Transcript Prunus africana - World Agroforestry Centre

Medicinal trees in smallholder agroforestry
systems: Assessing some factors influencing
cultivation by farmers East of Mt. Kenya
Jonathan Muriuki Kiura
Presentation summary
The research problem
 Research concept and objectives
 Study area and methods
 Results and discussions
 Conclusions and recommendations

2
The problem
Majority of Africa population is poor and ravaged by treatable
diseases but can’t afford modern medicine
Indicator
Austri Ethio Keny Mala Rwan Tanz Uga Zam
a
pia
a
wi
da ania nda bia
Population (2010 est.) mio
8.4
79.5
38.6
15.6
10.4
43.2
31.8
13.3
GDP (US$) trillions (2009)
385
38,748
29
936
30
1,572
5
859
5
1,071
22
16
1,358 1,219
128
1,431
4.4
86.9
64.4
89.4
112.4
72.6
76.9
92.7
5.4
145.3
104.1
131.8
187.8
118.4 127.4
157.0
GDP per capita US$ (2009)
Infant mortality rate (IMR) per
1000 births (2009)
Under five mortality rate per
1000 births (2009)
Maternal mortality rate per
100,000 live births (1999)
Total fertility rate (2007/8)
NA
870
590
1100
1100
530
510
650
1.42
5.29
4.96
5.59
5.92
5.16
6.46
5.18
Literacy rate (2007/8)
99.0
35.9
73.6
71.8
64.9
72.3
73.6
70.6
Life expectancy - years
(2007/8)
Contraceptive use (%) (1999)
79.8
52.9
54.1
48.3
46.2
52.5
51.5
42.4
NA
15(05) 46(09) 41(08) 36(08) 26(05) 24(06) 41(07)
An example of malaria – quick facts
Factor
Annual number of malaria cases globally
Annual number of malaria deaths globally
Number of malaria-endemic countries
Number of people at risk for malaria
Percent of global population at risk for malaria
Percent of malaria deaths in Africa
Percent of malaria deaths in children under 5
Percent of symptomatic children under 5 in
Africa treated with ACTs
Percent of at-risk people in Africa protected by
Insecticide-Treated Nets
Source: World Malaria Report 2008
Statistic
247 million
881000
109
3.3 billion
50%
91%
85%
3%
26%
Who offers treatment in Africa?
Country
Doctor : patient
Eritrea
Ethiopia
Doctors estimated at
120 in 1995
1:33,000
Kenya
1:7,142 (overall)
TMP : patient References
Government of Eritrea, 1995
World Bank, 1993
World Bank, 1993
1:833 (Mathare)
1:987 (Urban Mathare)
1:378 (Kilungu)
Malawi
1:50,000
1:138
Msonthi and Seyani, 1986
Mozambique
1:50,000
1:200
Green et al. 1994
Sudan
1:11,000
-
W Bank, 1993
Swaziland
1:10,000
1: 100
Tanzania
1:33,000
1:350-450 DSM
Green, 1985
Hoff and Maseko,1986
W Bank, 1993, Swantz, 1984
Uganda
1:25,000
1:708
WBank, 1993, Amai, 1997
Zambia
1:11,000
-
World Bank, 1993
Zimbabwe
1:6,250
1:234 (urban)
1:956 (rural)
World bank, 1993
Gelfand et al. 1985
Good. 1987:
Traditional medicine, mainly herbal, has been
substantially managing African health but is
under threat
Medicine
Plant
Knowledge
Phyto-medicines rely on two elements, plants (of which over 60%
are perennial trees and shrubs) and the knowledge associated with
6
their use. Either alone is useless.
Herbal medicine relying on wild plants collection is not viable because
biodiversity in Africa is threatened by agriculture, urbanization etc and
forests lost to below 10% in many countries (e.g. 1.7% in Kenya at
present)
Country area (x1000 hectares)
FRA 2005
categories
Austria
Forest*
Forest and other
wooded land
3862
Other land
Total land area
Inland water
bodies
Total area of
country
% forest of total
land area
% forest of total
area of country
Ethiopia
Rwan Tanzani Ugand Zambi
Kenya Malawi da
a
a
a
13000
3522
3402
480
35257
3627
42452
57650
38442
3402
541
40013
4777
45613
4293
51981
18472
6006
1926
48346
14933
28726
8273
109631
56914
9408
2467
88359
19710
74339
799
1123
2440
167
6150
4394
922
110430
58037
11848
2634
94509
24104
75261
46.7
11.9
6.2
36.2
19.5
39.9
18.4
57.1
46.1
11.8
6.1
28.7
18.2
37.3
15.0
56.4
3980
113
8386
Extent of forest and other wooded land in Eastern Africa compared to Austria by 2005 7
With increasing trade and TM use, medicinal plant
resource depletion is abundant and cultivation has been
recommended as a possible solution
But that is very easy for herbs (annuals) if appropriate germplasm and
products markets are accessible. For trees and other long rotation woody
perennials that poses a big challenge due to having to wait long and as long as
wild resources are available and perceived to be a common good
8
Conservation through use under cultivation What would be the ideal trend of growth in material supply as
knowledge of use improves?
9
Research questions
How do socio-economic factors influence the
decisions by farmers to cultivate or conserve
medicinal plants?
 How does ecology influence use and cultivation
of medicinal tree species?

