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Tropical Ecology 55(1): 19-32, 2014 © International Society for Tropical Ecology www.tropecol.com ISSN 0564-3295 Tamarindus indica L. patterns of diversity from the genetic to the niche-species level in East Africa P. NYADOI 1,2 * 2 2 2 3 3 , P. OKORI , J.B.L. OKULLO , J. OBUA , S FLUCH , K. BURG & R. JAMNADASS 1 Conservation Consult and Research Company Uganda Limited, P.O. Box 7412 Kampala, Uganda 2 Makerere University, P.O.BOX 7062 Kampala, Uganda 3 4 Austrian Institute of Technology Department of Environment and Health (formally the Austrian Research Centers GmbH–ARC, Department of Genetics and Bioresources), A-2444 Seibersdorf, Austria World Agroforestry Centre (ICRAF), United Nations Avenue, Gigiri P.O. Box 30677-00100 GPO, Nairobi, Kenya Abstract: For economically important, increasingly threatened species like tamarind is in East Africa, proper knowledge and maintenance of diversity existing within their populations and communities is key to attaining sustainability. The objective of our study was to generate knowledge on patterns of diversity from genetic to niche-species level for tamarind in East Africa. We hypothesized that patterns of diversity at these three levels would be similar, given possible cross-acting homogeneous spatial- temporal evolutionary factors in East Africa. Results obtained from a spatial-temporal homogeneous study of diversity in tamarind from genetic, morphological to niche-tree species levels were synthesized for patterns. A unidirectional pattern across the three levels emerged and we envisage that maintaining this diversity model will help long-term conservation of tamarind and its niche-tree species in East Africa. However, further investigations to establish causative factors for the observed unidirectional diversity pattern will be necessary to elucidate the required management strategies. Resumen: Para especies de importancia económica y cada vez más amenazadas, como lo es el tamarindo en África Oriental, el conocimiento adecuado y el mantenimiento de la diversidad que existe en sus poblaciones y comunidades son clave para alcanzar su sostenibilidad. El objetivo de nuestro estudio fue generar conocimiento sobre los patrones de diversidad desde el nivel genético hasta el de especie-nicho para el tamarindo en África Oriental. Hipotetizamos que los patrones de diversidad en los tres niveles considerados sería similar, en virtud de posibles factores evolutivos espacio-temporales homogéneos y de efectos cruzados en África Oriental. Los resultados obtenidos a partir de un estudio homogéneo espacio-temporal de la diversidad en el tamarindo, abarcando los niveles genético, morfológico y el de especie-nicho de los árboles fueron sintetizados en la búsqueda de patrones. Emergió un patrón unidireccional a través de los tres niveles y nosotros proponemos que el mantenimiento de este modelo de diversidad contribuirá a la conservación a largo plazo del tamarindo y de las especies-nicho de árboles en África Oriental. Sin embargo, hacen falta nuevas investigaciones para establecer los factores causales del patrón unidireccional de diversidad observado que permitan elucidar las estrategias de manejo requeridas. Resumo: Para as espécies economicamente importantes, cada vez mais ameaçadas como é o *Corresponding Author; e-mail: [email protected], [email protected], [email protected] 4 20 TAMARINDUS INDICA DIVERSITY MODELS tamarindo na África oriental, o conhecimento adequado e a manutenção da diversidade existente nas suas populações e comunidades é essencial para atingir a sustentabilidade. O objetivo do nosso estudo foi o de gerar conhecimento sobre os padrões de diversidadeindo do nível genética ao de nicho das espécies para o tamarindo na África Oriental. Trabalhámos com a hipótese de que os padrões de diversidade destes três níveis seria semelhante, dadaas possíveis acções cruzadas homogéneas dos factores evolutivos no espaço e tempo na África Oriental. Os resultados obtidos a partir de um estudo espacial-temporal homogéneo da diversidade no tamarindo,indo da genética, à morfologia e ao níveldo nicho de espécies arbóreas, foram sintetizados por padrões. Emergiuum padrão unidireccional entre os três níveis e prevemos que a manutenção deste modelo de diversidade ajudará, a longo prazo, a conservação do tamarindo e do seu nicho de espécies de árvores na África Oriental. No entanto, outras investigações para estabelecer os factores causais para o padrão unidireccionalde diversidade observadoserão necessárias para elucidar as estratégias de gestão requeridas. Key words: Conservation, diversity models, East Africa, Tamarindus