1. Potential natural vegetation maps
for western and central Kenya
Presently underutilized tools for the
selection of indigenous tree species and
their seed sources
Roeland Kindt (ICRAF / VVOB [Flanders, Belgium])
Jens-Peter B Lillesø (ICRAF / FaL [Denmark])
Paulo van Breugel (ecologist, formerly IPGRI)

2. Overview
• Which species to plant in a certain area for a
certain purpose: use of potential natural
vegetation maps to indicate ecological suitability
and databases/books to select potential
functions
– How were the maps and species lists developed?
– Do potential natural vegetation maps provide an
adequate picture of climatic/edaphic variation in
Kenyan highlands?
– Do potential natural vegetation maps delineate
assemblages of indigenous tree species?
– What are the options for agroecosystem
diversification?

3. Map of potential natural vegetation
of south-western Kenya
• High resolution maps available for south-western Kenya
(Trapnell and co-workers)
– Four 1: 250,000 maps with vegetation boundaries for 1960
based on aerial photographs (1:30,000 and 1:50,000) and dense
traverses (< 1 mile apart where accessible roads)
– Photographs mainly 1945-63 and fieldwork mainly 1945-1963
– Vegetation classified in 18 groups, 23 subgroups, 55 classes
and 217 subclasses
– Interpretation of climax vegetation types and eco-climatic
conditions through remnants of climax types and pioneer
(secondary) vegetation types
– Unfortunately limited documentation of criteria for vegetation
types
– Publication of maps took long time (1966-1986)
– Maps have not been used in the realm of agroforestry

4. 1966
1976
1986
1969

6. 17 potential natural vegetation
types
• Potential natural vegetation = the vegetation structure that would become
established if all successional processes were completed under the present
or future climatic and edaphic conditions
• Determined from names of original vegetation types and eco-climatic maps
• Main classification scheme is physiognomic (based on structure such as
percentage aerial cover and height) (similar in other schemes)
• Secondary classification scheme is floristic (based on dominant or typical
species)
• Other differences between types are interpretation of climatic conditions, but
not determined from rainfall or altitude criteria (eg dry montane forest)
• Four sheets produced (1:300,000; A3 format)
• Excel sheet with uses and vegetation types compiled for 362 tree species
that are indigenous to Kenya (types from legend map, other paper by
Trapnell on forests, other literature, herbarium vouchers; uses from
AgroforesTree Database + Useful trees book by RELMA)
• Herbarium locations obtained for 110 species (but > 20 for only 2 species)
• Detailed documentation of map interpretation and vegetation-specific lists
almost finalized (want to avoid problem with original map!)

7. Physiognomic vegetation types
Forest
touching and interlocking crowns
≥ 8 (10) m tall
lianas
Woodland
≥ (40) 50% cover, open
≥ 8 m tall
Wooded grassland (savanna)
10 – (40) 50% cover
≥ 6 m tall
Bushland and thicket (impenetrable)
≥ (40) 50% cover
3 - 7 m tall
Bushed grassland
10 – (40) 50% cover
< 6 m tall
Special types: swamp, bamboo, afro-alpine,
moorland

8. High mountain vegetation types (3)
Afro-alpine
Mountain scrubland and moorland
Bamboo woodland and thicket

9. Mountain scrubland and moorland
Afro-alpine
Bamboo woodland and thicket

10. Forest vegetation types (4)
Moist montane forest
Dry montane forest
Dry intermediate forest Moist intermediate forest

11. Dry montane forest
Moist montane forest
Moist intermediate forest Dry intermediate forest

12. Woodland and savanna vegetation types (4)
Lowland Acacia woodland, bushland and thicket
Upland Acacia woodland, savanna and bushland
Moist Combretum-Terminalia savanna Dry Combretum savanna

13. Moist Combretum-Terminalia savanna Dry Combretum savanna
Upland Acacia woodland, savanna and bushland Lowland Acacia woodland, bushland and thicket

14. Bushland and thicket vegetation types (3)
Lowland Acacia woodland, bushland and thicket
Evergreen and semi-evergreen bushland
Semi-evergreen thickets

15. Evergreen and semi-evergreen bushland
Semi-evergreen thickets
Lowland Acacia woodland, bushland and thicket

16. Vegetation types on soils with impeded drainage (3)
Acacia and allied vegetation on soils with impeded drainage
Swamp and Papyrus
Open grassland areas on soils with impeded drainage

17. Open grassland areas on soils with impeded drainage
Swamp and Papyrus
Acacia and allied vegetation on soils with impeded drainage

