Genetic diversity within and among southern Africanprovenances of Uapaca kirkiana Muell. Arg usingmorphological and AFLP markers

Weston F. Mwase • F. K. Akinnifesi • B. Stedje •

M. B. Kwapata • A. Bjørnstad

Received: 29 April 2008 / Accepted: 27 May 2010� Springer Science+Business Media B.V. 2010

Abstract Domestication of Uapaca kirkiana Muell. Arg is a high priority for improving

rural livelihoods of smallholder farmers in southern Africa. Domestication efforts require

knowledge of adaptive traits and intra-specific variation. Morphological traits and ampli-

fied fragment length polymorphic (AFLP) markers were used to assess genetic variation in

twelve provenances of U. kirkiana collected from southern Africa. Assessment of mor-

phological traits showed significant differences (P \ 0.05) between provenances. Prove-

nances from Zimbabwe and Zambia showed faster growth than those from Malawi (except

Phalombe) and Tanzania. Morphological traits exhibited strong genetic differentiation

between provenances and within provenances. The degree of provenance differentiation of

traits (QST = 0.03–0.139, QST mean = 0.092) was in the same range with that of AFLP

loci (FST mean = 0.089) detected among provenances and within provenances

(0.002 \ FST \ 0.259). The differentiation for some morphological traits could be

attributed to local adaptation and human selection of the U. kirkiana trees at the site of

origin. Mean Nei’s (H) genetic diversity of AFLP showed high diversity within the

provenances (H = 0.181–0.321, H mean = 0.256). An analysis of molecular variance

(AMOVA) revealed higher genetic variation (90.8%) within provenances than among

provenances (9.2%). There was no geographical pattern of variation in growth and mor-

phological traits among the seed sources. Chipata provenance from Zambia was the most

W. F. Mwase (&) � M. B. KwapataDepartment of Forestry and Horticulture, Bunda College of Agriculture,University of Malawi, P.O. Box 219, Lilongwe, Malawie-mail: westmwase@yahoo.co.uk

F. K. AkinnifesiWorld Agroforestry Centre (ICRAF), Southern Africa Regional Programme,Chitedze Agricultural Research Station, P.O. Box 30798, Lilongwe 3, Malawi

B. StedjeNatural History Museum, Botanical Garden, University of Oslo, P.O. Box 1172,Blindern, 0318 Oslo, Norway

A. BjørnstadDepartment of Plant and Environmental Sciences, Norwegian University of Life Sciences,P.O. Box 5003, 1432 As, Norway

123

New ForestsDOI 10.1007/s11056-010-9206-z

diverse while Mapanzure from Zimbabwe was the least diverse, though it was superior in

height and earliest in fruiting. The pattern of genetic diversity indicates low selection in

some areas and high gene flow which would be counteracting it. Therefore regional and

country collections and conservation strategies should consider differences by focussing on

the main range of the species by paying particular attention to unique populations within

countries.

Keywords AFLP � Conservation � Domestication � Genetic diversity � Provenance �Uapaca kirkiana � UPGMA

Introduction

Uapaca kirkiana Muell. Arg (family Euphorbiaceae) also known as African wild loquat is

a dioecious tree species indigenous to the miombo woodlands of eastern, central and

southern Africa (Ngulube et al. 1995). The tree can grow in the range of 11–13 m with a

juvenile phase of 9–10 years for planting materials derived from sexual propagation while

vegetatively propagated materials can take 2–4 years to fruit (Mhango 2000; Akinnifesi

et al. 2006). The seed is dispersed by humans, birds, bats, monkeys and rodents (Ngulube

et al. 1995). Several studies have reported the utilization of U. kirkiana fresh and processed

fruits as important source of nutrients and income to local communities (Saka et al. 2008;

Ham et al. 2008). The fruit pulp is mixed with maize or millet meal and the mixture is

cooked into porridge. The ripe fruit pulp, broken up and stored in water, is sometimes left

to ferment, making a sweet wine (Mashingaidze et al. 1991).