Main hypothesis
The level of medicinal tree cultivation (Mc) is a factor
of germplasm availability (g), species ecology (e –
climate, soil and competition), local disease burden
perception with appropriate knowledge on use of
medicinal trees (k), and availability of market for
medicinal tree products (m).
Mc = f(g, e, k, m, α)
10
Adapted from FAO (2001)
General Conceptual Frame on farmer
adoption of an agricultural practice
Conceptual framework
11
12
Seedling quality as
well as access and
cost may demotivate
Other Products
Timber, food, ethno
veterinary, etc
Access to inputs
Germplasm (g)
Motivates especially if not
extractive harvesting
Household Consumption
Self treatment knowledge (k)
Smallholder
production sub-system
Medicinal trees (C)
Production Technology
Cultivation ecology (e)
Niche defines quality
and interaction with
crops (opportunity cost
to land and labour
Alternatives
Clinical Medicine
Wild
sources
Income
Sold to Markets (m)
Human Capital
Motivation to plant
Fig. Conceptual framework showing some factors expected to
influence cultivation of medicinal trees by smallholder farmers
If alternative
perceived
better then
only this path
taken
Demotivates
depending on access
and abundance
Objectives
To collate the perspectives of farmers and herbalists on the
factors influencing their preference and cultivation of tree
species with medicinal value
2. To assess the influence of local disease burden perception
and knowledge of herbal treatment on the efforts by
farmers and herbalists to cultivate medicinal trees
3. To explore the contribution of farm grown herbal material
to medicinal tree product markets and its effect on
medicinal tree cultivation
4. To explore how germplasm access by farmers and on-farm
tree nurseries influence medicinal tree cultivation
5. To explore motivational drivers of cultivation and the
scope for herbalists’ and traders’ utilization of farm
produced medicinal tree products
1.
13
The study area








3 districts (Embu, Mbeere
and Meru central)
Population density 100-500
persons / sq km
Nine agroecological zones
(LM5 to LH1)
Rainfall – 500 -2600mm;
Altitude 500 -2500masl
Soils – varying from nitisols
to ferrasols
Mixed-crop and livestock
agric systems
14
Good tree planting culture
Data collection methods





Farmer group meetings - cultural domain analysis
- 13 groups
Individual interviews - analysis with SPSS
 200 farmers
 60 herbalists
 60 nursery operators
 55 market players in 3 cities
Species abundance surveys in farms, forests and
herbalist gardens - analysis with BiodiversityR
Personal observations
Triangulations - interview responses tested with
empirical measurements
15
Interview survey results
Medicinal species present in
farms and herbalist gardens
Medicinal plant species
encountered in farms
Trees

Farms – 295 total species
(trees – 45%, shrubs – 27% and
herbs – 28%)

Herbalists’ gardens – 203 total
species (trees – 40%, shrubs –
27% and herbs – 33%)