indica. Introduction Species diversity dynamics are a result of historical, ecological and evolutionary factors and these vary spatially and temporally (Barantes & Sandoval 2009). For example, correlations in diversity pattern from genetic to niche-species levels have been reported where such factors are homogeneous (Booth & Grime 2003; Lowe et al. 2005; Ma 2006; Vellend & Geber 2005). Understanding patterns of diversity based on different diversity indices and the causes of observed diversity patterns at different ecological scales help provide knowledge on the needs and strategies for species conservation (Barantes & Sandavol 2009). Unfortunately, few diversity models have been derived based on spatio-temporally homogenous studies, which would help yield knowledge applicable in day-to-day management of diversity for long-term conservation of species. Many of the existing diversity models are mainly drawn from reviews of studies conducted in different regions and times (Frankham et al. 2002; Lowe et al. 2005; Reed & Frankham 2001; Vellend & Geber 2005). The few recent investigations on diversity models based on spatio-temporally homogeneous studies reported correlations in diversity from genetic to community/species level in an experimental setting (Booth & Grime 2003) and in morphological and genetic diversity in Adansonia digitata (Assogbadjo et al. 2006). More spatiotemporally homogenous studies of diversity patterns for the species are necessary to help generate knowledge, establish models being drawn from reviews, and for immediate application in identification of conservation strategies for species. Such investigations are especially needed for economically exploited species whose populations and adaptations need strategic conservation to enable sustainability (Fisher 1930; Ledig 1986; Gebureka 1997; Lowe et al. 2004). In East Africa, Tamarindus indica L. (hereafter, tamarind) is an economically important species. However, the economic benefit from tamarind to dependent communities is threatened as the species’ natural populations face depletion due to over-exploitation, habitat loss, and absence of systematic conservation strategies (FAO 2004; Jama et al. 2005; Nyadoi et al. 2011). Another study has also shown that the East African population of tamarind is of conservation importance globally as the center of genetic diversity (Nyadoi 2010; Nyadoi et al. 2010b). Thus, tamarind conservation in East Africa is critical regionally for livelihoods of the people dependent on it and also globally for the preservation of important genetic resources. Knowledge of and maintenance of diversity and diversity relationships from genetic to nichespecies level is generally the advanced ideal conservation approach for species of economic importance (Gebureka 1997; Ledig 1986; Margules & Pressey 2000). For tamarind this approach could not yet be adopted as existing knowledge on its diversity and diversity relationships from genetic to niche species level were scant. In East Africa, and even globally, diversity studies done on tamarind have been focused on one or two diver- NYADOI et al. Fig. 1. Map of East Africa showing sites from which tamarind were studied for diversity patterns. 21 22 TAMARINDUS INDICA DIVERSITY MODELS sity levels and not on all the three levels of diversity at once (El-Sidig et al. 2006; Nyadoi et al. 2011; Pushpakumara et al. 2007, for example). Only recently, a study was done on diversity in tamarind from genetic to niche species level (Nyadoi 2010). However, synthesis and findings on diversity models from the study have not yet been published for wider applications. This paper synthesizes and presents the knowledge generated on tamarind diversity patterns from genetic to niche-tree-species level from the results of the 2007 - 2008 East African population study, for wider application for conservation management in growing areas. Materials and methods This paper is based on synthesis of data obtained on tamarind morphological (height, crown sectional area, diameter at breast height), genetic (mitochondria and chloroplast haplotypes) and niche-tree-species diversity studies conducted in East Africa (Uganda, Tanzania and Kenya) in 2007 (Nyadoi et al. 2009a, b, 2010a, b). Study sites and sampling units within selected study sites Study sites/environments (Fig. 1) were selected based on the diversity of factors affecting species evolution (Hartl & Clark 1997; Jeffrey et al. 2004; Margules & Pressey 2000; Young et al. 2000). We included vegetation types (White 1983), climate (temperature and rainfall zones), Western and Eastern Rift Valley Zones (Fig. 1); within these, tamarind was sampled from farms (on-farm), and from woodlands and riverbanks. Within a habitat, the first tamarind individual was sampled randomly on encounter and subsequent individuals were sampled at systematic intervals ≥ 500 m. From each sampled tamarind the following data or materials were collected: leaves for DNA characterisation, tree height, diameter at breast height and crown radii measured using standard methods. All other tree species found within 18 m radius with the tamarind stem as the centre were then enumerated. The geographic position coordinates of the tamarind were recorded using a global positioning system receiver (GPS). Further, for tamarind trees from on-farm sites, farmers were further interviewed to obtain data on their establishment methods (i.e., whether tamarind was planted or it grew naturally (wild)). Total number of tamarind trees studied from each of the three countries of East Africa is shown (Table 1). In addition to tamarind and its niche-tree species parameters recorded, soils were sampled using standard methods from under the trees studied, and the climatic conditions (rainfall and temperature) of the sites obtained for analysis. Table 1. Number of tamarind trees and seeds sampled from the diverse areas of East Africa, used in the study. Country in East Africa Uganda Tanzania Kenya Total number of tamarind trees studied Number of tamarind trees sampled and Latitudes studied for diversity (in degrees ) patterns from genetic to niche-tree-species levels 61 0-30º North 58 0-30º South 91 0-30º South and 0-30º North 210 Specific study steps, data collection and analysis Step 1. DNA characterisation of sampled tamarind leaves DNA was isolated from all the leaves sampled, using Quiagen protocol of 2006. The DNA was subjected to polymerase chain reaction (PCR) with over 30 different markers, of which, during the screening stage, only five were able to amplify well and reveal polymorphism in tamarind (see Appendix Table 1). Overall, the chloroplast genome showed high level of uniformity with very few unique haplotypes for tamarind and only the mitochondria Cox 11 was able to reveal considerable diversity within the East Africa tamarind populations (Nyadoi 2005). The diversity observed in the chloroplast genome has been omitted in this paper, due to the high level of homogeneity found. Homogeneity in the chloroplast genome for tamarind has been reported before (Pushpakumara et al. 2007). Polymorphism observed in the Cox 11 region was thus used in the current paper. The mitochondrial Cox 11 primers were subjected to restriction digest with ALU 1 (New England Biolabs) to obtain restriction fragment polymorphisms (RFLPs). The RFLPs were separated using 8 % Polyachrylamide gel electrophoresis NYADOI et al. (PAGE) and, silver staining conducted to enable visualisation and image documentation using the UVP image system (ASAR, USA). Haplotypes were identified from the RFLPs (Nyadoi et al. 2010b) and mapped within their populations. Furthermore, based on GPS recorded position coordinates of the tamarind from which haplotypes were obtained, the haplotypes were mapped within their populations using ArcView GIS software (ER1 2002). Step 2. Morphological characterisation of sampled tamarind The choice of height, diameter at breast height (DBH), and tree crown sectional area as morphological response variables was based on the economic importance of these traits to farmers in East Africa. These response variables were chosen, also, because these traits are in part influenced by genotypes and in part by environment. Environmental factors (soil, temperature, altitude, rainfall and vegetation types) known to influence these traits were also captured in the study and their effects on the morphological parameters were examined. The reproductive traits such as flower size, shape, colour, and fruit size, shape, and colour are also known to differ among tamarind populations (Pushpakumara et al. 2007) and are in fact influenced by genotype and environment, much like the height, crown sectional area and DBH investigated in our study. Reproductive traits like flower or fruit characteristics were, however, not included in our study because our data collection period was not in phase with the reproductive phenology of tamarind. For each of the tamarind characterised for haplotypes diversity, the height and crown radii (later used to determine tamarind crown sectional area; CSA) were measured in metres, and DBH was measured in centimetres. The height, crown sectional area and DBH data were then subjected to multivariate analysis of variance (MANOVA) in relation to environment (vegetation types, soils, temperature, rainfall, altitude) and haplotypes