A regional-wide survey undertaken to determine needs and preference of farmers and

various users in southern Africa identified Uapaca kirkiana as a priority indigenous fruit

tree for utilization, conservation and domestication (Maghembe et al. 1998; Akinnifesi

et al. 2004a). Efforts are in progress to domesticate and commercialise U. kirkiana in

southern Africa forming part of a global initiative to promote indigenous fruit trees in

agroforestry for community livelihood benefits (Akinnifesi et al. 2006; Leakey et al. 2004,

2005). Conservation of genetic diversity is a fundamental goal of conservation biology and

knowledge of the extent and structure of genetic variation in provenances of U. kirkiana is

essential not only for understanding processes of evolution, but also for development of

appropriate and efficient strategies for collection, conservation and domestication of

superior populations.

Several molecular markers are available for studying genetic diversity in plants.

Amplified Fragment Length Polymorphism (AFLP) (Vos et al. 1995) based on the poly-

merase chain reaction (PCR) are spread all over the genomes and are hypervariable. Use of

AFLP markers is advantageous in generation of large number of markers spanning the

whole genome without prior knowledge of the sequence of the genome. Amplified frag-

ment length polymorphism has been used successfully in plant population genetic studies

of tree species (Muluvi et al. 1999; Kremer et al. 2005; Cao et al. 2006). So far, only one

study has been reported on their application in population studies of U. kirkiana (Mwase

et al. 2006b) and another study used random amplified polymorphic DNA (RAPDs) (Agufa

2002). Understanding the morphological and phenological variations among trees, fruits,

seeds and seedlings (Ngulube et al. 1997; Mwase et al. 2006a) from populations derived

from different geographical areas is central to the study of genetic diversity.

In order to detect genetically differentiated lineages that may impact on domestication

and tree improvement programmes of U. kirkiana, combining both morphological and

New Forests

123

genetic criteria parameters is crucial for measuring genetic diversity. The present study is

part of a wider project, which seeks to explore opportunities for the selection, domesti-

cation and cultivation of U. kirkiana in southern Africa (Akinnifesi et al. 2008). The

objective of this study was to assess the level of genetic variation within and among

U. kirkiana provenances of southern Africa based on molecular and morphological tree

attributes, and to recommend appropriate germplasm collection and conservation

strategies.

Materials and methods

Seed sources

Range-wide collections of U. kirkiana provenances were made from five countries of

southern Africa during November 1995 to January 1996. Geographically, the origin of

seeds can be categorized into three regions namely eastern African region (Tanzania),

south eastern Africa (Malawi and Mozambique), south- central Africa (Zambia and

Zimbabwe). Seeds were randomly collected from 15 to 20 superior trees of twenty-four

provenances and exchanged among Malawi, Tanzania, Zambia and Zimbabwe making

sixteen provenances and twelve of the provenances are part of this study (Table 1). The

four countries represent part of the geographical range of natural distribution of U. kirkianain southern Africa region defined by geographical and political boundaries (Fig. 1). The

twelve provenances were from three categories of elevation from low (600–1,200), med-

ium ([1,200–1,300) and high ([1,300 m).The seedlings were established in multi-location

trials with 12–16 provenances in each of the four countries, i.e. at Chipata in Zambia,

Iringa in Tanzania, Domboshawa in Zimbabwe and Makoka in Malawi (Akinnifesi et al.

2004b, 2006). The experimental design generally employed across countries was ran-

domized block with 20 replications. Each treatment consisted of a line-plot of four-trees

planted at 2 m spacing within row and 4 m between rows. The data reported in this study is

based on the data collected from the provenance established at Makoka Agricultural

Table 1 Source of germplasm of U. kirkiana established at ICRAF–Makoka, Zomba in Malawi

Code Provenance Countryof origin

Latitude (S) Longitude (E) Elevationcategory (m)

Rainfall(mm)

1 Phalombe Malawi 16�090 34�290 1,260 (medium) 1,000

2 Chimaliro Malawi 12�150 33�500 1,338 (medium) 1,200

3 Litende Malawi 11�490 34�100 1,120 (low) 1,500

4 Chipata Zambia 13�400 32�400 1,050 (low) 980

5 Choma Zambia 16�510 27�040 1,200 (medium) 800

6 Serenje Zambia 13�030 30�370 1,559 (high) 1,200

7 Iringa Tanzania 7�500 35�460 1,540 (high) 1,100

8 Mbeya Tanzania 9�450 33�300 [2,000 (high) 1,500

9 Mpwapwa Tanzania 6�050 35�460 1,330 (medium) 550

10 Nyamukwarara Zimbabwe 18�400 32�550 1,800 (high) 1,450

11 Mapanzure Zimbabwe 20�200 31�000 1,100 (low) 650

12 Murelwa Zimbabwe 17�400 31�500 1,470 (high) 800

New Forests

123

Research Station in southern Malawi (15� 300 S and 35� 150 E; altitude 1,029 m above sea

level). The rainfall is unimodal, with most of the rain occurring from November to April.