60 species known as medicinal by
farmers but not recorded in any
farm (22 trees, 26 shrubs and 12
herbs)

Do farmers know more species
than herbalists?????
Shrubs
Herbs
Medicinal plant species
encountered in herbalists'
gardens
Trees
Shrubs
Herbs
16
Factors influencing cultivation
Farmers’ rating
Herbalists ranking
Freq.% Mean
Freq % Mean
(n=200)
rate
(n=60)
rank
97
2.3
98
4.3
Factor influencing
cultivation decision
Knowledge of treatment
Access to medicinal
1.2
products’ markets
89
98
2.9
Germplasm availability
80
1.2
98
2.5
Conservation of species
1.2
that were getting scarce
54
98
4.0
Species cultivation
1.3
technology known
81
98
1.4
Other uses of species
19
1.3
2
1
Herbalists knowledge issue was only a species treating many
diseases
17
Species highly preferred for cultivation
Growth form Frequency (%) of preference by
Species
herbalists
farmers
Prunus africana
Tree
56
26
Warburgia ugandensis
Tree
56
7
Aloe spp.*
Herb
49
45
Azadirachta indica
Tree
40
47
51
18
26
35
9
10
23
26
13
14
12
6
Olea europaea ssp africana
Strychnos henningsii
Erythrina abyssinica
Myrsine melanophloeos
Caesalpinia volkensii
Tree
Tree
Tree
Tree
Zanthoxylum chalybeum
Shrub
Tree
Senna didymobotrya
Tree
Ocotea usambarensis
Croton megalocarpus
Tree
Tree
9
19
12
11
18
Summary on farmers and herbalists’
perceptions