18. Distribution of vegetation types,
climate and species
• Both vegetation and species distribution can be
explained by the same explanatory variables (biotic,
abiotic, landscape configuration, evolutionary time)
• Literature on vegetation types lists typical species for
each type
• Flora, databases, books and herbarium records list
vegetation types (habitat) for each species
• Present and historical climatic conditions can be
determined from pollen composition
• Vegetation map of Africa (White) turned out to be map of
plant endemism (phytochoria) and was later used as
biogeographical map for African terrestrial ecoregions
• Sophisticated statistical models perform better when
vegetation (landuse) is one of the explanatory variables

19. Biome 4 model (Kaplan et al. 2003)
Equilibrium distribution of 28 major potential natural vegetation types
(biomes) from latitude (photosynthetically active solar radiation),
atmospheric CO2 concentration, mean monthly climate (mean monthly
precipitation, temperature, and percent sunshine) and soil physical
properties (water holding capacity and percolation rate)

20. Check of relevance of maps
• Vegetation boundaries vs. patterns in
climatic/soil differences
• Vegetation boundaries and original
species composition vs. current species
composition

21. Interpolated surface layers
Data layer Resolution
• Investigation
Annual precipitation 5 km (grid)
how well
Annual potential evapotranspiration 5 km (grid)
potential Mean minimum temperature of the coldest 5 km (grid)
vegetation month
Number of dry months 5 km (grid)
types
Rootable depth 1:1 000 000 (vector)
correspond to
Cation exchange capacity 1:1 000 000 (vector)
climate, soil
Soil water pH 1:1 000 000 (vector)
and DEM Percentage of clay 1:1 000 000 (vector)
information Percentage of sand 1:1 000 000 (vector)
Altitude (DEM) 92 m (grid)
Slope 92 m (grid)
Topographic wetness index 92 m (grid)

22. Interpolated surface layers
Afro-alpine
Crosses indicate 10%-25%-75%-90% quantiles
1800
and are centred on mean
1600
ALP
Precipitation
1400
MIF MSM
MCO MMF
Precipitation
Montane scrubland
BAM
1200
SWADIF and moorland
SET IAC
1000
Bamboo
OGR DMF
DCO MIX
UAC EB Dry montane forest
800
LAC
Evergreen bushland
600
Lowland Acacia-Commiphora Upland Acacia
1000 2000 3000 4000
Altitude
Altitude

23. Forests
moist intermediate moist montane
1600
Precipitation
1400
MIF
MMF
Precipitation
Convex hulls delineate
1200
DIF
all observations; line
1000
DMF types show concentric
hulls after outer hull was
800
left out
1500 2000 2500
1800
Altitude
Altitude
1600
1400
MIF
dry intermediate MMF
Precipitation
1200
dry montane DIF
1000
DMF
800
600
1000 1500 2000 2500 3000
Altitude

24. 1100
Woodlands
lowland Acacia- Upland Acacia
Commiphora
1000
Precipitation
900
Precipitation
UAC
800
LAC
700
600
1400
800 1000 1200 1400 1600 1800
Altitude
Altitude
1200
1000
Precipitation
UAC
800
LAC
600
500 1000 1500 2000
Altitude

25. Moist Combretum-Terminalia
1400
Savannas
Impeded Acacia
MCO
Precipitation
1200
Precipitation
IAC
1000
Mixtures of evergreen
DCO MIX
UAC bushland and broad-
800
leaved savanna
600
1000 1200 1400 1600 1800 2000 2200 2400
1800
Altitude
Altitude
1600
1400
MCO
Precipitation
1200
Dry Combretum 1000
IAC
Upland Acacia DCO UACMIX
800
600
500 1000 1500 2000 2500 3000 3500
Altitude

26. 1400
Bushland and thicket
Semi-evergreen thickets
1200
Precipitation
SET
Evergreen bushland
Precipitation
1000
MIX
UAC EB
800
LAC
600
800 1000 1200 1400 1600 1800 2000
Altitude
Altitude
1600
1400
1200
Precipitation
lowland Acacia- SET
1000
Commiphora Upland Acacia MIXEB
800
UAC
LAC
600
500 1000 1500 2000
Altitude

27. Linear discriminant analysis:
predictions based on GIS layers
All
Impeded grassland
Dry Intermediate Forest
Swamp
Dry Combretum
Bamboo
Moist Combretum
Mixtures
Impeded Acacia
Upland Acacia
Moist Intermediate Forest
Evergreen bush
Semi-evergreen thicket
Moist Montane Forest
Mountain moorland
Alpine
Lowland Acacia
Dry Montane Forest
0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00%
Correct Same physiognomy Wrong