The total annual rainfall ranges from 560 to 1,200 mm, with a 30-year mean of 1,024 mm.

The soils at the site are classified as Ferric Lixisol (FAO/UNESCO) comprising 46% sand,

46% clay and 8% silt. The clay content in the site increases with soil depth, but major

chemical characteristics are relatively constant to [1 m depth (Akinnifesi et al. 2008).

Measurements of growth and morphological traits

Tree height, diameter at breast height and root collar diameter were measured every year

from 1998 to 2006. Height was measured to the nearest centimetre using a telescopic

measuring pole and diameter to the nearest 0.1 cm using callipers while stem straightness

was scored as described by Cundall et al. (2003). In addition each tree was scored

Fig. 1 Map of southern African countries showing location of twelve provenances as sources of germplasmplanted at ICRAF-Makoka, Zomba in Malawi

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subjectively for morphological traits: branch angle; length of primary branches, crown

depth and fruiting. Details of the scoring procedures are provided in Table 2.

Plant material and DNA extraction

A total of 96 individual U. kirkiana trees representing twelve provenances were used for

leaf sampling at Makoka Agricultural Research Station. Young leaves about 500 mg were

harvested and preserved in silica gel in 50 ml tubes. Total genomic DNA extraction

followed the protocol of Hodgetts et al. (2001) and Paterson et al. (1993), with minor

modifications (Mwase et al. 2006b). DNA quality was checked by ethidium bromide

staining on a 1% agarose gel and concentration was estimated by visual assessment relative

to 1 kb DNA (New England Biolabs) ladder of different known concentrations.

Amplified fragment length polymorphic marker assays

The AFLP analysis was performed as described by Vos et al. (1995), but with minor

modifications (Mwase et al. 2006b). From an initial 64 EcoRI and 8 MseI primer pairs that

were screened the following six primer pairs were selected based on clarity and repro-

ducibility of bands: E-ACA/M-CAA, E40?A/M-CTC, E41?A/M-CTA, E-ACC/M-CTT,

Table 2 List of growth and morphological traits of Uapaca kirkiana and their description

Trait Unit/range Explanation

Quantitative traits

Total height cm Measured from root collar to tip

Bole height cm Measured from the root collar to first livingbranch of the tree crown

Diameter at breast height cm Measured at 1.3 m above ground

Root collar diameter cm Measured at 3 cm above the soil surface

Bark thickness cm Measured using bark gauge at 3 cm above soil surface

Crown depth cm Measured from starting point of branches to stem tip

Branch length cm Measured from stem to branch tip for primary branches

Branching habit

Branch angle 1–2 1 = upright, \60�; 2 = horizontal [60�Branchlet length cm Measured from stem to branch tip for two randomly

selected branches per whorl

Qualitative traits

Stem straightness 1–5 1 = not vertical [2 bends

2 = roughly vertical [2 bends

3 = roughly vertical, 1–2 bends

4 = roughly vertical and straight

5 = completely vertical and straight

Survival Percent Based on 4 tree -row plot

Reproduction

Fruiting 1–2 1 = yes presence of fruits

2 = no: not fruiting

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E33?C/M-CAA and E-AAG/M-CTA. AFLP products were separated on a 6% (w/v)

denaturing polyacrylimide gel and visualised with silver nitrate. The gels were rinsed in

ultra pure water three times and dried at room temperature in fume hood for seven hours.

AFLP fragments were scored as present (1) or absent (0) for each primer pair between 50

and 500 bp and variations in band length were recorded as polymorphism.

Statistical analysis

Analysis of variance for morphological traits was performed across provenances and

separately within each country of origin using the general linear model in MINITAB 14.0.