Herbalists preferred trees that treat more diseases
and are scarce – farmers knowledge then markets
Farmers in Mbeere influenced by germplasm
availability than markets
Multiple use of species not very important to
influence both farmers and herbalists
Cultivation technology rated low – but factors such
as appropriate niches and farm sizes important
Women farmers rated knowledge, markets and
multiple use higher than men
Trees on farm correlated loosely with the frequency
of species preference
Usually one tree per household is enough for self
treatment and neighbours can use
19
Most socio-economically important diseases
Disease
Herbalist s’ score Herb Rank
Farmers’ score
Farm Rank
Malaria
10.7
1
11.2
1
Typhoid
5.7
7
8.5
2
Respiratory problems
8.3
3
7.9
3
HIV/AIDS
8.6
2
6.7
4
Pneumonia
7.0
4
6.1
5
Hypertension
5.2
9
5.0
6
Tuberculosis
5.9
6
4.4
7
Diabetes
6.1
5
4.2
8
Back/bones/joints aches
3.6
16
4.2
9
Cancers
5.0
11
4.0
10
Measles
3.5
18
3.9
11
Dental disorders
5.3
8
2.8
20
Rheumatism
4.8
13
3.8
15
Amoeba
4.8
12
3.7
16
Asthma
5.1
10
2.6
24
20
Disease effect management by farmers
Health management measure
Preventive (ex ante risk minimising)
Clean drinking water
Contribute to development of community health facilities
Good diets
Immunization through vaccination
Keep useful medicine in house
Keeping warm
Medicinal plant conservation
Other preventive methods
Other traditional health practices
Personal and household hygiene
Public health training and practices
Use of mosquito nets
Treatment (ex post risk coping)
Off the counter medicine
Seek conventional medicine assistance
Use of herbal medicine
Grand Total
Percent (n =142)
232
30
3
30
3
19
4
51
1
3
57
1
31
32
4
3
25
21
264*
Number of species used in treating
important diseases
27
Allergies
16
Diabetes
37
Dental
81
Coughs
52
Amoebiosis
Herbalists
Farmers
37
Bones
42
Typhoid
54
Rheumatism
40
Pneumonia
90
Malaria
0
20
40
60
80
100
120
14022
Aloe sp
Azadirachta indica
Caesalpinia volkensii
Dalbergia melanoxylon
Erythrina abyssinica
Moringa oleifera
Myrsine melanophloeos
Olea europaea
Prunus africana
Strychnos henningsii
Warburgia ugandensis
6
2
5
1
13
14
4
2
5
15
5
10
12
1
6
6
3
3
32
13
9
2
6
5
2
8
3
2
95
126
49
27
10
1
12
2
5
2
3
3
17
1
12
10
4
2
1
Typhoid
Rheumatism
Pneumonia
Malaria
Diabetes
Dental
problems
Cough/flu
Amoebiasis
Back/joint/
bone
problems
Highly ranked species in treatment
of most important diseases
8
15
1
8
25
2
1
6
7
1
4
1
1
2
7
13
3
2
1
23
Farmers’ sources of knowledge on use of
medicinal plants for disease treatment
Information sources
Herbalists
Nursery operators
Media (newspapers,
radios )
Older relatives (parents,
grandparents )
Neighbours
Seminars
Exchange programmes
by NGOs
No response
Total
Frequency (%) of mention
as source number: (N=200)
1
2
3
Total
25
0
0
25
3
0
0
3
6
5
0
10
57
7
1
21
16
3
4
9
1
82
32
5
2
2
100
4
53
100
1
85
100
6
300
Most information
passed through
genealogy and
herbalists
contribution is low!
24
Who speaks about importance of
medicinal tree cultivation to farmers?
Herbalists
Tree nursery operators
Media (newspapers, radios)
Older relatives (parents,
grandparents )
Neighbours
Development programmes
(govt, NGOs
Medicinal tree product
buyers*
Own initiative*
No response
1st
11
6
2
2nd
0
1
2
3rd
0
0
1
Total
11
7
4
6
2
1
4
0
3
6
78
16 7
1
23
1 1
14 3
45 84
0
1
95
1
17
25
So knowledge of medicinal tree species
varies with socio-demographic categories
Socio-economic factor
1
2
3
4
5
6
P - value
Gender
Age
Education level
District
First response to symptom
of illness by family member
12.6
8.4
16.1
9.2
13.2
0.551
10.1 12.9 14.9 14.9 12.7 0.002
13.2 12.5 11.1 6.6
0.012
15.1 13.9
0.000
15.1 10.8 12.2 9.0
Number of species known increased with age, district harshness, and use
but decreased with education level attained by respondent
Key: Gender -1(Female), 2 (Male); Age in years – 1 (<25), 2 (25-35), 3 (35-45), 4 (55-65), 5
(>65); Level of education attained – 1 (not schooled), 2 (primary level), 3 (village
polytechnic), 4 (secondary), 5 (post secondary); District – 1 (Embu), 2 (Mbeere), 3 (Meru
Central); First response to ailment - 1 (find a medicinal plant), 2 (buy an over the counter
drug), 3(consult a medical clinic or hospital), 4 (consult a herbalist)
26
Does farmer’s knowledge influence cultivation
Only planted tree species All medicinal tree species
in farms
Ka = All species known and the
diseases treated
All med species in farm
Observed
Linear
r = 0.8
25
Kb
Same
as Ka
All med species in farm
r = 0.7
Observed
Linear
25
2
20
Kc = Kb with the diseases weighted by the
farmer perceived socio-economic importance
r2 = 0.5
20
r = 0.6
15
15
10
10
5
5
0
0
0
20
40
60
0
100
Knowledge index a
200
300
400
Knowledge index c
All planted med species
Observed
Linear
r = 0.6
20
r2 = 0.4
15
Same
as Ka
All planted med species
r2 = 0.3
15
10
10
5
5
0
Observed
Linear
r = 0.5
20
0
0
20
40
60
80
Knowledge index b
100
120
0
100
200
300
400
Knowledge index c
Kb = Ka plus species used at home weighted by multiplying by 2 – same relationship as Ka
Only number of species used and not total number of trees since farmers indicated that one
27
tree was enough for household self medication for almost all species
Summary on farmers knowledge on TM
and its influence on med tree planting