of populations using SAS (Nyadoi 2010; Nyadoi et al. 2010a). Step 3. On-farm tamarind establishment method and niches For all tamarind sampled on-farm and studied in steps 1 and 2 above, farmer responses on their establishment method (whether they were planted or they grew naturally/wild) were used to generate numbers of planted and wild tamarind on-farm. The means of planted and wild tamarind on-farm 23 were then analysed for variance to determine domestication level (Nyadoi et al. 2009a). Step 4. Tamarind-niche-tree species diversity For each of the tamarind sampled from all the different habitats and included in study steps, 1, 2 and 3 above, tree species found in their niche, i.e., in an 18 m radius plot with tamarind at the centre (niche definition in context of this study) were recorded. Some woody non-tree species like bamboo and agricultural crops like bananas in the niche were also included. This was done to enable identification of compatible spatial mixtures including tamarind, which can be promoted for conservation on-farm. Data on tree species presence/ absence from all plots from all habitats studied were then analysed to generate Shannon diversity indices (see Nyadoi et al. 2009b for details). In this study, Shannon-Wiener species diversity index, denoted by H′, defined as a mathematical measure which provides information on species richness, relative abundance, rarity or commonness of different species in a community or sample (Kent & Coker 2000; Shannon 1948) was adopted. Shannon H′ is derived as: s H' = − ∑ j =1 p i ln p i .................................................1 where, H′ is the diversity in a sample of S species, S the number of species in the sample, Pi the relative abundance of ith species or kinds of species measured as = ni/N, where, N is the total number of individuals of all species or kinds of species, ni is the number of individuals of ith species and ln is the natural logarithm. The value of H′ ranges from 0 meaning every species in the sample is the same (no diversity) to 4.6 signifying high species richness and that different species in the sample or community are equally abundant (Magurran 2004). The other diversity index used in this study is Shannon species evenness denoted HE, which measures how equal the numbers of individuals of different species are in a sample or community. Shannon species evenness index HE is given by HE=H′/Hmax= H′/lnS..................................................2 where, HE is Shannon species evenness index, H′ is Shannon species diversity, ln, is the natural log and S, the number of species in the sample or community of the species. The values of HE range from 0 (meaning complete unevenness) to 1 (meaning the different species occur in equal numbers). To assess whether differences observed in the 24 TAMARINDUS INDICA DIVERSITY MODELS Shannon diversity indices were statistically significant, they were analyzed using analysis of variance (ANOVA). Paleontological Statistical Package (Hammer & Harper 2005) was used for the diversity analyses in this study. Paleontological Statistical Package (PAST) was additionally advantageous in that it is able to detect species extinctions within and among niches. In data management and analysis, each tree species recorded in tamarind niche plots was scored using binary approach; presence (1) and absence (0) in all the 187 plots inventoried. Each plot was grouped by its habitat type and country of collection. A table of regional species list and their respective frequencies among all plots per habitat and per country were generated. The binary data was loaded into PAST and the programme used to generate Shannon-Wiener diversity indices; species richness (S), relative abundance (Pi) and diversity (H′, HE,) per habitat type per country. The diversity indices were then comparatively analyzed for variance; (a) among the three different habitats (on-farm, woodland and riverbank) regionally and within a country and (b), among similar habitats across the three different countries (Uganda, Kenya and Tanzania). In these comparisons, generated P values were interpreted to infer level of significance of the observed differences in diversity among the different habitats regionally and within a country and, across the three countries, similar habitats. Synthesis of the results of study steps 1, 2, 3 and 4 The results obtained from study steps 1, 2, 3 and 4 above were then compared. The patterns of variability and/or diversity obtained for the study steps 1, 2 and 4 were examined for similarity/ divergence and in relation to study step 3, and emerging patterns/models of diversity from all are discussed in this