The morphological traits were compared with AFLP loci through comparison of FST and

QST values after partitioning variance components of ANOVA to obtain QST = rbp2 /

2rwp2 ?rbp

2 where rbp2 is the genotypic variance between provenance and rwp

2 is the geno-

typic variance within provenance (McKay and Latta 2002). It was assumed that variance

between and within provenances is mainly due to additive effects. When QST and FST are

equal, genetic drift is among the main cause of differentiation, while when

QST [ or \ than FST, then selection is acting on the morphological traits. Polymorphism is

the primary source for variation of morphological appearance of plants, the most frequently

used index of polymorphism is gene diversity (H) which is the probability that two alleles

taken at random in a population are different and is calculated with H = 1 -P

pi2 where

pi is the frequency of the ith alllele of the locus. Genetic diversity is a fundamental

component of biodiversity occurring at three fundamental levels of genetic diversity

namely: genetic variation within individuals (heterozygosity), genetic variation among

individuals within a population (HS) and genetic differentiation which is the difference in

the level of polymorphism between the different levels calculated as GST = 1 - (HS/HT).

The standardized mean values of the morphological traits were used to perform cluster

analysis using NTSYS 2.1 (Rohlf 2000) and a dendrogram was constructed using the

unweighted pair group method of arithmetic average (UPGMA). Genetic distances

between provenances were calculated with the squared Euclidean distance (Sneath and

Sokal 1973). It was assumed that the populations were in Hardy–Weinberg equilibrium as

Uapaca kirkiana is a dioecious plant and it is predominantly out-crossing. To estimate

population genetic diversity, the percentage of polymorphic sites (PPL) and Nei’s (1973)

gene diversity (H) were obtained using programme Arlequin 2.0 (Schneider et al. 2000),

average difference between all genotypes in the population (Tajima 1993) were also cal-

culated. Hierarchical structuring of genetic variation within and among provenances was

determined by an analysis of molecular variance (AMOVA) (Excoffier et al. 1992). A

matrix of corrected average pairwise differences between all pairs of provenances gener-

ated by Arlequin was used for constructing dendrograms using UPGMA in NTSYS-pc 2.1

(Rohlf 2000). Simple matching coefficients of similarity (Sneath and Sokal 1973) were

calculated for all pair wise comparisons among provenances. Matrices of Euclidean dis-

similarity coefficients based on morphological and AFLP data sets were tested for corre-

lation using the Mantel test. A matrix of geographical distances among provenances was

obtained (http://www.jan.ucc.nau.edu/-cvm/latlongdist.html) and compared with the cor-

responding simple matching similarity coefficients to investigate possible association

between geographical and genetic distance (MXCOMP in Mantel test in NTSYS). Data

from the AFLP matrix and morphological traits were subjected to principal component

analysis (PCA) (Esbensen 2007) in Unscrambler 9.7 to investigate further relationships

among provenances.

New Forests

123

Results

Morphological traits of provenances

The mean absolute values of the growth and morphological characters used in the char-

acterization are presented in Table 3. Differences within the southern Africa region were

highly significant (P \ 0.001) for diameter at breast height (dbh) and significant

(P B 0.05) for total height, bark thickness, branch length, crown depth and stem

straightness. Provenance differences within countries were not significantly different for

dbh, bole height and root collar diameter. There were no significant differences (P C 0.05)

between the provenances for the traits crown spread, leaf length and breadth, fruiting

and plant survival. The QST values for each morphological trait followed similar trends and

ranged from 0.029 to 0.139 and values were higher than 0.060 except for stem survival and

bole straightness.

There were significant differences (P B 0.05) in plant height, with provenances from

Zimbabwe- Murelwa, Mapanzure and Nyamukwalala being the tallest followed by Choma

from Zambia while Chimaliro from Malawi and Serenje from Zambia were the shortest

(Table 4). Overall, Serenje provenance performed poorly on most traits especially height,

root collar diameter, bark thickness, crown depth and branch length.

Genetic diversity and differentiation

The average genetic differentiation (FST) for the provenances was 0.0922 with individual

population differentiation ranging from 0.002 to 0.259. The six primer combinations

generated a total of 450 loci out of which 90 were polymorphic representing 20% poly-

morphism. The percentage polymorphic loci scored per provenance ranged from 38.9 to

77.7% with an average of 59.4% (Table 5). Nei’s measure of gene diversity (H) showed a

Table 3 Growth and morphological traits of Uapaca kirkiana showing means and QST values