No difference in rating of disease economic
importance between farmers and herbalists
rate -same as hospitals
Medicinal trees play role in household health
Herbalists use more of wild species while
farmers use agroforestry species more
Farmers learn about medicinal trees from
relatives and cultivation mainly own initiative
The medicinal species present in farms
influenced more by the species known little by
the perception of the socioeconomic
importance of diseases
28
Medicinal plant markets and cultivation
of medicinal trees
Final products
Herbal clinics
Pre-processors
Business
categories
Final
products
Freq %
(n=55)
Av Trade
period
Av % annual Av no Species Av % volume
growth
traded
purchased
Av %of
volume wild
36
11
424
7
69
29
Herbal Clinic
Preprocessing
40
17
158
6
45
59
24
17
100
5
36
72
Grand Total
100
15
241
6
53
51
29
Sources of herbal materials in markets
Species
Growth Freq %
habit
(n=55)
Av Trade Av annual
period
trade (Kg)
Av annual
growth %
Av %
Demand
from farm trend
Aloe spp
Shrub
51
14
286
333
55
Rising
Azadirachta indica
Tree
44
14
693
496
88
Rising
Warburgia ugandensis
Tree
24
11
333
231
44
Rising
Eucalyptus spp
Tree
22
10
117
600
98
Rising
Prunus africana
Tree
22
14
408
255
73
Rising
Urtica dioica
Ekebergia capensis
Herb
Tree
20
13
8
22
943
105
1122
32
30
5
Const
Rising
Zanthoxylum gillettii
Tree
13
15
175
109
0
Rising
Albizia anthelmintica
Tree
9
20
77
75
0
Rising
Kigelia africana
Tree
9
5
269
214
30
Const
Moringa oleifera
Tree
9
5
463
864
100
Rising
Croton megalocarpus
Rhamnus prinoides
Senna didymobotrya
Tree
Tree
Shrub
7
5
5
20
6
12
168
104
80
189
150
199
95
33
33
Rising
Rising
Const
The numbers show the average per trader for each parameter; n=55
30
Traders’ preference for source of medicinal plant materials
Preferred
source
Reason for preference
Farms (27% of
respondents)
• Natural resource conservation
5
• Good tree husbandry in farms
11
Own collection
39%
• Species authenticity in farms
4
Purchased 61%
• Species scarcity in the wild
7
• To create market / future sources
2
Total
29
• Customary preference in practice
2
• Mature plants and grown in rich
substrate
16
• Less contamination/interference
15
• Little or no cost of procurement
7
Total
76
Natural
forests and
woodlands
(69% of
respondents)
No preference • Depends on distance and costs
(4% of resp)
• No reason given
% of respondents
giving reason
2
2
4
Procurement
approach
Own collection
51%
Purchased 49%
Own collection
100%
31
But farmers reported little connection to markets
Summary on trade
Species
Markhamia lutea
Myrsine
melanophloeos
Olea europaea
Osyris lanceolata
Warburgia ugandensis
Number of
farmers
1
Plant part
sold
Roots
3
2
1
1
Seeds
Cuttings
Whole plant
Bark
Where sold
Herbalist/neighbours (1)
Vendors (1); Market (2);
Neighbours (1)
Vendors (2)
Vendors (1)
Herbalist (1)
• Trade in medicinal trees was rising but farmers were not
participating in any significant manner
• Most of indigenous tree species were traded collected from
the wild – threats
• Two thirds of traders who purchased materials preferred farm
sourced materials – mostly in the final products category
• Getting materials at little or no costs contributes to more wild
collection – distance may discourage but not tested in this
32
study
Focus on tree seedling sources
No of
nurseries
Av size
(m”)
Space with
trees (%)
Embu
20
103
93
Mbeere
20
47
94
Meru
Central
20
544
79
Total/
Average
60
231
89
10.0
Number of tree species in nursery
District