28. Linear discriminant analysis:
predictions
Impeded grassland
Swamp
Alpine
Dry Intermediate Forest
Mixtures
Mountain moorland
Dry Combretum
Bamboo
Upland Acacia
Moist Combretum
Semi-evergreen thicket
Moist Intermediate Forest
Lowland Acacia
Moist Montane Forest
Impeded Acacia
Evergreen bush
Dry Montane Forest
0 1000 2000 3000 4000 5000 6000 7000
correct physiognomic wrong

29. Ecotones and/or resolution?
Dry montane
forest
Dry montane
forest
Moist montane
Mount Kenya forest
Moist montane
forest

30. Linear discriminant analysis:
commissions (false predictions)
Impeded grassland
Swamp
Alpine
Dry Intermediate Forest
Mixtures
Mountain moorland
Bamboo
Moist Intermediate Forest
Moist Montane Forest
Semi-evergreen thicket
Upland Acacia
Dry Combretum
Moist Combretum
Evergreen bush
Lowland Acacia
Dry Montane Forest
Impeded Acacia
0 500 1000 1500 2000 2500
< 1 km 1 - 5 km > 5 km

31. Floristic differences
MCO
principal coordinates analysis
based on Bray-Curtis distance
0.4
for presence-absence of 362
DCO
species (Biodiversity.R)
0.2
MIF
DIF
Dim2
EB
0.0
SET MMF
UAC
IAC DMF
LAC
-0.2
BAM
-0.4
-0.5 0.0 0.5
Dim1

32. Floristic differences
MCO distance-based
precipitation MIF
redundancy
2
analysis based on
Bray-Curtis distance
(Biodiversity.R)
1
MMF DIF SET
DCO
CAP2
0
IAC LAC
-1
DMF
UAC
EB
-2
altitude
BAM
-4 -2 0 2 4
CAP1

33. Current patterns of indigenous tree
diversity around Mount Kenya
Survey by Ogi
et al.
250 quadrats of
50 × 100 m2
within map
279 indigenous
tree species
(174 species
also in literature
description)

34. Total and shared species richness between
literature and current species assemblages
Potential Natural n Species (Based Species % Species total Kulczynski
Vegetation Type total on total confirmed (survey) ecological
(literature) shared) by survey distance
Moist intermediate 57 105 51 31 61% 82 0.41
forest
Dry Combretum 40 23 21 18 86% 108 0.45
Dry montane forest 37 91 58 31 53% 83 0.42
Moist montane 37 99 46 30 65% 85 MIF
forest (dif 0.005)
Lowland Acacia- 25 92 48 35 73% 102 0.36
Commiphora
Evergreen bushland 16 44 38 18 47% 52 0.47
Dry intermediate 15 74 49 27 55% 63 0.43
forest
Upland Acacia 7 22 20 6 30% 35 ST
(dif 0.108)
Acacia (impeded) 6 28 18 5 28% 18 UA
(dif 0.042)
Semi-evergreen 6 29 19 6 32% 52 DC
thicket (dif 0.233)

35. Frequencies of species
Potential natural Species Rank Frequency
vegetation type (%)
Moist intermediate forest Cordia africana 1 67
n = 57 Croton macrostachyus 2 60
Commiphora eminii 3 53
Bridelia micrantha 4 51
Markhamia lutea 5 37
Erythrina abyssinica 6 33
Croton megalocarpus 7 32
Catha edulis 8 23
Prunus africana 9 21
dry Combretum savanna Croton macrostachyus 1 45
n = 40 Combretum molle 2 42
Euphorbia tirucalli 3 40
Combretum collinum 4 35
Croton megalocarpus 5 32
Piliostigma thonningii 5 32
Azanza garckeana 7 30
Senna singueana 8 25
Dry montane forest Croton megalocarpus 1 62
n = 37 Euclea divinorum 2 51
Juniperus procera 3 49
Plectranthus barbatus 4 41
Rhus natalensis 5 38
Lippia javanica 6 35
Scutia myrtina 7 30
Psiadia punctulata 8 27
Solanum incanum 8 27
Olea europaea 10 22