Trait Region Countries withinregion

Provenance withincountry

QST

Total height (cm) 367.00 ± 8.58* 322.26 ± 9. 380* 348.6 ± 16.2*** 0.115

Bole height (cm) 79.66 ± 3.59* 79.66 ± 3.59*** 89.93 ± 6.13ns 0.029

Dbh (cm) 5.38 ± 0.097*** 5.024 ± 0.152*** 5.157 ± 0.238ns 0.139

Root collar diameter (cm) 8.64 ± 0.133ns 6.75 ± 0.210*** 8.057 ± 0.336ns 0.105

Bark thickness (cm) 0.89 ± 0.023* 0.7850 ± 0.037* 0.807 ± 0.0376ns 0.060

Crown depth (cm) 2.65 ± 0.061* 2.65 ± 0.126ns 2.657 ± 0.126ns 0.103

Branch length (cm) 53.73 ± 1.38* 54.43 ± 2.13* 56.45 ± 1.83ns 0.12

Branch angle (degrees) 51.40 ± 0.902ns 55.13 ± 2.30ns 44.93 ± 4.39ns ns

Leaf length (cm) 13.763 ± 0.39ns 13.11 ± 0.568ns 13.85 ± 1.11ns ns

Leaf breadth (cm) 5.86 ± 0.262ns 4.80 ± 0.312ns 5.04 ± 0.57ns ns

Height crown ratio (m) 1.36 ± 0.062* 1.30 ± 0.025ns 1.3125 ± 0.0304ns 0.12

Fruiting (1;0) 1.97 ± 0.012ns 0.075 ± 0.042ns 0.0750 ± 0.0422ns ns

Stem survival (0;1) 2.275 ± 0.085ns 2.40 ± 0.195ns 2.475 ± 0.199ns 0.03

Stem straightness (0–5) 3.39 ± 0.232* 2.27 ± 0.103ns 3.395 ± 0.124ns 0.10

*, *** and ns indicate significance at P \ 0.05, P \ 0.001 and not significantly different at P \ 0.05,respectively

New Forests

123

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New Forests

123

wide range of values from H = 0.181 to H = 0.322 with Mapanzure from Zimbabwe

being least diverse while Chipata from Zambia was the most diverse. Analysis of

molecular variance (AMOVA) (Excoffier et al. 1992) revealed that 90.8% of the genetic

variation is among individuals within provenances. Although variation among provenances

is also highly significant (P \ 0.001), this contributed only 7.7% of the total molecular

variance (Table 6). Partitioning of the overall variance into two hierarchical levels using

AMOVA revealed that differences between countries and altitudes accounted for only 1.6

and 1.0%, respectively. A random permutation indicated that the proportions of variance

attributed to countries and provenances were significant (P = 0.0381, P = 0.000,

Table 5 Genetic variation in twelve provenances of U. kirkiana based on AFLP data

Provenance PPL Average difference Nei’s gene diversity (H)

Phalombe 58.8 22.42 0.249 ± 0.140

Chimaliro 58.8 22.71 0.252 ± 0.141

Litende 53.3 20.03 0.247 ± 0.139

Chipata 77.7 28.92 0.321 ± 0.179

Choma 74.4 26.14 0.290 ± 0.162

Serenje 47.8 18.00 0.222 ± 0.125

Mpwapwa 52.2 18.57 0.235 ± 0.133

Mbeya Kyela 56.7 23.50 0.261 ± 0.146

Iringa 61.0 22.89 0.254 ± 0.143

Nyamukwarara 65.6 23.89 0.277 ± 0.156

Murelwa 67.8 25.17 0.280 ± 0.156

Mapanzure 38.9 15.60 0.181 ± 0.103

PPL percentage polymorphic loci; the average difference is mean number of pair wise differences betweenindividuals in the provenances

Table 6 AMOVA for 96 individuals of U. kirkiana from twelve provenances in southern Africa using 90AFLP markers

Source of variation d.f. SS MS Variancecomponent

Percentvariation

FST P value

Among countries 3 73.271 24.42 0.2029 1.58 0.092 \0.038

Among provenances withincountries

8 156.417 19.55 0.983 7.65 \0.000

Within provenances across4 countries

84 981.250 11.68 11.681 90.78 \0.000

Among 3 altitude groups 2 48.352 24.18 0.129 1.00 0.090 [0.107

Among provenances withinaltitude groups

9 181.335 20.15 1.058 8.22 \0.000

Within provenances across3 altitude groups

84 981.250 11.68 11.681 90.78 \0.000

Among provenances acrosscountries

11 229.688 20.880 1.149 8.96 0.089 \0.000

Within provenances acrosscountries

84 981.250 11.681 11.681 91.04 \0.000

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respectively), while the variance attributed to altitude was not significant (P = 0.107).