7.5


5.0


2.5

Mer u timber
Mer u medicinal
Mer u fruits
Mer u fodder
Mbe ere timber
Mbe ere medicinal
Mbe ere fruits
Mbe ere fodder
Embu timber
Embu me dicinal
Embu fruits
Herbalists with nurseries
(numbers
are % nGiven
= 60) sold or
Planted
Embu fodder
0.0
Exclusiv Grand
District and ca te gory of tre e specie s
District in garden away given free ely sold Total
Embu
7
7
5
5
23
Mbeere
3
0
2
0
5
Meru
Central
5
2
2
3
12
Total
15
8
8
8
40
33
Presence of highly preferred species in nurseries
Freq Av no Av seedlings
Growt % (n = seedlin supplied
Species
h habit 60)
gs
before
Prunus africana
T
25
211
1111
Azadirachta indica
T
13
37
43
Olea europaea
T
12
292
1477
Aloe spp.
H
8
101
61
Croton megalocarpus
T
8
7
46
Juniperus procera
T
8
406
2223
Hagenia abyssinica
T
7
4
108
Croton macrostachyus
T
5
0
87
Markhamia lutea
T
5
305
93
Myrsinne melanophloeos
T
5
668
3438
Acacia xanthophloea
T
3
5
33
Bridelia micrantha
T
3
0
25
Av trend
Demand
H
H
H
H
C
H
H
C
C
H
C
H
34
Sources of medicinal trees in farms
Species
% farms
NR
Neighbours
Tree nurseries Wildlings
Aloe sp
52
17
6
5
64
Azadirachta indica
27
9
4
59
6
Croton macrostachyus
24
48
2
17
29
Prunus africana
23
24
2
22
50
Senna didymobotrya
21
67
2
2
21
Croton megalocarpus
20
3
3
48
35
Erythrina abyssinica
20
68
3
3
25
Tithonia diversifolia
19
24
8
0
62
Olea europaea
17
41
3
12
35
Psidium guajava
16
10
3
48
23
Solanum incanum
13
96
0
0
4
Terminalia brownii
11
81
0
5
14
Ocimum suave
10
80
5
0
10
Zanthoxylum chalybeum
10
90
0
0
10
35
Summary on seedling sources
• Farmers
were mainly planting medicinal trees
from wildlings
• Demand for medicinal species lower than
timber and higher than fruits and fodder in
Meru; lower than fruits and fodder in Mbeere
and fruits in Embu
• Demand for medicinal seedlings higher than
supply in nurseries – but not all species
• Need investment in diversifying germplasm in
both private and herbalist nurseries
36
Key species abundance surveys (focus
on 30 most preferred)
Farms
 In twenty farms and ten
herbalist gardens in each
district
 Key species abundance
 Age/size class distributions
relating to regeneration
method
 Niche in the farm
 Other competing household or
market uses of the species
Forests and woodlands
(herbalist in team)
 Species abundance
 Age/size distributions
 Evidence of harvesting
method damage
37
38
Species abundance survey results
The thirty species were whose abundance was measured
include
Albizia gummifera
Ficus sycomorus
Rhamnus priniodes
Aloe sp
Ficus thonningii
Ricinus communis
Azadirachta indica
Kigelia africana
Senna didymobotrya
Brideria micrantha
Leonotis mollissima
Solanum incanum
Ceasalpinia volkensii
Moringa oleifera
Strychnos henningsii
Cordia africana
Croton
macrostachyus
Ocotea usambarensis
Myrsine
melanophloeos
Tithonia diversifolia
Croton megalocarpus
Dalbergia
melanoxylon
Osyris lanceolata
Olea europaea ssp
africana
Erythrina abyssinica
Prunus africana
Warburgia ugandensis
Zanthoxylum
chalybeum
Zanthoxylum
usambarense
39
Vepris nobilis
General abundance of species in surveyed
farms, forests and herbalists’ gardens
Ra Farms
nk
1
2
3
4
5
6
7
8
9
10
Eucalyptus spp
Grevillea robusta
Catha edulis
Solanum incanum
Acacia tortilis
Acacia spp
Acacia brevispica
Lantana camara
Tithonia diversifolia
Aloe spp
%
Herbalists‘
Prop gardens
11.3
10.0
9.4
9.1
6.0
3.2
3.2
2.9
2.9
2.6
Lantana camara
Catha edulis
Solanum incanum
Erythrina abyssinica
Leucaena spp
Grevillea robusta
Indigofera lupatana
Acacia nilotica
Acacia tortilis
Maytenus
senegalensis
Forests
%
Prop
16.4
9.2
9.1
6.8
6.4
3.2
3.1
2.9
2.6
2.6
Sizygium guinense
Mugiru
Mwenyuka
Mukwethe
Mutengerethe
Aspilia africana
Gnidia subcordata