36. Frequencies of species
Potential natural Species Rank Frequency
vegetation type (%)
Moist montane forest Croton megalocarpus 1 70
n = 37 Croton macrostachyus 2 49
Species = 85 Commiphora eminii 3 41
S1 = 42 Prunus africana 3 41
Bridelia micrantha 5 27
Clerodendrum johnstonii 6 22
Cordia africana 7 19
Erythrina abyssinica 7 19
Vitex keniensis 7 19
Vangueria infausta 10 16
Lowland Acacia- Acacia tortilis 1 64
Commiphora
n = 25 Terminalia brownii 2 60
Species = 102 Melia volkensii 3 52
S1 = 49 Albizia anthelmintica 4 40
Acacia senegal 5 36
Acacia ataxacantha 6 32
Berchemia discolor 6 32
Acacia mellifera 8 28
Combretum aculeatum 8 28
Senna singueana 8 28
Evergreen bushland Croton megalocarpus 1 63
n = 16 Euclea divinorum 2 44
Species = 52 Ipomoea kituiensis 2 44
S1 = 26 Acacia drepanolobium 4 38
Plectranthus barbatus 4 38
Acacia xanthophloea 6 31

37. Selection of species for
agroecosystem diversification
• Select frequent species? Promote underutilized species?
Balance with exotic species?
• Timber, for example
– All confirmed species?
– Faster growing primary species with relatively high current
frequencies?
• Juniperus procera (49 and 27% of quadrats in dry forests)
• Vitex keniensis (19 and 18% of quadrats in moist forests)
– Faster growing primary species with low current frequencies?
• Hagenia abyssinica (1 quadrat), Zanthoxylum gillettii (none),
Podocarpus latifolius (none)
– Slower growing primary species?
• Olea europaea (22%), Ocotea usambarensis (1 quadrat),
Cassipourea malosana (2 quadrats), Podocarpus falcatus (none)

38. Limitations of vegetation maps to
map species distribution
• Changes in climatic or soil conditions from those
associated with the map
– Need for successional processes (pioneer, climax)
– Ecosystem restoration: first abiotic, then biotic filters?
– Changes in ecological/dispersal/habitat pools? (landuse, climate
change, invasive species)
• Mapped vegetation types are often mosaics with some
small vegetation types that differ from the main type
• Vegetation types have ecotones where each species
reaches another environmental limit (fuzzy boundaries
between vegetation types), whereas maps show hard
boundaries (indicate ecotone width by LDA?)
• Species consist of different populations (provenances)
that differ in adaptation to local conditions (precautionary
principle!)

39. Seed sources of Calliandra calothyrsus identified during seed source survey (2004)
Good seed sources 57
56
55
54
53
52
51
50
49
1 47 48
46
2
3
44
4 45
31
32
5 30
33 34 35
6 29
7 11 28
27 36 43 37
89
9 22 23 25 41
12 26 39
13
21 24 38
15
14 17
16 40 42
Poor seed sources 18 20
19

40. Correspondence to other
vegetation classification schemes
White. 1983.
1:5,000,000
42
54
19a 45
11a
4 65
4
42
19a Good correspondence for high mountain
45 19a
vegetation(65), montane forest (19a),
11a 45 evergreen and semi-evergreen bushland (45),
45 moist Combretum savanna (11a), lowland
42 42 Acacia bushland (42) and semi-evergreen
thickets (45)

41. Correspondence to other
vegetation classification schemes
Olson et al. 42
2001. 54
19a 45
1:5,000,000 11a
4 65
From White 4
42
19a
AT0711 45 19a
AT1313 11a 45
AT0108 AT1005 45
AT0721 42 42
AT0711
AT0108 What happened with evergreen and
AT0108
semi-evergreen bushland, semi-evergreen
thickets and in the western part of the map?
AT0711
AT0716
AT0108
Boundary between lowland Acacia types?

42. Conclusions
• Bad news: good models and detailed maps for species
distribution or suitability require good presence-only or
presence-absence data, and detailed input maps for
large range of explanatory variables, whereas neither
are commonly available for most components of
biodiversity (including tree populations!)
• Good news: potential natural vegetation maps can
provide a reasonable summary of climate and the
potential distribution of indigenous tree species, they are
available for most places on earth and information is
available on their species assemblages
• Best news: we already compiled information for a couple
of hundred species for a detailed map for central and
western Kenya + confirmed some of climatic/floristic
information + have information for their uses for many
• Way forward: combine existing potential natural
vegetation maps with more extensive set of presence-
data and GIS layers to build better species suitability
maps

43. A (some) word of thanks
• Meshack
• Sammy, Jonathan, Sally-Anne, Walter
• Trees and markets (Tony)
• Our donors
• Everybody in the audience today

44. Topics for discussion?
• How confident should users
be when using the maps or
we when we advise?
• Further testing of maps
• Expansion of maps to
White/WWF ecoregions,
Eastern Africa, …
• Sharing of information
(printed maps, website,
documentation)
• How to deal with biotic and
abiotic changes