Overall, levels of genetic diversity within provenances did not vary greatly.

Cluster analyses

A dendrogram generated from standardized morphological data suggested three main

clusters with a mean genetic dissimilarity of 0.33 (Fig. 2). The first cluster contained six

populations collected from Malawi (Phalombe, Chimaliro) Zambia (Chipata, Serenje) and

Tanzania (Mbeyakyela and Mpwapwa) while the second cluster has provenances from

Malawi (Litende), Zambia (Choma), Tanzania (Iringa) and Zimbabwe (Nyamukwalala).

Litende provenance from Malawi is genetically closer to Choma from Zambia and Iringa

from Tanzania, physically more than 800 km away, than the provenance of Chimaliro in

Malawi, physically about 150 km from the sampled Litende site.

Using AFLP data, UPGMA separated the twelve provenances into five clusters that did

not consistently reflect their geographic origin (Fig. 3). The main cluster contains seven

provenances from Phalombe, Chimaliro and Litende (Malawi), Chipata and Serenje

(Zambia), and Mbeyakyela and Iringa (Tanzania). The provenance Mpwapwa from Tan-

zanian clusters with Nyamukwalala from Zimbabwe in the second cluster whilst the third,

fourth and fifth clusters consist of a single provenance each from Zambia and Zimbabwe.

The provenance Mapanzure with the lowest genetic diversity is clearly separated from the

rest of the provenances. In general, the topology of Fig. 3 showed some similarity to that

provided by morphological traits, however, Mantel test show that the correlation between

the two dissimilarity matrices was not significant (r = 0.52, P = 0.09). Moreover, the

Mantel test revealed no significant correlations between AFLP based differentiation and

geographic distance between pairs of populations (r = 0.26, P = 0.558).

Fig. 2 Dendrogram of twelve southern African U. kirkiana provenances derived from UPGMA fromdissimilarity matrix of morphological data

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Principal component analysis

There was considerable overlapping between individuals from different provenances and

countries as discerned from the principal component analysis performed on the AFLP

matrix. Three clusters were observed (Fig. 4) and the first two principal components

accounted for only 22% of the variation, corresponding to 16% for PC1 and 6% for PC2.

Principal component 2 separated Mapanzure from the rest of the populations. The results

clearly distinguished Mapanzure from the rest of the provenances and seem to be

Fig. 4 PCA plot of twelve provenances of U. kirkiana based on AFLP polymorphic markers

Fig. 3 Dendrogram of twelve provenances using 90 polymorphic AFLP markers based on UPGMA ofcorrected average pairwise differences

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significantly distinct from others while most provenances from Malawi, Tanzania and

Zambia form one group cluster I. Inspection of the loading plots showed that certain alleles

were missing in Mapanzure, however, it also had two markers that distinguished it from the

rest of the provenances. Most of the provenances seem to cluster independently from their

geographical origin. This well exemplified in the case of Nyamukwalala, Chimaliro and

Iringa provenances that are distantly located exhibited close PCA clustering distribution.

The biplot of PCA (figure not shown) obtained with the two marker sets showed mor-

phological traits specifically total height, diameter at breast height, bark thickness and

crown depth loading into the first two principal components and responsible for discrim-

inating some populations by their geographic origin.

Discussion

The geographic source of germplasm for domestication is an important consideration based

on the degree of local adaptation, cost and availability of planting material from different

sites. The variation among populations in the provenance trial might be attributed to genetic

differences caused by the adaptation of the different populations to different environment in

their local sites of origin. The pattern of genetic variation along a geographical distribution

is confounded by specific local environmental conditions. Serenje from Zambia had inferior

traits at the test site, this could be attributed to differences in environmental conditions with

the site of collection; however, it was also one of the poor performers in most traits at a

provenance trial in Chipata (Akinnifesi et al. 2004b) suggesting that it is an inferior

provenance. Apparently, apart from Chimaliro from Malawi, provenances collected from

Zimbabwe (Mapanzure and Murelwa), Zambia (Choma), Tanzania (Iringa) and Malawi

(Phalombe) have good adaptive growth traits at the test site in Malawi. Akinnifesi et al.