paper. Results Patterns of tamarind diversity from genetic to niche-tree-species in East Africa Tamarind morphology varied among vegetation types. The Somali Masaai vegetation type in Kenya had taller trees with larger DBH and wider CSA than trees in Uganda, Tanzania, and Zanzibar and Lamu Islands (Table 2). The patterns in the variation of tamarind morphology were similar to the variability of haplotypes in the populations. That is, tamarind height and DBH were greater within Kenyan habitats, where the number of different haplotypes (4) was also more compared to the Uganda and Tanzania habitats (2 and 3, respectively) (Table 2 and Fig. 2). Diversity pattern for tree species in tamarind niches (Table 3) was also similar to the diversity pattern observed for tamarind morphology and haplotypes. This was based on data from on-farm plots (46 from Uganda, 47 from Kenya and 34 from Tanzania), woodland plots (12 from Uganda, 13 from Tanzania and 22 from Kenya), and riverbank plots (4 from Uganda, 9 from Tanzania and 14 from Kenya), i.e., 187 plots sampled in tamarind niches East Africa wide. A total of 725 individuals composed of 171 different species of 53 families were found in tamarind niches (Table 3, also see Nyadoi et al. 2009a,b for detailed results). Analysis at the regional level revealed an overall high species diversity (H′ = 4.07, Table 3) but low species evenness (HE = 0.34) and lower diversity of families (H′ = 3.37; HE = 0.55). At habitat level regionally, 129 species were found in tamarind niches on-farm (species diversity H′ = 3.86 and HE, 0.36), in woodlands there were 96 species (H′ = 3.94 and HE = 0.53) while the riverbanks had 69 species with H′ = 3.69 and HE = 0.55. Diversity analysis at country level revealed that species richness (S) on-farm in Uganda was 45, in Kenya 69, and 58 in Tanzania (Table 3). Ugandan woodlands had 30 species, Kenya had 51, and Tanzania had 41, while Ugandan riverbanks had 10 species, Kenya had 42, and Tanzania had 30 (Table 3). Analysis of variance based on means of Shannon diversity index, H′, between similar habitats revealed significant differences (P = 0.003) among countries (Kenya, Uganda and Tanzania) on farm with (mean H′) HM =3.37, P = 0.002 for the woodlands with HM = 3.31 and, P = 0.01 for the riverbanks with HM = 3.85. Analysis of variance based on means of Shannon H′ diversity between different habitats (on-farm, woodland, and riverbank) within countries revealed significant differences; P = 0.01 for Uganda with HM being 2.76, in Tanzania P = 0.001 with HM = 3.31 and in Kenya P = 0.001 with HM = 3.46. Analysis of on-farm tamarind establishment methods revealed a higher level of planting in Uganda (65.6 %) and Kenya (60 %) while in Tanzania on-farm populations of tamarind are still largely wild (77 %) (Fig. 3). However, at regional NYADOI et al. 25 Table 2. Tamarind morphological variability in East Africa habitats. Values are mean (s.e.). Tamarind habitats Tamarind height Tamarind diameter at breast height Tamarind crown sectional area Sudanian (Uganda) 11.54 (1.35) 36.67 (34.9)xx 189.59 (29.82) Guineo-Congolia (Uganda) 12.79 (1.59) 139.82 (41.18) 189.52 (35.18) Lake Victoria regional (Uganda) 12.72 (1.88) 103.85 (48.67) 183.84 (41.58) Somalia Maasai (Kenya) Zanzibar Inhambane (Lamu Kenya, Zanzibar, Tanzania) Zambesia (Tanzania) xxsignificantly 14.54 (1.12)xx 229.07 (28.87)xx 4.41 (1.48)xx -10.59 (38.13)xx 11.39 (1.09)x 182.82(28.06)xx 199.56 (24.67) 61.77 (32.57)xx 161.99(23.97) Number of different tamarind mitochondria haplotypes recorded in population 2 4 3 2 different values for tamarind morphology variation in habitats. Table 3. Tamarind-niche-tree species diversity in on-farm, woodland, and riverbank habitats in East Africa. Spatial scale of study Species richness ( S) Number of individuals (i) Shannon H′ diversity index Shannon species evenness HE East Africa wide Overall regional 171 (range 130-148) On-farm regional 725 (725-725) 4.07 (3.81-4.08) 0.34 (0.33-0.41) 129 (92-108) 460 (460-460) 3.86 (3.55-3.85) 0.37 (0.36-0.46) Woodlands regional 96 (65-79) 211(211-211) 3.94 (3.48-3.86) 0.54 (0.47-0.64) Riverbanks regional 69 (44-56) 140 (140-140) 3.64 (3.14-3.59) 0.55 (0.48-0.68) On-farm Uganda 45 (30-40) 146 (146-146) 3.02 (2.60-3.08) 0.46 (0.41-0.59) On-farm Kenya 69 (47-58) 188 (188-188) 3.59 (3.18-3.56) 0.52 (0.48-0.64) On-farm Tanzania 58 (38-48) 128 (128-128) 3.49 (3.01-3.46) 0.57 (0.49-0.70) Country levels Woodlands Uganda 30 (18-26) 58 (58-58) 3.04 (2.46-2.99) 0.69 (0.60-0.83) Woodlands Kenya 51 (32-42) 93 (93-93) 3.47 (2.91-3.39) 0.63(0.54-0.75) Woodland-Tanzania 41(27-35) 82 (82-82) 3.42 (2.91-3.33) 0.75 (0.64-0.84) Riverbanks Uganda 10 (5-9) 