Lantana camara
Murieni
Ocimum suave
%
Pro
p
8.7
7.8
6.4
2.9
2.9
2.7
2.6
2.4
2.3
1.8
40
20
15
10
Embu
Herbalist gardens/farms
Mbeere Embu Meru
Meru
Mbeere
5
species richness
Mbeere
0
Species richness
15
10
Forest and woodlands
Mbeere Embu Meru
5
Embu
Meru
Embu Meru
Mbeere
Meru
Embu
25
25
Mbeere
2
0
Speciesspeciesrichness
richness
20
20
30 top species accumulation curves
4
6
sites
5
10
15
20
20
Sites
Mbeere
15
Embu
10
richness
richness
Speciesspecies
20
20
sites
Smallholder farms
Mbeere Embu Meru
0
5
Embu
Mbeere
Meru
5
10
15
Sites
sites
20
20
Meru
8
10
10
• More abundance in forests and
woodlands in Mbeere than Embu
and Meru
• Herbalists in Embu and Meru plant
more – response to scarcity
• Not much difference in abundance
in smallholder farms in the three
districts but smallholders generally
plant less
41
3.0
30 top species Renyi profiles
2.5
1.5
H-alpha
1.0
2.0
Meru
Meru
Embu
Mbeere
0.0
Meru
H-alpha
2.0
1.5
1.0
H-alpha
Embu
0.5
H-alpha
1.5
1.0
Embu
Mbeere
0.0
0.0
Meru
Mbeere
0.5
H-alpha
H-alpha
2.0
2.5
2.5
Embu
Meru
Embu
Mbeere
Meru
Embu
0.5
Mbeere
3.0
3.0
Mbeere
Embu
Meru
Mbeere
0
0.25
0.5
1
2
4
8
Inf
0
0.25
0.5
1
alpha
8
3.0
3.5
2
4
8
Inf
Five
0
0
0.25
0.5
1
2
alpha
Combined
4
8
Inf
0.25
0.5
1
2
4
8
Inf
Forests and distance RP
alpha
20
5
10
15
Ten
Five
Ten
0
0.0
Forests
Herbalists
species richness
2.0
1.5
1.0
Five
0.5
H-alpha
H-alpha
Ten
Species richness
2.5
3.0
2.5
2.0
1.5
1.0
Farmers
0.5
H-alpha
1
Farms and districts
25
Five
Ten
0.0
H-alpha
0.5
alpha
Forests
Farmers
Mbeere
0.25
Inf
Herbalists and districts
Herbalists
Meru
4
alpha
Forests and districts
Embu
2
25
0
0
10
20
30
40
Forests and distance SAC
>5 km from village <5 km from village
sites
42
Age and Dbh class comparisons
Mean proportion of tree numbers planted by
Age class Farmers Herbalists
Average
F
Sig
0-5
36
104.8 0.00
19
56
6,0-20
15
34.3 0.00
8
24
20+
2
5
4
4.0
0.04
NR
71
15
45
259,6051 0.00
Size class Mean proportion found in
Farms
herbalists Forests Average
F
sig
0,5 - 4,9
17
7.10
0.00
19
22
8
5,0-9,9
52
3.51
0.03
57
53
45
10-19,9
13
12
13
13
0.21
0.81
20-39,9
7
9
15
10
5.91
0.00
40+
3
5
19
8
22.28
0.00
* numbers represent the average of the proportion of the trees in the age/dbh category to all the trees of each of the
study species in the farm/plot
• More planting by herbalists in the lower age classes than farmers
• More lower size classes in farms than forests
• But farmers only 30% of the species were said to be primarily for
medicinal use by farmers compared to 66% by herbalists
43
Parameter
Cluster centres
Is there potential
for herbalists
and
1
2
3
4
General
Believes ecology
affects
medicine
quality
2
2 herbal
2
2
traders
to
use
farm-grown
ecological
Prefers farm (1) or forest (2) source
2
1
1
2
perception
in future?
Prefers humid material
(1) or dry (2) source
2
2
0
2
Item
Prefers cool (1) or warm (2) source
2
2
0
2
2
3
3
3
2
2
3
4
4
1
2
1
15
22
17
43
51
25
2
22
32
23
10
33
1
1
0
1
Cluster analysis based on ecological
1
1
preferences for herbal medicine
raw0 1
1
1
0
1
material
sources
by herbalists
and
traders
Mean
score for fast
growth rate
3
4
3
2
Perception ofPrefers isolated (1) or many (2) trees
farm as only Prefers fertile (1) or infertile (2) site
source
Prefers open (1) or shaded (2) sites
Preference
for improved Mean score for resilience with constant
medicinal
harvesting
tree
Mean score for high chemical composition
ideotype*
Mean score for high biomass production
Percent of
Herbalists (n=60)
respondents Traders (n=55)
in clusters
Total
Options for ideotype improvement preference:- 1. Least important; 2. A bit
important; 3. Important; 4. Most important
44
Summary findings on species abundance