(2004b) reported that provenances are more adapted to climatic conditions at their origin,

but the pattern and degree of local adaptation varies among species. In this trial, provenance

ranking in terms of tree height and diameter was not always consistent with results con-

ducted in Zambia where Chipata and Choma provenances had greatest growth (Akinnifesi

et al. 2004b). The good performance of these provenances could be attributed to similarity

of the climatic factors, especially rainfall and elevation between the source of the seed and

test site. The lack of consistency in the results at the two sites indicates the likely presence of

significant provenance and environment interactions.

Minor differences were observed between FST and the range of QST values for some

morphological traits. The morphological traits QST mean = 0.092 was not significantly

different from the AFLP FST mean = 0.089. There were some inconsistent patterns across

provenances but in all traits a trend of higher QST values were found for tree height,

diameter at breast height and branch length suggesting low differential selection for traits

which may be attributed to adaptation at the site of origin. The utility of the AFLP markers

should be considered with caution due to the small sample size of 8 individuals per

provenance which may make it difficult to obtain accurate estimates of allele frequencies

and polymorphism which might result in underestimating the percentage polymorphic loci.

However, studies on similar tree species by Mwase et al. (2006b) used a sample size of 12

individuals per provenance and had mean FST value of 0.079 for the AFLP marker.

Significant levels of variation and moderate levels of differentiation have been reported in

the same species using AFLPs for natural populations collected from Malawi (Mwase et al.

2006b) where AFLP-based diversity (HS) ranged from 0.223 to 0.322 with a mean of 0.27.

Similar mean levels of diversity were found in U. kirkiana after applying RAPD DNA

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markers (Agufa 2002). In this study the mean diversity (HS) of 0.256, the AFLP-based

estimates vary to overall values obtained in studies where RAPDs were used (H range of

0.154–0.250, mean H = 0.192) (Agufa 2002) suggesting that AFLP and RAPDs can

produce different results. The levels of diversity are within the range reported for forest

tree species of similar life history and reproductive ecology such as Sclerocarya birrea,Prunus africana and Vitex fischeri (Muok et al. 2007; Kadu et al. 2006; Lengkeek et al.

2006). The low genetic diversity in Mapanzure could be attributed to genetic drift because

of small population size and forest fragmentation. Like most tropical trees U. kirkiana is

obligatory out crossing and high intrapopulation variation revealed in the AMOVA con-

firms the general observation that differentiation is expected to be very restricted in long-

lived woody, outcrossed and late successional species (Hamrick et al. 1992; Loveless and

Hamrick 1984).

The use of morphological traits is not always the best way to evaluate genetic distance

since the degree of divergence between genotypes at the phenotypic level is not necessarily

correlated with a similar degree of genetic difference (Hamrick and Loveless 1989). The

lack of correlation between morphological and molecular markers shows that most of the

growth and morphological traits are influenced by several genes. The bulk of genetic

diversity is contained within provenances but there is still appreciable differentiation

among provenances. According to Wright (1978) FST values between 0.05 and 0.15

indicate moderate genetic differentiation (Hartl and Clark 1997). The mean FST value of

the provenances was 0.089 which is generally considered to be below the threshold where

genetic drift has a significant impact on the population and level of differentiation could be

mainly due to gene flow. A range of insects possible pollinators of U. kirkiana include bees

(Apis mellifera) and beetles (Dothera bennigseni and Chelomenes lunata) which migrate

only short distance (Ngulube et al. 1998). Monkeys and gorillas disperse fruits through

dung to distant places farther than 20 km contributing high-quality dispersal to favourable

sites over varied and changing environments (Voysey et al.1999). Furthermore, human

transportation of fresh fruits across large distances between forests and towns improves

germplasm exchange through seed dispersal acting as a homogenization factor between

populations (Mwase et al. 2006b). Provenances from Zimbabwe showed higher levels of

differentiation than provenances from Malawi, Zambia and Tanzania. This implies that

provenances of U. kirkiana cannot be considered a single panmictic unit. This may explain

the limited genetic differentiation among provenances within countries although geo-

graphical distance between provenances varies from 95 to 480 km. Although there were no

significant correlations between either morphological or AFLP-based differentiation with

geographical distance between pairs of provenances, geographically close provenances

were more similar than provenances from distant locations. Different levels of human

impacts from origin site of collection might have effects on genetic parameters measured

and could explain the discrepancy between genetic and geographic distances.