12 (12-12) 2.21 (1.35-2.4) 0.91 (0.73-0.96) Riverbanks Kenya 42 (26-35) 78 (78-78) 3.32 (2.77-3.24) 0.66 (0.57-0.79) Riverbank Tanzania 30(17-25) 53 (53-53) 3.02 (2.41-2.96) 0.67 (0.59-0.83) Regional Species families 57 (41-51) 171 (171-171) 3.67 (3.33-3.61) 0.69 (0.64-0.77) Table note; Analysis of variance of Shannon diversity index H′ for tamarind-niche tree species across the three countries for similar habitat revealed significant difference on farm (P = 0.00) with the mean index of diversity HM = 3.37, in the woodland (P = 0.00) with HM = 3.31 and for the riverbanks (P = 0.01) with HM = 2.85. Analysis of variance of Shannon diversity index H for tamarind-niche tree species among the three different habitats (on-far, woodlands and riverbanks) within countries also revealed significant difference; In Kenya (P = 0.001) with the mean index of diversity HM being 3.46, in Tanzania (P = 0.001) with HM = 3.31 and in Uganda (P = 0.01) with the HM = 2.76. In the table, HE is Shannon species evenness, a measure of how equal the numbers of individuals of different species are in a sample or community and is derived as shown earlier (equation 2). 26 TAMARINDUS INDICA DIVERSITY MODELS 1,2,3,4 Somalia Masaai > p<0.05 1, 5 > p<0.05 Guineo–Congolia, Sudanian Lake Victoria, Zambesia 1, 2, 3 Zanzibar Inhambane Fig. 2. Tamarind height, crown sectional area, diameter at breast height variations (R = 59.5 %) with environment (vegetation types) and haplotypes (1, 2, 3, 4 and 5) in East Africa. NYADOI et al. Fig 3. Numbers of individual tamarind trees recorded, classified by establishment methods, across study sites in East Africa. level in East Africa, differences in means of the number of planted and wild tamarind on-farm is not significant (Nyadoi et al. 2009a). Discussion and conclusions Our results reveal similarity in diversity patterns from the population (genetic and morphological) to the community (niche-tree species) level for tamarind, with higher diversity in areas where farmer intervention by way of on-farm planting was also high. Our study is, to the best of our knowledge, the first spatial-temporal attempt to elucidate diversity models from genetic to nichespecies level in tamarind. Interestingly, our findings corroborate diversity patterns reported based on reviews of different non-spatio-temporal and inphase studies of species. Assogbadjo and colleagues (Assogbadjo et al. 2006) for example, found correlations between genetic and morphological (height, number of branches and thickness of capsules of trees) diversity in Adansonia digitata. At community levels in an experimental setting, genetic diversity has been reported to increase with species diversity (Booth & Grime 2003). In evolution it is common knowledge that species diversity patterns are shaped among other factors by, historical factors like dispersal events, geographic isolation, extinction due to climatic and geological events and, ecological factors such as predation and competition (Barantes & Sandoval 2009; Rasingam & Parathasarathy 2009; Shukla 2009). Abundance and/or diversity per species are also influenced by their life history e.g. reproductive rate, intra- and inter-species inter- 27 actions, parasitism and competition (Barantes & Sandoval 2009; Goparaju & Jha 2010). Genetic variation within- and among-populations are also influenced by these same factors. Species lifehistory traits such as reproductive rate and competition, for example, influence their survival, and consequently, their ability to contribute to genetic variation (Hedley et al. 2009; Young et al. 2000). At the global level, combined effects of environmental factors have been implicated in homogeneity of species diversity patterns (Kreft & Jetz 2007). Even among different geographic regions, similarity in evolutionary factors influence species diversity patterns (Vellend & Geber 2005). Even in agricultural and forested landscapes, evidence has shown that regional and localized species diversity dynamics are a result of evolutionary factors acting at such levels (Kaur et al. 2012; Ma 2006; Pant & Samant 2012). Drawing from the above reviews, the unidirectional diversity pattern from genetic to niche-tree-species levels observed in our tamarind study could be attributed to cross acting-shared historical events. In the past there could have been similarity of dispersal, geographical isolation, climatically and geologically driven extinction events. These may have involved the ecology (predation, competition), and life-history strategies (reproductive rate, intra- and inter-species interactions) for tamarind within East Africa as a region. Higher diversity observed in Kenyan