Highly preferred medicinal trees were more abundant
and even in herbalist gardens than farms and forests
There were more lower age and size classes in
herbalist gardens hence diversity may increase in
future
Herbalists planted more in areas where diversity was
less in forests
There were no specific niches that mimicked forests
that herbalists preferred to plant medicinal trees
More herbalists and traders preferred medicinal trees
sourced from forests but not necessarily farm niches
that mimicked forest situations
Upto 67% of the current traders and herbalists can
switch preference to farm grown herbal material if
forest trees were not very accessible
45
General conclusions







Farmers maintain medicinal tree species on farms for
household health insurance – only one tree is enough
per household
The more trees known the more conserved
Herbalists not engaged in conservation advocacy and
young and educated farmers least informed
Herbalists cultivation is increasing as a response to
scarcity – good entry to ensure diversity in farms
Trade in medicinal trees’ products is growing and could
stimulate cultivation
Strategies needed to support nurseries in dry areas as
current abundance will disappear fast
Empirical measurements supported survey responses
46
Recommendations - actions






Involve herbalists and tree nursery operators in
extension on medicinal trees information
Further development of markets and link to farmers
Policy incentives to promote cultivation and
discourage wild collection
Germplasm conservation and production linking
herbalists and nursery operators
Policies to develop arid areas as future sources of
medicinal tree material
Further research on influence of various cultivation
approaches on medicinal tree active component
concentration
47
Multi-stakeholder approach needed to collate
and share information with farmers on
•Useful medicinal species for what diseases
•Markets needs (MIS)
•High quality germplasm sources
•Appropriate cultivation technologies
48
Recommendations - top species for
domestication priority – matrix ranked










Azadirachta indica
Aloe sp
Warburgia ugandensis
Caesalpinia volkensii
Prunus africana
Zanthoxylum chalybeum
Strychnos henningsii
Senna didymobotrya
Moringa oleifera
Dalbergia melanoxylon









•
Leonotis mollissima
Croton macrostachyus
Croton megalocarpus
Olea europaea ssp africana
Psidium guajava
Osyris lanceolata
Plectranthus barbatus
Erythrina abyssinica
Rhamnus prinoides
Fagaropsis angolensis
49
Senna didymobotrya Dalbergia melanoxylon Azadirachta indica
Zanthoxylum
chalybeum
Olea europaea ssp
africana
Aloe sp
Moringa oleifera
50
Warburgia ugandensis
Acknowledgements
•
•
•
•
•
•
•
•
•
•
Prof. Gerhard Glatzel
Prof. Christian Vogl
Profs. From IFE : Gratzer, Hager and others
ICRAF senior staff: Drs. T. Simons, S. Franzel, R. Jamnadass
OEAD
ICRAF administration and GRP1 colleagues
Fellow students and IFS staff
My family (Esther, Grace,Victor)
Extended family and friends
et al
And many thanks to you all
for attending and listening
‘If many little people, in many little places, do many
little things, they can change the face of the earth.’
52