The provenance groupings accomplished through UPGMA were inconsistent with the

geographical distribution of the studied provenances. Such results are consistent with the

F-statistics for these areas, indicating that differences among countries have small impli-

cations in the distribution of genetic variation. Comparison of genetic diversity values

between morphological traits and AFLP markers showed that the former ranged from

0.001 to 0.490, while the later from 0.002 to 0.259 (data not shown). The correlations

between the two genetic distances were low and non significant, indicating discrepancy

between the two methods. Several comparisons between molecular and morphological

studies also indicated that these two methods were different and highly variable

(Roldan-Ruiz et al. 2001). Data from common gardens like this one is considered to

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represent genetic variation between individuals, populations and regions. The traits

measured in this study represent a much larger proportion of the tree genome than do the

AFLP loci. While molecular markers show expression of the genotype, morphological

markers are very useful in studying adaptive traits. While acknowledging the importance of

using local provenance for ecological adaptation our studies have shown that there is weak

evidence that variation in average plant height among populations is associated with

environmental gradients. High growth rates observed for provenances from Zambia and

Zimbabwe suggests existence of high within provenance variation which allows the species

to adapt to different environments without major genetic alteration.

The principal component analysis (PCA) shows that the twelve populations segregated

into clusters consistent with results from morphological and AFLP derived dendrograms.

The low percentage (22%) of the variation explained by the first two components in the

PCA could be attributed to high extent of genetic variability between individuals of each

population relative to the low variation among the provenances. Although there were three

clusters in the PCA only the cluster comprising of individuals from Mapanzure was distinct

and this agrees with clusters obtained from UPGMA. The PCA also supports the

dendrograms produced from morphological data, although there are some differences in

the pattern of clustering. This has an important implication suggesting that it is difficult to

predict the genetic diversity of populations based on morphological differences only. The

PCA showed that Mapanzure was the most distinct and Nei’s gene diversity showed least

genetically diverse; however, adaptive growth traits ranked Mapanzure as one of the best

provenances and it was the only population that had started fruiting after 10 years of

growth. Makoka appears to be ideal for growth of Mapanzure provenance considering that

both fall in the same altitude category and receive low rainfall amount. Strategies for

prioritizing conservation of species diversity should consider the level of diversity as well

as the existing threat of populations. The conservation in the different countries must

consider the inevitable anthropogenic impacts of cultivation of forest lands on the distri-

bution of genetic variation of the species. Our results indicate that populations from

Chipata, Choma and Murelwa harbour significant amount of diversity to warrant priority

for conservation. The identification of moderate genetic variation have important impli-

cations for utilization of the species including the development of strategies for

improvement of economically important traits such as fruit size, sweetness, colour, number

of seeds and growth traits such as time to fruiting.

Conclusion

The analysis of genetic diversity of southern Africa provenances of U. kirkiana will assist

in conserving the diversity of the species. The results show a moderate degree of differ-

entiation between provenances in both molecular and morphological traits. The QST values

were slightly lower than FST values though not significantly different suggesting com-

plementarities in use of results from morphological and molecular markers. Existence of

higher level of variation within and between populations suggests a vast genetic base

available for selection while high variation within provenances suggests that sampling

from a few populations within a country may capture a large proportion of variation;

nevertheless, sampling from a wide range among the countries is still advisable. Although

morphological and growth characterisations are influenced by environment, they can be

used hand in hand with molecular markers for revealing genetic variation. The significant

variation in morphological and growth traits in U. kirkiana is attributed to presence of

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adaptive genetic variation related to micro-environmental factors and selection of locally

preferred individuals suggesting that there is great potential to establish high-diversity seed

orchards. When deciding on the most appropriate domestication and improvement strategy

for U. kirkiana, heritability, vegetative propagation methods and genetic correlations

between growth and desirable fruit traits such as fruit size, time to first fruiting, sweetness

and pulp ratio should be investigated under different environments.

Acknowledgments The research grant was provided by Norwegian Research Council for Higher Edu-cation (NUFU) through Plant Biotechnology Project of University of Malawi. We acknowledge Anne-GuriMarøy and Dr. A. Holefors at the Centre for Plant Growth in Controlled Environment (SKP) for technicalassistance. We are indebted to Thomson Chilanga and Jarret Mhango formerly of ICRAF for fruitfuldiscussions.

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