habitats than in Uganda and Tanzania may be the result of higher level of human intervention aiding survival and diversity of the species. Taking tamarind alone, the level of on-farm planting in Kenya was similar to that in Uganda but at species diversity level Uganda is the least diverse. This result portrays a culture/value of conservation of trees among Kenyan communities more than among Ugandans. Unlike Uganda, over 60 % of Kenya is dry lands with hasher climatic conditions (Jaetzold & Schmidt 1983). Tree conservation could be an adaptation measure Kenyans embraced for environmental micro-climate amelioration. Whereas Uganda is generally a climatically favourable country, for two decades now, deforestation and forest degradation have remained problems (Amaniga Ruhanga & Manyindo 2010). Deforestation and forest degradation a factor of species depletion in many other regions (Kaur et al. 2012; Pant & Samant 2012 for example) may be the cause of diversity declines in Ugandan habitats despite people planting and retaining on-farm, 28 TAMARINDUS INDICA DIVERSITY MODELS trees of their interest (Nyadoi 2005). Increasing monoculture of Tobacco promoted by British American Tobacco Co. (BAT), other commercial crops and needs for land use (Nyadoi 2010) are among likely factors of deforestation and revealed species loss in Ugandan habitats. In conservation, the ideal goal is to maintain existing spatial and temporal diversity within and among species (Jeffrey et al. 2004; Margules & Pressey 2000). Of conservation value, therefore, our finding of convergent diversity patterns from genetic to niche-species levels for tamarind imply the need for maintenance of diversity at these levels. Our results revealed a similarly higher diversity in tamarind from genetic to niche levels in Kenyan habitats where also, considerable onfarm planting of the species took place. This suggests on-farm planting enhanced diversity meaning that for the diversity sustainability, farmers need to be engaged in design and implementation of tamarind and its niche-tree species conservation strategies. The data we analysed for diversity patterns from genetic, morphological to niche-species levels for tamarind were obtained from the same individuals and at the same time (i.e., the data were spatially and temporally homogeneous). Unidirectional diversity patterns found, therefore, provide new evidence supporting convergent diversity models postulated elsewhere (Booth & Grime 2003; Vellend & Gebber 2005). For tamarind our model is a pioneer and will be valuable in furthering investigations of diversity relationships at different ecological levels. It is clear from our results that, diversity in tamarind and tamarind niche-tree species is higher on-farms. This could be due to a number of factors, perhaps in selection; farmers actively promote diversity in their farming practices. Also, our finding allude to tree species depletion taking place in the wild (forests, riverbanks), need to focus conservation efforts in farm lands and, commencement of restoration measures in the earlier habitats. Nevertheless, detailed study to elucidate underpinning factors to observed higher diversity of tamarind and niche-tree species onfarm is necessary to reveal more insight on important conservation approaches. Finally, for immediate applications we recommend that the observed diversity pattern at all the three levels be maintained or promoted in conservation approaches for tamarind in East Africa. Thus, efforts should be made to preserve natural populations of tamarind in habitats and the diversity (at niche-tree species, morphological and genetic levels) within the populations. To come up with appropriate management guidelines to achieve this conservation approach, evolutionary factors contributing to observed unidirectional diversity pattern in tamarind need to be known. Therefore, we recommend model studies to elucidate them. Acknowledgements Authors thank Third World Organisation of Women in Sciences, International Foundation of Science, Austrian Agency for Development Cooperation, and Austrian Institute for Technology (formally Austrian Research Centres) for funding. We thank Dr. Denis P. Garity, Prof. Tony Simons, Prof. August B. Temu, Assoc. Prof. J. R. S. Kaboggoza, and Dr. Wilson K. Kasolo for institutional support. We thank Ric Coe, Patricio Lopez, Maria Berenyi, Andreas Homolka, Henry Mulindwa, Karin Fohringer, and Agnes Burg for technical research methodology support, and L. Ben, Phoebe Owino, Charlie Charlie, and Agnes B. Were for field assistance. We are very much grateful to the anonymous reviewers of Tropical Ecology and to Dr. Ankila J. Hiremath and Professor J. S. Singh for the review inputs that helped us improve this manuscript. References Amaniga Ruhanga, I. & J. Manyindo. 