% of southern Africa. Therefore, al-though Savanna appears to be the most utilizedbiome, it is not necessarily the most threatenedby commercial harvesting. Urbanization is a ma-jor influence on the loss of natural areas (Lowand Rebelo 1996). Gauteng grasslands are es-pecially threatened by extensive urban devel-opment, industrialization, mining and, to a lesserextent, agriculture (Bredenkamp and van Rooy-en 1996).

The use of and demand for traditional medi-cines can be species specific and alternatives arenot easily provided due to the characteristics ofthe plant material, their symbolism, and the formin which they are taken (Cunningham 1991b).African people have depended for ages on theirnatural environment for their health and survival(Mabogo 1990). This dependence has developedfrom centuries of experimentation with the floraavailable to them. The lack of scientific proof ofthe efficacy of (some of) the medicines does notnecessarily mean that the medicines used are notvaluable (Mabogo 1990).

Thirty-nine percent of the taxa sold commer-cially (Groups I and IV) exhibit no significantdifferences between their observed and expectedfrequencies. Utilization, therefore, is likely to beproportional to their availability in the southernAfrican flora and biomes, and random—i.e., thetaxa have an equal chance of being harvested.

Evidence suggests that 46% of the taxa tradedcommercially have a higher than expected prob-ability of being utilized (Group III and someGroup II). There thus appears to be specific fac-

tors determining the utilization, selection, har-vesting, and commercial value of species inthese families by the traditional health care pro-fession, the commercial gatherers, and the mar-ket. Pharmacologically active chemical com-pounds present in Group II and III families maypartially explain utilization (especially in GroupII where the families are smaller and geograph-ical distribution is not as extensive as someGroup III families). Overutilization of someGroup II families is possibly the result of largefamily size and their prevalence in Savanna andGrassland. Families that are underutilized mayhave limited representation in the vegetationtypes proximate to the major harvesting sources(e.g., Mesembryanthemaceae) or they may bechemically inert. Poaceae, for example, isranked 1 and 2 in Savanna and Grassland re-spectively, yet only six species are traded. Thefamily may be under-represented because itshigh availability has eroded its commercial val-ue.

CONCLUSION

Knowing what species are traded commer-cially is the foundation for identifying threat-ened taxa and comparing regional and nationalmedicinal markets. Furthermore, understandingthe dynamics of the trade and factors influencingsupply and demand are steps towards identifyingsolutions and survey methods for setting priori-ties and goals for sustainable development.

In unraveling the commercial market for me-dicinal plants on the Witwatersrand, a trendemerges. The trend is that ethnic and floristicdiversity are influential in deciding the sourcesand suppliers of plants and the high diversityand equitability of species that are traded. In ad-dition, the diversity and geographic distributionof southern African taxa are partly responsiblefor at least 46% of the families traded havinghigher than expected probabilities of being uti-lized.

Finally, in this survey of the Witwatersrandmedicinal plant market, quantitative methodsand techniques rarely attempted by ethnobota-nists were used to collect and analyze data. Inthe process, the results were statistically vali-dated, and new questions relating to the patternof plant utilization and trade were answered withmore confidence.

Chapter 3; Pg. 16


ACKNOWLEDGMENTSWe thank the National Research Foundation (NRF, formerly FRD) In-

digenous Plant Use Programme and Inland Resources Programme forfinancial support; the Endangered Wildlife Trust’s Eddie Young MemorialBursary for additional funding; Fanny Mokgaba for assistance during thesurvey; and David Newton, from TRAFFIC East Southern Africa, forvaluable discussion.

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, , and . n.d. A lexicon of plantstraded in the Witwatersrand umuthi shops. Bothaliain press.

Chapter 3; Pg. 17


APPENDIX. MEDICINAL PLANT FAMILIES OF THE

UMUTHI SHOPS. LIST OF THE 119 PLANT FAMILIES

RECORDED FOR SALE IN 50 UMUTHI SHOPS ON THE

WITWATERSRAND, SOUTH AFRICA BETWEEN JULY

AND DECEMBER 1994. FIVE HUNDRED AND ELEVEN

SPECIES REPRESENTING 326 GENERA WERE RE-CORDED.

FamilyNumber

of genera

Numberof speciesand infra-specific

taxa

ANGIOSPERMSAcanthaceaeAizoaceaeAmaranthaceaeAmaryllidaceaeAnacardiaceae

22365

223

155

AnnonaceaeApocynaceaeAquifoliaceaeAraceaeAraliaceaeAsclepiadaceae

251217

39121

11BalanitaceaeBalanophoraceaeBasellaceaeBegoniaceaeBignoniaceae

11111

11121

BoraginaceaeBrassicaceaeBurseraceaeBuxaceaeCactaceae

21111

21321

CampanulaceaeCanellaceaeCapparaceaeCarophyllaceaeCelastraceaeChenopodiaceae

113291

1156

132

ChrysobalanaceaeCombretaceaeCommelinaceaeCompositae/AsteraceaeConvolvulaceaeCornaceae

121

2031

171

3441

CrassulaceaeCucurbitaceaeCunoniaceaeDioscoreaceaeDipsacaceaeEbenaceae

111122

211327

EuphorbiaceaeFlacourtiaceaeGeraniaceaeGraminaeGreyiaceae

145221

286261

APPENDIX. CONTINUED.

FamilyNumber

of genera


taxa

HaloragaceaeGuttiferae

12

13

HydnoraceaeHypoxidaceaeIcacinaceaeIridaceaeLabiatae/LamiaceaeLauraceae

111643

141855

LecythidaceaeLeguminosae-CaesalpinioideaeLeguminosae-MimosoideaeLeguminosae-PapilionoideaeLiliaceae sensu latoLoganiaceae

175

1623

3

17

112057

6LoranthaceaeMalpighiaceaeMalvaceaeMartyniaceaeMeliaceaeMelianthaceae

112131

123154

MennispermaceaeMesembryanthemaceaeMoraceaeMyricaceaeMyrothamnaceae

13111

13111

MyrsinaceaeMyrtaceaeNymphaceaeOchnaceae

3212

3223

OlacaceaeOleaceaeOliniaceaeOrchidaceaePassifloraceaePedaliaceae

111721

212

1021

PeriplocaceaePhytolaccaceaePittosporaceaePlumbaginaceaePolygalaceaePolygonaceae

211121

221192

PortulacaceaeProteaceaePtaeroxylaceaeRanunculaceaeRhamnaceaeRhizophoraceae

221351

231452

RosaceaeRubiaceaeRutaceaeSantalaceae

213

52

314

62

Chapter 3; Pg. 18


APPENDIX. CONTINUED.

FamilyNumber

of genera


taxa

Sapindaceae 4 4SapotaceaeScrophulariaceaeSolanaceaeSterculiaceaeThymelaeaceae

33322

63725

TiliaceaeTyphaceaeUlmaceaeUmbelliferae/ApiaceaeVerbenaceae

21253

31294

ViscaceaeVitaceaeZingiberaceaeZygophyllaceae

Total

1111

313

1211

495

GYMNOSPERMSCupressaceaePinaceaePodocarpaceaeStangeriaceaeZamiaceae

Total

21111

6

21111

6

PERIDOPHYTAAdiantiaceaeAspidaceaeCyathaceaeEquisetaceaeLycopodiaceaePolypodiaceae

Total

211111

7

421111

10

Chapter 3; Pg. 19

chapter 3 2000 econ bot paper.pdf

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