2010. Uganda’s Environment and Natural Resources: Enhancing Parliament’s Oversight. Norway. Assogbadjo, E. A., T. Kyndt, B. Sinsin, G. Gheysen & P. Van Damme. 2006. Patterns of genetic and morphometric diversity in Baobab (Adansonia digitata) populations across different climatic zones of Benin (West Africa). Annals of Botany 97: 819-830. Barantes, G. & L. Sandoval. 2009. 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Primer Foreword /reverse sequences tRNAleu (Intron 1 F) 5'-CGAAATCGGTAGACGCTACG-3' tRNAleu (Intron1 R) 5'-GGGGATAGAGGGACTTCAAC-3' MatkF MatKR trnL F TrnF CCB 203 F 5'-ASGTTCTACGGACCGATGCC-3' CCB 203 R 5'-CACGGGGAGGGAGCRGGCGA-3' CR 5'-CACGGGTCGCCCTCGTTCCG-3' RC 5'-GTGTGGAGGATATAGGTTGT-3' CB 5'-GCATTACGATCTGCAGCTCA-3' BC 5'-GGGCTCGATTAGTTTCTGC-3' NA41 5'-CAGTGGGTTGGTCTGGTATG-3' NA14 5'-TCATATGGGCTACTGAGGAG-3' NA42 5'-TGTTTCCCGAAGCGACACTT-3' NA24 5'-GGAACACTTTGGGGTGAACA-3' ORF 25F 5'-AAGACCRCCAAGCYYTCTCG-3' ORF25R 5'-TTGCTGCTATTCTATCTATT-3' AS 5'-ACTTCTGGTTCCGGCGAACGA-3' SA 5'-AACCACTCGGCCATCTCTCCT-3' CD 5'-CCAGTTCAAATCTGGGTGTC-3' DC 5'-GGGATTGTAGTTCAATTGGT-3' MatK F 5'-AACCCGGAACTAGTCGGATG-3' trnK 5'-TCAATGGTAGAGTACTCGGC-3' trnlR trnLFA trnEDoyle 10 GTCCTATCCATTAGACAATGG TrnTM 11 CTACCACTGAGTTAAAAGGG TrnHF Source PCR success with tamarind in this study Taberlet et al. Amplified in some and failed in other 1991 individuals, Polymorphic with Hinf1 but poor resolution Not used in final study Nishikawa et al. 2002 Amplified in some and failed in other individuals Not used in study Nishikawa et al. 2002 Amplification failure Not used in study Duminil et al. 2002 Amplified in some and failed in other individuals Not used in study Demesure et al. 1995 Amplified in some and failed in others Not used in study Demesure et al. 1995 Amplified in some and failed in other individuals Not used in study Demesure et al. 1995 Amplification failure Not used in study Demesure et al. 1995 Amplified in some and not in other individuals Not used in study Dumunil et al. Amplification failure Not used in study 2002 Demesure et al. 1995 Amplification failure Not used in study Demesure et al. 1995 Amplification failure Not used in study Nishikawa et al. 2002 Amplification failure Not used in study Jung et al. 2004 Amplification failure Not used in study Doyle et al. 1992 Amplified in some and failed in others Not used in study Tsumura et al. Amplification failure Not used in study 1996 PSB A3 (8) atBSam 17 Samuel et al. 1997 atBsam 20 rbcl F Amplification failure Not used in study Amplified in some and failed in others Not used in study rbcl R ORF 62 P CTTGCTTTCCAATTGGCTGT trnf-M CATAACCTTGAGGTCACGGG Amplification failure Not used in study Demesure et al. 1995 Contd... 32 TAMARINDUS INDICA DIVERSITY MODELS Appendix Table 1. Continued. Primer Foreword /reverse sequences trnG 2(III) GTTTAGTGGTAAAAGTGTGATTCG TrnG 1 R CCGCATCGTTAGCTTGGAAGGC rpl2f (2) ACCGATATGCCCTTAGGCACGGC TrnH-M GTGAATCCACCAYGCGCGGG PSB A5 (7) TACGTTCRTGCATAACTTCC PSBA3 (8) CTAGCACTGAAAACCGTCTT NAD9 F GGTCATCTCAATTGGGYTCAG NAD 9 R TATAGTTGGGAGACTTTACC Cox 11 F 5'-TAGRAACAGCTTCTACGACG-3' Cox 11 R 5'-GRGTTTACTATGGTCAGTGC-3' rps 14 Cob DT 5'-ACCAATTGAACTACAATCCC-3' TD 5'-CTACCACTGAGTTAAAAGGG-3' rbcl samuel GAAGTAGTAGGATTGATTCTC Source Shaw et al. 2005 PCR success with tamarind in this study Amplified across populations Used in study Amplified across populations Was used in study Tsumura et al. Amplified across populations was used in study 1995 Amplified across populations Was used in study Duminil et al. 2002 Amplified across populations was used in study Demesure et al. 1995 Amplified in some and failed in others Not used in study Demesure et al. 1995 Amplification failure Not used in study Samuel et al. 1997 Amplification failure Mot used in study Duminil et al. 1995 Amplification failure Not used in study Rbcl Samuel R CCCTACAACTCATGAATTAAG Atp9 F 5'-CCAAGTGAGATGTCCAAGAT-3' Atp 9 R 5'-CTTCGGTTAGAGCAAAGCC-3' NA12 Amplified in some and failed in others Not used for study NA21 MatKF Amplified in some and failed in others Not used for study trnlKR ITS F Amplifies in all Not used in study ITS R FT Amplification failure Not used in study TF Rpoc F Amplification failure Not used in study Rpoc R Rps 4 F 5'-CSTTTCYGCTCCGAAGAG-3' Rps 4 R 5'-TCTCCGAAGATTGAGG-3' Amplification failure Not used in study IGR F Amplification failure Not used in study IGR R 18S F Amplified in all Used to test DNA quality for PCR 18S R atB Samuel F GAAGTAGTAGGATTGATTCTC Rbcl Samuel R CCCTACAACTCATGAATTAAG Samuel et al. 1997 Amplification failed Not used in study